Improving Methods for Estimating Livestock …gsars.org/wp-content/uploads/2016/12/WP_Improving...Improving Methods for Estimating Livestock Production and Productivity Test Stage:

Improving Methods for Estimating

Livestock Production and Productivity

Test Stage: Fieldwork Report and

Summary Data Analysis

Appendices

Gap Analysis Report

November 2016

Working Paper No. 13

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Improving Methods for Estimating

Livestock Production and

Productivity

Test Stage: Fieldwork Report and

Summary Data Analysis

Appendices

Drafted By

Michael Coleman

Phil Morley

Derek Baker

Jonathan Moss

Table of Contents

1. Analysis of data and indicators produced........................................................ 12

1.1. Summary of indicators produced and data source................................... 12

1.2. Botswana – sheep and goats..................................................................... 16

1.3. Botswana – feed availability..................................................................... 37

1.4. Tanzania – eggs......................................................................................... 54

1.5. Tanzania – milk.......................................................................................... 61

1.6. Indonesia – cattle and goats..................................................................... 65

1.7. Indonesia – milk........................................................................................ 82

2. Actual data from TEST phase fieldwork on costs of data collection.............. 92

List of Tables Table 1.1 Summary of indicators used and data sources, sheep and goats, Botswana................................................................................................... 12 Table 1.2 Summary of indicators used and data sources, feed availability, Botswana................................................................................................... 13 Table 1.3 Summary of indicators used and data sources, eggs, Tanzania ................ 13 Table 1.4 Summary of indicators used and data sources, milk, Tanzania................. 14 Table 1.5 Summary of indicators used and data sources, cattle and goats, Indonesia................................................................................................... 14 Table 1.6 Summary of indicators used and data sources, milk, Indonesia................ 15

Table 1.7 Respondent demographics, Botswana, existing and alternative questionnaires........................................................................................... 16 Table 1.8 Farming context, Botswana, existing and alternative questionnaires............................................................................................ 17 Table 1.9 Average number of sheep on respondent farms, Botswana, existing and alternative.................................................................................................. 18 Table 1.10 Average number of goats on respondent farms, Botswana, existing and alternative questionnaires................................................................ 18 Table 1.11 Average number of sheep by breed, Botswana, existing questionnaire.. 19

Table 1.12 Average number of sheep by breed, Botswana, alternative questionnaire........................................................................................... 19 Table 1.13 Average number of goats by breed, Botswana, existing questionnaire... 19 Table 1.14 Average number of goats by breed, Botswana, alternative questionnaire.......................................................................................... 20 Table 1.15 Average changes to sheep herd numbers (additions and deductions) in the period from October 1st, 2014, to September 30th, 2015, Botswana, existing questionnaire (n = 20)............................................... 21 Table 1.16 Average changes to goat herd numbers (additions and deductions) in the period from October 1st, 2014, to September 30th, 2015, Botswana, existing questionnaire (n = 57).............................................. 22 Table 1.17 Average additions to sheep herd per respondent in the period from October 1st, 2014, to September 30th, 2015, Botswana, alternative questionnaire.......................................................................................... 23 Table 1.18 Average deductions from sheep herd per respondent in the period from October 1st, 2014, to September 30th, 2015, Botswana, alternative questionnaire........................................................................ 24 Table 1.19 Average additions to goat herd per respondent in the period from October 1st, 2014, to September 30th, 2015, Botswana, alternative questionnaire.......................................................................................... 25 Table 1.20 Average deductions from goat herd per respondent in the period from October 1st, 2014, to September 30th, 2015, Botswana, alternative questionnaire........................................................................ 25 Table 1.21 Average numbers of sheep and goats purchased from different sources, Botswana, alternative questionnaire......................................... 27

Table 1.22 Average numbers of sheep and goats sold to different sources, Botswana, alternative questionnaire………………………………………………….

27

Table 1.23 Average numbers of sheep and goats dying from different causes, Botswana, alternative questionnaire.................................................... 29 Table 1.24 Average weight of sheep and goats by age category (kg; respondent estimate, alternative questionnaire)....................................................... 31 Table 1.25 Average body weight (kg) of sheep and goats by gender, Botswana, gold standard data, baseline observation............................................... 32 Table 1.26 Average girth measurement (cm) of sheep and goats by gender, Botswana, gold standard data, baseline observation.............................. 32 Table 1.27 Average shoulder height measurement (cm) of sheep and goats by gender, Botswana, gold standard data, baseline observation................. 32 Table 1.28 Average body condition score of sheep and goats by gender, Botswana, gold standard data, baseline observation.............................. 33 Table 1.29 Average area of different crops grown, Botswana, alternative questionnaire.......................................................................................... 38 Table 1.30 Average grazing area available to respondents using each type of grazing (Ha.), Botswana, alternative questionnaire……………………………… 38 Table 1.31 Average number of days maize crops and/or crop residues used to feed livestock, Botswana, alternative questionnaire............................... 39 Table 1.32 Average number of days bean crops and/or crop residues used to feed livestock, Botswana, alternative questionnaire....................................... 39 Table 1.33 Average number of days livestock grazed by respondents on each type of grazing area, where available.............................................................. 40 Table 1.34 Average ratings of the presence of Seloka Grass and the extent of bush encroachment on different types of grazing land, where 1 = None, 2 = Some, 3 = Moderate, and 4 = Severe)...................................................... 41 Table 1.35 Average quantity of feed of different types purchased by respondents (kg), Botswana, existing questionnaire..................................................... 42 Table 1.36 Average quantity of feed of different types purchased by respondents (kg), Botswana, alternative questionnaire................................................ 43 Table 1.37 Proportion of respondents using different purchased feed types to feed their livestock (multiple response, %), Botswana, existing questionnaire.......................................................................................... 44 Table 1.38 Average number of days different purchased feeds used to feed cattle, Botswana, alternative questionnaire....................................................... 45 Table 1.39 Average number of days different purchased feeds used to feed sheep, Botswana, alternative questionnaire........................................... 46 Table 1.40 Average number of days different purchased feeds used to feed goats, Botswana, alternative questionnaire....................................................... 47 Table 1.41 Number of locations in which herbaceous species were identified (frequent species only reported by number of survey locations)............ 48 Table 1.42 Number of times each herbaceous species identified across all transects where one or more identifications were made (all regions; frequent species only reported by number of times plant identified)................................................................................................. 50

Table 1.43 Herbaceous biomass per site, district and total averages (g/m2)............ 51 Table 1.44 Proportion of estimates of grass palatability per district and across all sites (%).................................................................................................... 51 Table 1.45 Number of transect sites in which herbaceous species were identified (frequent species only reported by number of survey locations)............ 52 Table 1.46 Number of times each woody species identified across all transect sites where one or more identifications were made (all regions; frequent species only reported by number of times plant identified)................................................................................................. 53 Table 1.47 Proportion of woody species identified at various heights (metres) across all transect sites surveyed (all regions; top five species by number of site identifications only; %).................................................... 54 Table 1.48 Average eggs produced per respondent for each of these hen breeds over a 12 month period, for the first or only breed of hen named by each respondent, Tanzania, alternative questionnaire........................... 59 Table 1.49 Estimated average eggs produced per hen over a 12 month period, Tanzania, gold standard daily data.......................................................... 60 Table 1.50 Average daily milk production during lactation period (litres/cow), Tanzania, alternative questionnaire (indigenous and improved cows ... 65 Table 1.51 Numbers of cattle and goats kept by respondents, Indonesia, questionnaire........................................................................................... 66 Table 1.52 Household cattle numbers; types currently present and average numbers looked after and/or owned, Indonesia, questionnaire............. 66 Table 1.53 Responsibility of household members for animal husbandry (n = 408, multiple response), Indonesia, questionnaire......................................... 67 Table 1.54 Average changes to cattle numbers (additions and deductions) since last Eid al-Adha (n = 408), Indonesia, questionnaire……………………………. 68 Table 1.55 Cattle and goat feeding practices; proportion of respondents using various feed type/s over the past 12 months (%; multiple response; n = 408), Indonesia, questionnaire............................................................. 69 Table 1.56 Average body weight (kg) for cattle and goats of various age categories, Indonesia, gold standard data, baseline observation............ 70 Table 1.57 Average girth measurement (cm) for cattle and goats of various age categories, Indonesia, gold standard data, baseline observation............ 70 Table 1.58 Proportion of observed cattle and goats of each sex, by age category (%), Indonesia, gold standard data.......................................................... 75 Table 1.59 Household cattle numbers; types currently present and average numbers looked after and/or owned, Indonesia, questionnaire (n = 60)..................................................................................................... 82 Table 1.60 Average changes to herd numbers (additions and deductions) since last Eid al-Adha, Indonesia, questionnaire (n = 60)……………………………… 83 Table 1.61 Cattle feeding practices; proportion of respondents using various feed type/s over the past 12 months, Indonesia, questionnaire (%; multiple response; n = 60)..................................................................................... 84 Table 1.62 Average daily milk production (litres) for each Body Condition Score for high (n = 60) and low (n = 60) production cows, Indonesia, gold standard data........................................................................................... 89

List of Figures Figure 1.1 Proportion of sheep ‘missing’ between first and second animal measurement visits by district, Botswana, gold standard data (%).... 30

Figure 1.2 Proportion of goats ‘missing’ between first and second animal measurement visits by district, Botswana, gold standard data (%).... 30

Figure 1.3 Body condition score (BCS) for female and male sheep, Botswana, gold standard data, baseline observation (% of goats) ...................... 33

Figure 1.4 Body condition score (BCS) for female and male goats, Botswana, gold standard data, baseline observation (% of goats)....................... 34

Figure 1.5 Average change in weight of male and female sheep and goats between enumerator visits (kg), Botswana, gold standard data........ 35

Figure 1.6 Average change in girth measurement of male and female sheep and goats between enumerator visits (cm), Botswana, gold standard data...................................................................................... 37 Figure 1.7 Average change in shoulder height measurement of male and female sheep and goats between enumerator visits (cm), Botswana, gold standard data............................................................ 37 Figure 1.8 Average number of clutches per hen in last 12 months, Tanzania, alternative questionnaire (n = 68)...................................................... 55 Figure 1.9 Days from beginning of one clutch to beginning of the next clutch, Tanzania, alternative questionnaire (% of respondents; n = 67)......... 56 Figure 1.10 Number of eggs per hen in the last 12 months, including trendline, Tanzania, alternative questionnaire (% of respondents; n = 68)....... 56 Figure 1.11 Number of eggs as a percentage of total 12 month production per respondent, Tanzania, existing questionnaire................................... 57 Figure 1.12 Proportion of respondents producing eggs for each month, Tanzania, existing questionnaire (%)................................................. 58 Figure 1.13 Egg production per month as a percentage of all eggs produced, Tanzania, communal question (%; n = 301)....................................... 58 Figure 1.14 Breeds of hen, multiple response, Tanzania, alternative questionnaire (n = 68)....................................................................... 59 Figure 1.15 Breeds of hen, Tanzania, gold standard daily data (n = 355)............. 60 Figure 1.16 Number of respondents experiencing highest and lowest milk production of their cow/s, for each month of the calendar year, Tanzania, existing questionnaire (n = 76).......................................... 63 Figure 1.17 Milk production per month as a percentage of all milk produced, Tanzania, communal question (%; n = 300)....................................... 63 Figure 1.18 Average daily milk production (litres/cow), Tanzania, alternative questionnaire (indigenous and improved cows)............................... 65 Figure 1.19 Average body condition score (BCS) for cattle of various age categories, Indonesia, gold standard data, baseline observation (% of cattle in each category)................................................................. 71 Figure 1.20 Average body condition score for goats of various age categories, baseline observation (% of goats in each category).......................... 71

Figure 1.21 Average change in weight of cattle of different age categories between enumerator visits (kg), Indonesia, gold standard data.......

72

Figure 1.22 Average change in girth measurement of cattle of different age categories between enumerator visits (cm), Indonesia, gold standard data.................................................................................... 73 Figure 1.23 Average change in weight of goats of different age categories between enumerator visits (kg), Indonesia, gold standard data....... 74 Figure 1.24 Average change in girth measurement of goats of different age categories between enumerator visits (cm), Indonesia, gold standard data.................................................................................... 74 Figure 1.25 Average body condition score by age and sex of cattle, Indonesia, gold standard data, baseline observation......................................... 76 Figure 1.26 Average body weight (kg) by age and sex of cattle, Indonesia, gold standard data, baseline observation................................................. 76 Figure 1.27 Average girth measurement (cm) by age and sex of cattle, Indonesia, gold standard data, baseline observation....................... 77 Figure 1.28 Average body condition score by age and sex of goats, Indonesia, gold standard data, baseline observation......................................... 78 Figure 1.29 Average body weight (kg) by age and sex of goats, Indonesia, gold standard data, baseline observation................................................. 78 Figure 1.30. Average girth measurement (cm) by age and sex of goats, Indonesia, gold standard data, baseline observation...................... 79 Figure 1.31. Average change in weight of female cattle of different age categories between enumerator visits (kg), Indonesia, gold standard data.................................................................................... 80 Figure 1.32. Average change in weight of male cattle of different age categories between enumerator visits (kg), Indonesia, gold standard data.................................................................................... 80 Figure 1.33 Average change in weight of female goats of different age categories between enumerator visits (kg), Indonesia, gold standard data.................................................................................... 81 Figure 1.34 Average change in weight of male goats of different age categories between enumerator visits (kg), Indonesia, gold standard data.................................................................................... 81 Figure 1.35 Number of respondents experiencing highest and lowest milk production of their cow/s, for each month of the calendar year, Indonesia, questionnaire (n = 60)...................................................... 87 Figure 1.36 Average daily milk produced (litres) by high production cows during the data collection period, by age (months) of cow, including trendline, Indonesia, gold standard data........................... 88 Figure 1.37 Average daily milk produced (litres) by low production cows during the data collection period, by age (months) of cow, including trendline, Indonesia, gold standard data........................... 89

Figure 1.38 Average daily milk produced (litres) by high production cows during the data collection period, by girth measurement (cm) of cow, including trendline, Indonesia, gold standard data..................

90

Figure 1.39 Average daily milk produced (litres) by low production cows during the data collection period, by girth measurement (cm) of cow, including trendline, Indonesia, gold standard data.................. 90

12

1 Analysis of Data and

Indicators Produced

1.1. SUMMARY OF INDICATORS PRODUCED AND DATA

SOURCE

Table 1.1. Summary of indicators used and data sources, sheep and goats, Botswana

Indicator Source

Changes to herd structure (births, deaths, acquisitions, disposals) over a 12 month

period Existing

Impact of animal age and time of year/season on changes to herd structure

(births, deaths, acquisitions, disposals) over a 12 month period Alternative

Sources of livestock of different ages and at different times of year Alternative

Purchasers of livestock of different ages and at different times of year Alternative

Causes of death of livestock of different ages and at different times of year Alternative

Average body weight x age category of livestock Alternative

Average body weight x sex of goats or sheep Gold standard

Average girth measurement x sex of goats or sheep Gold standard

Average shoulder height measurement x sex of goats or sheep Gold standard

Average body condition score x sex of goats or sheep Gold standard

Changes in body weight x sex of goats or sheep Gold standard

Changes in girth measurement x sex of goats or sheep Gold standard

Changes in shoulder height measurement x sex of goats or sheep Gold standard

Proportion of animals with each body condition score x sex of goats or sheep Gold standard

13

Table 1.2. Summary of indicators used and data sources, feed availability, Botswana

Indicator Source

Total area sown to (unspecified) feed crops over the last agricultural year Existing

Average total area sown to specific feed crops ‘each year’ Alternative

Quantity of specific livestock feeds purchased annually (kg) Existing,

Alternative

Proportion of farmers using various stock feed options to supplement the diet of cattle,

sheep and goats Existing

Number of days purchased feed used for cattle, sheep and goats, by stock age categories Alternative

Number of days annually each type of livestock uses particular feed crops and their

residue categories Alternative

Number of days annually different types of grazing area grazed by different types of

livestock Alternative

Rating of pasture degradation on a scale from ‘None’ to ‘Severe’ using the contributing

factors of presence of Seloka Grass, and bush encroachment Alternative

Composition and density of herbaceous species across different communal grazing sites Gold

standard

Amount and quality of herbaceous biomass across different communal grazing sites Gold

standard

Composition and density of woody species across different communal grazing sites Gold

standard

Distribution of woody species of different heights across different communal grazing

sites

Gold

standard

Table 1.3. Summary of indicators used and data sources, eggs, Tanzania

Indicator Source

Eggs produced on farm over 12 month period: Number of eggs Sep +

Number of eggs Oct + … + Number of eggs Aug Existing

Eggs produced on farm over 12 month period: Number of hens laying eggs

last 12 months x Average number of clutches per hen x Average number of

eggs per clutch

Alternative

Eggs produced per hen over 12 month period: (Number of eggs counted /

number of days data collection carried out for this hen) x 365 days Gold standard

Eggs produced per hen over 12 month period: Average number of clutches

per hen x Average number of eggs per clutch. Alternative

Times of year of high and low egg production Existing; Communal

Influence of hen breed on egg production Alternative; Gold

standard

14

Table 1.4. Summary of indicators used and data sources, milk, Tanzania

Indicator Source

Daily milk production per cow per day Existing;

Alternative; Gold

standard Annual milk production per cow: Average milk production per cow

per day x Average number of months cows milked for x 30

(days/month)

Existing

Daily milk production per farm: Average milk production per cow per

day x Number of cows milked in the last 12 months Existing

Annual milk production per farm: Average milk production per cow

per day x Number of cows milked in the last 12 months x Average

number of months cows milked for x 30 (days/month)

Existing

Influence of time of day on milk production Gold standard

Influence of time of year on milk production Existing

Influence of breed on milk production Gold standard

Quantity of milk produced per lactation per cow (indigenous and

improved cows) Alternative

Table 1.5. Summary of indicators used and data sources, cattle and goats, Indonesia

Indicator Source

Body weight of cattle or goats by age category: Average body weight x age of

cattle or goats

Gold

standard

Girth measurement of cattle or goats by age category: Average girth

measurement x age of cattle or goats

Gold

standard

Body condition score of cattle or goats by age category: Proportion of cattle or

goats under each BCS x age of cattle or goats

Gold

standard

Changes in body weight of cattle or goats by age category: Changes in body

weight x age of cattle or goats

Gold

standard

Changes in girth measurement of cattle or goats by age category: Changes in

girth measurement x age of cattle or goats

Gold

standard

Changes in body condition score of cattle or goats by age category by sex:

Changes in body condition score x age x sex of cattle or goats

Gold

standard

Changes in body weight of cattle or goats by age category by sex: Changes in

body weight x age x sex of cattle or goats

Gold

standard

Changes in girth measurement of cattle or goats by age category by sex:

Changes in girth measurement x age x sex of cattle or goats

Gold

standard

15

Table 1.6. Summary of indicators used and data sources, milk, Indonesia

Indicator Source

Average annual milk production per cow: Average milk production per

cow per day x Average number of months cows milked for x 30

(days/month)

Questionnaire

Average annual milk production for high production, low production and

all observed cows: Average milk production per [high production/low

production/all observed] cows per day (GS) x Average number of months

cows milked for (Q) x 30 (days/month)

Questionnaire;

Gold standard

Average daily milk production per farm: Average milk production per

cow per day x Number of cows milked in the last 12 months Questionnaire

Average annual milk production per respondent: Average milk

production per cow per day x Number of cows milked in the last 12

months x Average number of months cows milked for x 30 (days)

Questionnaire

Influence of time of day on milk production Gold standard

Influence of productivity of individual cows on daily milk production Gold standard

Influence of time of year on milk production Questionnaire

Influence of body weight, girth measurement, and body condition score

on daily milk production Gold standard

Influence of calf suckling practice on daily milk production Questionnaire

16

1.2. BOTSWANA – SHEEP AND GOATS

1.2.1. PRODUCTION CONTEXT

1.2.2. DEMOGRAPHICS

The existing and alternative sheep and goat questionnaires included a set of

identical demographic questions. Table 1.7 shows relatively balanced gender

participation in both surveys, as well as an average respondent age of

approximately 45 years. Nearly 50 per cent of respondents have completed

secondary schooling or above, although nearly 20 per cent had never attended

school. Average time at school was approximately 10 years.

Table 1.7. Respondent demographics, Botswana, existing and alternative questionnaires

Gender (%) Existing Questionnaire

(n = 62)

Alternative Questionnaire

(n = 60)

Male 50 58.3

Female 50 41.7

Average Age Existing Questionnaire Alternative Questionnaire

Years 45.95 44.48

Level of Schooling

(%)

Existing Questionnaire

(n = 62)


(n = 60)

None 19.4 18.3

Primary 32.3 28.3

Secondary 38.7 41.7

Tertiary 9.7 11.7

Average Time at

School Existing Questionnaire Alternative Questionnaire

Years 9.92 9.82

The questionnaires also included identical questions on the farm context Table

1.8). In both surveys, the majority of respondents only source up to 500 PULA

monthly in income from non-farm sources, though approximately 25 per cent

receive more than 1000 PULA/month. Alternative questionnaire respondents

employed slightly more herdsmen (both family and non-family) on average.

Less than 20 per cent of respondents were members of a small stock association

or similar organisation, while over 75 per cent were likely to be in contact with

an extension officer less than five times per year (approximately 20 per cent

never having contact with an extension officer).

17

Table 1.8. Farming context, Botswana, existing and alternative questionnaires

Amount of monthly non-

farm sourced income

(PULA; %)


(n = 62)


(n = 60)

Up to 500 71 58.3

500 to 1000 6.5 16.7

More than 1000 22.6 25

Average no. herdsmen

employed Existing Questionnaire Alternative Questionnaire

From within the family 1.06 1.1

Non-family members 1 1.2

Membership of small stock

association or similar (%)


(n = 62)


(n = 61)

Yes 16.1 19.7

No 83.9 80.3

No. annual meetings with

extension officers (%)


(n = 62)


(n = 61)

Never 25.8 18

1-5 Times 59.7 62.3

6-10 Times 4.8 9.8

More than 10 Times 9.7 9.8

Respondents to both the existing and alternative questionnaires were asked to

indicate the number of sheep and goats in their possession (adult and young

male and female animals), as well as provide a breakdown of sheep and goat

breeds and numbers. The alternative questionnaire included the facility for

respondents to indicate a wider variety of sheep and goat breeds.

1.2.3. HERD NUMBERS AND CHARACTERISTICS

Average numbers of sheep and goats on farm from both questionnaires are

presented in Table 1.9 and Table 1.10. These show that the average sheep herd

size is larger than the average goat herd size, but that approximately twice as

many respondents to both questionnaires had goats than sheep. Adult females

comprise the greatest proportion of both sheep and goat herds.

18

Table 1.9. Average number of sheep on respondent farms, Botswana, existing and

alternative questionnaires

Existing questionnaire

(n = 25)

Alternative questionnaire

(n = 33)

Rams > 1 year old 2.2 1.8

Castrated males > 1 year old 4.7 3.2

Females > 1 year old 45.5 42.8

Males < 1 year old 15.9 14.0

Females < 1 year old 19.2 14.5

Total 87.5 76.2

Table 1.10. Average number of goats on respondent farms, Botswana, existing and

alternative questionnaires

Existing questionnaire

(n = 57)

Alternative questionnaire

(n = 58)

Bucks > 1 year old 1.4 1.7

Castrated males > 1 year old 5.4 4.9

Females > 1 year old 28.8 29.4

Males < 1 year old 9.6 12.7

Females < 1 year old 10.5 12.2

Total 55.6 60.8

Average numbers of sheep by breed from the existing and alternative

questionnaires are presented in Table 1.11 and Table 1.12, while goat data are

presented in Table 1.13 and Table 1.14. In the existing questionnaire,

respondents were only given the opportunity to identify Tswana (indigenous),

cross-bred or exotic breed sheep and goats. However the alternative

questionnaire included a wider range of breeds, including the option to indicate

‘other’ breeds not on the list. The existing questionnaire asked respondents to

recall sheep and goat numbers on October 1st, 2014, while the alternative

questionnaire asked for current numbers (at the time of response).

In the case of sheep, where there were 20 responses to the other breed option in

the alternative questionnaire, breeds identified included Afrikaner, Damara, Ile

de France, Vanroin, and cross-breeds of the Dorper, Tswana and Damara

breeds. Tswana and Dorper appear to be the most commonly held sheep breeds.

A wider variety of goat breeds could be selected by respondents to the

alternative questionnaire (Table 1.14). Tswana and Boer goats appear to be the

most commonly held breeds, though Tswana/Boer cross-bred goats are also

19

common. Respondents with Boer goats had a much larger herd size than those

with other specified breeds, suggesting that this breed may be favoured by

farmers tending towards larger commercial operations.

Table 1.11. Average number of sheep by breed, Botswana, existing questionnaire.

Tswana

(n = 10)

Crosses

(n = 6)

Exotic Breeds

(n = 13)

Rams > 1 year old 0.9 1.0 3.0

Castrated males > 1 year old 1.9 4.8 5.4

Females > 1 year old 7.6 72.5 48.2

Males < 1 year old 1.4 15.8 22.2

Females < 1 year old 3.5 14.8 27.4

Total 15.3 109.0 106.2

Table 1.12. Average number of sheep by breed, Botswana, alternative questionnaire.

Dorper

(n = 14)

Karakul

(n = 1)

Tswana

(n = 14)

Other

(n = 20)

Don't

know

(n = 1)

Rams > 1 year old 2.1 1.0 0.8 0.8 -

Castrated males > 1

year old 2.9 - 3.1 3.05 -

Females > 1 year old 25.9 - 20.4 44.15 2.0

Males < 1 year old 10.6 - 5.6 11.85 -

Females < 1 year old 11.5 - 5.6 11.85 1.0

Total 52.9 1.0 35.5 71.8 3.0

Table 1.13. Average number of goats by breed, Botswana, existing questionnaire.

Tswana

(n = 38)

Crosses

(n = 25)

Exotic Breeds

(n = 19)

Bucks > 1 year old 0.7 1.2 1.1

Castrated males > 1 year old 3.7 3.8 3.8

Females > 1 year old 23.8 15.3 18.5

Males < 1 year old 4.7 8.6 7.9

Females < 1 year old 6.1 8.6 8.1

Total 39.0 37.6 39.5

20

Table 1.14. Average number of goats by breed, Botswana, alternative questionnaire.

Tswana

(n = 32)

Boer

(n = 19)

Crosses

(n = 10)

Karahari

(n = 4)

Savannah

(n = 5)

Sanaan

(n = 2)

Other

(n = 2)

Boer X

Tswana

(n = 24)

Bucks > 1

year old 0.8 2.1 0.9 0.3 0.4 - 1.5 0.9

Castrated

males > 1

year old

4.7 4.3 4.2 - - - 4.5 2.8

Females

> 1 year

old

20.0 32.1 10.0 1.5 0.6 2.0 32.0 12.8

Males < 1

year old 5.6 11.7 8.4 0.8 0.4 - 18.0 9.1

Females <

1 year old 7.6 10.9 9.9 1.5 0.8 - 12.0 9.2

Total 38.8 61.1 33.4 4.0 2.2 2.0 68.0 34.7

1.2.4. CHANGES TO HERD STRUCTURE

The existing questionnaire gave respondents the opportunity to indicate changes

to their herd structure (births and deaths, purchases, sales and other exchanges)

in the period from October 1st, 2014, to September 30

th, 2015.

Existing Questionnaire. Changes to herd structure over a 12 month

period.

Changes to sheep herd structure for 20 respondents are presented in

Table 1.15. The data show that the large majority of additions to the

sheep herd came from lambs born over this period, with only small

numbers of sheep being purchased. However, the average total

deduction from the herd was slightly higher than average total addition,

showing that respondent sheep herds reduced slightly in size. While

respondents sold approximately 10 sheep on average, stray or stolen

young and adult sheep, as well as sheep deaths, were the major

contributors to reduced herd size.

21

Table 1.15. Average changes to sheep herd numbers (additions and deductions) in the

period from October 1st

, 2014, to September 30th

, 2015, Botswana, existing questionnaire

(n = 20).

Additions to herd Average

Births

Number of lambs born 53.7

Other additions to herd

Rams purchased 0.2

Rams traded in or obtained 0.0

Other sheep purchased 1.8

Other sheep traded in or obtained 0.0

Average total additions to sheep herd 55.6

Deductions from herd Average

Lambs, stray or theft 10.5

Sheep, stray or theft 11.0

Private slaughter 4.0

Sheep given away 1.1

Rams sold 5.2

Rams traded out 3.5

Sheep sold 10.5

Sheep traded out 0.1

Deaths

Dead lambs 6.2

Dead sheep 6.7

Average total deductions from sheep herd 58.7

Similarly, data on changes to goat herd size and structure from the existing

questionnaire are presented in Table 1.16. In contrast to sheep numbers,

additions to the goat herd (largely from births), considerably outweighed

deductions from the herd, which were most likely to be a result of deaths in the

herd. Deaths were most likely to occur amongst kid goats, and a comparison of

this figure with the average birth rate suggests that goat farmers responding to

the survey experienced an approximately 25% mortality rate amongst their

younger goats.

22

Table 1.16. Average changes to goat herd numbers (additions and deductions) in the

period from October 1st


, 2015, Botswana, existing questionnaire

(n = 57).


Births

Number of kids born 30.2


Bucks purchased 0.0

Bucks traded in or obtained 0.0

Other goats purchased 0.1

Other goats traded in or obtained 0.1

Average total additions to goat herd 30.4


Kids, stray or theft 0.9

Goats, stray or theft 2.3


Goats given away 0.4

Bucks sold 1.4

Bucks traded out 0.0

Goats sold 5.4

Goats traded out 0.2

Deaths

Dead kids 7.6

Dead goats 3.5

Average total deductions from goat herd 23.1

The alternative questionnaire differed greatly from the existing questionnaire in

the amount of detail respondents were able to provide on changes to the

structure of their herd. As was the case with the existing questionnaire, these

questions focused on the period from October 1st, 2014, to September 30

th,

2015. However, all questions on additions to and deductions from the herd

included a break-down on the basis of animal age and gender, as well as

whether the additions or deductions took place during the rainy or dry seasons

(October to March, and April to September respectively).

Alternative Questionnaire. Impact of animal age and time of year/season

on changes to herd structure over a 12 month period.

Average additions to and deductions from the sheep herds of alternative

questionnaire respondents are presented in Table 1.17 and Table 1.18. Total

additions and deductions have not been produced given the different number of

23

respondents to each question and on the basis of rainy or dry season. However,

the data suggest a seasonal pattern to herd structure changes, whereby sheep

births are most likely to take place during the dry season, as are sheep

purchases. Sheep deaths appear much more likely to occur during the rainy

season compared to the dry season, while likewise respondents were more

likely to slaughter sheep for domestic consumption during the rainy season, or

to give sheep away. Sheep sales appear to take place year-round. Unlike the

existing questionnaire where a considerable proportion of deductions from the

herd appeared to be associated with stray or stolen sheep, a question on this

issue was not included in the alternative questionnaire.

Table 1.17. Average additions to sheep herd per respondent in the period from October

1st


, 2015, Botswana, alternative questionnaire.

Births Rainy Season (n = 15) Dry Season (n = 24)

Male Births 5.5 16.1

Female Births 5.7 16.1

Purchases Rainy Season (n = 4) Dry Season (n = 6)

Rams > 1 year old Purchased 0.5 0.7

Castrated males > 1 year old

Purchased 0.0 0.0

Females > 1 year old Purchased 2.3 9.0

Males < 1 year old Purchased 0.0 0.0

Females < 1 year old Purchased 0.3 0.3

Total Purchased 3.0 10.0

24

Table 1.18. Average deductions from sheep herd per respondent in the period from

October 1st



Sales Rainy Season (n = 11) Dry Season (n = 11)

Rams > 1 year old Sold 4.9 0.6

Castrated males > 1 year old Sold 4.6 2.6

Females > 1 year old Sold 3.8 10.0

Males < 1 year old Sold 0.3 0.3

Females < 1 year old Sold 0.8 0.9

Total Sold 14.4 14.4

Deaths Rainy Season (n = 13) Dry Season (n = 18)

Rams > 1 year old Died 0.2 0.2

Castrated males > 1 year old Died 0.9 0.8

Females > 1 year old Died 7.2 3.7

Males < 1 year old Died 5.1 2.2

Females < 1 year old Died 4.1 1.8

Total Deaths 17.5 8.7

Given Away Rainy Season (n = 4) Dry Season (n = 4)

Rams > 1 year old Given Away 1.0 0.0

Castrated males > 1 year old Given

Away 0.5 0.8

Females > 1 year old Given Away 1.3 0.3

Males < 1 year old Given Away 0.0 0.0

Females < 1 year old Given Away 0.0 0.0

Total Given Away 2.8 1.0

Slaughtered for Consumption Rainy Season (n = 12) Dry Season (n = 10)

Rams > 1 year old Slaughtered 1.4 0.0


Slaughtered 4.1 3.1

Females > 1 year old Slaughtered 1.7 1.5

Males < 1 year old Slaughtered 0.8 0.3

Females < 1 year old Slaughtered 0.0 0.0

Total Slaughtered 7.9 4.9

Table 1.19 and Table 1.20 include average additions to and deductions from

goat herds amongst alternative questionnaire respondents. In contrast to the

response regarding sheep, goat births are only somewhat more likely to take

place during the dry season, while goat purchases appear more likely to occur

during the rainy season. As was the case with respect to sheep herd structure,

season does not seem to have a great impact on goat sales. However unlike

sheep where deaths, decisions to give animals away, or decisions to slaughter

for private consumption are more likely to be associated with the rainy season,

25

in the case of goats these factors have a much weaker association with season,

appearing to be much more year-round phenomena.

Table 1.19. Average additions to goat herd per respondent in the period from October 1st

,

2014, to September 30th


Births Rainy Season (n = 38) Dry Season (n = 40)

Male Births 7.2 12.2

Female Births 8.6 11.0

Purchases Rainy Season (n = 11) Dry Season (n = 7)

Rams/Bucks > 1 year old

Purchased 1.5 0.7


Purchased 0.7 1.4

Females > 1 year old Purchased 14.6 6.0

Males < 1 year old Purchased 3.1 2.1

Females < 1 year old Purchased 2.3 1.4

Total Purchased 22.1 11.7

Table 1.20. Average deductions from goat herd per respondent in the period from October

1st, 2014, to September 30th, 2015, Botswana, alternative questionnaire.

Sales Rainy Season (n = 22) Dry Season (n = 25)

Rams/Bucks > 1 year old Sold 1.3 0.4

Castrated males > 1 year old Sold 3.0 1.9

Females > 1 year old Sold 4.5 4.6

Males < 1 year old Sold 0.1 0.3

Females < 1 year old Sold 1.5 1.2

Total Sold 10.3 8.4

Deaths Rainy Season (n = 22) Dry Season (n = 25)

Rams/Bucks > 1 year old Died 0.2 0.0

Castrated males > 1 year old Died 1.1 0.4

Females > 1 year old Died 4.0 4.2

Males < 1 year old Died 2.0 2.1

Females < 1 year old Died 2.5 2.7

Total Deaths 9.8 9.4

Given Away Rainy Season (n = 6) Dry Season (n = 6)

Rams/Bucks > 1 year old Given

Away 0.5 0.0

Castrated males > 1 year old Given

Away 0.5 1.2

Females > 1 year old Given Away 0.8 0.3

Males < 1 year old Given Away 0.7 0.3

Females < 1 year old Given Away 0.7 1.0

Total Given Away 3.2 2.8

26

Slaughtered for Consumption Rainy Season (n = 14) Dry Season (n = 20)

Rams/Bucks > 1 year old

Slaughtered 0.1 0.0


Slaughtered 1.6 1.5

Females > 1 year old Slaughtered 0.1 0.9

Males < 1 year old Slaughtered 0.6 0.3

Females < 1 year old Slaughtered 0.1 0.1

Total Slaughtered 2.4 2.8

1.2.5. PURCHASE AND SALE OF LIVESTOCK, IN HERD DYNAMICS

For each age range and gender of sheep and goats, respondents were also able

to indicate from which source/s they purchased animals during the rainy and

dry seasons, and who purchased their animals. Response was possible to these

questions for each of the rainy and dry seasons, and with respect to young and

adult male and female animals. However, given the relatively small number of

responses possible for this pilot project, the data on season and age of animals

have been aggregated. A large-scale survey using this questionnaire form would

allow more detailed analysis of these factors and their relationship to season

and sheep and/or goat age.

Alternative Questionnaire. Sources of livestock of different ages and at

different times of year.

Alternative Questionnaire. Purchasers of livestock of different ages and

at different times of year.

Relatively few responses on the source of sheep purchases were provided

(Table 1.21), reflecting the small number of respondents purchasing sheep

(Table 1.17). However, the small response suggested that ‘other sources’ (in

this questionnaire, family members, government, or stud breeders) may be the

source of larger quantities of sheep. In the case of goats, respondents sourced

similar quantities of animals on average by purchasing from traders, other

farmers, or other sources, however other farmers were the most common source

of goat purchases.

27

Table 1.21. Average numbers of sheep and goats purchased from different sources,

Botswana, alternative questionnaire.

Source of Purchase Sheep

Trader (n = 1) 1.0

Other Farmer (n = 4) 3.5

Other Source (n = 2) 28.0

Source of Purchase Goats

Trader (n = 1) 13.0


Other Source (n = 2) 12.0

Respondents to the alternative questionnaire were far more likely to sell sheep

(Table 1.22) than to buy them (Table 1.21). The most likely purchaser of sheep

was other farmers, followed by slaughterhouses and other buyers. Other buyers

(not specified in the questionnaire or data set) were likely to buy the highest

number of sheep from respondents. Likewise, respondents were most likely to

sell goats to other farmers, followed by other buyers and retailers or butchers.

Larger numbers of goats were sold to traders on average, however respondents

selling both sheep and goats were relatively unlikely to interact with traders.

Table 1.22. Average numbers of sheep and goats sold to different sources, Botswana,

alternative questionnaire.

Purchaser Sheep

Trader (n = 1) 7.0


Retailer or Butcher (n = 4) 9.3

Slaughterhouse (n = 5) 5.8

Other Buyer (n = 5) 22.6

Purchaser Goats

Trader (n = 3) 13.3


Retailer or Butcher (n = 10) 7.3

Slaughterhouse (n = 1) 4.0

Other Buyer (n = 13) 9.2

28

1.2.6. FACTORS AFFECTING PRODUCTION AND PRODUCTIVITY

1.2.7. CAUSES OF LIVESTOCK DEATH

The alternative questionnaire included a question on the causes of death of

sheep and goats that had been lost during the period from October 1st, 2014, to

September 30th

, 2015 (Table 1.18 and Table 1.20). Respondents were able to

indicate numbers of animals that had died as a result of disease, parasites,

accidents, predators, drought, and other unspecified causes.

Alternative Questionnaire. Causes of death of livestock of different ages

and at different times of year.

The resulting data for season, age and gender of animals impacted have been

aggregated and presented in Table 1.23, though larger scale implementation of

the questionnaire may allow trends involving these factors and cause of death to

be identified and presented.

Owners of both sheep and goats were most likely to indicate that they had lost

animals to disease, although this was not the cause of the largest average

number of sheep or goats lost per respondent. In the case of sheep, the largest

average losses came from predators, followed by parasites, while for goats

respondents lost the largest number of animals on average as a result of

drought, followed by predators. Other causes of death, not specified in the

questionnaire, were relatively commonly cited but responsible only for

relatively small numbers of sheep and goat deaths.

29

Table 1.23. Average numbers of sheep and goats dying from different causes, Botswana,


Cause of Death Sheep

Disease (n = 11) 7.0

Parasites (n = 3) 13.0

Accidents (n = 1) 1.0

Predators (n = 9) 18.8

Drought (n = 8) 4.5

Other (n = 7) 1.6

Cause of Death Goats

Disease (n = 42) 5.9

Parasites (n = 5) 5.4

Accidents (n = 1) 5.0

Predators (n = 19) 7.1

Drought (n = 11) 17.3

Other (n = 13) 1.7

1.2.8. ‘MISSING’ LIVESTOCK

While collecting the gold standard data to measure the physical characteristics

of selected sheep and goats, the enumerators recorded animals that were

‘missing’ at the time the second on-farm visit took place. This involved

recording animals that had died (for unspecified reasons) between the first and

second visits, those that were missing (again for unspecified reasons), and in

rare cases, animals that had been sold over this approximately 30 day period.

Figure 1.1 and Figure 1.2 illustrate that the rate of ‘missing’ animals between

visits amounted to a total of just over 10 per cent for sheep, and approximately

9 per cent for goats. There appears to be a much wider variation in the

proportion of sheep missing across the various districts compared to goats,

though it should be noted that the number of sheep measured was much smaller

than the number of goats.

30

Figure 1.1. Proportion of sheep ‘missing’ between first and second animal measurement

visits by district, Botswana, gold standard data (%)

Figure 1.2. Proportion of goats ‘missing’ between first and second animal measurement

visits by district, Botswana, gold standard data (%)

31

1.2.9. LIVESTOCK AGE AND WEIGHT

The alternative questionnaire asked respondents to estimate the weights of their

sheep and goats at the ages of 3, 6 and 12 months (Table 1.24).

Alternative Questionnaire. Average body weight x age category of

sheep or goats.

The data suggest the both sheep and goats approximately double in weight

between each of these age categories, however it is important to note that

responses varied widely under each age category for both types of livestock (as

shown in the ‘Min’ and ‘Max’ rows in each case). This may relate to lack of

understanding of the question, inexperience of small-scale livestock owners

with weighing their livestock, or potentially issues during data entry. It can

therefore be suggested that ‘gold standard’ measurement of weight and other

physical characteristics of livestock, as presented below, will provide a much

more accurate understanding of the relationship between the age and weight of

sheep and goats.

Table 1.24. Average weight of sheep and goats by age category

(kg; respondent estimate, alternative questionnaire).

Sheep (n = 13) 3 Months Age 6 Months Age 12 Months Age

Weight (kg) 10.2 23.6 41.4

Std Dev 2.0 5.0 20.0

Min 2.0 5.0 20.0

Max 20.0 50.0 75.0

Goats (n = 19) 3 Months Age 6 Months Age 12 Months Age

Weight (kg) 7.1 17.5 36.4

Std Dev 3.6 9.5 17.2

Min 1.0 3.0 11.0

Max 13.0 40.0 70.0

1.2.10. LIVESTOCK PRODUCTION MEASURES

The average body weight, girth measurement, shoulder height measurement and

body condition score of goats and sheep were recorded as part of the gold

standard data collection for the project. Data collection focused only on animals

less than 12 months old, while animal breed data were not collected. These

livestock production measures are presented in Table 1.19, Table 1.20, Table

1.21, and Table 1.22.

32

The data show that male sheep and goats tend to be slightly larger than female

goats, in terms of weight, girth and height. However, the body condition scores

of both males and female animals were relatively similar on average.

Gold standard data collection. Average body weight x sex of sheep or

goats.

Gold standard data collection. Average girth measurement x sex of

sheep or goats.

Gold standard data collection. Average shoulder height measurement x

sex of sheep or goats.

Gold standard data collection. Average body condition score x age of

sheep or goats.

Table1.25. Average body weight (kg) of sheep and goats by gender, Botswana, gold

standard data, baseline observation.

Sheep Average Std Dev n

Female 16.2 8.3 380

Male 17.3 8.2 300

Goats Average Std Dev n

Female 12.4 7.4 765

Male 13.6 8.4 825

Table 1.26. Average girth measurement (cm) of sheep and goats by gender, Botswana,

gold standard data, baseline observation.


Female 59.6 11.5 380

Male 59.8 11.3 300


Female 50.7 10.6 765

Male 51.9 11.4 825

Table 1.27. Average shoulder height measurement (cm) of sheep and goats by gender,

Botswana, gold standard data, baseline observation.


Female 49.0 6.8 380

Male 50.8 7.1 300


Female 45.7 8.2 765

Male 47.3 9.1 825

33

Table.1.28. Average body condition score of sheep and goats by gender, Botswana, gold



Female 2.62 0.46 380

Male 2.58 0.46 300


Female 2.35 0.41 765

Male 2.39 0.42 825

Body condition score (BCS) was measured on a scale of 1-4 (1 being poor

condition and 4 excellent condition) for all sheep and goats observed (Figure

1.3. and Figure 1.4.). In some cases, the enumerators provided a score that was

not rounded to the nearest 0.5 (e.g. ‘2.8’). However, for ease of data

presentation all scores have been rounded to the nearest 0.5. The results in the

two figures below show that sheep were more likely to attract a BCS of 2.5 or

3.0, while goats were more likely to attract a BCS or 2.0 or 2.5. This supports

the result in Table 1.22 which showed that the average BCS of observed sheep

was higher than that of goats.

Gold standard data. Proportion of sheep or goats under each BCS x sex

of animals.

Figure 1.3. Body condition score (BCS) for female and male sheep, Botswana, gold

standard data, baseline observation (% of goats).

34

Figure 1.4. Body condition score (BCS) for female and male goats, Botswana, gold

standard data, baseline observation (% of goats).

1.2.11. LIVESTOCK GROWTH RATES

The enumerators sought to visit each farm on two occasions, with

approximately 30 days between each visit, to measure the weight, girth,

shoulder height and to estimate the BCS of observed sheep and goats less than

one year old. This made it possible to produce an estimate of the growth rates of

sheep and goats based on the observed data. Logistical limitations meant that

visits could not always be conducted exactly 30 days apart, with the length of

time between visits therefore varying across participating farms. The average

length of time between farm visits was 32.4 days, with a minimum of 28 days

and a maximum of 40 days.

The average growth rates of sheep and goats, in terms of weight (kg), girth (cm)

and shoulder height (cm) are presented in Figure 1.5, Figure 1.6 and Figure 1.7.

The results show that both female and male sheep and goats less than 12

months old experienced growth between the two measurement periods. Female

animals (both sheep and goats) exhibited a smaller amount of growth than male

animals, in keeping with the smaller starting weights and measurements of

female animals compared to their male counterparts. However, while both male

and female sheep gained more weight over the measurement period in

comparison to goats, the observed goats actually grew more than the sheep in

terms of both girth measurement and shoulder height measurement. This

suggests that girth or shoulder height measurement may not be a reliable proxy

for weight gain, particularly in cases where both sheep and goats are being

35

observed and compared. This may also be due to comparative physical and

structural characteristics of the two types of animals.

Gold standard data collection. Changes in body weight x sex of sheep

and goats.

Gold standard data collection. Changes in girth measurement x sex of

sheep and goats.

Gold standard data collection. Changes in shoulder height measurement

x sex of sheep and goats.

Figure 1.5. Average change in weight of male and female sheep and goats between

enumerator visits (kg), Botswana, gold standard data.

36

Figure 1.6. Average change in girth measurement of male and female sheep and goats

between enumerator visits (cm), Botswana, gold standard data.

Figure 1.7. Average change in shoulder height measurement of male and female sheep

and goats between enumerator visits (cm), Botswana, gold standard data.

37

1.3. BOTSWANA – FEED AVAILABILITY

1.3.1. FEED SUPPLY AND PRODUCTION

1.3.1.1. FEED CROP PRODUCTION

Both the existing and alternative questionnaires asked respondents to indicate

the area of crops grown (in hectares) and the type of crop/s planted. The

existing questionnaire focused on the ‘last agricultural year’ (October 1st 2014

to September 30th 2015), while the alterative questionnaire focused on a

standard (unspecified) year, suggesting that respondents were being asked to

estimate average area planted over time.

Specific type/s of crops sown were not included in the existing questionnaire

data, however the response to this question in the existing questionnaire (n =

16) suggested that 3.75 hectares had been planted per respondent to crops over

the previous agricultural year. Some respondents only planted a single crop,

while others had planted two or more crops.

Existing Questionnaire. Total area sown to (unspecified) feed crops over

the last agricultural season.

Alternative questionnaire respondents were asked to indicate the area of seven

specific crops grown, and provided the option to indicate the area grown to

other crops where relevant. Multiple responses were possible for those growing

two or more crops.

Alternative Questionnaire. Average total area sown to specific feed

crops ‘each year’.

The results (Table 1.29) suggest that maize is the most commonly grown feed

crop amongst the respondents, both in terms of number of responses as well as

average area grown. Grains crops more broadly are grown over relatively large

areas, however the next most commonly grown feed crop after maize was

beans. Of the 30 respondents who indicated they were growing one or more

feed crops, the average total area planted was 4.40 hectares.

38

Table 1.29. Average area of different crops grown, Botswana, alternative questionnaire.

Average area of crop grown (Ha.) n

Maize 2.1 27

Sorghum 1.5 6

Other grains 1.8 6

Oilseeds 1.3 4

Beans 1.2 20

Groundnuts 1.0 4

Lablab 1.6 11

Sweet Reeds 2.0 2

1.3.1.2. GRAZING LAND AVAILABILITY

Additionally, the alternative questionnaire covered the supply of grazing land

available to respondents, including fenced, communal and rented grazing, and

grazing along roadsides and in other public areas. Table 1.30 shows that

communal grazing is the most widely used option available to the respondents,

while communal grazing areas tended to be just under 6,000 hectares in size on

average. Rented and roadside/public area grazing appear to be rarely used.

Table 1.30. Average grazing area available to respondents using each type of grazing

(Ha.), Botswana, alternative questionnaire.

Average Std Dev n

Fenced grazing 611.4 1893.4 10

Communal grazing 5832.7 11816.3 29

Rented grazing 22500.0 - 1

Roadsides and other public areas 2500.0 - 1

1.3.2. CROP AND PASTURE FEED DEMAND AND USAGE

The alternative questionnaire addressed the number of days cattle, sheep and

goats were fed various by-products of feed crops grown by the respondents,

including grain, stubble, stover, and by-products. Seasonal data (whether the

crops were used to feed stock in the wet or dry season) were not recorded here.

The crops addressed included those listed in Table 1.29. However, the

complexity of the response, as well as lack of response for some crop/residue

type/livestock combinations, means that only data for the two most commonly

used feed crops, maize and beans, are presented here (Table 1.31 and

39

Table 1.32). Both maize and bean crop stover appears to be the most likely way

in which this crop is used as a livestock feed, particularly for goats. Both tables

again show that goats are likely to be fed from these crops for a considerably

longer number of days than sheep or more particularly cattle.

If additional data were available to provide an estimate of daily consumption

rates for livestock (for example, number of kg of maize stover consumed daily

by goats), these data could be used to provide an indication of annual

consumption rates.

Alternative Questionnaire. Number of days annually each type of

livestock uses particular feed crops and their residue categories.

Table 1.31. Average number of days maize crops and/or crop residues used to feed

livestock, Botswana, alternative questionnaire.

Cattle n (cattle) Sheep n (sheep) Goats n (goats)

Grain (avg no. days) - - 38 4 74.25 8

Stubble (avg. no. days) 7 1 19.33 3 73.4 10

Stover (avg. no. days) 70.33 3 28.38 8 78.5 22

By-products (avg. no. days) 183 1 39.5 4 73.43 7

Table 1.32. Average number of days bean crops and/or crop residues used to feed

livestock, Botswana, alternative questionnaire.

Cattle n (cattle) Sheep n (sheep) Goats n (goats)

Grain (avg no. days) - - 30.5 2 82.5 4

Stubble (avg. no. days) - - 13.5 2 60 3

Stover (avg. no. days) 47 3 63.33 3 74 10

By-products (avg. no. days) 180 1 89 4 85.2 5

The alternative questionnaire also included a question regarding the extent to

which various categories of grazing land were used to feed livestock. As Table

suggests, most respondents tend to use grazing land available to them year-

round, though it is notable that fenced grazing is only used for goats for around

120 days on average. This may reflect the relatively high standard of fencing

required to restrict goat movement compared to sheep or cattle, and therefore

relatively smaller areas of grazing land being fenced to a standard capable of

holding goats.

Alternative Questionnaire. Number of days annually different types of

grazing area grazed by different types of livestock.

40

Table 1.33. Average number of days livestock grazed by respondents on each type of

grazing area, where available.

Days used for cattle n

Fenced grazing 365 1

Communal grazing 365 18

Rented grazing 365 1

Roadsides and other public areas - -

Days used for sheep n

Fenced grazing 227.5 4



Roadsides and other public areas 365 2

Days used for goats n

Fenced grazing 121.1 10

Communal grazing 358.9 50


Roadsides and other public areas 365 2

Days used for other animals n

Fenced grazing 365 1



Roadsides and other public areas - -

1.3.3. DEGRADATION OF PASTURE

Pasture degradation was addressed in the alternative questionnaire through the

extent of presence of Seloka Grass (Heteropogon contortus), and the extent of

bush encroachment. Respondents were asked to rate these contributing factors

to pasture degradation on a scale from 1 (None) to 4 (Severe). Table 1.34 shows

that respondents rated bush encroachment as a more significant issue than the

impact of the weed Seloka Grass, particularly in the case of communal grazing

land where the average response of 56 respondents was between ‘Some’ and

‘Moderate’. The fact that these issues appear somewhat less important on

fenced grazing land may suggest that farmers are more likely to maintain their

own fenced land, while such issues on common land are more likely to go

unaddressed.

Alternative Questionnaire. Rating of pasture degradation on a scale from

‘None’ to ‘Severe’ using the contributing factors of presence of Seloka

Grass, and bush encroachment.

41

Table 1.34. Average ratings of the presence of Seloka Grass and the extent of bush

encroachment on different types of grazing land, where 1 = None, 2 = Some, 3 = Moderate,

and 4 = Severe).

Average rating: presence

of Seloka Grass

Average rating: extent of

bush encroachment n

Fenced grazing 1.6 2.2 10

Communal grazing 1.79 2.48 56

Rented grazing 1 1 1

Roadsides and other public

areas 1.5 1.5 2

1.3.4. PURCHASED FEED DEMAND AND USAGE

1.3.4.1. SOURCE AND QUANTITY OF FEED PURCHASED

In addition to covering feed crops grown and pasture used by the respondents,

both the existing and alternative questionnaires addressed purchased feeds

purchased from a third party. Both questionnaires asked for an indication not

only of which type/s of purchased feed were used, but also the quantity

purchased annually.

Existing and Alternative Questionnaires. Quantity of specific livestock

feeds purchased annually (kg).

The results between the two sets of survey respondents differed considerably,

suggesting that a larger sample would be required to obtain a statistically

significant representation of the total population’s usage of stock feed options.

Amongst existing questionnaire respondents, the most widely used feed options

(number of responses) included salt, drought pellets and moroko (Table 1.35),

while lablab featured as the feed purchased in the largest quantity, followed by

sheep pellets, salt and meal molasses. Amongst alternative questionnaire

respondents salt and drought pellets also featured as the most widely purchased

feed option, followed by moroko and dicalcium phosphate (Table 1.36).

Drought pellets were purchased in the greatest quantity per respondent,

followed by meal molasses, moroko, and nitrogen/protein feeds.

42

Table 1.35. Average quantity of feed of different types purchased by respondents (kg),

Botswana, existing questionnaire.

Quantity Purchased (kg) n

Lucerne 114.6 11

Nitrogen/protein feeds - -

Drought pellets 304.4 23

Ram, Lamb and Ewe pellets 540.0 5

Moroko 223.3 21

Salt 337.2 30

Dicalcium Phosphate 277.5 16

Lablab 603.1 8

Molasses (powder) 250.0 5

Molasses (liquid) 85.0 6

Molasses (meal) 310.7 15

Stover (Lotlhaka) 138.0 5

Grasses (fodder) - -

Grains (barley) 200.0 1

Mineral block (e.g. rumevite) 64.3 11

Hay - -

Feed grade urea - -

Other 370.0 10

43

Table 1.36. Average quantity of feed of different types purchased by respondents (kg),


Quantity Purchased (kg) n

Lucerne 222.1 14

Nitrogen/protein feeds 350.0 4

Drought pellets 731.0 27

Ram, Lamb and Ewe pellets 450.0 4

Moroko 410.5 25

Salt 316.2 30

Dicalcium Phosphate 280.6 18

Lablab 100.0 5

Molasses (powder) 154.3 7

Molasses (liquid) 58.6 7

Molasses (meal) 525.4 12

Stover (Lotlhaka) 199.8 5

Grasses (fodder) 20.0 1

Grains (barley) - -

Mineral block (e.g. rumevite) 120.9 16

Hay - -

Feed grade urea - -

Other 268.3 9

1.3.4.2. USAGE OF PURCHASED FEED

The existing questionnaire also asked the respondents to indicate which

livestock they used each of the purchased feeds for cattle, sheep and goats

(Table 1.37). The response suggests that the widest variety of stock feed options

was used for goats, perhaps reflecting the high proportion of respondents who

kept goats. All respondents using purchased feed for goats had used half of the

feed options listed. Respondents were less likely to use these various feed

options to feed cattle.

Existing Questionnaire. Proportion of farmers using various stock feed

options to supplement the diet of cattle, sheep and goats.

44

Table 1.37. Proportion of respondents using different purchased feed types to feed their

livestock (multiple response, %), Botswana, existing questionnaire.

Cattle Sheep Goats n

Lucerne 9.1 45.5 90.9 11

Drought pellets 4.3 30.4 95.7 23

Ram, Lamb and Ewe pellets 0.0 60.0 100.0 5

Moroko 22.7 27.3 100.0 22

Salt 26.7 30.0 96.7 30

Dicalcium phosphate 37.5 31.3 81.3 16

Lablab 0.0 37.5 100.0 8

Molasses (powder) 60.0 60.0 80.0 5

Molasses (liquid) 16.7 50.0 100.0 6

Molasses (meal) 25.0 25.0 87.5 16

Stover (Lotlhaka) 0.0 0.0 100.0 6

Grasses (fodder) 0.0 100.0 100.0 1

Grasses (barley) 0.0 100.0 100.0 1

Mineral block (e.g. rumevite) 36.4 36.4 100.0 11

Other 10.0 20.0 90.0 10

The alternative questionnaire allowed respondents to provide more detailed

information on usage of purchased feed options for cattle, sheep and goats.

These details included the number of days livestock were fed each of the feed

options, a breakdown of each category of livestock (e.g. calves, young cattle,

cows), and whether the feed was used in the wet or dry season. Multiple

responses were possible given that farmers commonly use more than one feed

option.

Overall, some 93 per cent of the respondents indicated that the feed option in

question was used during the dry season, with the remaining 7 per cent

indicating wet season. The data (presented in Table 1.38, Table 1.39 and Table

1.40), show that respondents were considerably more likely to consider these

feed options for goats or sheep than cattle. Of the three types of livestock

included in the survey, cattle appear to require purchased feed supplements for

a larger proportion of the year than sheep or goats.

Alternative Questionnaire. Number of days purchased feed used for

cattle, sheep and goats, by stock age categories.

45

Table 1.38. Average number of days different purchased feeds used to feed cattle,


Days fed

to cows

n

(cows)

Days fed to

young cattle

n

(young

cattle)

Days fed to

calves

n

(calves)

Lucerne 67.3 3 57.5 4 67.3 3

Nitrogen/protei

n feeds 90.0 1 90.0 1 75.0 2

Drought pellets 150.0 2 111.0 2 114.0 3

Moroko 80.3 4 72.3 3 100.0 3

Salt 221.6 8 197.8 9 203.7 9

Dicalcium

Phosphate 238.8 4 238.8 4 203.0 5

Molasses

(powder) 151.0 3 151.0 3 151.0 3

Molasses

(liquid) 274.0 2 274.0 2 202.7 3

Molasses

(meal) 135.0 2 135.0 2 97.0 3

Stover

(Lotlhaka) 95.0 2 95.0 2 180.0 1

Grasses

(fodder) 180.0 1 180.0 1 180.0 1

Mineral block

(e.g. rumevite) 272.5 2 272.5 2 161.8 4

Other 150.0 1 150.0 1 150.0 1

46

Table 1.39. Average number of days different purchased feeds used to feed sheep,


Days fed

to ewes

n

(ewes)

Days fed to

young

sheep

n

(young

sheep)

Days fed to

lambs

n

(lambs)

Lucerne 107.6 7 107.6 7 156.4 8

Nitrogen/prote

in feeds 45.0 1 45.0 1 45.0 1

Drought

pellets 182.0 10 182.0 10 365.0 10

Ram, lamb

and ewe

pellets

150.0 2 100.0 1 120.0 2

Moroko 105.7 11 89.4 13 121.6 14

Salt 167.9 10 171.2 12 162.9 10

Dicalcium

Phosphate 151.4 10 124.9 13 153.0 13

Lablab 90.0 1 169.0 3 71.0 2

Molasses

(powder) 158.5 4 137.2 5 173.8 5

Molasses

(liquid) 113.8 4 113.8 4 159.5 4

Molasses

(meal) 129.6 7 129.6 7 181.9 7

Stover

(Lotlhaka) 181.5 2 121.3 3 121.3 3

Grasses

(fodder) 180.0 1 180.0 1 180.0 1

Mineral block

(e.g. rumevite) 166.8 12 165.5 12 166.8 12

Other 82.3 3 82.3 3 82.3 3

47

Table 1.40. Average number of days different purchased feeds used to feed goats,


Days fed

to does

n

(does)

Days fed to

young goats

n

(young

goats)

Days

fed to

kids

n

(kids)

Lucerne 118.3 9 102.6 8 148.9 8

Nitrogen/protei

n feeds 45.0 1 45.0 1 45.0 1

Drought pellets 97.1 16 108.0 17 103.3 15

Ram, lamb and

ewe pellets 120.0 1 - - - -

Moroko 95.9 15 80.3 19 83.2 14

Salt 175.9 16 186.8 20 176.8 11

Dicalcium

Phosphate 153.8 12 120.8 16 113.3 12

Lablab 146.0 4 78.7 3 160.3 3

Molasses

(powder) 158.5 4 124.7 7 191.0 3

Molasses

(liquid) 121.0 5 131.3 6 157.6 5

Molasses (meal) 129.5 11 127.2 10 202.7 3

Stover

(Lotlhaka) 122.3 3 98.5 4 62.7 3

Grasses

(fodder) 180.0 1 180.0 1 - -

Mineral block

(e.g. rumevite) 147.9 14 153.7 15 177.5 11

Other 101.8 8 81.4 5 100.8 4

1.3.5. HERBACEOUS VEGETATION

Gold standard data collection. Composition and density of herbaceous

species across different communal grazing sites.

1.3.5.1. SAMPLE SIZES

Transact-sampling for herbaceous species frequency was completed at 244

survey sites, comprising 72 survey sites in the Central district, 53 survey sites in

the Kgalagadi district, and 119 survey sites at the Kweneng district. The survey

sites were selected in different locations within each district: 6 locations in the

Central district, 4 locations in the Kgalagadi district, and 11 locations in the

Kweneng district.

A total of 1,123 transects were completed across the 244 survey sites. Between

1 and 11 transects were completed at each site, with an average of 4.9 transects

48

being completed per site. The average number of transects per site differed in

each of the three districts (3.9 in the Central district, 9.1 in the Kgalagadi

district, and 2.9 in the Kweneng district).

1.3.5.2. HERBACEOUS SPECIES PRESENT

The field surveys identified 45 herbaceous species or groups, including 43

distinct species as well as unspecified forbs (22 identifications) and unspecified

sedges (5 identifications). Additionally, there were 21 of ‘bare ground’, as well

as 20 instances of ‘litter’ identified in the transects. Bare ground and litter were

reported at all three districts where transect-sampling was performed.

Table 1.41 shows the most commonly identified herbaceous species across all

survey locations and within each of the three districts. Aristida congesta was the

most commonly identified species with 17 identifications. The table also shows

notable differences in the species identified across the three districts where

transect-sampling was completed. The relative frequency with which some

species have been identified in the Kweneng and to a lesser extent the Central

district is partially a function of the greater number of transects that were

completed in these two districts.

Table 1.41. Number of locations in which herbaceous species were identified (frequent

species only reported by number of survey locations).

Species full name No. locations

Central

No. locations

Kgalagadi

No. locations

Kweneng Total

Aristida congesta 6 3 8 17

Digitaria eriantha 6 - 10 16

Schmidtia pappophoroides 5 3 8 16

Eragrostis rigidior 6 2 7 15

Eragrostis lehmanniana - 4 6 10

Urochloa mosambicensis 5 - 4 9

Eragrostis pallens - 3 3 6

Panicum maximum 5 - 1 6

Pogonarthria squarrosa 1 2 3 6

Stipagrostis uniplumis - 5 1 6

Tragus berteronianus 3 1 2 6

Aristida graciliflora - 3 2 5

Sporobolus ioclados 3 - 2 5

Tragus racemosa - - 5 5

Eragrostis denudata 3 - 1 4

Schmidtia kalihariensis - 4 - 4

49

1.3.5.3. HERBACEOUS SPECIES COUNTS

In addition to identifying herbaceous species within transects, the field survey

work involved counting the number of instances of species identification. This

allows for a comparison between how widespread a particular species is across

locations (Table 1.41), and how dense the population of plant herbaceous plant

species is within particular locations (transects; Table 1.42; most commonly

plants by number of times identified).

A comparison of these two tables suggests that there is some commonality in

plant species being widespread across and within locations. However, Table

1.42 also suggests that where they are identified, common herbaceous species

such as Eragrostis rigidior, Schmidtia kalihaiensis, Aristida graciflora, and

Stipagrostis obtusa may be more likely to form more dense populations on

communal grazing land, as illustrated by the high average number of plants per

transect found for these species. The data in the two tables may be tentatively

used to suggest that Eragrostis rigidior and Aristida congesta are amongst the

most important herbaceous species in the Central and Kwaneng districts, while

Schmidtia kalihariensis and Aristida graciflora feature amongst the most

important herbaceous species in the Kgalagadi district. Species with a common

district presence and frequent appearance in pastures warrant the most attention

with respect to their biomass, palatability and nutritional value to livestock.

50

Table 1.42. Number of times each herbaceous species identified across all transects

where one or more identifications were made (all regions; frequent species only reported

by number of times plant identified).

1.3.4.5. HERBACEOUS BIOMASS

Gold standard data collection. Amount and quality of herbaceous

biomass across different communal grazing sites.

1 x 1 metre quadrats were clipped to measure herbaceous biomass at 66 sites,

comprising 13 sites in the Central district, 38 sites in the Kgalagadi district, and

15 sites in the Kweneng district. All measurements were undertaken during a

dry period. Measures included biomass (g/m2), and an estimate of grass

palatability on a scale ‘Good – Intermediate – Poor’, with instances of ‘Litter’

also recorded.

The average biomass per site is shown in Table 1.43. It is notable in this table

that the average biomass measured on sites in the Kgalagadi district was

markedly higher than in the other two districts. The raw data shows that at ten

sites in Kgalagadi, herbaceous biomass was measured at above 50 g/m2, with a

high of 232.2 g/m2. In contrast, the highest herbaceous biomass measure taken

Species full name

No. transects

where at least 1

plant counted

No. times plant

identified

Avg. no. plants

per transect

Eragrostis rigidior 36 745 20.7

Schmidtia kalihariensis 25 507 20.3

Digitaria eriantha 36 412 11.4

Aristida congesta 40 411 10.3

Aristida graciliflora 16 299 18.7

Urochloa mosambicensis 21 218 10.4

Stipagrostis uniplumis 25 207 8.3

Eragrostis lehmanniana 22 192 8.7

Schmidtia

pappophoroides 31 146 4.7

Stipagrostis obtusa 9 140 15.6

Eragrostis pallens 15 86 5.7

Megaloprotachne

albescens 6 79 13.2

Sporobolus ioclados 6 62 10.3

Eragrostis denudata 12 59 4.9

Stipagrostis ciliata 7 50 7.1

Stipagrostis namaquensis 4 50 12.5

51

in the Central district was 18.2 g/m2, and 28.5 g/m

2 in Kweneng. In many cases

at all sites however, high biomass coincides with intermediate or poor grass

palatability, or ‘litter’.

Table 1.43. Herbaceous biomass per site, district and total averages (g/m2).

District Average Std Dev. n

Central 4.68 4.67 13

Kgalagadi 40.37 63.86 38

Kweneng 5.13 7.40 15

Total 25.33 51.69 66

Herbaceous biomass palatability to livestock was estimated at each site, with

the results presented in Table 1.44. These results suggest that while high

biomass was most likely to be found at sites in the Kgalagadi district, this

district had the lowest proportion of sites with good grass palatability, with less

palatable species appearing to be relatively dominant amongst the high quantity

of biomass.

Table 1.44. Proportion of estimates of grass palatability per district and across all sites

(%).

District Good Intermediate Poor Litter n

Central 46.15 46.15 7.69 - 13

Kgalagadi 15.79 39.47 26.32 18.42 38

Kweneng 26.67 53.33 13.33 6.67 15

Total 24.24 43.94 19.70 12.12 66

1.3.6. WOODY VEGETATION

At the end of each transect where herbaceous species were identified and

quantified, woody species counts were carried out in 10m x 10m quadrats. Each

woody plant was measured for height, and heights categorised.

Gold standard data collection. Composition and density of woody

species across different communal grazing sites.

Gold standard data collection. Distribution of woody species of different

heights across different communal grazing sites.

1.3.6.1. WOODY SPECIES PRESENT

The field surveys identified 48 woody species or groups, while in 9 cases no

woody species were present in the 10m x 10m quadrat.

52

Table 1.39 shows the most commonly identified woody species across all

survey locations and within each of the three districts. Grewia flavia was the

most commonly identified species with 49 identifications, followed by Acacia

mellifera (34 identifications) and Dichrostachys cinerea (33 identifications).

Table 1.45. Number of transect sites in which herbaceous species were identified

(frequent species only reported by number of survey locations).

Species full name No transect sites

Central

No. transect

sites Kgalagadi

No. transect

sites Kweneng Total

Grewia flava 16 15 18 49

Acacia mellifera 4 16 14 34

Dichrostachys cinerea 13 1 19 33

Acacia erioloba 13 10 4 27

Acacia tortilis 13 - 11 24

Boscia albitrunca 5 7 6 18

Terminalia sericea 1 1 14 16

Grewia flavescens 1 3 9 13

Ehretia rigida 7 1 4 12

Maytenus senegalensis - - 12 12

Acacia Leuderitzzi 1 6 4 11

Grewia bicolor 11 - - 11

1.3.6.3. WOODY SPECIES COUNTS

In addition to the number of locations (transect sites) being recorded for the

identification of each species, the number of plants was recorded at each

transect site. As with the herbaceous species, this allows for a comparison

between how widespread a particular species is across locations (Table 1.39),

and how dense the population of plant herbaceous plant species is within

particular locations (transects sites; Table 1.40; most commonly plants by

number of times identified).

As with the herbaceous species discussed above, there is some commonality in

woody plant species being widespread across and within locations. Plants

which appear most likely to form dense populations (Table 1.40) include

Diopyros lycioides, Maytenus senegalensis, and Euclea spp., though it is

notable that these species were only found at a relatively small number of

transect sites, suggesting that further field work may be required to determine a

more accurate average plant density. The data in the two tables may be

tentatively used to suggest that Maytenus senegalensis is a particularly

significant woody species in the Kweneng district.

53

Table 1.46. Number of times each woody species identified across all transect sites

where one or more identifications were made (all regions; frequent species only reported

by number of times plant identified).

Species full name

No. transects

where at least 1

plant counted

No. times plant

identified

Avg. no. plants per

transect site

Maytenus senegalensis 12 451 37.6

Grewia flava 49 292 6

Dichrostachys cinerea 33 240 7.3

Diopyros lycioides 5 192 38.4

Acacia mellifera 34 171 5

Acacia tortilis 24 156 6.5

Grewia avellana 2 148 74

Grewia flavescens 13 134 10.3

Acacia erioloba 27 127 4.7

Euclea spp 3 89 29.7

Terminalia sericea 16 71 4.4

Euclea schimperi 4 70 17.5

1.3.6.3. WOODY SPECIES HEIGHT

The height of each woody species counted was categorised as follows: between

0 and 0.5 metres; between 0.5 and 1 metre; between 1 and 2 metres; between 2

and 3 metres; and greater than three metres. The counts of the five most

commonly identified woody species (by number of transects identified, per

Table 1.38) is recorded below in Table 1.41. The results suggest that the most

commonly identified woody species across transect sites, Grewia flava, is a

shrub rather than a tree, rarely reaching a height greater than 2 metres in

communal grazing pastures. The other four most commonly identified species

listed in the table, in contrast, reach heights of 2 metres and above on a regular

basis, particularly Acacia mellifera of which over 30 per cent of plants

identified were 2 metres or higher.

54

Table 1.47. Proportion of woody species identified at various heights (metres) across all

transect sites surveyed (all regions; top five species by number of site identifications

only; %).

Species full name

Height

0 - 0.5

m

Height

0.5 - 1

m

Height

1 - 2 m

Height

2 - 3 m

Height

> 3 m n

Total

sites

Grewia flava 7.2 24.7 61.6 6.2 0.3 292 49

Acacia mellifera 40.9 9.9 18.1 15.2 15.8 171 34

Dichrostachys

cinerea 28.3 24.2 25.8 19.2 2.5 240 33

Acacia erioloba 48.8 27.6 7.1 3.9 12.6 127 27

Acacia tortilis 39.1 31.4 14.7 12.2 2.6 156 24

More detailed analysis of the data on woody species height may consider

factors such as the palatability and nutritional value of the commonly identified

species to livestock, their role in out-competing valuable pasture species in

communally grazed lands and therefore contributing to pasture degradation, and

the importance of higher-growing woody species in providing livestock with

shade and shelter, or acting as a wind break to assist with pasture quality

improvement. This analysis may also consider.

1.4. TANZANIA - EGGS

1.4.1. PRODUCTION AND PRODUCTIVITY

1.4.1.1. NUMBER OF EGGS PRODUCED

The 68 respondents to the alternative questionnaire indicated having a total of

442 hens that had laid eggs in the last 12 months (an average of 6.5 hens per

respondent).

In the existing egg questionnaire, respondents were asked to recall how many

eggs had been produced by their flock for each month over the last 12 months,

while in the alternative questionnaire, the respondents were asked to recall how

many hens laid eggs in the last 12 months, how many clutches each hen laid on

average during this time, and the number of eggs per clutch.

Both approaches facilitated calculation of indicators pertaining to how many

eggs were thought to be produced on each farm over a 12 month period.

Existing Questionnaire. Number of eggs Sep + Number of eggs Oct +

… + Number of eggs Aug.

55

Alternative Questionnaire. Number of hens laying eggs last 12 months x

Average number of clutches per hen x Average number of eggs per

clutch.

Gold standard daily data allowed an estimate of the number of eggs produced

per hen to be made for a 12 month period.

Gold standard data collection. (Number of eggs counted / number of

days data collection carried out for this hen) x 365 days.

The average number of eggs produced per existing questionnaire respondent’s

flock over a 12 month period was estimated at 107.6 (n = 67), whereas for

alternative questionnaire respondents it was estimated at 337.4 eggs per flock

over a 12 month period (n = 68). By comparison, the average number of eggs

produced per participant in the gold standard daily data collection over a 12

month period was estimated at 278.5 (n = 127), based on the number of eggs

produced over the time each hen was monitored.

Alternative questionnaire respondents were also asked to recall the average

number of clutches per hen (3.0 clutches on average, n = 68; Figure1.8), and the

average time from the beginning of one clutch to the beginning of the next

clutch (76.8 days, n = 67; Figure 1.9).

Figure 1.8. Average number of clutches per hen in last 12 months, Tanzania, alternative

questionnaire (n = 68).

56

Figure 1.9. Days from beginning of one clutch to beginning of the next clutch, Tanzania,

alternative questionnaire (% of respondents; n = 67).

Data on the number of clutches per hen and the number of eggs per clutch

collected for the alternative questionnaire were used to estimate the average

number of eggs produced per hen over a 12 month period amongst these

respondents.

Alternative Questionnaire. Average number of clutches per hen x

Average number of eggs per clutch.

The average number of eggs produced per hen amongst the respondents was

49.5 (n = 68). The range of responses is shown in Figure 1.10 below.

Figure 1.10. Number of eggs per hen in the last 12 months, including trendline, Tanzania,

alternative questionnaire (% of respondents; n = 68).

57


1.4.4. MORTALITY RATE HENS

Mortality rates will have an obvious impact on the productivity of farmer or

family hen flocks. The proportion of the sample flock in the study area dying

over the course of the gold standard daily data collection (average 13.7 days per

hen) was 5.9 per cent.

1.4.5. PRODUCTION AT DIFFERENT TIMES OF YEAR

Time of year affects the productivity of hens. Existing questionnaire data were

used to calculate the average proportion of respondent eggs produced in each

month per respondent (Figure 1.11), as well as the proportion of respondents to

this questionnaire whose flock was producing at least some eggs for each of

these months (Figure 1.12). These findings suggest that respondents to the

existing questionnaire were more likely to have productive hens in December,

as well as the period from June-August. Figure 1.13, produced from communal

data gathered in the Morogoro location, also suggests that egg production is

highest in the June-August period.

Existing Questionnaire. Times of year of high and low egg production.

Figure 1.11. Number of eggs as a percentage of total 12 month production per

respondent, Tanzania, existing questionnaire.

58

Figure 1.12. Proportion of respondents producing eggs for each month, Tanzania,

existing questionnaire (%).

Figure 1.13. Egg production per month as a percentage of all eggs produced, Tanzania,

communal question (%; n = 301).

1.4.6. PRODUCTIVITY OF DIFFERENT HEN BREEDS

Hen breeds amongst alternative questionnaire respondents are shown in Figure

1.14. Differences were found in the survey of the average eggs produced over a

12 month period per hen breed amongst respondents, as shown in Table 1.48.

Alternative Questionnaire. Influence of hen breed on egg production.

59

Figure 1.14. Breeds of hen, multiple response, Tanzania, alternative questionnaire

(n = 68).

Table 1.48. Average eggs produced per respondent for each of these hen breeds over a

12 month period, for the first or only breed of hen named by each respondent, Tanzania,


Breed Average n

Bukini 240 1

Indigenous 397.6 29

Kawa 488.9 9

Kawaida 233.6 29

During collection of the gold standard daily data, 354 hens were recorded as

having laid one or more eggs over the collection period (n = 127). Breeds of

hen observed during data collection are shown in Figure 1.15. These chicken

breeds were used to estimate the average eggs produced per hen over a 12

month period (Table 1.49).

Gold standard data collection. Influence of hen breed on egg

production.

60

Figure 1.15. Breeds of hen, Tanzania, gold standard daily data (n = 355)

Table 1.49. Estimated average eggs produced per hen over a 12 month period, Tanzania,

gold standard daily data.

Breed Average n

Improved 318.1 3

Indigenous 277.7 139

Kawaida 278.5 213

Breed not recorded 281.4 2

1.4.7. PRODUCTIVITY OF DIFFERENT MANAGEMENT

APPROACHES

As with breed, the survey work suggested that there may be a difference in hen

productivity on the basis of management approach. Of the 68 respondents to the

alternative questionnaire, 21 per cent transfer eggs from laying hens to brooding

hens, while 80.9 per cent remove eggs for sale, consumption, or to provide as

gifts to others.

The alternative survey data suggested that the strategy of removing eggs for

other uses may be associated with higher egg productivity (average of 373.2

eggs produced by the respondent over 12 months) than transferring eggs from a

laying hen to a brooding hen (average of 314.7 eggs produced by the

respondent over 12 months). This suggests that including these variables in the

61

alternative questionnaire allowed for a more nuanced exploration of factors

potentially associated with egg productivity.

1.5. TANZANIA – MILK

1.5.1. PRODUCTION AND PRODUCTIVITY

1.5.2. QUANTITY OF MILK PRODUCED

The respondents to the existing questionnaire milked a total of 479 cows in the

last 12 months (an average of 6.3 cows per respondent; n = 76). Breed was not

specified in the existing questionnaire.

Average daily milk production was estimated at 2 litres per cow amongst

existing questionnaire respondents. Given that cows may not be milked for the

whole calendar year, average annual milk production was calculated from the

existing questionnaire responses at 521.9 litres per cow.

Existing Questionnaire. Average milk production per cow per day.

Existing Questionnaire. Average milk production per cow per day x

Average number of months cows milked for x 30 (days/month).

Alternative questionnaire respondents milked a total of 422 indigenous cows in

the last 12 months (an average of 6.3 cows per respondent; n = 67), and a total

of 32 improved cows (an average of 1.1 cows per respondent; n = 28).

For the alternative questionnaire, respondents were able to indicate average

daily milk production over the whole lactation, for indigenous and improved

cows.

Average daily milk production over the whole lactation was estimated at 2.1

litres per cow amongst alternative questionnaire respondents for indigenous

cows, and 1.9 litres per cow amongst alternative questionnaire respondents for

improved cows.

Alternative Questionnaire. Average milk production per cow per day for

indigenous and improved cows.

In contrast, the gold standard daily data collection suggested an average daily

milk production across all cows monitored during the collection period, of 1.05

litres per cow.

62

Gold standard data collection. Average milk production per cow per

day.

Average daily milk production per respondent was calculated for each

respondent to the existing questionnaire, with an average of 15.4 litres.


Number of cows milked in the last 12 months.

From this same data set, average milk production per respondent was calculated

at 4,595.9 litres annually.


Number of cows milked in the last 12 months x Average number of

months cows milked for x 30 (days/month).


1.5.4. PRODUCTION AT DIFFERENT TIMES OF DAY

Time of day influences the productivity of cows milked. Collection of gold

standard daily data showed that some cows were milked twice per day (though

not every day) while others were milked once per day. Of those that were

milked once, milking was more likely to take place in the morning than in the

evening. Consequently, the average milk produced per cow for all the cows

monitored during data collection was 0.72 litres during the morning milking,

and 0.34 litres per cow during the evening milking.

Gold standard data collection. Influence of time of day on milk

production.


Time of year will also influence the productivity of cows. The existing

questionnaire asked the 76 respondents to recall in which month they

experienced their highest and lowest milk production, and to estimate how

many litres per cow per day were produced during each of these months.

During the highest month of milk production, the average milk production per

cow per day was 2.75 litres, whereas for the lowest month of milk production it

was 0.91 litres.

63

Existing Questionnaire; Communal. Influence of time of year on milk

production.

Figure 1.16 shows the number of existing questionnaire respondents

experiencing their highest and lowest months of milk production across the

calendar year. The data suggest that production peaks in the period of February-

April, with the highest month of production most likely to be in March. Low

production appears most likely to be experienced in the period June-September,

with lowest production most likely to be experienced in August.

Figure 1.16. Number of respondents experiencing highest and lowest milk production of

their cow/s, for each month of the calendar year, Tanzania, existing questionnaire (n = 76).

These findings show some correspondence with the communal questionnaire

addressed to research participants in the Morogoro location, which asked them

to indicate the distribution of milk production over the year (Figure 1.17). This

figure suggests that higher milk production was more likely to be experienced

in the March-May period.

Figure 1.17. Milk production per month as a percentage of all milk produced, Tanzania,

communal question (%; n = 300).

1.5.6. PRODUCTIVITY OF DIFFERENT COW BREEDS AND DURING

LACTATION PERIOD

Information on the cattle breed was recorded during gold standard data

collection and was collected using the alternative questionnaire.

64

During gold standard daily data collection, 258 indigenous cows were

monitored, along with 78 improved cows, and a further 6 for which the breed

was not specified. Analysis of the daily data showed that, on average, improved

cows produced nearly three times as much milk on a daily basis as indigenous

cows (2.1 litres per day for improved cows, compared to 0.73 litres per day for

indigenous cows).

Gold standard data collection. Influence of breed on milk production.

Some 67 alternative questionnaire respondents indicated that they had milked a

total of 422 indigenous cows over the previous 12 months (an average of 6.3

indigenous cows per these respondents), whereas 28 alternative questionnaire

respondents had milked 32 improved cows over the same period (1.1 cows per

these respondents on average).

The alternative milk questionnaire provided respondents with the opportunity to

provide more details on milk production during the lactation period of their

cows, for both indigenous and improved cows. Of the 68 responses with regards

to indigenous cows, an average of 532.8 litres of milk produced per lactation

was estimated:

Alternative Questionnaire. Average daily milk production per

indigenous cow over the whole lactation x Average number of months

milked per indigenous cow x 30 (days/month).

For improved cows, the average milk production per lactation (from 28

responses) was estimated at 412 litres:

Alternative Questionnaire. Average daily milk production per improved

cow over the whole lactation x Average number of months milked per

improved cow x 30 (days/month).

Alternative questionnaire respondents were also asked to recall the average

daily milk production of their indigenous and improved cows for the first three

months of the lactation period, as well as for the remainder of the lactation

period. Despite the average production per whole lactation period being

estimated at a lower amount for improved cows, daily production in the first

and third months of lactation appeared to be higher than for indigenous cows on

a per cow basis (Table 1.50 and Figure 1.18).

65

Table 1.50. Average daily milk production during lactation period (litres/cow), Tanzania,

alternative questionnaire (indigenous and improved cows).

First Month Second Month Third Month

After Third

Month

Indigenous cows 2.24 2.05 1.76 1.35

n (Indigenous) 67 65 64 65

Improved cows 2.54 2.01 1.88 1.34

n (Improved) 28 28 28 28

Figure 1.18. Average daily milk production (litres/cow), Tanzania, alternative

questionnaire (indigenous and improved cows).

1.6. INDONESIA – CATTLE AND GOATS


The questionnaire explored animal types kept on respondent farms (with a

focus on cattle and goats), changes to herd structure, responsibility of

household members for animal husbandry, feed types used, and use of cattle for

draught power.

1.6.2. HERD NUMBERS AND CHARACTERISTICS

Respondents indicated that they kept on average 3.7 cows and 4.7 goats (Table

1.51). Some respondents also kept domestic poultry (chickens and ducks),

however these numbers have not been reported because of the small number per

respondent, and the small number of respondents keeping these animals.

66

Table 1.51. Numbers of cattle and goats kept by respondents, Indonesia, questionnaire.

Total number of

animals kept by

the respondents

Average number of

animals kept per

respondent

Percentage of

respondents keeping

each animal type

(multiple response)

n

Cattle 815 3.7 53.7% 21

9

Goats 834 4.7 43.6% 17

8

1.6.3. HERD MANAGEMENT

Respondent households were slightly more likely to own cattle than to be

looking after other people’s cattle (‘present in the household’) and as likely to

own goats as to be looking after them (Table 1.52). Adult females (cattle and

goats) were most likely to be present or owned in the households. The survey

suggested that some 10 per cent of respondents who had cattle used their cattle

for draught power. Of these respondents, the large majority used their cattle for

transportation, with a relatively small number using them for ploughing or other

unspecified purposes.

Table 1.52. Household cattle numbers; types currently present and average numbers

looked after and/or owned, Indonesia, questionnaire.

Cattle Present in household n Owned by

household n

Male calves 1.37 99 1.38 98

Bulls 1.37 52 1.39 49

Steers 1.00 1 1.00 1

Female Calves 1.65 126 1.67 123

Cows 1.94 191 1.94 186

Heifers 1.30 27 1.35 23

Goats Present in household n Owned by

household n

Male Kids 1.80 98 1.77 93

Adult Male Goats 1.43 47 1.45 44

Female Kids 1.80 127 1.80 122

Adult Female

Goats 2.27 161 2.25 157

67

Adult male household members were approximately three times as likely to be

responsible for looking after both cattle and goats than adult female household

members. Likewise, children were approximately twice as likely to look after

these animals as adult females (Table 1.53). Adult females were much more

likely to be responsible for these animals than cattle or goats.

Table 1.53. Responsibility of household members for animal husbandry (n = 408, multiple

response), Indonesia, questionnaire.

Adult Female Adult Male Child

Cattle 16.5 53.7 29.8

Goats 15.2 55.4 29.3

Ducks 40.0 51.4 8.6

Chickens 38.1 49.2 12.7


Respondents were given the opportunity to indicate changes to the structure of

their herd (numbers and type of cattle and goats) since last Eid al-Adha

(October 4th, 2014). The average changes are presented in Table 1.54 and Table

1.55. These tables show average number of animals rather than percentage

changes to the cattle or goat herd sizes. For example, where Table 1.54 shows

that average total additions to the herd was ‘0.26’, this refers to 0.26 of a whole

animal, rather than a 26 per cent increase in herd size over this time. The data

therefore suggest that cattle herds were relatively static over this time, and goat

herds slightly less so. This is to be expected given that average herd size was

relatively small to begin with (Table 1.51).

In the case of both cattle and goats, leaving the herd (for example to be sold

privately or at a market) was the most common way in which the herd was

reduced over this period. The number of goats born per respondent was

approximately three times the number of cattle born, however on average the

size of cattle and goat herds alike became slightly smaller over this period

(average deductions from herd being slightly larger than average additions to

herd).

The average data can be converted to percentages by dividing the numbers in

these two tables by the average total herd size (Table 1.51). This allows

estimates to be calculated of death and slaughter rates, taking into account that

the average herd size excludes animals which left the herd in this manner before

the survey took place. Nonetheless, using this approach makes it possible to

estimate an average mortality rate of cattle (total cattle deaths) amongst

68

respondents over this period of approximately 2.4 per cent (0.09 total cattle

deaths on average, of an average total herd size of 3.7). Using the same

approach, average mortality rate for goats was approximately 3.4 per cent.

Average slaughter rates may likewise be estimated at 1.6 per cent in cattle

herds, and 1.7 per cent in goat herds.

Table 1.54. Average changes to cattle numbers (additions and deductions) since last

Eid al-Adha (n = 408), Indonesia, questionnaire.


Births

Number of cattle born 0.22


Adult Male 0.01

Adult Female 0

Young Growing Male 0.02

Young Growing Female 0.01

Average total additions to herd 0.26


Left the herd

Adult Male 0.04

Adult Female 0.05



Cattle slaughtered

Adult Male 0.05

Adult Female 0.01

Young Growing Male 0

Young Growing Female 0

Cattle deaths

Adult Male 0.01

Adult Female 0.03



Cattle lost

Adult Male 0.01

Adult Female 0.01



Average total deductions from herd 0.33

69

1.6.5. FEED SOURCE/S LIVESTOCK

Survey respondents were asked to indicate which feed/s they used for their

cattle over the last 12 months. As Table 1.56 shows, the respondents were most

likely to use collected native grasses to feed both their cattle and goats,

followed by stover (e.g. rice straw, maize) and grazing. Purchased roughages,

concentrates or rice bran, were rarely if ever used by the respondents.

Table 1.55. Cattle and goat feeding practices; proportion of respondents using various

feed type/s over the past 12 months (%; multiple response; n = 408), Indonesia,

questionnaire.

Cattle Goats

Grazing 31.4 30.7

Planted forages (e.g. elephant grass) 16.2 1.5

Collected native grasses 50.2 42.4

Stover (e.g. rice straw, maize) 37.2 34

Rice bran produced on farm 24.3 1.1

Tree legumes (e.g. sesbania) 0.2 0.7

Urea for feeding - -

Purchased roughages - -

Purchased concentrates or rice bran 0.4 -

Other feeds (Kolonjono) 0.5 -


Enumerators recorded baseline body condition score, weight (in kg) and girth

measurement (in cm) of selected cattle and goats amongst the respondents,

tagged these animals, and returned every three weeks to record changes in these

measurements. In most cases, the enumerators recorded these data for tagged

animals on three separate occasions. Additionally, the breed (where known),

age and sex of each animal was recorded. This allowed exploratory

development of indicators of cattle production on the basis of age, sex and

breed, both at the point of baseline measurement, as well as exploring changes

to animal condition over time.

To allow averages for the measurements of productivity to be produced on the

basis of age, cattle and goats were grouped into functional age categories as

follows:

Cattle: calves (0 – 8 months of age); weaners (9 – 12 months of age);

young adults (13 – 24 months of age); and adults (25+ months of age).

70

Goats: young goats (0 – 4 months of age); young growing goats (5 – 12

months of age); adult goats (13+ months of age).


The average body weight and girth measurement of cattle and goats of the

various age categories are presented in Table 1.57 and Table 1.58, and show a

clear and expected linear relationship between age and gains in weight and size.

Gold standard data collection. Average body weight x age of cattle or

goats.

Gold standard data collection. Average girth measurement x age of

cattle or goats.

Table 1.56. Average body weight (kg) for cattle and goats of various age categories,

Indonesia, gold standard data, baseline observation.

Cattle Average Std Dev n

Calves 112.2 75.8 97

Weaners 178.2 67.3 59

Young Adults 233.3 115.9 200

Adults 274.9 100.4 352


Young Goats 13.2 9.1 115

Young Growing Goats 26.0 13.2 174

Adult Goats 38.5 12.8 337

Table 1.57. Average girth measurement (cm) for cattle and goats of various age

categories, Indonesia, gold standard data, baseline observation.

Cattle Average Std Dev n

Calves 108.7 24.9 97

Weaners 130.2 17.2 59

Young Adults 147.3 65.3 200

Adults 158.7 70.4 352


Young Goats 52.4 7.8 115

Young Growing Goats 62.7 8.3 174

Adult Goats 74.6 7.6 337

71

Body condition score (BCS) was recorded on a scale of 1 (poor condition) to 5

(excellent condition) for all cattle and goats observed (Figure 1.19 and Figure

1.20). These figures show that cattle of all ages were most likely to attract a

BCS of 3, whereas goats were most likely to attract a BCS of 4. Older cattle

(young adults and adults) were more likely to be given a BCS of 4 than younger

cattle (calves and weaners), while young and young growing goats were more

likely to be given a BCS of 2 than adult goats.

Gold standard data collection. Proportion of cattle or goats under each

BCS x age of animals.

Figure 1.19. Average body condition score (BCS) for cattle of various age categories,

Indonesia, gold standard data, baseline observation (% of cattle in each category)

Figure 1.20. Average body condition score for goats of various age categories, baseline

observation (% of goats in each category)

72

1.6.8. LIVESTOCK GROWTH RATES

Given that enumerators visited each farm to measure weight and girth

measurement of cattle and goats on three separate occasions at three weekly

intervals, it was possible to produce indicators of observed growth rate between

visits.

The average growth rate in terms of weight (kg) and girth measurement (cm) of

cattle of the four functional age categories is presented in Figure 1.21 and

Figure 1.22. These results suggest that younger cattle (calves and weaners)

were more likely to gain weight over the period between the first and third

visits than older cattle whose rate of growth will have slowed or stopped. Adult

cattle lost just approximately one kg on average over this period, while girth

measurement declined by over five cm on average. This is perhaps a function of

seasonal factors such as climate, feed quality and availability, or incidence of

disease.

The results also suggest that there is a weak relationship between weight and

girth measurement of cattle, so that girth measurement may not necessarily be

used as a proxy measure for weight gain or loss.

Gold standard data collection. Changes in body weight x age of cattle.

Gold standard data collection. Changes in girth measurement x age of

cattle.

Figure 1.21. Average change in weight of cattle of different age categories between

enumerator visits (kg), Indonesia, gold standard data.

73

Figure 1.22. Average change in girth measurement of cattle of different age categories

between enumerator visits (cm), Indonesia, gold standard data.

Average changes to weight and girth measurement for goats are presented in

Figure 1.23 and Figure 1.24. As was the case with cattle, these confirm that

younger goats growth rates were higher than those for adult goats, which were

relatively stagnant. A comparison of the two charts suggests that there is a

closer correlation between weight change and girth measurement change than

there was for cattle, however there remain clear differences between the two

(for example comparing average weight change and girth measurement change

for young growing goats between the second and third visits). Nonetheless, the

suggestion of correlation means that further consideration is warranted of the

potential for using girth measurement as a proxy indicator for weight

measurement of goats.

Gold standard data collection. Changes in body weight x age of goats.

Gold standard data collection. Changes in girth measurement x age of

goats.

74

Figure 1.23. Average change in weight of goats of different age categories between


Figure 1.24. Average change in girth measurement of goats of different age categories

between enumerator visits (cm), Indonesia, gold standard data.

75

1.6.9. PRODUCTIVITY OF LIVESTOCK OF DIFFERENT GENDER

The sex of the observed cattle and goats was recorded, and has been used in the

remainder of this section to illustrate the influence of sex on productivity and

growth rates. Proportion of cattle and goats of each sex in each age category is

presented in Table 1.59.

Table 1.58. Proportion of observed cattle and goats of each sex, by age category (%),

Indonesia, gold standard data.

Cattle Female Male - Intact Male - Castrated n

Calves 56.1 43.9 0 98

Weaners 50.8 49.2 0 59

Young Adults 62.5 37.5 0 200

Adults 93.2 6.5 0.3 352

Goats Female Male - Intact Male - Castrated n

Young Goats 63.5 36.5 - 115

Young Growing Goats 66.9 33.1 - 175

Adult Goats 86.6 13.4 - 337

The average weight, girth measurement and BCS of cattle by sex are presented

in Figure 1.25, Figure 1.26 and Figure 1.27. These reveal that while the BCS of

older male cattle was higher on average than female cattle, the average body

weight and girth measurement of adult female cattle was higher. Figure 1.26

and Figure 1.27 also show some correlation between all three measures,

particularly where the average BCS, weight and girth measurement declines or

stagnates from young adult to adult cattle.

Gold standard data collection. Changes in body condition score x age x

sex of cattle.

Gold standard data collection. Changes in body weight x age x sex of

cattle.

Gold standard data collection. Changes in girth measurement x age x

sex of cattle.

76

Figure 1.25. Average body condition score by age and sex of cattle, Indonesia, gold


Figure 1.26. Average body weight (kg) by age and sex of cattle, Indonesia, gold standard

data, baseline observation.

77

Figure 1.27. Average girth measurement (cm) by age and sex of cattle, Indonesia, gold


Average BCS, weight and girth measurement of goats by sex are shown in

Figure 1.28, Figure 1.29 and Figure 1.30. These show a marked difference in

the average BCS of female compared to male goats, particularly in the case of

adult goats. However, Figure 1.29 and Figure 1.30 also demonstrate close

similarity in average body weight and girth measurement between female and

male goats. These charts also show a strong linear relationship between these

measures of production and age, and support the principle that further

exploration of girth measurement as a proxy indicator for weight of goats is

warranted.

Gold standard data collection. Changes in body condition score x age x

sex of goats.

Gold standard data collection. Changes in body weight x age x sex of

goats.

Gold standard data collection. Changes in girth measurement x age x

sex of goats.

78

Figure 1.28. Average body condition score by age and sex of goats, Indonesia, gold


Figure 1.29. Average body weight (kg) by age and sex of goats, Indonesia, gold standard

data, baseline observation.

79

Figure 1.30. Average girth measurement (cm) by age and sex of goats, Indonesia, gold


Average changes to the weight of female and male cattle are presented below in

Figure 1.31 and Figure 1.32. These results are notable for the difference in

cattle weight change based on sex. Female cattle show a relatively linear pattern

of weight gain being more significant for growing cattle (calves, weaners and to

a lesser extent young adult cattle), with adult female cattle weight change being

almost stagnant over this time (Figure 1.31). In contrast, the weight gains of

male cattle over this time showed a much less clear relationship to age, while

adult male cattle appeared to lose quite significant amounts of weight over the

data collection period (Figure 1.32).

80

Figure 1.31. Average change in weight of female cattle of different age categories between


Figure 1.32. Average change in weight of male cattle of different age categories between


81

Figure 1.33. Average change in weight of female goats of different age categories

between enumerator visits (kg), Indonesia, gold standard data.

Figure 1.34. Average change in weight of male goats of different age categories between


82

1.7. INDONESIA – MILK


The questionnaire explored the cattle and farming production context of the 60

respondents (all located in Malang), including herd structure, husbandry, other

livestock, and milk production and usage.

1.7.2. HERD NUMEBRS AND CHARACTERISTICS

The 60 respondents kept an average of 6.3 cattle of any type. Some 13

respondents kept goats (average 4.2 kept per respondent), while 9 respondents

kept chickens (average 6 kept per respondent), and 2 respondents kept ducks

(average 3 kept per respondent).

1.7.3. HERD MANAGEMENT

Respondents were more likely to be looking after cattle in the household rather

than owning the cattle personally (Table 1.60). Household cattle numbers

suggested that cows were most likely to be present in each household, followed

by female calves and heifers. No respondents kept steers (either owned or

looked after), and none of the respondents used their cattle for draught power.

Table 1.59. Household cattle numbers; types currently present and average numbers

looked after and/or owned, Indonesia, questionnaire (n = 60).

Average number looked after Average number owned n

Calves (Male) 1.3 1.1 29

Calves (Female) 1.7 1.3 32

Bulls (2 yrs+) 1.1 0.9 8

Steers - - -

Cows 4.3 3.1 60

Heifers 1.5 1.0 22

In 58 of the 60 households, one or more adult males were responsible for

looking after the cattle, while adult females were responsible for looking after

the cattle in 22 of the 60 households. Only in 2 cases were children partly or

fully responsible for cattle husbandry. Across the response group, adult females

and/or children appeared to be somewhat more likely to be responsible for

looking after chickens and goats.

83


Respondents were given the opportunity to indicate changes to the structure of

their herd (numbers and type of cattle) since last Eid al-Adha (October 4th,

2014). Female cattle (adult or young growing) were the most likely to be added

to the herd (Table 1.61). Private sale or sale at market were the most likely

ways used by respondents to dispose of cattle, and the survey suggested that

these were also the most likely sources from which respondents obtained new

cattle. Herd size was growing, reflected by the average total additions to the

herd (1.83) being larger than the average total deductions from the herd (1.02;

Table 1.61).

Table 1.60. Average changes to herd numbers (additions and deductions) since last

Eid al-Adha, Indonesia, questionnaire (n = 60).


Births

Number of cattle born 0.87


Adult Male 0.03

Adult Female 0.77



Average total additions to herd 1.83


Private Sale 0.41

Sale at Market 0.40


Trader (outside of market) 0.13

Cattle deaths

Disease 0.05

Average total deductions from herd 1.02

1.7.5. FEED SOURCES/S OF LIVESTOCK

Survey respondents were asked to indicate which feed/s they used for their

cattle over the last 12 months. Purchased concentrates or rice bran, and planted

forages, were the most likely feed sources for cattle (Table 1.62). This may be

contrasted with the Indonesian cattle and goat survey, where no respondents

were found to use purchased concentrates or rice bran (Table 1.56).

84

Table 1.61. Cattle feeding practices; proportion of respondents using various feed type/s

over the past 12 months, Indonesia, questionnaire (%; multiple response; n = 60).

Feeding practice Proportion of respondents (%)

Purchased concentrates or rice bran 93.3

Planted forages (e.g. elephant grass) 56.7

Stover (e.g. rice straw, maize) 36.7

Sugarcane shoots/top stem 33.3

Collected native grasses 20.0

Rice bran produced on farm 20.0

Purchased roughages 10.0

Urea for feeding 3.3

Bread 3.3

Grazing 1.7

Tree legumes (e.g. sesbania) 1.7

1.7.9. QUANTITY OF MILK PRODUCED

Both the questionnaire and the gold standard data included information on milk

production. In the questionnaire, daily milk production was estimated by the 60

survey respondents at 15.57 litres per cow on average.

Under the gold standard approach, fortnightly data were collected for two cows

for each respondent: a high production cow, and a low production cow. The

data were collected where possible at fortnightly intervals for each respondent,

at morning and again in the evening for the second milking. Of the 60 high

production cows observed during this eight week data collection period, the

average milk produced per day was 15.68 litres (comparable to respondent

estimates of daily milk production per cow, detailed above), whereas for the 60

low production cows it was 10.09 litres. Across the 120 observed cows, average

daily milk produced was therefore 12.89 litres.

In addition to estimating daily milk production per cow, the questionnaire asked

respondents to indicate how many cows were milked over the last 12 months, as

well as the average number of months that each respondent’s cow/s were

milked.

85

This information was used to estimate average annual milk production per cow,

at 3,503 litres (n = 60)

Questionnaire. Average milk production per cow per day x Average

number of months cows milked for x 30 (days/month).

The data on average number of months cows were milked for (based on

respondent recall), were used alongside the fortnightly data collected on milk

production to produce a second estimate of average annual milk production per

cow, for the high and low production cows, as well as for all 120 cows

observed during data collection. The results were as follows: high production

cow – 3,671.45 litres (n = 60); low production cow – 2,339.50 litres (n = 60);

all cows observed – 3,005.45 litres (n = 120).

Questionnaire (Q) and Gold standard (GS) data. Average milk

production per high production cow per day (GS) x Average number of

months cows milked for (Q) x 30 (days/month).


production per low production cow per day (GS) x Average number of

months cows milked for (Q) x 30 (days/month).


production per observed cow per day (GS) x Average number of months

cows milked for (Q) x 30 (days/month).

Average daily milk production per respondent, based on each respondent’s

estimation of average daily milk production per cow in the questionnaire, was

57.55 litres (n = 60).

Questionnaire. Average milk production per cow per day x Number of

cows milked in the last 12 months.

Average annual milk production per respondent was calculated from the

questionnaire data, at 13,518 litres (n = 60).

Questionnaire. Average milk production per cow per day x Number of

cows milked in the last 12 months x Average number of months cows

milked for x 30 (days).

86


1.7.11. PRODUCTION AT DIFFERENT TIMES OF DAY

All cows observed during fortnightly data collection were milked twice per day.

The productivity of cows was higher in the morning milking than in the evening

milking, at an average of 7.6 litres and 5.29 litres respectively (n = 120), over

the data collection period. High production cows produced, on average, 9.18

litres of milk in the morning and 6.5 litres in the evening (n = 60), while low

production cows produced an average of 6.02 litres in the morning milking, and

4.08 litres in the evening (n = 60).

Gold standard data collection. Influence of time of day on milk

production.

Gold standard data collection. Influence of productivity of individual

cows on daily milk production.


The questionnaire asked respondents to indicate during which period (month) of

the year milk production was highest, and lowest. Figure 1.35 shows the

number of respondents experiencing their highest and lowest months of milk

production across the calendar year. The data suggest that milk production is

most likely to peak in the months of May and September, but that the period of

low milk production is most likely to occur in March, or in the July-September

period. The unexpected and relative correlation of high and low milk

production amongst the respondents to the Indonesian questionnaire,

particularly for September, may be contrasted with the response to the

Tanzanian questionnaire, which showed a much clearer distinction between

months of high and low production (Figure 1.16).

Questionnaire. Influence of time of year on milk production.

87

Figure 1.35. Number of respondents experiencing highest and lowest milk production of

their cow/s, for each month of the calendar year, Indonesia, questionnaire (n = 60).


The Indonesian fortnightly data collection recorded the age (in months), body

condition score (BCS) and girth measurement (cm) of the high production and

low production cows observed.

For the high production cows (n = 60), the following results were observed:

Average age (months): 48.38

Average BCS: 3.15

Average girth measurement (cm): 168.77

The results for low production cows were as follows:

Average age (months): 59.67

Average BCS: 2.77

Average girth measurement (cm): 161.83

The data therefore show that high production cows are younger, have a

healthier BCS, and a larger girth measurement, and highlight the role that gold

standard data collection has made in facilitating these conclusions.

88

1.7.14. PRODUCTIVITY OF COWS WITH DIFFERENT PHYSICAL

CHARACTERISTICS

The data regarding age, BCS and girth measurement allowed correlations

between these features of the observed cows and milk production to be

explored. All features were observed to have some impact on the daily milk

productivity of the observed cows.

Gold standard data collection. Influence of body weight, girth

measurement, and body condition score on daily milk production.

The age of both high (n = 60) and low (n = 60) production cows appeared to be

positively correlated to average daily milk production – generally, older cows

produced more milk per day than younger cows (Figure 1.36 and Figure 1.37).

Figure 1.36. Average daily milk produced (litres) by high production cows during the data

collection period, by age (months) of cow, including trendline, Indonesia, gold standard

data.

89

Figure 1.37. Average daily milk produced (litres) by low production cows during the data

collection period, by age (months) of cow, including trendline, Indonesia, gold standard

data.

BCS also appeared to have a generally positive correlation with average daily

milk produced over the fortnightly data collection period (Table 1.63), although

amongst the high production cows observed, those with a BCS of 3 produced

more milk daily on average, than those with a BCS of 4.

Table 1.62. Average daily milk production (litres) for each Body Condition Score for high

(n = 60) and low (n = 60) production cows, Indonesia, gold standard data.

Body Condition Score Daily Milk Production

(litres) n

High Production Cows 2 9.25 1

3 15.85 49

4 15.48 10

Low Production Cows 2 8.53 14

3 10.4 46

Unlike the results with respect to the age of the cows observed during

fortnightly data collection, the correlation between daily milk production and

girth measurement differed for the high and low production cows. These data

suggest that girth measurement was negatively correlated with daily milk

production in the case of high production cows (Figure 1.38), and positively

correlated in the case of low production cows (Figure 1.39).

90

Figure 1.38. Average daily milk produced (litres) by high production cows during the data

collection period, by girth measurement (cm) of cow, including trendline, Indonesia, gold

standard data.

Figure 1.39. Average daily milk produced (litres) by low production cows during the data

collection period, by girth measurement (cm) of cow, including trendline, Indonesia, gold

standard data.

91

1.7.15. PRODUCTIVITY OF DIFFERENT MANAGEMENT

APPROACHES

Finally, suckling practices appear to be correlated with the average daily milk

production per cow amongst the questionnaire respondents. Of the 37

respondents who allow limited calf suckling on their cows, daily milk

production per cow was estimated at 14.4 litres. However, for the remaining 23

respondents who did not allow any calf suckling, daily milk production per cow

was estimated at 17.5 litres. No respondent indicated that they allowed their

calves to suckle to an unlimited extent.

Questionnaire. Influence of calf suckling practice on daily milk

production.

92

2 Actual Data from TEST

Phase Fieldwork on Costs of

Data Collection

EXCH RATE EXCH RATE EXCH RATE

2190.44 11.2486 13,586.99

TZ costs BOTS costs IN costs

day rate (TSH)day rate BPA)

Training costs

Trainers' time per day 120,000 130 454,545

Trainees' time per day 90,000 59 227,273

Meals per day per person 10,000 225 50,000

Accommodation per day per person 186,187 844 1,000,000

Transport per day per person 5,000 112 50,000

Facilities per day 1,000,000 2,250 1,000,000

Equipment per event 1,000,000 2,250 1,000,000

Stationery per event 1,000,000 2,250 1,000,000

Survey personnel

Supervisors per day 120,000 130 454,545

Enumerators per day 90,000 59 227,273

Extension officers and local officials per diems per day 90,000 100 300,000

Drivers per day 80,000 130 300,000

Logistic costs

Fuel per day per car 47,971 223 252,718

Car R&M per car per event 500,000 3,375 4,076,097

Phone cards per event 280,000 1,125 1,358,699



Data entry



Communal data collection



Extension officers and local officials per diems per day per person 90,000 100 300,000

Drivers per day 80,000 130 300,000

Car R&M per car per event 500,000 3,375 4,076,097

Fuel per day per car 47,971 223 252,718



Transport per day per person 5,000 112 50,000

Other costs per day per person 5,000 56 67,935

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