Ashwin Kumar Thumma · 2017. 7. 8. · LiDAR DEM, DSM Remote Sensing – Satellite Imagery Processing Flythrough modeling AM/FM – Utilities Water, Waste water, Sewer, Electric,

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Mapping and Analysis of Post Harvesting Supply Chain Entities of Mango Using GIS

A Case Study for Krishnagiri District, Tamilnadu, India

Ashwin Kumar Thumma, IIC TechnologiesDr. M. Krishnaveni, Anna University


Introduction

Study Area

Approach & Methodology

Materials & Methods

GIS Processing & Analysis

Results

Summary

Conclusion

References

Agenda


Introduction

MANGO - Major tropical fruit of economic, social and political significance to the country

Second largest mango producing district in Tamilnadu is Krishnagiri

Contributes the annual production of 2,00,000 tonnes

Exports mango based products worth of Rs.100 crores in 2003-2004

But 15% of the overall production is lost during post harvesting

Post harvest losses in mango are caused due to the existing problems in the supply

chain network entities like processing units, cold storage units and market outlets


Challenges

Assess the Post Harvest Losses

Methodology to identify the existing Supply Chain Management (SCM) problems

Creation of a Scientific database for mango supply chain

Suitable measures to enhance the efficiency of the supply chain using GIS technique

Develop the Post Harvesting Supply Chain entities like,

Cold storage units

Food processing units and

Market outlets


Study Area

Study area for the Project is Krishnagiri district, Tamilnadu

Geographical area of 5,143 sq. km (Source: www.krishnagiri.tn.)

Largest Mango growing belt in Tamilnadu

Major entities involved in mango production are,

Mango growing fields

Mango Mandis (Godown)

Processing units, Cold Storage units

Market outlets like Uzhavar Sandhai

Local market and Export centers


Study Area


Mango Supply Chain Entities

Location Map of Krishnagiri District Showing Existing Mango Supply Chain Entities


Remote Sensing data of IRS P6- RESOURCESAT LISS III (23.5m resolution)

acquired on 2007 used for the delineation of Mango growing area

Administrative and road network maps of the district are collected from corresponding

government authorities

The geographical co-ordinates (Latitude & Longitude) of the physical entities were

also taken as a primary data using handheld GPS (Geographical Positioning System)

The questionnaire survey was conducted with the various stake holders

The statistical data are collected from the Department of Horticulture, Krishnagiri,

Tamilnadu

Materials & Methods


Mango Processing Units

42 major processing units existing in the district

Weak spatial distribution of processing units in the study area is major concern

Marketing Outlets

Nearly more than 100 mandis, 5 Uzhavar sandais and 2 major exports centre are present

Cold Storage Units

Lack of the cold storage units is the reason for the major losses of mango

Transportation

Road Connectivity Infrastructure between village and district headquarters is less adequate

than existing

Statistical Data


Methodology of the study in the form of Flow Chart

Methodology


Spatial database of physical entities like,

Processing units

Cold storage unit

Mandis

Uzhavar sandai are created using ArcGIS software

Different layers of maps like,

Road Network

Administrative boundary are created and given as input to the system for Analysis

GIS Processing


Overlay Analysis

Administrative boundary & land use are overlaid to find out mango growing areas in study area

Also overlaid with processing units distribution layer map for getting spatial distribution pattern

Network Analysis

To analyze the mango supply chain network from production field to the end user

To reduce the transportation losses in terms of cost as well as time

Buffer Analysis

Minimize transportation losses by finding proximity of roads to processing units, farmer fields..

From the analysis, the potential influence of existing entities is well drawn and projected to find

an optimum location for new establishment of cold storage units

Analysis


Average percentage of supply of mango

from producer to end user drafted

Conducted questionnaire survey to farmers,

government officials & processing units

Flowchart depicts that highest % of mango

is supplied in the form of pulp to consumers

Pulp producing and storing units are given

more importance in this study

Results: Mango Supply Chain

Supply Chain of Mango


Spatial distribution of processing units with the mango growing area

Processing units are

clustered in a single block

Remaining units serve

the other blocks for pulp

production

Hence impact of spatial

distribution of processing

units in the supply chain of

Mango is less

Processing Units Distribution


Site for New Processing Unit

Map of Krishnagiri district showing the location for new processing unit establishment

Farmers in Thally block are isolated from the existing processing units

More money & time to reach industries

Thally block is in need of

new processing units

Site has been

suggested for establishing

a new processing unit

using the buffer analysis


Transportation Facilities

Network analyses for finding out shortest path from mango growing field to processing unit

Transportation loss of

5% in overall production

Network analysis helps

to find out shortest path

NH 66, serves for the

transportation of over

20% of Total product

transported

District is well established with the transportation facilities in terms of National (NH)

and State Highways (SH)


Storage Facilities

Cold storage has very less influence on mango for two major reasons

Mango as a pulp, need no cold storage as their shelf life is around 2 years

Mango as a fruit can be preserved in cold storage but it is costlier than profit itself

Agriculture Marketing and Business Centre, Krishnagiri District, finds a scope for the

cold storage unit for Mango

This is done on trail basis in their office complex which is accompanied by a Mango

Market Complex

Incorporation of Wax coating technology can improve the shelf life of the mango fruit

thus by increasing the national market export scope


Expansion of Production Area

In the supply chain of agricultural commodity, the supply-demand gap is increasing as

the production area is depleted or it is being shifted to some other crops

But in Krishnagiri, even though the mango cultivable area is increasing by 20% every

decade, the productivity finds ups and downs

The shortage of irrigation water is the main factor for the mango production area

increment

Also the most favorable climate (Temperature: 24oC and 27oC, low relative humidity)

satisfies the requirements and thus mango is chosen as an alternative crop for other

field crops, paves a way for production area increment


Market Outlets

The higher demand in the local markets for juices, jam, pickles and candy preparation

is for Banaganapalli, Neelam Totapuri and Rumenia varieties

The National markets demand the high quality mango Fruits (table varieties:

Alfonsa, Imam pasand, Malgova) rather than Pulp

Export market more likely demand the Pulp (varieties: Totapori, Neelam, Naati)

rather than Fruits

Even though the present demand gap is filled by supply in the district, more

production will increase the demand in markets, enhancing the overall revenue in turn


Summary

Incorporating new technologies like GIS and Remote Sensing would pave a way for

easy analysis of supply chain study of any horticultural crops with considerable in

reduction in effort, time and resources

The supply chain network study that was conducted for Mango fruit in Krishnagiri

district of Tamilnadu is drafted and presented

The overlay analysis, buffer analysis and network analysis are done in GIS with

respective layers to obtain the expected output


Conclusion

The supply chain flowchart gives the brief overview of the present scenario and aids

in analyses of issues related to supply chain itself

Thus incorporation of GIS in SCM analysis clearly depicts the effectiveness and the

simplicity of the methodology

Based on these analyses, the recommendations are given which are classified as

primary and secondary recommendations upon their necessity

This study can be created as a dynamic one by incorporating the techniques using

interfaces and database

Though it involves more complexity and cost of creation, it can be utilized for

multipurpose issues related to supply chain management

The wide ability of this study at national level will explores a different perception and

unknown issues that are behind the major problems in SCM


References

[1] Ray S S, Dutta S( 2000), “A GIS and Remote Sensing Based Approach for Siting

Cold Storage Infrastructure for Horticultural Crops: A Case study for Potato Crop in

Bradhaman District, West Bengal”, Journal of the Indian Society of Remote Sensing,

Vol.28, No.2&3

[2] Burrough P A(1966), “Principles of Geographical Information System for Land

Resources Assessment”, Clarendon Press(1986), Vol. 12, pp. 1-3

[3] Farzana and Panhwar (May 2005), “Post Harvest Technology of Mango Fruits, Its

Development, Physiology, Pathology and Marketing in Pakistan”, Vol.13, pp.1-2

[4] Xavier Susai A(January- June 2007), “ Economics Analysis of Mango Pulp Agro

Based Industry in Krishnagiri District, Tamil Nadu”, Political Economy Journal of

India17(1-2), pp 45-5


Documents

Ashwin Kumar Thumma · 2017. 7. 8. · LiDAR DEM, DSM Remote Sensing – Satellite Imagery Processing Flythrough modeling AM/FM – Utilities Water, Waste water, Sewer, Electric,