1985

PRODUCTIVITY ANALYSIS OF APPLE ORCHARDS

IN SHIMLA DISTRICT OF HIMACHAL PRADESH

Thesis

by

K. KIREETI

Submitted in partial fulfilment of the requirements for

the award of degree of

MASTER OF SCIENCE (Ag.)

AGRICULTURAL ECONOMICS

COLLEGE OF FORESTRY

Dr Yashwant Singh Parmar University of

Horticulture and Forestry, Nauni,

Solan - 173 230, (HP) INDIA

2013

Dr. L.R. SHARMA Department of Social Sciences

(Professor & Head) Dr. Y. S. Parmar University of

Horticulture and Forestry,

Nauni-Solan-173 230 (HP)

CERTIFICATE-I

This is to certify that the thesis entitled, "Productivity analysis of apple

orchards in Shimla district of Himachal Pradesh", submitted in partial fulfilment of the

requirements for the award of degree of MASTER OF SCIENCE (Ag.) AGRICULTURAL

ECONOMICS to Dr. Yashwant Singh Parmar University of Horticulture and Forestry,

Nauni, Solan (HP) is a bonafide record of research work carried out by Mr. K. Kireeti (F-

2011-02-M) under my guidance and supervision. No part of this thesis has been

submitted for any other degree or diploma.

The assistance and help received during the course of investigation has

been fully acknowledged.

Place: Nauni-Solan ( Dr. L.R.Sharma )

Dated: Chairman

Advisory committee

CERTIFICATE-II

This is to certify that thesis entitled “Productivity Analysis of Apple

Orchards in Shimla District of Himachal Pradesh”, submitted by Mr. K. Kireeti

(F-11-02-M) to Dr. Yashwant Singh Parmar University of Horticulture and Forestry,

Nauni, Solan (HP), in partial fulfilment of the requirements for the award of degree

of MASTER OF SCIENCE (Ag.) AGRICULTURAL ECONOMICS has been approved by

the Student’s Advisory Committee after an oral examination of the same in

collaboration with the internal examiner.

Dr. L.R. Sharma

Prof. & Head

(Dept. of Social Sciences)

Chairman

Advisory Committee

Dr.D.R. Bharadwaj

Professor

(Dept. of SAF)

Internal Examiner

Members, Advisory Committee

Dr. P.S. Chauhan

Professor and Head

(Dept. of Fruit Sciences)

Dr. Ravinder Sharma

Professor

(Dept. of Social Sciences)

Dr. M.K. Vaidya

Professor

(Dept. of Social Sciences)

Dr. R. K. Gupta

Professor

(Dept. of Basic Sciences)

Dr.S.S. Sharma

Professor

(Dept. of Basic Sciences)

Dean’s Nominee

Professor and Head

Dept. of Social Sciences

Dean

College of Forestry

CERTIFICATE-III

This is to certify that all the mistakes and errors pointed out by the external

examiner have been incorporated in the thesis entitled, “Productivity analysis of apple

orchards in Shimla district of Himachal Pradesh " submitted to Dr. Y. S. Parmar

University of Horticulture and Forestry, Nauni, Solan (HP) by Mr. K. Kireeti

(F-2011-02-M) in partial fulfilment of the requirements for the award of degree of

MASTER OF SCIENCE (Ag.) AGRICULTURAL ECONOMICS.

______________________

Dr. L.R. SHARMA

Chairman

Advisory Committee

______________________________

Professor and Head

Department of Social Sciences

Dr. Y.S. Parmar University of Horticulture and Forestry

Nauni, Solan (H.P.) 173 230

A C K N O W L E D G E M E N T

Above Everything: All the praise is to the “A L M I G H T Y”. Creator & sustainer of the heavens & the earth & all that is within them, the ‘’Eternal & Absolute’’, to whom alone ‘’All the Worship is Due’’. Let his intensified mercy shower upon all the people in the path of truth and those upon whom he has shown his favour. I avail this opportunity to express my deep sense of reverence to my Guruji Dr. L. R. Sharma, Chairman, advisory committee for the constructive implications of his knowledge & wisdom, unfailing patience, personal care, incessant guidance & synergetic efforts in structuring & as to fabricate this manuscript through all its phases which nurtured this research project in right direction.

I thank all my advisory committee members Dr. Ravinder Sharma for his advice & whole-hearted-co-operation, Dr. M.K. Vaidya for his unbounded support, Dr. R.K. Gupta for his aid & encouragement and Dr. P.S. Chauhan for his critical comments & help and also for all their useful substantial assistance rendered during this period of investigation & preparation of the thesis.

Thanks are also due to Dr. D.D. Sharma & Dr. Subhash Sharma for their courage & effective

suggestions during the project work and preparation of this manuscript. Also I am immensely thankful to each & every one of my “School Teachers” for “My Stand in Life Today”.

How shall i express my gratitude for my lifetime indebtedness to my beloved Father Sri. Kuruva

Uligappa garu (Appaji) & my darling Mother Smt. Kuruva Vijaya Lakhshmi garu (Ammaji) for their prayers, love, unremitting patience & support without which fulfillment of this endeavor would not have been possible. My success is also due to the prayers of my little sister Ashritha Kuruva (Chelli). It is also to mention espousal & patience of my dearest pal Vahiny (Bujjy) and all her prayers for my wellbeing. Thanks to my Amamma, Chote mamu & Didi, Nagendra bava & family, Naveen bava & family for their love, support & blessings. Its never late to cite, but true that the company of “The Good Fellas” from my school, who gave many best moments of life to reminisce are Harsh, Hari 2, Sunny, Hiday, Zubair, Chanti, Gibbs, Deepu & whose friendship gave me enough strength to get through all mind numbing circumstances. The days in “Nauni Natural” were cheerful & memorable due to Swamy, Kairon, Saurav, Rakesh, Romee, Manty & Tanu, Chand bhai, Chaman aate, Attri bhai, Vikram Bharata, King & Andy, Nane bhai, Deepak Bob & Sanjiv, Navy & Miyan, Chiru, Shilpa, Nisha & Many more whom I didn’t mention.

My special thanks to Anil Singha ji, Vikas Rohta Sir & Praneet Chauhan for their assistance in my stay & during the proceedings of my research survey.

Thanks are also due to staff of the Department of Social Sciences, & university for their

valuable help & cooperation. I thank all the well-wishers those who helped me in material or immaterial during “The Nauni Chapter of My Life”.

Place: Nauni, Solan Dated: Sep’2013. ( K I R E E T I . K )

CONTENTS

CHAPTER TITLE PAGE(S)

1 INTRODUCTION 1-3

2 REVIEW OF LITERATURE 4 - 28

3 METHODOLOGY 29 - 41

4 RESULTS AND DISCUSSION 42 – 91

5 SUMMARY AND CONCLUSION 92 – 100

6 REFERNCES 101-105

ABSTRACT 106

APPENDICES i - vii

LIST OF TABLES

Table TITLE Page

4.1 Compound growth of area, production and productivity of apple in various regions during 1973-74 to 2011-12

43

4.2 Comparative analysis of apple productivity of major apple producing countries

44

4.3 District wise changes in area of apple in Himachal Pradesh, (1973-74 to 2011-12)

46

4.4 District wise changes in production of apple in Himachal Pradesh, (1973-74 to 2011-12)

48

4.5 District wise changes in productivity of apple in Himachal Pradesh, (1973-74 to 2011-12)

49

4.6 Inter-district comparative analysis of apple productivity in Himachal Pradesh 51

4.7 Contribution of yield and area in the production of apples in different districts of Himachal Pradesh, 1973-74 to 2011-12

52

4.8 Contribution of yield and area in the production of apples in different regions, 1973-74 to 2011-12

53

4.9 Area (ha) under different categories of apple in Narkanda block of Shimla district, 2006

55

4.10 Type & size of the family & male /female divide in the study area, 2012-13 56

4.11 Distribution of family members according to the age group of the sampled farms in the study area, 2012-13

58

4.12 Marital status of family members in the study area, 2012-13 59

4.13 Distribution of workers and non- workers on sampled orchards in the study area, 2012-13

60

4.14 Literacy status of the family members in various sample apple orchard farms, 2012-13

61

4.15 Main and subsidiary occupation of the family members in the study region, 2012-13

62

4.16 Land use pattern of sampled apple growers in the study area, 2012-13 64

4.17 Average area under different crops on different altitudinal zones of farm in the study area, 2012-13

65

4.18 Average number of bearing and non-bearing plants of apple in the study area, 2012-13

65

Table TITLE Page

4.19 Average number of livestock on different categories of farms in the study area, 2012-13

66

4.20 Average investment per farm on different farm implements in different elevation zones of the study area, 2012-13

68

4.21 Farmer’s distribution and their average value of managerial skill index (MSI) in the study area, 2012-13

69

4.22 Elevation wise managerial skill index of study sample, 2011-12 70

4.23 Elevation wise productivity analysis of study sample 71

4.24 Productivity differences in different elevations of the study area 71

4.25 Distribution of households according to the gross apple income structure in the study region, 2012-13

73

4.26 Initial costs of apple orchards of Shimla district (per 100 plants) in the study sample

75

4.27 Maintenance cost of non - bearing apple per hundred apple plants in the orchards of Shimla district (study sample), 2012-13

76

4.28 Cumulative establishment cost per apple tree in Narkanda block 77

4.29 Maintenance cost of bearing apple per hundred plants on the orchards of Shimla district (study sample), 2012-13

78

4.30 Maintenance cost, yield & returns from apple orchards during bearing stage in Himachal (per 100 plants), 2012-13

80

4.31 Multiple regression analysis (log linear regression) 82

4.32 Marginal value products and factor price ratios (MVPxi /Pxi) in sampled farms under pooled condition.

83

4.33 Farmers' perception regarding the climate change 84

4.34 Problems faced by the farmers in production of apple 86

4.35 Problems faced by the farmers in marketing of apple 90

LIST OF FIGURES

Sr.

No TITLE

Page

Number

1 Selection of the study site (Narkanda block) 30

2 Schematic representation of the sampling frame 32

3 Annual average productivity (apple) of the major apple producing countries during 1973-74 to 2011-12

44

4 Trends in area under apple in Himachal Pradesh (ha), 1973-74 to 2011-12 47

5 Trends in production of apple in Himachal Pradesh (MT), 1973-74 to 2011-12 48

6 Trends in productivity of apple in Himachal Pradesh (MT/ ha), 1973-74 to 2011-12 50

7 Annual average productivity (apple) of the apple producing districts of Himachal Pradesh during 1973-74 to 2011-12

51

8 Percentage contribution due to yield & area in production 52

9 Gender split of farm families (study sample) based on age groups, 2012-13 57

10 Literacy status of the farm families of the study sample (percentage), 2012-13 61

11 Primary occupation by major sectors in the study sample, 2012 -13 63

12 Managerial skill index (MSI) of the orchardists (study sample), 2012-13 69

13 Mean productivities of different altitudinal zones 72

ABBREVIATIONS

TTTT : Indian National Rupee

$ : United States Dollar

% : Per cent

& : And

@ : At the rate

B : Bearing

CD : Critical Difference

CV : Coefficient of Variation

DOH : Department of Horticulture

et al. : et alii (Co- workers)

FAO : Food and Agricultural Organization

FYM : Farm Yard Manure

GDP : Gross Domestic Product

HP : Himachal Pradesh

ha : Hectare

i.e. : That is to say

J&K : Jammu & Kashmir

kg : Kilogram

amsl : Above Mean Sea Level

MT : Metric Ton

MSI : Managerial Skill Index

MPS : Mean Perception Score

MVP/MFC : Marginal Value Product/ Marginal Factor Cost

NB : Non Bearing

No. : Number

SD : Standard Deviation

Q : Quintal

Chapter-1

INTRODUCTION

Apples constitute a major part of the economy of Himachal Pradesh, with a turnover of

over Rs. 3000 crore and accounting for almost 10 percent of the gross domestic product. In

the post-independence period especially after the statehood in 1971, there has been a strong

backing from the state for apple plantations. Consequently the area under apple cultivation

has increased substantially from a mere 400 hectares in 1950s to 114939 hectares in 2011-12.

Of the total area under fruit production, apples make up for more than 48 percent and of the

total fruit production, apple alone accounts for more than 74 percent. Despite the meteoric

rise in area and production, the productivity of apple in India remains stagnated around 10

MT Ha-1 far behind from that of the leading countries Italy (42.41 MT ha-1), Chile (33.37 MT ha-

1) , France (44.36 MT ha-1) and the world average being 15.87 MT ha-1 in the year 2011 (FAO

2011). Considering the vital role that Apple has in the economy of Himachal Pradesh, there is

a need to analyse the trends in area, yield, production and economics of apple and problems

encountered by the orchardists in the state.

An orchard is a long term investment and careful planning is essential to ensure

economic success. Apple orchard is no exception in this regard (Marini, 1997).The gains in

production have come essentially from increase in the acreage rather than through intensive

cultivation practices. The situation calls for the intensive use of knowledge and skills based

farming to realise potential productivity.

Braun et al. (2003) argue that there exist strong and direct relationship between

productivity, hunger and poverty. Lewis (1978) pointed out that in the long run, productivity

is the only “engine of growth” to the farm economy. The authors suggest that an

improvement in agricultural productivity enables farmers to grow more food which translates

into better diets and higher farm incomes. It is the productivity growth that allows farmers to

break out of poverty and low income equilibrium trap and also contribute to overall economic

growth.

District Shimla has the largest production of apples, followed by Kullu, Kinnaur,

Mandi, Chamba and Solan. Majority of apple orchardists, according to 1989 horticulture

2

census, are marginal farmers (86%), small farmers (10%), semi-medium (3%), medium

(0.5%) and just 0.03 percent is large farmers. The low productivity of apple orchards in

Himachal Pradesh is due to the factors like preponderance of the small land holdings (85%)

and further relative sub-division of the same holdings (Sharma, 2011). Hence predominance

of small holding, deteriorating quality of land, changes in climatic conditions, inadequate

chilling hours during winters, hailstorms during springs, untimely and insufficient winter

precipitation, low temperature during blooming times, prolonged droughts are some of the

major constraints observed at different time periods of the year invariably affecting adversely

the productivity of the crop. The vast technological gaps existing in apple crop, indicates the

scope of increasing productivity rates by plugging these gaps through balanced use of

modern inputs.

The present study intends to assess the intertemporal, inter-country, inter-altitudinal

comparison in the productivity of apple crop, to know where we stand and what ought to be

done to achieve the international standards in the productivity. Quantification of productivity

level across regions, altitudes, will seriously bring this crucial aspect in limelight. It is

expected that the present study will not only help in identifying the causes of low

productivity, but also suggest ways and means to mitigate the constraints coming on the way.

The study will help in improving the understanding of factors which influence the

productivity of the crop. The proposed study will be useful in formulating horticultural

policies aimed at improving the apple productivity.

While the fundamental concept of productivity is relatively simple, it is only very

recently that the importance of productivity has become more widely recognized and

explored. Productivity has not only become the main topic of strategic discussions among the

economic planners, but it has also caught the attention and interest of fellow workers,

researchers, politicians and the public at large. Therefore, the country’s competitiveness can

be measured by its productivity. The challenge for the country then would be in promoting a

rapid and sustainable productivity growth. The understanding that “What we cannot

measure, we cannot manage” also reflect the importance of measuring the nation’s

productivity so that the development of its competitiveness can be monitored and

strengthened (Shahuren Ismail 2005).

3

By 2050 India will be the most populous country in the world; hence a dire need is

felt at the national level to increase productivity in agriculture with limited cultivable land

(46% of the total area) (Datt & Sundharam, 2007).

Further the questions warranting answers are: what is the existing status of

productivity at farm level across altitudes? What have been the sources of productivity

growth? How much are the productivity gaps? How climatic change has adversely affected

the productivity? What are various factors which influences the productivity? What are major

constraints/obstacles that hinder the growth of productivity? How to raise the apple

productivity? What are the perceptions of orchardists about the impact of climate on

productivity? These issues need to be addressed through a scientific and comprehensive

research study on constraint analysis for low apple productivity in Himachal Pradesh.

Thus the proposed study “Productivity analysis of apple orchards in Shimla district of

Himachal Pradesh” will focus on the issues related to these aspects including the problems

faced by the households engaged in this avocation. Thus, the proposed study will be

undertaken with the following objectives:

OBJECTIVES

i) To examine the trends in production and productivity of apple

ii) To study the cost of production of apples in the study area

iii) To analyze the factors affecting the apple production and productivity

Chapter-2

REVIEW OF LITERATURE

The scientific research is based upon methodical view developed on the previously

accrued erudition and experience. A meticulous insight into studies previously conducted

relating to the research area under contemplation, therefore, becomes imperative for

conceptual clarity, development of reliable methodology and for recognizing the critical gaps

for further improvement in research work. Keeping this idea into view, an effort has been

made in this chapter to present the resume of work done by various research workers in India

and abroad which have been organized and documented chronologically in a range of broad

sections. Findings have been categorized under different sections, namely;

2.1 Trends in Apple production and productivity

2.2 Estimation of cost of production of apple

2.3 Factors affecting apple production and productivity

2.4 Impact of climate on apple production and productivity

2.1 Trends in Apple Production and Productivity

Birthal (2008) examined the issue whether horticulture can revitalize agricultural

growth. Agricultural growth has decelerated from 3.2 per cent during 1980-81 to 1995-96 to

1.9 per cent during 1996-97 to 2005-06, leading to situation of agrarian distress in some parts

of the country. The paper besides looking into the contribution of horticulture to agricultural

growth, also examined the implications of horticulture led growth for small farmers. The

paper explained that during 1995-96 to 2004-05 the gross value of fruits and vegetables grew

at an annual rate of 5.6 per cent. Agricultural growth decelerated significantly during 1995-96

to 2004-05, and would have decelerated further, had the robust growth in fruits and

vegetables, not provided a cushion to it. Fruits and vegetables accounted for nearly 64 per

cent share in the overall growth during 1995-96 to 2004-05, which was more than thrice the

share during earlier period. According to agricultural census, in 2000-01 of the total 121

million land holding 81.9 per cent were of less than or equal to 2 ha and had an average size

of 0.5 ha. In 2000-01 they allocated 5.7 per cent of their total cropped area to horticultural

crops, compared to 3.9 per cent by the large farmers. Three important conclusions drawn

5

from the study are; a) technology has remained important source of growth in Indian

agriculture, b) diversification of agriculture towards horticultural crops has considerable

potential to accelerate agricultural growth, c) horticulture led growth is an opportunity for

small farmers to raise their income.

Singh et al. (2008) from their study on structural changes in horticulture sector in

India for XI Five Year Plan reported that agriculture sector has declined from 3.7 per cent

during 1991-92 to 1996-97 to 2.5 per cent per annum during Ninth & Tenth Plan 1997-08 to

2006-07 periods, while growth of GDP was observed to be 5.7 and 6.6 per cent per annum

during the corresponding period. Given the importance of horticulture sector in the Indian

economy, the present study was taken to suggest policy measures to accelerate development

of horticulture sector in the country. The Markov chain model was used to analyse the

structural changes in land holdings, land use, farm and market structure. Results showed that

high value crops (HVCs) account for a major share of total agricultural exports. Among

exports, Cashew ranked first, followed by spices, fresh fruits and fresh vegetables during the

triennium 2001-02 to triennium 2005-06. The growth and variability of area, production and

yield of major horticultural sub-sectors indicates that substantial growth has occurred in the

area of all the sub sectors during entire period of 1991-92 to 2005-06. The paper suggests that

area specific policy interventions based on area specific constraints are required for the

sector’s development. The development of horticulture sector is essential to achieve the

targets of agricultural growth and exports, food and nutritional security, and ultimately

efficient utilization of natural resources.

Kareemulla et al. (2007) conducted a study on production and marketing of Indian

Gooseberry – AONLA (Emblica officinalis Gaertn.) in Pratapgarh district of Uttar Pradesh.

He reported that the area occupied by amla based farming system grew at a growth rate of

4.02 per cent during the period 1995-2005. The production of aonla has increased from

47329 to 82690 tonnes in the reference period at a growth rate of 5.2 per cent and the

average productivity increased from 5.7 to 6.5 t per ha.

Prashar et al. (2006) estimated the supply function for Himachal apples. The specific

objectives of the present study were to estimate the supply response of apples and to suggest

appropriate policy measures for the development of apple industry in the state. The study was

based on the secondary data collected from various sources on area, production, prices,

subsidies on production and marketing of apple, weather parameters, wage index and

6

consumer index for agricultural labourers and the fertilizer wholesale price index for the

period 1969-2000. The model consists of equations for yield responses and new planting

responses. The results showed that apple production in the state has increased from 50,524

tonnes in 1969 to 3,76,720 tonnes in 2000 at a compound growth rate of 6.02 per cent per

annum. The results from the selected models, both in case of linear and double log formats

reveals that among the explanatory variables, chilling, hours were more crucial factors

affecting the yield of apple. The increase in parity ratios, i.e., an increase in apple prices at a

rate higher than the rate of increase in consumer price index would lead to positive short-run

response of the orchardists. A higher parity ratio will, in all probabilities, induce the farmer to

go in for intensive cultivation which increases the productivities in subsequent periods.

Expansion of infrastructural facilities, particularly the roads had a positive influence in

increasing acreage under apples in long run.

Saraswat and Rane (2006) conducted a study on production and marketing of peach

fruit: a case study of Rajgarh area of district Sirimour in Himachal Pradesh 50 farmers were

randomly selected for the detailed study. The compound growth rate with respect to area and

production shows that the area under peach increased at the rate of 4.31 per cent per annum.

The highest area under peach was recorded in Sirmour district, whereas district Mandi

registered the highest rate of production growth in the state i.e., 9.32 per cent per annum. The

district wise production scenario indicates that, there are variations in the outputs of peach.

Out of 12 districts only 4 districts have registered a positive growth in production i.e., Solan

(22.55%) followed by Una, Bilaspur and Mandi.

Singh (2004) conducted a study about the causes of low productivity in Himachal

Apple. The state of J&K occupies the first place in apple production in the country with

between 62 to 67 per cent of the production and 37 per cent of the total area under apple

orchards in India. Himachal Pradesh occupies the second place followed by Uttaranchal and

Arunachal Pradesh. The analysis of fruit production in Himachal Pradesh during twenty years

reveals that annual average production, taking the five year averages from the 1980-81

onwards into consideration, has almost stabilized between 250000 MT and 270000 MT. It is

interesting to note that, production has remained fairly static in spite of an expansion in the

area at a rate of over 2500 ha per year. Available data indicate that there has been

considerable decline in the productivity of apple during the last twenty years. The five year

average productivity declined from 6.57 MT/ha during the period 1980-81 to 1988-2000,

7

showing thereby a decrease of about 30 per cent. The factors which affect the yield are non-

uniformity in genetic potential of the cultivars planted, the effect of climatic and

environmental conditions and management practices employed by growers.

Masoodi (2003) stated that apple cultivation in Jammu & Kashmir has made

impressive progress with productivity going as highest as about 21.00 tonnes per hectare in

Baramulla district. Ambri cultivar of apple is a monopoly of Jammu & Kashmir. Apple

covers an area of about 90.08 thousand hectare. The annual production of apple in the state is

about 9.09 lakh tonnes with an average yield of 10.09 tonnes per hectare. Despite increase in

area from 86.65 thousand hectares to 90.08 thousand hectares, the production and

productivity has declined during the last few years. This is due to drought like conditions that

engulfed the state. Apple production has increased from just 6000 metric tonnes in 1950-51

to more than 9 lakh tonnes in 2001-02 and area increased from 7000 hectares to more than 90

thousand hectares. Besides highest apple production in country, the productivity of apple in

the state is much higher than the national average of 6.86 tonnes/ ha. It also compares well

with the world average of 10.82 tonnes/ha or China’s 9.93 tonnes/ha who is the world largest

producer of apple.

Farooqi (2003) conducted a study about future of apples in Jammu and Kashmir and

reported that apple is principal fruit crop of Kashmir and accounts for 60 to 65 per cent of

total area of 2.17 lakh hectare under all temperate fruits. The annual apple production in the

state is approximately 9,00,000 Metric tonnes. Except for Himachal Pradesh and small areas

in Uttaranchal, Jammu & Kashmir is the only state where apples are grown in India. The

present production of apples in the State contributes barely one apple per person per year to

the country’s population. There is thus a high market for this fruit in the country. The

increase in area and production of apples has been achieved through consistent and

systematic efforts from planner’s researchers and above all, the farmers.

More (1999) studied the growth rate in area, production and productivity of banana in

Nanded district, Parbhani district and Maharashtra state as a whole in Nanded

district, production growth rate had shown higher growth rate (21.04%). The higher

growth in production was contributed mainly by significant increase in area coupled with

productivity. The growth rate of productivity was high (1.43%) in Maharashtra state

as a whole as compared to Nanded (1.40%) and Parbhani (0.90%) district. It was due

8

to the use of improved cultural practices higher use of manures and fertilizers, more use

of other inputs and also increased yield level in other district of the state.

Saraswat (1997) conducted a study on organization of production and marketing of

apple in Himachal Pradesh: A case study of Kirari village. The study found that, in Himachal

Pradesh the area under apple has increased at a compound growth rate of 4.71 per cent per

annum while the production increased at 8.34 per cent per annum during 1966-67 to 1990-91.

The study revealed that the average productivity per hectare of apple orchards was 1,285

standard boxes of each 18 kg.

Handiganur (1995) studied the growth rates of area, production and productivity

of grapes in Bijapur district from 1978-79 to 1992-93. Growth rate analysis had

showed an increase of 7.12 per cent of area in Bijapur district and an increase of 0.6 per cent

in area,2.80 per cent in production and 2.0 per cent in productivity of grapes was

observed in Karnataka state. The increase in production and productivity was due to the use

of improved cultural practices, increased use of manures, fertilizers and plant protection

chemicals.

Sharma and Parihar (1994) conducted a study on production and marketing of apricot

in Jammu and Kashmir. They reported that compound growth rate (CGR) of the

production (3.30 %) is significantly higher than the CGR of area (2.23 %) in case of fresh

apricot whereas there is not much difference in the CGR of area and production of dried

apricot, CGR of yield is not increasing significantly as compared to area both in fresh and

dried apricot.

Singh et al. (1990) examined the economics of apple production in Himachal Pradesh.

The study examined (i) the trends in area, production, export of apple in Himachal Pradesh,

(ii) cost of production and economics of apple orchards (iii) the economic viability of apple

orchards (iv) the existing marketing system, costs, margins and price spreads; and (v) the

problems of apple growers. A sample of 214 apple growers (89 from Shimla, 72 from Kullu

and 53 from Mandi districts) was interviewed for the reference year 1989. Investment in

apple orchards was found to be profitable and financially viable besides providing

employment. The increase in the production of apples has led to a number of problems, such

as disposal of apples at remunerative prices, supply of packing material and its higher cost,

greater dependence of growers on middle men, malpractices in terminal markets, inadequate

9

and higher cost of transportation, utilization of culled fruits, no relationship in procurement

prices between quality apples and culled apples and decrease in producers share of the

consumers price. Study suggests that market infrastructure need to be improved, cool chain

system, transportation facilities and implementation of market regulation are some of the

measures needs to be implemented.

Patil et al. (1987) studied trends and growth rates in area, production and productivity

and the factor responsible for change in acreage under banana crop in Jalagaon district from

1950-51 to 1979-80. The area under banana increased tremendously from 6600 hectares to

33400 hectares and the production of banana has increased by 689 per cent in the same

period. Net irrigated area and one year lagged price of banana have jointly explained nearly

97 per cent of the variation in the acreage under banana.

Raju et al. (1987) estimated compound growth rates of area (1967-83) and production

(1970-83) for fruit crops by fitting the semilog function in Andhra Pradesh. The year to year

fluctuations in area and production of fruit crops were studied with the help of index numbers

and their per centage changes from the previous years. The production of grapes had showed

a phenomenal increase in (32.9%) 1973-74, the index stood at 511 in 1982-83. From 1973-74

to 1977-78 there was a continuous falls in production by 27.00, 24.00, 39.00, 3.88 and 8.64

per cent, respectively. Early 1980s witnessed an increasing trend in grape production.

Though the area under grapes which was concentrated only in two districts (RangaReddy and

Ananthpur) increased in absolute term, its growth rate was negative and significant (-2.44).

The compound growth rate of grape production was 12.09 per cent per annum and

statistically significant.

Indira devi et al. (1980) computed the trends in area, production and yield of banana

in Kerala state and quadratic function was fitted to explain the trend in a period of 17 years

(1970-87). The study revealed that banana production in the state showed an

increasing trend (94.57%) because of the intensive cultivation practices and favourable

price factors for banana. The study also indicated that the main determinant of production of

banana in Kerala during seventies was area (extensive cultivation). While it was yield

(intensive cultivation) in the eighties realizing the fact that banana cultivation had become

productivity oriented in the recent years.

10

2.2 Estimation of cost of production of apple Rauf (2009) has worked out the comparative economics of apple production in

Himachal Pradesh and Jammu & Kashmir on per 100 plant basis. He estimated that on an

average the overall initial cost were T 16225.87 in HP and T 16116.45 in J&K. The average

maintenance costs per 100 non bearing plants (for an age group of 2-8 years) in overall were

calculated to be in the range of T 11212.37 - T 29509.90 in HP & T 11157.77 - T 28611.56

in J&K. The establishment cost per tree was calculated to be 1533 in HP and 1496.57 in J&K.

The overall maintenance cost for 100 bearing orchards of apple was estimated to be in the

range of T 36386.49 - T 44242.50 & T 35654.65 - T 43489.77 in HP and J&K respectively

for different age groups of plants.

Kumar et al. (2007) worked out costs and returns of apple cultivation in Himachal

Pradesh. Multistage random sampling technique was used for selection of farmers located in

Shimla and Kullu district. The initial investment was very high. Maintenance cost incurred by

farmers for 7 years ranged from T 34,962 during first year to T 67,444 per hectare during

seventh year. Per hectare production costs on marginal orchards was T 1,31,976 per hectare

followed by T 1,35,149, 1,28,099, 1,27,321 and T 1,27,182 per hectare on large, semi

medium, medium and small orchards respectively. Net returns per hectare from apple was

highest on marginal orchards T 1,53,408 followed by large T 1,40,059 and least for medium

category orchardists T 1,29,143. Input–output ratio reveals that on investing rupee 1,

orchardists get a return of T 1.46, 1.48, 1.49, 1.49 and 1.50 on marginal, large, semi large,

medium and small orchards respectively. Hence marginal orchardists were more productive

as compared to other category of orchardists. This may be due to efficient management.

Rajesh (2006) studied the economic evaluation of vanilla cultivation in Uttar Kannada

district of Karnataka and found total cost incurred in processing of vanilla bean was T

6775.94 per quintal. The study revealed that labour cost was T 4680 (69.07 %), packing

material was T 50 (0.73 %) and fuel was T 60 (0.88 %). Gross returns and net returns

obtained from 20 kg of processed vanilla bean were T 30,000 and T 23,224.06 respectively.

Rane and Bagade (2006) studied economics of production and marketing of banana in

Sindhudurg district of Maharashtra. The study revealed that the per hectare cost at cost C in

Dadamarg and S awantawadi tehsil were T 1.52 lakhs and T 1.53 lakh respectively. In

Dodamarg tahsils banana was grown as a sole crop where per hectare cost of cultivation was

11

T 1.28 lakh and in Sawantaadi tehsil the per hectare cost was T 1.15 lakh benefit cost ratio in

Dadamarg tehsil and Sawantwadi tehsil were 2.20 and 2.33 respectively. The average benefit

cost ratio of banana cultivation was 227.

Alagumani (2005) in the study on economic analysis of tissue cultured banana and

sucker-propagated banana in Theni district of Tamil Nadu revealed that per hectare cost was

high in case of tissue cultured banana (T 141040) compared to sucker propagated banana

(T 108294). The net income was also high in case of tissue cultured banana (T 112262)

compared to sucker propagated banana (T 78855) clearly indicating the higher profitability

of tissue cultured banana production compared to sucker propagated banana production.

Anand (2005) conducted study an economic analysis of production and marketing of

papaya in North Karnataka. The capital productivity measures indicated that the investment

on papaya garden in the region was profitable proposition. The benefit cost ratio was 3.51.

The positive net present value indicated the soundness of investment made in the papaya

cultivation. The internal rate of return also indicated favorable nature of return.

Silva et al. (2005) carried out a study in Brazil to survey the potential of banana and

apple cultivation in the region as well as to determine the technical and economic indicators

of two production systems, both using micro propagated and conventional seedlings. The

results of economic analysis turned out to be quite satisfactory in this region for both

production systems however the net income obtained from the utilization of micro

propagated seedlings was 34 per cent higher than the one obtained from the conventional

system.

Umesh et al. (2005) observed that the establishment cost of cashew was T 15631 per

hectare in all the variety studied during the first three years. The maintenance cost per ha

from fourth year onwards varied from T 5881 to T 7882, in Ullal-3 and T 5821 to 7229 in

Ullal-4. The net returns of cashew orchard per ha being fairly high were in the order of T

61314, T 62425, T 49672 and T 34231 in Chintamani-1, Ullal-4, Ullal-3 and Ullal-1.

Sundaravardarajan and Ramanathan (2002) estimated the establishment cost of

cashew plantation for the first year at T 7690, T 8664 and at T 9491for marginal, small and

large farmers respectively. The maintenance costs of cashew plantation in the case of

marginal farms were T 4059, 4410, 4910, 5385, 841, 6332, 6771 and T 6990 for second,

12

third, fourth, fifth, sixth, seventh, eighth, ninth year respectively and in case of large farms

the maintenance cost were T 5040, 5250, 6764, 6145, 6558, 7021, 7438 and T 7745 for

second, third, fourth, fifth, sixth, seventh, eighth and ninth year respectively. The output-

input ratio per ha were 1.43, 1.55 and 1.83 marginal, small and large farms respectively.

Deepak Shah (2002) studied the production and marketing pattern of grapes in

Maharashtra. The per acre annual gross maintenance cost of grape orchardists increased

sharply during the phase the production rose before leveling off to a constant stage and

thereafter, it declined. The cost structure revealed that 67 per cent of the gross maintenance

cost was spent on production related operations and the remaining 33 per cent owed it to

investments on various marketing functions. The share of material input cost in gross

maintenance cost of production was about 10-11 per cent. In general, one acre of grape

orchard yields a net income to tune of T 32,388 during increasing production stage, T 36,345

during constant stage and T 22,402 during declining production stage.

Shivanand (2002) studied the cost and return structure in banana in North Karnataka

and concluded that cultivation of banana in the study area is highly profitable and on

an average banana growers obtained net returns of T 85,260 per hectare per year which is

about T 261726 for cycle of three years period.

Pawan Dahiya et al. (2002) conducted a study on cost-benefit analysis of ber

cultivation in Rohtak district Haryana. For the study they collected the data from thirty

ber growers randomly. To examine the economic feasibility in ber cultivation four

indicators like net present value, internal rate of return, benefit cost ratio and payback period

were used. The study indicated that ber cultivation it is intensive with an IRR of 22.5 per

cent. The NPV and BCR at a discount rate of 14 per cent is T 26,346 and 1:1.22 respectively.

The investment in ber orchard has a payback period of 7 years. Liberal credit

facilities, adequate supply system on inputs particularly good quality of planting

materials, were identified main factors which could increase viability of ber cultivation.

Singh et al. (2001) carried out a study on production and marketing of fruits crop viz.,

pear, guava and grapes in Punjab. The study was based on the data that was collected from

those sites where post-harvest infrastructural facilities were developed. Cost of fruits

cultivation showed that total annual cost of pear was estimated at T 24, 176.47 per hectare.

Manure and fertilizer were largest cost component. Pre-planting operations like cutting,

13

planting and pandal erection, operations occupied a very high proportion in total investment

for pear fruit. The total annual cost of cultivation of guava was T 22381.22 per hectare.

Fertilizer and manure cost amounted to T 1560.80 per ha, accounting to largest share

followed by human labour. Cost of cultivation of grapes was T 26547.69 per hectare. The

results conclude that manures/fertilizer occupied the major share in total cost of investment.

Maintenance cost occupied the largest share in the total cost of cultivation of all the fruits.

Groot (2000) worked out the economics of apple production with minimal use input

of chemicals in Slovenia apple industry. He advocated that the health value of food is very

important issue, through which the demand for environmental friendly produced food is

increased. In this case, care for environment means a minimal or no use at all of chemical

inputs for crop protection, growth regulation and fertilization. So in 1990, fruit research

system started a system comparison with three production systems for apple at two places.

First production system was based on crop protection; in second system fewer chemicals

were used. In the third system, chemicals were replaced by biological and mechanical

grading techniques system. Economic evaluation has been done in two ways. The results

contain the returns (Production, Prices) of a planting minus some of the costs of the planting

system. Only the costs that differ between the systems have been included. Labour costs and

material costs were included. To make economic evaluation for the entire life span the

method of annually net present value (ANVP) were used. The calculation of ANPV was

based on life span of 12 years. Results showed that planting with low use of chemicals had

lower physical and therefore lower economic returns.

Mishra et al. (2000) conducted a study on production and marketing of banana in

Gorakhpur district of Uttar Pradesh. The researcher worked out the total per hectare cost of

production of banana on small, medium and large farms at T 36,281.50, T 37,820.50 and

T 38,447.50 respectively with average cost of T 37516.50 per hectare. The average gross

returns were T 71,133.33 per hectare which was higher on large farms (T 73,400) followed

by medium forms (T 72,250) and small farms (T 67,750). The average input output ratio

was 1:1.89.

Kaul (1997) carried out a study on production, marketing and processing of

horticulture produce in India. He explains that according to National Accounts Statistics

(Govt. of India, 1994), the total value of horticultural products produced in country in 1993-

14

94 was T 23,016 crore with fruits and vegetables together contributing over 65 per cent of

this value. The value has been steadily increasing since the last three decades. It increased by

about 300 per cent between 1970-71 and 1984-85 and by over 78 per cent in the last 10 years.

These crops claimed a share of 34.5 per cent of the total value of the agricultural produce

despite former covering 7.2 per cent of the gross cropped area. Comparison of cost benefit

analysis of these crops further confirms their potential by generating higher income per unit

area. The benefit cost ratio (BCR) for mango was 3.39 as against 1.67 for groundnut and 1.71

for Sorghum. At 1986 prices, the value added per hectare by fruits was Rs. 9,418 and by

vegetables T 5,829, as against T 1,629 by wheat, T 2,219 by rice and T 5288 by ground nut.

Extending the comparison to the export potentials, the per hectare export earnings at 1995-96

prices of mango was $ 4,446, of grapes $ 10,407 and of vegetables $ 2,892, while for wheat it

was only $ 416 for rice (non-basmati) $ 456 and for basmati rice, $ 976.5. This is due to

higher yields per hectare combined with higher unit price in international markets available

for horticultural commodities.

Chitra et al. (1997) in the study on economics of ber production in and around

Hyderabad city of Andhra Pradesh found that, payback period in ber cultivation was 4.42

years and the benefit cost ratio was 5.25 indicating the profitability of ber cultivation. The net

present value worked out was T 12, 061. The IRR was 73.54 per cent which was higher than

the lending rates of commercial banks. The results of the study indicated that even though ber

cultivation required relatively higher initial capital investment compared to other fruit crops,

the returns were higher during the bearing period and economic indicators clearly indicated

that the production of ber was economically viable.

Deepak Shah (1996) studied the production and marketing pattern of grapes in

Maharashtra. The study showed sharp increase in per acre annual gross maintenance cost as

well as returns grape orchards. In general about 67 per cent of gross maintenance cost of

grape production was spent on various production related operations and the remaining 33

per cent owed it to investment on various marketing functions. The profitability in

grape cultivation was considerably high in the state of Maharashtra.

Maurya (1996) studied the profitability of banana production in Wajipur district of

Bihar state, India, during 1993-94. The study revealed that banana production was the most

15

profitable crop production activity in this area, as it provided a net income of T 29748.05 per

ha with a total expenditure of T 2160.70 and gross income of T 49958.75.

Sirinivas et al. (1994) carried out economic analysis of cashew nut production in

Prakasam district of A.P. Data for the study was collected from the cultivators through survey

method for the reference year 1990. The economic returns start from the 6th year. The results

concluded that T 7,932.24 was incurred to establish and maintain cashew nut orchard till the

economic bearing period. Annual maintenance cost was to a low of T 903.48. The high farm

business income (T 2,928.81) indicates the soundness of the business. Benefit-cost ratio and

internal rate of return were 1.26 and 18.97 per cent respectively. These indicate that the

investment on cashew orchard was worth investable.

Wani et al. (1994) worked out economic viability of apple orchards in Kashmir. The

objective of the study was to assess the age wise cost and returns structure of apple and its

viability under Kashmir conditions. A sample of 160 apple growers was drawn randomly

with at least 3 orchards under age groups. To study economic viability, project evaluation

techniques were used. The results reveal that gross returns ranged between T 675 ha-1 in 7th

year to T 1350 ha-1 in the 2nd year from sowing of inter crops. The total cost ranged from Rs.

4290.73 ha-1 in the first year of establishment to T 37101.04 ha-1 in 35th year of

establishment. The gross returns ranged from T 1300.00 ha-1 in 1st year of establishment to

T 9290 ha-1 in the 32nd year of establishment. Returns showed a gradual decline after 32nd

year. Economic evaluation reveals that payback period was 14 years. The net present value

worked out to be T 53417.14 ha-1. Benefit cost ratio was 2.29 and internal rate of return 26

per cent. Values were discounted at 12 per cent interest rate. All these measures clearly reveal

that establishment of orchards in Kashmir are quite profitable and economically viable.

Sinthilnathan and Srinivasan (1994) estimated the costs and returns of poovan

cultivar banana production in Tamil Nadu over a period of three years. The per hectare total

cost of cultivation was T 124668.11. The gross income obtained was T 286913.80 with the

net income of T 162235.69. The study clearly showed that the high profitability of poovan

variety banana with a high return-cost ratio 23:1 in the study area.

Hiremath (1993) in his study on economics of production and marketing of

lime in Bijapur district, Karnataka revealed that the per ha cost of establishment for the

four year gestation period was T 56424.58 in small, T 49179.62 in medium and T

16

47143.09 in large orchards. The intercrops reduced the establishment cost by T 588253.90

and 46.68 per cent in three size group of orchards respectively. The per hectare cost of

cultivation (8th to 30th year) was high in medium (T 12454.34) followed by large (T

1203.76) and (T 11399.60) small orchards. The average yield of lime was 340.59,

366.98 and 379.25bags in small, medium and large orchards, respectively.

Koujalagi and Kunnal (1992) evaluated financial feasibility of pomegranate orchards

in Bijapur district of Karnataka. The study revealed per hectare establishment cost was

T 15,230 and maintenance cost was T 13,050. The discounted benefit cost ratio at 12 per

cent discount rate was 1.53. The net present worth for the entire life period of the project was

T 18,283.81. The payback period was 6.56 years and internal rate of return was 15.55 per

cent.

Azad and Sikka (1991) in their study on production and marketing of temperate fruits

applied project evaluation measures to study economic viability of fruits like apple, peaches

and plum. The net present value was T 26,237 for apples, T 89,222 for peaches and

T 117,137 for plums. The internal rate of return was 32, 36 and 47 per cent respectively. The

benefit cost ratio was 1.36, 3.87 and 5.10 in that order.

Hugar et al. (1991) examined the economic potentiality and viability of guava

cultivation under scientific management. The study revealed that the net present worth was

T 73,804 per hectare. The benefit-cost ratio, internal rate of returns and payback period were

found to be 3.88, 57.82 per cent and 6 years respectively.

Koujalagi (1990) studied the pattern of investment in pomegranate orchards in Bijapur

district, Karnataka. The establishment cost (T 24229.53) consisted of material cost in the

initial year (85.65) and maintenance cost (49.35%) up to bearing three years. The per hectare

total establishment cost worked out to be (T 24,224.53) and returns per orchard was

T 45, 429.96.

Raikar (1990) studied production and marketing of cashew in Karnataka. The study

revealed that the per hectare annual maintenance cost of cashew plantation was higher on

small sizes (T 1,674.17) plantation compared to large size plantation (T 1303.65). The per

hectare gross returns over maintenance cost was the highest (T 3787.61). the gross returns

were T 3234.32 for the overall size group of plantation. The net return over total cost was

17

found to be T 1487.42, T 800.77 and T 1049.61 on small, large and overall size groups of

plantations respectively.

Reddy (1989) made an attempt to evaluate the financial feasibility of sweet

orange plantation in Prakasam district, Andhra Pradesh. The study showed that per acre net

present value for the entire life period of the project was found to be T 11,833.43 in case of

small orchard, T 27,540.33 in large orchard and T 16,682.94 in average orchard. The

discounted benefit cost ratio at 12 per cent discount rate was 1.28 in small orchard, 2.04 in

large orchard and 1.47 in average orchard. The payback period was eight, seven and eight

years in small, large and average orchards, respectively and corresponding internal rate

of return was 14.70, 21.24 and 16.26 per cent.

Awasthi et al. (1987) examined the economics of guava orchards in Jabalpur district.

The main objective of the study was to analyse the economics of guava at recommended level

of inputs based on data collected from 25 guava orchardists during 1980-86. The

establishment cost worked out to T 2,827 per hectare. The operational cost incurred on its

maintenance year after year varied from T 1,525 in the first year to T 2, 895 per hectare for

the orchard in the 6th year of age. In later years, manure, fertilizers and plant protection were

the major inputs accounting for a share of 30 to 40 per cent in the operational cost. The

positive net returns started after 4th year and reaches up to T 5,694 per hectare in the sixth

year, which was assumed to continue for next 24 years. For the first three year guava famers

incurred a net loss ranging from T 69.50 to T 3,295. The conclusion of the study is that there

is a tremendous scope for improving the income from guava orchards if proper management

in respect of spacing, fertilization, plant protection practices is taken into account.

Thakur et al. (1987) evaluated economic feasibility and profitability of kinnow

plantations in Kangra district of Himachal Pradesh. The study revealed that the investment on

plantation was T 8,208 and maintenance cost was T 10,580 per acre. The payback period for

the orchard was 6 years. The total net present worth was T 13,040. The internal rate of

returns was as high as 46 per cent for the plantation.

Subrahamanyam (1987) studied the cost and returns of mango orchards in

Karnataka. It was observed that on an average the establishment of mango orchard required

T 3000 per ha. The maintenance cost of mango orchards was only T 200 per ha. The gross

18

return from a hectare of mango orchard was T 1200 in Karnataka. As indicated by the study

the payback period was 11 years. Internal rate of return was 30 per cent and B-C ratio was

2.00 indicating that the investment was profitable.

Mahella et al. (1987) worked out per hectare establishment cost of kagzi lime

orchards. A sampling of 44 lime growers having a total area of 31.78 hectares under lime

orchard in Akola district of Maharashtra was selected. The required data for the period from

1981-92 to 1986-87 were collected from lime growers every year by survey method. The

results showed the total, per hectare utilization levels of key inputs i.e. male labour, females

labour, bullock labour, manure, nitrogen, phosphorus and potash during six-year period

worked out to 719.13 days 128.60 days, 23.10 days, 18.07 cart loads, 154.33 kg, 87.72 kg and

26.75 kg respectively. The gross cost of establishment per hectare for each of the six years

worked out to T 2,280, 2,178, 2, 155, 2,692, 3, 413 and T 40.50 respectively and net cost of

establishment worked out to T 1,629, 1,989, 1,751, 2,219, 2,152 and T 3,303 respectively.

The total gross cost and net cost of establishment of lime orchards for all the six years

worked out to T 16,770 and T 12,736 per hectare respectively.

Nighot et al. (1987) examined the per hectare input use, costs and returns and

profitability of orange cultivation in Nagpur district of Maharashtra, based on data of 40

orange orchards selected from five villages of the district. The total cost which consists of

establishment cost and annual maintenance cost of orange cultivation amounted to T 11,667

per hectare. Human labour, manure, fertilizers and pesticides are the important items of

expenditure in orange cultivation. The yield of orange per hectare and per tree was observed

to be 114.5 thousand fruits and 344 fruits respectively, while gross returns per hectare and per

tree were T 28,599 and T 86 respectively. Based on the total returns and total costs, output-

input ratio for orange production worked out to 2.56. Thus, under existing cost price situation

cultivation of oranges gives 156 per cent returns over variable costs.

Sharma et al. (1987) evaluated the costs and returns of oranges and kinnow cultivation

in Himachal Pradesh. This aspect was selected because of the vast potential for the citrus

growing in low hills of the state. The results revealed that cost of establishment amounted to

T 3,330 in the case of orange, while it was T 3,911 for kinnow orchards in terms of 1986-87

prices. Labour accounted for 42 per cent of the establishment cost in both types of orchards.

Kinnow incurred more expenditure in all the years, on manure and fertilizers, plant protection

19

and labour use. In initial years annual cost per hectare was more, because the plants require

more attention in respect of labour and material used. The per hectare net returns were greater

in the case of kinnow as compared to orange due to better tree performance, fruit quality,

yield and price of kinnow fruit.

Sikka (1992) evaluated the economic viability of apple cultivation in Himachal

Pradesh. The study was carried out in apple growing districts of Shimla, Kullu and Mandi.

Final sample of 89, 72 and 53 orchardists were taken out from these districts. Evaluation

techniques like payback period, net present value (NPV), internal rate of return IRR and

benefit cost ratio (BCR) was utilized. Age wise cost return data were used to compute the

various measures of investment. Net present value and benefit cost ratio being function of

discount rate, were obtained for 12 per cent. Results show that pay back, period was 16 years

in all sampled orchards, but for Shimla it was 15 years. Net present value at 12 per cent

discount rate was Rs. 29,872 per hectare in Shimla, Rs. 7, 627 in Kullu, Rs. 6, 365 per hectare

in Mandi and net present value of overall sample was Rs. 14, 655 per hectare. The IRR was

24. 07 per cent in Shimla 17.84 per cent in Mandi and 16.49 per cent in Kullu area. In overall

sample the IRR was 20.43 per cent, benefit cost ratio was 1.34, 1.06, 1.09 and 1.116 in

Shimla, Kullu, Mandi and overall samples, respectively. On the basis of these investment

criteria, investment in apple cultivation in all the three areas under study was found to be

quite profitable and economically viable as well.

Sikka and Swarup (1985) conducted a study on the economics of apple production in

Shimla & Kullu district of Himachal Pradesh and reported that the net present value at 12 per

cent discount rate varied from T 21,850 to T 30,504 per hectare depending on small and large

farms The internal rate of return varied from 20.62 per cent to 23.53 per cent. The benefit

cost ratio was found to be T 1.29, T 1.36 and T 1.42 at the 12 per cent discount rate on small,

medium and large farm categories respectively. The sample orchards have been classified

into various age groups i.e. in case of non - bearing plants all the age groups have been

considered, whereas in bearing plants only 8 age groups have been considered, i.e. 8, 9, 10

years , 11-12 years, 13-15 years, 16-20 years, 21-30 years and 31 and above. Initial cost of

investment was T 3,820, T 3577 and T 3,690 per hectare for Shimla, Kullu and overall

sample respectively. About 37 per cent of total cost is incurred on layout, digging and filling

of pits etc. and 31 per cent on manure and fertilizers. The other major cost to be incurred is

cost of nursery which accounts about 28 per cent. The study shows that incremental income

20

from apple orchards in case of Shimla farmers is T 6,499, T 6,096, and T 8,504 for small,

medium and large farmers respectively, while for Kullu it was about T 3929, T 6,657 and T

6,673 for the three sizes of farmers.

Sunderesan and Thanasekaran (1984) studied the costs and returns from cultivation of

Muscat grapes in Madurai district of Tamil Nadu. The study revealed that on an average

T 49,465 per hectare were required for establishing vines up to bearing stage of which

operation and maintenance costs amounted to T 26,658 The cost of production of grape

was T 1.58 per kg for the first four years T 1.80 from the fifth to eight year and T 2.29 per kg

after eighth year.

Subrahamanyam and Mohandas (1982) estimated the costs and returns from Coorg

Mandarin oranges in Karnataka. They found that the Mandarin orange tree requires seven

years to establish and starts bearing from eight year. The average cost of maintenance from

the eighth year onwards was found to vary from T 65 to T 590 with an average of Rs 370 per

acre. Per acre returns, ranged between T 219 and T 3000. The average gross return per acre

was found to be Rs 992.

Menon (1979) studied the feasibility of investment in grape gardens in Bangalore

north taluk. The estimated life of the vine yards were 30 and 25 years for Bangalore blue and

Anab-e-Shahi respectively. The study in which the net present worth was found to be T

38,22,828 per hectare, the benefit cost ratio was 1.42 and internal rate of return was 40 per

cent in the case of Bangalore blue variety. For Anab-e-Shahi the respective values were T

92, 46,096 per hectare 1.76 and 49.06 per cent.

Sharma and Pandey (1972) studied the costs and net profits from Guava orchard in

Uttar Pradesh. The cost of raising Guava orchard was estimated at T 3,964.82 per hectare in

the first year. The maintenance costs amounted to T 589.49 per hectare per year. The net

return from the inter crops during the three year period worked out to T 6,287.50 per

hectare. It was observed that the Guava orchard generated a net return of T 6,500 per hectare.

Patil et al. (1969) studied the cost of grape cultivation in Sangli district, and

production and marketing of mango in Ratnagiri district, through survey under taken

during 1966-67. The study revealed that the total cost and gross income moved together and

the average output – input ratio was 2.4 in grape cultivation. The total cost of establishment

21

of mango was found to be T 1863 for five years, out of which more than 50 per cent was

incurred during first year of establishment itself. The gross returns increased up to 40 years

age of garden.

Bore (1968) worked out the cost of cultivation of banana per acre in Jalgaon district at

cost ‘A’ as T 2030.69, at cost ‘B’ T 2482 and at cost ‘C’ T 2711.78 giving a gross income per

acre of T 4875. The net profit worked at cost ‘A’ was T 2845.37, at cost ‘B’ T 2393.44 and

at cost ‘C’ T 2164.21. He also pointed out that cultivators using electrical pumping for

irrigation spent about 50 per cent of the cost on labour in irrigation operations. However,

expenditure on irrigation charges, manures and fertilizers and human labors accounted the

major portion of total cost (84%) of cultivation in banana.

Heady (1968) in his book “Economics of Agricultural Production and Resource Use”

has quoted the pattern of costs and incomes in apple industry. He stated that at the outset of

an apple orchard, costs were incurred but no revenue was forthcoming from apples. A sale

value existed for the trees and land, which was based on the discounted future returns; initial

costs were high because of costs of plants and the costs of planting. While both cost and

revenue rose as the productivity of the trees increased up to 35 or 40 years of age, the annual

costs, depending upon the prices might exceed annual revenue for nearly 12 years.

Thereafter, annual revenue rose at a faster rate than costs up to the time the trees are about 30

years of age. Annual undiscounted net income was then at a maximum but began to decrease

while costs remained relatively constant and revenue fell below costs somewhere in the

neighborhood of 50 or 60 years, depending upon the level of prices.

2.3.1 Factors affecting apple production and productivity Singh and Vashist (1994) conducted the study to examine the input and output

relationship and resource use efficiency on different sizes of farms in Salem district of Tamil

Nadu. Multistage stratified random sampling procedure was adopted for the selection of

farms of different sizes from the district. The Cobb-Douglas production function which gave

the best fit was selected to establish the output - input relations with returns per farm as

dependent variables and six inputs, viz., land, human labour, bullock labour, fertilizer

expenditure, irrigation expenditure and seed expenditure as independent variables. The study

reveals that expenditure on fertilizers, irrigation and bullock labor significantly increased the

farm returns on all sizes of farms. Human labour, which was available in abundance on the

22

small farms, was used excessively and inefficiently, whereas on the large farms the

manpower increased the farm returns considerably. As regards the allocate efficiency of

labour use, land was being used efficiently on the small farms. Fertilizers and irrigation water

were also being applied at sub-optimal levels on all the three sizes of farms. Hence, there is a

lot of scope for increasing of these inputs up to the optimal level.

Wani et al. (1993) in their study on resource use efficiency and factor productivity in

apple analyzed the factors affecting the productivity of apple orchards. Cobb-Douglas

production function was applied to find resource use efficiency. The various factors

influencing apple production included in the production functions explained about 95, 67, 68,

and 67 per cent of total variation in apple production on categories A, B, C, D, E and on

pooled data, respectively. Human labour was not significant in category A & C, plant

protection turned out to be significant in all the categories. One per cent increase in

fertilizers, in category A, C & E would increase apple production by 1.7718, 0.5995 and

2.0596 per cent respectively while 0.6752 and 1.0114 per cent increase in apple production

would result by increasing plant protection by one per cent in category D & E. In case of

human labour, a one per cent increase would result in 2.3134 per cent increase only in

category B. The increase in case of pooled sample would be 0.1297, 0.3801 and 0.1692 per

cent by increasing the fertilizer, plant protection and human labour by one per cent. The study

finds out, that use of input factors below their optimum level, was one of the most felt

problems, and as such it is suggested that education need to be imparted to apple growers for

optimum allocation of resources in order to have more gains.

Babu (1992) attempted to estimate the resource use, labour employment and

efficiency in rubber plantations of Dakshina Kannada district of Karnataka state. This district

occupies first place by claiming around 85 per cent of the area under rubber cultivation in

Karnataka. Multiple random sampling techniques were adopted to select the sample farmers

considering higher area under rubber as the main criterion. Finally 67 rubber growers were

randomly selected. Labour employment was estimated by converting all the labour employed

into man days for 8 hours. Linear form of function was fitted separately for the two groups of

farms, small farm (less than 5 acres) and large farm (> 5 acres). Results revealed that rubber

cultivation provides ample opportunities for employment in case of large farms. Efficient

allocation of resources could increase the yield and also returns to the farmers. The forward

and backward linkages of rubber plantation could be strengthened by setting up of small scale

23

industries for processing and redemption of raw rubber type and tube manufacturing etc. this

could bring more income and also employment opportunities for the unemployed educated

youth of the locality.

Randev et al. (1992) conducted a study about rationale of resource use in apple

cultivation in tribal areas of Himachal Pradesh. The study was to analyse the economic

efficiency of resource use and compare the intra-farm productivities of various farm inputs in

different size groups and age groups of apple orchards. The author used the Cobb-Douglas

type of production function for studying the relationship between output of apple and various

input variables. The entire regression coefficient was found positive and significant for small

orchardists in age group of 8-14 years, except manure and fertilizer. Dummy variable for

mode of sale was significant and positive in both the age group of apple orchards.

Comparison of MVPs in the age group of 8-14 years indicated that MVPs of all variables

under study were higher than one except maintenance and establishment cost on small

orchards. The difference between actual elasticity coefficients and estimated elasticities in

case of large and small orchards in age group of 8-14 years indicated that the MVP of manure

and fertilizer, fixed capital, method of sale and establishment and maintenance cost was

higher on small orchard than large orchards. The study concludes that expenditure on human

labour indicated scope for additional absorption of labour on the orchards. The study also

revealed that there is possibility of reducing fertilizer consumption on large orchardists and

this surplus should be distributed among small and medium orchardists which will lead to

overall development of area.

Bhat et al. (1989) analyzed the resource use efficiency of apple cultivation in Jammu

& Kashmir. Their objective was to determine optimum allocation of resources in apple

cultivation and to suggest, to increase profit, without increase of total expenditure. To

examine the allocative efficiency of resources at apple orchards, Cobb-Douglas production

function was adopted. Cobb-Douglas function assisted in estimation of marginal value

product. Results predicted that regression coefficient turned out to be significant in case of

working capital, land and labour. The regression coefficient of land was 0.3262 significant at

5 per cent level. The production elasticity of labour was 0.2582 and significant at 10 per cent

level. The elasticity of working capital is 0.6780 which is significant at 1 per cent level. The

production elasticity of fixed capital is no significant with regression coefficient of 0.1172.

The coefficient of determination or R2 = 0.9235, showing a 92 per cent variation in net

24

income. The calculated F-value is 190.2209, and therefore R2 is significant at 1 per cent level.

Marginal value product indicates returns in money terms. The labour input has to be

decreased from 473 units to 397 units. The expenditure on working and fixed capital has to

be increased from Rs. 4735.10 to Rs. 11411.59 and R. 2929.16 to Rs. 3514.98 respectively.

The results conclude that shift of resources from labour input to manure and fertilizer and

fixed capital input is necessary to maximize the returns even at the existing level of

expenditure.

Nadda (1987) carried out a study about supply response of perennial crops of

Himachal Pradesh. The objective of study was acreage response behaviour of apple growers

in Himachal Pradesh. He used Nerlovian price expectation model as the basis for supply

response study of the apple crops. The most significant finding of study was that apple

growers in Himachal Pradesh are responsive to raw prices, profitability of crop, and

development of infrastructure. The trend also exhibited positive impact, while taking long

term plantation decisions. The study found that parity ratio showed an inverse relationship

with apple production. The study concluded that price policy can be effective instrument in

bringing about desired changes in acreage under perennial horticultural crops.

Tewari et al. (1987) conducted a study on rational of resource use in apple cultivation

in tribal areas of Himachal Pradesh. The coefficients of Cobb-Douglas type of production

function indicated that all exogenous variables under consideration were positive and

significant except manures of fertilizers in case of large orchardists 80 per cent variation in

endogenous variables have been explained by exogenous variables in all categories of

orchards in age groups of 8-14 years. The same variables explained less than 60 per cent of

variation in apple output in the medium and small orchards in the age group of 15-40 years,

while in case of large ones they explained 95 per cent of the variation. The reason for this

may be site aspects and more number of plants in age groups of 15-25 years on large

orchards. Medium orchards in the age group of 8-14 years and 15-40 years used manures and

fertilizers optimally, while large orchards in age group of 15-40 years used it in excess

quantity. Comparison of marginal productivities of resources between medium and small

orchardists indicated that small farms devoted greater care to apple cultivation as compared

to medium farms, while comparison between large and small farms revealed that large

orchardists paid more attention than latter.

25

Sharma (1983) conducted an econometric study of production and marketing of apple

in Shimla district. He found that elasticity coefficients of all the explanatory variables viz:

number of trees, manure and fertilizers and human labour, were significant but response of

number of trees was the most significant in explaining variation in apple production on all

sizes of farms. The analysis of MVP /factor cost ratio showed that the apple growers should

increase investment on tree plantations and increase the use of manure and fertilizers and

human labour. The producers’ share in the consumer’s rupees was less than half of the price

paid by the consumers and about 1/5th of the rupee paid by the consumer was spent on

marketing. The study suggested that transportation facilities should be improved in the study

area, and minimum support price should be announced like other crops by the Government or

HPMC to give an impetus to apple industry.

Rana et al. (1978) conducted a case study of Kumarsain Block of Shimla District on

economic optima in apple cultivation by using Cobb-Douglas type of production function.

They found that the extent of variation in apple production explained by human labour,

fertilizers and organic manures, pesticides and age of the orchard was about 99.96 and 98 per

cent in the case of progressive, non progressive and pooled samples of both the regions,

respectively. However, the regression coefficients of human labour with respect to non

progressive apple growers and of pesticides for progressive region indicated negative

contribution to the apple production in the study area. The negative value of M V P of human

labour in non progressive apple growers showed a problem of disguised unemployment. The

negative M V P for pesticides in progressive growers showed its curtailment and positive for

non progressive showed its increased use for increasing returns. The positive M V P for

manures also showed increasing use at the existing level. They also showed that from the

statistical point of view, there appeared no difference in the technical efficiency of apple

production between two regions.

Kahlon and Acharya (1967) conducted a study on management input in farming with

an idea to identify the management factors and to devise a criterion to measure this. They

prepared an index of management on the basis of ten important decisions, and ranked the

decisions according to their importance. These ranks were further converted into scores by

using Fisher & Yates’ table for normalization of ranks. They concluded that the factors

identified could largely explain the variation in output and a very high significant correlation

existed between farm income and management input. It did not have significant partial

26

correlation with any of the conventional input. The change in the signs and magnitude of

partial regression coefficients of other conventional inputs by the inclusion of management

input in the equation indicated that resource productivity studies were biased; management

input was not incorporated in the equation. The productivities of those factors with which

management input was not correlated were under estimated, while those with which it was

relatively highly correlated were over-estimated. The returns to scale were under estimated, if

management input was excluded from the production function analysis.

2.3.2 Impact of climate change on apple production and productivity

Braun and Muller (2012) reported in the state of Hesse that in fruit trees, one can

consider a number of possible threats to production associated with climate change. These

could be the increased risk of spring frost, increased risks due to new or more aggressive

diseases and pests, hail and water shortage due to drier summers or more variable rainfall

with longer droughts. They stressed on the spring period with initial flowering and full

flowering as the critical phenological stages using apple trees as reference.

Panwar (2011) reported that apple production in Himachal Pradesh is an impending

crisis for the farmers. As 90% of the apple orchardists are from poor and marginal peasant

class based on the extent of land holding. The inherent cause of this crisis is the nature of

land holding pattern in addition to the deteriorating quality of land. He also mentioned that

changes in the climate have severely affected the apple produce.

Sharma H R (2011) has studied the impact of climate change on crops in Himachal

Pradesh and reported that there is slow but perceptible change in weather and climate

conditions which has posed yet another serious threat to the cultivation of some of the high

value crops. He determined that during the last fifteen-twenty years, the cultivation of apple

has shifted along the altitude, primarily because of inadequate precipitation in the form of

snow and rains leading to non-fulfillment of the chilling requirement of the crop. This has

resulted into year to year wild fluctuations in apple output inflicting huge losses on apple

growers

Ashebir (2010) reported that lack of effective chilling during the dormant season is

one of the major problems when apples are growing under a tropical climate in a tropical

mountain area. The trials were carried out between 2004 and 2006. The results show positive

effect of the dormancy breaking agents on the productivity of the trees after defoliation

27

leading to the spread flowering period over five weeks. The results of these first trials

indicate that it is possible to develop new apple production in the mountain region of Tigray,

Ethiopia.

Rana et al. (2009) reported that the production of apple has gradually increased but

the productivity has fallen from 10.8 to 5.8 t/ha. The reasons they attributed to it are climate

variability, soil, crop improvement etc. Among all the productivity reducing factors, climate

is difficult to manage. They examined change in climatic parameters especially chilling units

and farmers perceptions in Himachal Pradesh over time and its associated changes in apple

productivity.

Randev (2009) has determined the Impact of climate change on apple productivity in

Himachal Pradesh. The study was conducted through water resource availability, linkages

among weather parameters by adopting functional and statistical tools. Results reveal

average annual rain and snowfall as 121.9 cm and 96.5 cm. Albeit rainfall (121.9 cm) has

been found within the required range (100-125cm) for good apple production, yet

productivity has shown huge differential (1 to 53 kg/tree) due to non availability of water at

critical stages of at first dormant stage followed by other critical stages of growth. Linkages

between productivity and weather parameters have revealed ‘temperature variations’ as

pivotal factor in disturbing the hydrological cycle and intensity of occurrence of other

parameters. Mean difference in annual maximum temperature has been worked out to be

24.41 per cent indicating ‘warming up of the eco system’. This temperature variation has

disturbed the timely availability of water simultaneously accompanied by changes in other

parameters thereby cumulatively bringing apple production range between 2-110 ton/ha.

Thus, functional analysis of weather parameters have revealed that availability of weather

factors within the critical limits of growth stages has been found to be a ‘must’ otherwise

drastic fluctuations in productivity have been reported. Hence, integrated efforts in water

resource developmental projects through creation of vegetative cover have been considered

as the best for improving water availability for enhancing apple productivity.

Deodhar (2006) reported that most of the apple orchards in India are nearly 30 years

old and even older and are characterized by declining yield and lack of fruit uniformity in

terms of shape, size, and color. Low productivity compared with most other domestic fruit as

well as other apple-producing countries raises apple prices relative to substitute foods and

limits growth in domestic apple consumption. It is unclear if the production constraints

28

imposed by terrain and climate can and will be overcome by the introduction of improved

varieties and cultivation practices.

Neeraj Vedwan and Robert E. Rhoades (2001) examined the perception of farmers in

the western Himalayas of India regarding the impact of climatic change on the apple. This

was done by comparing the locally idealized traditional weather cycle with climate change as

perceived by the farmers of the region. They have used snowfall and rainfall data from 1962

–1996 to measure the accuracy of perceptions. Although climate change was usually

described by farmers as the temporal displacement of the weather cycle, the changes

themselves still were not perceived as altering the idealized weather calendar. Most

importantly, perception of climate change was structured by knowledge of crop-climate

interaction and by differential apple performance outcomes associated with the changed

conditions.

Mattioli (1998) carried out field studies during 1985-89 at Piacenza, Italy, to

investigate the effect of environmental factors at the flowering stage on apple production.

Results showed no direct correlation between frost damage in spring and yield losses.

However, he stated that the effect may vary based on the heterogeneity of the landscape

particularly in valleys where temperature is low.

Chapter-3

METHODOLOGY

Systematic methodology is the base of any scientific study as the precision; reliability

and validity of scientific enquiry depend upon appropriate methodology. This chapter outlines

briefly the characteristics of the study area, the methodology used in selection of the Study area

and samples, the nature and sources of data and the various analytical frameworks employed.

These items are described under the following sub-heads.

3.1 Sampling Procedure

3.2 Nature and Source of Data

3.3 Analytical Techniques

3.4 Limitations of the Study

3.1 SAMPLING PROCEDURE

3.1.1 The study area

Site selection can be difficult, time consuming, expensive task and probably cannot be

fully completed before beginning the apple farming. The list of information ultimately desired is

long and involves detailed data on various parameters. Therefore, taking all these limitations into

consideration, the study attempts to depict various aspects of apple farming in the selected

villages in the study area. The main objectives were to study the production aspects, with a view

to elucidate the growth, development, economics and problems encountered in apple cultivation.

Among all the districts in Himachal Pradesh, Shimla district was purposively selected due to its

highest concentration of apple plantations. This district has been found to be on the cutting edge,

as far as varying indicators of commercialization of agriculture through fruit farming are

concerned. Further Narkanda block was randomly selected for the final study. Keeping this in

view, this block provided suitable background to conduct the present investigation. The Figure 1

draws the picture of selection of the study block.

30

Fig.1 Selection of the Study Site (Narkanda Block)

31

3.1.2. Sampling frame

To obtain data for the research survey, a sample is usually required. The reason being, the

population may be so large as to make it difficult to get to every individual. Therefore population

should be sampled keeping the confinements due to time and money. A sample is a subset of a

population from which to obtain information. The multistage random sampling technique was

applied for the selection of households in the selected block. The entire sampling plan consisted

of several steps. At the first stage one apple producing district from state of Himachal Pradesh

was chosen purposively. At the second stage one block from the selected district was chosen

randomly. In the third stage the block was divided into five altitudinal zones and were designated

as E1, E2, E3, E4 and E5 for ≤1500m, 1500-2000m, 2000-2500m, 2500- 3000m, ≥3000m above

msl respectively. Selection of villages constitutes the fourth stage in the sampling frame. In the

fourth stage, a list of villages falling under each altitudinal zone was prepared along with the area

under apple and other crops. There after 2 villages were selected randomly from each altitudinal

zone. Thus, in all 10 villages viz., Kirti, Namjha, Mangsu, Shamathla, Thanadar, Pamlai, Jarol,

Tikkar, Saroga and Shilajan were ultimately selected for the present investigation. The sample

design with distribution of selected households is presented in Figure 2.

A complete enumeration of all the 10 villages was done and the list of the households

was prepared with the help of patwari of the village. From the list of commercial apple growers

so prepared, 7 households from each village were selected based on equal allocation sampling

method. Thus a sample of 70 apple growers from the block was drawn at random.

3.2 NATURE AND SOURCE OF DATA

To meet the objectives of the present study, both primary as well as secondary data were

collected.

3.2.1 Primary data

The primary data on demographic features family size, age, education, occupation etc,

economic parameters (land inventory, cropping pattern and income), cost of production, yield

and problems faced by the growers in various facets of production and marketing were collected

on well designed pre-tested schedule by adopting a personal interview method from the selected

households in the study area during the year 2012-13.

32

Fig. 2 Schematic representation of the Sampling frame

3.2.2 Secondary data

Secondary data pertaining to the list of village households, cropped area, production,

productivity of Himachal Pradesh, India and World were recorded from the Directorate of

Horticulture Shimla Himachal Pradesh, National Horticulture Board, Block Development offices

of respective blocks, respective revenue offices, Directorates of Land Records and FAO.

3.3 ANALYTICAL TECHNIQUES

As a preliminary definition one could think of a model as an attempt to describe a certain

process or system through use of simplified representation. Preferably a quantitative

mathematical expression, that focuses on a relatively few variables that control the process or

system. Also variability in the orchardists and farming conditions draws the focus towards

applying the statistical techniques in order to analyse the data, which in turn builds an accurate

understanding of the present scenario of the apple farming in the study area.

33

Therefore to meet out the requirements of the study objectives, tabular analysis, averages,

percentages, standard deviation, coefficient of variation, index numbers, decomposition

techniques and regression analysis, likert scale, were used as and when required. Simple tabular

analysis was used to examine socio-economic status of the growers, resource structure, income

and expenditure pattern in farming and growers’ opinions about the production problems.

Simple statistical tools like averages and percentages were used to compare, contrast and

interpret results. The sex ratio, literacy rate and index were calculated using the following

formulas.

Sex Ratio =

No. of Females in a Family

X 1000

No. of Males

Literacy Rate =

Total Number of Literate persons

X 100

Total Population

Literacy Index =

∑ Wi Xi

∑ Wi

Where,

Wi = Weights (0, 1, 2,3,4,5 & 6) for illiterate, primary, middle, senior secondary, secondary and

graduate, post graduate & above respectively.

Xi = Number of persons in respective category.

Dependency Ratio =

No. of Dependents in a family

Total workers in the family

34

3.3.1 Effect of Area and Yield on Production

In order to study the effect of area and yield in increasing production during the period

under study, the following model of Narula and Vidya Sagar was employed.

Qn - Qo =

(Yn - Yo) An + Ao

+

(An + Ao) Yn + Yo

2 2

Where:

Qn and Qo = Production of a crop during the end period (2011-12) and base period (1973-74)

respectively.

Yn and Yo = Yield of a crop during the end and base period respectively.

An and Ao = Area under a crop during the end and base period respectively.

3.3.3 Comparative analysis of Apple productivity

One Way Classification method was applied

CD = “ t ” table value at error d. f. X 2 X MSE

r

CV = SD

X 100 Mean

Where, r = Number of observations in each category

CD = Critical Difference

CV = Coefficient of variation

3.3.4 Compound growth rate (CGR)

The compound growth rates for different variables were computed by fitting the power

function to the figures of area, production and productivity of apple for the period of 1973-1974

35

to 2011-2012 to world, Asia, India and different districts of Himachal Pradesh. The ordinary

least square method was used to fit the power function of the following form Y= abt. It was

converted into log linear function with the help of logarithmic transformation as under:

Log Y = Log a + t log b.

Where:

Y = Dependent variable (Area, production and productivity etc.)

t = Independent variable (time in a year).

Compound growth rates (CGRs) were calculated by using the following formula:

CGR = (Antilog b-1) × 100

Standard error (SE) of C G R was calculated by using the following formula:

SE of CGR = 100 b

× SE Log b Log e 10

Student’s t test was used to test the significance of growth rates.

3.3.5 Managerial skill index

Managerial skill index was used to measure the management capability of different

orchardists. The formula to calculate the managerial skill index (MSI) (Timothy, O and

Krishnamurthy S, 1990) is given as under:

MSI = Mi

X 100

M Where,

Mi =

1M1 + 2M2 + 3M3

6

36

M1 = Number of years of schooling

M2 = Years of experience in farming

M3 = Farm training undergone, if any

With,

M1 = 0 If illiterate

1 If up to school/literate

3 If college/college drop out

M2 = 0 If no experience of farming

1 If there is 1 to 10 years of experience in farming.

3 If there is more than 10 years of experience in farming.

M3 = 0 If no farm training undergone.

1 If once trained

3 If trained more than once.

Managerial skill index of each orchardist was estimated and grouped.

3.3.6 Multiple regression analysis

Category-wise multiple regression analysis was carried out to know the factors

influencing the apple productivity. Production function was estimated on per hectare basis of

bearing apple plants to measure returns to various factors of production and to mitigate the effect

of Multicolinearity. Thus, all the variables except management skill index, spray deviation from

recommended Schedule and altitude were transformed into per hectare basis. Some of the non -

strategic collinear variables were omitted from the analysis to improve the precision of

regression parameter. The variables considered for explaining the level of production at the

farmers end in regression equations, were same, between sampled categories. In sample farms,

following variables were used.

Log linear equations

Log Y = Loga + b1 logX1 + b2 logX2 + b3 logX3+ b4 logX4 + b5 logX5 + b6 logX6 + b7 logX7

+ b8 logX8.

37

Y = Productivity of Apple orchards in study area (MT/Ha)

X1 = Quantity of FYM applied (Kg)

X2 = Quantity of Fertilizers applied (Kg)

X3= Deviation from prescribed spray schedule

X4 = Human labour days (No.)

X5 = Expenditure on fixed capital (Rs.)

X6 = Plant Density / Hectare

X7 = Literacy Index

X8 = Managerial Skill Index

u = Random term which follows normal distribution with zero mean and constant

variance.

a = Intercept and b1 to b8 are the elasticity coefficients

Productivity (Y): The productivity has been defined as the average quantity of yield produced

per hectare of land area in past three years (including the reference year).

Quantity of FYM applied (X1): It is the physical quantity of the farm yard manure applied in

terms of Kilograms.

Quantity of fertilizers applied (X2): It is the physical quantity of the fertilizers applied in terms

of Kilograms.

Deviation from prescribed spray schedule (X3): The details of deviation of number of sprays

from the spray schedule was assigned by the values 1.14, 1, 0.86 and 0.71 for 8, 7, 6 and 5

number of sprays.

Human labour (X4): In this study human labour was measured in adult man days of eight hours.

It included family labour, permanent and casually hired labour. The variation in the efficiency of

labour was removed by converting the female and child labour days into adult man days. The

38

difference in the efficiency of labour has been taken into account by considering one man day

equivalent of one adult (18 years and above) working for 8 hours on day. One man day was

considered equivalent to two minors (less than 18 years) and three women days were considered

equivalent to two man days.

Expenditure on fixed capital (X5): Fixed capital includes the sum of annual depreciation on

farm implements, machinery, farm building, livestock and interest in on fixed capital, amortized

establishment cost and rental value of land.

Plant Density / Hectare (X6): It represents the number of plants per hectare of land area.

Literacy Index (X7): Explained in Para 3.3

Managerial skill index (X8): Management index was prepared on the basis education,

experience and skill acquired by the orchardists. The procedure for computation of managerial

skill index (MSI) has been outlined in section 3.3.5 of this chapter.

3.3.7 Criteria for selection of appropriate function

Two types of algebraic forms viz,; linear and cobb – Douglas were tried in the present

study with the optimism that one of these would give best fit and confirm to the logic of signs

and magnitude of the estimated parameters. The final choice of function was made on the basis

of economic and statistical criteria such as value of R2, sign & significance of regression

coefficients of the function. Accordingly, Cobb–Douglas form of function turned out to be the

best fit function, and hence used in functional analysis.

3.3.8 Returns to scale

The sum of elasticity coefficients in Cobb-Douglas indicates the returns to scale. The

return to scale suggests the percentage increase in output when all the inputs are increased

simultaneously by one per cent. The Σbi was statistically tested by ‘F’ test as follows:

F (1, N-K) d.f. = ΣΣΣΣ (bi-1)

2

Var. ΣΣΣΣbi / N-K

39

Where,

N = Number of observations

K = Total number of parameters estimated

Σ bi = Summation of elasticity coefficients

3.3.9 Adjusted coefficient of multiple determination ( R2

)

_2

The adjusted value of R is calculated as follows (Koutsoyiannis, 1987).

2 = 1- ( 1- R2 )

N-1

R N-K

Where

N = number of sample observations

K = number of parameters estimated.

R2 = Unadjusted multiple correlation coefficient

3.3.10 Test for overall significance of regression

‘F’ test has been used to test the overall significance of explanatory variables whether

they affect the dependent variable or not. The expression for the test is as under (Koutsoyiannis,

2002)

2

×

N-K F ( k - 1, N- k) d. f. = R

2 K-1

1 - R

Where,

K = Number of parameters

N = Number of observations in the sample

R2 = Coefficient of adjusted multiple determination

40

3.2.11 Marginal value products

In order to evaluate the economic rationale of resource use on different categories of

farms, the marginal value productivities (MVPs) of different resources was calculated by

multiplying regression coefficient of given resources with the ratio of geometric means of yield

to the geometric mean of given resources. The marginal value product of a particular resource

represents the expected addition to the gross returns caused by an addition of one unit of that

resource while other inputs are held constant. For estimation of MVPxi the computational steps

followed are as under:

MVPxi = ( b i ) Y ( P y )

X i

Where,

Y = Geometric mean of output

Xi = Geometric mean of input

bi = regression coefficients

i = 1 , 2, ………n and

Py = price of apple per unit ( R )

3.3.12 Mean Perception Score (MPS)

The perception of the respondents on the effects of climate change on apple production

and productivity was measured with the help of the scale developed for the purpose. The scale

consisted of 11statements/items which were framed by personally interacting with the

respondents and then edited the responses as per the criteria given by Edwards and Kilpatrick

(1948). The response of each respondent against each statement was obtained, on a five point

continuum scale viz. Strongly Agree, Agree, Undecided/don’t know, Disagree and Strongly

Disagree with respective score of 5, 4, 3, 2, and 1.

3.4 Limitations of the study Since, the data was collected by survey method; the inbuilt lacunae affiliated with this

type of enquiry might have crept into the study. The findings are based on the expressed opinion

41

of the respondents and the errors in recollecting the facts by the respondents cannot be

completely ruled out on account of the non-maintenance of the farm records. Sincere efforts have

been made to elicit accurate and reliable information as far as possible by cross questioning; the

degree of discrepancy if any would be negligible as the estimates presented are in averages.

It may however, be recognized that the finding of the study need not be generalized

beyond the boundaries of the area under investigation and applicable to such other areas having

similar agro-climatic and socio-economic conditions.

The data stands for the year 2012-13 only, due to time, money and labour constraints, the

analysis has been restricted to only 70 respondents of the study area.

Chapter-4

RESULTS AND DISCUSSION

This chapter explains the results of the present study. The results have been presented

under the following sub- heads and under eight sections.

Section I : Trends in area, production and productivities of apples

Section II : Background of the study area

Section III : Socio-economic characteristics of sampled orchardists

Section IV : Existing resource structure

Section V : Costs and returns structure in apple cultivation

Section VI : Factors affecting apple productivity

Section VII : Farmers’ perception regarding the climate change

Section VIII : Production and marketing problems faced by the sampled

orchardists

4.1 TRENDS IN AREA, PRODUCTION AND PRODUCTIVITY OF APPLE

World Scenario

India ranks second in the production of fruits next to China. Apple is widely grown in

the temperate regions of the world, and in the year 2011-12, the world apple production was

7.56 crore tonnes. The world apple production has grown at compound growth rate of 2.4 per

cent per annum from 1973-74 to 2011-12. Asian continent has witnessed an impressive

growth in area, production and productivity of apple as noticed from the Table 4.1. China

happens to be the major growth engine in apple farming for Asia. China ranks first in the

subject of apple production, accounting for nearly 40 per cent of global production followed

by United States of America 6.65 per cent, Turkey 4.25 per cent, Poland 4.13 per cent, Iran

4.01 per cent, France 3.64 per cent and Italy 3.31 per cent. The average share of Indian apple

production based on 2011-12 data was 3.82 per cent and ranked 8th among the apple

producing countries of the world. At present India has achieved a production potential of

28.91 lakh tonnes annually. During the period 1973-74 to 2011-12, apple production in India

recorded a significant growth of 3.5 per cent per annum. In apple production, India’s growth

rate was found more than world’s growth rate, but less than Asian growth in production.

43

Presently apple occupies 4.5 per cent of area under total fruits and contributes 3.9 per cent

towards total fruit production in India.

Table 4.1 Compound Growth of Area, Production and Productivity of Apple in

various regions during 1973-74 to 2011-12

Region Area Production Productivity

India 2.4**

(0.044) 3.5*

(0.090) 1.1

(0.088)

Asia 3.9*

(0.181) 6.3*

(0.093) 2.4*

(0.133)

World 1.2

(0.088) 2.4**

(0.044) 1.2

(0.088)

Source: FAO , 2013

Note: * - significant at 1 % level of significance ** - significant at 5 % level of significance

In India, the production of apple is majorly confined to Jammu and Kashmir,

Himachal Pradesh, Uttarakhand, Arunachal Pradesh, Nagaland and Sikkim. However, Jammu

and Kashmir and Himachal Pradesh are the most important states together accounting for 81

per cent of the total area and 95 per cent of the production in the country. The fruit plays an

important role in the economy of these hilly states and well-being of farming community.

International comparison of productivity in apple

The study of productivity per unit of land is important to study the comparative

advantages/ disadvantages in various pockets of apple production. Competitiveness between

states, regions and nations in the long run is influenced by comparative advantage and ability

to develop the comparative advantages. Therefore, estimates of productivities of major apple

producing countries were used to study the comparative advantages in the apple production.

The disparity in apple yields between the countries may depend upon level of adoption and

degree of adjustments of production system to the new technological advances and the

climatic factors.

The average annual yield per hectare for 1973-74 through 2011-12 was found highest

for France (33.60 MT/ha), followed by Italy (31.38 MT/ha), Chile (25.50 MT/ha) and USA

(24.65 MT/ha). Next to the above-mentioned countries were Brazil (20.85 MT/ha), followed

by Turkey (18.08 MT/ha), Iran (10.65 MT/ha) and China (6.81 MT/ha). It is fascinating to

note that though China is the leader in apple production, it stood eighth in terms of

productivity. In comparison with all other major countries, it is depressing to note that India

44

was falling behind all of them with a meager productivity of 5.92 MT/ha placing itself in a

critical position amidst the apple industry. The related details are given in Table 4.2.

The productivity was found relatively more stable in countries like, USA, Italy,

Turkey, France and India. The degree of instability in the productivity was found highest in

China followed by Brazil, Chile and Iran.

Table 4.2 Comparative analysis of apple productivity of major apple producing

countries

Sr. No Country Range

Annual average for the

period 1973-74 - 2011-12

(MT/ ha)

Coefficient of

Variation

(%)

1 China 2.62 - 17.54 06.81 68.28

2 USA 17.59 - 31.95 24.65 15.90

3 Turkey 10.92 - 23.81 18.08 18.97

4 Italy 23.60 - 42.41 31.38 16.73

5 India 4.14 - 10.00 05.92 20.10

6 France 18.69 - 44.36 33.60 19.67

7 Iran 3.95 - 16.00 10.65 34.27

8 Brazil 5.89 - 38.39 20.85 46.52

9 Chile 10.34 - 40.00 25.50 34.51

Source: FAO, 2013 CD = 1.89

Fig.3 Annual average productivity (Apple) of the major apple producing countries

during 1973-74 - 2011-12

5.92 6.81

10.65

18.0820.85

24.65 25.50

31.3833.60

0.00

5.00

10.00

15.00

20.00

25.00

30.00

35.00

40.00

India China Iran Turkey Brazil USA Chile Italy France

M T

/ h

a

<< Major apple producing countries >>

45

The table reveals that, there was statistically no difference in the average annual mean

productivity of China and India and between USA and Chile because productivity differences

are less than that of critical difference value that is 1.89. In case of other countries, there

existed major differences between the productivities. The countries like France, Italy, USA

and Turkey with higher levels of productivity experienced higher levels of stability in

productivity except the cases of Chile and India.

These international differences in apple productivity may be endorsed to different

factors like land area, type of land, cultivars, technology adopted, geographical conditions

like slope, elevation and aspect, the irrigation facilities, managerial skills and risk bearing

abilities of the farmers. Above all, factors like micro and macroclimate play a very crucial

role.

Trends in area, production and productivity of Himachal Pradesh

The level of growth in output is jointly determined by the growth rate in area and that

in yield. The purpose of this analysis is to examine the performance of apple cultivation in

the study state and see if there have been any noticeable changes during the last four decades.

This would help in finding out the underlying factors responsible for such performance and

thereby permit a broad judgment about the overall production possibilities in times to come.

Himachal Pradesh has undergone a revolution in the apple production during last few

decades. The area under apple has increased by more than six-folds since 1966-67. It

increased at a compound growth rate of 3.27 per cent per annum between 1973-74 and 2011-

12 period. During 1966-67, the area under apples constituted nearly 58 per cent of the total

fruit area in the state. In the later years, there has been relatively more emphasis of planting

of other fruit trees in the state as a consequence of which the proportionate share of apple

area has come down to nearly 48.30 per cent in the year 2011-12. More than 2 lakh farm

families are engaged in apple cultivation out of which nearly 90 per cent are small and

marginal with an average holdings of less than 0.6 hectares. Apple farming is the fastest

growing economic activity of the state and is being grown in 9 out of 12 districts. Due to

varied agro-climatic condition across the districts, there exists large variation in the area and

output growth of this crop activity.

46

Changes in Acreage The district wise broad picture of change in the apple acreage has been presented in

Table 4.3. A cursory glance on the table reveals that, the area under apple has been showing a

steady growth in Himachal Pradesh. For the state as a whole, the area increased by nearly

224.37 per cent during triennium ending 2011-12 over the base triennium 1975-76. In terms

of compound growth rates, it grew at the rate of 3.27 per cent per annum during the study

period. The area growth was quite impressive and significant in Lahaul & Spiti, Chamba,

Kinnaur districts. These districts constitute backward tribal districts, which received added

attention in the recent past by the state government for augmenting growth promotion in these

untapped non- traditional areas. Moreover, climatic conditions are more favourable in these

districts for the successful cultivation of apples. Shimla, Mandi and Kullu districts comprises

of the traditional areas for apple that recorded an increase of 118.40, 215.69 and 199.00 per

Table 4.3 District wise changes in area of apple in Himachal Pradesh, 1973-74 to

2011-12

Sr. No District

Base triennium

ending 1975-76

( 000'Ha )

Triennium

ending 2011-12

( 000'Ha )

Percentage change

over base triennium

ending 1975-76

Compound growth

rate (% per annum)

1 Chamba 0.87 12.23 1305.75 7.50*

(0.094)

2 Kangra 0.34 0.44 29.41 0.50**

(0.131)

3 Kinnaur 0.95 9.98 950.53 6.10*

(0.092)

4 Kullu 8.07 24.13 199.00 3.00*

(0.045)

5 Lahaul & Spiti 0.06a 8.66 14333.33 9.40*

(0.239)

6 Mandi 4.97 15.69 215.69 3.30*

(0.045)

7 Shimla 15.87 34.66 118.40 2.20*

(0.044)

8 Solan 0.18 0.09 - 50.00 - 3.00*

(0.379)

9 Sirmaur 2.34 3.12 33.33 0.80*

(0.088)

Himachal

Pradesh 33.60 108.99 224.37

3.27*

(0.045)

Source: Directorate of Horticulture, Govt. of Himachal Pradesh, Navbahar Shimla-II Note: a – denotes the Base triennium ending 1984-85 * - denotes significant at 1 % level of significance **- denotes significant at 5 % level of significance

47

cent respectively in the study area during triennium ending 2011-12 over base triennium

1975-76. The corresponding figures of growth rates in area worked out to 2.20, 3.30 and 3.00

per cent per annum.

Fig. 4 Trends in Area under apple in Himachal Pradesh (ha), 1973-74 to 2011-12

District Kangra and Sirmaur, which have lesser comparative advantage of growing

apple, also experienced positive and significant growth of 0.50 and 0.80 per cent per annum

respectively. It is interesting to note that, district Solan, exhibited a declining trend in the area

expansion during the study period of 39 years.

Changes in Production

Amongst all the fruits grown in the state, apple occupies the premier position in terms

of production also, accounting for nearly 74 per cent of total fruit production. The results of

the district wise analysis of change in the production of apple have been presented in Table

4.4. The table shows that apple production has taken new stride, and has increased by about

289 per cent during triennium 1975-76. Production has increased at the compound growth

rate of 3.50 per cent per annum during the study period in the state. The perusal of the table

reveals that, the three tribal districts viz., Lahaul & Spiti, Kinnaur and Chamba (High growth

districts) has recorded a significant increase in the production at a compound growth rate of

9.90, 8.20 and 4.50 per cent per annum respectively during the span of 39 years. The low

altitude districts of Kangra, Solan and Sirmaur recorded negative growth in the production of

apples during study period. This may be attributed to change in climatic conditions adversely

0

20000

40000

60000

80000

100000

120000

140000

A r

e a

( h

a )

<< Y e a r >>

48

affecting the productivity of the crop. The incremental production of apples has come mainly

because of area expansion and the productivity of this fruit is quite low as compared to

advanced countries.

Table 4.4 District wise changes in production of apple in Himachal Pradesh, 1973-74

to 2011-12

Sr. No District

Base triennium

ending 1975-76

( 000'MT )

Triennium

ending 2011-12

( 000'MT )

Percentage change

over base triennium

ending 1975-76

Compound growth

rate (% per annum)

1 Chamba 1.63 5.94 264.42 4.50*

(0.454)

2 Kangra 1.25 0.41 - 67.20 - 1.10

(0.601)

3 Kinnaur 3.35 52.45 1465.67 8.20*

(0.283)

4 Kullu 34.55 96.74 180.44 2.80*

(0.402)

5 Lahaul & Spiti 0.02a 0.17 844.44 9.90*

(0.527)

6 Mandi 17.41 11.80 - 32.22 2.80*

(0.402)

7 Shimla 56.98 314.42 451.81 3.60*

(0.360)

8 Solan 0.60 0.08 - 86.67 - 6.60* (0.366)

9 Sirmaur 8.21 0.46 - 94.40 - 4.60* (0.498)

Himachal

Pradesh 124 482.42 289.05

3.50* (0.315)

Source: Directorate of Horticulture, Govt. of Himachal Pradesh, Navbahar Shimla-II Note: a – denotes base triennium ending 1984-85 * - denotes significant at 1 % level of significance

Fig. 5 Trends in Production of apple in Himachal Pradesh (MT), 1973-74 to 2011-12

0

100000

200000

300000

400000

500000

600000

700000

800000

900000

1000000

Q u

a n

t i

t y

( M

T )

<< Y e a r >>

49

Changes in Productivity

Productivity in fruit farming is most often assessed by measures of crop yield. The

growth rate in productivity is an important determinant of agricultural transformation and is

considered as the engine of growth to the farm economy. Thus, it is important to assess the

fruit productivity; its growth, to know our stand and what ought to be done to achieve the

international standards in the productivity. The crop productivity growth is an indicator of use

of farming knowledge, technology, infrastructural development, farm investments, and

development of suitable price policy. The productivity growth allows farmers to break out of

poverty and low-income equilibrium trap and contribute to overall economic growth. To

achieve this, there is a need for strengthening the efforts at increasing production by

maintaining or increasing productivity.

In Himachal Pradesh, the overall productivity of apple hovers around 4 tonnes per

hectare as compared to 7 tonnes per hectare of all India level and is much below the

international level of 40 tonnes per hectare. The district wise growth in the productivity of

bearing plants in Himachal Pradesh is given in Table 4.5.

Table 4.5 District wise changes in productivity of apple in Himachal Pradesh, 1973-74

to 2011-12

S.No District Base triennium

ending 1975-76 ( MT/ ha )

Triennium

ending 2011-12 ( MT/ ha )

Percentage change

over base triennium

ending 1975-76

Compound growth

rate (% per annum)

1 Chamba 1.85 0.49 -73.51 - 3.00* (0.421)

2 Kangra 3.66 0.94 -74.31 - 1.60

(0.684)

3 Kinnaur 3.43 5.25 53.06 2.10*

(0.222)

4 Kullu 4.22 4.02 - 4.74 - 0.20

(0.391)

5 Lahaul & Spiti 0.3a 0.08 -73.33 - 3.70* (0.795)

6 Mandi 3.57 0.76 -78.71 - 0.40

(4.325)

7 Shimla 3.58 9.08 153.63 1.40*

(0.396)

8 Solan 3.43 0.32 - 90.67 - 3.60* (0.545)

9 Sirmaur 3.51 0.15 - 95.73 - 5.40* (0.494)

Himachal

Pradesh 3.67 4.38 19.33

0.30 (0.305)

Note: a-denotes base triennium ending 1984-85 * - denotes significant at 1 % level of significance ** - denotes significant at 5 % level of significance

50

It is very disheartening to note that except Kinnaur and Shimla districts, all the

districts have exhibited the very waning trends in growth in productivity. The declining

growth n productivity was significant for the districts of Solan, Sirmaur, Chamba and Lahaul

& Spiti. Growth in productivity was observed in only two districts namely Shimla and

Kinnaur. The scenario of continued deceleration in apple productivity is a cause of concern.

This dismal growth in yield may be attributed to predominance of old and senile orchards,

development of apple industry in rainfed conditions, global warming, low density of

plantation, lack of efficient use of irrigation water, quality seeds and planting material,

pollination problems, site selection, imbalanced use of resources etc.

Fig. 6 Trends in productivity of apple in Himachal Pradesh (MT/ ha), 1973-74 to

2011-12

Inter- district comparison of apple productivity In the same manner, the productivities of various districts of Himachal Pradesh were

compared and is given in Table 4.6. As revealed by the table, average annual productivity

was highest in Shimla district, followed by Kullu and Kinnaur districts of the state. This may

be due to existence of niche advantages for the cultivation of apple in these districts. These

high productivity districts also exhibited high degrees of stability and productivity levels. In

general, the low productivity districts were found facing higher instability in the yield levels.

Therefore, apple farming is getting low prominence in these districts. The table shows that

there existed statistically no differences in the productivity between the districts Solan,

Sirmaur, Lahul & Spiti and Kangra. Similarly, productivity differences in apple in Mandi,

0

1

2

3

4

5

6

7

8

9

Y i

e l

d (

M T

/ h

a )

<< Y e a r >>

51

Chamba and Kangra were non-significant. However, statistically wide differences were

observed in apple productivity between Kinnaur, Kullu and Shimla districts of the State.

Table 4.6 Inter-district comparative analysis of apple productivity in Himachal Pradesh

Fig.7 Annual average productivities (Apple) of the districts of Himachal Pradesh

during the period 1973-74 to 2011-12

Effect of Area and Yield on Production Yield and area are considered important contributors in the production of apples. In

order to visualize the contribution of each of them in the production, Narula and Sagar model

was used. The results of the analysis have been presented in the table 4.7 for different apple

producing districts of Himachal Pradesh. The table clearly shows that, for the state as a

whole, increase in apple production during the period of 39 years, was mainly due to area

0.22

0.48

0.65

1.13

1.24

1.26

3.46

4.24

6.67

0.00 1.00 2.00 3.00 4.00 5.00 6.00 7.00 8.00

Lahul & Spiti

Sirmour

Solan

Kangra

Chamba

Mandi

Kinnaur

Kullu

Shimla

<< M T / h a >>

<<

D i

s t

r i

c t

s >

>

Sr. No District Range

Annual average for the

period 1973-74 - 2011-12

(MT/ ha)

Coefficient of

Variation

(%)

1 Chamba 0.18 - 11.64 1.24 145.97

2 Kangra 0.05 - 4.47 1.13 97.34

3 Kinnaur 0.46 - 6.38 3.46 36.42

4 Kullu 0.38 - 8.68 4.24 46.7

5 Lahaul & Spiti 0.00 - 0.71 0.22 90.91

6 Mandi 0.27 - 6.78 1.26 92.06

7 Shimla 0.6 - 17.41 6.67 51.27

8 Solan 0.06 - 5.14 0.65 163.07

9 Sirmaur 0.02 - 4.63 0.48 197.92

Source: DOH, Shimla CD = 0.67

expansion (85.67%). The yield factor contributed only 14.33 per cent towards the total

increase in apple output. This may be due to the better management and adoption of new

farm technology. Yield effect was more pronounced in Kangra, Mandi, Solan and Sirmaur

districts of the state. In Lahaul & Spiti and Shimla districts, increase in apple pro

almost equally shared by yield and area. Production of apple increased by 305.72 and 104.96

per cent due to increase in acreage in Chamba and Kullu districts respectively and the

corresponding effects of yield in these districts, decreased the

per cent.

Table 4.7 Contribution of Yield and Area in the production of Apples in different

districts of Himachal Pradesh, 1973

District

Chamba

Kangra

Kinnaur

Kullu

Lahaul & Spiti

Mandi

Shimla

Solan

Sirmaur

Himachal Pradesh

Source: DOH, Sh

Fig.8 Percentage contribution due to yield & area in production As exposited in Table 4.8, at all India level, the contribution of yield towards the

growth of production was estimated at 52 per cent, while area shared 48 per cent towards

increased production. For the Asia as a whole, increase in apple area contributed more than

- 205.72

126.54

305.72

- 26.54

-50%

0%

50%

100%

Chamba Kangra Kinnaur

P e

r c

e n

t a

g e

( %

)

expansion (85.67%). The yield factor contributed only 14.33 per cent towards the total

crease in apple output. This may be due to the better management and adoption of new

farm technology. Yield effect was more pronounced in Kangra, Mandi, Solan and Sirmaur

districts of the state. In Lahaul & Spiti and Shimla districts, increase in apple pro

almost equally shared by yield and area. Production of apple increased by 305.72 and 104.96

per cent due to increase in acreage in Chamba and Kullu districts respectively and the

corresponding effects of yield in these districts, decreased the production by 205.72 and 4.96

Contribution of Yield and Area in the production of Apples in different

districts of Himachal Pradesh, 1973-74 to 2011-12

Percentage contribution due to

Yield Area

-205.72 305.72

126.54 -26.54

20.27 79.73

-4.96 104.96

Lahaul & Spiti 49.99 50.01

489.05 -389.05

53.90 46.10

71.61 28.39

118.38 -18.38

Himachal Pradesh 14.33 85.67

DOH, Shimla

Fig.8 Percentage contribution due to yield & area in production

As exposited in Table 4.8, at all India level, the contribution of yield towards the

growth of production was estimated at 52 per cent, while area shared 48 per cent towards

production. For the Asia as a whole, increase in apple area contributed more than

20.27 - 4.96 49.99

489.05

53.90 71.61

79.73104.96

50.01

- 389.05

46.10 28.39

Kinnaur Kullu Lahul &

Spiti

Mandi Shimla Solan

<< Apple districts of Himachal Pradesh >>

Yield Area

expansion (85.67%). The yield factor contributed only 14.33 per cent towards the total

crease in apple output. This may be due to the better management and adoption of new

farm technology. Yield effect was more pronounced in Kangra, Mandi, Solan and Sirmaur

districts of the state. In Lahaul & Spiti and Shimla districts, increase in apple production was

almost equally shared by yield and area. Production of apple increased by 305.72 and 104.96

per cent due to increase in acreage in Chamba and Kullu districts respectively and the

production by 205.72 and 4.96

Contribution of Yield and Area in the production of Apples in different

Fig.8 Percentage contribution due to yield & area in production

As exposited in Table 4.8, at all India level, the contribution of yield towards the

growth of production was estimated at 52 per cent, while area shared 48 per cent towards

production. For the Asia as a whole, increase in apple area contributed more than

118.38

- 18.38

Solan Sirmour

53

the productivity. In the total world production of apples, the contribution of yield was 53.84

per cent and that of area it was 46.16 per cent.

Table 4.8 Contribution of Yield and Area in the production of Apples in different

Regions, 1973-74 to 2011-12

Region Per cent age contribution due to

Yield Area

India 52.00 48.00

Asia 40.51 59.49

World 53.84 46.16

Source: FAO, 2013

4.2 BACKGROUND OF THE STUDY AREA

Shimla district is the major district of Himachal Pradesh, which falls under the

western Himalayan region of India that makes itself a verily-suitable agroclimatic zone for

apple farming. This district lies between the longitude 77.00’’ and 78.19’’ east and latitude

30.45’’ and 31.44’’ north. It is surrounded by Mandi and Kullu in the north, Kinnaur in the

east, Solan in the southwest and Sirmaur in the south. The elevation of the district ranges

from 300 m to 6000 m above mean sea level. It is the third most populous and most

urbanized district of the state having an area of 5131 sq.kms. Agriculture and horticulture are

the prime economic activities of this district. Horticulture has proved to be major source of

cash crop in the district. The district has earned a place of pride to the state of Himachal

Pradesh in the production of apples and as a result, the state is known as the "Apple State of

India”. Besides, tourism industry has also developed substantially in the district because of

the topography and scenic beauty it contains.

To explain the present study in a feasible manner, Narkanda block has been selected

randomly amongst all other blocks of the district. Further details of Narkanda block is

explained in brief as the following.

Location and Climate

District Shimla is comprised of ten development blocks, out of which Narkanda block

happens to be one of the influential block. This block lies between 3108’40’’ to 31042’50’’ N

latitude and 72018’50’’ to 77058’0’’ E longitudes. The elevation varies from 1100 m to 3000 m

above sea level with an average elevation of 2621 meters. The mean rainfall of the area is

54

about 1272 mm. Though climate of this block during summers is pleasant, yet the

temperature during winter falls to around freezing points. Snowfall occurs during winter

months.

Area The total geographical area of the block is 23791 hectares, out of which, the net sown

area comprises of 24.40 per cent, area under forests 28.40 per cent, cultivable waste 40.35 per

cent, and area not available for cultivation is 6.85 per cent. Irrigated area comprises of 3.26

per cent of the net sown area in the block.

Apple orchard characteristics in Narkanda Block

Narkanda block with 5373.91 hectares area under apple plantation was first block in

Shimla district where apple plantation was introduced hence most orchards have dense or

moderately dense canopy. The important belts are Kotgarh, Thanadhar, Saroga, Barobagh,

Pamlahi, Bhareridhar, Nankhari, Kumarsain, Bhutti, Khaneti etc. As a whole, the block

comprises of 14.28 per cent of Apple area of the district. More than 55 per cent of the apple

belt in Narkanda is moderately planted and densely planted area accounted for 42.31 per cent,

remaining being sparsely planted (1.81 %). Mainly 78.6 per cent of the apple plantation of the

block is concentrated in the altitudinal zone ranging 1500-2500 m above mean sea level,

followed by 15.9 per cent apple plantation in the 2500-3000 m, ≤1500 m (4.2 %) and the

least area falling in ≥3000 m (1.1 %) above mean sea level. More than half of the Apple area

in the block (in relation to aspect) was found in the NE + SE (56.1 %) and the rest lied in NW

+ SW aspect (42.6 %) particularly. Maximum proportion of apple area in the block falls in

the slope ranging from 200-400 (38.40 per cent), followed by 100-200 (25.0 per cent), 300-400

(23.20 per cent) more than 400 (9.1 per cent) and less than 100 comprise of only 4.3 per cent

of the total apple area in the selected block (Table 4.9).

Population

According to 2001 census, the total population of the block is 39864 constituting 5.52

per cent of the district population. Male population comprises of 51 per cent and the rest are

females. The density of population of the block is 167 persons per square kilometer. The

proportion of scheduled caste population accounts for 30.52 per cent and that of scheduled

tribes 0.21 per cent. About 98 per cent of the population in the block resides in 186 villages

administered through 26 panchayats and mainly depends on horticulture for their livelihood.

55

The average size of the family in the block is 4.60 persons as against 4.67 in Shimla district.

The proportion of the literate persons in the block is 71.02 per cent of the total population.

Female literates constituted for about 43.64 per cent of the total literates. The percentage of

the cultivators to the total workers in the block is 38.26 per cent.

Table 4.9 Area (in ha) under different categories of apple in Narkanda block of Shimla

district, 2006

S.No Particulars Area (ha) Percentage

1 Apple area in Narkanda block 5393.10 14.28*

2 Types in density of plantation

a) Sparse 97.57 1.82

b) Moderate 3002.63 55.88

c) Dense 2273.7 42.32

3 Area in relation to elevation (m amsl)

a) ≤ 1500 226.48 4.2

b) 1500 - 2000 1705.82 31.7

c) 2000 - 2500 2520.75 46.9

d) 2500 - 3000 852.19 15.9

e) ≥ 3000 57.6 1.1

4 Area in relation to aspect

South - East 1842.68 -34.3

North - East 1172.68 21.8

South - West 977.13 18.2

North - West 1311.9 24.4

5 Area in relation to slope

a) ≤ 10

0 229.71 4.3

b)100 – 200 1345.65 25

c) 200 – 300 2063.29 38.4

d)300 – 400 1247.27 23.2

e) ≥ 40

0 488.51 9.1

Source: Himachal Pradesh Remote Sensing Cell State Council for Science, Technology & Environment,

Shimla Note: * - denotes the percent area in the block out of total apple area in the district m amsl – meters above

mean sea level

56

4. 3 SOCIO-ECONOMIC CHARACTERISTICS OF SAMPLE ORCHARDISTS The study of socio-economic status helps in identifying the adaptive capacity of the

individuals or communities based on the characteristics like education, economic status,

gender, experience, training undergone, access to information etc., and play a vital role in

understanding their mode of farming in a keen manner. In this section, an attempt has been

made to highlight the socio economic characteristics of the study area on the basis of the

primary data.

4.3.1 Type and size of family: The type and size of the family, work force and literacy among the apple growers are

the essential components influencing the apple crop enterprise, which happens to be family

labour-based occupation at the village level. These factors ascertain the socio-economic

prosperity of the family in particular and the area in general. It plays a critical part in the farm

business activities. The type and size of sample family in the study area has been presented in

Table 4.10. As expounded in the table, the average family size in pooled elevation comprises

of 6.56 persons, out of which 56.86 per cent are males and rest being females in the study

area. On an average, the family size ranged from 5.64 to 7.86 in different altitudinal zones.

Highest sex ratio was found in E3 elevation and lowest of 673.47 in E 1 elevation while under

pooled condition, it was 834.78. Among the sampled farm families there were 67.14 per cent

nuclear families and rest were joint families.

Table 4.10 Type & Size of the family & male /female divide in the study area, 2012-13

S.No Particulars Elevations

E 1 E 2 E 3 E 4 E 5 Pooled

1 No. of House Holds 14 14 14 14 14 70

2 No. of Males 3.57

(63.29) 4.5

(57.27) 3.43

(53.93) 3.43

(56.47) 3.72

(54.17) 3.73

(56.86)

3 No. Females 2.07

(36.71) 3.36

(42.73) 2.93

(46.07) 2.64

(43.53 3.14

(45.83) 2.83

(43.14)

4 Average Family Size 5.64 7.86 6.36 6.07 6.86 6.56

5 Type of Family

a)Joint

2 (14.29)

7 (50.00)

5 (35.71)

3 (21.43)

6 (42.86)

23 (32.86)

b)Nuclear

12 (85.71)

7 (50.00)

9 (64.29)

11 (78.57)

8 (57.14)

47 (67.14)

7 Sex ratio 673.47 803.74 961.9 850 879.76 834.78

Note: Figures in parentheses indicate percentage to the total population in each case

57

4.3.2 Age composition

Socio-economic transformation and adoption of innovations are greatly influenced by

the age, particularly that of the decision maker. The age of head of family has important role

to play in responding to a change. Keeping this in view, based on the age, the distribution of

male/female divide in farm families of different altitudinal zones of sample farms has been

analyzed and the results are presented in Table 4.11. The perusal of the table shows that, at

overall level, in Narkanda block, maximum proportion of the average family falls in the age

group of 18-60 years (69.51 %), followed by greater than 60 years (10.82 %), 6-18 years

(10.56 %), and less than 6 years (9.15 %). The corresponding figures for male population on

average situation worked out to 71.31, 8.58, 11.26 and 8.85 per cent in the study area. The

proportion of female members was found relatively more in the age group of more than 60

years and less than 6 years, and the reverse was true for the male population for the age group

of 18-60 years and 6-18 years. The table is self-explanatory to explain the age wise and

elevation wise breakup of the sampled family members.

Fig. 9 Gender split of farm families (study sample) based on age groups, 2012-13

57.1462.50 57.89

46.00

42.8637.50 40.87

54.00

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

≤6 yrs 6-18 yrs 18-60 yrs ≥60 yrs

P e

r c

e n

t a

g e

( %

)

<< A g e g r o u p s >>

Females (%) Males (%)

58

Table 4.11 Distribution of family members according to the age group of the sampled orchards in the study area, 2012-13

Age

group

(Years)

Elevations

E 1 E 2 E 3 E 4 E 5 Pooled

M F T M F T M F T M F T M F T M F T

≤ 6 0.54

(15.22) 0.24

(11.59) 0.78

(13.83) 0.28

(6.22) 0.37

(11.07) 0.65

(8.27) 0.38

(11.08) 0.28

(11.08) 0.64

(10.06) 0.36

(10.50) 0.14

(5.30) 0.50

(8.24) 0.14

(3.70) 0.29

(66.67) 0.43

(6.27) 0.33

(8.85) 0.27

(9.54) 0.60

(9.15)

6 - 18 0.20 (5.60) 0.08

(3.86) 0.28

(4.96) 0.57

(12.67) 0.43

(12.80) 1.00

(12.72) 0.38

(11.08) 0.34

(11.60) 0.72

(11.32) 0.28

(8.16) 0.22

(8.33) 0.50

(8.24) 0.65

(17.47) 0.28

(8.92) 0.93

(13.56) 0.42

(11.25) 0.27

(9.54) 0.69

(10.52)

18 - 60 2.50

(70.03) 1.43

(69.08) 3.93

(69.68) 3.30

(73.33) 2.13

(63.39) 5.43

(69.08) 2.45

(71.43) 1.91

(65.19) 4.36

(68.56) 2.50

(72.89) 1.93

(73.10) 4.43

(72.98) 2.50

(67.20) 2.14

(68.15) 4.64

(67.64) 2.66

(71.31) 1.90

(67.14) 4.56

(69.51)

≥ 60 0.33

(9.24) 0.32

(15.46) 0.65

(11.52) 0.35

(7.78) 0.43

(12.80) 0.78

(9.92) 0.22

(6.41) 0.42

(14.33) 0.64

(10.06) 0.29

(8.45) 0.35

(13.25) 0.64

(10.54) 0.43

(11.56) 0.43

(13.69) 0.86

(12.54) 0.32

(8.58) 0.39

(13.78) 0.72

(10.82)

Total 3.57

(100.00) 2.07

(100.00) 5.64

(100.00) 4.50

(100.00) 3.36

(100.00) 7.86

(100.00) 3.43

(100.00) 2.93

(100.00) 6.36

(100.00) 3.43

(100.00) 2.64

(100.00) 6.07

(100.00) 3.72

(100.00) 3.14

(100.00) 6.86

(100.00) 3.73

(100.00) 2.83

(100.00) 6.56

(100.00)

Note: Figures in parentheses indicate percentages to the total population in each case

M - denotes male, F - denotes female, T - denotes total

59

4.3.3 Marital Status The marital status of family members of sample orchards has been presented in Table

4.12. It can be noticed from the table that nearly 50.11 per cent of all the farm population were

married. The proportion of married members was highest in E1 elevation (58.23 %) and lowest in

E3 elevation. The proportion of widows/widowers comprise of 6.32 per cent on average situation,

which it varied from 4.55 per cent (E2 elevation) to 7.29 per cent of total family in E5 elevation

zone orchardists.

Table 4.12 Marital Status of Family Members in the Study Area, 2012-13 (Percentage)

Sr.

No Particulars

Elevations

E 1 E 2 E 3 E 4 E 5 Pooled

1 Married 58.23 47.27 49.44 51.76 45.83 50.11

2 Unmarried 35.44 48.18 42.70 42.35 46.88 43.57

3 Widow/Widower 6.33 4.55 7.87 5.88 7.29 6.32

Total 5.64

(100.00) 7.86

(100.00) 6.36

(100.00) 6.07

(100.00) 6.80

(100.00) 6.56

(100.00)

4.3.4 Work force

The economy of households depends on strength of active farm workers. Apple being

labour intensive activity depends on the workforce available in the family. Working class of the

families earns bread and butter of the family. They shoulder responsibilities and are held

responsible for the well-being of the whole family. The number of workers and non-workers in

the sampled households of study area are given in Table 4.13. The perusal of the table shows that

on an average 4.57 are workers out of 6.56 members of the family are available on an average in

the study area, out of which 68.12 per cent are males and 31.88 per cent constitute female

workers. The trends in male and female workers are almost similar in each elevation zone, that is

male workers are overtaking the female workers. Of the total number of workers, at overall level,

the number of workers actually engaged in apple farming comprise of 69.15 per cent. This

number was highest in lowest elevation followed by highest elevation (E5) and E2, E2 and E3

elevation orchards. At pooled level, the dependency ratio worked out to 0.44, which indicates

that an average worker has to support less than a person. Dependency ratio varied from 0.31 in

E 1 elevation to 0.53 in E2 elevation in the study area.

60

Table 4.13 Distribution of workers and non- workers on sampled orchards in the study

area, 2012-13

(2012-13)

Sr. No. Particulars Elevations

E 1 E 2 E 3 E 4 E 5 Pooled

1 Family size 5.64 7.86 6.36 6.07 6.86 6.56

2 No of workers 4.29 5.14 4.50 4.21 4.71 4.57

3

(a) Males 3.07

(71.67) 3.57

(69.44) 3.07

(68.25) 2.79

(66.10) 3.07

(65.15)

3.11

(68.12)

(b) Females 1.21

(28.33) 1.57

(30.56) 1.43

(31.75) 1.43

(33.90) 1.64

(34.85)

1.46

(31.88)

4

No. of workers

actually engaged in

farming

3.21 (74.82)

3.57 (69.45)

2.93 (65.11)

2.64 (62.70)

3.43 (72.82)

3.16

(69.15)

5 Dependency Ratio 0.31 0.53 0.41 0.44 0.46 0.44

Note: Figures in parentheses indicate percentage to respective total

4.3.5 Literacy status

The education is an important ingredient in the development process. This is true in the

farming as well. The literate persons are better placed to perceive and adopt new technology than

illiterates. Therefore, the study of educational status of the family gains importance. It was with

this importance in mind the educational status of sampled orchardists was analysed and

presented in Table 4.14.

The cursory glance on the table revealed that, on an average, nearly 90 per cent of

family members are literates. Across the elevations, there was not much difference, in the

literacy rates among the orchardists’ family members. It is very heartening to note that, in the

study area, the proportion of family members having higher education (i.e., graduates and

postgraduates) comprised of 52.28 per cent while the persons with secondary education

accounted for 17.86 per cent at overall level. The members having matriculation, middle and

primary education accounted for 8.28, 7.41 and 3.70 per cent of total population respectively.

There are more or less similar trends across the elevation zones as far as levels of education is

concerned as can be evidenced from the table. Attempt was also made to work out the literacy

index of orchardists in each elevation zone and it worked out to 1.39 at overall level. Literacy

index was found highest (1.61) in E2 elevation followed by E5 elevation (1.44), E3 (1.22) and

lowest of 1.14 in lowest elevation zone.

61

Table 4.14 Literacy statuses of the family members in various sample apple orchard farms,

2012-13

Sr. No Particulars Score Elevations

E 1 E 2 E 3 E 4 E 5 Pooled

1 Non School going 0 0.43

(7.59) 0.50

(6.36) 0.64

(10.11) 0.43

(7.06) 0.43

(6.25) 0.49

(7.41)

2 Illiterate 0 0.14

(2.53) 0.07

(0.91) 0.07

(1.12) 0.36

(5.88) 0.36

(5.21) 0.20

(3.05)

3 Primary 1 0.14

(2.53) 0.64

(8.18) 0.07

(1.12) 0.14

(2.35) 0.21

(3.31) 0.24

(3.70)

4 Middle 2 0.43

(7.59) 0.64

(8.18) 0.64

(10.11) 0.36

(5.88) 0.36

(5.21) 0.49

(7.41)

5 Matriculation 3 0.29

(5.06) 0.86

(10.91) 0.57

(8.99) 0.29

(4.71) 0.71

(10.42) 0.54

(8.28)

6 Senior Secondary 4 1.21

(21.52) 1.29

(16.36) 0.93

(14.61) 1.29

(21.18) 1.14

(16.67) 1.17

(17.86)

7 Graduate 5 2.00

(35.44) 2.07

(26.36) 1.93

(30.34) 2.00

(32.94) 2.22

(32.29) 2.04

(31.15)

8 Post Graduate 6 1.00

(17.72) 1.79

(22.73) 1.50

(23.60) 1.21

(20.00) 1.43

(20.83) 1.39

(21.13)

9 Total 21 5.64

(100.00) 7.86

(100.00) 6.36

(100.00) 6.07

(100.00) 6.86

(100.00) 6.56

(100.00)

11 Literacy rate - 90.40 91.57 89.67 88.63 89.48 89.95

12 Literacy Index - 1.14 1.61 1.34 1.22 1.44 1.39

Note: Figures in parentheses indicate percentages to total

Fig.10 Literacy status of the farm families of the study sample (Percentage), 2012-13

3.05% 3.70%

7.41%

7.41%

8.28%

17.86%21.13%

31.15%

Illiterate

Primary

Non School going

Middle

Matriculation

Sr.Sec

Post Graduate

Graduate

62

4.3.6 Occupational distribution

Occupational distribution of the head and other members of the family are very crucial in

determining the status of the household class. It is presumed that more developed is the area, the

more diversified the employment pattern and it would result in increased income to the family.

Generally, in hilly terrains there are few avenues other than farming, so the Hilly people are

always in search of alternative sources of income to enhance the economic status of the home. It

is exposited in the Table 4.15 that horticulture is the main occupation of the people of Study area

as nearly 70.31 per cent of the work force practice farming. Next significant occupation in the

study area is the service comprising in public / private sectors nearly 26 per cent of total work

force. On an average 3.75 per cent of the total family workforce were engaged in business

activity.

Table 4.15 Main and Subsidiary occupation of the family members in the study region,

2012-13

Particulars Elevations

E 1 E 2 E 3 E 4 E 5 Pooled

Main occupations

1 Agriculture 45

(75.00)

50

(69.44)

41

(65.08)

41

(69.49)

48

(72.73)

225

(70.31)

2 Service 12

(20.00)

20

(27.78)

20

(31.75)

15

(25.42)

16

(24.24)

83

(25.94)

3 Business 3

(5.00)

2

(2.78)

2

(3.17)

3

(5.08)

2

(3.03)

12

(3.75)

Subsidiary occupation

4 Agriculture 10

(16.67)

8

(11.11)

11

(17.46)

9

(15.25)

12

(18.18)

50

(15.63)

5 Business 4

(6.67)

1

(1.39)

2

(3.17)

1

(1.69)

5

(7.58)

13

(4.06)

Total work force 60

(100)

72

(100)

63

(100)

59

(100)

66

(100)

320

(100)

Note: Figures in parentheses indicate percentages to total work force in each elevation

The percentage of agriculture, business as their ancillary occupation was 15.63 & 4.06

per cent respectively among the working sum of the people.

63

Fig. 11 Primary occupation by major sectors in the study sample, 2012 -13

4.4 EXISTING RESOURCE STRUCTURE

This section deals with the existing resource structure like land, labour, management,

farm investments etc. Elevation wise results in different aspects are given below.

4.4.1 Land

Land is a basic resource in the agrarian economy. Size of land holding is a focal variable

which directly affects the income, expenditure, saving and investment of land owning

households. In Narkanda study block where the bulk of holdings are small, land holding occupies

a special status in determining the income generation opportunities in rural areas. An

investigation of the pattern of land holdings thus, attains significance not only from the point of

rural economy but also from the overall welfare stance.

Elevation wise distribution of land holding of apple growing sampled farmers of the

study area is summarized in Table 4.16. The average size of land holding was worked out to 1.28

5

3

3

5

3

4

20

28

32

25

24

26

75

69

65

69

73

70

0 20 40 60 80

E 1

E 2

E 3

E 4

E 5

Pooled

<< Percentage ( % ) >>

<<

E l

e v

a t

i o

n

z o

n e

s >

>

Agriculture

Service

Business

64

hectares for the study area as a whole. The holding size of orchardists was ranging between 0.88

hectares (E5 elevation) and 1.56 hectares in (E4 elevation). Of the total holding, at overall level

operational holding constituted more than 97 per cent, while the area under grasslands comprised

of above 2 per cent of total holding respectively. Almost similar trends were observed across the

altitudinal zones also. Fruit orchards occupied the largest share of total land holding in the study

area, comprising of 97.78 per cent of the total area.

Table 4.16 Land use pattern of sampled apple growers in the study area, 2012-13

Sr.

No. L U C*

Elevations

E 1 E 2 E 3 E 4 E 5 Pooled

1 Orchard land 0.95

(98.54)

1.37

(96.32)

1.44

(98.12)

1.49

(97.60)

0.86

(98.31)

1.22

(97.78)

2 Grass land/

Forests

0.01

(1.46)

0.13

(3.68)

0.03

(1.88)

0.08

(2.40)

0.02

(1.69)

0.05

(2.22)

Total 0.96

(100.00) 1.50

(100.00) 1.47

(100.00) 1.56

(100.00) 0.88

(100.00) 1.28

(100.00)

Note: Figures in parentheses indicate percentage to respective total

LUC* - Denotes Land Use class

4.4.2 Cropping pattern:

Cropping pattern in any region depends mainly on soil, altitude, microclimate,

accessibility of resources and management factors. The per cent share of area under different

crops in the gross cropped area reveals the extent of diversification in sampled farms. A scrutiny

of the cropping pattern suggests the status of agriculture in the area. A look at the proportional

share of a particular crop in gross cropped area on the farm suggests the significance that the

farmer attaches to a particular crop. This importance can be of both economic nature as well as

social considerations on the part of the farmer. Cropping pattern of sampled farms was examined

and results are discussed in Table 4.17. It is evidenced from the table that apple is occupying the

place of pride sharing 89.43per cent of the gross cropped area in the study area at an overall

level. Of the gross cropped area, the area under apple was lowest (58.94 %) in E 1 elevation and

highest in E3 elevation (97.22 %). The other fruits like pear, apricot, cherry, almonds and plums

occupied largest proportion of gross cropped area in lowest elevation while it was lowest of 2.78

per cent in E3 elevation zone in the study area.

65

Table: 4.17 Average area under different crops on different altitudinal zones of farm in

the study area, 2012-13

Sr. No. Category/

Crops

Elevations

E 1 E 2 E 3 E 4 E 5 Pooled

1 Apple 0.56

(58.94) 1.28

(93.43) 1.40

(97.22) 1.40

(93.96) 0.84

(97.67) 1.10

(89.43)

2 Other fruits 0.39

(41.06)

0.09

(6.57)

0.04

(2.78)

0.09

(6.04)

0.02

(2.33)

0.13 (10.57)

Gross cropped

Area (ha.)

0.95

(100.00)

1.37

(100.00)

1.44

(100.00)

1.49

(100.00)

0.86

(100.00)

1.23

(100.00)

Note: Figures in parentheses indicate percentage of total area in hectares.

4.4.3 Number of plants under Horticultural crops

The details of average number of bearing and non-bearing plants per orchard owned by

orchardists of different elevations are placed in Table 4.18. The average orchardists in the study

area have a mix of 419 plants of which 21 per cent comprise non-bearing plants. At overall level

of the total number of plants, apple dominated the whole scenario accounting for 83 per cent,

followed by cherry (4.34 per cent), almond (4.29 per cent); pear (3.91 per cent), apricot and plum

each constitute 2.15 per cent per farm. The per hectare total number of plants established by

orchardists in E1, E2, E3 , E4, E5 elevations comes to nearly 384, 328, 322, 342 and 349 plants

respectively. The proportion of non-bearing plants are highest in E2 elevation followed by E3, E4,

E5 and E 1 elevation. In case of apples, at overall level, the proportion of non-bearing plants

comes to 25 per cent. The number of non-bearing plants is highest in E2 elevation, followed by

E4, E3 and E1 elevation orchards. Amongst bearing apple plants, Royal Delicious variety plants

were in more than 90 per cent, followed by Golden Delicious and spur varieties.

Table: 4.18 Average number of Bearing and Non-bearing plants of apple in the study area,

2012-13

Elevation Orchard

Area (Ha)

Number of Bearing & non Bearing Plants

Apple Pear cherry Apricot Plum Almond Total plants

B NB B NB B NB B NB B NB B NB B NB Total

E 1 0.95 178 32 9 0 0 0 24 0 32 0 90 0 333 32 365

E 2 1.38 274 124 22 2 26 1 4 0 0 0 0 0 326 127 453

E 3 1.44 306 112 20 0 19 0 3 0 4 0 0 0 352 112 464

E 4 1.49 330 114 19 0 33 0 8 0 6 0 0 0 396 114 510

E 5 0.87 218 54 11 0 14 0 4 0 3 0 0 0 250 54 304

Pooled 1.22 261 87 16 0 18 0 9 0 9 0 18 0 331 88 419

Note: NB - Denotes non- bearing plants B - Denotes bearing plants

66

4.4.4 Livestock Livestock rearing is an integral part of farming system in the hilly states. Not only they

produce milk directly, they also provide key inputs to agriculture and are source of energy for

farm operations. The orchards in the study area are situated in too steep terrains and justifying

not owning or using a tractor and the alternatives are animal power or human labour. These

livestock become a crucial link in nutrient cycle, returning nutrients to the soil in forms that

plants can readily use. They can bring nutrients from pasture, range land, and concentrate them

on cropland through their waste. It is a good supplementary source of income for the orchardists.

The productivity of apple orchards is greatly affected by the use of farmyard manure.

From time immemorial, India has been an agrarian country and the cow has been the

backbone of our agriculture. When fertilizers and tractors were unknown, cow was the only

source sustaining the entire agriculture. Agriculture would not have been possible without cows.

Cow is the base of economic sustainable agriculture with positive impact on environment.

Table 4.19 Average Number of livestock on different elevations of farms in the study area,

2012-13

(Number)

S.No Livestock

Elevations

E 1 E 2 E 3 E 4 E 5 Pooled

1 Cows 0.58

(58.00)

0.87

(57.61)

0.73 (56.15)

1.08 (57.75)

0.66 (56.90)

0.77 (56.62)

2 Dry 0.15

(15.00) 0.15

(9.93) 0.15

(11.54) 0.22

(11.76)

0.08

(6.90)

0.14 (10.29)

3 Milch 0.43

(43.00) 0.72

(47.68) 0.58

(44.62) 0.86

(45.99) 0.58

(50.00) 0.63

(46.32)

4 Young Stock 0.43

(42.00) 0.64

(42.39) 0.57

(43.85) 0.79

(42.25) 0.50

(43.10) 0.59

(43.38)

Total 1.00

(100.00)

1.51 (100.00)

1.30 (100.00)

1.87 (100.00)

1.16 (100.00)

1.36 (100.00)

Note: Figures in the parentheses refers to their respective total

The detailed view of different types of livestock being kept on different categories of

selected farms is presented by the data given in Table 4.19. One of the significant features of the

table is that all the livestock were cows. It is noticed that the livestock rearing is reduced due to

labour shortage and lack of interest among the farming communities in animal husbandry. Low

availability of per capita land, substantial availability of common property resources, and lack of

67

other income generating activities compels the farmers to rear less number of animals. The table

reveals that, cows are most preferred farm animals in the study area. On an average, the livestock

population on the sampled apple farms in Himachal Pradesh was 1.36. Cows dominate the whole

scenario in livestock population in the study area. At overall level, more than 46 per cent of the

cows were in milch condition. The young stock accounted for 43.38 per cent of total livestock

holding. This analysis across the elevation reveals almost similar pattern in milch and dry cows.

This data reveals that there were many farm families without livestock in the study region.

4.4.5 Level of investment on implements In apple farming, farmers make investment on different mechanical equipments because

these implements and equipments make the farming activity easier to perform. They invest on

residential houses, storehouses, polyhouses, power tillers, sprayers, electric motor, baskets,

pruning scissors, plastic pipes, etc. Different farmers make different levels of investment on

different items and farmers vary in their total investment on different items depending upon their

requirement, ability, capital constraints and many other factors etc. In this study, an attempt has

been made to examine level of investment on different implements and tools and their share in

total investment.

Table 4.20 shows the detailed per farm average investment particularly on the farm

implements of the sampled orchards of the study area. It has been observed that the major

spending on the farm implements was for the sprayers, which ranged from T 9,725 in E1

elevation to T 15,336 in E2 elevation with corresponding percentages of 39.78 and 53.19 in the

total investment. On an average, the orchardists of study area spent T 12,669 on spraying

machines, which comes to 46.54 per cent of total farm investment. In the matter of farm

investments next in importance were plastic kilta and plastic crates accounting 9.18 per cent each

in the total investment. Across the elevation zones, investment was highest of T 2818 each in E1

elevation and lowest of T 2286 each in E2 elevation. The third important item of investment

includes wooden baskets/ kiltas obviously used for harvesting and carriage of apple, constituted

5.49 per cent of total investment at overall level. This investment ranged between 4.71 in E3

elevation and 6.84 per cent in E1 elevation. The table shows that an average orchardist spent

4.60, 4.18, 3.78 and 3.77 per cent of total investment on pipes, ladders, pruning scissors and

grafting knives respectively. The remaining items of farm investments together comprise of

10.03 per cent at an overall level in the study area.

68

Table 4.20 Average investment per farm on different farm implements in different

elevation zones of the study area, 2012-13 (TTTT/Farm)

Particulars

Elevations

E 1 E 2 E 3 E 4 E 5 Pooled

TTTT % TTTT % TTTT % TTTT % TTTT % TTTT %

Traditional Plough 100 0.41 207 0.72 225 0.77 164 0.56 200 0.83 179 0.66

Sprayer 9725 39.78 15336 53.19 15046 51.70 13693 46.41 9546 39.39 12669 46.54

Pruning Scissors 871 3.56 879 3.05 896 3.08 1371 4.65 1129 4.66 1029 3.78

Saw 293 1.20 364 1.26 275 0.94 414 1.40 393 1.62 348 1.28

Shovels (Phawda) 261 1.07 246 0.85 229 0.79 250 0.85 225 0.93 242 0.89

Pickaxe(Gainti) 750 3.07 1000 3.47 964 3.31 964 3.27 750 3.09 886 3.25

Axe (Khulhadi 686 2.80 657 2.28 571 1.96 571 1.94 514 2.12 600 2.20

Hoe 251 1.03 240 0.83 229 0.79 240 0.81 229 0.94 238 0.87

Tooth Rake 236 0.96 225 0.78 214 0.74 225 0.76 214 0.88 223 0.82

Machetes (Darrat) 300 1.23 284 0.98 336 1.15 382 1.30 314 1.30 323 1.19

Sickle 126 0.51 120 0.42 114 0.39 120 0.41 114 0.47 119 0.44

Spade(Khurpi) 471 1.93 514 1.78 429 1.47 450 1.53 429 1.77 459 1.68

Grafting Knives 1007 4.12 893 3.10 1015 3.49 1150 3.90 1064 4.39 1026 3.77

Basket / Kiltas 1671 6.84 1371 4.76 1371 4.71 1500 5.08 1564 6.45 1496 5.49

Plastic Kiltas 2818 11.53 2286 7.93 2286 7.85 2500 8.47 2607 10.76 2499 9.18

Plastic Crates 2818 11.53 2286 7.93 2286 7.85 2500 8.47 2607 10.76 2499 9.18

Ladders 1064 4.35 950 3.30 1186 4.07 1364 4.62 1121 4.63 1137 4.18

Pipes 1000 4.09 971 3.37 1429 4.91 1643 5.57 1214 5.01 1251 4.60

Total Investment (TTTT) 24449 100.00 28830 100.00 29101 100.00 29503 100.00 24236 100.00 27224 100.00

4.4.6 Management

In practice, management is a continuous process through observing and conceiving ideas.

It covers all aspects of farm business that have a bearing on the economic efficiency of a farm.

Solutions of economic problems faced by farmers are generally facilitated through recording of

data related to farm. Management plays an important role in agricultural production in cohesion

with other resources. Through the improvement in agriculture technology, farming has gone

beyond its framework of just providing the necessities of life to the farm family. Not only the

farmer now produces to meet family subsistence needs, but at the same time endeavours to

produce maximum marketable surplus. This has made agricultural production market oriented

and introduced business content in the farming profession. The management resource itself is

very much responsible to achieve the objectives of professionalism. Attempt has been made in

69

this section to measure the managerial ability of the orchardists in the study area through a

special index termed as managerial skill index.

(a) Management skill index of study area

At overall level, the detailed distribution of orchardists and average value of managerial

skill index (MSI) is shown in Table 4.21. It was observed from the table that maximum number

of orchardists (52.86 %) were falling in the MSI range of 100-50 having average MSI of 83.99;

followed by 30 per cent orchardist in MSI range of 150-100 with average MSI of 124.65 and

11.43 per cent orchardists in MSI range of 200-150 with average MSI of 169.12 in the study

area. Only 5.71 per cent of the farmers were in the range of less than ≤ 50 MSI score having

average MSI of 49.02. When pooled, MSI ranged between 49.02 -176.47, with average MSI of

99.58.

Table: 4.21 Orchardists’ distribution and their average value of Management Skill

index (MSI) in the study area, 2012-13

Range of

MSI

Orchardists Range Average MSI SD

Number Percentage

200-150 8 11.43 156.86 - 176.47 169.12 3.59

150-100 21 30.00 117.65 - 147.06 124.65 11.66

100-50 37 52.86 58.82 - 98.04 83.99 16.27

≤ 50 4 5.71 49.02 49.02 0.00

Total 70 100.00 49.02 - 176.47 99.58 34.63

Fig. 12 Managerial Skill Index of the farmers (study sample), 2012-13

0.00

20.00

40.00

60.00

80.00

100.00

120.00

140.00

160.00

180.00

200.00

0 10 20 30 40 50 60 70 80

M S

I

v a

l u

e s

<< Number of Farmers >>

MSI Index

70

(b) Elevation wise Management skill index of the study area

In case of elevation wise orchards, the detailed distribution of orchardists and average

value of managerial skill index (MSI) is placed in Table 4.22. Table depicts that maximum

average MSI value of orchardists was in the E5 elevation (110.64) and minimum being in E1

elevation (98.04). E2, E3 and E4 elevation farmers had equal average MSI value (103.64).

Table: 4.22 Elevation wise Management skill index of study sample, 2011-12

Elevation Orchardists

Range Average MSI SD Number Percentage

E 1 14 20.00 49.02 - 156.86 98.04 37.88

E 2 14 20.00 49.02 - 156.86 103.64 37.63

E 3 14 20.00 49.02 - 176.47 103.64 36.82

E 4 14 20.00 49.02 - 176.47 103.64 32.57

E 5 14 20.00 58.82 - 156.86 110.64 31.81

Pooled 56 80.00 49.02 - 176.47 103.92 34.63

4.4.7 Elevation wise productivity Analysis

The statistical analysis of the productivity is done with precision. As enumerated in the

Table 4.23, it states that the productivity varied from 9.13 - 24.91 MT/ha in the pooled condition.

The mean productivity is worked out to 15.60 MT/ha and the standard deviation in the

productivity was noticed to be 3.17. This variance in the range of apple productivity is estimated

to be the act of the chokepoints like climatic variations. It is significant to note that the average

yield per hectare has positive relationship with the altitudinal range indicating thereby that

altitude play an important and positive role in increasing the productivity of the orchards. This

provides ample evidence to the fact that, altitude being a proxy for climatic factors in causing a

shift in apple farming towards higher elevation zones, which implies that in future all-out efforts

must be directed towards establishment of apple, in higher elevation zone to run the industry on

profitable lines.

71

Table 4.23 Elevation wise productivity Analysis

S.No Elevation Apple productivity (MT/ ha)

SD Minimum Maximum Mean

1 E 1 9.13 15.42 11.93 1.47

2 E 2 12.25 20.39 15.54 2.10

3 E 3 14.26 20.19 16.28 1.99

4 E 4 13.33 24.91 16.87 3.80

5 E 5 13.60 22.74 17.38 2.85

Pooled 9.13 24.91 15.60 3.17

Note: SD - denotes standard deviation

An argument may be contentious, but well thought out and researched line of reasoning

productivity analysis plays a pivotal role in helping plan in a defined manner for future

prosperity in the global stratum.

Table: 4.24 Productivity differences in different elevations

Altitudes Range (MT/Ha) Mean

(MT/ha)

C.V.

(%)

E 1 9.13 - 15.42 11.93 12.33

E 2 11.99 - 20.39 15.54 13.51

E 3 13.66 - 24.19 16.28 12.22

E 4 12.79 - 24.91 16.87 22.53

E 5 13.03 - 22.74 17.38 16.49

CD = 1.94

The mean values of productivities in different elevation zones have been presented in

Table 4.24. As shown in the table, the maximum mean productivity of 17.38 MT/ ha was

observed in E5 elevation. This elevation was statistically at par with E4 (16.87 MT/ ha), E3 (16.28

MT/ ha) and E2 (15.54 MT/ ha) elevations respectively. Whereas the minimum mean productivity

of 11.93 MT/ ha was observed in E1 elevation.

72

Fig.13 Mean productivities of different altitudinal zones

Therefore, it is observed that there is no major disparity among the productivities of

different altitudinal zones except between E 1 and other zones. As the mean productivity value in

E1 zone was noted to be 11.93 MT/ha, the mean productivity varied merely from 15.54 – 17.38

MT/ha among E2 – E5 elevations. The critical difference value was computed to 1.94 and there

was statistically no difference in the apple productivities of the orchards falling in E2, E3, E4 and

E5 elevation zones, which was less than the CD value (1.94). It is expected that the geographical

situation in the E1 zone is held responsible for the low productivity. The data heaves into an

ambiguous situation of thought that there has been an increasing clamor from the climate change

on the lower elevations. As a result, there is continuous slide in the productivity in lower

elevations.

4.4.8 Gross apple income structure

Distribution of households according to the income earned from apple farming by the

sample orchardists is depicted in Table 4.25. Majority of orchardists (55.71 per cent) are falling

in the income scale of T 2-5 lakhs; 24.29 per cent in the scale of T 5-10 lakhs; 14.29 per cent

orchardists in T ≥ 15 lakh scale and only 5.71 per cent of orchardists are earning income in the

range of T 10-15 lakhs per annum.

In E1 elevation, 71.42 per cent of orchardists were falling in an income scale of T 2-5

lakhs and remaining 28.58 per cent in the income range of T 5-10 lakhs per annum. The

orchardists in E2 elevation, were maximum in the earnings scale of 2-5 lakhs (42.86 %). Three

11.93 15.54 16.28 16.87 17.380

5

10

15

20

25

E 1 E 2 E 3 E 4 E 5

< P

r o

d u

c t

i v

i t

y

>

<< A l t i t u d i n a l z o n e s >>

73

(21.43 %) orchardists were falling each in T 5-10 lakh and T ≥15-lakh scale, the rest 14.28 per

cent orchardists were having earnings of T 10-15 lakhs per annum. Maximum number of

orchardists in E3 elevation were found in income scale of T 5-10 lakhs (42.85 %), followed by T

2-5 lakhs (28.58 %) and two each in T 10-15 and T ≥ 15 lakhs/ annum income scale. Half of the

orchards of E4 elevation had an income scale of T 2-5 lakhs, 28.58 per cent orchards were found

with earnings of T 5-10 lakhs and the remaining 14.28 per cent of them were falling in the

earning scale of T ≥ 15 lakhs/ annum. Nearly 78.57 per cent of the orchards of E5 elevation fall

in an income scale of 2-5 lakhs, followed by T ≥ 15 lakhs of income range in 14.28 per cent

orchards and the 7.14 per cent orchards within the income scale of T 5-10 lakhs per annum.

Table 4.25 Distribution of households according to the gross apple income structure in the

study region, 2012-13

GAI* (Lakh TTTT) E 1 E 2 E 3 E 4 E 5 Pooled

2 - 5 10

(71.42) 6

(42.86) 4

(28.58) 7

(50.00) 11

(78.57) 39

(55.71)

5 - 10 4

(28.58) 3

(21.43) 6

(42.85) 4

(28.58) 1

(7.14) 17

(24.29)

10 - 15 0 2

(14.28) 2

(14.28) 0 0

4 (5.71)

≥ 15 0 3

(21.43) 2

(14.28) 3

(21.42) 2

(14.28) 10

(14.29)

Total 14

(100.00) 14

(100.00) 14

(100.00) 14

(100.00) 14

(100.00) 70

(100.00)

* Gross Annual Income Slab Figures in parentheses indicate percentages to respective total

4.5 COST AND RETURNS STRUCTURE IN APPLE CULTIVATION The cost of cultivation is a subject of attention to a wide range of users of cost data and it

assumes particular importance in the area of planning. The efficacy of data on the cost of

cultivation of horticultural commodities for planning is appreciated as these data inform the

planners about the area where it is economical to produce various commodities and the regions

that would accordingly be most appropriate for the development of industries based on the

agricultural raw material. At the micro level, it enables the farm management experts to examine

the efficiency of the various cultivation practices and revise the crop planning by furnishing

information regarding their profitability. This facilitates the experts to make practical

recommendations for farm planning aimed at better allocation of existing resources and

introduction of improved agronomic practices that would increase the competence in apple

production.

74

Cost structure, output and returns from apple crop grown in study area have been

discussed under, cost of plantation, cost in maintaining the orchard in non-bearing stage and

expenditure incurred during bearing stage. The summation of cost incurred during initial

investment and non bearing stage is termed as establishment cost, from which annual amortized

established amount cost has been worked out.

For estimating the cost and returns estimates for apple crop, it has been assumed that:

i. First bearing starts from 9th year in the study area.

ii. The major operations and input requirement vary in different ages of the orchards,

therefore, average values have been taken as a whole

iii. Total economic life of the plantations is 40 years in the study area.

The analysis in this section has been divided into three parts.

a. Initial investment

b. Cost during non-bearing stage (other than plantation cost), and

c. Bearing stage costs

In apple, initial investment is quite heavy for reasons of the cost involved in land

development, digging of pits, application of manure and fertilizers and material cost. Growers

have to incur cost on maintenance for about 8 years without any returns. Farmers can take inter-

crop from the orchard up to 3rd year after which this practice becomes uneconomic due to

competition for nutrition and shade effects.

4.5.1 Cost structure during non- bearing years in Himachal Pradesh

a) Initial investment The information on initial investment was taken from those farmers who are doing new

plantations in place of old and senile plants and in areas lying vacant in their orchards in all the

elevation zones. The item-wise plantation cost incurred in the first year is presented in Table

4.26. It is imperative to examine the resource position of the growers before deciding to establish

an orchard. It is clear from the table that, apple orchardists in the study area incurred a total cost

of T 43,399.28 per hundred plants on an average in the first year of plantation. Labour

investment was around 21.46 per cent and cost incurred on material inputs averaged nearly 46.51

per cent of the total cost. Managerial cost and risk margin each accounted for 6.36 per cent of the

total cost. Rental value of land shared 10.43 per cent of the total cost at overall level.

75

Table 4.26 Initial costs of Apple Orchards (Per 100 Plants) in the study area

Particulars Unit Quantity Value ( TTTT ) Percentage

1 Labour Cost Man Days 46.58 9314.44 21.46

a) Family Man Days 9.46 1890.66 4.36

b) Hired Man Days 37.12 7423.78 17.11

2 Material Cost

a) Plant material Number 100 7114.25 16.39

b) FYM Kg 3250 11375.46 26.21

c) Fertilizer Kg 100 1699.00 3.91

3 Interest on WC TTTT @ 11.70 % of WC 1615.33 3.72

4 Risk Margin TTTT @10.00 % of WC 2761.25 6.36

5 Managerial Cost TTTT @10.00 % of WC 2761.25 6.36

6 Land Revenue TTTT - 39.71 0.09

7 Depreciation TTTT - 1485.70 3.42

8 Rental value of Land TTTT - 4525.00 10.43

9 Interest on Fixed Capital TTTT @ 11.70 % of WC 707.90 1.63

Total Variable Cost TTTT - 34750.32 80.07

Total Fixed Cost TTTT - 8648.96 19.93

Total Plantation Cost (TTTT) TTTT - 43399.28 100.00

b) Maintenance cost during non-bearing stage

Maintenance cost during non-bearing stage was estimated based on information collected

from orchardists from entire sample irrespective of elevation zones. This was possible because

the orchards in the study block are quite old and farmers are replacing old plants with new

plantations. Maintenance cost per hundred plants during non-bearing stage for various age

groups of apple plantation in Narkanda block is given in Table 4.27.

It is obvious from the table that the maintenance cost of non-bearing plants has a positive

relationship with age of plants. However, in case of labour, material and other costs no

perceptible pattern could be observed between plantation age and different costs during gestation

period. Total labour cost varied from 12.90 per cent in the 8th year to 18.43 per cent in 4th year.

Cost of hired labour ranged from 6.42 per cent in the eighth year to 8.53 per cent in third year. In

absolute terms, the cost of necessary critical inputs like fertilizer and plant protection increased

76

with increase in the age of plants. In percentage terms, the share of critical inputs together was

highest in sixth year and lowest in second year.

Table: 4.27 Maintenance cost of non - bearing apple per hundred apple plants in the

orchards of study area, 2012-13 (Percentage)

Particulars Age of plantation in years

2 3 4 5 6 7 8

1 Labour cost 18.39 17.54 18.43 17.15 16.56 14.98 12.90

a Family 10.69 9.01 10.22 9.03 8.30 7.51 6.44

b Hired 7.70 8.53 8.21 8.12 8.25 7.48 6.42

2 Manure 11.51 13.63 13.95 13.21 12.79 12.89 13.00

3 Fertilizer 3.29 3.73 4.21 4.73 4.72 4.51 4.95

4 Plant protection 3.51 3.71 3.81 4.08 4.45 4.50 4.00

5 Replacement cost 1.77 0.88 0.45 NA NA NA NA

6 Interest on working capital 1.63 1.78 1.79 1.76 1.77 1.72 1.66

7 Managerial cost 2.78 3.05 3.06 3.01 3.02 2.94 2.84

8 Risk margin 2.78 3.05 3.06 3.01 3.02 2.94 2.84

9 Land revenue 0.06 0.05 0.04 0.03 0.03 0.02 0.01

10 Depreciation 5.63 4.25 3.40 2.87 2.39 2.03 2.25

11 Rental value of owned land 20.32 17.73 14.13 11.81 9.63 8.13 7.48

12 Interest on fixed capital. 3.04 2.58 2.05 1.72 1.41 1.19 1.14

13 Interest on past establishment

cost 25.30 28.03 31.61 36.60 40.21 44.15 46.98

Total variable cost 34.97 38.36 38.55 37.93 38.02 36.97 35.70

Total fixed cost 65.03 61.64 61.45 62.07 61.98 63.03 64.30

Total cost ( T T T T ) 20073.94 26496.19 33298.53 39407.52 47328.41 55652.55 66161.74

As expected interest on working capital exhibited positive relationship, age of plants until

6th year then was decreased in last two years, while interest on fixed capital decreased with the

age of plants. Managerial cost and risk margins exhibited positive trends until fourth year;

thereafter-declining trend was noticed with age in this category of costs. The depreciation cost,

rental value of land and interest on fixed capital declined with the age of plants. The

proportion of interest on past establishment cost in the total cost exhibited positive

relationship with the age of plants during non-bearing years as the their values were ascending

from 25.30 per cent in 2nd year to 44.15 per cent in 8th year. The total variable cost during the

77

non-bearing years was found highest (38.55 %) in the fourth year and lowest in second year

(34.97 %). The total fixed cost during the non-bearing years was in the range of 61.45 per cent

(fourth year) and 65.03 per cent (second year).

Among the fixed costs, interest on establishment cost accounted for the maximum

proportion of the fixed costs in the study area. Next in importance was rental value of land whose

share in total cost ranged between 7.48 per cent (8th year) to 20.32 per cent in second year. The

total maintenance cost during non-bearing stage was mounting from T 20,073.94 per 100 plants

in 2nd year to T 66,161.74 per 100 plants in 8th year. It depicts that the total annual costs during

non-bearing years, increased with increase in the age of plantation. During 8th year, the total cost

was found more than three times as compared to cost incurred in second year.

4.5.2 Cumulative Cost of Plantation

The cumulative cost of plantation in Narkanda block per tree was worked out and placed

in Table 4.28. The cumulative per tree establishment cost worked out to T 3,318.19.

Table 4.28 Cumulative establishment cost per apple tree

(TTTT per tree)

Age in years Annual cost

(Rs.)

Cumulative

cost

1 433.99 433.99

2 200.74 634.73

3 264.96 899.69

4 332.99 1232.68

5 394.08 1626.76

6 473.28 2100.04

7 556.53 2656.57

8 661.62 3318.19

The annual cost per plant worked out to T 433.91, 200.74, 264.96, 332.99, 394.08,

473.28, 556.53 and T 661.62 during 1st, 2nd, 3rd, 4th, 5th, 6th, 7th and 8th years respectively.

4.5.3 Maintenance cost during bearing stage

Since the life cycle data based on cross sectional information on apple plantation was not

available during bearing years, therefore, cash flow analysis was not attempted. Thus, the cost

and returns analysis was carried out on an average age basis in the bearing stage of sampled

78

apple orchards in each elevation zones. The detailed analysis of maintenance cost of apple during

bearing stage in the study region for the apple orchards is given in the Table 4.29. The

establishment cost has been spread over 32 years of bearing life on prorated basis using interest

rate of 11.70 per cent. In other words, it is akin to the situation where total establishment cost has

been assumed to be borrowed at the rate of 11.70 per cent interest rate and prorated figure

presents the value of installment to fully repay the amount in 32 years.

A cursory glance on the table indicated that the total labour cost varied from 26.36 per

cent in E3 elevation to 27.82 per cent in E2 elevation. At overall level, the labour cost constituted

27.43 per cent of the total maintenance cost. Labour is used in the application of critical inputs,

manure, in training and pruning, harvesting operations in the study area indicating thereby that

apple cultivation is labour intensive activity. It is significant to note that, orchardists of lowest

elevation (E1) use less hired labour as compared to the orchards in other elevations. The fertilizer

costs works out to 19.17 per cent of the total cost under pooled conditions.

Table: 4.29 Maintenance cost of bearing apple per hundred plants on the orchards of

study area, 2012-13

(Percentage)

Sr.

No Particulars

Elevations

E 1 E 2 E 3 E 4 E 5 Pooled

1 Labour Cost 26.38 27.82 26.36 26.45 27.08 27.43

a Family 17.24 10.23 8.68 8.27 9.59 10.35

b Hired 9.14 17.58 17.68 18.18 17.50 17.08

3 FYM 15.13 12.52 12.79 12.59 12.86 13.46

4 Fertilizer 5.86 7.80 8.01 8.08 7.61 5.71

5 Plant Protection 15.76 13.40 13.63 14.02 14.66 14.61

6 Interest on WC 2.68 3.00 3.05 3.09 3.08 2.98

7 Managerial Cost 4.59 5.13 5.21 5.29 5.26 5.09

8 Risk Margin 4.59 5.13 5.21 5.29 5.26 5.09

9 Land Revenue 0.04 0.07 0.08 0.08 0.05 0.06

10 Depreciation 2.29 2.41 2.40 2.53 2.12 2.41

11 Rental value of Owned Land 6.81 7.56 7.84 7.56 7.22 7.58

12 Prorated Establishment Cost 13.25 12.51 12.71 12.38 12.26 12.91

13 Interest on Fixed Capital 2.62 2.64 2.69 2.64 2.53 2.69

Total variable Cost 57.74 64.57 65.59 66.55 66.23 64.01

Total Fixed Cost 42.26 35.43 34.41 33.45 33.77 35.99

Total Cost ( T T T T ) 60169.88 63722.02 62706.50 64421.61 65010.12 61769.01

79

However, the nutrient costs ranged from 20.47 per cent in highest elevation to 20.99 in

lowest elevation, which were almost similar. Farmers are using heavy doses of supplementary

inputs to replenish the soil fertility status. The share of plant protection costs ranged between

13.40 per cent (E2 elevation) to 15.76 per cent (E1 elevation). The higher plant protection costs in

lowest elevation may be attributed to higher incidence of pest and diseases in the area.

The management cost and risk margins were worked out at the rate of 10 per cent of the

working capital in order to arrive at the true cost of cultivation. The managerial cost and risk cost

together ranged between 9.18 per cent in lowest elevation to 10.58 per cent in E4 elevation and

under pooled condition, it works out to be 10.18 per cent. The proportionate share of variable

cost in different elevation zones worked out to 57.74, 64.57, 65.59, 66.55 and 66.23 per cent of

the total maintenance cost in E1, E2, E3, E4 and E5 respectively.

Among the fixed costs prorated establishment cost, rental value of land accounted for the

maximum proportion of the fixed costs in all the elevation zones under study. The share of

depreciation and interest on fixed cost hovered around 2.5 per cent in each elevation zone. The

total fixed cost during the bearing years was found highest (42.26 %) in the lowest elevation

zone and lowest in E4 (34.41 %) zone.

The total maintenance cost during bearing stage varied from T 60,169.88 per 100 plants

in lowest zone to T 65,010.12 per 100 plants in E5 zone. At overall level, the total maintenance

cost worked out to rupees T 61,769.01 per 100 plants of which the proportion of variable cost

was 64.01 per cent and that of fixed cost was 35.99 per cent.

4.5.4 Maintenance Cost, yield & returns from apple orchards of Himachal Pradesh

The maintenance cost, average yield, net returns, cost of production and output-input

ratio of apple cultivation for the year 2012 for different elevations has been summarized in Table

4.30. It can be seen from the table that on average situation, the total output of apple per 100

plants works out to 65.17 quintals. The production was found lowest in lowest elevation (E 1)

and highest in E3 elevation. The relatively lower production in E1 elevation may be attributed to

lesser comparative advantages prevalent in this elevation due to change in climatic conditions.

80

Table: 4.30 Maintenance cost, yield & returns from apple orchards during bearing Stage

in Himachal (per 100 plants), 2012-13

Items Elevations

E 1 E 2 E 3 E 4 E 5 Pooled

Total cost (TTTT) 60169.88 63722.02 62706.50 64421.61 65010.12 61769.01

Average production (Q) 38.92 70.53 74.16 71.78 70.47 65.17

Gross returns (TTTT) 222987.02 314372.00 332069.12 318721.52 313236.46 300277.22

Gross margins (TTTT) 188242.25 273226.84 290939.21 275250.64 270183.30 260736.81

Net returns (TTTT) 162817.14 250649.98 269362.63 254299.91 248226.34 238508.21

Average cost per kg. (TTTT) 15.40 9.08 8.44 9.08 9.28 10.01

Output / Input ratio 3.76 4.93 5.34 4.92 4.80 4.89

However, there is no existence of much difference in the outputs of E4 and E5 elevation

orchardists. The low average output of apple in E5 elevation is due to smaller holding size in this

elevation zone. The gross returns varied from T 2.23 lakhs in E 1 elevation to T 3.32 lakhs in E3

altitudinal range. On an average, the orchardists are earning about T 3lakhs as gross income per

100 plants in the study area. Under pooled conditions, the net profits and gross margins work out

to T 2.38 lakh and 2.61 lakhs respectively. These figures were lowest in E1 altitude and highest

in E3 altitude. The cost of production was found highest (T 15.40 per kg) in E1 elevation and

lowest (T 8.44 per kg) in the E3 elevation zone. At overall level, the average cost of production

per kilogram comes out to T 10 per kg.

The output- input ratio, which is considered the index of profitability, was lowest of 3.76

in lowest altitudinal zone and highest of 5.34 in E3 elevations. At overall level, the output-input

ratio worked out to 4.89. This implies that, the apple industry in the study area is a high pay off

enterprise as each unit of rupee expenditure is resulting on an average an income of T 4.89.

4.6 RESOURCE USE EFFICIENCY IN APPLE PRODUCTION

In the previous sections, we have attempted to work out the costs and returns of the apple

cultivation, which has not cast off adequate light on the productivity and efficiency of resource

allocation. It merely provides general indication of overall productivity of apple orchards.

Therefore, in this section, we have tried to identify the factors affecting the apple

production as a part of the study using high precision methods and measures of resource use with

the help of production function analysis. The outcome of regression analysis under pooled

81

conditions is given in Table 4.31. The ‘F’ test applied to test the overall significance of the

regression was found significant.

4.6.1 Input-output Relationship One important area of agricultural research centers on the physical relationship between

input used and output produced. Once this relationship has been defined, a basis exists for

answering the questions about how productivity of a crop is affected by the changes in the size of

various factors of production utilized in the production process. Productivity of apples depends

upon a variety of factors, some of which are controllable while some factors may be

uncontrollable represented by ‘u’. In the present study, Farm Yard Manure, Chemical fertilizers,

human labour, expenditure on fixed capital, management factor, literacy of orchardists, and

deviation of the orchardists from the prescribed spray schedule and density of plantation were

identified as the main factors affecting the productivity and production of apples in the study

area. It was hypothesized that farm yard manure, chemical fertilizers, human labour, fixed costs,

literacy rate and management skills of the orchardists has positive impact on the productivity of

apple crop. The deviation from the prescribed number of sprays during production period, plant

density was assumed to have negative impact on the apple yield. The regression analysis was

carried out for all the sampled orchardists, the results of which are presented in table.

Eighty five per cent of variation in the dependent variable was explained through the

chosen variables on pooled orchard data in the selected study block. The adjusted coefficient of

multiple determination that explains the explanatory power of the model was found to be 0.70.

The OLS parameter estimates with respect to FYM, chemical fertilizers, human labour

and expenditure on fixed capital were positive as well as significant which indicated that one per

cent increase in each of these variables, apple orchard productivity, on an average, would

increase by 0.102, 0.385, 0.44 and 1.088 per cent respectively. The signs and magnitude of the

aforesaid variables were in accordance with the theory. In case of deviational variable, (when the

orchardists are deviating from the prescribed schedule of spray) and that of the plant density/ha

were examined, the results have revealed that one per cent change from the optimum would

result 0.348 and 0.862 per cent decrease in the productivity. This clearly indicated the irrational

use of these practices by the orchardists in the study area. The elasticity coefficients of literacy

index and management index were found negative albeit non-significant, hence cannot be

commented upon.

82

Table: 4.31 Multiple Regression Analysis (Log linear Regression)

Variable B S E t - value

Constant - 9.96 6.50 -1.533

X1 = FYM applied (Kg) 0.102NS 0.111 0.924

X2 = Fertilizers applied (Kg) 0.385* 0.055 7.058

X3 = Deviation from prescribed Schedule - 0.348* 0.135 - 2.568

X4 = Human labour days (No.) 0.444* 0.083 5.382

X5 = Expenditure on fixed capital (Rs.) 1.088** 0.619 1.759

X6 = Plant Density / Hectare - 0.862* 0.223 - 3.856

X7 = Literacy Index - 0.003NS 0.057 - 0.046

X8 = managerial Skill Index - 0.008NS 0.027 -0.298

_ ∑ bi = 0.71

*, R

2 = 0.70, R

2 = 0.85, F Value = 20.084

Note: *** - Denotes significant at 10 per cent level of significance

** - Denotes significant at 5 per cent level of significance

* - Denotes significant at 1 per cent level of significance

The returns to scale ( ∑ bi ) was also estimated , the values of non-significant variables

have been excluded from its estimation, since their null hypothesis of ‘ bi’ equal to zero was

accepted. The results indicate that returns to scale were less than one measuring thereby that

decreasing returns to scale are thus operative. The decreasing returns to scale indicated that the

orchardists are operating in rational zone of production in the study area.

4.6.2 MVP – MFC ratio analysis The theory of economics justifiably asserts that the marginal value products must

equalize the marginal factor cost. The ratio of the marginal value productivities of resources to

their factor costs were computed for the apple farms of the study sample (Table-4.32).

The MVPs of the apple orchards in the study area pertaining to FYM, fertilizers, human

labour, expenditure on fixed assets have symbolized a positive sign. It conveyed that there is

ample amount of scope to raise the returns by an efficient usage of these resources. The ratios of

the MVPs to their associated costs were found considerably greater than unity, which indicates

83

that returns from apple farming could have been increased by increasing use of these three

resources.

The analysis of data indicates that there exist more scope to augment the income by

making more usage of chemical fertilizers, human labour, FYM and fixed costs. The inefficiency

was noticed in the density of planting as the MFC ratio was negatively focussed. It depicts that

for every rupee spent on one extra tree will result in to a loss of 4.69 rupees. The fixed cost has

shown high MVP-Factor price ratio of 19.55, which indicates that the income of the growers

through apple cultivation can be enhanced by investing more on better type of implements and

machinery, livestock, storages, farm houses, irrigation structure etc.,. It also indicated that

optimum strategy should be adopted as a whole in order to improve income through apple

cultivation.

Table 4.32 Marginal Value Products (MVPxi) and factor price ratios (MVPxi /Pxi) on sampled

orchards

Sr. No. Variables MVPxi MVPxi/Pxi

1 Farm Yard Manure (X1) 945.49 2.70

2 Chemical Fertilizers (X2) 241.36 17.24

3 Human Labour (X4) 1160.36 4.64

4 Fixed Cost (X5) 19.55 19.55

5 Plant Density (X6) - 1878.52 - 4.69

4.7 FARMER PERCEPTION REGARDING CLIMATE CHANGE IN THE STUDY

AREA

It is expected from the information cited in section 4.1, that there might be the impact of

climate change on the production and productivity of apple farming. For example, the apple belt

in Solan, Sirmaur, Kangra and Mandi districts of Himachal Pradesh is showing decline in the

apple area and production. The reliability of apple farming on climatic factors makes it more

peculiar to its change as a whole. Farmers in areas like Kullu and lower belts of Shimla are

opting for a change in crop industry or choosing suitable cultivars of apple that suits the

geographical location.

It has been viewed in the context of widespread perception of the farmers that climate

change does occur and is exhibiting certain impact on all the aspects of apple farming. The

84

perusal of the Table 4.33 states that, farmers believed in the existence of a drastic climate change

scenario in the study area.

Table: 4.33 Farmers’ perception regarding the climate change

Sr. No Statement

Perception

MPS* Rank SA A UD DA SDA

5 4 3 2 1

1 Farmers are concerned about the Climate change 50 18 2 0 0 4.69 2

2 Chilling requirements for apple production has been adversely affected by climate change

46 23 1 0 0 4.65 3

3 There is decline in the snowfall during past years due to climate change

43 27 0 0 0 4.62 4

4 Climate change has adversely affected the winter precipitation in the study area

18 32 20 0 0 3.33 10

5 Climate change has unseemly affected rainfall consequently the apple production

33 32 5 0 0 4.4 8

6 Owing to climate change the farmers have to shift high chilling varieties to the higher elevations

42 22 6 0 0 4.52 7

7 Due to drastic change in temperature as a part of global warming has caused a great obstacle in apple production

54 16 0 0 0 4.78 1

8 Due to climate change , untimely occurrences of hail storms have increased affecting apple production in contrary

40 30 0 0 0 4.58 6

9 Sustainability of apple production may be affected in the long run due to climate change

47 17 6 0 0 4.59 5

10 Climate has resulted in untimely rainfall particularly at flowering and fruit development stage untowardly affecting apple production

22 43 5 0 0 4.25 9

11 Climate change has enhanced the concern of the Government

0 9 13 30 18 2.19 11

Note: SA-Strongly Agree, A-Agree, UD-Un Decided/ can’t say, DA-Disagree, SDA-Strongly Disagree * Mean Perception Score (MPS)

As per the mean perception score (MPS) of 4.78, the most weighed perception among the

farmers was that due to extreme change in temperature as a part of global warming that has

caused a great obstacle in apple production. More than 68 per cent of the orchardists believed

that climate change has not enhanced the concern of the Government (MPS: 2.19).

Thereafter, the farmers have also expressed their concern due to climatic factors that it is

affecting their apple farming practices (MPS: 4.69). The next problem of importance was that the

chilling requirements for apple production have been adversely affected by climate change

(MPS: 4.65), followed by the problem of less snowfall (MPS: 4.62), and they were not sure

about their apple industries future (MPS: 4.59). The farmers were also anxious because of

85

unexpected occurrences of the hailstorms, which adversely affect their apple production (MPS:

4.58), trailed by the shift of the traditional apple belt to the higher elevations (MPS: 4.52). The

major issue was for the reason that the climate change has unseemly affected rainfall (MPS:

4.40) and thereby its unexpected occurrence especially during flowering and fruit development

(MPS: 4.25) have raised the trepidation among the farmer community in the study area. Then

was the problem of the winter precipitation in the recent past, which has been affected by the

climate change (MPS: 3.34).

4.8 PROBLEMS FACED BY APPLE GROWERS With the increase in the production of apples in the district, many problems in the field of

production and marketing are arising. In this section, an effort has been made to scrutinize the

problems faced by the orchardists in the environs of production and marketing. The

production problem faced by the sampled orchardists in study area was also recorded during

survey and the same is presented in Table 4.34 for the sample farms of the study area.

Production Problems

a. Shortage of labour

Shortage of both unskilled and skilled labour for conducting various intercultural

operations, application of farmyard manure and fertilizers, training and pruning of trees and

plant protection measures were reported by 65.71 per cent of orchardists in the study area at

overall level. More than 58.57 per cent of orchardists surveyed in Narkanda block reported

higher wage rate as one of the hindrances in the proper management of orchards on scientific

lines. Non-availability at peak periods and lack of technical know-how were also intimated by

more than 82.86 per cent surveyed orchardists of the study region.

b. Chemical fertilizers

The sample orchardists also forwarded their opinions regarding the problems pertaining

to cost and availability of chemical fertilizers. A cursory glance on Table 4.34 reveals that non-

availability of desired brand; untimely availability and high costs were intimated as the main

problems by 48.57, 52.86 and 34.29 per cent of average sampled growers in study region.

86

c. Plant protection chemicals

Plant protection chemicals constitute an important critical input in apple production. High

prices of chemicals, non-availability in time, and availability of spurious chemicals were the

main problems faced by sample orchardists in the study area. At overall level, high prices, non-

availability and availability of spurious brand were reported by 71.43, 77.14 and 82.86 per cent

respondents respectively in the study area.

Table 4.34 Problems faced by the farmers in production of Apple (Multiple response in percentage)

Particulars Elevations

Labour problems E 1 E 2 E 3 E 4 E 5 Pooled

i Shortage of Labour 10

(71.43) 9

(64.29) 9

(64.29) 10

(71.43) 8

(57.14) 46

(65.71)

ii Higher wages 12

(85.71) 7

(50.00) 9

(64.29) 7

(50.00) 6

(42.86) 41

(58.57)

iii Non Availability 12

(85.71) 13

(92.86) 10

(71.43) 10

(71.43) 13

(92.86) 58

(82.86)

Chemical fertilizers

i High cost 10

(71.43) 6

(42.86) 5

(35.71) 5

(35.71) 8

(57.14) 34

(48.57)

ii Desired brand not available 7

(50.00) 7

(50.00) 9

(64.29) 6

(42.86) 8

(57.14) 37

(52.86)

iii Fertilizers not available in time 6

(42.86) 4

(28.57) 5

(35.71) 5

(35.71) 4

(28.57) 34

(34.29)

Plant Protection Chemicals

i High prices of chemicals 11

(78.57) 10

(71.43) 10

(57.14) 10

(71.43) 11

(78.57) 50

(71.43)

ii Chemicals not available in time 12

(85.71) 10

(71.43) 12

(85.71) 10

(71.43) 10

(71.43) 54

(77.14)

iii Sale of spurious chemicals. 12

(85.71) 12

(85.71) 13

(92.86) 10

(71.43) 11

(78.57) 58

(82.86)

Other problems

i Non availability of healthy plant material

10 (71.43)

9 (64.29)

7 (50.00)

7 (50.00)

9 (64.29)

42 (60.00)

ii Limited availability of FYM 13

(92.86) 11

(78.57) 10

(71.43) 12

(85.71) 10

(71.43) 56

(80.00)

iii Irrigation facility not available 14

(100.00) 13

(92.86) 11

(78.57) 12

(85.71) 14

(100.00) 64

(91.43)

d. Plant material, farm yard manure and irrigation problems

Healthy plant material is the key to quality production of apple. Non-availability of

healthy and genetically improved spur varieties of apple plants was reported by 60 percent

87

growers in the study sample. Similarly, use of FYM is vital for health and production of fruit

plants. Actual need of FYM is rarely met in the study region. Nearly 80 per cent sample

orchardists in the study area reported about the limited availability of this crucial factor. Absence

of irrigation facility was the problem reported by 91.43 per cent of the farmers at overall level.

Marketing problems

Marketing of apple is as critical as production. Lack of markets and improved

marketing practices contribute to the intricate nature of the marketing of apple in the

hills. In the absence of any planned marketing programme for apple, producers often remain

deprived of remunerative prices for their produce. The various marketing problems and

constraints faced by the apple growers need to be tackled in order to boost up the growth of

area under apple crop. The returns from apple depend on several factors like quality of fruit,

which otherwise depend upon time of picking. care taken in grading and packaging, time

taken in transportation, mode of transport used, time and type of storage, quantity and quality

of packing material etc. keeping all these facts in view, opinion of apple, growers with the

problems of marketing were sought, and the responses in the study area accordingly. The

Table in support to the above details is given in the Table 4.35.

Shortage of grading and packaging labour

Shortage of skilled labour d u r i n g g r a d i n g a n d p a ck i n g were reported by 65.71

per cent of orchardists in the study area at overall level. More than 58.57 per cent of

orchardists surveyed in Narkanda block reported higher wage rate as one of the hindrances in

the post harvest management. Non-availability of l abour in requ i red amount was

repor ted to be a ser ious p roblem as intimated by more than 82.86 per cent surveyed

orchardists of the study region.

Packing material

Apple being fragile in nature needs good packaging which may ensure least damage

to fruits during transportation. The indecent quality of fruits may result into non-remunerative

prices. 27.14 per cent orchardists in study area reported shortage of other packing material. At

overall level, nearly 38.57 per cent growers complained high prices of packing material as a

problem.

88

Storage problems

Apple produce being perishable, require immediate disposal. Due to lack of cool chain

system, huge losses are borne by the participants of marketing process. Farmers in both

regions do not have enough scientific storage facilities for Apple. Storage is normally

carried out in some improvised or ill-ventilated homes sheds at home. The inappropriate

storage facility normally, increases the quantitative and qualitative losses. Marketing seasons

of Himachal Pradesh apples extend from July to end of October. During peak harvesting

time, producers are strained to route to distress sales.

No storage and inadequate storage facilities were more severe problems in sampled area

of study area. Nearly 55.71 per cent sample grower in study area reported about non-availability

of storage facility. Inadequate storage was reported as the main problem by 12.86 per cent

orchardists in Shimla district.

Transportation problems

Transportation is one of the important marketing functions required in apple marketing

because consumers are situated at longer distances from producing areas. Transportation

involves bringing produce from orchards to road head and then road head to consumers. Often

family and hired labour is used for carrying the produce from orchards to assembling points.

After doing packing at the assembling point, the produce is carried to road-head either on

human backs or on the mules. From the road-head, after doing appropriate marketing

motorized transport is hired for taking the produce to local or terminal markets. An analysis of

grower problems revealed that major concern is high transport cost. Further concern is about

the lack of all weather and metallic road. A few of them felt the need of improved link roads

in the producing areas. Nearly 45.71 per cent of farmers reported that their villages are not

linked with proper metal led link roads. In hilly terrain during rainy season landslides and

road blockage, take place. Marketing reason of apple is harmonized with monsoon rains. In

study area, nearly 78.57 per cent farms reported that, their villages are not linked with all-

weather roads. 42.86 per cent farms of study area voiced a high transport charge. During the

peak season of horticultural operations, there is a tendency to ask for higher wages performing

the marketing operations.

89

Market intelligence

Market intelligence plays a momentous role in the marketing of perishables.

Less majority of the growers show up that, they remain unaware of exact information in

respect of prices and supply available in different markets. The information regarding the

market demand, arrival and prices prevailing in the market are very important as the same

can affect the income of the growers. Market intelligence problems here relates to late

information, limited information, misleading information or information available for limited

markets.

31.43 per cent of the farms revealed that they were getting inadequate information

to plan their marketing strategy. Nearly 35.71 per cent respondents in farms informed that they

were getting misleading information. The growers reported that market intelligence supplied

by the government were generally for few markets. Thus, they were not in a position to

plan their marketing in an efficient way. Nearly 24.29 per cent farms reported that

information about prices was received late.

Mal - practices

The regulation of markets was done with a view to watch the welfare of the sellers

and buyers by restraining the malpractices existing in the markets. The apple growers had a

general criticism that, the intermediaries were charging assorted marketing charges from the

sale proceeds, while these charges are expected to be paid by them as per the market

regulations. Nearly 81.43 per cent of the farms complained that the intermediaries were

deducting more than the genuine charges. The part payment was reported as a problem by

22.86 per cent at overall level. At overall level, 82.86 per cent orchardists from both the study

regions reported that, commission agents/ wholesalers in the market quote lower than actual

prices. 65.71 per cent of the farmers felt that, their consent was not taken in fixing the prices.

Market intervention scheme (culled fruit)

14.29 per cent of all the farms felt that the prices were not announced in time. Price not

paid in time was a problem for nearly 15.71 per cent of the farmers. Merely 8 per cent of them

felt that the prices were low. However, 11.43 per cent of the farmers believed that the

announced prices were not been given.

90

Table 4.35 Problems faced by the farmers in marketing of Apple

(Multiple response in percentage)

Particulars Elevations

1. Grading and packing Labour E 1 E 2 E 3 E 4 E 5 Pooled

a) Shortage of Skilled Labour 10.00

(71.43)

9.00

(64.29)

9.00

(64.29)

10.00

(71.43)

8.00

(57.14)

46.00

(65.71)

b) Higher wages 12.00

(85.71)

7.00

(50.00)

9.00

(64.29)

7.00

(50.00)

6.00

(42.86)

41.00

(58.57)

c) Non Availability 12.00

(85.71)

13.00

(92.86)

10.00

(71.43)

10.00

(71.43)

13.00

(92.86)

58.00

(82.86)

2. Packing Material

b) Shortage of other package material 7.00

(50.00)

3.00

(21.43)

4.00

(28.57)

2.00

(14.29)

3.00

(21.43)

19.00

(27.14)

c) High Prices 6.00

(42.86)

4.00

(28.57)

5.00

(35.71)

5.00

(35.71)

7.00

(50.00)

27.00

(38.57)

3. Storage facility

a) No storage facility 10.00

(71.43)

8.00

(57.14)

6.00

(42.86)

9.00

(64.29)

6.00

(42.86)

39.00

(55.71)

b) Inadequate storage facility 2.00

(14.29)

1.00

(7.14)

3.00

(21.43)

2.00

(14.29)

1.00

(7.14)

9.00

(12.86)

4. Transportation

b) Vehicles not available in time 2.00

(14.29)

1.00

(7.14)

1.00

(7.14)

1.00

(7.14)

3.00

(21.43)

8.00

(11.43)

c) Villages are not linked with metal road 8.00

(57.14)

6.00

(42.86)

5.00

(35.71)

5.00

(35.71)

8.00

(57.14)

32.00

(45.71)

d) High transportation charges 6.00

(42.86)

5.00

(35.71)

7.00

(50.00)

6.00

(42.86)

6.00

(42.86)

30.00

(42.86)

e) Lack of all weathers roads 12.00

(85.71)

10.00

(71.43)

9.00

(64.29)

11.00

(78.57)

13.00

(92.86)

55.00

(78.57)

5. Market Intelligence

a) Late information 2.00

(14.29)

3.00

(21.43)

1.00

(7.14)

1.00

(7.14)

3.00

(21.43)

10.00

(14.29)

b) Information available for local market only 3.00

(21.43)

2.00

(14.29)

4.00

(28.57)

2.00

(14.29)

3.00

(21.43)

14.00

(20.00)

c) Inadequate information 5.00

(35.71)

8.00

(57.14)

3.00

(21.43)

2.00

(14.29)

4.00

(28.57)

22.00

(31.43)

d) Misleading information 7.00

(50.00)

3.00

(21.43)

4.00

(28.57)

6.00

(42.86)

5.00

(35.71)

25.00

(35.71)

91

6.Malpractices in market

a) Deduct more charges 12.00

(85.71)

10.00

(71.43)

11.00

(78.57)

11.00

(78.57)

13.00

(92.86)

57.00

(81.43)

b) Part payment 5.00

(35.71)

3.00

(21.43)

2.00

(14.29)

2.00

(14.29)

4.00

(28.57)

16.00

(22.86)

e) Do not take the consent of the farmer

for fixing the price

11.00

(78.57)

10.00

(71.43)

9.00

(64.29)

7.00

(50.00)

12.00

(85.71)

46.00

(65.71)

f) Quote lower price than actual price 10.00

(71.43)

12.00

(85.71)

12.00

(85.71)

13.00

(92.86)

11.00

(78.57)

58.00

(82.86)

7. Market intervention Scheme (culled fruit)

a) Price not announced at time 1.00

(7.14)

3.00

(21.43)

3.00

(21.43)

1.00

(7.14)

2.00

(14.29)

10.00

(14.29)

b) Price are not paid in time 2.00

(14.29)

1.00

(7.14)

2.00

(14.29)

2.00

(14.29)

4.00

(28.57)

11.00

(15.71)

c) Prices are low 8.00

(57.14)

12.00

(85.71)

10.00

(71.43)

11.00

(78.57)

13.00

(92.86)

54.00

(77.14)

d) Do not give announced prices 1.00

(7.14)

1.00

(7.14)

3.00

(21.43)

2.00

(14.29)

1.00

(7.14)

8.00

(11.43)

Note: Figures in parentheses indicate percentage to respective total

Chapter-5

SUMMARY & CONCLUSION

Productivity is a term with high significance in any enterprise. Especially in

agriculture, at national level, it raises living standards because more real income improves

peoples’ ability to purchase goods and elevate their livelihoods. Productivity in fruit farming

is also a subject which facilitates this view and is most often assessed by measures of crop

yield. The growth rate in productivity is an important determinant of agricultural

transformation and is considered as the engine of growth to the farm economy. The crop

productivity growth is an indicator of use of farming knowledge, technology, infrastructural

development, farm investments, and development of suitable price policy. It implies more

efficient distribution of scarce resources.

Horticulture development in Himachal Pradesh is an economic necessity. Horticulture

sector in the state has made remarkable contributions in the upliftment of the socio-economic

conditions of the farming community. However, the success of horticulture is more

pronounced in temperate regions of the state and apple is predominant fruit crop in the state.

The apple alone accounts for more than 48.30 percent of area and 74.21 percent of production

of all fruits in the state of Himachal Pradesh during 2011-12. The expansion in the area and

production alone is not an indicator of enhanced income, but improvement in the

productivity status is equally important to ensure better returns from the produce. The

account of apple farming systems shall highlight the socio-economic aspects, objectives,

priorities, cultivation practices and problems encountered by the orchardists. The lessons

drawn from the experiences shall help suggest possible improvement in the producing region.

Besides, a thorough understanding of existing production system will help in evolving

effective measures, policies and procedures for tackling the problems of apple orchardists. In

view of this a study was undertaken with special reference to analysis of productivity

and economics of production of apples in Narkanda block to document and analyze

various important production aspects. More specifically, the important objectives of the

present study were as under:

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Objectives

� To examine the trends in production and productivity of apple

� To study the cost of production of apples in the study area

� To analyze the factors affecting the apple productivity and production

3.1.2. Sampling frame

Multistage random sampling technique was used for the selection of households. A

sample of 70 orchardists from Narkanda block was drawn in this study. The orchardists were

classified based on the five altitudinal zones and were designated as E1, E2, E3, E4 and E5 for

≤1500m, 1500-2000m, 2000-2500m, 2500-3000m, ≥3000m above msl elevation respectively.

To meet the objectives of the present study, both primary as well as secondary data

were collected. The primary data on demographic features family size, age, education,

occupation etc, economic parameters (land inventory, livestock, cropping pattern and

income), cost of production, yield and problems faced by the growers in various aspects of

production and marketing were collected on well designed pre-tested schedules by adopting a

personal interview method from the selected households during the year 2012-13.

Secondary data pertaining to the list of villages, households, cropped area, production,

productivity of apples, were recorded from the officials of Directorate of Horticulture, Shimla

Himachal Pradesh, National Horticulture Board, Food and agricultural organization and

Block Development office of Narkanda block, the data list of households for the selected

villages were collected from patwari of respective villages.

Analytical Techniques

To meet out the requirements of the study objectives, tabular analysis averages,

percentages, standard deviation, coefficient of variation, critical difference, index numbers,

correlation, production function analysis and likert scaling techniques were used as and when

required. Simple tabular analysis was used to examine socio- economic status of the

growers, resource structure, income and expenditure pattern, growers opinions about the

production and marketing problems and growers’ perception regarding the impact of climate

change on the production and productivity of the apple.

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Main Findings

After analyzing to best of my ability, under limitation of money and time, attempt has

been made to present the main findings of the present study as following:

1) The compound growth rate of area, production and productivity of apple with respect

to India worked out to 2.4, 3.5 and 1.1 per cent respectively. Similarly, corresponding

growth rates for Asia were 3.9, 6.3 and 2.4 per cent. Comparably the world as a whole

has shown the trends of 1.2, 2.4 and 1.2 per cent of growth in area, production and

productivity of apple.

2) The mean productivity differences between 9 major apple producing countries were

calculated for the period of 1973-2011, and was observed that highest mean

productivity was achieved by France (33.60 MT/ ha) and the least among them was

observed with India (5.92 MT/ ha). Statistically the productivities of USA and Chile

were at par with each other and in the same way China was at par with India. In

contrast to these countries like France, Italy, Turkey, Iran and Brazil have shown

diversity in their apple productivities.

3) The trends in area, production and productivities of the apple growing districts of

Himachal were computed for the time period ranging 1973-74 to 2011-12. It was

found that the percent changes in acreage ranged from least in Kangra (29.41 %) to

highest in district Lahaul & Spiti (14333.33 %). The highest change in production

trends of apple was of 1456.67 per cent in Kinnaur and lowest was in Sirmaur district

(- 94.40 %). In the context of productivity, all the changes were in declining trend

except in the district Shimla with 153.63 percent positive change and district Kinnaur

exhibiting a change of 53.06 per cent in the span of 39 years.

The area, production and productivity in Himachal Pradesh increased at a compound

rate of 3.27, 3.5 and 0.3 per cent per annum during 1973-74 to 2011-12 period respectively.

The districts Chamba, Kinnaur, Lahaul & Spiti and Shimla experienced a significant growth

in the area & production under apple. In the matter of productivity only two districts namely

Shimla and Kinnaur exhibited positive growth while in rest of the districts, the productivity

growth turned out to be declining.

4) The analysis of inter-district productivity differentials revealed statistically wide

differences in apple productivity between Kinnaur, Kullu and Shimla districts of the

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state. No differences in the productivities were observed between the districts Solan,

Sirmaur, Lahaul & Spiti and Kangra. The high productivity districts exhibited high

degrees of stability in the productivity, whereas, the low productivity districts have

exhibited high instability in the productivity.

5) In the state of Himachal Pradesh the increase in the apple production during the

period of 39 years was mainly due to area expansion rather than the improvement in

the productivity. At all India level however, the contribution of yield towards the

growth of production was estimated at 52 per cent while area shared 48 per cent

towards increased production. Similar trends were observed in case of total world

production of apples. However, for the Asia as a whole the contribution of area was

more than the contribution of yield towards the growth of apple production.

6) The total geographic area of the Narkanda block is 23791 ha, out of which 5373.91 ha

area is under apple that constitutes to 14.28 percent of total area under apple in the

Shimla district. The net sown area comprises of 24.40 percent of the total

geographical area. The average area under irrigation is 3.26 percent of the net sown

area in the study block. The population of the block, according to 2001 census is

39684. About 98 per cent of the total population in the district resides in 186 villages

of the selected study block. The average family size in the block was 4.60 persons as

against 4.67 persons in Shimla district.

7) The cropping pattern analysis revealed that apple is the dominant fruit crop of the

study area of Narkanda block. It was followed by cherry, almond, pear, apricot and

plum respectively.

8) At overall level, the average family size of sampled orchardists comprises of 6.56

persons, out of which 56.86 percent are males and rest are females in the study area.

The number of females per thousand of males worked out to 834.78 at overall level.

Nuclear families comprised of 67.14 percent and the rest were joint families.

9) Age composition analysis showed that in the study area, maximum proportion of

family members fall in the age group of 18-60 years, this implies that persons

engaged in the age group of 18-60 years which comprises of work force in the

family and accounted for around 69.51 percent of the average family size

10) On an average, the number of workers in a family in orchards of the study area are

4.57 (69.66 %). The proportion of active workers working in orchards to total work

force was 69.15 per cent at overall level. On an average, the dependency ratio was

0.44.

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11) Literacy situation revealed that nearly 89.95 per cent family members are literates in

case of sample orchards of the study area. The majority of family members (52.28%)

had education up to graduation and more.

12) Occupational distribution revealed that 70.31 per cent of work force in the

study area practice farming, followed by service sector (25%), business (3.75 %) at

overall level.

13) The average size of land holding in the study area worked out to 1.27 hectares. The

holding size of E1, E2, E3, E4 and E5 orchardists was 0.97, 1.49, 1.48, 1.57 and 0.89

hectares respectively.

14) Apple is occupying the place of pride sharing 86.45 per cent of the total fruit plants in

the sample farms of the study area at an overall level. The next in importance is

Cherry sharing 4.34 per cent area followed by almond (4.29 percent), pear (3.91

percent), apricot and plum (2.15 percent) each. An average orchardist owns 419 plants

per farm, out of which nearly 21 per cent comes out to non-bearing plants in the study

area.

15) Livestock population at overall sampled apple farms in Himachal Pradesh was 1.36.

Cows form nearly 56.62 of the livestock population followed by young stock animals

which were about 43.38 per cent.

16) Management is a continuous process through observing and conceiving ideas. At

overall level, in the study area the average value of MSI was 99.58. Nearly 52.86

percent of orchardists had MSI of 124.65, 11.43 percent orchardists MSI worked out

to be highest of 169.12.

17) In apple farming, farmers make investment on constructions, different mechanical

equipments used in farming, and livestock population. At overall level, per farm

investment on the farm implements worked out to T 27224.

18) The study revealed that the average yield per hectare has a positive relationship with

altitudinal range indicating thereby that altitude play an important and positive role in

increasing the productivity of the apple orchards. It was further concluded that there is

no major disparity between the productivities of different altitudinal zones except

between E1 zone and other elevation zones. The mean productivity varied merely

from 15.54 to 17.38 MT/ha between E2 –E5 elevations. Statistically they were at par

with each other. The computed value of critical difference was 1.94.

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19) On the basis of current data, the average productivity of apple in the study area was

found two and a half times more to that of average apple productivity of the state as a

whole and nearly one and a half times more to that of Indian apple productivity. The

study area apple productivity matches with the world apple productivity. However,

the productivity in the study area was found far less from the productivities attained

by the many developed nations such as France. Italy, Brazil, Chile etc.

20) The analysis of gross income structure in the study area orchards, showed that,

majority of sampled orchardists in the study area, fall in the income scale of T

2-5 lakhs (55.71). Nearly 24.29 per cent growers in study area fall in the income

slab of T 5-10 lakhs, 5.71 percent in T 10-15 lakhs and the remaining 14.29 percent

in the income slab of T ≥ 15 lakhs per annum.

21) Apple orchardists in study area incurred a total cost of T 43399.28 on an average, per

hundred plants in the first year of plantation. Maintenance cost during non-bearing

stage per hundred apple plants at overall level in the study area ranged from Rs T

20,073.94 to T 66,161.74. On an average per tree establishment cost worked out to T

3318.19. Maintenance cost of bearing apple per hundred plants at over all level, in the

study area was worked out to T 61,769.01.

22) Average production varied from 38.92 qt. & 74.16 qt. per 100 plants. Net returns

varied from T 161756.68 to T 268129 in different altitudinal zones. Average cost per

kg was T 10.20.Average gross margins were T 260736.81.

23) Functional analysis of apple orchards at over all level, revealed that variables

like farm yard manure, chemical fertilizers, human labour, fixed costs has positive

impact on apple productivity. Deviation from the prescribed number of sprays during

production period and plant density revealed negative impact on the apple yield. R2

was 0.70.

24) The MVP-MFC ratio revealed that, an average orchardist in the study area is making

sub-optimal use of available resources. There exist a scope to increase the apple

productivity in the study block, by increasing the levels of chemical fertilizers,

expenditure on fixed assets, human labour since currently they were used sub-

optimally on the sampled orchards of the Narkanda block. Productivity of apple

can be further enhanced if the orchards in the study area, sticks to optimum plantation

density and optimum number of sprays to control disease infection and insect

infestation.

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25) The climatic factors play an important role in the productivity of apples. In this

context the perceptions, of the farmers were solicited about the impact of the climate

on the productivity of the apple orchards. The majority of the sampled orchardists

believed that there has been drastic change in temperature as a part of global warming

which has caused great obstacle in apple production. The mean weighted perception

score in this context worked to 4.78. More than 68 per cent of the orchardists believed

that climate change has not enhanced the concern of the government. They reported

that the climatic changes, have adversely affected the chilling requirements; resulted

in the decline of the snowfall; caused untimely occurrences of hailstorms; unseemly

effected rainfall particularly at flowering and fruit development stages which in turn

has adversely affected the productivity of the apples in the study area.

26) Shortage of skilled and unskilled labour for conducting intercultural operations,

application of nutrients, training and pruning, high wage rates, non availability of

labour, high chemical costs, non availability of chemicals, sale of spurious chemicals,

non-availability of quality planting material, shortage of farm yard manure, poor

irrigation facilities were the main problems faced by the orchardists in the study area.

27) The shortage of grading and packing labour, packing material, in adequate storage

facilities, transportation problem, problems in market intelligence, and malpractices in

the market and the inaccuracy in the market intervention scheme were the critical

marketing problems faced by the orchardists in the study area.

Taking all the above findings into consideration it is propounded that the high apple

productivities are not witnessed in lowly elevated orchard sites like ≤ 1500 m amsl. This

situation of apple farming is on par with the wide range of research undertaken in the country

and around the world as well. It is well recognized fact that there exists global warming on a

rapid pace, which is affecting the face of agriculture around the world.

Particularly the effect of climate change is expected to be in reign in the State of

Himachal Pradesh, India. Horticulture being the major contributor to the gross domestic

product of the state is a foremost source of income to majority of farmers. Therefore, it

becomes very essential to take up best remedies in order to face this alarming situation due to

climate change and its impact on the apple productivity in the study area.

The reasons for the low apple productivity in lower altitudinal zones may also be

imputed to the topography of the orchard site which becomes a hurdle in apple farming, the

99

variance in the management due to differences in farm experience, affected rate of adoption

to new technology owing to preponderance of the marginal land holdings, high reliability on

the rainfed conditions as a source of irrigation, obstructive weather and climate for the

available cultivars in the area, over exploitation of the scarce resources, fading population of

the honey bees – the gifted pollinators, lack of appropriate proportion of the pollinating

cultivars among the orchards etc.,

It is also observed that the cultivation of apple in adversely affected due to, among

other things, falling soil fertility, emergence of numerous pests and diseases due to erratic

weather conditions. Loss of micronutrients have lead to deterioration in the overall soil

health. The problem has been compounded due to the availability of spurious inputs,

especially agro-chemicals. There is as yet no regulatory mechanism to control the supply of

spurious inputs. The high prevalence of diseases and low production has directed to an

excessive use of agrochemicals and chemical fertilizers that have given rise to a vicious cycle

of declining yield-more use of chemicals– more plunge in productivity, and so on. This has

not only escalated the production cost but has also affected environment defiantly.

Low and stagnant productivity levels coupled with high cost of production are other

important aspects to worry. In case of apple, nearly one-fifth of the crop bearing plantations

are over-aged which pull down the overall productivity. These need to be replaced by new

dwarf, spur bearing and high yielding plantations (Sharma, 2011).

POLICY IMPLICATIONS

Based on the findings of the study, following policy options and recommendations

have emerged for the formulation of development strategies in respect of apple farming on

the study area.

The growth rate in the productivity of the state and its contribution towards expansion

of total production has presented a dismal picture which is a cause of concern to the

development planners and the scientists. In order to improve the productivity levels, serious

efforts are needed to rejuvenate the senile and old apple orchards to arrest the decreasing

trends in productivity. In Himachal Pradesh since apple cultivation is mostly practiced on

rainfed area, therefore insitu soil conservation practices and watershed management to

harvest rainwater for prolonged availability needs to be urgently promoted in the apple

100

producing regions. Micro irrigation popularly known as drip irrigation should be popularized

among the orchardists to enhance yield, reduce weed population, exercise savings in costs

and improve fruit quality. It is therefore most important step that water potential should be

explored to the fullest extent in the study area. Water availability can be ensured through

,maintenance of existing kuhls, construction of water tanks and resources for storing water

and whenever possible lift irrigation should be installed to cope with the water shortages

facing apple orchards.

The initial inputs like organic and inorganic fertilizers, FYM and the fixed capital

items were used sub optimally by the apple growers in the study area. The balanced use of

these inputs by the orchardists can enhance the apple productivity and in economic viability

to a large extent. All out effort are needed to motivate and educate the orchardists by holding

short term training programmes with regard to integrated nutrient and pest management,

fertigation , micro irrigation, use of biofertilizers, pruning and training, planting techniques,

model nursery productions to the apple growers. Besides, critical inputs should be made

available to the orchardists on in proper time, desired quality and brand at an affordable price.

In order to address the problem of change in the climatic factor, it is suggested that

orchardists should gradually shift to the suitable cultivars best suited to the respective

geographical location in accordance with the changing climate.

Chapter-6

BIBLIOGRAPHY

Alagumani T. 2005. Economic analysis of tissue cultured banana and sucker propagated banana. Agricultural Economic Research Review, 18: 81-89.

Anand C and Shivannavar. 2005. An economic analysis of production and marketing of papaya in North Karnataka. M. Sc. (Agri.) Thesis, UAS, Dharwad, Karnataka (India)

Ashebir Dereje, Deckers T, Nyssen, J, Wubetu Bihon, Alemtsehay Tsegay, Hailemariam Tekie, Poesen J, Mitiku Haile, Fekadu Wondumagegneheu, Raes D, Mintesinot Behailu, Deckers J. 2010. Growing apple (Malus domestica) under tropical mountain climate conditions in northern Ethiopia. Experimental Agriculture. 46(1): 53-65

Awasthi P K, Raguwanshi N K, Choubey K G and Mishra A. 1987. Economics of guava orchards in Jabalpur district. Indian Journal of Agricultural Economics, 42(3) 461.

Azad K C and Sikka B K. 1991. Production and marketing of temperate fruits in north-west region of India. Acta. Horticulturae, 270: 67-74.

Babu K R. 1992. Resource use efficiency in rubber plantation of in traditional areas. A case of Dakshina Kannada district of Karnataka state. Agricultural Economics Research

Review, 52(2): 167-175.

Bhat G M and Dhar M K. 1989. Resource use efficiency of apple cultivation in Jammu and Kashmir State. Indian Journal of Economics, 4 (3): 611-616

Birthal P S and Joshi P K. 2008. Institutional Innovations for Improving Smallholders participation in High Value Agriculture: A case of Fruit and Vegetable Growers Associations. Quarterly Journal of International Agriculture, 46 (1): 49-68.

Bore D P. 1968. Economics of production and marketing of banana in Jalgaon district. M. Sc. (Agri.) Thesis, Mahatma Phule Krishi Vidyapeeth, Rahuri (Maharashtra).

Braun P and Muller M. 2012. Effects of climate change on fruit production in the state of Hesse. INKLIM 2012 Module II plus

Braun V J, Swaminathan M S and Rosegrant M W. 2003. Agriculture, food, Security, nutrition and the millennium development goals. IFPRI Publications.

Chitra P, Narendar B and Reddy K. 1997. Economics of ber production in around Hyderabad city of Andhra Pradesh. Indian Journal of Agricultural Economics, 52 (3): 623-624.

Datt R and Sundharam K P M. 2007. Natural Resources, Economic Development and Environmental Degradation. Indian Economy. S Chand & Co Ltd., Ram Nagar, New Delhi :99-100.

Deepak Shah. 2002. Production and marketing pattern of grapes in Maharashtra: an appraisal. Gokhle Institute of Politics and Economics. Pune, 14(1): 41-49.

Deepak Shah.1996. Production and marketing pattern of grapes in Maharashtra Journal of

Agricultural Marketing, 20 (1):10-12.

102

Deodhar S Y, Landes M and Krissoff B.2006. Prospects for India’s Emerging Apple Market. Electronic Outlook Report from the Economic Research Service. United States Department of Agriculture. FTS-319-01

Edwards A L and Kilpatrick. 1948. Informal criteria for attitude statements. In: Techniques of attitude scale construction (Edwards, Allen L.) New York, Appleton- century-crofts, Inc.

FAO. 2013. Crop Production Statistics

Farooqi K D. 2003. Future of the Apples in the Apple state of India, Jammu & Kashmir. Apple Farming and Livelihood in the Himalayas. 112-116.

Groot M J. 2000. Economics of Apple Production System with Minimal input of chemicals. Proceedings of XIV International Symposium on Horticultural Economics, Acta

Horticulture. 536: 47-51.

Handiganur S. 1995. Economics of production and processing of grapes in Bijapur district, Karnataka. University of Agricultural Sciences, Dharwad, Karnataka (India).

Heady E O. 1968. Economics of Agricultural production and resource use. Prentice Hall of India Private Limited, New Delhi.

Hiremath G M. 1993, Economics of production and marketing of lime in Bijapur district, Karnataka. M.Sc. (Agri.) Thesis, University of Agricultural Sciences, Dharwad, Karnataka (India).

Hugar L B, Murthy P S S, Umesh K B and Reddy B S. 1991. Economic feasibility of guava cultivation under scientific management– empirical evidence. Agricultural Situation in

India, 46 (4): 211-214.

Indiradevi P, Thomas E K and Thomas J K. 1980. Growth and supply response of banana in Kerala. Agricultural Situation in India, 45 (4): 239-242.

Kahlon A S and Acharya S S.1967. Study on management input in farming. Indian Journal of

Agricultural Economics. XXII (3): 45-53

Kareemulla K, Tewari R K, Singh B and Kuldeep Kumar. 2007, Production and marketing of Indian Gooseberry – Aonla (Emblica officinalis Gaertn.) in Pratapgarh district of U.P. Indian Journal of Agricultural Marketing, 21 (3): 41-45.

Kaujalagi C B and Kunnal L B. 1992. Input use efficiency in pomegranate orchards in Bijapur district, Karnataka. Indian Journal of Agricultural Economics, 47 (3): 527-530.

Kaul G L. 1997. Horticulture in India: production marketing and processing. Indian Journal

of Agricultural Economics, 52(3): 561-568.

Koujalagi C B.1990. An economic analysis of production and marketing of pomegranate in Bijapur district, Karnataka. M.Sc. (Ag) Thesis, UAS, Dharwad, Karnataka (India)

Koujalagi S B and Kunnal L B. 1992. Input use efficiency in pomegranate orchards in Bijapur district, Karnataka. Indian Journal of Agricultural Economics, 47 (3): 527-530.

Kumar Suresh, Anshuman Karol, Singh Ranveer and Vaidya C S. 2007. Cost and return from apple cultivation: A study in Himachal Pradesh. Agricultural Situation in India, 64(7): 307-313

Lewis A W. 1978. Evolution of the international economic order. Princeton University Press.

103

Mahella Y P and Galgalikar V D. 1987. Cost of establishment of kagzi lime orchards. Indian

Journal of Agricultural Economics, 42(3): 469.

Marini R P. 1997. Growing peaches and nectarines in Virginia, Virginia cooperative extension. Horticulture Publication, pp 422–519

Masoodi M A. 2003. Agriculture in Jammu and Kashmir-a perspective. Mohisraw Book Series, Srinagar.

Mattioli P.1998. Estimation of damage caused by frost and hoarfrost in apple. Informatore-

Agrario.; 54(4): 115-125

Maurya. 1996. Profitability of banana production in Wajipur district of Bihar state. Ind.J.

Agril.Econ., 30 (2): 120-123.

Menon S K.1979. Resource use and productivity of grape cultivation on Bangalore north taluk of Bangalore district. M.Sc.(Agri.) Thesis, University of Agricultural Sciences, Bangalore.

Mishra J P, Ramachandra and Rawat S K. 2000. Production and marketing of banana in Gorakhpur district of Uttar Pradesh. Agricultural. Marketing, pp. 36-40.

More S S. 1999, Economics of production and marketing of banana in Maharashtra state. M. Sc. (Agri.) Thesis, Univ. Agric. Sci., Dharwad, Karnataka (India).

Nadda A L. 1987. Supply response of perennial crops - a study of Himachal apples. Indian

Journal of Agricultural Economics; 42(3): July-Sept. 446-453.

Nighot M N, Alshi M R and Joshi C K. 1987. Economics of production of Nagpur oranges. Indian Journal of Agricultural Economics, 42(3): 468.

Patil B N, Suryavanshi S D and Desale P G. 1987. Acreage response of banana in Jalagaon district of western Maharashtra. Ind. J. Agric. Econ., 42 (3): 458-459.

Patil T Y, Hinge B J and Rajamane K D. 1969. Economic problems of horticultural plantations in Maharashtra. Indian J. Agric. Econ., 24(4) : 249-255.

Pawan Dahiya, Singh I J and Rai K N. 2002. Cost benefit analysis of ber cultivation in Rohtak district of Haryana. Ind. J. of Agril. Making, 16 (2): 49-52.

Prashar R S, Manjusha Thomas and Negi Y S. 2006. Estimation of Supply Function for Himachal Apples. Indian Journal of Economics: 434-487.

Raikar N A. 1990. Investment in production and marketing of cashew in Karnataka. M.Sc. (Agri.) Thesis, Univ. Agric. Sci., Dharwad, Karnataka (India).

Rajesh D B. 2006. Economic evaluation of Vanilla cultivation in Uttar Kannada district of Karnataka, M. Sc. (Agri.) Thesis, Univ. Agric. Sci., Dharwad, Karnataka (India).

Raju V T, Dasari V S and Ravishankar C. 1987, Spatio-temporal growth and distribution of fruit crops in Andhra Pradesh. Ind. J. Agric. Econ., 42 (4): 438-445.

Rana R S, Bhagata R S, Kalia V and Lal H .2009.Impact of climate change on shift of apple belt in himachal Pradesh. ISPRS Archives XXXVIII-8/W3 Workshop Proceedings: Impact of Climate Change on Agriculture

Rana R S, Jain S C and Gupta K K. 1978. Economic optima in Apple cultivation – A case study of Kumarsain Block of Shimla District. Financing Agriculture, X(2) : 13-26.

104

Randev A K. 2009. Impact of climate change on apple productivity in Himachal Pradesh-India. 60th International Executive Council Meeting & 5th Asian Regional Conference, New Delhi, India.9p

Randev A K, Tewari S C and Sharma R K. 1992. Rationale of resource use in apple cultivation - a case study of tribal area in Himachal Pradesh. Indian Journal of

Agricultural Economics, 47(4): 669-676.

Rane A A and Bagade S R. 2006. Economics of production and marketing of banana in Sindhur district Maharashtra. Indian Journal of Agricultural marketing, 20 (1): 38-45.

Rauf A. 2009. Production and marketing of apple in Himachal Pradesh and Jammu & Kashmir: a comparative study. P.hD. Thesis. Dr.YSPUHF, Nauni, Solan (HP)

Reddy M R. 1989. Pattern of investment and returns in citrus orchards: a study of sweet orange in Prakasam district, Andhra Pradesh. M.Sc. (Agri.) Thesis, University of agricultural Sciences, Dharwad.

Saraswat and Rane, 2006, Production and marketing of peach fruit – A case study of Rajgarh village. Indian Journal of Agricultural marketing, 8 (5): 318-325.

Saraswat S P. 1997. Organization of production and marketing of apple in Himachal Pradesh: A case study of Kirari village. Ind. J. of Agril. Econ., 52 (3): 630-631.

Shahuren Ismail. 2005. Productivity management tools for enhanced export competitiveness: In: the seminar on improvement of agricultural marketing systems for enhancing international competitiveness. Apo seminar on improvement of agricultural marketing systems for enhancing international competitiveness, Pakistan: 68-80

Sharma G D and Pandey. H.K., 1972, Economics of production and marketing: A case

study. Indian Hortic., 17(1) : 5-6.

Sharma H R. 2011. Crop diversification in Himachal Pradesh: patterns, determinants and challenges : policy options and investment priorities for accelerating agricultural productivity and development in India, IGIDR Proceedings/Projects Series. India International Centre, New Delhi.p-19

Sharma K R. 1983. An Econometric Study of Apple Production and Marketing in Shimla District of Himachal Pradesh. M.Sc.Thesis (unpublished). Himachal Pradesh Krishi Vishva Vidyalaya, Palampur.

Sharma L R and Chand M. 1987. Citrus cultivation in Himachal Pradesh - An economic appraisal. Indian Journal of Agricultural Economics, 42(3): 487.

Sharma S and Parihar R S.1994, Marketing of apricot in Jammu and Kashmir. Ind. J. of Agril.

Mkting, 8 (1): 23-27.

Shivanand S G. 2002. Performance of banana plantation in north Karnataka. An economic analysis. M.Sc. (Agri.) Thesis, Univ. Agril. Sci., Dharwad.

Sikka B K and Swarup R. 1985. Economics of apple production in Himachal Pradesh. Report Agro-Economic Research Center HPU, Shimla-5.

Sikka B K, Singh R and Kumar R. 1992. Profitability of apple cultivation in Himachal Pradesh. Agricultural Situation in India, 637-640.

Silva M De C A, Da Tarsitano M A A and Bolani A C. 2005. Technical and economical analysis of apple and banana tree (Musa spp.) culture, in the north-west region of Sao Paulo state. Revista – Brasileira de Fruticultura, 27 (1): 139-142.

105

Singh C and Vashist A K. 1994. Resource allocative efficiency on various sizes of farms in Salem district (Tamil Nadu). Agricultural Economic Research Review, 7(2): 141-145.

Singh J. 2004. Low productivity trend in Apple growing state of India Himachal Pradesh – Contributing factors. Apple growing and livelihood in the Himalayas Basin. New Delhi. Singh, Mahinder Pal Singh, Cannaught Place 43-56

Singh K, Grover D K, Vatta K and Kumar S. 2001. Pattern of production and marketing of fruit crops in Punjab. Indian Journal of Agriculture Marketing, 15(2): 11-17

Singh M and Mathur V C. 2008. Structural changes in Horticulture: Retrospect and Prospects for 11th Five Year Plan. Indian Journal of Agricultural Economics. 63(3): 333.

Singh P T. 2011. Apple production in Himachal Pradesh: impending crisis. Economic and

Political Weekly, 25: 10-12

Singh R, Meenakshi and Sikka B K.1990. Economics of apple production in Himachal Pradesh. Indian Journal of Agricultural Economics.pp.163-171

Sinthilnathan S and Srinivasan R. 1994. Production and marketing of poovan banana in Trichirapalli district of Tamil Nadu. Indian Journal of Agricultural marketing, 8 (1): 46-53.

Srinivas T, Raju V T, Shareef S M and Naidu G M. 1994. Economic analysis of cashew nut production in Prakasam district of Andhra Pradesh. Agricultural Situation in Indian, 69(3): 198-199.

Subramanyam K V and Mohandas V. 1982. Economic evaluation of Coorg Mandarin (orange) in Karnataka. Indian J. Agric. Econ., 137: 70-76.

Subramanyam K V. 1987. Economics of investment in mango cultivation in Karnataka. The Mysore Journal of Agricultural Sciences, 211: 96-200.

Sundaravardarajan K R and Jaganmohan K R. 2002. Marketing cost, margin, price spread and marketing efficiency of cashew in Tamil Nadu. Agri. Situation in India, 59 (1): 9-16.

Sunderesan R and Thanasekaran M. 1984. Production and marketing of grapes in Madurai

district. Indian Journal of Marketing, 14: 26-29.

Tewari S C, Randev A K and Sharma A K. 1987. Rationale of resource use in apple cultivation: A case study of tribal areas in Himachal Pradesh. Indian Journal of

Economics, 42(3): 456.

Thakur D S, Sharma H R and Saibabu M V S. 1987. Economic feasibility of kinnow plantation in Himachal Pradesh. Indian Journal of Agricultural Economics, 42(3): 459.

Umesh K B, Vishnuvardhana and Thirumalaraju G T. 2005. Business opportunities in cashew industry. Agro-India. The Integrated Agribusiness Magazine, 8 (1): 14-17.

Vedwan N. 2006. Culture, climate and the environment: local knowledge and perception of climate change among apple growers in northwestern India. Journal of Ecological

Anthropology, Volume 6:4-18

Wani M H, Mir N A and Bhat A R. 1994. Economic viability of apple orchards in Kashmir. Agricultural Situation in India, 64(9): 659-662.

Wani M H, Singh R L, Bhat A R and Mir A N. 1993. Resource use efficiency and factor productivity in apple. Agricultural Economic Research Review, 6(1): 26-35.

106

Dr Y S Parmar University of Horticulture and Forestry,

Nauni, Solan (HP) 173 230

Department of Social Sciences

Title of Thesis : “Productivity Analysis of Apple Orchards in

Shimla District of Himachal Pradesh”

Name of the Student : K. Kireeti

Admission Number : F-2011-02-M

Major Advisor : Dr L. R. Sharma

Major Field : Agricultural Economics

Minor Field(s) : i) Environmental Science ii) Fruit Science

Degree Awarded : M.Sc.

Year of Award of Degree : 2013

No. of pages in Thesis : 106+VII

No. of words in Abstract : 479

ABSTRACT

The present study entitled “Productivity analysis of apple orchards in Shimla District of Himachal Pradesh” was undertaken with a vision to study the status of apple productivity. Narkanda was selected randomly as the ultimate block of study from the Shimla district of Himachal Pradesh state. The objectives were aimed at analyzing the trends in apple production and productivity, cost of apple cultivation and the factors affecting the apple production and productivity. The study sample was drawn using random sampling method in four stages making a total of 70 orchardist households from five altitudinal zones namely ≤ 1500 m, 1500-2000, 2000-2500, 2500 -3000 and 3000 m amsl respectively in the study area. General mathematical and statistical methods were utilized to perform the present study. Overall multiple regression analysis was carried to know the factors influencing the apple production and for evaluating the economic efficiency of resources. The literacy situation revealed that nearly 89 percent family members are literates in the study area. The average MSI value was calculated to 99.58 at overall level. It was observed that India has registered a compound growth rate of 1.1 MT/ha which is at par with the world average of 1.2 MT/ha in the context of apple productivity, whereas in Himachal Pradesh it was 0.03 MT/ha during the time period 1973-74 to 2011-12. The maximum mean productivity was noticed in France with an apple yield of 33.60 MT/ha over the 39 years. Among the districts of Himachal Pradesh, Shimla and Kinnaur have shown positive trend in all aspects of apple cultivation. The apple had the pride of having more than 89 per cent of the orchard area in the study region. The productivity analysis in different elevations in the study area revealed that the apple productivities were at par with each other except of that in the lowest elevation

(≤ 1500 m). Majority of sampled orchardists in the study region, fall in the income scale of T 2-5 lakhs. On an average per tree establishment cost worked out to R 3318.19 in the study area. Maintenance cost of bearing apple per hundred in the study area ranged between R 60,169.88 to R 61,769.01in different elevations and net return varied between R 162,817.14 and R 269,362.63.17 in different elevations. However, the mean apple productivity (15.60 MT/ha) in the study area as a whole has shown similarity with that of the world average value. The regression analysis has indicated that there exist a scope to increase the apple productivity in the study block, by increasing the levels of the variables like FYM, Chemical fertilizers, human labour, fixed costs and also that it should stick to optimum no. of sprays for plant protection and plant density must be maintained. The findings of the present study strongly recommend the optimum use of the resources in order to adapt to the adverse conditions and attain desired growth in apple cultivation and ultimately the productivity.

Signature of the Major Advisor Signature of the Student

Countersigned

Professor and Head

Department of Social Sciences

Dr Y S Parmar University of Horticulture & Forestry

Nauni, Solan, (HP) - 173 230

i

APPENDIX-I

Bock wise Apple area ( ha) in Shimla district

Sr. No. Block/District Apple Area % of Apple area of

district

1 Jubbal-Kotkhai 7942.23 21.1

2 Rohru 6142.35 16.32

3 Narkanda 5373.91 14.28

4 Theog 4597.4 12.21

5 Rampur 4066.27 10.8

6 Chopal 3819.57 10.15

7 Chirgaon 3552.25 9.43

8 Mashobra 2136.56 5.67

Shimla Dist. 37630.54

Block wise Area ( ha) under different categories of apple in Shimla district

Sr. No. Block/District Area under categories

Sparse Moderate Dense

1 Jubbal-Kotkhai 1421.97 5340.84 1179.42

2 Rohru 2248.53 3182.11 711.71

3 Narkanda 97.57 3002.63 2273.7

4 Theog 2654.44 1575.24 367.72

5 Rampur 251.37 2218.98 1595.92

6 Chopal 1217.49 2292.02 310.06

7 Chirgaon 1689.64 1497.02 365.59

8 Mashobra 78.51 1865.38 192.67

Shimla Dist. 9659.52 20974.22 6996.79

Block wise Apple area ( ha.) in relation to Elevation in Shimla district

Sr. No. Block/ District

Apple area in Elevation

<1500m 1500-

2000m

2000-

2500m

2500-

3000m >3000m

1500-

2500m

1 Jubbal- Kotkhai 74.36 (0.9)

1961.63 (24.7)

4800.33 (60.4)

987.96 (12.4)

104.31 (1.3)

6761.96 (85.1)

2 Rohru 18.03 (0.3)

1670.92 (27.2)

3485.32 (56.7)

916.36 (14.9)

40.72 (0.7)

5156.24 (83.9)

3 Narkanda 226.48

(4.2) 1705.82

(31.7) 2520.75

(46.9) 852.19 (15.9)

57.6 (1.1)

4226.57 (78.6)

4 Theog 313.11

(6.8) 1756.8 (38.2)

2295.07 (49.9)

223.60 (4.9)

0.12 (0.0)

4051.87 (88.1)

5 Rampur 42.68 (1.0)

789.87 (19.4)

2074.29 (51.0)

711.53 (17.4)

438.62 (10.8)

2864.16 (70.4)

6 Chopal 102.18

(2.7) 1015.55

(26.6) 2335.0 (61.1)

276.48 (7.2)

84.21 (2.2)

3350.5 (87.7)

7 Chirgaon 12.79

(0.4) 301.02

(8.5) 1845.16

(51.9) 1023.49

(28.8) 363.46 (10.2)

2146.18 (60.4)

8 Mashobra 967.80 (47.5)

985.71 (48.4)

174.30 (8.6)

5.01 (0.2)

0.00 (0.00)

1160.01 (56.9)

Shimla Dist.

1757.43 (4.7)

10187.31 (27.1)

19530.2 (51.9)

4996.63 (13.3)

1089.04 (2.9)

29717.51 (79.0)

Values in Parenthesis are percentage (%) of total apple are

ii

Apple area ( ha.) in relation to Aspect in Shimla district and its blocks.

S. No. Block/

District

Apple Area in Aspect

North- East

(NE)

South- East

(SE)

South- West

(SW)

North-West

(NW) NE+SE

1 Jubbal- Kotkhai

2728.11 (32.0)

2739.74 (32.2)

920.91 (10.8)

1471.45 (17.3)

5467.85 (64.2)

2 Rohru 2002.00

(32.6) 2646.55

(43.1) 925.80 (15.1)

525.20 (8.6)

4648.55 (75.7)

3 Narkanda 1842.68

(34.3) 1172.68

(21.8) 977.13 (18.2)

1311.90 (24.4)

3015.36 (56.1)

4 Theog 1793.55

(39.0) 1871.89

(40.7) 623.40 (13.6)

278.61 (6.1)

3665.44 (79.7)

5 Rampur 1134.60

(27.9) 1530.37

(37.6) 656.87 (16.2)

704.85 (17.3)

2664.97 (65.5)

6 Chopal 1463.27

(38.3) 1126.3 (29.5)

658.02 (17.2)

509.24 (13.3)

2589.57 (67.8)

7 Chirgaon 1219.68

(34.3) 1589.53

(44.7) 408.04 (11.5)

309.43 (8.7)

2809.21 (79.1)

8 Mashobra 527.10 (25.9)

628.13 (30.8)

608.49 (29.9)

355.33 (17.4)

1155.23 (56.7)

Shimla Dist.

12711.0 (33.8)

13305.20 (35.4)

5778.66 (15.4)

5466.01 (14.5)

26016.2 (69.1)

Note: Values in Parenthesis are percentage (%) of total apple area.

Apple area ( ha.) in relation to Slope in Shimla district and its blocks

S. No. Block/

District

Apple Area In Slope

<10 20-Nov 20-30 30-40 >40 21-40°

1 Jubbal- Kotkhai

277.69 (3.5)

1664.58 (21.0)

3266.15 (41.1)

2064.27 (26.0)

669.54 (8.4)

5330.42 (62. 1)

2 Rohru 313.11 1577.38 2450.25 1379.98 421.63 5630.23

5.1 25.7 39.9 22.56 6.9 65.6

3 Narkanda 229.71 1345.65 2063.29 1247.27 488.51 3310.56

4.3 25 38.4 23.2 9.1 63.4

4 Theog 239.79

(5.2) 1305.50

(28.4 ) 1947.51

(42.4 ) 905.64 (19.7)

198.95 (4.3)

2853.15 (70.8)

5 Rampur 388.86 934.33 1382.98 952.53 407.58 2335.51

9.6 23 34 23.4 10 57

6 Chopal 123.55 476.58 1145.66 1265.76 808.01 2411.42

3.2 12.5 30 33.1 21.2 (42. 5)

7 Chirgaon 144.46

(4. 1) 677.43 (19.1)

1258.27 (35.4)

991.07 (27.96)

481.02 (13.5)

2249.34 (54.5)

8 Mashobra 167.32

(8.2 ) 556.65 (27.3)

749.84 (36.8)

479.00 (23.5)

183.74 (9.0)

1228.84 (64.2)

Shimla 1884.50

(5.0)

8538.11

(22.7)

14263.95

(37.9)

9285.52

(24.7 )

3658.98

(9.7)

23549.47

(60.6)

iii

Apple area, production and productivity of Himachal Pradesh State during

1973-74 to 2011-12

Himachal Pradesh

Year Total Area (ha.) Total production (MT.) Productivity (MT/ha.)

1973-74 32127 128676 4.0052

1974-75 33628 43311 1.2879

1975-76 35031 200000 5.7092

1976-77 36809 120634 3.2773

1977-78 38900 131617 3.3835

1978-79 40630 121896 3.0001

1779-80 41914 135476 3.2322

1980-81 43331 118012 2.7235

1981-82 45335 306795 6.7673

1982-83 47354 139086 2.9372

1983-84 48292 257913 5.3407

1984-85 49840 170629 3.4235

1985-86 51093 174618 3.4177

1986-87 52399 359321 6.8574

1987-88 54912 259277 4.7217

1988-89 57456 165156 2.8745

1989-90 59987 431428 7.1920

1990-91 62827 342062 5.4445

1991-92 66766 301731 4.5192

1992-93 69438 279051 4.0187

1993-94 72405 294734 4.0706

1994-95 75468 122862 1.6280

1995-96 78288 276681 3.5341

1996-97 80339 288539 3.5915

1997-98 82418 234253 2.8423

1998-99 85628 393653 4.5972

1999-00 88669 49129 0.5541

2000-01 89743 376736 4.1979

2001-02 92816 180528 1.9450

2002-03 81626 348263 4.2666

2003-04 84108 459492 5.4631

2004-05 86562 527601 6.0951

2005-06 92159 540356 5.8633

2006-07 91800 268402 2.9238

2007-08 94722 592575 6.2559

2008-09 97434 510160 5.2360

2009-10 99560 280104 2.8134

2010-11 112479 892111 7.9314

2011-12 114939 275036 2.3929

Source: Directorate of Horticulture Himachal Pradesh

iv

District wise Area of apple in Himachal Pradesh during (1973 -74 to 2012-2013)

Years Chamba Kangra Kinnaur Kullu Lahaul

& Spiti Mandi Shimla Solan Sirmour

1973-74 826 335 852 7536 0 4616 15519 156 2287

1974-75 865 335 935 8101 0 4946 15944 175 2327

1975-76 920 351 1049 8573 29 5354 16140 198 2417

1976-77 1032 394 1234 9000 31 5660 16600 216 2642

1977-78 1308 394 1420 9343 32 6041 17352 336 2674

1978-79 1458 394 1703 9669 36 6290 17855 438 2787

1779-80 1529 401 1843 9938 42 6468 18355 470 2868

1980-81 1582 416 2026 10264 48 6728 18887 483 2897

1981-82 1854 436 2203 10767 52 7106 19422 490 3005

1982-83 2180 472 2403 11199 56 7303 20122 493 3126

1983-84 2345 487 2826 11322 58 7344 20255 494 3161

1984-85 2532 495 2929 11574 63 7504 21066 500 3177

1985-86 2698 510 3056 11814 71 7604 21611 505 3224

1986-87 2848 515 3279 12086 85 7864 21939 506 3277

1987-88 3031 522 3572 13109 95 8318 22453 512 3300

1988-89 3105 540 3839 13703 107 8972 23266 517 3407

1989-90 3490 560 4043 14244 112 9513 23980 523 3522

1990-91 3980 589 4302 14342 131 10141 25191 528 3623

1991-92 4624 592 4431 15386 145 10638 26754 529 3667

1992-93 5066 596 4608 15770 156 11054 27916 540 3732

1993-94 5515 598 4770 16211 175 11681 29123 544 3788

1994-95 6054 602 5116 16897 216 12105 30114 546 3818

1995-96 6480 599 5332 17541 281 12431 31213 547 3864

1996-97 6809 602 5516 17952 334 12749 31956 548 3873

1997-98 7655 600 5010 18552 342 12872 32908 550 3929

1998-99 8307 600 5836 19035 407 13232 33707 550 3954

1999-00 9207 603 6249 19383 475 13727 34465 552 4008

2000-01 9554 603 6369 19156 536 13853 35052 553 4067

2001-02 10485 603 6604 19886 608 14065 35905 554 4106

2002-03 9020 382 6840 20116 345 13957 27678 110 3178

2003-04 9451 404 7392 20383 434 14365 28247 111 3321

2004-05 9853 410 8312 20560 489 14610 28775 112 3441

2005-06 10441 430 11754 20821 621 14832 29671 112 3477

2006-07 11023 444 8473 21824 685 14964 30666 112 3609

2007-08 11473 453 8874 23179 734 15135 31323 108 3443

2008-09 11842 454 9671 23663 812 15353 32195 100 3344

2009-10 11990 450 9838 23870 959 15531 33579 95 3248

2010-11 12196 431 9999 24002 12321 15687 34612 87 3144

2011-12 12509 430 10100 24503 12712 15842 35778 85 2980

Source: Directorate of Horticulture Himachal Pradesh

v

District wise production of apple in Himachal Pradesh during (1973 -74 to 2012-2013)

(Metric Tonnes)

Years Chamba Kangra Kinnaur Kullu Lahaul

& Spiti Mandi Shimla Solan Sirmour

1973-74 1564 1215 2985 30214 0 31316 50000 802 10580

1974-75 593 968 432 10516 0 2023 23923 66 4790

1975-76 2737 1568 6622 62931 0 18892 97031 946 9273

1976-77 1178 1406 2990 31387 0 2131 81275 74 193

1977-78 1044 1214 3203 46853 0 6129 72113 292 769

1978-79 1375 813 4602 30741 0 3003 80410 351 601

1779-80 2194 710 4551 42060 0 7524 76981 416 1040

1980-81 1735 694 7151 29058 0 4190 73521 504 1159

1981-82 2795 822 7765 72892 0 10665 209240 627 1989

1982-83 3186 513 4612 33017 5 4302 92617 179 655

1983-84 5448 149 9529 50025 30 12861 178592 236 1043

1984-85 777 79 5323 26387 20 6489 129670 148 1736

1985-86 3719 27 9788 60236 25 11854 87593 175 1201

1986-87 6427 31 11066 83926 42 17021 238364 212 2232

1987-88 3716 54 7326 69036 26 6846 171522 105 646

1988-89 2365 48 10045 38651 17 7876 105176 101 877

1989-90 40621 361 11582 123690 42 10123 243938 121 950

1990-91 2661 422 9150 70857 27 15359 243042 70 474

1991-92 4712 130 16530 64101 50 7389 208247 256 316

1992-93 2079 190 12395 62925 58 8016 191961 180 1247

1993-94 4982 301 23190 84758 119 8192 172851 53 288

1994-95 1090 169 16345 20476 60 7588 75250 112 1772

1995-96 5014 196 18219 48604 55 4612 199373 71 537

1996-97 2502 289 17902 59429 61 6216 201781 64 295

1997-98 7381 213 24639 69649 65 4185 127341 38 742

1998-99 5685 442 18509 98219 61 11255 258621 416 445

1999-00 1761 110 15432 7398 56 3726 20536 33 77

2000-01 4480 295 21793 58926 113 16612 274056 99 362

2001-02 8650 300 18808 30433 112 10905 110857 61 402

2002-03 4238 285 22177 81489 41 10147 229207 87 592

2003-04 8811 595 33074 98781 135 23261 294402 66 367

2004-05 7564 710 38066 141844 209 20131 318449 68 560

2005-06 10357 550 41101 140633 193 36631 310252 59 580

2006-07 9864 530 39450 98654 154 34251 84902 57 540

2007-08 7744 423 41550 160124 473 32283 349262 27 689

2008-09 8640 502 55169 77409 577 30300 336753 34 776

2009-10 3962 401 40289 54385 193 8659 171945 28 242

2010-11 10789 425 63781 191212 194 22315 602684 38 673

2011-12 3074 400 53290 44619 126 4417 168634 19 457

Source: Directorate of Horticulture Himachal Pradesh

vi

District wise productivity of apple in Himachal Pradesh during (1973 -74 to 2012-2013)

Years Chamba Kangra Kinnaur Kullu Lahaul &

Spiti Mandi Shimla Solan Sirmour

1973-74 1.8935 3.6269 3.5035 4.0093 0.0001 6.7842 3.2219 5.1410 4.6261

1974-75 0.6855 2.8896 0.4620 1.2981 0.0001 0.4090 1.5004 0.3771 2.0584

1975-76 2.9750 4.4672 6.3127 7.3406 0.0001 3.5286 6.0118 4.7778 3.8366

1976-77 1.1415 3.5685 2.4230 3.4874 0.0001 0.3765 4.8961 0.3426 0.0731

1977-78 0.7982 3.0812 2.2556 5.0148 0.0001 1.0146 4.1559 0.8690 0.2876

1978-79 0.9431 2.0635 2.7023 3.1793 0.0001 0.4774 4.5035 0.8014 0.2156

1779-80 1.4349 1.7706 2.4693 4.2322 0.0001 1.1633 4.1940 0.8851 0.3626

1980-81 1.0967 1.6683 3.5296 2.8311 0.0001 0.6228 3.8927 1.0435 0.4001

1981-82 1.5076 1.8853 3.5247 6.7699 0.0001 1.5008 10.7733 1.2796 0.6619

1982-83 1.4615 1.0869 1.9193 2.9482 0.0893 0.5891 4.6028 0.3631 0.2095

1983-84 2.3232 0.3060 3.3719 4.4184 0.5172 1.7512 8.8172 0.4777 0.3300

1984-85 0.3069 0.1596 1.8173 2.2799 0.3175 0.8647 6.1554 0.2960 0.5464

1985-86 1.3784 0.0529 3.2029 5.0987 0.3521 1.5589 4.0532 0.3465 0.3725

1986-87 2.2567 0.0602 3.3748 6.9441 0.4941 2.1644 10.8649 0.4190 0.6811

1987-88 1.2260 0.1034 2.0510 5.2663 0.2737 0.8230 7.6392 0.2051 0.1958

1988-89 0.7617 0.0889 2.6166 2.8206 0.1589 0.8778 4.5206 0.1954 0.2574

1989-90 11.6393 0.6446 2.8647 8.6837 0.3750 1.0641 10.1726 0.2314 0.2697

1990-91 0.6686 0.7165 2.1269 4.9405 0.2061 1.5145 9.6480 0.1326 0.1308

1991-92 1.0190 0.2196 3.7305 4.1662 0.3448 0.6946 7.7838 0.4839 0.0862

1992-93 0.4104 0.3188 2.6899 3.9902 0.3718 0.7252 6.8764 0.3333 0.3341

1993-94 0.9034 0.5033 4.8616 5.2284 0.6800 0.7013 5.9352 0.0974 0.0760

1994-95 0.1800 0.2807 3.1949 1.2118 0.2778 0.6268 2.4988 0.2051 0.4641

1995-96 0.7738 0.3272 3.4169 2.7709 0.1957 0.3710 6.3875 0.1298 0.1390

1996-97 0.3675 0.4801 3.2455 3.3104 0.1826 0.4876 6.3143 0.1168 0.0762

1997-98 0.9642 0.3550 4.9180 3.7543 0.1901 0.3251 3.8696 0.0691 0.1889

1998-99 0.6844 0.7367 3.1715 5.1599 0.1499 0.8506 7.6726 0.7564 0.1125

1999-00 0.1913 0.1824 2.4695 0.3817 0.1179 0.2714 0.5959 0.0598 0.0192

2000-01 0.4689 0.4892 3.4217 3.0761 0.2108 1.1992 7.8186 0.1790 0.0890

2001-02 0.8250 0.4975 2.8480 1.5304 0.1842 0.7753 3.0875 0.1101 0.0979

2002-03 0.4698 0.7461 3.2423 4.0510 0.1188 0.7270 8.2812 0.7909 0.1863

2003-04 0.9323 1.4728 4.4743 4.8462 0.3111 1.6193 10.4224 0.5946 0.1105

2004-05 0.7677 1.7317 4.5796 6.8990 0.4274 1.3779 11.0669 0.6071 0.1627

2005-06 0.9920 1.2791 3.4968 6.7544 0.3108 2.4697 10.4564 0.5268 0.1668

2006-07 0.8949 1.1937 4.6560 4.5204 0.2248 2.2889 2.7686 0.5089 0.1496

2007-08 0.6750 0.9338 4.6822 6.9081 0.6444 2.1330 11.1503 0.2500 0.2001

2008-09 0.7296 1.1057 5.7046 3.2713 0.7106 1.9736 10.4598 0.3400 0.2321

2009-10 0.3304 0.8911 4.0952 2.2784 0.2013 0.5575 5.1206 0.2947 0.0745

2010-11 0.8846 0.9861 6.3787 7.9665 0.0157 1.4225 17.4126 0.4368 0.2141

2011-12 0.2457 0.9302 5.2762 1.8210 0.0099 0.2788 4.7133 0.2235 0.1534

vii

Apple productivity of major apple producing countries during period 1973-2011

Year Brazil Chile China France India Iran Italy Turkey USA

1973 5.89 10.50 3.03 39.54 5.09 4.00 27.33 11.49 17.59

1974 6.18 10.60 3.01 34.54 5.46 3.95 24.69 12.61 18.62

1975 6.67 10.38 3.27 40.09 4.41 4.00 28.06 11.74 21.34

1976 7.06 10.34 3.21 32.67 4.15 5.43 29.36 12.20 17.99

1977 7.00 11.48 3.65 22.87 4.14 5.88 25.36 10.92 18.73

1978 7.21 12.68 3.81 42.25 4.34 5.00 26.65 12.75 21.06

1979 8.14 14.25 3.72 33.71 5.08 5.79 28.46 15.58 22.35

1980 7.98 15.81 3.20 39.70 4.74 6.00 27.83 15.40 23.98

1981 10.33 17.66 4.15 19.66 5.63 6.94 24.99 15.54 20.91

1982 13.18 19.60 3.38 27.65 6.03 9.72 36.81 16.84 21.76

1983 9.12 20.17 4.89 28.07 5.98 9.48 27.04 18.10 22.12

1984 13.46 21.93 3.89 41.23 5.98 8.42 29.21 19.22 22.06

1985 14.39 21.46 4.78 24.73 5.98 9.17 26.34 18.89 20.60

1986 16.96 23.90 2.85 24.56 7.62 9.39 25.71 18.53 19.91

1987 15.89 26.28 2.96 28.60 4.83 9.80 28.44 16.34 26.62

1988 19.42 27.55 2.62 27.47 5.38 10.15 29.26 18.75 22.07

1989 22.89 28.70 2.67 27.69 5.81 9.58 24.63 17.79 23.22

1990 24.33 30.09 2.65 28.37 5.84 10.84 26.28 18.10 22.86

1991 20.56 32.98 2.74 18.69 6.07 9.56 23.60 17.90 24.37

1992 24.81 32.55 3.43 35.95 5.90 10.77 31.65 20.02 26.03

1993 27.24 30.22 4.03 30.52 6.11 11.52 29.12 19.68 26.06

1994 25.82 27.18 4.14 31.50 6.50 13.88 31.34 19.90 28.06

1995 25.70 26.20 4.74 33.32 5.71 13.67 28.91 19.37 25.63

1996 27.67 27.30 5.71 31.36 5.58 13.66 28.95 20.54 24.89

1997 30.04 21.18 6.07 35.03 5.88 14.17 30.26 23.81 24.72

1998 30.07 25.39 7.43 31.57 5.80 12.31 33.37 23.01 27.92

1999 32.84 31.42 8.53 30.92 5.97 14.81 36.85 23.40 25.86

2000 38.39 22.49 9.06 30.95 4.57 14.54 35.70 22.28 26.92

2001 23.14 31.79 9.69 39.82 5.13 15.83 36.70 22.58 25.28

2002 27.20 32.98 9.93 37.08 4.83 15.66 36.33 20.00 24.20

2003 26.70 35.30 11.10 35.72 5.88 16.00 34.32 22.29 24.98

2004 29.71 36.02 12.61 37.93 7.56 11.50 37.12 17.75 30.36

2005 23.96 37.36 12.70 38.82 7.54 13.22 38.36 21.24 28.70

2006 23.90 38.35 13.72 37.72 8.01 13.02 37.29 16.48 29.91

2007 29.48 40.00 14.20 39.86 6.44 13.17 39.81 19.25 29.03

2008 29.53 36.57 14.98 40.45 7.58 15.46 37.46 19.31 30.80

2009 32.01 31.05 15.46 42.44 7.24 13.79 39.79 20.89 31.28

2010 33.03 31.40 16.18 42.90 6.28 12.76 38.08 15.75 30.46

2011 35.17 33.37 17.54 44.36 10.00 12.38 42.41 18.82 31.95

Source: FAO website’2013

CURRICULUM VITAE

Name : K. Kireeti Father’s Name : K. Uligappa Date of Birth : 25.12.1985 Sex : Male Marital status : Unmarried Nationality : Indian Educational qualifications:

Certificate/Degree Board/University Year

Matriculation C.B.S.E, Board 2001

10+2 ( Bi.P.C) B.I.E.A.P. 2003

B.Sc. (CA & BM) A.N.G.R.A.U. 2009

Whether sponsored by some state/ : NA

Central Govt./Univ./SAARC

Scholarship/Stipend/Fellowship, any : NA other financial assistance received during the study period

( K. Kireeti )