Beneficiary Results Assessment Survey ReportConducted in 9 project districts
Government of NepalMinistry of Agriculture Development
Agriculture and Food Security project
February, 2016
Technical Assistance: Food and Agriculture Organization of the United Nations
AcronymsAFSP : Agriculture Food Security Project
BRA Survey: Beneficiaries Result Assessment Survey (output survey)
DIME : Development Initiatives for Impact Evaluation
DPSU : District Program Support Unit
DTOs : District Technical Officers
FAO TA : Food and Agriculture Organization Technical Assistance
FY : Fiscal Year
FYM : Farm yard manure
GAFSP : Global Agriculture and Food Security Program
GM : Grinding Machine
GoN : Government of Nepal
Ha : Hectare
HH : Household
ICS : Improved Cooking Stove,
IWM : Improved Water Mill
M&E : Monitoring and Evaluation
MDD : Minimum Dietary Diversity
MoAD : Ministry of Agricultural Development
N : Total sample size (Number)
PAD : Project Appraisal Document
PMU : Project Management Unit
PNW : Pregnant and Nursing Women
PPS : probability proportional to Size
SD : Standard Deviation
VDC : Village development committee
WB : World Bank
WDDS : Women’s Dietary Diversity Score
Table of Contents
Acronyms............................................................................................................................................................2
1 BACKGROUND............................................................................................................................................8
2 OBJECTIVE...................................................................................................................................................8
3 METHODOLOGY..........................................................................................................................................8
4 SAMPLE SIZE...............................................................................................................................................9
5 LIMITATION..............................................................................................................................................10
6 FINDINGS..................................................................................................................................................11
6.1 Demography................................................................................................................11
6.2 Key indicators of Result Framework............................................................................12
6.2.1 Yield of major crops at household level.......................................................................12
6.2.2 Seed Replacement Rate of major crops.......................................................................13
6.2.3 Productivity of Livestock products...............................................................................14
6.2.4 Nutrition indicators......................................................................................................146.3 Findings on other relevant indicators.........................................................................15
6.3.1 Changes in cropping intensity and cropping pattern before and after small irrigation support.........................................................................................................................15
6.3.2 Changes in proportion of HH adopting improved crop management practices...........16
6.3.3 Production, consumption and sales of vegetables at HH level.....................................16
6.3.4 Proportion of improved and local Livestock breed at HH level (goat, buffalo, cattle & poultry)........................................................................................................................17
6.3.5 Changes in production and productivity level of milk and eggs...................................18
6.3.6 HH adopting improved livestock breeds and management practices..........................18
6.3.7 Plantation of fodder and forage...................................................................................19
6.3.8 Minimum dietary diversity (MDD) of women..............................................................19
6.3.9 Women involvement on groups...................................................................................20
6.3.10 Proportion of HHs using women drudgery reduction technologies.............................21
6.3.11 Project contribution in enhancing livelihoods, increasing supply of meat products and enhancing nutritional status........................................................................................22
7 LESSONS LEARNT...........................................................................................................................................25
Annex-1: Details of sample districts, VDCs and sample size.............................................................................26
Annex-2 Survey Questionnaire.........................................................................................................................27
A. Executive Summary
This beneficiary results assessment survey (output survey) has been conducted as an internal monitoring of project interventions to assess the immediate and intermediate outputs/results of crop, livestock and nutrition intervention and also to determine the adoption level of improved technologies. Information has been collected from 1093 respondent beneficiary households of nine sample districts and 140 Households of seven districts (control VDCs of baseline). Sampling technique has been used to select the districts, VDCs and beneficiaries. Details are provided in the methodology part. The field survey task was carried out by the project field staff by themselves during the month of November 2015.
The findings of report are presented in three sub headings namely; demography, findings on key result framework indicators and other relevant indicators.
Analysis on the changes in the result framework Indicators
As suggested by MTR mission, DIME and PMU worked together for the calculation of Key indicators of Result framework with due consideration to the contribution of AFSP interventions (treatment effect). Due to the delay in the conduction of midline survey1, the output survey results have been used as preliminary estimate for measuring the changes in the result framework indicators for MTR purpose.
Firstly, for proper comparison, DIME calculated the baseline value based on the same nine sample districts. Double difference was used to calculate the treatment effect of the project except few cases2 on which simple before and after difference was used; as there was massive increase/decrease in the control group. The final value for result framework indicators was calculated by adding the baseline value calculated for 19 districts to the treatment effect. The following tables give the synopsis of the changes in the key indicators of result frame work:
Table-I : Average productivity of major Crops (yield in tons/ha)
CropBaseline nine districts 2013
(DIME Survey)Output Survey nine Districts
2015 (PMU survey)
Double Difference (Treatment
Effect)
Baseline for all
treatment 19
Districts
Updated Producti
vity Value
for MTR)
Percentage
Increase in Yield
External control
Treatment
Difference at baseline
Control
Treatment
Difference at follow up/output
(I) (II) (III)=(II)-(I) (IV) (V) (VI)=(V)-(IV)
(VII)=(VI)-(III)
(VIII) (X) = (VII)+(VIII
(XI)= (VII)/(VIII)*100
Wheat 1.337 1.387 0.05 1.30 1.61 0.31 0.26 1.40 1.66 19 %
Maize 1.692 1.964 0.27 1.80 2.33 0.53 0.26 1.90 2.16 14%
Paddy 2.216 2.743 0.53 1.60 2.80 1.20 0.67 2.90 3.57 23%
Potato 5.846 5.502 (0.34) 4.70 5.60 0.90 1.24 4.80 6.04 26%Source: Baseline survey database, DIME, Aug 2014 and Output survey report, PMU, 2016
1 provisioned in PAD to be conducted by DIME, responsible entity for Impact evaluation for AFSP2Few cases include SRR of potato & maize and productivity of buffalo milk due to heavy imbalance in between Treatment and Control
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Treatment effects for the crop indicators have been calculated using a standard double-difference. The treatment effect was calculated using the Output survey and baseline, with data from both surveys restricted to the nine districts of the Output survey. The final value for the results framework was calculated by adding the baseline value (calculated using 19 districts) to the treatment effect. One point of note that although there is a positive estimated treatment effect, the yields for Paddy actually did not increase compared to the baseline. The positive effect came from the fact that production dropped in the control group, likely because of poor rains. However, such effects can still be counted as positive as the project likely prevented losses in yield despite the drought.
Table II: Seed Replacement Rate (in Percentage)
Crop Baseline Survey nine Districts (DIME)
Output Survey nine Districts, 2015 (PMU, survey)
After minus Before
Treatment
After minus Before Control
Double Differenc
e
BL value (treatment)
3
(X)
Treatment Effect, Final RF number
(XI)=(X)+ (IX)
External control
Treatment
Diff. at baseline
External Control (
Treatment
Diff at output survey
(I) (II) (III)= (II)-(I)
IV) (V) (VI) =(V) - (IV)
(VII)= (V)-(II)
(VIII)=(IV)-(I)
(IX)=(VII)-(VIII)
Main Paddy
1.58 1.37 (0.21) 7.03 12.99 5.96 11.62 5.45 6.17 7.20 13.37*
Wheat 1.13 0.67 (0.46) 5.26 9.80 4.54 9.13 4.13 5.00 4.60 9.60*
Maize 2.25 9.57 7.32 13.80 12.70 (1.10) 3.13 11.55 (8.42) 14.70 17.83**
Potato 0.00 19.83 19.83 3.86 27.27 23.41 7.44 3.86 3.58 16.00 23.44**
Source: Baseline survey database, DIME, Aug 2014 and output survey report, PMU, 2016Note:* used double difference; **used before and after difference
The situation for seed replacement rate calculation was a bit complicated. First of all, to make the data comparable, PMU and DIME agreed to make uniformity on the SRR definition, by including seeds received only from the reliable sources (Agro-vet, Government (DADO/NARC), Seed producers' group/cooperatives, purchased from a private company, or received from a NGO/INGO). This made changes in the numbers in the baseline report, as it also included seeds purchased from the local market, so the baseline numbers will need to be updated. Next, there was a complication as there were major differences between the SRR values at baseline between treatment and control, specifically for Maize and Potato. This tells us that the control VDCs were not adequate controls, as the use/availability of seeds in these was fundamentally different from the project area. Therefore a bit of an unorthodox strategy was used as per the recommendation of DIME. The treatment effect was calculated using the double-difference for SRR for Paddy and Wheat, whereas used a simple after-before difference for Maize and Potato. As for the other indicators, the final value was calculated by adding the treatment effect from double difference to the baseline value, where the baseline value was calculated using all 19 districts. (The treatment effect was calculated using just the 9 districts covered in the output survey.)
3Baseline Survey, 19 districts, DIME Survey, 20145
Table III: Productivity of Livestock ProductsLivestock products Baseline Survey 9 Districts
(DIME, 2013)Output Survey 9 Districts 2015
(PMU, survey)Treatment Effect Baseline
Values ( treatment, 19 districts)
Final RF Value
Effect %
External control
Treatment Diff
External Control
Treatment Diff
Double Diff. Or Before-After
(I) (II) (III)= (II)-(I) (IV) (V) (VI)=
(V)-(IV)(VII)=
(VI)-(III) (VIII)(IX)=(VII)+(VIII)
(X)=(VII)/
(VIII)*100Eggs/hen/year 21.923 14.989 (6.9) 27.0 37.0 10.0 16.9 20.0 36.9 84.7%*Cow Milk, liters/cow/year 226.457 232.819 6.4 249.0 377.0 128.0 121.6 263.4 385.0 46.2%*Buffalo Milk, liters/buffalo/year 503.755 617.107 113.4 627.0 687.0 60.0 69.9** 640.4 710.3 10.9%**
* Used double difference ** Used simple before-after difference
Treatment effects for the livestock indicators were bit more complicated. For eggs and cow milk, a standard double difference method was used. However, for Buffalo milk, it was felt that a double difference was unrealistic due to heavy imbalance in between treatment and control at baseline, as well as a very small sample size (N=30 in control) for buffalo milk at follow-up. Therefore, for buffalo milk, a simple before-after difference was used to calculate the treatment effect. The treatment effect was calculated using the output survey and baseline, with data from both surveys restricted to the 9 districts of the output survey. The final value for the results framework was calculated by adding the baseline value (calculated using 19 districts) to the treatment effect.
Table IV: Improved Dietary Practices (Percentage of children)
IndicatorsBaseline Survey, 9 Districts
(DIME)Output Survey, 9 Districts
(PMU, preliminary estimate)
Double Diff Baseline
number (from all 19
Districts)
Final Number
for Results Framew
orkControl
Treatment
Diff at baselin
e
Treatment
Control
Diff at follow up
(I) (II) (III)=(II)-(I) (IV) (V) (VI)= (V)-
(iV)(VII)= (VI)-
(III) (VIII)(IX)=(VII)+(VIII)
Women consumed animal proteins
50.75 54.99 4.24 83 62 21 16.77 56.00 72.77
Women consumed vegetables & fruits
54.14 52.29 (1.84) 85 50 35 36.84 57.00 93.84
Percentage of children having 3 IYCF practices
45.28 31.94 (13.34) 81 58 23 36.34 42.00 78.34
Source: Baseline survey database, DIME, Aug 2014 and output survey report, PMU, 2016
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Treatment effects for the nutrition indicators were calculated using a standard double-difference. The treatment effect was calculated using the follow up (output survey) and baseline, with data from both surveys restricted to the 9 districts of the follow-up survey. The final value for the results framework was calculated by adding the baseline value (calculated using 19 districts) to the treatment effect. There were a couple of key differences between the surveys that are worth noting. Although the results framework says that the IYCF indicator should be calculated for children 6-23 months, in the follow-up survey the exact age of the children was not recorded, so the values are for all children from 0-23 months. Additionally, questions about breastfeeding were not asked, which affects calculations on dairy consumption (which is part of the 3 IYCF practices).This was adjusted by assuming that 100% of children consumed milk products in the past 24hr, which was the estimate from baseline. Deviations from following 3 IYCF practices therefore come from the other two IYCF indicators (meal diversity and meal frequency).
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1 BACKGROUND
Agriculture and Food Security Project (AFSP) is jointly implemented by Ministry of Agricultural Development (MoAD) and Ministry of Health (MoH) in 19 mid and high hill districts of the Mid-western and Far-western development regions of Nepal4 with funding support of Global Agriculture and Food Security Program (GAFSP), the World Bank (WB) is the supervising entity. The project has been designed to enhance the food and nutrition security of targeted communities through a holistic set of interventions comprising of technology development, dissemination and nutrition related activities. The project aims to improve the livelihoods of crop and livestock farmers, women engaged in household /kitchen garden production and households with pregnant and nursing women. The project intends to serve nearly 162,500 beneficiary households of 190 VDCs directly over the period of five years (April 2013 – March 2018).The total funding of this project is US$ 58 million of which GAFSP contribution is US $ 46.5 million and contribution of GoN is US$11.5 million.
The project coverage is based on its’ VDC coverage plan-i.e, on three phases; in the first phase, coverage of two VDCs in each district (from FY 2013/14), second phase covered additional four VDCs totaling to six VDCs (from FY 2014/15) and third phase additional four VDCs with total coverage of 10 VDCs in each district (from FY 2015/16).
In Project Appraisal Document (PAD), provisions have been made to carry out baseline survey, mid-term survey and end project survey to assess the changes/impact on its’ result framework indicators. DIME has been made responsible for such surveys. DIME has accomplished baseline survey. Besides, in line with M&E Strategy of AFSP, the project has conducted Beneficiary results assessment survey (output survey) to determine/monitor the immediate outputs and results of the project interventions (crop, livestock and nutrition) in November 2015.
2 OBJECTIVE
The main objective of this survey was to monitor the immediate and intermediate outputs/results of project interventions at beneficiary level in the first phase and second phase VDCs and also aims to determine proportion of households receiving benefits from project interventions along with their perception on the usefulness of the project interventions. In specific, the survey will focus on to:
i. Assess the immediate outputs/results of project activities on crop, livestock and nutrition at beneficiary level
ii. Determine the adoption level of technologies delivered through project, and gather feedbacks for improvement
iii. Determine the level of awareness of beneficiaries on the environmental and social safeguard aspects
3 METHODOLOGY
For the selection of sample districts, all 19 project districts were divided into two strata, high hill and mid hill districts. At the first stage, 9sample districts were selected (approximately 50% of total
4Surkhet, Dailekh, Jajarkot, Rukum, Rolpa, Salyan, Pyuthan, Jumla, Humla, Dolpa, Mugu, Kalikot of Mid western region and Dadeldhura, Doti, Baitadi, Achham, Bajura, Bajhang and Darchula of far western region
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project districts).Four districts were selected from high hill districts and five districts from mid hill districts randomly.
At the second stage, within the selected districts, two VDCs were selected from six VDCs (2-first phase and 4-second phase VDCs), on which the project has already started its activities/interventions. Whilst selecting the VDCs in each district, the sampling frame was designed on such a way that one VDC was selected from first phase5VDCs (one of the two VDCs) and other one VDC were selected from the second phase4 VDCs (one of four VDCs). Simple Random Sampling method was used to select the sample VDCs. The total number of sample beneficiary HHs was estimated based on simple random sampling techniques with due consideration of non-response error and design effect. The number of sample households in the selected VDC was estimated based on probability proportional to Size (PPS) sampling method, the weights being the number of beneficiary household of selected VDCs. Within the selected VDC, the sample beneficiary HH was selected based on systematic sampling method from the beneficiary list of AFSP (crop and livestock).
Project field staffs were used as enumerators for the collection of information from selected households provided by PMU. A XLS data entry sheet was designed to enter the data collected from the field and XLS pivot table was used to analyze the data. This task was carried out by FAO TA team in close consultation with concerned PMU officials.
Please refer to annex-2 for the list of selected VDCs and number of sample HHs selected in the sample VDCs. In addition, survey was also carried out in 140 households of the 14 external control VDCs set out in 7 districts by the baseline survey. A set of questionnaire was developed to interview the selected HHs and attached herewith in annex-2.
With regards to the qualitative questions, the respondents were asked to provide their opinion on four ranks, 1, 2, 3 and 4. The score 1 was being the lowest and 4 being the highest. The estimate average score was calculated and compared with median score (2.5) to know on which direction the parameter stands for. Likewise, the data series was divided into four equal intervals, (Score 1-1.75) as Very Low, (1.75-2.5) as Low, as (2.5-3.25) High and (3.25-4) as very high; from which one can determine interval (level) to which the parameter fits on.
4 SAMPLE SIZE
The total number of sample HHs was estimated using the following formula for simple random sampling
Where,
n = sample size
SE=Standard error=should be used from past surveys=α * P(in this case, as past information of particular area not available)
α = level of significance(at95% confidence interval, α will be 5%) = 0.05
P= proportion that any element falls in the sample=50%=0.5
5First phase VDCs are those two VDCs on which project started interventions from FY 2013/149
n= 1SE2
P(1−P )+ 1N
N= population=Total beneficiaries of 6 VDCs of 19 districts on which project intervention started till FY 2014/15 (crop and livestock)=30,569HHs6
A total of 1233 HHs were interviewed (1093 project beneficiary households plus 140 non project beneficiary households) in this survey. The sample size was estimated using Simple random Sampling Techniques with due consideration to correction factor for non-response error considering rate of response of the population at 90%and change in sample design effect 7(@ 2.5 times of adjusted sample. Out of estimated sample size of 1112 HHs, 1093 HHs was interviewed, as the 19 selected HHs were not present in the village at the time of survey (seasonally migrated to India and Terai districts). The sample HHs for control VDCs were the same HHs that was set out during baseline survey. The list of external control VDCs and list of sample HHs was provided by DIME.
Administration of survey:
Concept note, survey questionnaire, instruction for enumerators, and sampling design of the Beneficiary Results Assessment Survey were prepared at central level by PMU with technical assistance of FAO TA. The name of sample VDCs, sample size and list of sample beneficiaries for interview was provided by PMU to District Project Support Unit (DPSUs). Regional M&E officers provided orientation and technical guidance to DTOs (Supervisors) on the objective and technical aspects (data collection forms and methodology) of the survey. DPSUs with the help of DTO/coordinator provided orientation to enumerators (Service provider field staff) on questionnaire and data collection method at field.
The (field staff) technicians and project facilitators of SP were used for collection of information at field.
DTOs performed as the role of survey supervisor in the districts and provided technical monitoring and assistance to enumerator (field staff) for the survey. In addition, Regional M&E officers also monitored the field during fieldwork for validation, quality assurance and necessary support to field staff. The monitoring plan of each district was prepared and submitted to PMU and FAO TA before field work by DPSU/DTOs. Besides, PMU officials and FAO TA professionals also carried out field supervision during the survey.
The filled questionnaires were submitted to DTOs by enumerators for validation and checking of questionnaire. After checking of questionnaire by DTOs, the DPSUs submitted questionnaire to PMU. The two project staff entered the data into data entry sheet and completed this task by fourth week of December 2015. The two Regional M&E officers assisted on data cleaning and validation and analysis. M&E Specialist and respective SMS assisted PMU for data analysis, tabulation and report writing.
5 LIMITATION
The survey was intended to determine the immediate and intermediate outputs and results of the project interventions only and sample HHs were selected among the project
6AFSP database 7As sample design has been changed from Simple Random Sampling for administrative purpose, we need to add samples for the design effect, which is generally considered as 2 to 2.5 times. To be at safer side, we multiplied adjusted sample size by 2.5 times.
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beneficiaries list (crop and livestock). So, the estimate may not properly represent for overall impact assessment purpose.
Due to design effect in the selection of sample VDCs in the districts, the estimate may not be representative in some cases. However, correction factors have been applied to minimize such biases.
As the estimates are based on the samples, the estimate gives the representation of population but cannot be extrapolated to larger scale.
Field staff themselves collected the information, so there may be some biases due to their professional favors. However, due attention was given by DTOs in the data collection work whilst collecting the data by field staff. Cross validations was also carried out to check the information in sample basis. Regional Monitoring Officers, PMU, FAO TA central staff also monitored the survey work.
6 FINDINGS
The findings of the Beneficiary Results assessment survey is presented in three main headings Demography, indicators of result framework and other vital immediate output indicators.
6.1 Demography
Out of the total households surveyed, 30% households were headed by Women. Whilst analyzing the ethnicity, Brahmin and Chhetri dominates all other ethnic castes having a share of 68%, followed by Dalit’s 18% share, which is followed by indigenous nationalities with a share of 11% and rest others’ have a 3% share. Please refer to annex-XX for details of ethnic castes.
Table 1 provides details of proportion of Households with children below 2 years and with pregnant and nursing women. The average household size is estimated as 6.59 persons per household. The number of households with children below two year is 348; this implies 32% households do have children below 2 years. Likewise, 408 (37%) households do have pregnant and nursing women in their households.
Figure 1 and 2 presents the proportion of male and female headed households and ethnic composition of the area.
Fig 1: Proportion of Household heads by sex, N-1093
Male
; 764; 70%
Female
; 329; 30%
Male Female
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From ethnicity point of view (figure 2), it reveals that the project has been able to maintain adequate proportion among beneficiaries, as the proportion of dalits' and indigenous nationalities of project beneficiaries (treatment VDCs) is similar to that of overall population of AFSP VDCs.
Figure 2: Proportion of Household by ethnicity, N=1093
Overall AFSP VDCs (9 districts) Sample-Treatment VDCs (9 districts) -
10.0
20.0
30.0
40.0
50.0
60.0
70.0
80.0
67.2
4263
7820
2443
68
8.92
0772
0566
2387
11
21.4
8164
9894
0994
18
0.14
2397
3004
3437
2
02.21
2542
9285
9793
3
Brahmin/Chhetry Ind. Nationalities Dalit Madhesi Other
Comparison of ethnic composition between overall AFSP VDCs population and Sample Treatment VDCs (in %)
The following table gives the proportion of HH with children below two years and pregnant and nursing women:
Table 1: Proportion of Households with children < 2 years and pregnant and nursing women
Description Number Percentage
Households with children below 2 years 348 32 %
Households with pregnant and nursing women 408 37 %
Total HHs (N) 1093
Source: BRA Survey, 2015
6.2 Key indicators of Result Framework
The survey has focused to assess the status of result framework indicators and presented on this chapter. Seed replacement rate, yield of major crops (paddy, maize, wheat and potato), productivity of livestock products (egg, milk production/animal) and proportion of HHs with pregnant and nursing women consuming animal protein and Vegetable and fruits are some of the indicators presented in this chapter.
6.2.1 Yield of major crops at household level
The table 2 presents the average yield of major crops from sample project VDCs (treatment) and control VDCs and whilst comparing the estimated average yield with baseline figures (Table: I in executive summary), we can see that the productivity of all crops has been increased except paddy.
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The main reasons for the reduction in productivity of paddy was because of delayed monsoon causing late transplanting of paddy, less rainfall even in the main monsoon period and early termination of monsoon, all of which severely affected crop performance in the field during the paddy season in the year 2014/15. The national average productivity of paddy was also reduced from 3.36 MT/ha to 3.15 MT/ha. Likewise, the paddy yield in mid-western region was reduced by 13% in comparison to previous year and the average yield was estimated as 2.9 MT/ha far western region by MoAD.
The treatment effect for the crop yield indicators have been calculated using a standard double difference and presented in table: I in the analysis of result framework part.
Table 2: Household level average yield of major cereal crops
Yield (MT/ha)
Crops Control Project VDCs (treatment)
N Mean Std. Dev Number Mean Std. Dev
Main Paddy yield 101 1.6 0.93 583 2.80 1.2Wheat yield 134 1.3 1.19 980 1.61 1.24Winter Maize yield 101 1.8 1.99 899 2.33 2Potato yield 132 4.7 0.23 350 5.6 4.15
Source: BRA survey, 2015
6.2.2 Seed Replacement Rate of major crops
The seed replacement rate of main paddy, wheat, maize and potato is presented in Table-3. The comparison of Seed Replacement Rate8 by improved crop varieties was found higher in case of paddy and wheat whereas it was slightly lower in case of maize and potato compared with the baseline figures. However, the seed replaced by improved seed is higher for all crops in comparison to the baseline SRR figures. Please refer to the table: II in the analysis of result framework part for detail.
Table 3: Household level Seed Replacement Rate of major cereal crops
Output Survey, 2015
Crops Control VDCs Treatment VDCsN Seed Replaced
only (%)N Area
(ha)Seed Replaced from Reliable
source9only (%)
Area covered by improved
varieties (%)Main Paddy 104 7.03 704 162.4 12.99 15.08Wheat 134 5.26 869 238.2 9.80 14.08Summer Maize 114 13.8 843 155.1 12.70 26.30Potato 138 3.86 380 25.3 27.27 51.1
8SRR is understood as the ratio of area of seed replaced by improved seed from reliable source and total cultivated area of particular crop.9 Includes sources such as NRAC stations, seed companies, agro-vets, seed producers groups/cooperatives
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6.2.3 Productivity of Livestock products
The productivity of livestock products (egg, cow milk and buffalo milk) per animal per year is presented in table 4. The productivity of egg production/hen/year, cow milk production liter/cow/year and buffalo milk liter/buffalo/year is found significantly higher in comparison to the baseline figures. Analysis of changes in the level of productivity of livestock products in comparison with baseline has been presented in the table: III, in result framework indicator analysis part.
Table 4: productivity of Livestock product at household level
Output, 2015
Indicator Control TreatmentN Mean SD N Mean SD
Livestock- average production
Eggs(numbers/hen) 75 27 18.6 221 37 34.2Cow Milk (liters /cow, per year) 50 249 203 392 377 247Buffalo milk (liters /buffalo, per year) 30 627 210 315 687 237.4
6.2.4 Nutrition indicators
The following table gives the proportion of households with children below two years and households with pregnant and nursing women.
Table 5: Proportion of Households with children < 2 years and pregnant and nursing women
Description Number Percentage
Households with children below 2 years 348 32Households with Pregnant and Nursing women 408 37Total HHs (N) 1036
The status of consumption of animal protein and vegetable and fruits by pregnant and nursing women is presented in table 6. Whilst calculating the animal protein consumption by PNW, firstly the households with PNW were segregated and out of total food groups mentioned in the questionnaire, consumption of meat or fish or egg or milk or milk products, on the previous day by PNW were accounted. The similar process was adopted for consumption of fruits and vegetables by PNW. The analysis shows that the consumption of animal protein and consumption of vegetables & fruits is higher in comparison to the baseline figures (Table: IV).
Table 6:Pregnant and Lactating women consuming animal protein & vegetables and fruits
Output survey, 2015
Indicator Control TreatmentN Mean N Mean (2)
Pregnant and nursing women
Women Consume animal protein 48 0.62 340 0.83 Women Consume vegetable & fruits 39 0.50 346 0.85
Source: BRA Survey, 2015
Likewise, whilst calculating the minimum dietary diversity among children less than 24 months, the food groups mentioned in the questionnaire were grouped into 7 food groups and the proportion of children consuming 4 or more food groups was estimated. As the exact age of the children was not
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recorded in the output survey, so the values are for all children 0-23 months. Likewise, questions about breastfeeding were not asked, which affects calculation on milk consumption and this was adjusted by assuming 100% of children consumed milk product in the past 24hr, which was the estimate from baseline. Detail of comparison with baseline figures has been presented in Table-IV.
Though the nutrition interventions of project has started recently the increase in consumption of animal protein and vegetables by women is due to the crop and livestock interventions such as village level model farm, homestead nutrition garden and rural poultry program.
Table 6: IYCF practices among children less than 24 months of age
Output survey, 2015
Indicator Control TreatmentN Mean N Mean (2)
Children <24 months10 54 348 Minimum dietary diversity 54 0.50 348 0.82 Minimum meal frequency 54 0.82 348 0.93 Milk or milk product 54 1.00 348 1.00 With 3 IYCF practices (Milk, diversity, frequency) 54 0.58 348 0.81
6.3 Findings on other relevant indicators
6.3.1 Changes due to small irrigation support
ASFP has been supporting farmers to construct/repair micro and small irrigation schemes. The survey report shows that only 59HHs out of 1093 household received support in small irrigation. The major support was extended to repair and maintenance of earlier constructed schemes, which were not fully functional. These small irrigation schemes have increased the no. of crops cultivated at household level from 1.8 crops/year to 2.5 crops/year in the small irrigation supported areas.
Table7: HH responding for receiving Small Irrigation Support
Particular Before AFSP
After AFSP
Total sample size (N)
No. of HH responding for receiving small irrigation support
28 59 1082
average no. of crop planted (no.) 1.8 2.5
6.3.2 Changes in proportion of HH adopting improved crop management practices
The table 8 provides details of adoption of improved crop management technologies and practices (seeds, chemical fertilizer, bio pesticides, irrigation and HHs with Kitchen garden). The comparison
C
10In output survey, these parameters were estimated for children below two years instead of 6-23 months children due to the unavailability of information for 6-23 months children
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with baseline figures shows that farmers are well adopting technologies. However, the HHs using irrigation is slightly reduced; this might be because of some of the irrigation schemes not functioning due to landslide or problem in infrastructure. Further, the findings also show some decline in the use of chemical fertilizers and has increased the use of Improved FYM. This may be due to adoption of learning of FFS or trainings provided by the project.
Table 8: Adoption of improved crop variety, chemical fertilizer, improved FYM
Baseline Output Survey
All VDCs Control VDCs Treatment VDCs% of HH having Irrigation facility 70.4% 42.3% 65.5%Total respondents (N) NA 136 1082
% of HH used improved crop variety NA 32.5% 39.3%Total respondents (N) NA 77 916
% of HH used of chemical fertilizer 32.9% 16.4% 28.6%Total respondents (N) NA 140 1085
% of HH using Bio fertilizer (Improved FYM)
4% 4.4% 15.5%
Total respondents (N) NA 136 1072
% of HH with Kitchen garden 83.6% 91.4% 93.8%Total respondents (N) NA 140 1088
Source: Baseline Survey of AFSP, 2014 and BRA survey, 2015
6.3.3 Production, consumption and sales of vegetables at HH level
The following table gives the details of vegetable production, consumption and sales in the project locations:
Table9: Production, consumption and sale of vegetables
Vegetable Control VDCs Treatment VDCs
N Mean SD N Mean SDProductivity, consumption and sale per Households per year
Production (Quantity: kg/HH/year) 127 176.2 181 1007 272.87 374Consumption (Quantity: kg/HH/year) 127 137.2 122.5 1007 175.95 138Sale (Quantity: kg/HHs/year) 23 215 168.8 262 372.5 534
Source: BRA survey, 2015
Table9 shows that production, consumption and sales of vegetable is considerably higher among treatment VDCs which is logical as farmers with access to VMF and HNG might have encourage to produce and consume vegetables. There is a considerable variation among farmers of both control and treatment VDCs. As only a small proportion of the households among control groups’ sale vegetables, variations could not be generalized.
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Standard deviation seems higher than the mean value in production and sales figure, which indicates that the variation in data is higher, which may be due to big variation in the level of production among the farmers. The average volume of sale per household is considerably higher than the average production in both control and treatment VDCs, this is because only the few portions of farmers (23 out of 127 in control) and (262 out of 1007 in treatment VDCs) sell their vegetables. This implies that even the average volume of sale is higher than the average production; the proportion of farmers' who sell vegetable is very low and should not be generalized.
6.3.4 Proportion of improved and local Livestock breed at HH level (goat, buffalo, cattle & poultry)
The following table 10 gives the status of ownership of livestock assets at household level. Table reveals that there is significant improvement in adoption of improved livestock breeds in AFSP intervention DVCs.Table10 : Status of Livestock (Goat, Buffalo, Cow and Poultry) owned at Household level
Animal Breed Average number of cattle per HHs
Control VDCs Treatment VDCsNo. of HH
responding for having
Average no.
animals/HH
No. of HH responding for having
Average no. of
animals/HH
Goat Improved
3 5 47 7
Local 87 7 848 4Total sample HH* 140 1093
Buffalo Improved
4 2 9 2
Local 41 2 468 1Total sample HH* 140 1093
Cow Improved
3 4 25 3
Local 90 3 802 2Total sample HH* 140 1093
Poultry Improved
9 3 259 6
Local 50 4 552 6Total sample HH* 140 1093* It should be understood that out of total sample HH, the respondents are those who possess mentioned livestock and rest do not possess those mentioned livestock.
Above table 10 shows that there is predominance of local breed of goat, buffalo and cattle whether it is control VDC or treatment VDC. Similarly, the ownership pattern in terms of number of animals per household for all three types of animals both in treatment and control VDCs shows that there is predominance of subsistence production and great scope for breeding improvement which is the main basis of productivity improvement.
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6.3.5 Changes in production and productivity level of milk and eggs
The following table 11 gives the details of production, consumption and sales of cow milk, buffalo milk and egg. Whilst comparing baseline and survey figures, the average cow milk production per household is increased by 144 liter per year whereas buffalo milk is increased by 44 liter per year/HH and that of egg production is increased by 70 number per year per household. Likewise sales is also increased by 15.9 liter/year/HH for cow milk and 22.6 liter per/year/HH for buffalo milk. It should also be noted that the proportion of milk selling household is very low in both control and treatment VDCs. It is worthy noted that the average annual sale of egg per household is higher than average annual egg production, this is because the proportion of farmers selling egg is very low (90 out of 269 farmers) and this should not be generalized.
Table 11: Changes in production, consumption and sale of milk and eggs Indicator Baseline Output, 2015
Base Control Treatment Change
Average Production N Mean (1) SD N Mean SD N Mean (2) SD (2)-(1)Cow Milk (liter per HHs/year) NA 309.5 NA 41 394.1 225 326 453.9 262.5 144.4Buffalo Milk (liter per HHs/year) NA 687 NA 29 598 219.6 296 731.4 232 44.4Egg production (No. Per HHs per year)
NA 46.9 NA 22 62 39.95 269 80 81.7 33.1
Average Consumption
Cow Milk (liter per HHs/year) NA NA NA 41 394.1 225 326 442.8 257.9Buffalo Milk (Kg per HHs/year) NA NA NA 29 463.8 157.9 296 600.1 254.2Egg consumption (No. Per HH per year)
NA NA NA 22 58 38.6 267 62 61.7
SalesMilk cow (liter per Hs/year) NA 312.3 NA 0 0 0 10 362 197 15.9Milk Buffalo (liter per HH/year) NA 382.7 NA 11 366 114.3 84 469.5 163.2 22.6Egg (No. per HH) NA NA 2 45 35.5 92 102 105.6
Source: Baseline Survey of AFSP, 2014 and BRA survey, 2015
6.3.6 HH adopting improved livestock breeds and management practices
The following table gives the proportion of households adopting improved livestock management practices. From table, it can be observed that the proportion of households using hayrack, animals dipping in tank for ecto-parasite control, vaccination and deworming has increased significantly.
The findings seems consistent as adoption of learning from farmers field school in goats, on the spot training on goat management and provision of veterinary drug fund in both goat productivity improvement package and goat livelihood improvement package have encouraged farmers to adopt regular deworming practices.
Table 12: Proportion of household adopting improved livestock management practices
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Indicators Baseline Treatment VDCs
N Percent Total respondents (N)
% of HH adopting improved practices (out of N)
HHs those reported on the
Use of Hayrack or feed trough NA NA 468 46.1%Planting fodder/forage in their land NA NA 1067 68%Purchasing fodder and forage NA 7% 724 5.9%Dipping animals in tank for ecto- parasite control NA 21% 638 42%Vaccination NA 9% 874 68%Deworming NA 13% 874 84%
Source: Baseline Survey of AFSP, 2014 and BRA survey, 2015
6.3.7 Plantation of fodder and forage
The table 13 gives the number of households involved in fodder and forage plantation in their owned land. The Forage plantation with average area coverage of 1.05 ropani (0.052 ha) per year was found in 52 % of sampled households. Likewise 59% households were found to be involved in fodder plantation with an average number plantation of 33 plants/ year. The fodder area was not calculated, as the question was in number of plants and the area of fodder varies from species to species.
Further, looking into the ownership pattern of goats and cattle, the area coverage is not enough to grow quality green forage throughout the year. However, looking into average size of land holding it is sizeable area but in case of hills usually these are un-irrigated and marginal land with poor productivity.
Table 13: Household responding for planting fodder and forage
Description Households planting fodder and forage and area coverage per HHs
Control VDCs Treatment VDCs HH planting HH involving in
plantationArea (ropani/HHs); Fodder (plants/HHs)
HH involving in plantation
Area (ropani/HHs); Fodder (plants/HHs)
Forage (ropani /HH) 30 0.578 560 1.05Fodder (no. of plants/HH)
40 33 644 33
Total sample size 140 1093
(20 ropani of land= 1 ha)
6.3.8 Minimum dietary diversity (MDD) of women
The Women’s Dietary Diversity Score (WDDS) is an indicator used to measures women’s dietary quality over the last 24 hours with recall of food intake the previous day. This module of the questionnaire was asked to the 1036 households that had an adult female household member present to complete the section. Table 14 presents the summary of women’s minimum dietary diversity and dietary diversity of women at lowest, medium and high level.
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Table- 14 Dietary diversity of women
Output survey
Control VDC Project VDC (Treatment)
Description Total respondents (N)
Mean SD Total respondents (N)
Mean SD
Proportion of women consuming food on the previous day of the survey
Lowest Dietary diversity (<=3 food groups)
139 0.26 1036 0.04
Medium Dietary diversity (4 or 5 food groups)
139 0.37 1036 0.36
High dietary diversity (>= 6 food groups) 139 0.37 1036 0.60
Women’s dietary diversity (no. of food groups) 139 4.60 2.22 1036 5.77 1.29
6.3.9 Women involvement on groups
The following figure 3 shows that 93% of HH do have women participating on groups supported by AFSP and 8% of women were holding key positions on the groups. By key position, it should be understood as 3 positions (Chair, Secretary and Treasurer).
Figure 3: HHs with women participating on groups
Yes; 1018; 93.14%
No; 75; 6.86%
Hoseholds with women partcipating on groups (N=1018)
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Figure 4: HHs with women holding various positions on groups
4.13% 3.54%5.30%
86.35%
0.69%
Households with women holding various positions (N=1018)
Chairperson Secretary Treasure Member Other*
Households having knowledge about the project’s grievances redress mechanism
Table 15 gives the proportion of households having knowledge about the project’s grievances redress mechanism and the offices that they have contacted for addressing their grievances respectively. Out of 1090 respondent households 84 % responded for having knowledge about the project’s grievances redress mechanism
Table: 15 Knowledge on grievances redressal mechanism
Description Responses
No. of HHs that knew about the project’s grievances redress mechanism
Yes No Grand Total
Grand Total 914 (84%) 176 (16%) 1090
6.3.10 Proportion of HHs using women drudgery reduction technologies
Table 16 and 17 gives the idea about the proportion of households that have knowledge on women drudgery reduction technologies and various types of tools and technologies that they have been applying for reducing the women drudgery. Eighty three percent of the respondent households
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responded for having knowledge on women drudgery reduction technologies; of which 78% have applied such techniques. The techniques and tools that the respondents using were Improved Cooking Stove (51% HHs), grinding machine (40% HH), Rice huller (35% HH), Improved water mill (25% HH), Corn Sheller and Bio gas by 1% HHs each.
Table: 16Knowledge on women drudgery reduction technologies
HH responses for having knowledge on women drudgery reduction technologies
No .of HHs respondingDescription Yes No Total Responding
HH NHH responding for having Knowledge on women drudgery reduction tools (1)
902 188 1090
Percentage of (1) 83 172. HH applying women drudgery reduction tools and technologies 702 200 902Percentage of (2) 78 22
Table: 17Various means applied for reduction of women drudgery
Description No. of responses for using Various tools and techniques
Corn Sheller
Rice huller
GM IWM Bio gas
ICS Others* N
HHs using various women drudgery reduction tools and technologies
13 316 359 226 13 461 11 702
Percentage (%) 2 45 51 32 2 66 2Note: IWM= Improved water mill, ICS=improved cooking Stove, GM=grinding machine* includes fruit harvesting machine, chaf cutter
6.3.11 Project contribution in enhancing livelihoods, increasing supply of meat products and enhancing nutritional status
Perception on enhancements of the livelihoods of the people
Table 18 gives the perception of households on the project’s contribution helped in enhancing the livelihoods of local people. The question was asked to provide their perception on four options-No (1) to a lot (4). Most of respondents (64%) provided opinion that the project is contributing to enhance livelihoods to some extent, 22 % responded as contributing a lot whereas few very 2.3% responded as the project is not contributing to enhance the livelihoods. Whilst calculating the average score, it comes around 3.06 score which above median score value (2.5) so that it is on positive direction and falls under high category.
Table 18: Perception on whether project helped in enhancing livelihoods of people
Description No. of responses
No (1) Little bit Some A lot Grand
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(2) extent (3) (4) TotalHHs providing option whether the project helped in enhancing livelihoods of people
24 123 698 241 1086
Percentage 2.3 11 64 22
Average score 3.06
Median Score=2.5 (1-1.75=Very Low, 1.75-2.5=Low, 2.5-3.25=High, 3.25-4=Very High)
Perception on the increase availability of the meat and egg
Likewise table 19 gives perception of respondent households on the project’s contribution helped for increasing availability of egg and meat in the local area. 70 % of the respondents provided their perception in positive direction whereas 18% respondents provided opinion as little bit and 12% respondents provided opinion as no. The estimated average score for this parameter is 2.68, which is just greater than median values and still falls in high category. It reveals that some measures should be taken in the area from which most have reported for No (1).
Table19: Perception on project contribution to increase the availability of meat and egg products in the locality
Description No. of responses
No (1)
Little bit (2)
Some extent (3)
A lot (4)
Grand Total (N)
HHs providing opinion whether the project helped in increasing meat products in village
125 199 617 145 1086
Percentage 12 18 57 13 100Estimated average Score 2.68
Median Score=2.5 (1-1.75=V Low, 1.75-2.5=Low, 2.5-3.25=High, 3.25-4=Very High)
Perception on the enhancement of nutritional status
Table 20 gives the perception of respondent households on the project’s contribution helped for enhancing the nutritional status of the people. 79% of the respondent HHs provided opinion that the project has contributed in increasing nutritional status of local people whereas 18% provided opinion that the project has contributed a little bit for the same whilst 3% provided opinion as no. The average score is estimated at 3.02, which is greater than median score value 2.5 and will fall in high (positive) category.
Table 20: Perception whether the project helped to enhance nutritional status of people
Description No. of responses
No (1)
Little bit (2)
To some extent (3)
A lot (4)
Grand Total
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HHs providing opinion whetherproject helped to enhance nutritional status
34 194 551 310 1089
Percentage 3 18 51 28
Estimated average score 3.02
Median Score=2.5 (1-1.75=V Low, 1.75-2.5=Low, 2.5-3.25=High, 3.25-4=Very High)
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7 LESSONS LEARNT
The analysis reveals that the project has been able to maintain the adequate proportion in the ethnic composition of beneficiary in comparison to that of overall population of project districts; though indicator was not set for ethnicity. However, it would be better to sensitize field staff on this regard during field staff training.
Though there is increase in the yield of potato due to treatment effect, the yield of potato is still very low in comparison to national average yield (13.70 t/ha11) of 2014 and that of Far western region was (13.65 mt/ha)12. Thus, focus needs to be given to increase yield of potato either through the promotion of improved varieties and improved seed or through improved management practices, or by both.
Regarding Seed Replacement Rate (SRR), as agreed during MTR mission, DIME should incorporate the revised baseline figures13in the baseline report and circulated to concern stakeholders.
The ownership pattern of animals (high number of local breed) per household for all three types of animals (goat, cow and buffalo) both in treatment and control VDCs show that there is predominance of subsistence production. Given the big gap in productivity of local and cross breed animals (Ag. Statistics, MOAD- 2014), there exists a great scope for breeding improvement which is the main basis of productivity improvement.
BCC nutrition activities have recently initiated in the project VDCs. The increase in intake of vegetable & animal protein by Pregnant and Nursing Women reveals that crop and livestock activities such as Village model farm, Homestead nutrition garden and rural poultry production package have helped a lot for increasing such food intake. Thus, additional focus should be given to such activities, which helps people to get access to nutritious foods directly.
The use of improved crop varieties is around 39% in treatment VDCs, which reveals that efforts need to be focused on increasing adoption of improved crop varieties at farmers' level.
The annual production of vegetable is estimated as 272 kg/ household, which reveals that it is below the standard requirements, which comes around 533kg/household/year14. Therefore, should provide additional focus on vegetable production program.
11 Statistical Pocket Book of Nepal-2014, Central Bureau of Statistics, Kathmandu Nepal, 12 Statistical year book of Nepal-2013, CBS, Kathmandu, Nepal13 Using the adjusted definition of SRR calculations i.e, including the seeds received only from reliable sources; NARC, DOA farms, agro-vets, seed companies, seed producer's group/ co-operatives or seed from NGO/INGO) as mentioned in early chapter14Calculation based on FAO set requirements: 100gm leafy vegetable/day/person + 125 gm root crop/day/person*6.5persons/hh*365days
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Annex-1: Details of sample districts, VDCs and sample size
District Sample VDCs (treatment) Sample Control VDCs Total sample size in district
Name of VDCs Sample size Name of VDC Sample size
Achham Siddheswor 73 Balata 10 146Basti 53 Ridikot 10
Bajura Kolti 55 Bandhu 10 116Kailashmandu 42 Budhiganga 10
Dadeldhura Dewaldibyapur 43 - 172Gangkhet 105 -
Dailekh Bansi 84 Bhawani 10 176Gamaudi 69 Rahutkot 10
Darchula Dattu 62 Huti 10 134Sunsera 62 Uku 10
Jajarkot Punma 93 - 190Sima 71 -
Jumla Dillichour 51 Patmara 10 96Malikathanta 35 Ghodemahadev 10
Mugu Seri 28 Karkiwada 10 96Shreenagar 43 Shrikot 10
Rolpa Gairigaun 68 Bhawang 10 146Jaimakasala 56 Mighing 10
Total sample size
1093 140 1233
-
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Annex-2 Survey Questionnaire
DRAFT
Agriculture and Food Security Project
Beneficiary Results Assessment Survey Questionnaire, 2015
A, General Information
Questionnaire no: Date of interview (dd/mm/yy):
Name of the beneficiary: Contact number:
Sex of beneficiary: Male ( ) Female ( ) Age: …….. year
Ethnicity: Dalit ( )Ind. Nationalities ( ) Brahmin/chhetry ( ) Madhesi ( ) Others ( )
District: VDC: Ward No.:
Name of Household head (if different from beneficiary):
Sex of HH head Put tick mark for the appropriate: Male ( ) Female ( )
Household membership (number):
Total members Male Female
Number of children below 2 years: …………..
Name of respondent (if respondent is different from beneficiary):
A. Were you or member of your HH a participant/beneficiary of AFSP interventions (activities)? Put tick mark for the appropriate oneYes ( ) No ( ) if no, go to another householdIf yes, in which program were you involved in? Crop ( ) Livestock ( ) Nutrition ( ) (multiple choice question)
B. If you or any member of HH were involved in AFSP activities, please tell, on which particular activities, that you were involved in? multiple choice question-put tick mark where appropriate
a.Crop Farmer Field School FFS ( )
b. Demonstration activities ( )
c. Livestock FFS ( ) d. Goat programme ( )
e. Poultry program ( ) f. Dairy production ( ) g. mother group ( ) h. Village model Farm/Homestead Nutrition Garden ( )
i. Seed Production j. Small irrigation ( ) k. Small Grant ( ) l. others ( )
27
program ( ) specify…………
B. Crop1. Did you or any member have participated on Farmer Field School (crop) program conducted
by AFSP? Put tick mark for the appropriate oneYes ( ) No ( ) Do not know ( )
a. If yes, have you applied the technology that learnt on your own farm? Put tick mark for the appropriate oneYes ( ) No ( ) Do not know ( )
b. If you have applied learnt technologies, please mention what were those (main two)?a. ……………………………… b. ……………………………………….
2. Have you or any of your family member involved in any crop related activities conducted by project? Yes ( ) No ( ) Do not know ( )
a. If you were involved, have you used at least one of the improved (high yielding) variety of cereal seed out of those you grow in last year? Put tick mark for the appropriate oneYes ( ) No ( ) Do not know ( )
3. Total area of land cultivated last year15 (own plus rented): ....... ropani or ……………… Total irrigated land: ………..ropani or ……….. (if other than ropani specify unit as well)
4. Would you please provide information on improved and local variety that you have grown last year along with their production as given in following questions:
a. Area of cultivated land covered by improved variety and farmers’ own variety along with their production in the last year
.Description Unit
1
6
Rice Maize Wheat Potato If answer is in local unit, conversion factor to ropani or to Kg
Area of land covered byimproved variety
Name of improved variety used
Total production from improved variety
Area covered by local/farmers’ variety
15 Last year period should be basically understood as Srawan 16 July to Ashad 15 July 16If the answer is on ropani, mention the magnitude in number and if the answer is on local unit then write the unit on which answer comes for area or production and also mention its conversion factor from local unit to ropani in case of area and conversion factor local unit to Kg in case of production, at the last column
28
Total production of local/farmers’ variety
29
b. If you have used certified seeds, please tell us area covered by certified/improved seed brought from reliable sources and area covered by farmers’ own seed on four major crops
.Description Unit
1
7
Rice Maize Wheat Potato If answer is in local unit, conversion factor to ropani or to Kg
Area covered by certified/ improved seed brought from reliable sources (A)Area covered by farmer’s own seed(B)
Note: reliable sources could be NARC/ GoN farms, agrovets/seed cooperatives/ seed producers groups
5. Did you use Chemical fertilizers, last year? Put tick mark for the appropriate oneYes ( ) No ( )
a. If yes, How much chemical fertilizer did you buy in the past twelve months?Quantity: …………………….Kg Value of chemical fertilizer: ……….NRs
6. Did you use bio-pesticides for crop cultivation in last year? Put tick mark for the appropriate oneYes ( ) No ( )If yes, how much bio-pesticides did you buy in the past twelve months?Quantity: …………………….Kg Price (Value): ……………………………..NRs
7. Do you (have) irrigation facility in your land? Put tick mark for the appropriate oneyes ( ) No ( )
a. If yes, from when the irrigation facility was available?Put tick mark for the appropriate oneBefore AFSP ( ) after the start of AFSP program ( )
b. Have your group received support of AFSP project for irrigation from District Agriculture Development Office? Put tick mark for the appropriate oneYes ( ) No ( ) Do not Know ( )
7.3 If you received support, please provide following information
Descriptions Unit Before irrigation facility After irrigation facilityNo. of crops cultivated in the same irrigated plot:
Number
Name of crops cultivated in the same irrigated plot:1. Name of crop:Total cultivated area18:Total Production 19:2. Name of crop:
17 If the answer is on ropani, mention the magnitude in number and if the answer is on local unit then write the unit on which answer comes for area or production and also mention its conversion factor from local unit to ropani in case of area and conversion factor local unit to Kg in case of production, at the last column18 Please write the unit on which answer comes for area at the unit column and if the answer comes in local unit other than ropani or Katha, mention its conversion factor to ropani at the remarks column
30
Total cultivated area:Total Production:
8. Have you planted vegetables in your land in last one year period? Put tick mark for the appropriate oneYes ( ) No ( ) If no go to question 12
9. If yes, please tell how many types of vegetables that you cultivated? ………. typesPlease tell the name of vegetables that you cultivated last year? Put tick mark where appropriate-multiple choice question
Cauliflower ( ) Cabbage ( ) Okra ( ) Radish ( )
Onion ( ) Tomato ( ) Bottle Gourd ( ) Sponge gourd ( )
Green vegetables ( ) Garlic ( ) Beans ( ) Chickpea ( )
Brinjal ( ) Carrot ( ) Pumpkin ( ) Others specify ……………
9.1 What was the tentative total production of vegetable last year? …………………… kg
10. How did you utilize those produced vegetable? Put tick mark for the appropriate oneConsumed at home ( ) Consumed and also sold ( ) others ( ) specify…….
11. From your own production, please tell tentative quantity of vegetables that you consumed at home and sold last year?
Tentative quantity of consumption/day:……… kg
No. of days that you consumed vegetables in a months…………………days/month
Number of months that you consumed vegetable from your production………. Months/year
Tentative quantity of vegetable that you sold at time: ……… kg
No. of times that you sell vegetable in a month:………. Times/month
Number of months that you sell vegetable in a year………… months/year
19 Please write the unit on which answer comes for production at the unit column and If the answer in local unit mention its conversion factor to kg at the remarks column
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C. Livestock12. Do you have livestock at home?? Put tick mark for the appropriate one
Yes ( ) No ( )12.1 if yes, please give following information
Name Goat Buffalo Cattle Poultry
Improved Local Improved Local Improved Local Improved Local
Name of breed
Number
Note: the number should include all adult/calves/chicks
13. Did you or any member have participated on Farmer Field School (crop) program conducted by AFSP? Put tick mark for the appropriate one: Yes ( ) No ( ) Do not know ( )
a. If yes, have you applied the technology that learnt on your own farm? Put tick mark for the appropriate oneYes ( ) No ( ) Do not know ( )
b. If you have applied learnt technologies, please mention what were those (main two)?a. ……………………………………. b. ……………………………………………….
14. Would you tell whether you have constructed improved shed/pen for above mentioned livestock in last one year period? Put tick mark for the appropriate oneYes ( ) No ( )
15. Would you please give me the information on milk production, household consumption and sales in the past one year’s period:
Description Cow Buffalo Goat
No. of milking animal (no.)
Quantity of Milk produced/day (lit)
No. of months milk production (No.)
Quantity of Milk consumed/day (lit)
Quantity of Milk sold/day (lit)
No. of months on which sold milk
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Description Cow Buffalo Goat
No. of milking animal (no.)
Average price of Milk (Rs/ litre)
33
16. Would you please provide the information about production, consumption and sell of livestock product of last one year’s period?
Livestock Production Consumed at HH Sold
Number Tentative Live weight/animal (kg)
Quantity (number)
Quantity (number)
Approx. Value (Rs.)
Buck
Castrated goat
Goat/doe
Hen
Eggs
Cock
Note: only the mature animal/bird should be considered
17. Did you follow stall feeding practices for goat using hayrack? Put tick mark for the appropriate oneYes ( ) No ( ) if yes, 17.1 if yes, from when? From last …….. year
18. Did you plant fodder or forage in your own land in two years’ period? Put tick mark for the appropriate one: Yes ( ) No ( ) 18.1 if yes, please tell the following description Forage: ……… kg and fodder: ………….. number
19. Did you also purchase fodder/straw for any one of your livestock last year? 19.1 Yes ( ) No ( ) 19.2 If yes, Quantity of purchase of fodder/straw:……………. kg and Value: ………… rupees
20. Did you vaccinated your livestock in last one years’ period? Put tick mark for the appropriate one Yes ( ) No ( )
21. Did you deworm your animal against internal parasites, last year? Put tick mark for the appropriate oneYes ( ) No ( ) if yes number of times : ……………
22. Have you done dipping to your goats last year, to save from external parasites? Put tick mark for the appropriate oneYes ( ) No ( )
34
D. Nutrition23. Is there any pregnant women or nursing mothers in your household? Yes ( ) No ( )
24. Has any woman in your HH received trainings on food preparation, processing and preservation supported by AFSP? Put tick mark for the appropriate oneYes ( ) No ( ) Do not know ( )
25. Have you or any member of your HHreceived any nutrition messages (especially on dietary diversity or Maternal, Infant and Young Child Nutrition (MIYCN) in the last 6 months? Put tick mark for the appropriate one Yes ( ) No ( ) Do not know ( ) if no then go to question 25
a. If yes, from whom did you receive those nutrition messages? Multiple choice question
a. Doctor ( ) b. Nurse/Midwife/ANM ( ) c. Health assistant/AHW ( )
d. Female Health Child Volunteer( )
e. Project facilitators ( )
f. mother’s group member ( ) g. Traditional healer ( )
h. others specify……….
25.2 From which source did you receive the nutrition messages/counseling? Multiple choice question-put tick mark where appropriate
Farmer Field School (Crop) ( ) Farmer Field School (Livestock) ( ) Village Model Farm ( )Home Nutrition Garden ( ) During health mother’s group meeting
( )Household visit by AFSP Staff( )
Radio/local FM Station ( )
TV ( ) Other (Specify)………………………
25.3 Can you tell me what were the nutrition education/counseled on? Multiple choice question-put tick mark where appropriate
Breastfeeding ( ) Dietary diversity of pregnant and lactating woman ( )
Dietary diversity for infant and children under 2 years of age ( )
Preparation of nutritious recipe( )
Food hygiene ( ) Safe drinking water and hand washing ( )
Reducing pregnant women workload ( )
Other (Specify) ………..
25.4 Did you find those messages were useful? Put tick mark for the one that is appropriate
Very useful ( ) Useful ( ) little useful ( ) Not useful ( )
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25.5 If you found useful have you applied those messages in your practical life?Put tick mark for the one that is appropriate
Yes ( ) To some extent ( ) little bit ( ) Not used ( )
26. Mothers’ Dietary Diversity Score (Question to mothers)
Instruction: Ask the 24 hr diet recall for yesterday, if it was a typical day. If not, ask for the day before. If both were atypical days, proceed to ask about the diet from yesterday. For whichever 24 hr period is recalled, probe the respondent to include all food (meals and snacks) consumed during the morning, day, and night, whether at home or outside the home. Start with the first food eaten after waking up and ask about each time of day probing until there is no further food recalled.
Read aloud: I would like to now ask you about what you ate and drank yesterday (or the day before if yesterday was unusual) and Please put tick mark on appropriate options
S.N. Question ResponseFood item Yes No
1 CEREALS(e.g. Rice, roti, bread, puffed rice, pressed rice, noodles, or any other foods rice, wheat, maize/corn, or other locally available grains)
2 VITAMIN A RICH VEGETABLES AND TUBERS(e.g. Pumpkin, carrots, sweet potatoes that are orange and yellow inside)
3 WHITE TUBERS AND ROOTS OR OTHER STARCHY FOODS(e.g. Potatoes, white yams, white sweet potato (not orange inside) or other foods made from roots)
4 DARK GREEN LEAFY VEGETABLES(e.g. Spinach, amaranth leaves, mustard leaves, pumpkin leaves, yam leaves, etc.)
5 OTHER VEGETABLES(e.g. Cauliflower, cabbage, eggplant, green papaya, radish, onion, etc.)
6 VITAMIN A RICH FRUITS(e.g. Ripe mangoes, ripe papaya/pawpaw, jack fruit)
7 OTHER FRUITS(e.g. Tomatoes, Bananas, apples, guavas, oranges, other citrus fruits, pineapple, watermelon, grapes, strawberries, plum, etc.)
8 MEAT(e.g. Goat, lamb, chicken, duck, or other birds, liver, kidney, heart, or other organ meats)
9 EGGS(e.g. Eggs of different birds – chicken, duck, etc.)
10 FISH(e.g. Big/small fresh or dried fish or shellfish such as prawn, crab etc.)
11 BEANS, PEAS, OR LENTILS(e.g. Soybeans, beans, peas, lentils, other pulses, peas)
12 MILK AND MILK PRODUCTS(e.g. Milk, cheese, yogurt, or other milk products)
13 NUTS AND SEEDS14 OILS AND FATS
(e.g. Oil, fats, or butter added to food or used for cooking including ghee)15 SWEETS
(e.g. Sugar, honey, rock candy, chocolates, biscuits, cold drinks)16 TEA/COFFEE17 Other (Specify) _________________________
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27. CHILD DIETARY DIVERSITY (same as in mothers’ food dietary diversity) put tick mark for the one that is appropriate
Now I would like to ask you about liquids or foods that the child had yesterday during the day or at night. I am interested in whether your child had the item I mention even if it was combined with other foods.Did child (drink/eat):
Yes No DKPlain water?Juice or juice drinks?Soup?Milk such as tinned, powdered, or fresh animal milk?IF YES: How many times did (NAME) drink milk? # timesIF 7 OR MORE TIMES, RECORD '7'.Infant formula like Lactogen?IF YES: How many times did (NAME) drink infant formula? # timesIF 7 OR MORE TIMES, RECORD '7'.Any other liquids?Yogurt?IF YES: How many times did (NAME) eat yogurt? # timesIF 7 OR MORE TIMES, RECORD '7'.Any fortified baby food like Cerelac, Nestum, Championetc?Roti, rice, maize, millet, noodles, porridge, or other foods made from grains?Pumpkin, carrots, squash or sweet potatoes that are yellow or orange inside?White potatoes, white yams, colocasia, or any other foods made from roots?Any dark green, leafy vegetables like spinach, amaranth leaves, mustard leaves?Ripe mangoes, papayas or apricot?Any other fruits or vegetables?Liver, kidney, heart or other organ meats?Any meat, such as pork, buff, lamb, goat, chicken, or duck?Eggs?Fresh or dried fish or shellfish?Any foods made from beans, peas, lentils, or nuts?Cheese or other food made from milk?Any other solid, semi-solid, or soft food (jaulo, lito, sarbottampitho etc.)?
How many times did the child eat solid, semisolid, or soft foods yesterday during the day or at night?
# times
28. Did you find the nutrition messages that the received were new to you? Yes ( ) No ( ) If the messages were not new, when did you knew? …….. years ago
E. Environmental and Social Safeguards
29. Do you know about the practices that will make agriculture and livestock related activities environment friendly20? Yes ( ) No ( ) If yes, from how long? …….. yearsIf you know, have you applied those in practices? Yes ( ) No ( )
20 Environment friendly activities should be understood as those agricultural and livestock activities of project, which will not make negative effect on precipitation (water pollution), climate, forest, bio diversity, soil erosion, landslide etc. .
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30. Would you tell us what were those environment friendly practices/activities that you have applied? Put tick mark where appropriate-multiple choice question
a. Forage\fodder plantation ( ) b. Improved farm yard manure preparation ( )
c. Improved cow\goat shed construction ( )
d. Improved Poultry pen ( ) e Bio –pesticide use ( ) f. others specify ……….
31. Is any of womenmember of your HH are AFSP related groups (crop, livestock, mother group) or co-operatives? Yes ( ) No ( ) If yes, please tell her position in AFSP groups or co-operatives? Put tick mark for appropriate option
a. Chairperson ( ) b. Secretary ( ) c. Treasurer ( )d. Member ( ) e. others specify
………………………….f. Do not know ( )
32. Have the AFSP staff have informed you about the grievance redress mechanism of project?
Yes ( ) No ( )
If yes, which office did you contact for informing the grievances? (multiple choice question, put tick mark where appropriate)
a. District Agriculture Development Office ( ) b. District Livestock Development Office ( )c. District health Office ( ) d. Project Management Unit of AFSP ( )e. others ( ) Specify ….. f. Not needed ( )
33. In your opinion, whether all interested people in your village are able to get involved in farmer group? Yes ( ) No ( )
If not then what were the reasons
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34. Did you know about technologies that reduces women drudgery? Yes ( ) No ( )
If yes, you have applied those technologies on practice? Yes ( ) No ( )
If you applied those technologies, then tell us what were those? (Multiple choice question put tick mark where appropriate)
a. Corn Sheller ( ) b. Hulling mill ( ) c. Grinding mill ( ) d. Improved water mill ( )
e. Bio gas ( ) f. Improved cooking stove ( )
g. Winding machine for paddy ( )
h. Fruit harvesting machine ( )
i. chef-cutter ( ) j. Others ( ) specify…….
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35. In your opinion, whether AFSP has helped to enhance the livelihoods of local farmers?
Very much ( ) to some extent ( ) little bit ( ) No ( )
36. In your opinion, whether AFSP has helped to increase supply of cereal, vegetables, milk, meat, egg to household level or local market?
Very much ( ) to some extent ( ) little bit ( ) No ( )
37. In your opinion, whether AFSP has helped to improve nutritional status of pregnant and lactating mothers, women and children?
Very much ( ) to some extent ( ) little bit ( ) No ( )
38. At last, do you have any suggestions to make AFSP interventions more effective?
i. ------------------------------------------------------------------------------------------------------------
ii. ------------------------------------------------------------------------------------------------------------
iii. -------------------------------------------------------------------------------------------------------------
Thank you so much for your valuable information and time
Name of enumerator (field staff):
Designation: Working VDC:
Signature: Contact number:
Date:
Name of supervisor (DTO):
Signature:
Date:
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