DDI-TZA-NBS-AGRSCS-2007/2008v01. National Bureau of Statistics Accelerated Data Program 2012-12-06 NADA Version 1.0 (Dec 2012) Agriculture Sample Census Survey 2007/08 ASCC 2007 TZA-NBS-AGSS-2007-v01. National Bureau of Statistics Office of Chief Government Statistician-Zanzibar Ministry of Agriculture, Food Security and Cooperatives Ministry of Livestock Development and Fisheries Ministry of Water and Irrigation Ministry of Agriculture, Livestock and Environment, Zanzibar The Prime Minister's Office, Regional Administration and Local Government Ministry of Industries, Trade and Marketing The Food and Agriculture Organization of the United Nations The Censuses and Surveys Technical Working Group (c) 2007, National Bureau of Statistics NADA The Government of Tanzania The Department for International Development The Japanese Government through the Japan International Cooperation Agency Director General Agricultural Census [ag/census] This is the fourth Agricultural Census to be carried out in Tanzania, the first one was conducted in 1971/72, the second in 1993/94 and 1994/95 (during 1993/94 data on household characteristics and livestock count were collected and data on crop area and production in 1994/95), and the third was conducted in 2002/03 It is considered that this census is one of the largest to be carried out in Africa and indeed in many other countries of the world. The census collected detailed data on crop production, crop marketing, crop storage, livestock production, fish farming, and poverty indicators. In addition to this, the census was large in its scope and coverage as it provides data that can be disaggregated at district level and thus allow comparisons with the 2002/03 National Sample Census of Agriculture. The census covered smallholders in rural areas only and all the large scale farms. Version 01 (Public use file for web dissemination) TRADE, INDUSTRY AND MARKETS [2] The 2007/08 Agricultural Sample Census was designed to meet the data needs of a wide range of users down to district level including policy makers at local, regional and national levels, rural development agencies, funding institutions, researchers, NGOs, farmers' organizations, and others. The dataset is both more numerous in its sample and detailed in its scope and coverage so as to meet the user demand. The census was carried out in order to: - Identify any structural changes,in the size of farm household holdings, crop and livestock production, farm input and implement use. It also seeks to determine if there are any improvements in the rural infrastructure and the level of agricultural households living conditions; -Provide benchmark data on productivity, production and agricultural practices in relation to policies and interventions promoted by the Ministry of Agriculture and Food Security and other stakeholders; and - Obtain data that will be used to address specific issues such as: food security, rural poverty, gender, agro-processing, marketing and service delivery. Tanzania Tanzania Mainland and Zanzibar Clusters Community, Household, Individual Small scale farmers, Large Scale Farmers, Community Sample survey data [ssd] The census used three different questionnaires: SMALL SCALE FARM questionnaire was the main census instrument and it included questions related to crop and livestock production and practices; population demographics; access to services, community resources and infrastructure; issues on poverty and gender . The main topics covered were: - Household demographics and activities of the household members - Land access, ownership, tenure and use - Crop and livestock production and productivity - Access to inputs and farming implements - Access and use of credit - Access to infrastructure (roads, district and regional headquarters, markets, advisory services, schools, hospitals). - Crop marketing, storage and agro processing - Tree farming, agro-forestry, and fish farming - Access and use of communal resources (grazing land, communal forests, water for humans and livestock, beekeeping) - Investment activities ( irrigation structures, water harvesting, erosion control, fencing) - Off farm income and non agricultural related activities - Households living conditions (housing, sanitary facilities ) - Livelihood constraints - Poverty Indicators COMMUNITY LEVEL questionnaire was designed to collect village level data such as access and use of common resources, community tree plantation and seasonal farm gate prices. LARGE SCALE FARM questionnaire was administered to large farms either privately or corporately managed National Bureau of Statistics The Mainland sample consisted of 3,192 villages. The total Mainland sample was 47,880 agricultural households while in Zanzibar, a total of 317 EAs were selected and 4,755 agricultural households were covered. The villages were drawn from the National Master Sample (NMS) developed by the National Bureau of Statistics (NBS) to serve as a national framework for the conduct of household based surveys in the country. The National Master Sample was developed from the previous 2002 Population and Housing Census. The numbers of villages/Enumeration Areas (EAs) were selected for the first stage with a probability proportional to the number of villages/EAs in each district. In the second stage, 15 households were selected from a list of agricultural households in each village/EA using systematic random sampling. Face-to-face [f2f] The census used three different questionnaires: - Small scale farm questionnaire - Community level questionnaire - Large scale farm questionnaire The small scale farm questionnaire was the main census instrument and it included questions related to crop and livestock production and practices; population demographics; access to services, community resources and infrastructure; issues on poverty and gender. The main topics covered were: - Household demographics and activities of the household members - Land access, ownership, tenure and use - Crop and livestock production and productivity - Access to inputs and farming implements - Access and use of credit - Access to infrastructure (roads, district and regional headquarters, markets, advisory services, schools, hospitals). - Crop marketing, storage and agro processing - Tree farming, agro-forestry, and fish farming - Access and use of communal resources (grazing land, communal forests, water for humans and livestock, beekeeping) - Investment activities ( irrigation structures, water harvesting, erosion control, fencing) - Off farm income and non agricultural related activities - Households living conditions (housing, sanitary facilities ) - Livelihood constraints - Poverty Indicators The community level questionnaire was designed to collect village level data such as access and use of common resources, community tree plantation and seasonal farm gate prices. The Large Scale Farm questionnaire was administered to large farms either privately or corporately managed. Data collection was monitored by a hierarchical system of supervisors which included the Mobile Response Team, Regional and District Supervisors. The Mobile Response Team, which was headed by the Manager of Agriculture Statistics Department, provided an overall direction to the field operations and responded to queries arising outside the scope of the training exercise. Decisions made on the definitions and procedures were then communicated back to the enumerators via the Regional and District Supervisors. On the Mainland, each region had two Regional Supervisors (total 42) and two district supervisors per district (total 266). During the household listing exercise, 3,192 extension staff participated on the Mainland and a total of 177 enumerators participated during the listing exercise and the enumeration of small scale farms in Zanzibar. A total of 1,596 enumerators were involved in data collection of small scale farms on the Mainland. Additional five percent of the enumerators were kept as reserves in case of drop outs during the enumeration exercise. Data collection was monitored by a hierarchical system of supervisors which included the Mobile Response Team, Regional and District Supervisors. The Mobile Response Team, which was headed by the Manager of Agriculture Statistics Department, provided an overall direction to the field operations and responded to queries arising outside the scope of the training exercise. Decisions made on the definitions and procedures were then communicated back to the enumerators via the Regional and District Supervisors. On the Mainland, each region had two Regional Supervisors (total 42) and two district supervisors per district (total 266). The first checks on the questionnaires were carried out by enumerators in the field during enumeration, followed by district, regional and national supervisors. Supervisory visits at all levels of supervision focused on the completeness of the questionnaires and data consistency. Any inconsistencies encountered were corrected, and where necessary, call backs to the respective respondents were made by the enumerators to obtain the correct information. Furthermore, quality control checks were made by the supervisors in each district. District supervision were performed by staff from the Prime Minister's Office, Regional Administration and Local Government (PMO-RALG). Regional and national supervision was provided by senior staff from the National Bureau of Statistics and the sector Ministries of Agriculture. In Zanzibar, the enumeration was conducted by staff from the Ministry of Agriculture and Natural Resources and Ministry of Livestock and Fisheries. Supervision was provided by senior officers of the same Ministries and the Office of the Chief Government Statistician. The sample design was a stratified two-stage sample, where the rural part of Tanzania was stratified into districts. The first stage (Primary Stage) units were villages in the case of Tanzania Mainland and rural enumeration areas in the case of Tanzania Zanzibar. In the first stage, villages/EAs were selected in each rural part of the district. About 27 villages/rural EAs per district were selected. The sample was expected to give estimates of different parameters with error margin of 5 percent at 95 confidence level. The selection of villages/rural EAs was as follows: - All villages/rural EAs were selected if the number of villages/rural EAs in the district was less than or equal to 27; - 27 villages/rural EAs were selected if the number of villages/rural EAs in the district was greater than 27; and - All villages covered during the 2002/03 census were considered. Additional villages were sampled in the new districts to reach the required number of 27 sampled villages. In the second stage, farming households were selected in each of the selected villages/EAs. A sample of 15 farming households was selected per selected village/rural EA..The villages/EAs in the first stage were selected with probability proportional to the number of households in the village (PPS). The cumulative total method was used to achieve the PPS selection of villages/EAs. In the second stage (Secondary Stage), farming households were selected using a systematic random sampling procedure whereby a list of farming households was compiled from each selected village/EA and a systematic random sample was then drawn. Basic Formulae for Estimation In the sample, the primary stage unit was the village/rural EA. The estimates obtained were for the village/rural EA, rural part of the District, rural part of the Region and rural part of the Nation. The selection of the villages/rural EAs was with probability proportional to the number of households in the village/rural EA and systematic random selection procedure was used to select households. Data editing took place at a number of stages throughout the processing, including: - Manual cleaning exercisePrior to scanning. (Questionnaires found dirty or damaged and generally unsuitable for scanning were put aside for manual data entry ) - CSPro was used for data entry of all Large Scale Farms and Community based questionnaires - Scanning and ICR data capture technology for the smallholder questionnaire - There was an Interactive validation during the ICR extraction process. - The use of a batch validation program developed in CSPro. This was used in order to identify inconsistencies within a questionnaire. - Statistical Package for Social Sciences (SPSS) was used to produce the Census tabulations - Microsoft Excel was used to organize the tables, charts and compute additional indicators -Arc GIS (Geographical Information System) was used in producing the maps. - Microsoft Word was used in compiling and writing up the reports Confidentiality of respodents is guaranteed by section 20 of Tanzania Statistics act number 1 of 2002 Before being granted access to the dataset, all users have formally agree: 1.all identifying information such as the name and address of respondent has been removed; and 2.the information is disclosed in a manner that is not likely to enable the identification of the particular person or undertaking or business to which it relates. 3.not attempt to identify any particular person or undertaking or business; 4.use of information for research or statistically purpose only; 5.not to disclose the information to any other person, organization 6.when required by the Director General, return all documents made available to him to the Director General; 7.comply with the directions given by the Director General relating to the records. 8.every person involved in the research or statistical project for which information is disclosed pursuant to this section shall make the declaration of secrecy set out in the first schedule. National Bureau of Statistics "National Bureau of Statistics, Agriculture Sample Census Survey 2007/2008 version 1.0 of the public use dataset (Dec 2011) provided by the National Bureau of Statistics, www.nbs.go.tz" Tanzania NBS considered three levels of accessibility: 1) Public use files, accessible by all 2) Licensed datasets, accessible under certain conditions 3) Datasets only accessible on location, for certain datasets Public use files accessible to all for statistical and research purposes only, under the following terms and conditions: 1.The data and other material will not be redistributed or sold to other individuals, institutions, or organization without the written agreement of the National Bureau of Statistics. 2.The data will be used for statistical and scientific research purposes only. They will be used solely for reporting of aggregated information, and not for investigation of specific individuals or organizations. 3.No attempt will be made to produce links among dataset provided by the National Bureau of Statistics, or among data from the (National Bureau of Statistics) and other datasets that could identify individuals or organizations 4.No attempt will be made to re-identify respondents, and no use will be made of the identify of any person or establishment discovered inadvertently. Any such discovery would immediately be reported to the National Bureau of Statistics. 5.Any books, articles, conference papers, theses, dissertations, reports, or other publications that employ data obtained from the National Bureau of Statistics will cite the source of data in accordance with the Citation Requirement provided with each dataset. "The user of the data should acknowledges that, National Bureau of Statistics is the original collector of the data , the authorised distributor of the data, and the relevant funding agency bear no responsibility for use of the data or for interpretations or inferences without a written agreement from the National Bureau of Statistics" R00-Small Scale Farmers 0 91 R031-Small Scale Farmers 0 21 R041-Small Scale Farmers 0 11 R042-Small Scale Farmers 0 11 R051-Small Scale Farmers 0 41 R052-Small Scale Farmers 0 41 R053-Small Scale Farmers 0 43 R061-Small Scale Farmers 0 12 R062-Small Scale Farmers 0 13 R063-Small Scale Farmers 0 14 R064-Small Scale Farmers 0 13 R066-Small Scale Farmers 0 12 R091-Small Scale Farmers 0 14 R092-Small Scale Farmers 0 15 R093-Small Scale Farmers 0 14 R094-Small Scale Farmers 0 13 R095-Small Scale Farmers 0 11 R099-Small Scale Farmers 0 23 R104-Small Scale Farmers 0 13 R0651-Small Scale Farmers 0 13 R0831-Small Scale Farmers 0 12 R0910-Small Scale Farmers 0 17 R0911-Small Scale Farmers 0 11 R000-Large Scale Farms 0 48 R031-Large Scale Farms 0 5 R032-Large Scale Farms 0 5 R041-Large Scale Farms 0 13 R043-Large Scale Farms 0 16 R071-Large Scale Farms 0 4 R081-Large Scale Farms 0 10 R098-Large Scale Farms 0 8 R099-Large Scale Farms 0 9 R101-Large Scale Farms 0 8 R111-Large Scale Farms 0 9 R111_4-Large Scale Farms 0 9 R114-Large Scale Farms 0 8 R422-Large Scale Farms 0 13 R511-Large Scale Farms 0 10 R522-Large Scale Farms 0 21 R522_1-Large Scale Farms 0 21 R621-Large Scale Farms 0 6 R622-Large Scale Farms 0 6 R910-Large Scale Farms 0 6 R911-Large Scale Farms 0 8 R917-Large Scale Farms 0 7 R921-Large Scale Farms 0 8 R926-Large Scale Farms 0 7 R931-Large Scale Farms 0 4 R941-Large Scale Farms 0 5 R951-Large Scale Farms 0 7 R954-Large Scale Farms 0 8 R971-Large Scale Farms 0 9 R972-Large Scale Farms 0 8 Region Region Region Region Region 01 Dodoma 02 Arusha 03 Kilimanjaro 04 Tanga 05 Morogoro 06 Pwani 07 Dar es Salaam 08 Lindi 09 Mtwara 10 Ruvuma 11 Iringa 12 Mbeya 13 Singida 14 Tabora 15 Rukwa 16 Kigoma 17 Shinyanga 18 Kagera 19 Mwanza 20 Mara 21 Manyara 51 North Unguja 52 South Unguja 53 Urban West 54 North Pemba 55 South Pemba District District District District District Ward Ward Ward Ward Ward Village Village Village Village Village Head of household number Head of household number Head of household number Head of household number Head of household number 1.2.1 Number of local leader 1.2.1 Number of local leader 1.2.1 Number of local leader 1.2.1 Number of local leader 1.2.1 Number of local leader 1.2.2 Number of Household Head 1.2.2 Number of Household Head 1.2.2 Number of Household Head 1.2.2 Number of Household Head 1.2.2 Number of Household Head 1.2.3 Sex of Head of Household 1.2.3 Sex of Head of Household 1.2.3 Sex of Head of Household 1.2.3 Sex of Head of Household 1.2.3 Sex of Head of Household 1 Male 2 Female 1.2.5 Relationship of Respondent to Head hh 1.2.5 Relationship of Respondent to Head hh 1.2.5 Relationship of Respondent to Head hh 1.2.5 Relationship of Respondent to Head hh 1.2.5 Relationship of Respondent to Head hh 1 Head of Household 2 Spouse 3 Son/Daughter 4 Father/Mother 5 Grandson/Granddaughter 6 Other relative 7 Not Related 2.1 Type of Agriculture Household 2.1 Type of Agriculture Household 2.1 Type of Agriculture Household 2.1 Type of Agriculture Household 2.1 Type of Agriculture Household 1 Crops only 2 Livestock only 3 Pastoralist 4 Crops and Livestock 4.1.8 Was all Land Available to the Hh Used During 2007/08? 4.1.8 Was all Land Available to the Hh Used During 2007/08? 4.1.8 Was all Land Available to the Hh Used During 2007/08? 4.1.8 Was all Land Available to the Hh Used During 2007/08? 4.1.8 Was all Land Available to the Hh Used During 2007/08? 1 Yes 2 No 4.1.9 Do you Consider that you have sufficient land for the 4.1.9 Do you Consider that you have sufficient land for the 4.1.9 Do you Consider that you have sufficient land for the 4.1.9 Do you Consider that you have sufficient land for the 4.1.9 Do you Consider that you have sufficient land for the 1 Yes 2 No 4.1.10 Do any Female Members of the Hh own or have customary 4.1.10 Do any Female Members of the Hh own or have customary 4.1.10 Do any Female Members of the Hh own or have customary 4.1.10 Do any Female Members of the Hh own or have customary 4.1.10 Do any Female Members of the Hh own or have customary 1 Yes 2 No 5.1 Did the Hh plant any crops 2007/08 during Short Rainy Se 5.1 Did the Hh plant any crops 2007/08 during Short Rainy Se 5.1 Did the Hh plant any crops 2007/08 during Short Rainy Se 5.1 Did the Hh plant any crops 2007/08 during Short Rainy Se 5.1 Did the Hh plant any crops 2007/08 during Short Rainy Se 1 Yes 2 No 5.2 Did the Hh plant any crop during 2007/08 Long Rainy Seas 5.2 Did the Hh plant any crop during 2007/08 Long Rainy Seas 5.2 Did the Hh plant any crop during 2007/08 Long Rainy Seas 5.2 Did the Hh plant any crop during 2007/08 Long Rainy Seas 5.2 Did the Hh plant any crop during 2007/08 Long Rainy Seas 1 Yes 2 No 5.3 Does your Household have any Permanent / Perennial Crops 5.3 Does your Household have any Permanent / Perennial Crops 5.3 Does your Household have any Permanent / Perennial Crops 5.3 Does your Household have any Permanent / Perennial Crops 5.3 Does your Household have any Permanent / Perennial Crops 1 Yes 2 No 6.2 Did you use Draft animals to cultivate your land during 6.2 Did you use Draft animals to cultivate your land during 6.2 Did you use Draft animals to cultivate your land during 6.2 Did you use Draft animals to cultivate your land during 6.2 Did you use Draft animals to cultivate your land during 1 Yes 2 No 6.5.1 Does the Household Practice Irrigation? 6.5.1 Does the Household Practice Irrigation? 6.5.1 Does the Household Practice Irrigation? 6.5.1 Does the Household Practice Irrigation? 6.5.1 Does the Household Practice Irrigation? 1 Yes 2 No 6.6.1 Does the household have any erosion problem on their f 6.6.1 Does the household have any erosion problem on their f 6.6.1 Does the household have any erosion problem on their f 6.6.1 Does the household have any erosion problem on their f 6.6.1 Does the household have any erosion problem on their f 1 Yes 2 No 6.6.2 Does the household have any erosion control/water harv 6.6.2 Does the household have any erosion control/water harv 6.6.2 Does the household have any erosion control/water harv 6.6.2 Does the household have any erosion control/water harv 6.6.2 Does the household have any erosion control/water harv 1 Yes 2 No 7.1 During the year 2007/08 did any of the hh members borrow 7.1 During the year 2007/08 did any of the hh members borrow 7.1 During the year 2007/08 did any of the hh members borrow 7.1 During the year 2007/08 did any of the hh members borrow 7.1 During the year 2007/08 did any of the hh members borrow 1 Yes 2 No Source of Credit (7.1.1a) Source of Credit (7.1.1a) Source of Credit (7.1.1a) Source of Credit (7.1.1a) Source of Credit (7.1.1a) 1 Family, friend or relative 2 Bank 3 Savings & credit Soc 4 Cooperative 5 Savings & credit Soc 6 Trader/trade store 7 Private individual 8 NGO/Project Source of Credit (7.1.2a) Source of Credit (7.1.2a) Source of Credit (7.1.2a) Source of Credit (7.1.2a) Source of Credit (7.1.2a) 1 Family, friend or relative 2 Bank 3 Savings & credit Soc 4 Cooperative 5 Savings & credit Soc 6 Trader/trade store 7 Private individual 8 NGO/Project Source of Credit (7.1.3a) Source of Credit (7.1.3a) Source of Credit (7.1.3a) Source of Credit (7.1.3a) Source of Credit (7.1.3a) 1 Family, friend or relative 2 Bank 3 Savings & credit Soc 4 Cooperative 5 Savings & credit Soc 6 Trader/trade store 7 Private individual 8 NGO/Project Credit given to (7.1.1b) Credit given to (7.1.1b) Credit given to (7.1.1b) Credit given to (7.1.1b) Credit given to (7.1.1b) 1 Male 2 Female Credit given to (7.1.2b) Credit given to (7.1.2b) Credit given to (7.1.2b) Credit given to (7.1.2b) Credit given to (7.1.2b) 1 Male 2 Female Credit given to (7.1.3b) Credit given to (7.1.3b) Credit given to (7.1.3b) Credit given to (7.1.3b) Credit given to (7.1.3b) 1 Male 2 Female 7.2 If the answer to question 7.1 above is 'NO' what is the 7.2 If the answer to question 7.1 above is 'NO' what is the 7.2 If the answer to question 7.1 above is 'NO' what is the 7.2 If the answer to question 7.1 above is 'NO' what is the 7.2 If the answer to question 7.1 above is 'NO' what is the 1 Not needed 2 Not available 3 Did not want to go into debt 4 Interest rate/cost too high 5 Did not know how to get credit 6 Difficult bureaucratic procedure 7 Credit granted too late 8 Other (specify) 9 Dont know about credit 8.1 Did the households or any member of the household partic 8.1 Did the households or any member of the household partic 8.1 Did the households or any member of the household partic 8.1 Did the households or any member of the household partic 8.1 Did the households or any member of the household partic 1 Yes 2 No 8.2 Did the households or any member of the household Partic 8.2 Did the households or any member of the household Partic 8.2 Did the households or any member of the household Partic 8.2 Did the households or any member of the household Partic 8.2 Did the households or any member of the household Partic 1 Yes 2 No 9.1 Did the household own, raise or manage any Cattle during 9.1 Did the household own, raise or manage any Cattle during 9.1 Did the household own, raise or manage any Cattle during 9.1 Did the household own, raise or manage any Cattle during 9.1 Did the household own, raise or manage any Cattle during 1 Yes 2 No 9.1.8 How did you identify your cattle? 9.1.8 How did you identify your cattle? 9.1.8 How did you identify your cattle? 9.1.8 How did you identify your cattle? 9.1.8 How did you identify your cattle? 1 Chapa ya moto 2 Koo za ng'ombe 3 Kukata Masikio/Mkia 4 Rangi za Mifugo 5 Hereni za Masikio 8 Nyingine 9.3 Did the Hh own, raise or manage any GOAT during 2007/08? 9.3 Did the Hh own, raise or manage any GOAT during 2007/08? 9.3 Did the Hh own, raise or manage any GOAT during 2007/08? 9.3 Did the Hh own, raise or manage any GOAT during 2007/08? 9.3 Did the Hh own, raise or manage any GOAT during 2007/08? 1 Yes 2 No 9.4 Did the household own, raise or manage any SHEEP during 9.4 Did the household own, raise or manage any SHEEP during 9.4 Did the household own, raise or manage any SHEEP during 9.4 Did the household own, raise or manage any SHEEP during 9.4 Did the household own, raise or manage any SHEEP during 1 Yes 2 No 9.5 Did the household own, raise or manage any PIGS during 2 9.5 Did the household own, raise or manage any PIGS during 2 9.5 Did the household own, raise or manage any PIGS during 2 9.5 Did the household own, raise or manage any PIGS during 2 9.5 Did the household own, raise or manage any PIGS during 2 1 Yes 2 No 9.7 Did you deworm your animals during 07/08? 9.7 Did you deworm your animals during 07/08? 9.7 Did you deworm your animals during 07/08? 9.7 Did you deworm your animals during 07/08? 9.7 Did you deworm your animals during 07/08? 1 Yes 2 No 9.7.1 Dewormed Cattles 9.7.1 Dewormed Cattles 9.7.1 Dewormed Cattles 9.7.1 Dewormed Cattles 9.7.1 Dewormed Cattles 1 Yes 2 No 3 Not Applicable 9.7.2 Dewormed Goats 9.7.2 Dewormed Goats 9.7.2 Dewormed Goats 9.7.2 Dewormed Goats 9.7.2 Dewormed Goats 1 Yes 2 No 3 Not Applicable 9.7.3 Dewormed Sheep 9.7.3 Dewormed Sheep 9.7.3 Dewormed Sheep 9.7.3 Dewormed Sheep 9.7.3 Dewormed Sheep 1 Yes 2 No 3 Not Applicable 9.7.4 Dewormed Pigs 9.7.4 Dewormed Pigs 9.7.4 Dewormed Pigs 9.7.4 Dewormed Pigs 9.7.4 Dewormed Pigs 1 Yes 2 No 3 Not Applicable 9.7.5 Do you normally encounter a TICK problem? 9.7.5 Do you normally encounter a TICK problem? 9.7.5 Do you normally encounter a TICK problem? 9.7.5 Do you normally encounter a TICK problem? 9.7.5 Do you normally encounter a TICK problem? 1 Yes 2 No 3 Not Applicable 9.7.6 Which methods of TICK control did you use 9.7.6 Which methods of TICK control did you use 9.7.6 Which methods of TICK control did you use 9.7.6 Which methods of TICK control did you use 9.7.6 Which methods of TICK control did you use 1 Dipping 2 Spraying 3 Smearing 4 None 5 Other 9.7.7 Do you normally encounter a TSETSE FLY problem? 9.7.7 Do you normally encounter a TSETSE FLY problem? 9.7.7 Do you normally encounter a TSETSE FLY problem? 9.7.7 Do you normally encounter a TSETSE FLY problem? 9.7.7 Do you normally encounter a TSETSE FLY problem? 1 Yes 2 No 3 Not Applicable 9.7.8 Which methods of control did you use? 9.7.8 Which methods of control did you use? 9.7.8 Which methods of control did you use? 9.7.8 Which methods of control did you use? 9.7.8 Which methods of control did you use? 1 Dipping 2 Spraying 3 Trappig 4 None 5 Other 9.7.9 Do you normally encounter a NEWCASTLE Disease problem 9.7.9 Do you normally encounter a NEWCASTLE Disease problem 9.7.9 Do you normally encounter a NEWCASTLE Disease problem 9.7.9 Do you normally encounter a NEWCASTLE Disease problem 9.7.9 Do you normally encounter a NEWCASTLE Disease problem 1 Yes 2 No 3 Not Applicable 9.7.10 Which methods of control did you use? 9.7.10 Which methods of control did you use? 9.7.10 Which methods of control did you use? 9.7.10 Which methods of control did you use? 9.7.10 Which methods of control did you use? 1 Vaccination 2 Local Herbs 3 None 9.7.11 Do you normally encounter FOWL TYPHOID problem on you 9.7.11 Do you normally encounter FOWL TYPHOID problem on you 9.7.11 Do you normally encounter FOWL TYPHOID problem on you 9.7.11 Do you normally encounter FOWL TYPHOID problem on you 9.7.11 Do you normally encounter FOWL TYPHOID problem on you 1 Yes 2 No 3 Not Applicable 9.7.12 Which methods of control did you use? 9.7.12 Which methods of control did you use? 9.7.12 Which methods of control did you use? 9.7.12 Which methods of control did you use? 9.7.12 Which methods of control did you use? 1 Vaccination 2 Local Herbs 3 None 9.7.13A Foot and mouth disease 9.7.13A Foot and mouth disease 9.7.13A Foot and mouth disease 9.7.13A Foot and mouth disease 9.7.13A Foot and mouth disease 1 Yes 2 No 3 Not Applicable 9.7.13B Lumpyskin 9.7.13B Lumpyskin 9.7.13B Lumpyskin 9.7.13B Lumpyskin 9.7.13B Lumpyskin 1 Yes 2 No 3 Not Applicable 9.9 Was fish farming carried out by this household during 20 9.9 Was fish farming carried out by this household during 20 9.9 Was fish farming carried out by this household during 20 9.9 Was fish farming carried out by this household during 20 9.9 Was fish farming carried out by this household during 20 1 Yes 2 No 9.10 Do you harvest HONEY in your household? 9.10 Do you harvest HONEY in your household? 9.10 Do you harvest HONEY in your household? 9.10 Do you harvest HONEY in your household? 9.10 Do you harvest HONEY in your household? 1 Yes 2 No 10.1.1 Used materials for Roofing? 10.1.1 Used materials for Roofing? 10.1.1 Used materials for Roofing? 10.1.1 Used materials for Roofing? 10.1.1 Used materials for Roofing? 1 Iron Sheets 2 Tiles 3 Concrete 4 Asbestos 5 Grass/leaves. 6 Grass & mud.. 8 Other (Specify) 10.1.2 Used materials for Floor? 10.1.2 Used materials for Floor? 10.1.2 Used materials for Floor? 10.1.2 Used materials for Floor? 10.1.2 Used materials for Floor? 1 Earth, Sand, Dung 2 Wood Planks, Bamboo, Palm. 3 Parquet Or Polished Wood 4 Ceramic Tiles, Terrazzo 5 Cement 8 Other (specify) 10.1.3 Used materials for Walls? 10.1.3 Used materials for Walls? 10.1.3 Used materials for Walls? 10.1.3 Used materials for Walls? 10.1.3 Used materials for Walls? 1 Grass 2 Poles And Mud 3 Sun-Dried Bricks 4 Baked Bricks 5 Wood, Timber 6 Cement Blocks 7 Stones 8 Other (specify) 10.1.4 Number of rooms 10.1.4 Number of rooms 10.1.4 Number of rooms 10.1.4 Number of rooms 10.1.4 Number of rooms 10.2.1 Radio/cassette, music system 10.2.1 Radio/cassette, music system 10.2.1 Radio/cassette, music system 10.2.1 Radio/cassette, music system 10.2.1 Radio/cassette, music system 1 Yes 2 No 10.2.2 Telephone (landline) 10.2.2 Telephone (landline) 10.2.2 Telephone (landline) 10.2.2 Telephone (landline) 10.2.2 Telephone (landline) 1 Yes 2 No 10.2.3 Telephone (mobile) 10.2.3 Telephone (mobile) 10.2.3 Telephone (mobile) 10.2.3 Telephone (mobile) 10.2.3 Telephone (mobile) 1 Yes 2 No 10.2.4 Pressing Iron 10.2.4 Pressing Iron 10.2.4 Pressing Iron 10.2.4 Pressing Iron 10.2.4 Pressing Iron 1 Yes 2 No 10.2.5 Wheelbarrow 10.2.5 Wheelbarrow 10.2.5 Wheelbarrow 10.2.5 Wheelbarrow 10.2.5 Wheelbarrow 1 Yes 2 No 10.2.6 Bicycle 10.2.6 Bicycle 10.2.6 Bicycle 10.2.6 Bicycle 10.2.6 Bicycle 1 Yes 2 No 10.2.7 Vehicle 10.2.7 Vehicle 10.2.7 Vehicle 10.2.7 Vehicle 10.2.7 Vehicle 1 Yes 2 No 10.2.8 Television 10.2.8 Television 10.2.8 Television 10.2.8 Television 10.2.8 Television 1 Yes 2 No 10.2.9 Refrigerator 10.2.9 Refrigerator 10.2.9 Refrigerator 10.2.9 Refrigerator 10.2.9 Refrigerator 1 Yes 2 No 10.2.10 Motor Cycle 10.2.10 Motor Cycle 10.2.10 Motor Cycle 10.2.10 Motor Cycle 10.2.10 Motor Cycle 1 Yes 2 No 10.3.1 Energy used for Lighting 10.3.1 Energy used for Lighting 10.3.1 Energy used for Lighting 10.3.1 Energy used for Lighting 10.3.1 Energy used for Lighting 1 Mains electricity 2 Solar 3 Gas (hh biogas) 4 Hurican Lamp 5 Pressure Lamp 6 Wick Lamp 7 Candles 8 Fire Wood 98 Other (specify) 10.3.2 Energy used for Cooking 10.3.2 Energy used for Cooking 10.3.2 Energy used for Cooking 10.3.2 Energy used for Cooking 10.3.2 Energy used for Cooking 1 Mains electricity 2 Solar 3 Gas (hh biogas) 4 Bottled gas 5 Paraffin/kerocine. 6 Charcoal 7 Firewood 8 Crop Residues 9 Livestock dung 98 Other (specify) 10.5.1 What type of toilet does your hh use? 10.5.1 What type of toilet does your hh use? 10.5.1 What type of toilet does your hh use? 10.5.1 What type of toilet does your hh use? 10.5.1 What type of toilet does your hh use? 1 No toilet/bush 2 Flush toilet 3 Pit latrine - traditional 4 Improved pit latrine - hh owned 8 Other type (specify) 10.6.1 Number of meals the hh normally has per day 10.6.1 Number of meals the hh normally has per day 10.6.1 Number of meals the hh normally has per day 10.6.1 Number of meals the hh normally has per day 10.6.1 Number of meals the hh normally has per day 10.6.2 Number of days hh consumed meat last week 10.6.2 Number of days hh consumed meat last week 10.6.2 Number of days hh consumed meat last week 10.6.2 Number of days hh consumed meat last week 10.6.2 Number of days hh consumed meat last week 10.6.3 Number of days hh consumed Fish last week 10.6.3 Number of days hh consumed Fish last week 10.6.3 Number of days hh consumed Fish last week 10.6.3 Number of days hh consumed Fish last week 10.6.3 Number of days hh consumed Fish last week 10.6.4 How often did the hh have problems in satisfying the 10.6.4 How often did the hh have problems in satisfying the 10.6.4 How often did the hh have problems in satisfying the 10.6.4 How often did the hh have problems in satisfying the 10.6.4 How often did the hh have problems in satisfying the 1 Never 2 Seldom 3 Sometimes 4 Often 5 Always 10.7.1 What is the household main source of cash income? 10.7.1 What is the household main source of cash income? 10.7.1 What is the household main source of cash income? 10.7.1 What is the household main source of cash income? 10.7.1 What is the household main source of cash income? 1 Sale of food crops 2 Sale of Livestock 3 Sale of livestock products 4 Sale of cash crops 5 Sale of forest products 6 Business income 7 Wages or salaries in cash 8 ther casual cash earnings 9 Cash remittances 10 Fishing 98 Other 99 Not applicable Year Year Year Year Year Month Month Month Month Month Day Day Day Day Day Starting Time(hour) Starting Time(hour) Starting Time(hour) Starting Time(hour) Starting Time(hour) Starting Time(minutes) Starting Time(minutes) Starting Time(minutes) Starting Time(minutes) Starting Time(minutes) Ending Time (hour) Ending Time (hour) Ending Time (hour) Ending Time (hour) Ending Time (hour) Ending Time (minutes) Ending Time (minutes) Ending Time (minutes) Ending Time (minutes) Ending Time (minutes) District Supervisor District Supervisor District Supervisor District Supervisor District Supervisor Regional Supervisor Regional Supervisor Regional Supervisor Regional Supervisor Regional Supervisor National Supervisor National Supervisor National Supervisor National Supervisor National Supervisor Questionnaire Quality Questionnaire Quality Questionnaire Quality Questionnaire Quality Questionnaire Quality EndTime last page(HRS) EndTime last page(HRS) EndTime last page(HRS) EndTime last page(HRS) EndTime last page(HRS) EndTime last page(MIN) EndTime last page(MIN) EndTime last page(MIN) EndTime last page(MIN) EndTime last page(MIN) Village Identification Village Identification Village Identification Village Identification Village Identification District Identification District Identification District Identification District Identification District Identification 011 Kondoa 012 Mpwapwa 013 Kongwa 015 Dodoma Urban 016 Bahi 017 Chamwino 021 Monduli 023 Arusha 024 Karatu 025 Ngorongoro 026 Longido 027 Arusha Rural 028 Meru 031 Rombo 032 Mwanga 033 Same 034 Moshi Rural 035 Hai 037 Siha 041 Lushoto 042 Korogwe 043 Muheza 044 Tanga 045 Pangani 046 Handeni 047 Kilindi 048 Mkinga 051 Kilosa 052 Morogoro 053 Kilombero 054 Ulanga 055 Morogoro Urban 056 Mvomero 061 Bagamoyo 062 Kibaha 063 Kisarawe 064 Mkuranga 065 Rufiji 066 Mafia 071 Kinondoni 072 Ilala 073 Temeke 081 Kilwa 082 Lindi Rural 083 Nachingwea 084 Liwale 085 Ruangwa 086 Lindi Urban 091 Mtwara Rural 092 Newala 093 Masasi 094 Tandahimba 095 Mtwara Urban 096 Nanyumbu 101 Tunduru 102 Songea Rural 103 Mbinga 104 Songea Urban 105 Namtumbo 111 Iringa Rural 112 Mufindi 113 Makete 114 Njombe 115 Ludewa 116 Iringa Urban 117 Kilolo 118 Njombe Mji 121 Chunya 122 Mbeya (R) 123 Kyela 124 Rungwe 125 Ileje 126 Mbozi 127 Mbarali 128 Mbeya Urban 131 Iramba 132 Singida Rural 133 Manyoni 134 Singida Urban 141 Nzega 142 Igunga 143 Uyui 144 Urambo 145 Sikonge 146 Tabora Urban 151 Mpanda 152 Sumbawanga Rural 153 Nkasi 154 Sumbawanga Urban 161 Kibondo 162 Kasulu 163 Kigoma Rural 164 Kigoma Urban 171 Bariadi 172 Maswa 173 Shinyanga Rural 174 Kahama 175 Bukombe 176 Meatu 177 Shinyanga Urban 178 Kishapu 181 Karagwe 182 Bukoba Rural 183 Muleba 184 Biharamulo 185 Ngara 186 Bukoba Urban 187 Missenyi 188 Chato 191 Ukerewe 192 Magu 194 Kwimba 195 Sengerema 196 Geita 197 Missungwi 198 Ilemela 201 Tarime 202 Serengeti 203 Musoma Rural 204 Bunda 205 Musoma Urban 206 Rorya 211 Babati 212 Hanang 213 Mbulu 214 Simanjiro 215 Kiteto 511 Kaskazini-A 512 Kaskazini-B 521 Kati 522 Kusini 531 Magharibi 541 Wete 542 Micheweni 551 Chake 552 Mkoani Region Region Region Region Region 01 Dodoma 02 Arusha 03 Kilimanjaro 04 Tanga 05 Morogoro 06 Pwani 07 Dar es Salaam 08 Lindi 09 Mtwara 10 Ruvuma 11 Iringa 12 Mbeya 13 Singida 14 Tabora 15 Rukwa 16 Kigoma 17 Shinyanga 18 Kagera 19 Mwanza 20 Mara 21 Manyara 51 North Unguja 52 South Unguja 53 Urban West 54 North Pemba 55 South Pemba District District District District District Ward Ward Ward Ward Ward Village Village Village Village Village Head of household number Head of household number Head of household number Head of household number Head of household number S/No S/No S/No S/No S/No Relationship to Head Relationship to Head Relationship to Head Relationship to Head Relationship to Head 1 Head of Household 2 Spouse 3 Son / Daughter 4 Father / Mother 5 Grandchild 6 Other Relative 8 Others Sex Sex Sex Sex Sex 1 Male 2 Female Age Age Age Age Age Marital status Marital status Marital status Marital status Marital status 1 Married 2 Not Married 3 Living together 4 Separated 5 Widowed Survival of Mother Survival of Mother Survival of Mother Survival of Mother Survival of Mother 1 Yes 2 No 3 Don't know Survival of Father Survival of Father Survival of Father Survival of Father Survival of Father 1 Yes 2 No 3 Don't know Read & Write Read & Write Read & Write Read & Write Read & Write 1 Swahili 2 English 3 Swahili & English 4 Any Other Language 5 Don't Read / Write Education Status Education Status Education Status Education Status Education Status 1 Attending School 2 Completed 3 Never Attended to School Education Level Education Level Education Level Education Level Education Level Under Standard One 1 Standard One 2 Standard Two 3 Standard Three 4 Standard Four 5 Standard Five 6 Standard Six 7 Standard Seven 8 Standard Eight 9 Training After Primary Education 10 Pre Form One 11 Form One 12 Form Two 13 Form Three 14 Form Four 15 Form Five 16 Form Six 17 Training After Secondary Education 18 University & Other Tertiary Education 19 Adult Education 99 Not applicable Involvement in Farming Involvement in Farming Involvement in Farming Involvement in Farming Involvement in Farming 1 Works Full-time on Farm 2 Works Part-time on Farm 3 Rarely Works on Farm 4 Never Works on Farm Main Activity Main Activity Main Activity Main Activity Main Activity 1 Crop/Seaweed Farming 2 Livestock Keeping / Herding 3 Livestock Pastoralist 4 Fishing 5 Fish Farming 6 Government / Parastatal 7 Private - NGO / Mission / etc 8 Self Employed (Non Farmimg) with Employees 9 Self Employed (Non Farmimg) without Employees 10 Unpaid Family Helper (Non Agriculture) 11 Not Working & Available 12 Not Working & Unavailable 13 Housemaker / Housewife 14 Student 15 Unable to Work / Too Old / Retired / Sick / Disabled 98 Other Off Farm Income Off Farm Income Off Farm Income Off Farm Income Off Farm Income 1 Yes 2 No Village Identification Village Identification Village Identification Village Identification Village Identification District Identification District Identification District Identification District Identification District Identification 011 Kondoa 012 Mpwapwa 013 Kongwa 015 Dodoma Urban 016 Bahi 017 Chamwino 021 Monduli 023 Arusha 024 Karatu 025 Ngorongoro 026 Longido 027 Arusha Rural 028 Meru 031 Rombo 032 Mwanga 033 Same 034 Moshi Rural 035 Hai 037 Siha 041 Lushoto 042 Korogwe 043 Muheza 044 Tanga 045 Pangani 046 Handeni 047 Kilindi 048 Mkinga 051 Kilosa 052 Morogoro 053 Kilombero 054 Ulanga 055 Morogoro Urban 056 Mvomero 061 Bagamoyo 062 Kibaha 063 Kisarawe 064 Mkuranga 065 Rufiji 066 Mafia 071 Kinondoni 072 Ilala 073 Temeke 081 Kilwa 082 Lindi Rural 083 Nachingwea 084 Liwale 085 Ruangwa 086 Lindi Urban 091 Mtwara Rural 092 Newala 093 Masasi 094 Tandahimba 095 Mtwara Urban 096 Nanyumbu 101 Tunduru 102 Songea Rural 103 Mbinga 104 Songea Urban 105 Namtumbo 111 Iringa Rural 112 Mufindi 113 Makete 114 Njombe 115 Ludewa 116 Iringa Urban 117 Kilolo 118 Njombe Mji 121 Chunya 122 Mbeya (R) 123 Kyela 124 Rungwe 125 Ileje 126 Mbozi 127 Mbarali 128 Mbeya Urban 131 Iramba 132 Singida Rural 133 Manyoni 134 Singida Urban 141 Nzega 142 Igunga 143 Uyui 144 Urambo 145 Sikonge 146 Tabora Urban 151 Mpanda 152 Sumbawanga Rural 153 Nkasi 154 Sumbawanga Urban 161 Kibondo 162 Kasulu 163 Kigoma Rural 164 Kigoma Urban 171 Bariadi 172 Maswa 173 Shinyanga Rural 174 Kahama 175 Bukombe 176 Meatu 177 Shinyanga Urban 178 Kishapu 181 Karagwe 182 Bukoba Rural 183 Muleba 184 Biharamulo 185 Ngara 186 Bukoba Urban 187 Missenyi 188 Chato 191 Ukerewe 192 Magu 194 Kwimba 195 Sengerema 196 Geita 197 Missungwi 198 Ilemela 201 Tarime 202 Serengeti 203 Musoma Rural 204 Bunda 205 Musoma Urban 206 Rorya 211 Babati 212 Hanang 213 Mbulu 214 Simanjiro 215 Kiteto 511 Kaskazini-A 512 Kaskazini-B 521 Kati 522 Kusini 531 Magharibi 541 Wete 542 Micheweni 551 Chake 552 Mkoani Region Region Region Region Region 01 Dodoma 02 Arusha 03 Kilimanjaro 04 Tanga 05 Morogoro 06 Pwani 07 Dar es Salaam 08 Lindi 09 Mtwara 10 Ruvuma 11 Iringa 12 Mbeya 13 Singida 14 Tabora 15 Rukwa 16 Kigoma 17 Shinyanga 18 Kagera 19 Mwanza 20 Mara 21 Manyara 51 North Unguja 52 South Unguja 53 Urban West 54 North Pemba 55 South Pemba District District District District District Ward Ward Ward Ward Ward Village Village Village Village Village Head of household number Head of household number Head of household number Head of household number Head of household number Land Access Land Access Land Access Land Access Land Access 1 Area Leased/Certificate of ownership 2 Area owned under Customary Law 3 Area Bought from others 4 Area Rented from others 5 Area Borrowed from others 6 Area Share -cropped from others 7 Area under Other forms of tenure Area in Acres Area in Acres Area in Acres Area in Acres Area in Acres Village Identification Village Identification Village Identification Village Identification Village Identification District Identification District Identification District Identification District Identification District Identification 011 Kondoa 012 Mpwapwa 013 Kongwa 015 Dodoma Urban 016 Bahi 017 Chamwino 021 Monduli 023 Arusha 024 Karatu 025 Ngorongoro 026 Longido 027 Arusha Rural 028 Meru 031 Rombo 032 Mwanga 033 Same 034 Moshi Rural 035 Hai 037 Siha 041 Lushoto 042 Korogwe 043 Muheza 044 Tanga 045 Pangani 046 Handeni 047 Kilindi 048 Mkinga 051 Kilosa 052 Morogoro 053 Kilombero 054 Ulanga 055 Morogoro Urban 056 Mvomero 061 Bagamoyo 062 Kibaha 063 Kisarawe 064 Mkuranga 065 Rufiji 066 Mafia 071 Kinondoni 072 Ilala 073 Temeke 081 Kilwa 082 Lindi Rural 083 Nachingwea 084 Liwale 085 Ruangwa 086 Lindi Urban 091 Mtwara Rural 092 Newala 093 Masasi 094 Tandahimba 095 Mtwara Urban 096 Nanyumbu 101 Tunduru 102 Songea Rural 103 Mbinga 104 Songea Urban 105 Namtumbo 111 Iringa Rural 112 Mufindi 113 Makete 114 Njombe 115 Ludewa 116 Iringa Urban 117 Kilolo 118 Njombe Mji 121 Chunya 122 Mbeya (R) 123 Kyela 124 Rungwe 125 Ileje 126 Mbozi 127 Mbarali 128 Mbeya Urban 131 Iramba 132 Singida Rural 133 Manyoni 134 Singida Urban 141 Nzega 142 Igunga 143 Uyui 144 Urambo 145 Sikonge 146 Tabora Urban 151 Mpanda 152 Sumbawanga Rural 153 Nkasi 154 Sumbawanga Urban 161 Kibondo 162 Kasulu 163 Kigoma Rural 164 Kigoma Urban 171 Bariadi 172 Maswa 173 Shinyanga Rural 174 Kahama 175 Bukombe 176 Meatu 177 Shinyanga Urban 178 Kishapu 181 Karagwe 182 Bukoba Rural 183 Muleba 184 Biharamulo 185 Ngara 186 Bukoba Urban 187 Missenyi 188 Chato 191 Ukerewe 192 Magu 194 Kwimba 195 Sengerema 196 Geita 197 Missungwi 198 Ilemela 201 Tarime 202 Serengeti 203 Musoma Rural 204 Bunda 205 Musoma Urban 206 Rorya 211 Babati 212 Hanang 213 Mbulu 214 Simanjiro 215 Kiteto 511 Kaskazini-A 512 Kaskazini-B 521 Kati 522 Kusini 531 Magharibi 541 Wete 542 Micheweni 551 Chake 552 Mkoani Region Region Region Region Region 01 Dodoma 02 Arusha 03 Kilimanjaro 04 Tanga 05 Morogoro 06 Pwani 07 Dar es Salaam 08 Lindi 09 Mtwara 10 Ruvuma 11 Iringa 12 Mbeya 13 Singida 14 Tabora 15 Rukwa 16 Kigoma 17 Shinyanga 18 Kagera 19 Mwanza 20 Mara 21 Manyara 51 North Unguja 52 South Unguja 53 Urban West 54 North Pemba 55 South Pemba District District District District District Ward Ward Ward Ward Ward Village Village Village Village Village Head of household number Head of household number Head of household number Head of household number Head of household number Land Use Land Use Land Use Land Use Land Use 1 Area under Temporary Mono-crops 2 Area under Temporary Mixed crops (eg Maize & beans) 3 Area under Permanent Mono-crops 4 Area under Permanent Mixed crops (eg bananas, coffee & trees 5 Area under Permanent/temporary mix (eg bananas & maize) 6 Area under Pasture 7 Area under Fallow 8 Area under Natural Bush 9 Area under Planted Trees 10 Area Rented to others 11 Area Unusable 12 Area of Uncultivated Usable land (excluding fallow) Area in Acres Area in Acres Area in Acres Area in Acres Area in Acres Village Identification Village Identification Village Identification Village Identification Village Identification District Identification District Identification District Identification District Identification District Identification 011 Kondoa 012 Mpwapwa 013 Kongwa 015 Dodoma Urban 016 Bahi 017 Chamwino 021 Monduli 023 Arusha 024 Karatu 025 Ngorongoro 026 Longido 027 Arusha Rural 028 Meru 031 Rombo 032 Mwanga 033 Same 034 Moshi Rural 035 Hai 037 Siha 041 Lushoto 042 Korogwe 043 Muheza 044 Tanga 045 Pangani 046 Handeni 047 Kilindi 048 Mkinga 051 Kilosa 052 Morogoro 053 Kilombero 054 Ulanga 055 Morogoro Urban 056 Mvomero 061 Bagamoyo 062 Kibaha 063 Kisarawe 064 Mkuranga 065 Rufiji 066 Mafia 071 Kinondoni 072 Ilala 073 Temeke 081 Kilwa 082 Lindi Rural 083 Nachingwea 084 Liwale 085 Ruangwa 086 Lindi Urban 091 Mtwara Rural 092 Newala 093 Masasi 094 Tandahimba 095 Mtwara Urban 096 Nanyumbu 101 Tunduru 102 Songea Rural 103 Mbinga 104 Songea Urban 105 Namtumbo 111 Iringa Rural 112 Mufindi 113 Makete 114 Njombe 115 Ludewa 116 Iringa Urban 117 Kilolo 118 Njombe Mji 121 Chunya 122 Mbeya (R) 123 Kyela 124 Rungwe 125 Ileje 126 Mbozi 127 Mbarali 128 Mbeya Urban 131 Iramba 132 Singida Rural 133 Manyoni 134 Singida Urban 141 Nzega 142 Igunga 143 Uyui 144 Urambo 145 Sikonge 146 Tabora Urban 151 Mpanda 152 Sumbawanga Rural 153 Nkasi 154 Sumbawanga Urban 161 Kibondo 162 Kasulu 163 Kigoma Rural 164 Kigoma Urban 171 Bariadi 172 Maswa 173 Shinyanga Rural 174 Kahama 175 Bukombe 176 Meatu 177 Shinyanga Urban 178 Kishapu 181 Karagwe 182 Bukoba Rural 183 Muleba 184 Biharamulo 185 Ngara 186 Bukoba Urban 187 Missenyi 188 Chato 191 Ukerewe 192 Magu 194 Kwimba 195 Sengerema 196 Geita 197 Missungwi 198 Ilemela 201 Tarime 202 Serengeti 203 Musoma Rural 204 Bunda 205 Musoma Urban 206 Rorya 211 Babati 212 Hanang 213 Mbulu 214 Simanjiro 215 Kiteto 511 Kaskazini-A 512 Kaskazini-B 521 Kati 522 Kusini 531 Magharibi 541 Wete 542 Micheweni 551 Chake 552 Mkoani Region Region Region Region Region 01 Dodoma 02 Arusha 03 Kilimanjaro 04 Tanga 05 Morogoro 06 Pwani 07 Dar es Salaam 08 Lindi 09 Mtwara 10 Ruvuma 11 Iringa 12 Mbeya 13 Singida 14 Tabora 15 Rukwa 16 Kigoma 17 Shinyanga 18 Kagera 19 Mwanza 20 Mara 21 Manyara 51 North Unguja 52 South Unguja 53 Urban West 54 North Pemba 55 South Pemba District District District District District Ward Ward Ward Ward Ward Village Village Village Village Village Head of household number Head of household number Head of household number Head of household number Head of household number Crop Code Crop Code Crop Code Crop Code Crop Code 1 Mung Bean 2 Okra 3 Radish 4 Turmeric 5 Bitteer Aubergine 6 Sour Soup 7 Rubber Vine Fruit 8 Mangostine 9 Kothmir 11 Maize 12 Paddy 13 Sorghum 14 Bulrush Millet 15 Finger Millet 16 Wheat 17 Barley 18 Irish Potatoes 19 Yam 20 Vanila 21 Cassava 22 Sweet Potato 23 Irish potatoes 24 Yams 25 Coco Yam 26 Onion 27 Ginger 29 Garlic 30 Zukkin 31 Beans 32 Cowpeas 33 Green gram 34 Pigeon pea 35 Chick peas 36 Bambaranuts 37 Field Peas 39 Star Fruit 41 Sunflower 42 Simsim 43 Groundnut 44 Palm Oil 45 Coconut 46 Cashewnut 47 Soya Beans 48 Castor Fung 50 Cotton 51 Tobacco 52 Sisal 53 Pyrethrum 54 Coffee 55 Tea 56 Cacao 57 Rubber 58 Wattle 59 Kapok 60 Sugar Cane 61 Cardamom 62 Jute 63 Tamarin 64 Cinamon 65 Nutmeg 66 Cloves 67 Mshelisheli 68 Pomelo 69 Jack Fruit 70 Mpesheni 71 Banana 72 Avocado 73 Mango 74 Papaw 75 Pineapple 76 Orange 77 Grape fruit 78 Grape 79 Mandarine tangerine 80 Guava 81 Plums 82 Apples 83 Pears 84 Pitches 85 Lime Lemon 86 Cabbage 87 Tomatoes 88 Spinach 89 Carrot 90 Chillies 91 Amaranths 92 Pumpkins 93 Cucumber 94 Egg Plant 95 Water Mellon 96 Cauliflower 97 Durian 98 Mbilimbi 99 Rambutan Actual Planted Area (acres) Actual Planted Area (acres) Actual Planted Area (acres) Actual Planted Area (acres) Actual Planted Area (acres) Who own the most part of the land Who own the most part of the land Who own the most part of the land Who own the most part of the land Who own the most part of the land Type of Seeds Planted Type of Seeds Planted Type of Seeds Planted Type of Seeds Planted Type of Seeds Planted 1 Local Seeds 2 Improved Seeds Area Applied Area Applied Area Applied Area Applied Area Applied 1 Used for the whole crop 2 Used on 3/4 of whole crop 3 Used on 1/2 of whole crop 4 Used on 1/4 of whole crop 5 Used on less than 1/4 of whole crop Unit Unit Unit Unit Unit 1 Kilogram 2 Seedlings 3 Gram Quantity used Quantity used Quantity used Quantity used Quantity used Cost (Tshs) Cost (Tshs) Cost (Tshs) Cost (Tshs) Cost (Tshs) Irrigation Use Irrigation Use Irrigation Use Irrigation Use Irrigation Use 1 Used for the whole crop 2 Used on 3/4 of whole crop 3 Used on 1/2 of whole crop 4 Used on 1/4 of whole crop 5 Used on less than 1/4 of whole crop 6 Did not Apply Area Applied Area Applied Area Applied Area Applied Area Applied 1 Used for the whole crop 2 Used on 3/4 of whole crop 3 Used on 1/2 of whole crop 4 Used on 1/4 of whole crop 5 Used on less than 1/4 of whole crop 6 Did not Apply Type of Fertilizer Used Type of Fertilizer Used Type of Fertilizer Used Type of Fertilizer Used Type of Fertilizer Used 1 Organic 2 Inorganic Unit Unit Unit Unit Unit 1 Kilogram 2 Lita 3 Mil-lita Quantity (kg) Quantity (kg) Quantity (kg) Quantity (kg) Quantity (kg) Cost (Tshs) Cost (Tshs) Cost (Tshs) Cost (Tshs) Cost (Tshs) Area Applied Area Applied Area Applied Area Applied Area Applied 1 Used for the whole crop 2 Used on 3/4 of whole crop 3 Used on 1/2 of whole crop 4 Used on 1/4 of whole crop 5 Used on less than 1/4 of whole crop 6 Did not Apply Unit Unit Unit Unit Unit 1 Kilo 2 Lita 3 Gram 4 Mili-Lita Quantity used Quantity used Quantity used Quantity used Quantity used Cost (Tshs) Cost (Tshs) Cost (Tshs) Cost (Tshs) Cost (Tshs) Area Applied Area Applied Area Applied Area Applied Area Applied 1 Used for the whole crop 2 Used on 3/4 of whole crop 3 Used on 1/2 of whole crop 4 Used on 1/4 of whole crop 5 Used on less than 1/4 of whole crop 6 Did not Apply Unit Unit Unit Unit Unit 1 Kilo 2 Lita 3 Gram 4 Mili-Lita Quantity used Quantity used Quantity used Quantity used Quantity used Cost (Tshs) Cost (Tshs) Cost (Tshs) Cost (Tshs) Cost (Tshs) Area Applied Area Applied Area Applied Area Applied Area Applied 1 Used for the whole crop 2 Used on 3/4 of whole crop 3 Used on 1/2 of whole crop 4 Used on 1/4 of whole crop 5 Used on less than 1/4 of whole crop 6 Did not Apply Unit Unit Unit Unit Unit 1 Kilo 2 Lita 3 Gram 4 Mili-Lita Quantity used Quantity used Quantity used Quantity used Quantity used Cost (Tshs) Cost (Tshs) Cost (Tshs) Cost (Tshs) Cost (Tshs) Quantity Harvested (kgs) Quantity Harvested (kgs) Quantity Harvested (kgs) Quantity Harvested (kgs) Quantity Harvested (kgs) Quantity Stored (kg) Quantity Stored (kg) Quantity Stored (kg) Quantity Stored (kg) Quantity Stored (kg) Method of Storage Method of Storage Method of Storage Method of Storage Method of Storage 1 In locally made traditional structure 2 In Improved locally made structure 3 In modern store 4 In Sacks/open drum. 5 In airtight drum 6 Unprotected pile 7 Did Store 8 Other (Specify) Quantity sold (kgs) Quantity sold (kgs) Quantity sold (kgs) Quantity sold (kgs) Quantity sold (kgs) Kiasi kikubwa cha zao kiliuzwa wapi Kiasi kikubwa cha zao kiliuzwa wapi Kiasi kikubwa cha zao kiliuzwa wapi Kiasi kikubwa cha zao kiliuzwa wapi Kiasi kikubwa cha zao kiliuzwa wapi 1 Neghbours 2 Local Market/Trade Store 3 Secondary Market 4 Tertially Market 5 Marketing Cooperative 6 Farmers Society 7 Large Scale Farm 8 Trader at Farm 9 Contract Farmer 10 Did not Sell 11 Other Marketing problems Marketing problems Marketing problems Marketing problems Marketing problems 1 Open Market Price too low 2 No Transport 3 Transport Cost too high 4 No buyer 5 Crop Market too Far 6 Farmer Association problems 7 Cooperative problems 8 Trade Union Problems 9 Goernment Rugulatory Problems 10 Lack of Market Information 98 Other 99 Not Applicable Village Identification Village Identification Village Identification Village Identification Village Identification District Identification District Identification District Identification District Identification District Identification 011 Kondoa 012 Mpwapwa 013 Kongwa 015 Dodoma Urban 016 Bahi 017 Chamwino 021 Monduli 023 Arusha 024 Karatu 025 Ngorongoro 026 Longido 027 Arusha Rural 028 Meru 031 Rombo 032 Mwanga 033 Same 034 Moshi Rural 035 Hai 037 Siha 041 Lushoto 042 Korogwe 043 Muheza 044 Tanga 045 Pangani 046 Handeni 047 Kilindi 048 Mkinga 051 Kilosa 052 Morogoro 053 Kilombero 054 Ulanga 055 Morogoro Urban 056 Mvomero 061 Bagamoyo 062 Kibaha 063 Kisarawe 064 Mkuranga 065 Rufiji 066 Mafia 071 Kinondoni 072 Ilala 073 Temeke 081 Kilwa 082 Lindi Rural 083 Nachingwea 084 Liwale 085 Ruangwa 086 Lindi Urban 091 Mtwara Rural 092 Newala 093 Masasi 094 Tandahimba 095 Mtwara Urban 096 Nanyumbu 101 Tunduru 102 Songea Rural 103 Mbinga 104 Songea Urban 105 Namtumbo 111 Iringa Rural 112 Mufindi 113 Makete 114 Njombe 115 Ludewa 116 Iringa Urban 117 Kilolo 118 Njombe Mji 121 Chunya 122 Mbeya (R) 123 Kyela 124 Rungwe 125 Ileje 126 Mbozi 127 Mbarali 128 Mbeya Urban 131 Iramba 132 Singida Rural 133 Manyoni 134 Singida Urban 141 Nzega 142 Igunga 143 Uyui 144 Urambo 145 Sikonge 146 Tabora Urban 151 Mpanda 152 Sumbawanga Rural 153 Nkasi 154 Sumbawanga Urban 161 Kibondo 162 Kasulu 163 Kigoma Rural 164 Kigoma Urban 171 Bariadi 172 Maswa 173 Shinyanga Rural 174 Kahama 175 Bukombe 176 Meatu 177 Shinyanga Urban 178 Kishapu 181 Karagwe 182 Bukoba Rural 183 Muleba 184 Biharamulo 185 Ngara 186 Bukoba Urban 187 Missenyi 188 Chato 191 Ukerewe 192 Magu 194 Kwimba 195 Sengerema 196 Geita 197 Missungwi 198 Ilemela 201 Tarime 202 Serengeti 203 Musoma Rural 204 Bunda 205 Musoma Urban 206 Rorya 211 Babati 212 Hanang 213 Mbulu 214 Simanjiro 215 Kiteto 511 Kaskazini-A 512 Kaskazini-B 521 Kati 522 Kusini 531 Magharibi 541 Wete 542 Micheweni 551 Chake 552 Mkoani Region Region Region Region Region 01 Dodoma 02 Arusha 03 Kilimanjaro 04 Tanga 05 Morogoro 06 Pwani 07 Dar es Salaam 08 Lindi 09 Mtwara 10 Ruvuma 11 Iringa 12 Mbeya 13 Singida 14 Tabora 15 Rukwa 16 Kigoma 17 Shinyanga 18 Kagera 19 Mwanza 20 Mara 21 Manyara 51 North Unguja 52 South Unguja 53 Urban West 54 North Pemba 55 South Pemba District District District District District Ward Ward Ward Ward Ward Village Village Village Village Village Head of household number Head of household number Head of household number Head of household number Head of household number Crop Code Crop Code Crop Code Crop Code Crop Code 1 Mung Bean 2 Okra 3 Radish 4 Turmeric 5 Bitteer Aubergine 6 Sour Soup 7 Rubber Vine Fruit 8 Mangostine 9 Kothmir 11 Maize 12 Paddy 13 Sorghum 14 Bulrush Millet 15 Finger Millet 16 Wheat 17 Barley 18 Irish Potatoes 19 Yam 20 Vanila 21 Cassava 22 Sweet Potato 23 Irish potatoes 24 Yams 25 Coco Yam 26 Onion 27 Ginger 29 Garlic 30 Zukkin 31 Beans 32 Cowpeas 33 Green gram 34 Pigeon pea 35 Chick peas 36 Bambaranuts 37 Field Peas 39 Star Fruit 41 Sunflower 42 Simsim 43 Groundnut 44 Palm Oil 45 Coconut 46 Cashewnut 47 Soya Beans 48 Castor Fung 50 Cotton 51 Tobacco 52 Sisal 53 Pyrethrum 54 Coffee 55 Tea 56 Cacao 57 Rubber 58 Wattle 59 Kapok 60 Sugar Cane 61 Cardamom 62 Jute 63 Tamarin 64 Cinamon 65 Nutmeg 66 Cloves 67 Mshelisheli 68 Pomelo 69 Jack Fruit 70 Mpesheni 71 Banana 72 Avocado 73 Mango 74 Papaw 75 Pineapple 76 Orange 77 Grape fruit 78 Grape 79 Mandarine tangerine 80 Guava 81 Plums 82 Apples 83 Pears 84 Pitches 85 Lime Lemon 86 Cabbage 87 Tomatoes 88 Spinach 89 Carrot 90 Chillies 91 Amaranths 92 Pumpkins 93 Cucumber 94 Egg Plant 95 Water Mellon 96 Cauliflower 97 Durian 98 Mbilimbi 99 Rambutan Actual Planted Area (acres) Actual Planted Area (acres) Actual Planted Area (acres) Actual Planted Area (acres) Actual Planted Area (acres) Who own the most part of the land Who own the most part of the land Who own the most part of the land Who own the most part of the land Who own the most part of the land Type of Seeds Planted Type of Seeds Planted Type of Seeds Planted Type of Seeds Planted Type of Seeds Planted 1 Local Seeds 2 Improved Seeds Area applied Area applied Area applied Area applied Area applied 1 Used for the whole crop 2 Used on 3/4 of whole crop 3 Used on 1/2 of whole crop 4 Used on 1/4 of whole crop 5 Used on less than 1/4 of whole crop Unit Unit Unit Unit Unit 1 Kilogram 2 Seedlings 3 Gram Quantity used Quantity used Quantity used Quantity used Quantity used Cost (Tshs) Cost (Tshs) Cost (Tshs) Cost (Tshs) Cost (Tshs) Irrigation Use Irrigation Use Irrigation Use Irrigation Use Irrigation Use 1 Used for the whole crop 2 Used on 3/4 of whole crop 3 Used on 1/2 of whole crop 4 Used on 1/4 of whole crop 5 Used on less than 1/4 of whole crop 6 Did not Apply Area Applied Area Applied Area Applied Area Applied Area Applied 1 Used for the whole crop 2 Used on 3/4 of whole crop 3 Used on 1/2 of whole crop 4 Used on 1/4 of whole crop 5 Used on less than 1/4 of whole crop 6 Did not Apply Type of Fertilizer Used Type of Fertilizer Used Type of Fertilizer Used Type of Fertilizer Used Type of Fertilizer Used 1 Organic 2 Inorganic Unit Unit Unit Unit Unit 1 Kilogram 2 Lita 3 Mil-lita Quantity (kg) Quantity (kg) Quantity (kg) Quantity (kg) Quantity (kg) Cost (Tshs) Cost (Tshs) Cost (Tshs) Cost (Tshs) Cost (Tshs) Area Applied Area Applied Area Applied Area Applied Area Applied 1 Used for the whole crop 2 Used on 3/4 of whole crop 3 Used on 1/2 of whole crop 4 Used on 1/4 of whole crop 5 Used on less than 1/4 of whole crop 6 Did not Apply Unit Unit Unit Unit Unit 1 Kilo 2 Lita 3 Gram 4 Mili-Lita Quantity used Quantity used Quantity used Quantity used Quantity used Cost (Tshs) Cost (Tshs) Cost (Tshs) Cost (Tshs) Cost (Tshs) Area Applied Area Applied Area Applied Area Applied Area Applied 1 Used for the whole crop 2 Used on 3/4 of whole crop 3 Used on 1/2 of whole crop 4 Used on 1/4 of whole crop 5 Used on less than 1/4 of whole crop 6 Did not Apply Unit Unit Unit Unit Unit 1 Kilo 2 Lita 3 Gram 4 Mili-Lita Quantity used Quantity used Quantity used Quantity used Quantity used Cost (Tshs) Cost (Tshs) Cost (Tshs) Cost (Tshs) Cost (Tshs) Area Applied Area Applied Area Applied Area Applied Area Applied 1 Used for the whole crop 2 Used on 3/4 of whole crop 3 Used on 1/2 of whole crop 4 Used on 1/4 of whole crop 5 Used on less than 1/4 of whole crop 6 Did not Apply Unit Unit Unit Unit Unit 1 Kilo 2 Lita 3 Gram 4 Mili-Lita Quantity used Quantity used Quantity used Quantity used Quantity used Cost (Tshs) Cost (Tshs) Cost (Tshs) Cost (Tshs) Cost (Tshs) Quantity Harvested (kgs) Quantity Harvested (kgs) Quantity Harvested (kgs) Quantity Harvested (kgs) Quantity Harvested (kgs) Quantity stored (kg) Quantity stored (kg) Quantity stored (kg) Quantity stored (kg) Quantity stored (kg) Method of Storage Method of Storage Method of Storage Method of Storage Method of Storage 1 In locally made traditional structure 2 In Improved locally made structure 3 In modern store 4 In Sacks/open drum. 5 In airtight drum 6 Unprotected pile 7 Did Store 8 Other (Specify) Quantity sold (kgs) Quantity sold (kgs) Quantity sold (kgs) Quantity sold (kgs) Quantity sold (kgs) Kiasi kikubwa cha zao kiliuzwa wapi Kiasi kikubwa cha zao kiliuzwa wapi Kiasi kikubwa cha zao kiliuzwa wapi Kiasi kikubwa cha zao kiliuzwa wapi Kiasi kikubwa cha zao kiliuzwa wapi 1 Neghbours 2 Local Market/Trade Store 3 Secondary Market 4 Tertially Market 5 Marketing Cooperative 6 Farmers Society 7 Large Scale Farm 8 Trader at Farm 9 Contract Farmer 10 Did not Sell 11 Other Marketing problems Marketing problems Marketing problems Marketing problems Marketing problems 1 Open Market Price too low 2 No Transport 3 Transport Cost too high 4 No buyer 5 Crop Market too Far 6 Farmer Association problems 7 Cooperative problems 8 Trade Union Problems 9 Goernment Rugulatory Problems 10 Lack of Market Information 98 Other 99 Not Applicable Village Identification Village Identification Village Identification Village Identification Village Identification District Identification District Identification District Identification District Identification District Identification 011 Kondoa 012 Mpwapwa 013 Kongwa 015 Dodoma Urban 016 Bahi 017 Chamwino 021 Monduli 023 Arusha 024 Karatu 025 Ngorongoro 026 Longido 027 Arusha Rural 028 Meru 031 Rombo 032 Mwanga 033 Same 034 Moshi Rural 035 Hai 037 Siha 041 Lushoto 042 Korogwe 043 Muheza 044 Tanga 045 Pangani 046 Handeni 047 Kilindi 048 Mkinga 051 Kilosa 052 Morogoro 053 Kilombero 054 Ulanga 055 Morogoro Urban 056 Mvomero 061 Bagamoyo 062 Kibaha 063 Kisarawe 064 Mkuranga 065 Rufiji 066 Mafia 071 Kinondoni 072 Ilala 073 Temeke 081 Kilwa 082 Lindi Rural 083 Nachingwea 084 Liwale 085 Ruangwa 086 Lindi Urban 091 Mtwara Rural 092 Newala 093 Masasi 094 Tandahimba 095 Mtwara Urban 096 Nanyumbu 101 Tunduru 102 Songea Rural 103 Mbinga 104 Songea Urban 105 Namtumbo 111 Iringa Rural 112 Mufindi 113 Makete 114 Njombe 115 Ludewa 116 Iringa Urban 117 Kilolo 118 Njombe Mji 121 Chunya 122 Mbeya (R) 123 Kyela 124 Rungwe 125 Ileje 126 Mbozi 127 Mbarali 128 Mbeya Urban 131 Iramba 132 Singida Rural 133 Manyoni 134 Singida Urban 141 Nzega 142 Igunga 143 Uyui 144 Urambo 145 Sikonge 146 Tabora Urban 151 Mpanda 152 Sumbawanga Rural 153 Nkasi 154 Sumbawanga Urban 161 Kibondo 162 Kasulu 163 Kigoma Rural 164 Kigoma Urban 171 Bariadi 172 Maswa 173 Shinyanga Rural 174 Kahama 175 Bukombe 176 Meatu 177 Shinyanga Urban 178 Kishapu 181 Karagwe 182 Bukoba Rural 183 Muleba 184 Biharamulo 185 Ngara 186 Bukoba Urban 187 Missenyi 188 Chato 191 Ukerewe 192 Magu 194 Kwimba 195 Sengerema 196 Geita 197 Missungwi 198 Ilemela 201 Tarime 202 Serengeti 203 Musoma Rural 204 Bunda 205 Musoma Urban 206 Rorya 211 Babati 212 Hanang 213 Mbulu 214 Simanjiro 215 Kiteto 511 Kaskazini-A 512 Kaskazini-B 521 Kati 522 Kusini 531 Magharibi 541 Wete 542 Micheweni 551 Chake 552 Mkoani Region Region Region Region Region 01 Dodoma 02 Arusha 03 Kilimanjaro 04 Tanga 05 Morogoro 06 Pwani 07 Dar es Salaam 08 Lindi 09 Mtwara 10 Ruvuma 11 Iringa 12 Mbeya 13 Singida 14 Tabora 15 Rukwa 16 Kigoma 17 Shinyanga 18 Kagera 19 Mwanza 20 Mara 21 Manyara 51 North Unguja 52 South Unguja 53 Urban West 54 North Pemba 55 South Pemba District District District District District Ward Ward Ward Ward Ward Village Village Village Village Village Head of household number Head of household number Head of household number Head of household number Head of household number Permanent Crop /Fruit Tree Code Permanent Crop /Fruit Tree Code Permanent Crop /Fruit Tree Code Permanent Crop /Fruit Tree Code Permanent Crop /Fruit Tree Code 1 Mung Bean 2 Okra 3 Radish 4 Turmeric 5 Bitteer Aubergine 6 Sour Soup 7 Rubber Vine Fruit 8 Mangostine 9 Kothmir 11 Maize 12 Paddy 13 Sorghum 14 Bulrush Millet 15 Finger Millet 16 Wheat 17 Barley 18 Irish Potatoes 19 Yam 20 Vanila 21 Cassava 22 Sweet Potato 23 Irish potatoes 24 Yams 25 Coco Yam 26 Onion 27 Ginger 29 Garlic 30 Zukkin 31 Beans 32 Cowpeas 33 Green gram 34 Pigeon pea 35 Chick peas 36 Bambaranuts 37 Field Peas 39 Star Fruit 41 Sunflower 42 Simsim 43 Groundnut 44 Palm Oil 45 Coconut 46 Cashewnut 47 Soya Beans 48 Castor Fung 50 Cotton 51 Tobacco 52 Sisal 53 Pyrethrum 54 Coffee 55 Tea 56 Cacao 57 Rubber 58 Wattle 59 Kapok 60 Sugar Cane 61 Cardamom 62 Jute 63 Tamarin 64 Cinamon 65 Nutmeg 66 Cloves 67 Mshelisheli 68 Pomelo 69 Jack Fruit 70 Mpesheni 71 Banana 72 Avocado 73 Mango 74 Papaw 75 Pineapple 76 Orange 77 Grape fruit 78 Grape 79 Mandarine tangerine 80 Guava 81 Plums 82 Apples 83 Pears 84 Pitches 85 Lime Lemon 86 Cabbage 87 Tomatoes 88 Spinach 89 Carrot 90 Chillies 91 Amaranths 92 Pumpkins 93 Cucumber 94 Egg Plant 95 Water Mellon 96 Cauliflower 97 Durian 98 Mbilimbi 99 Rambutan Area of of Plants/Trees/ Bushes in Mono Crop (acres) Area of of Plants/Trees/ Bushes in Mono Crop (acres) Area of of Plants/Trees/ Bushes in Mono Crop (acres) Area of of Plants/Trees/ Bushes in Mono Crop (acres) Area of of Plants/Trees/ Bushes in Mono Crop (acres) Area Covered by Permanent Crop in Mixed Crop (acres) Area Covered by Permanent Crop in Mixed Crop (acres) Area Covered by Permanent Crop in Mixed Crop (acres) Area Covered by Permanent Crop in Mixed Crop (acres) Area Covered by Permanent Crop in Mixed Crop (acres) Number of Plants/Trees/Bushes in Mixed Crop Number of Plants/Trees/Bushes in Mixed Crop Number of Plants/Trees/Bushes in Mixed Crop Number of Plants/Trees/Bushes in Mixed Crop Number of Plants/Trees/Bushes in Mixed Crop Who own the most part of the land Who own the most part of the land Who own the most part of the land Who own the most part of the land Who own the most part of the land Type of Seeds Planted Type of Seeds Planted Type of Seeds Planted Type of Seeds Planted Type of Seeds Planted 1 Local Seeds 2 Improved Seeds Area applied Area applied Area applied Area applied Area applied 1 Used for the whole crop 2 Used on 3/4 of whole crop 3 Used on 1/2 of whole crop 4 Used on 1/4 of whole crop 5 Used on less than 1/4 of whole crop Unit Unit Unit Unit Unit 1 Kilogram 2 Seedlings 3 Gram Quantity used Quantity used Quantity used Quantity used Quantity used Cost (Tshs) Cost (Tshs) Cost (Tshs) Cost (Tshs) Cost (Tshs) Irrigation Use Irrigation Use Irrigation Use Irrigation Use Irrigation Use 1 Used for the whole crop 2 Used on 3/4 of whole crop 3 Used on 1/2 of whole crop 4 Used on 1/4 of whole crop 5 Used on less than 1/4 of whole crop 6 Did not Apply Area Applied Area Applied Area Applied Area Applied Area Applied 1 Used for the whole crop 2 Used on 3/4 of whole crop 3 Used on 1/2 of whole crop 4 Used on 1/4 of whole crop 5 Used on less than 1/4 of whole crop 6 Did not Apply Type of Fertilizer Used Type of Fertilizer Used Type of Fertilizer Used Type of Fertilizer Used Type of Fertilizer Used 1 Organic 2 Inorganic Quantity (kg) Quantity (kg) Quantity (kg) Quantity (kg) Quantity (kg) Cost (Tshs) Cost (Tshs) Cost (Tshs) Cost (Tshs) Cost (Tshs) Area Applied Area Applied Area Applied Area Applied Area Applied 1 Used for the whole crop 2 Used on 3/4 of whole crop 3 Used on 1/2 of whole crop 4 Used on 1/4 of whole crop 5 Used on less than 1/4 of whole crop 6 Did not Apply Unit Unit Unit Unit Unit 1 Kilo 2 Lita 3 Gram 4 Mili-Lita Quantity used Quantity used Quantity used Quantity used Quantity used Cost (Tshs) Cost (Tshs) Cost (Tshs) Cost (Tshs) Cost (Tshs) Area Applied Area Applied Area Applied Area Applied Area Applied 1 Used for the whole crop 2 Used on 3/4 of whole crop 3 Used on 1/2 of whole crop 4 Used on 1/4 of whole crop 5 Used on less than 1/4 of whole crop 6 Did not Apply Unit Unit Unit Unit Unit 1 Kilo 2 Lita 3 Gram 4 Mili-Lita Quantity used Quantity used Quantity used Quantity used Quantity used Cost (Tshs) Cost (Tshs) Cost (Tshs) Cost (Tshs) Cost (Tshs) Area Applied Area Applied Area Applied Area Applied Area Applied 1 Used for the whole crop 2 Used on 3/4 of whole crop 3 Used on 1/2 of whole crop 4 Used on 1/4 of whole crop 5 Used on less than 1/4 of whole crop 6 Did not Apply Unit Unit Unit Unit Unit 1 Kilo 2 Lita 3 Gram 4 Mili-Lita Quantity used Quantity used Quantity used Quantity used Quantity used Cost (Tshs) Cost (Tshs) Cost (Tshs) Cost (Tshs) Cost (Tshs) Area Harvested Area Harvested Area Harvested Area Harvested Area Harvested Number of Mature Trees Number of Mature Trees Number of Mature Trees Number of Mature Trees Number of Mature Trees Quantity Harvested (kgs) Quantity Harvested (kgs) Quantity Harvested (kgs) Quantity Harvested (kgs) Quantity Harvested (kgs) Quantity Stored (kg) Quantity Stored (kg) Quantity Stored (kg) Quantity Stored (kg) Quantity Stored (kg) Method of Storage Method of Storage Method of Storage Method of Storage Method of Storage 1 In locally made traditional structure 2 In Improved locally made structure 3 In modern store 4 In Sacks/open drum. 5 In airtight drum 6 Unprotected pile 7 Did Store 8 Other (Specify) Quantity sold (kgs) Quantity sold (kgs) Quantity sold (kgs) Quantity sold (kgs) Quantity sold (kgs) Marketing problems Marketing problems Marketing problems Marketing problems Marketing problems 1 Open Market Price too low 2 No Transport 3 Transport Cost too high 4 No buyer 5 Crop Market too Far 6 Farmer Association problems 7 Cooperative problems 8 Trade Union Problems 9 Goernment Rugulatory Problems 10 Lack of Market Information 98 Other 99 Not Applicable Village Identification Village Identification Village Identification Village Identification Village Identification District Identification District Identification District Identification District Identification District Identification 011 Kondoa 012 Mpwapwa 013 Kongwa 015 Dodoma Urban 016 Bahi 017 Chamwino 021 Monduli 023 Arusha 024 Karatu 025 Ngorongoro 026 Longido 027 Arusha Rural 028 Meru 031 Rombo 032 Mwanga 033 Same 034 Moshi Rural 035 Hai 037 Siha 041 Lushoto 042 Korogwe 043 Muheza 044 Tanga 045 Pangani 046 Handeni 047 Kilindi 048 Mkinga 051 Kilosa 052 Morogoro 053 Kilombero 054 Ulanga 055 Morogoro Urban 056 Mvomero 061 Bagamoyo 062 Kibaha 063 Kisarawe 064 Mkuranga 065 Rufiji 066 Mafia 071 Kinondoni 072 Ilala 073 Temeke 081 Kilwa 082 Lindi Rural 083 Nachingwea 084 Liwale 085 Ruangwa 086 Lindi Urban 091 Mtwara Rural 092 Newala 093 Masasi 094 Tandahimba 095 Mtwara Urban 096 Nanyumbu 101 Tunduru 102 Songea Rural 103 Mbinga 104 Songea Urban 105 Namtumbo 111 Iringa Rural 112 Mufindi 113 Makete 114 Njombe 115 Ludewa 116 Iringa Urban 117 Kilolo 118 Njombe Mji 121 Chunya 122 Mbeya (R) 123 Kyela 124 Rungwe 125 Ileje 126 Mbozi 127 Mbarali 128 Mbeya Urban 131 Iramba 132 Singida Rural 133 Manyoni 134 Singida Urban 141 Nzega 142 Igunga 143 Uyui 144 Urambo 145 Sikonge 146 Tabora Urban 151 Mpanda 152 Sumbawanga Rural 153 Nkasi 154 Sumbawanga Urban 161 Kibondo 162 Kasulu 163 Kigoma Rural 164 Kigoma Urban 171 Bariadi 172 Maswa 173 Shinyanga Rural 174 Kahama 175 Bukombe 176 Meatu 177 Shinyanga Urban 178 Kishapu 181 Karagwe 182 Bukoba Rural 183 Muleba 184 Biharamulo 185 Ngara 186 Bukoba Urban 187 Missenyi 188 Chato 191 Ukerewe 192 Magu 194 Kwimba 195 Sengerema 196 Geita 197 Missungwi 198 Ilemela 201 Tarime 202 Serengeti 203 Musoma Rural 204 Bunda 205 Musoma Urban 206 Rorya 211 Babati 212 Hanang 213 Mbulu 214 Simanjiro 215 Kiteto 511 Kaskazini-A 512 Kaskazini-B 521 Kati 522 Kusini 531 Magharibi 541 Wete 542 Micheweni 551 Chake 552 Mkoani Region Region Region Region Region 01 Dodoma 02 Arusha 03 Kilimanjaro 04 Tanga 05 Morogoro 06 Pwani 07 Dar es Salaam 08 Lindi 09 Mtwara 10 Ruvuma 11 Iringa 12 Mbeya 13 Singida 14 Tabora 15 Rukwa 16 Kigoma 17 Shinyanga 18 Kagera 19 Mwanza 20 Mara 21 Manyara 51 North Unguja 52 South Unguja 53 Urban West 54 North Pemba 55 South Pemba District District District District District Ward Ward Ward Ward Ward Village Village Village Village Village Household number Household number Household number Household number Household number Equipment/Asset Name Equipment/Asset Name Equipment/Asset Name Equipment/Asset Name Equipment/Asset Name 1 Panga 2 Hand Hoe 3 Hand Sprayer 4 Grater, Chiper,Oil Press, Oil Mill 5 Ox Plough 6 Ox Seed Planter 7 Ox Cart 8 Tractor 9 Tractor Plough 10 Tractor Harrow 11 Oxen 12 Bulls 13 Cow 14 Donkeys 15 Shellers/threshers 16 Power Tiller 17 Ox Ridger Used Used Used Used Used 1 Yes 2 No Number owned Number owned Number owned Number owned Number owned Village Identification Village Identification Village Identification Village Identification Village Identification District Identification District Identification District Identification District Identification District Identification 011 Kondoa 012 Mpwapwa 013 Kongwa 015 Dodoma Urban 016 Bahi 017 Chamwino 021 Monduli 023 Arusha 024 Karatu 025 Ngorongoro 026 Longido 027 Arusha Rural 028 Meru 031 Rombo 032 Mwanga 033 Same 034 Moshi Rural 035 Hai 037 Siha 041 Lushoto 042 Korogwe 043 Muheza 044 Tanga 045 Pangani 046 Handeni 047 Kilindi 048 Mkinga 051 Kilosa 052 Morogoro 053 Kilombero 054 Ulanga 055 Morogoro Urban 056 Mvomero 061 Bagamoyo 062 Kibaha 063 Kisarawe 064 Mkuranga 065 Rufiji 066 Mafia 071 Kinondoni 072 Ilala 073 Temeke 081 Kilwa 082 Lindi Rural 083 Nachingwea 084 Liwale 085 Ruangwa 086 Lindi Urban 091 Mtwara Rural 092 Newala 093 Masasi 094 Tandahimba 095 Mtwara Urban 096 Nanyumbu 101 Tunduru 102 Songea Rural 103 Mbinga 104 Songea Urban 105 Namtumbo 111 Iringa Rural 112 Mufindi 113 Makete 114 Njombe 115 Ludewa 116 Iringa Urban 117 Kilolo 118 Njombe Mji 121 Chunya 122 Mbeya (R) 123 Kyela 124 Rungwe 125 Ileje 126 Mbozi 127 Mbarali 128 Mbeya Urban 131 Iramba 132 Singida Rural 133 Manyoni 134 Singida Urban 141 Nzega 142 Igunga 143 Uyui 144 Urambo 145 Sikonge 146 Tabora Urban 151 Mpanda 152 Sumbawanga Rural 153 Nkasi 154 Sumbawanga Urban 161 Kibondo 162 Kasulu 163 Kigoma Rural 164 Kigoma Urban 171 Bariadi 172 Maswa 173 Shinyanga Rural 174 Kahama 175 Bukombe 176 Meatu 177 Shinyanga Urban 178 Kishapu 181 Karagwe 182 Bukoba Rural 183 Muleba 184 Biharamulo 185 Ngara 186 Bukoba Urban 187 Missenyi 188 Chato 191 Ukerewe 192 Magu 194 Kwimba 195 Sengerema 196 Geita 197 Missungwi 198 Ilemela 201 Tarime 202 Serengeti 203 Musoma Rural 204 Bunda 205 Musoma Urban 206 Rorya 211 Babati 212 Hanang 213 Mbulu 214 Simanjiro 215 Kiteto 511 Kaskazini-A 512 Kaskazini-B 521 Kati 522 Kusini 531 Magharibi 541 Wete 542 Micheweni 551 Chake 552 Mkoani Region Region Region Region Region 01 Dodoma 02 Arusha 03 Kilimanjaro 04 Tanga 05 Morogoro 06 Pwani 07 Dar es Salaam 08 Lindi 09 Mtwara 10 Ruvuma 11 Iringa 12 Mbeya 13 Singida 14 Tabora 15 Rukwa 16 Kigoma 17 Shinyanga 18 Kagera 19 Mwanza 20 Mara 21 Manyara 51 North Unguja 52 South Unguja 53 Urban West 54 North Pemba 55 South Pemba District District District District District Ward Ward Ward Ward Ward Village Village Village Village Village Household number Household number Household number Household number Household number Type of Draft Animal Type of Draft Animal Type of Draft Animal Type of Draft Animal Type of Draft Animal 1 “Oxen” 2 “Bulls” 3 “Cows” 4 “Donkeys” 5 “Tractor” 6 “Power Tiller” Number owned Number owned Number owned Number owned Number owned Number used Number used Number used Number used Number used Area Cultivated (Acres) Area Cultivated (Acres) Area Cultivated (Acres) Area Cultivated (Acres) Area Cultivated (Acres) Village Identification Village Identification Village Identification Village Identification Village Identification District Identification District Identification District Identification District Identification District Identification 011 Kondoa 012 Mpwapwa 013 Kongwa 015 Dodoma Urban 016 Bahi 017 Chamwino 021 Monduli 023 Arusha 024 Karatu 025 Ngorongoro 026 Longido 027 Arusha Rural 028 Meru 031 Rombo 032 Mwanga 033 Same 034 Moshi Rural 035 Hai 037 Siha 041 Lushoto 042 Korogwe 043 Muheza 044 Tanga 045 Pangani 046 Handeni 047 Kilindi 048 Mkinga 051 Kilosa 052 Morogoro 053 Kilombero 054 Ulanga 055 Morogoro Urban 056 Mvomero 061 Bagamoyo 062 Kibaha 063 Kisarawe 064 Mkuranga 065 Rufiji 066 Mafia 071 Kinondoni 072 Ilala 073 Temeke 081 Kilwa 082 Lindi Rural 083 Nachingwea 084 Liwale 085 Ruangwa 086 Lindi Urban 091 Mtwara Rural 092 Newala 093 Masasi 094 Tandahimba 095 Mtwara Urban 096 Nanyumbu 101 Tunduru 102 Songea Rural 103 Mbinga 104 Songea Urban 105 Namtumbo 111 Iringa Rural 112 Mufindi 113 Makete 114 Njombe 115 Ludewa 116 Iringa Urban 117 Kilolo 118 Njombe Mji 121 Chunya 122 Mbeya (R) 123 Kyela 124 Rungwe 125 Ileje 126 Mbozi 127 Mbarali 128 Mbeya Urban 131 Iramba 132 Singida Rural 133 Manyoni 134 Singida Urban 141 Nzega 142 Igunga 143 Uyui 144 Urambo 145 Sikonge 146 Tabora Urban 151 Mpanda 152 Sumbawanga Rural 153 Nkasi 154 Sumbawanga Urban 161 Kibondo 162 Kasulu 163 Kigoma Rural 164 Kigoma Urban 171 Bariadi 172 Maswa 173 Shinyanga Rural 174 Kahama 175 Bukombe 176 Meatu 177 Shinyanga Urban 178 Kishapu 181 Karagwe 182 Bukoba Rural 183 Muleba 184 Biharamulo 185 Ngara 186 Bukoba Urban 187 Missenyi 188 Chato 191 Ukerewe 192 Magu 194 Kwimba 195 Sengerema 196 Geita 197 Missungwi 198 Ilemela 201 Tarime 202 Serengeti 203 Musoma Rural 204 Bunda 205 Musoma Urban 206 Rorya 211 Babati 212 Hanang 213 Mbulu 214 Simanjiro 215 Kiteto 511 Kaskazini-A 512 Kaskazini-B 521 Kati 522 Kusini 531 Magharibi 541 Wete 542 Micheweni 551 Chake 552 Mkoani Region Region Region Region Region 01 Dodoma 02 Arusha 03 Kilimanjaro 04 Tanga 05 Morogoro 06 Pwani 07 Dar es Salaam 08 Lindi 09 Mtwara 10 Ruvuma 11 Iringa 12 Mbeya 13 Singida 14 Tabora 15 Rukwa 16 Kigoma 17 Shinyanga 18 Kagera 19 Mwanza 20 Mara 21 Manyara 51 North Unguja 52 South Unguja 53 Urban West 54 North Pemba 55 South Pemba District District District District District Ward Ward Ward Ward Ward Village Village Village Village Village Head of household number Head of household number Head of household number Head of household number Head of household number Type of organic Fertiliser Type of organic Fertiliser Type of organic Fertiliser Type of organic Fertiliser Type of organic Fertiliser 1 Farm Yard Manure (FYM) 2 Compost Manure Used Used Used Used Used Unit Unit Unit Unit Unit Quantity used (kg) Quantity used (kg) Quantity used (kg) Quantity used (kg) Quantity used (kg) Area applied (acres) Area applied (acres) Area applied (acres) Area applied (acres) Area applied (acres) Village Identification Village Identification Village Identification Village Identification Village Identification District Identification District Identification District Identification District Identification District Identification 011 Kondoa 012 Mpwapwa 013 Kongwa 015 Dodoma Urban 016 Bahi 017 Chamwino 021 Monduli 023 Arusha 024 Karatu 025 Ngorongoro 026 Longido 027 Arusha Rural 028 Meru 031 Rombo 032 Mwanga 033 Same 034 Moshi Rural 035 Hai 037 Siha 041 Lushoto 042 Korogwe 043 Muheza 044 Tanga 045 Pangani 046 Handeni 047 Kilindi 048 Mkinga 051 Kilosa 052 Morogoro 053 Kilombero 054 Ulanga 055 Morogoro Urban 056 Mvomero 061 Bagamoyo 062 Kibaha 063 Kisarawe 064 Mkuranga 065 Rufiji 066 Mafia 071 Kinondoni 072 Ilala 073 Temeke 081 Kilwa 082 Lindi Rural 083 Nachingwea 084 Liwale 085 Ruangwa 086 Lindi Urban 091 Mtwara Rural 092 Newala 093 Masasi 094 Tandahimba 095 Mtwara Urban 096 Nanyumbu 101 Tunduru 102 Songea Rural 103 Mbinga 104 Songea Urban 105 Namtumbo 111 Iringa Rural 112 Mufindi 113 Makete 114 Njombe 115 Ludewa 116 Iringa Urban 117 Kilolo 118 Njombe Mji 121 Chunya 122 Mbeya (R) 123 Kyela 124 Rungwe 125 Ileje 126 Mbozi 127 Mbarali 128 Mbeya Urban 131 Iramba 132 Singida Rural 133 Manyoni 134 Singida Urban 141 Nzega 142 Igunga 143 Uyui 144 Urambo 145 Sikonge 146 Tabora Urban 151 Mpanda 152 Sumbawanga Rural 153 Nkasi 154 Sumbawanga Urban 161 Kibondo 162 Kasulu 163 Kigoma Rural 164 Kigoma Urban 171 Bariadi 172 Maswa 173 Shinyanga Rural 174 Kahama 175 Bukombe 176 Meatu 177 Shinyanga Urban 178 Kishapu 181 Karagwe 182 Bukoba Rural 183 Muleba 184 Biharamulo 185 Ngara 186 Bukoba Urban 187 Missenyi 188 Chato 191 Ukerewe 192 Magu 194 Kwimba 195 Sengerema 196 Geita 197 Missungwi 198 Ilemela 201 Tarime 202 Serengeti 203 Musoma Rural 204 Bunda 205 Musoma Urban 206 Rorya 211 Babati 212 Hanang 213 Mbulu 214 Simanjiro 215 Kiteto 511 Kaskazini-A 512 Kaskazini-B 521 Kati 522 Kusini 531 Magharibi 541 Wete 542 Micheweni 551 Chake 552 Mkoani Region Region Region Region Region 01 Dodoma 02 Arusha 03 Kilimanjaro 04 Tanga 05 Morogoro 06 Pwani 07 Dar es Salaam 08 Lindi 09 Mtwara 10 Ruvuma 11 Iringa 12 Mbeya 13 Singida 14 Tabora 15 Rukwa 16 Kigoma 17 Shinyanga 18 Kagera 19 Mwanza 20 Mara 21 Manyara 51 North Unguja 52 South Unguja 53 Urban West 54 North Pemba 55 South Pemba District District District District District Ward Ward Ward Ward Ward Village Village Village Village Village Household number Household number Household number Household number Household number Input name Input name Input name Input name Input name 1 Chemical Fertiliser 2 Farm Yard Manure 3 Compost 4 Insecticide/fungicide 5 Herbicide 6 Improved Seeds Used Used Used Used Used 1 Yes 2 No Source of input Source of input Source of input Source of input Source of input 1 Government 2 Local farmers group 3 Local market/Trade Store 4 Secondary Market 5 Development project 6 Crop buyers 7 Large scale farm 8 Locally produced by household 9 Neighbour 10 Cooperative 98 Other (specify) 99 Not applicable Distance to Source Distance to Source Distance to Source Distance to Source Distance to Source 1 Less than 1 Km 2 Between 1 and less than 3 km 3 between 3 and less than10 km. 4 Between 10 and less than 20 km 5 20 km and above 9 not applicable Village Identification Village Identification Village Identification Village Identification Village Identification District Identification District Identification District Identification District Identification District Identification 011 Kondoa 012 Mpwapwa 013 Kongwa 015 Dodoma Urban 016 Bahi 017 Chamwino 021 Monduli 023 Arusha 024 Karatu 025 Ngorongoro 026 Longido 027 Arusha Rural 028 Meru 031 Rombo 032 Mwanga 033 Same 034 Moshi Rural 035 Hai 037 Siha 041 Lushoto 042 Korogwe 043 Muheza 044 Tanga 045 Pangani 046 Handeni 047 Kilindi 048 Mkinga 051 Kilosa 052 Morogoro 053 Kilombero 054 Ulanga 055 Morogoro Urban 056 Mvomero 061 Bagamoyo 062 Kibaha 063 Kisarawe 064 Mkuranga 065 Rufiji 066 Mafia 071 Kinondoni 072 Ilala 073 Temeke 081 Kilwa 082 Lindi Rural 083 Nachingwea 084 Liwale 085 Ruangwa 086 Lindi Urban 091 Mtwara Rural 092 Newala 093 Masasi 094 Tandahimba 095 Mtwara Urban 096 Nanyumbu 101 Tunduru 102 Songea Rural 103 Mbinga 104 Songea Urban 105 Namtumbo 111 Iringa Rural 112 Mufindi 113 Makete 114 Njombe 115 Ludewa 116 Iringa Urban 117 Kilolo 118 Njombe Mji 121 Chunya 122 Mbeya (R) 123 Kyela 124 Rungwe 125 Ileje 126 Mbozi 127 Mbarali 128 Mbeya Urban 131 Iramba 132 Singida Rural 133 Manyoni 134 Singida Urban 141 Nzega 142 Igunga 143 Uyui 144 Urambo 145 Sikonge 146 Tabora Urban 151 Mpanda 152 Sumbawanga Rural 153 Nkasi 154 Sumbawanga Urban 161 Kibondo 162 Kasulu 163 Kigoma Rural 164 Kigoma Urban 171 Bariadi 172 Maswa 173 Shinyanga Rural 174 Kahama 175 Bukombe 176 Meatu 177 Shinyanga Urban 178 Kishapu 181 Karagwe 182 Bukoba Rural 183 Muleba 184 Biharamulo 185 Ngara 186 Bukoba Urban 187 Missenyi 188 Chato 191 Ukerewe 192 Magu 194 Kwimba 195 Sengerema 196 Geita 197 Missungwi 198 Ilemela 201 Tarime 202 Serengeti 203 Musoma Rural 204 Bunda 205 Musoma Urban 206 Rorya 211 Babati 212 Hanang 213 Mbulu 214 Simanjiro 215 Kiteto 511 Kaskazini-A 512 Kaskazini-B 521 Kati 522 Kusini 531 Magharibi 541 Wete 542 Micheweni 551 Chake 552 Mkoani Region Region Region Region Region 01 Dodoma 02 Arusha 03 Kilimanjaro 04 Tanga 05 Morogoro 06 Pwani 07 Dar es Salaam 08 Lindi 09 Mtwara 10 Ruvuma 11 Iringa 12 Mbeya 13 Singida 14 Tabora 15 Rukwa 16 Kigoma 17 Shinyanga 18 Kagera 19 Mwanza 20 Mara 21 Manyara 51 North Unguja 52 South Unguja 53 Urban West 54 North Pemba 55 South Pemba District District District District District Ward Ward Ward Ward Ward Village Village Village Village Village Household number Household number Household number Household number Household number Type of erosion control/water harvesting structure Type of erosion control/water harvesting structure Type of erosion control/water harvesting structure Type of erosion control/water harvesting structure Type of erosion control/water harvesting structure 1 Terraces 2 Erosion control bunds 3 Gabions/Sandbags 4 Vetiver Grass 5 Tree belts 6 Water harvesting bunds 7 Drainage ditches 8 Others Number of structures Number of structures Number of structures Number of structures Number of structures Year of construction Year of construction Year of construction Year of construction Year of construction Village Identification Village Identification Village Identification Village Identification Village Identification District Identification District Identification District Identification District Identification District Identification 011 Kondoa 012 Mpwapwa 013 Kongwa 015 Dodoma Urban 016 Bahi 017 Chamwino 021 Monduli 023 Arusha 024 Karatu 025 Ngorongoro 026 Longido 027 Arusha Rural 028 Meru 031 Rombo 032 Mwanga 033 Same 034 Moshi Rural 035 Hai 037 Siha 041 Lushoto 042 Korogwe 043 Muheza 044 Tanga 045 Pangani 046 Handeni 047 Kilindi 048 Mkinga 051 Kilosa 052 Morogoro 053 Kilombero 054 Ulanga 055 Morogoro Urban 056 Mvomero 061 Bagamoyo 062 Kibaha 063 Kisarawe 064 Mkuranga 065 Rufiji 066 Mafia 071 Kinondoni 072 Ilala 073 Temeke 081 Kilwa 082 Lindi Rural 083 Nachingwea 084 Liwale 085 Ruangwa 086 Lindi Urban 091 Mtwara Rural 092 Newala 093 Masasi 094 Tandahimba 095 Mtwara Urban 096 Nanyumbu 101 Tunduru 102 Songea Rural 103 Mbinga 104 Songea Urban 105 Namtumbo 111 Iringa Rural 112 Mufindi 113 Makete 114 Njombe 115 Ludewa 116 Iringa Urban 117 Kilolo 118 Njombe Mji 121 Chunya 122 Mbeya (R) 123 Kyela 124 Rungwe 125 Ileje 126 Mbozi 127 Mbarali 128 Mbeya Urban 131 Iramba 132 Singida Rural 133 Manyoni 134 Singida Urban 141 Nzega 142 Igunga 143 Uyui 144 Urambo 145 Sikonge 146 Tabora Urban 151 Mpanda 152 Sumbawanga Rural 153 Nkasi 154 Sumbawanga Urban 161 Kibondo 162 Kasulu 163 Kigoma Rural 164 Kigoma Urban 171 Bariadi 172 Maswa 173 Shinyanga Rural 174 Kahama 175 Bukombe 176 Meatu 177 Shinyanga Urban 178 Kishapu 181 Karagwe 182 Bukoba Rural 183 Muleba 184 Biharamulo 185 Ngara 186 Bukoba Urban 187 Missenyi 188 Chato 191 Ukerewe 192 Magu 194 Kwimba 195 Sengerema 196 Geita 197 Missungwi 198 Ilemela 201 Tarime 202 Serengeti 203 Musoma Rural 204 Bunda 205 Musoma Urban 206 Rorya 211 Babati 212 Hanang 213 Mbulu 214 Simanjiro 215 Kiteto 511 Kaskazini-A 512 Kaskazini-B 521 Kati 522 Kusini 531 Magharibi 541 Wete 542 Micheweni 551 Chake 552 Mkoani Region Region Region Region Region 01 Dodoma 02 Arusha 03 Kilimanjaro 04 Tanga 05 Morogoro 06 Pwani 07 Dar es Salaam 08 Lindi 09 Mtwara 10 Ruvuma 11 Iringa 12 Mbeya 13 Singida 14 Tabora 15 Rukwa 16 Kigoma 17 Shinyanga 18 Kagera 19 Mwanza 20 Mara 21 Manyara 51 North Unguja 52 South Unguja 53 Urban West 54 North Pemba 55 South Pemba District District District District District Ward Ward Ward Ward Ward Village Village Village Village Village Household number Household number Household number Household number Household number Cattle Type Cattle Type Cattle Type Cattle Type Cattle Type 1 Castrated Bulls (Oxen) 2 Uncastrated Bulls 3 Cows 4 Steers 5 Heifers 6 Male Calves 7 Female Calves Number of Indigenous Number of Indigenous Number of Indigenous Number of Indigenous Number of Indigenous Number of Improved Beef Number of Improved Beef Number of Improved Beef Number of Improved Beef Number of Improved Beef Number of Improved Dairy Number of Improved Dairy Number of Improved Dairy Number of Improved Dairy Number of Improved Dairy Total Cattle Total Cattle Total Cattle Total Cattle Total Cattle Village Identification Village Identification Village Identification Village Identification Village Identification District Identification District Identification District Identification District Identification District Identification 011 Kondoa 012 Mpwapwa 013 Kongwa 015 Dodoma Urban 016 Bahi 017 Chamwino 021 Monduli 023 Arusha 024 Karatu 025 Ngorongoro 026 Longido 027 Arusha Rural 028 Meru 031 Rombo 032 Mwanga 033 Same 034 Moshi Rural 035 Hai 037 Siha 041 Lushoto 042 Korogwe 043 Muheza 044 Tanga 045 Pangani 046 Handeni 047 Kilindi 048 Mkinga 051 Kilosa 052 Morogoro 053 Kilombero 054 Ulanga 055 Morogoro Urban 056 Mvomero 061 Bagamoyo 062 Kibaha 063 Kisarawe 064 Mkuranga 065 Rufiji 066 Mafia 071 Kinondoni 072 Ilala 073 Temeke 081 Kilwa 082 Lindi Rural 083 Nachingwea 084 Liwale 085 Ruangwa 086 Lindi Urban 091 Mtwara Rural 092 Newala 093 Masasi 094 Tandahimba 095 Mtwara Urban 096 Nanyumbu 101 Tunduru 102 Songea Rural 103 Mbinga 104 Songea Urban 105 Namtumbo 111 Iringa Rural 112 Mufindi 113 Makete 114 Njombe 115 Ludewa 116 Iringa Urban 117 Kilolo 118 Njombe Mji 121 Chunya 122 Mbeya (R) 123 Kyela 124 Rungwe 125 Ileje 126 Mbozi 127 Mbarali 128 Mbeya Urban 131 Iramba 132 Singida Rural 133 Manyoni 134 Singida Urban 141 Nzega 142 Igunga 143 Uyui 144 Urambo 145 Sikonge 146 Tabora Urban 151 Mpanda 152 Sumbawanga Rural 153 Nkasi 154 Sumbawanga Urban 161 Kibondo 162 Kasulu 163 Kigoma Rural 164 Kigoma Urban 171 Bariadi 172 Maswa 173 Shinyanga Rural 174 Kahama 175 Bukombe 176 Meatu 177 Shinyanga Urban 178 Kishapu 181 Karagwe 182 Bukoba Rural 183 Muleba 184 Biharamulo 185 Ngara 186 Bukoba Urban 187 Missenyi 188 Chato 191 Ukerewe 192 Magu 194 Kwimba 195 Sengerema 196 Geita 197 Missungwi 198 Ilemela 201 Tarime 202 Serengeti 203 Musoma Rural 204 Bunda 205 Musoma Urban 206 Rorya 211 Babati 212 Hanang 213 Mbulu 214 Simanjiro 215 Kiteto 511 Kaskazini-A 512 Kaskazini-B 521 Kati 522 Kusini 531 Magharibi 541 Wete 542 Micheweni 551 Chake 552 Mkoani Region Region Region Region Region 01 Dodoma 02 Arusha 03 Kilimanjaro 04 Tanga 05 Morogoro 06 Pwani 07 Dar es Salaam 08 Lindi 09 Mtwara 10 Ruvuma 11 Iringa 12 Mbeya 13 Singida 14 Tabora 15 Rukwa 16 Kigoma 17 Shinyanga 18 Kagera 19 Mwanza 20 Mara 21 Manyara 51 North Unguja 52 South Unguja 53 Urban West 54 North Pemba 55 South Pemba District District District District District Ward Ward Ward Ward Ward Village Village Village Village Village Household number Household number Household number Household number Household number Season Season Season Season Season Cattle Type Cattle Type Cattle Type Cattle Type Cattle Type Number of milked cows Number of milked cows Number of milked cows Number of milked cows Number of milked cows Average milk production per cow per day Average milk production per cow per day Average milk production per cow per day Average milk production per cow per day Average milk production per cow per day Average number of days for cows on milked Average number of days for cows on milked Average number of days for cows on milked Average number of days for cows on milked Average number of days for cows on milked Average price per litre per season Average price per litre per season Average price per litre per season Average price per litre per season Average price per litre per season Village Identification Village Identification Village Identification Village Identification Village Identification District Identification District Identification District Identification District Identification District Identification 011 Kondoa 012 Mpwapwa 013 Kongwa 015 Dodoma Urban 016 Bahi 017 Chamwino 021 Monduli 023 Arusha 024 Karatu 025 Ngorongoro 026 Longido 027 Arusha Rural 028 Meru 031 Rombo 032 Mwanga 033 Same 034 Moshi Rural 035 Hai 037 Siha 041 Lushoto 042 Korogwe 043 Muheza 044 Tanga 045 Pangani 046 Handeni 047 Kilindi 048 Mkinga 051 Kilosa 052 Morogoro 053 Kilombero 054 Ulanga 055 Morogoro Urban 056 Mvomero 061 Bagamoyo 062 Kibaha 063 Kisarawe 064 Mkuranga 065 Rufiji 066 Mafia 071 Kinondoni 072 Ilala 073 Temeke 081 Kilwa 082 Lindi Rural 083 Nachingwea 084 Liwale 085 Ruangwa 086 Lindi Urban 091 Mtwara Rural 092 Newala 093 Masasi 094 Tandahimba 095 Mtwara Urban 096 Nanyumbu 101 Tunduru 102 Songea Rural 103 Mbinga 104 Songea Urban 105 Namtumbo 111 Iringa Rural 112 Mufindi 113 Makete 114 Njombe 115 Ludewa 116 Iringa Urban 117 Kilolo 118 Njombe Mji 121 Chunya 122 Mbeya (R) 123 Kyela 124 Rungwe 125 Ileje 126 Mbozi 127 Mbarali 128 Mbeya Urban 131 Iramba 132 Singida Rural 133 Manyoni 134 Singida Urban 141 Nzega 142 Igunga 143 Uyui 144 Urambo 145 Sikonge 146 Tabora Urban 151 Mpanda 152 Sumbawanga Rural 153 Nkasi 154 Sumbawanga Urban 161 Kibondo 162 Kasulu 163 Kigoma Rural 164 Kigoma Urban 171 Bariadi 172 Maswa 173 Shinyanga Rural 174 Kahama 175 Bukombe 176 Meatu 177 Shinyanga Urban 178 Kishapu 181 Karagwe 182 Bukoba Rural 183 Muleba 184 Biharamulo 185 Ngara 186 Bukoba Urban 187 Missenyi 188 Chato 191 Ukerewe 192 Magu 194 Kwimba 195 Sengerema 196 Geita 197 Missungwi 198 Ilemela 201 Tarime 202 Serengeti 203 Musoma Rural 204 Bunda 205 Musoma Urban 206 Rorya 211 Babati 212 Hanang 213 Mbulu 214 Simanjiro 215 Kiteto 511 Kaskazini-A 512 Kaskazini-B 521 Kati 522 Kusini 531 Magharibi 541 Wete 542 Micheweni 551 Chake 552 Mkoani Region Region Region Region Region 01 Dodoma 02 Arusha 03 Kilimanjaro 04 Tanga 05 Morogoro 06 Pwani 07 Dar es Salaam 08 Lindi 09 Mtwara 10 Ruvuma 11 Iringa 12 Mbeya 13 Singida 14 Tabora 15 Rukwa 16 Kigoma 17 Shinyanga 18 Kagera 19 Mwanza 20 Mara 21 Manyara 51 North Unguja 52 South Unguja 53 Urban West 54 North Pemba 55 South Pemba District District District District District Ward Ward Ward Ward Ward Village Village Village Village Village Household number Household number Household number Household number Household number Goat Type Goat Type Goat Type Goat Type Goat Type 1 Billy Goat 2 Castrated Goat 3 She Goat 4 Male Kid 5 She Kid Number of Indigenous Number of Indigenous Number of Indigenous Number of Indigenous Number of Indigenous Number of Improved for Meat Number of Improved for Meat Number of Improved for Meat Number of Improved for Meat Number of Improved for Meat Number of Improved Dairy Number of Improved Dairy Number of Improved Dairy Number of Improved Dairy Number of Improved Dairy Total Goat Total Goat Total Goat Total Goat Total Goat Village Identification Village Identification Village Identification Village Identification Village Identification District Identification District Identification District Identification District Identification District Identification 011 Kondoa 012 Mpwapwa 013 Kongwa 015 Dodoma Urban 016 Bahi 017 Chamwino 021 Monduli 023 Arusha 024 Karatu 025 Ngorongoro 026 Longido 027 Arusha Rural 028 Meru 031 Rombo 032 Mwanga 033 Same 034 Moshi Rural 035 Hai 037 Siha 041 Lushoto 042 Korogwe 043 Muheza 044 Tanga 045 Pangani 046 Handeni 047 Kilindi 048 Mkinga 051 Kilosa 052 Morogoro 053 Kilombero 054 Ulanga 055 Morogoro Urban 056 Mvomero 061 Bagamoyo 062 Kibaha 063 Kisarawe 064 Mkuranga 065 Rufiji 066 Mafia 071 Kinondoni 072 Ilala 073 Temeke 081 Kilwa 082 Lindi Rural 083 Nachingwea 084 Liwale 085 Ruangwa 086 Lindi Urban 091 Mtwara Rural 092 Newala 093 Masasi 094 Tandahimba 095 Mtwara Urban 096 Nanyumbu 101 Tunduru 102 Songea Rural 103 Mbinga 104 Songea Urban 105 Namtumbo 111 Iringa Rural 112 Mufindi 113 Makete 114 Njombe 115 Ludewa 116 Iringa Urban 117 Kilolo 118 Njombe Mji 121 Chunya 122 Mbeya (R) 123 Kyela 124 Rungwe 125 Ileje 126 Mbozi 127 Mbarali 128 Mbeya Urban 131 Iramba 132 Singida Rural 133 Manyoni 134 Singida Urban 141 Nzega 142 Igunga 143 Uyui 144 Urambo 145 Sikonge 146 Tabora Urban 151 Mpanda 152 Sumbawanga Rural 153 Nkasi 154 Sumbawanga Urban 161 Kibondo 162 Kasulu 163 Kigoma Rural 164 Kigoma Urban 171 Bariadi 172 Maswa 173 Shinyanga Rural 174 Kahama 175 Bukombe 176 Meatu 177 Shinyanga Urban 178 Kishapu 181 Karagwe 182 Bukoba Rural 183 Muleba 184 Biharamulo 185 Ngara 186 Bukoba Urban 187 Missenyi 188 Chato 191 Ukerewe 192 Magu 194 Kwimba 195 Sengerema 196 Geita 197 Missungwi 198 Ilemela 201 Tarime 202 Serengeti 203 Musoma Rural 204 Bunda 205 Musoma Urban 206 Rorya 211 Babati 212 Hanang 213 Mbulu 214 Simanjiro 215 Kiteto 511 Kaskazini-A 512 Kaskazini-B 521 Kati 522 Kusini 531 Magharibi 541 Wete 542 Micheweni 551 Chake 552 Mkoani Region Region Region Region Region 01 Dodoma 02 Arusha 03 Kilimanjaro 04 Tanga 05 Morogoro 06 Pwani 07 Dar es Salaam 08 Lindi 09 Mtwara 10 Ruvuma 11 Iringa 12 Mbeya 13 Singida 14 Tabora 15 Rukwa 16 Kigoma 17 Shinyanga 18 Kagera 19 Mwanza 20 Mara 21 Manyara 51 North Unguja 52 South Unguja 53 Urban West 54 North Pemba 55 South Pemba District District District District District Ward Ward Ward Ward Ward Village Village Village Village Village Household number Household number Household number Household number Household number Sheep Type Sheep Type Sheep Type Sheep Type Sheep Type 1 Ram 2 Castrated Sheep 3 She Sheep 4 Male lamb 5 She lamb Number of Indigenous Number of Indigenous Number of Indigenous Number of Indigenous Number of Indigenous Number of Improved for Mutton Number of Improved for Mutton Number of Improved for Mutton Number of Improved for Mutton Number of Improved for Mutton Total Sheep Total Sheep Total Sheep Total Sheep Total Sheep Village Identification Village Identification Village Identification Village Identification Village Identification District Identification District Identification District Identification District Identification District Identification 011 Kondoa 012 Mpwapwa 013 Kongwa 015 Dodoma Urban 016 Bahi 017 Chamwino 021 Monduli 023 Arusha 024 Karatu 025 Ngorongoro 026 Longido 027 Arusha Rural 028 Meru 031 Rombo 032 Mwanga 033 Same 034 Moshi Rural 035 Hai 037 Siha 041 Lushoto 042 Korogwe 043 Muheza 044 Tanga 045 Pangani 046 Handeni 047 Kilindi 048 Mkinga 051 Kilosa 052 Morogoro 053 Kilombero 054 Ulanga 055 Morogoro Urban 056 Mvomero 061 Bagamoyo 062 Kibaha 063 Kisarawe 064 Mkuranga 065 Rufiji 066 Mafia 071 Kinondoni 072 Ilala 073 Temeke 081 Kilwa 082 Lindi Rural 083 Nachingwea 084 Liwale 085 Ruangwa 086 Lindi Urban 091 Mtwara Rural 092 Newala 093 Masasi 094 Tandahimba 095 Mtwara Urban 096 Nanyumbu 101 Tunduru 102 Songea Rural 103 Mbinga 104 Songea Urban 105 Namtumbo 111 Iringa Rural 112 Mufindi 113 Makete 114 Njombe 115 Ludewa 116 Iringa Urban 117 Kilolo 118 Njombe Mji 121 Chunya 122 Mbeya (R) 123 Kyela 124 Rungwe 125 Ileje 126 Mbozi 127 Mbarali 128 Mbeya Urban 131 Iramba 132 Singida Rural 133 Manyoni 134 Singida Urban 141 Nzega 142 Igunga 143 Uyui 144 Urambo 145 Sikonge 146 Tabora Urban 151 Mpanda 152 Sumbawanga Rural 153 Nkasi 154 Sumbawanga Urban 161 Kibondo 162 Kasulu 163 Kigoma Rural 164 Kigoma Urban 171 Bariadi 172 Maswa 173 Shinyanga Rural 174 Kahama 175 Bukombe 176 Meatu 177 Shinyanga Urban 178 Kishapu 181 Karagwe 182 Bukoba Rural 183 Muleba 184 Biharamulo 185 Ngara 186 Bukoba Urban 187 Missenyi 188 Chato 191 Ukerewe 192 Magu 194 Kwimba 195 Sengerema 196 Geita 197 Missungwi 198 Ilemela 201 Tarime 202 Serengeti 203 Musoma Rural 204 Bunda 205 Musoma Urban 206 Rorya 211 Babati 212 Hanang 213 Mbulu 214 Simanjiro 215 Kiteto 511 Kaskazini-A 512 Kaskazini-B 521 Kati 522 Kusini 531 Magharibi 541 Wete 542 Micheweni 551 Chake 552 Mkoani Region Region Region Region Region 01 Dodoma 02 Arusha 03 Kilimanjaro 04 Tanga 05 Morogoro 06 Pwani 07 Dar es Salaam 08 Lindi 09 Mtwara 10 Ruvuma 11 Iringa 12 Mbeya 13 Singida 14 Tabora 15 Rukwa 16 Kigoma 17 Shinyanga 18 Kagera 19 Mwanza 20 Mara 21 Manyara 51 North Unguja 52 South Unguja 53 Urban West 54 North Pemba 55 South Pemba District District District District District Ward Ward Ward Ward Ward Village Village Village Village Village Household number Household number Household number Household number Household number Pig Type Pig Type Pig Type Pig Type Pig Type 1 Boar 2 Castrated male 3 Sow/Gilt 4 Male piglet 5 She piglet Number of Pig Number of Pig Number of Pig Number of Pig Number of Pig Village Identification Village Identification Village Identification Village Identification Village Identification District Identification District Identification District Identification District Identification District Identification 011 Kondoa 012 Mpwapwa 013 Kongwa 015 Dodoma Urban 016 Bahi 017 Chamwino 021 Monduli 023 Arusha 024 Karatu 025 Ngorongoro 026 Longido 027 Arusha Rural 028 Meru 031 Rombo 032 Mwanga 033 Same 034 Moshi Rural 035 Hai 037 Siha 041 Lushoto 042 Korogwe 043 Muheza 044 Tanga 045 Pangani 046 Handeni 047 Kilindi 048 Mkinga 051 Kilosa 052 Morogoro 053 Kilombero 054 Ulanga 055 Morogoro Urban 056 Mvomero 061 Bagamoyo 062 Kibaha 063 Kisarawe 064 Mkuranga 065 Rufiji 066 Mafia 071 Kinondoni 072 Ilala 073 Temeke 081 Kilwa 082 Lindi Rural 083 Nachingwea 084 Liwale 085 Ruangwa 086 Lindi Urban 091 Mtwara Rural 092 Newala 093 Masasi 094 Tandahimba 095 Mtwara Urban 096 Nanyumbu 101 Tunduru 102 Songea Rural 103 Mbinga 104 Songea Urban 105 Namtumbo 111 Iringa Rural 112 Mufindi 113 Makete 114 Njombe 115 Ludewa 116 Iringa Urban 117 Kilolo 118 Njombe Mji 121 Chunya 122 Mbeya (R) 123 Kyela 124 Rungwe 125 Ileje 126 Mbozi 127 Mbarali 128 Mbeya Urban 131 Iramba 132 Singida Rural 133 Manyoni 134 Singida Urban 141 Nzega 142 Igunga 143 Uyui 144 Urambo 145 Sikonge 146 Tabora Urban 151 Mpanda 152 Sumbawanga Rural 153 Nkasi 154 Sumbawanga Urban 161 Kibondo 162 Kasulu 163 Kigoma Rural 164 Kigoma Urban 171 Bariadi 172 Maswa 173 Shinyanga Rural 174 Kahama 175 Bukombe 176 Meatu 177 Shinyanga Urban 178 Kishapu 181 Karagwe 182 Bukoba Rural 183 Muleba 184 Biharamulo 185 Ngara 186 Bukoba Urban 187 Missenyi 188 Chato 191 Ukerewe 192 Magu 194 Kwimba 195 Sengerema 196 Geita 197 Missungwi 198 Ilemela 201 Tarime 202 Serengeti 203 Musoma Rural 204 Bunda 205 Musoma Urban 206 Rorya 211 Babati 212 Hanang 213 Mbulu 214 Simanjiro 215 Kiteto 511 Kaskazini-A 512 Kaskazini-B 521 Kati 522 Kusini 531 Magharibi 541 Wete 542 Micheweni 551 Chake 552 Mkoani Region Region Region Region Region 01 Dodoma 02 Arusha 03 Kilimanjaro 04 Tanga 05 Morogoro 06 Pwani 07 Dar es Salaam 08 Lindi 09 Mtwara 10 Ruvuma 11 Iringa 12 Mbeya 13 Singida 14 Tabora 15 Rukwa 16 Kigoma 17 Shinyanga 18 Kagera 19 Mwanza 20 Mara 21 Manyara 51 North Unguja 52 South Unguja 53 Urban West 54 North Pemba 55 South Pemba District District District District District Ward Ward Ward Ward Ward Village Village Village Village Village Household number Household number Household number Household number Household number Production Unit Number Production Unit Number Production Unit Number Production Unit Number Production Unit Number Fish Farming System Fish Farming System Fish Farming System Fish Farming System Fish Farming System 1 Natural pond 2 Dug out pond 3 Water resevoir 4 Other Size of Unit/pond Size of Unit/pond Size of Unit/pond Size of Unit/pond Size of Unit/pond Source of Fingerling Source of Fingerling Source of Fingerling Source of Fingerling Source of Fingerling 1 Own pond 2 Government institution 3 NGO/Project 4 Neighbour 5 Private trade 6 Natural pond 8 Other Frequency of stocking Frequency of stocking Frequency of stocking Frequency of stocking Frequency of stocking Kiwango cha Huduma ya bwawa Kiwango cha Huduma ya bwawa Kiwango cha Huduma ya bwawa Kiwango cha Huduma ya bwawa Kiwango cha Huduma ya bwawa 1 High 2 Meadium/Average 3 Low 4 Don't know Number of Tilapia Number of Tilapia Number of Tilapia Number of Tilapia Number of Tilapia Number of Milkfish Number of Milkfish Number of Milkfish Number of Milkfish Number of Milkfish Number of Prawns Number of Prawns Number of Prawns Number of Prawns Number of Prawns Number of Others (Lulu) Number of Others (Lulu) Number of Others (Lulu) Number of Others (Lulu) Number of Others (Lulu) Number of fish harvested Number of fish harvested Number of fish harvested Number of fish harvested Number of fish harvested Weight of fish harvested Weight of fish harvested Weight of fish harvested Weight of fish harvested Weight of fish harvested Weight of Fish Sold Weight of Fish Sold Weight of Fish Sold Weight of Fish Sold Weight of Fish Sold Mainly Sold to Mainly Sold to Mainly Sold to Mainly Sold to Mainly Sold to 1 Neighbour 2 Local market 3 Secondary market 4 Processing industry 5 Large scale farm 6 rade at farm 7 Did not sell 8 Other Village Identification Village Identification Village Identification Village Identification Village Identification District Identification District Identification District Identification District Identification District Identification 011 Kondoa 012 Mpwapwa 013 Kongwa 015 Dodoma Urban 016 Bahi 017 Chamwino 021 Monduli 023 Arusha 024 Karatu 025 Ngorongoro 026 Longido 027 Arusha Rural 028 Meru 031 Rombo 032 Mwanga 033 Same 034 Moshi Rural 035 Hai 037 Siha 041 Lushoto 042 Korogwe 043 Muheza 044 Tanga 045 Pangani 046 Handeni 047 Kilindi 048 Mkinga 051 Kilosa 052 Morogoro 053 Kilombero 054 Ulanga 055 Morogoro Urban 056 Mvomero 061 Bagamoyo 062 Kibaha 063 Kisarawe 064 Mkuranga 065 Rufiji 066 Mafia 071 Kinondoni 072 Ilala 073 Temeke 081 Kilwa 082 Lindi Rural 083 Nachingwea 084 Liwale 085 Ruangwa 086 Lindi Urban 091 Mtwara Rural 092 Newala 093 Masasi 094 Tandahimba 095 Mtwara Urban 096 Nanyumbu 101 Tunduru 102 Songea Rural 103 Mbinga 104 Songea Urban 105 Namtumbo 111 Iringa Rural 112 Mufindi 113 Makete 114 Njombe 115 Ludewa 116 Iringa Urban 117 Kilolo 118 Njombe Mji 121 Chunya 122 Mbeya (R) 123 Kyela 124 Rungwe 125 Ileje 126 Mbozi 127 Mbarali 128 Mbeya Urban 131 Iramba 132 Singida Rural 133 Manyoni 134 Singida Urban 141 Nzega 142 Igunga 143 Uyui 144 Urambo 145 Sikonge 146 Tabora Urban 151 Mpanda 152 Sumbawanga Rural 153 Nkasi 154 Sumbawanga Urban 161 Kibondo 162 Kasulu 163 Kigoma Rural 164 Kigoma Urban 171 Bariadi 172 Maswa 173 Shinyanga Rural 174 Kahama 175 Bukombe 176 Meatu 177 Shinyanga Urban 178 Kishapu 181 Karagwe 182 Bukoba Rural 183 Muleba 184 Biharamulo 185 Ngara 186 Bukoba Urban 187 Missenyi 188 Chato 191 Ukerewe 192 Magu 194 Kwimba 195 Sengerema 196 Geita 197 Missungwi 198 Ilemela 201 Tarime 202 Serengeti 203 Musoma Rural 204 Bunda 205 Musoma Urban 206 Rorya 211 Babati 212 Hanang 213 Mbulu 214 Simanjiro 215 Kiteto 511 Kaskazini-A 512 Kaskazini-B 521 Kati 522 Kusini 531 Magharibi 541 Wete 542 Micheweni 551 Chake 552 Mkoani Region Region Region Region Region 01 Dodoma 02 Arusha 03 Kilimanjaro 04 Tanga 05 Morogoro 06 Pwani 07 Dar es Salaam 08 Lindi 09 Mtwara 10 Ruvuma 11 Iringa 12 Mbeya 13 Singida 14 Tabora 15 Rukwa 16 Kigoma 17 Shinyanga 18 Kagera 19 Mwanza 20 Mara 21 Manyara 51 North Unguja 52 South Unguja 53 Urban West 54 North Pemba 55 South Pemba District District District District District Ward Ward Ward Ward Ward Village Village Village Village Village Household number Household number Household number Household number Household number Season Season Season Season Season 1 Wet 2 Dry Main source of drinking water Main source of drinking water Main source of drinking water Main source of drinking water Main source of drinking water 1 Piped Water 2 Protected Well 3 Protected / Covered Spring 4 Uprotected Well 5 Unprotected Spring 6 Surface Water (Lake / Dam / River / Stream) 7 Covered Rainwater Catchment 8 Uncovered Rainwater Catchment 9 Water Vendor 10 Tanker Truck 11 Bottled Water 98 Other Distance to source (km) Distance to source (km) Distance to source (km) Distance to source (km) Distance to source (km) Time to and from source Time to and from source Time to and from source Time to and from source Time to and from source Village Identification Village Identification Village Identification Village Identification Village Identification District Identification District Identification District Identification District Identification District Identification 011 Kondoa 012 Mpwapwa 013 Kongwa 015 Dodoma Urban 016 Bahi 017 Chamwino 021 Monduli 023 Arusha 024 Karatu 025 Ngorongoro 026 Longido 027 Arusha Rural 028 Meru 031 Rombo 032 Mwanga 033 Same 034 Moshi Rural 035 Hai 037 Siha 041 Lushoto 042 Korogwe 043 Muheza 044 Tanga 045 Pangani 046 Handeni 047 Kilindi 048 Mkinga 051 Kilosa 052 Morogoro 053 Kilombero 054 Ulanga 055 Morogoro Urban 056 Mvomero 061 Bagamoyo 062 Kibaha 063 Kisarawe 064 Mkuranga 065 Rufiji 066 Mafia 071 Kinondoni 072 Ilala 073 Temeke 081 Kilwa 082 Lindi Rural 083 Nachingwea 084 Liwale 085 Ruangwa 086 Lindi Urban 091 Mtwara Rural 092 Newala 093 Masasi 094 Tandahimba 095 Mtwara Urban 096 Nanyumbu 101 Tunduru 102 Songea Rural 103 Mbinga 104 Songea Urban 105 Namtumbo 111 Iringa Rural 112 Mufindi 113 Makete 114 Njombe 115 Ludewa 116 Iringa Urban 117 Kilolo 118 Njombe Mji 121 Chunya 122 Mbeya (R) 123 Kyela 124 Rungwe 125 Ileje 126 Mbozi 127 Mbarali 128 Mbeya Urban 131 Iramba 132 Singida Rural 133 Manyoni 134 Singida Urban 141 Nzega 142 Igunga 143 Uyui 144 Urambo 145 Sikonge 146 Tabora Urban 151 Mpanda 152 Sumbawanga Rural 153 Nkasi 154 Sumbawanga Urban 161 Kibondo 162 Kasulu 163 Kigoma Rural 164 Kigoma Urban 171 Bariadi 172 Maswa 173 Shinyanga Rural 174 Kahama 175 Bukombe 176 Meatu 177 Shinyanga Urban 178 Kishapu 181 Karagwe 182 Bukoba Rural 183 Muleba 184 Biharamulo 185 Ngara 186 Bukoba Urban 187 Missenyi 188 Chato 191 Ukerewe 192 Magu 194 Kwimba 195 Sengerema 196 Geita 197 Missungwi 198 Ilemela 201 Tarime 202 Serengeti 203 Musoma Rural 204 Bunda 205 Musoma Urban 206 Rorya 211 Babati 212 Hanang 213 Mbulu 214 Simanjiro 215 Kiteto 511 Kaskazini-A 512 Kaskazini-B 521 Kati 522 Kusini 531 Magharibi 541 Wete 542 Micheweni 551 Chake 552 Mkoani Region Region Region Region Region 01 Dodoma 02 Arusha 03 Kilimanjaro 04 Tanga 05 Morogoro 06 Pwani 07 Dar es Salaam 08 Lindi 09 Mtwara 10 Ruvuma 11 Iringa 12 Mbeya 13 Singida 14 Tabora 15 Rukwa 16 Kigoma 17 Shinyanga 18 Kagera 19 Mwanza 20 Mara 21 Manyara 51 North Unguja 52 South Unguja 53 Urban West 54 North Pemba 55 South Pemba District District District District District Ward Ward Ward Ward Ward Village Village Village Village Village Household number Household number Household number Household number Household number Main Source of Irrigation Water Main Source of Irrigation Water Main Source of Irrigation Water Main Source of Irrigation Water Main Source of Irrigation Water 1 River" 2 Lake 3 Dam 4 Well 5 Borehole 6 Canal 7 Tape Water Main method of Obtaining Water Main method of Obtaining Water Main method of Obtaining Water Main method of Obtaining Water Main method of Obtaining Water 1 Gravity 2 Hand Bucket 3 Hand Pump 4 Motor pump 8 Others Irrigatable Area (Acrea) Irrigatable Area (Acrea) Irrigatable Area (Acrea) Irrigatable Area (Acrea) Irrigatable Area (Acrea) Area of irrigated Land agriculture year 2007/08 (acres) Area of irrigated Land agriculture year 2007/08 (acres) Area of irrigated Land agriculture year 2007/08 (acres) Area of irrigated Land agriculture year 2007/08 (acres) Area of irrigated Land agriculture year 2007/08 (acres) Village Identification Village Identification Village Identification Village Identification Village Identification District Identification District Identification District Identification District Identification District Identification 011 Kondoa 012 Mpwapwa 013 Kongwa 015 Dodoma Urban 016 Bahi 017 Chamwino 021 Monduli 023 Arusha 024 Karatu 025 Ngorongoro 026 Longido 027 Arusha Rural 028 Meru 031 Rombo 032 Mwanga 033 Same 034 Moshi Rural 035 Hai 037 Siha 041 Lushoto 042 Korogwe 043 Muheza 044 Tanga 045 Pangani 046 Handeni 047 Kilindi 048 Mkinga 051 Kilosa 052 Morogoro 053 Kilombero 054 Ulanga 055 Morogoro Urban 056 Mvomero 061 Bagamoyo 062 Kibaha 063 Kisarawe 064 Mkuranga 065 Rufiji 066 Mafia 071 Kinondoni 072 Ilala 073 Temeke 081 Kilwa 082 Lindi Rural 083 Nachingwea 084 Liwale 085 Ruangwa 086 Lindi Urban 091 Mtwara Rural 092 Newala 093 Masasi 094 Tandahimba 095 Mtwara Urban 096 Nanyumbu 101 Tunduru 102 Songea Rural 103 Mbinga 104 Songea Urban 105 Namtumbo 111 Iringa Rural 112 Mufindi 113 Makete 114 Njombe 115 Ludewa 116 Iringa Urban 117 Kilolo 118 Njombe Mji 121 Chunya 122 Mbeya (R) 123 Kyela 124 Rungwe 125 Ileje 126 Mbozi 127 Mbarali 128 Mbeya Urban 131 Iramba 132 Singida Rural 133 Manyoni 134 Singida Urban 141 Nzega 142 Igunga 143 Uyui 144 Urambo 145 Sikonge 146 Tabora Urban 151 Mpanda 152 Sumbawanga Rural 153 Nkasi 154 Sumbawanga Urban 161 Kibondo 162 Kasulu 163 Kigoma Rural 164 Kigoma Urban 171 Bariadi 172 Maswa 173 Shinyanga Rural 174 Kahama 175 Bukombe 176 Meatu 177 Shinyanga Urban 178 Kishapu 181 Karagwe 182 Bukoba Rural 183 Muleba 184 Biharamulo 185 Ngara 186 Bukoba Urban 187 Missenyi 188 Chato 191 Ukerewe 192 Magu 194 Kwimba 195 Sengerema 196 Geita 197 Missungwi 198 Ilemela 201 Tarime 202 Serengeti 203 Musoma Rural 204 Bunda 205 Musoma Urban 206 Rorya 211 Babati 212 Hanang 213 Mbulu 214 Simanjiro 215 Kiteto 511 Kaskazini-A 512 Kaskazini-B 521 Kati 522 Kusini 531 Magharibi 541 Wete 542 Micheweni 551 Chake 552 Mkoani Region Region Region Region Region 01 Dodoma 02 Arusha 03 Kilimanjaro 04 Tanga 05 Morogoro 06 Pwani 07 Dar es Salaam 08 Lindi 09 Mtwara 10 Ruvuma 11 Iringa 12 Mbeya 13 Singida 14 Tabora 15 Rukwa 16 Kigoma 17 Shinyanga 18 Kagera 19 Mwanza 20 Mara 21 Manyara 51 North Unguja 52 South Unguja 53 Urban West 54 North Pemba 55 South Pemba District District District District District Ward Ward Ward Ward Ward Village Village Village Village Village Household number Household number Household number Household number Household number Extension Message Extension Message Extension Message Extension Message Extension Message 1 Spacing 2 Use of agrochemicals 3 Erosion control 4 Organic fertiliser use 5 Inorganic fertiliser use 6 Use of improved seed 7 Mechanisation/LST 8 Irrigation Technology 9 Crop Storage 10 Vermin control 11 Other Received Advice Received Advice Received Advice Received Advice Received Advice 1 Yes 2 No Source of Crop Extension Source of Crop Extension Source of Crop Extension Source of Crop Extension Source of Crop Extension 1 Government 2 NGO/Dev project 3 Cooperative 4 Large scale farmer 5 Radio/Television/NewsPaper 6 Neighbour 8 Other (Specify) Village Identification Village Identification Village Identification Village Identification Village Identification District Identification District Identification District Identification District Identification District Identification 011 Kondoa 012 Mpwapwa 013 Kongwa 015 Dodoma Urban 016 Bahi 017 Chamwino 021 Monduli 023 Arusha 024 Karatu 025 Ngorongoro 026 Longido 027 Arusha Rural 028 Meru 031 Rombo 032 Mwanga 033 Same 034 Moshi Rural 035 Hai 037 Siha 041 Lushoto 042 Korogwe 043 Muheza 044 Tanga 045 Pangani 046 Handeni 047 Kilindi 048 Mkinga 051 Kilosa 052 Morogoro 053 Kilombero 054 Ulanga 055 Morogoro Urban 056 Mvomero 061 Bagamoyo 062 Kibaha 063 Kisarawe 064 Mkuranga 065 Rufiji 066 Mafia 071 Kinondoni 072 Ilala 073 Temeke 081 Kilwa 082 Lindi Rural 083 Nachingwea 084 Liwale 085 Ruangwa 086 Lindi Urban 091 Mtwara Rural 092 Newala 093 Masasi 094 Tandahimba 095 Mtwara Urban 096 Nanyumbu 101 Tunduru 102 Songea Rural 103 Mbinga 104 Songea Urban 105 Namtumbo 111 Iringa Rural 112 Mufindi 113 Makete 114 Njombe 115 Ludewa 116 Iringa Urban 117 Kilolo 118 Njombe Mji 121 Chunya 122 Mbeya (R) 123 Kyela 124 Rungwe 125 Ileje 126 Mbozi 127 Mbarali 128 Mbeya Urban 131 Iramba 132 Singida Rural 133 Manyoni 134 Singida Urban 141 Nzega 142 Igunga 143 Uyui 144 Urambo 145 Sikonge 146 Tabora Urban 151 Mpanda 152 Sumbawanga Rural 153 Nkasi 154 Sumbawanga Urban 161 Kibondo 162 Kasulu 163 Kigoma Rural 164 Kigoma Urban 171 Bariadi 172 Maswa 173 Shinyanga Rural 174 Kahama 175 Bukombe 176 Meatu 177 Shinyanga Urban 178 Kishapu 181 Karagwe 182 Bukoba Rural 183 Muleba 184 Biharamulo 185 Ngara 186 Bukoba Urban 187 Missenyi 188 Chato 191 Ukerewe 192 Magu 194 Kwimba 195 Sengerema 196 Geita 197 Missungwi 198 Ilemela 201 Tarime 202 Serengeti 203 Musoma Rural 204 Bunda 205 Musoma Urban 206 Rorya 211 Babati 212 Hanang 213 Mbulu 214 Simanjiro 215 Kiteto 511 Kaskazini-A 512 Kaskazini-B 521 Kati 522 Kusini 531 Magharibi 541 Wete 542 Micheweni 551 Chake 552 Mkoani Region Region Region Region Region 01 Dodoma 02 Arusha 03 Kilimanjaro 04 Tanga 05 Morogoro 06 Pwani 07 Dar es Salaam 08 Lindi 09 Mtwara 10 Ruvuma 11 Iringa 12 Mbeya 13 Singida 14 Tabora 15 Rukwa 16 Kigoma 17 Shinyanga 18 Kagera 19 Mwanza 20 Mara 21 Manyara 51 North Unguja 52 South Unguja 53 Urban West 54 North Pemba 55 South Pemba District District District District District Ward Ward Ward Ward Ward Village Village Village Village Village Household number Household number Household number Household number Household number Bee Type Bee Type Bee Type Bee Type Bee Type 1 Sting Bee 2 Stingless Bee Was Honey Harvested? Was Honey Harvested? Was Honey Harvested? Was Honey Harvested? Was Honey Harvested? 1 Yes 2 No Number of Improved Bee Hives Number of Improved Bee Hives Number of Improved Bee Hives Number of Improved Bee Hives Number of Improved Bee Hives Number of Local Bee Hives Number of Local Bee Hives Number of Local Bee Hives Number of Local Bee Hives Number of Local Bee Hives Amount of honey harvested 2007/08 Amount of honey harvested 2007/08 Amount of honey harvested 2007/08 Amount of honey harvested 2007/08 Amount of honey harvested 2007/08 Amount of honey Sold Amount of honey Sold Amount of honey Sold Amount of honey Sold Amount of honey Sold Price per Litre Price per Litre Price per Litre Price per Litre Price per Litre Main Market Main Market Main Market Main Market Main Market 1 Neighbour 2 Local market 3 Secondary market 4 Processing industry 5 Large scale farm 6 Trade at farm 7 Did not sell 8 Other Village Identification Village Identification Village Identification Village Identification Village Identification District Identification District Identification District Identification District Identification District Identification 011 Kondoa 012 Mpwapwa 013 Kongwa 015 Dodoma Urban 016 Bahi 017 Chamwino 021 Monduli 023 Arusha 024 Karatu 025 Ngorongoro 026 Longido 027 Arusha Rural 028 Meru 031 Rombo 032 Mwanga 033 Same 034 Moshi Rural 035 Hai 037 Siha 041 Lushoto 042 Korogwe 043 Muheza 044 Tanga 045 Pangani 046 Handeni 047 Kilindi 048 Mkinga 051 Kilosa 052 Morogoro 053 Kilombero 054 Ulanga 055 Morogoro Urban 056 Mvomero 061 Bagamoyo 062 Kibaha 063 Kisarawe 064 Mkuranga 065 Rufiji 066 Mafia 071 Kinondoni 072 Ilala 073 Temeke 081 Kilwa 082 Lindi Rural 083 Nachingwea 084 Liwale 085 Ruangwa 086 Lindi Urban 091 Mtwara Rural 092 Newala 093 Masasi 094 Tandahimba 095 Mtwara Urban 096 Nanyumbu 101 Tunduru 102 Songea Rural 103 Mbinga 104 Songea Urban 105 Namtumbo 111 Iringa Rural 112 Mufindi 113 Makete 114 Njombe 115 Ludewa 116 Iringa Urban 117 Kilolo 118 Njombe Mji 121 Chunya 122 Mbeya (R) 123 Kyela 124 Rungwe 125 Ileje 126 Mbozi 127 Mbarali 128 Mbeya Urban 131 Iramba 132 Singida Rural 133 Manyoni 134 Singida Urban 141 Nzega 142 Igunga 143 Uyui 144 Urambo 145 Sikonge 146 Tabora Urban 151 Mpanda 152 Sumbawanga Rural 153 Nkasi 154 Sumbawanga Urban 161 Kibondo 162 Kasulu 163 Kigoma Rural 164 Kigoma Urban 171 Bariadi 172 Maswa 173 Shinyanga Rural 174 Kahama 175 Bukombe 176 Meatu 177 Shinyanga Urban 178 Kishapu 181 Karagwe 182 Bukoba Rural 183 Muleba 184 Biharamulo 185 Ngara 186 Bukoba Urban 187 Missenyi 188 Chato 191 Ukerewe 192 Magu 194 Kwimba 195 Sengerema 196 Geita 197 Missungwi 198 Ilemela 201 Tarime 202 Serengeti 203 Musoma Rural 204 Bunda 205 Musoma Urban 206 Rorya 211 Babati 212 Hanang 213 Mbulu 214 Simanjiro 215 Kiteto 511 Kaskazini-A 512 Kaskazini-B 521 Kati 522 Kusini 531 Magharibi 541 Wete 542 Micheweni 551 Chake 552 Mkoani Region Region Region Region Region 01 Dodoma 02 Arusha 03 Kilimanjaro 04 Tanga 05 Morogoro 06 Pwani 07 Dar es Salaam 08 Lindi 09 Mtwara 10 Ruvuma 11 Iringa 12 Mbeya 13 Singida 14 Tabora 15 Rukwa 16 Kigoma 17 Shinyanga 18 Kagera 19 Mwanza 20 Mara 21 Manyara 51 North Unguja 52 South Unguja 53 Urban West 54 North Pemba 55 South Pemba District District District District District Ward Ward Ward Ward Ward Village Village Village Village Village Household number Household number Household number Household number Household number Order of Most Importance Order of Most Importance Order of Most Importance Order of Most Importance Order of Most Importance 1 1st Most Importance 2 2nd Most Importance 3 3rd Most Importance 4 4th Most Importance 5 5th Most Importance Constraint Constraint Constraint Constraint Constraint 1 Access to Land 2 Ownership of Land 3 Poor Soil Cultivation Equipment 4 Soil Fertility 5 Access to Improved Seed 6 Irrigation Facilities 7 Access to Chemical Inputs 8 Cost of Inputs 9 Extension Services 10 Access to Forest Resources 11 Hunting and Gathering 12 Access to Potable Water 13 Access to Credit 14 Access to Off Farm Income 15 Threshing 16 Harvesting 17 Crop Storage 18 Crop Processing 19 Marketing Information 20 Higher Transport Costs 21 Destruction by Animals 22 Stealing 23 Pest and Disease 24 Local Government Taxation 25 Extended dry spell 26 Crop Farmers/Livestock keepers Conflicts Village Identification Village Identification Village Identification Village Identification Village Identification District Identification District Identification District Identification District Identification District Identification 011 Kondoa 012 Mpwapwa 013 Kongwa 015 Dodoma Urban 016 Bahi 017 Chamwino 021 Monduli 023 Arusha 024 Karatu 025 Ngorongoro 026 Longido 027 Arusha Rural 028 Meru 031 Rombo 032 Mwanga 033 Same 034 Moshi Rural 035 Hai 037 Siha 041 Lushoto 042 Korogwe 043 Muheza 044 Tanga 045 Pangani 046 Handeni 047 Kilindi 048 Mkinga 051 Kilosa 052 Morogoro 053 Kilombero 054 Ulanga 055 Morogoro Urban 056 Mvomero 061 Bagamoyo 062 Kibaha 063 Kisarawe 064 Mkuranga 065 Rufiji 066 Mafia 071 Kinondoni 072 Ilala 073 Temeke 081 Kilwa 082 Lindi Rural 083 Nachingwea 084 Liwale 085 Ruangwa 086 Lindi Urban 091 Mtwara Rural 092 Newala 093 Masasi 094 Tandahimba 095 Mtwara Urban 096 Nanyumbu 101 Tunduru 102 Songea Rural 103 Mbinga 104 Songea Urban 105 Namtumbo 111 Iringa Rural 112 Mufindi 113 Makete 114 Njombe 115 Ludewa 116 Iringa Urban 117 Kilolo 118 Njombe Mji 121 Chunya 122 Mbeya (R) 123 Kyela 124 Rungwe 125 Ileje 126 Mbozi 127 Mbarali 128 Mbeya Urban 131 Iramba 132 Singida Rural 133 Manyoni 134 Singida Urban 141 Nzega 142 Igunga 143 Uyui 144 Urambo 145 Sikonge 146 Tabora Urban 151 Mpanda 152 Sumbawanga Rural 153 Nkasi 154 Sumbawanga Urban 161 Kibondo 162 Kasulu 163 Kigoma Rural 164 Kigoma Urban 171 Bariadi 172 Maswa 173 Shinyanga Rural 174 Kahama 175 Bukombe 176 Meatu 177 Shinyanga Urban 178 Kishapu 181 Karagwe 182 Bukoba Rural 183 Muleba 184 Biharamulo 185 Ngara 186 Bukoba Urban 187 Missenyi 188 Chato 191 Ukerewe 192 Magu 194 Kwimba 195 Sengerema 196 Geita 197 Missungwi 198 Ilemela 201 Tarime 202 Serengeti 203 Musoma Rural 204 Bunda 205 Musoma Urban 206 Rorya 211 Babati 212 Hanang 213 Mbulu 214 Simanjiro 215 Kiteto 511 Kaskazini-A 512 Kaskazini-B 521 Kati 522 Kusini 531 Magharibi 541 Wete 542 Micheweni 551 Chake 552 Mkoani Farm Serial Number Farm Serial Number Farm Serial Number Farm Serial Number Farm Serial Number Region Region Region Region Region 01 Dodoma 02 Arusha 03 Kilimanjaro 04 Tanga 05 Morogoro 06 Pwani 07 Dar es salaam 08 Lindi 09 Mtwara 10 Ruvuma 11 Iringa 12 Mbeya 13 Singida 14 Tabora 15 Rukwa 16 Kigoma 17 Shinyanga 18 Kagera 19 Mwanza 20 Mara 21 Manyara 51 North Unguja 52 South Unguja 53 Urban West 54 North Pemba 55 South Pemba 2.1 Using the options below indicate the type of farm owners 2.1 Using the options below indicate the type of farm owners 2.1 Using the options below indicate the type of farm owners 2.1 Using the options below indicate the type of farm owners 2.1 Using the options below indicate the type of farm owners 1 Government 2 Parastatal 3 Private registered 4 Private Non- registered 5 Other 2.2 Type of Agriculture Holding 2.2 Type of Agriculture Holding 2.2 Type of Agriculture Holding 2.2 Type of Agriculture Holding 2.2 Type of Agriculture Holding 1 Crops Only 2 Livestock only 3 Crops and Livestock 4 Production of Flowers 4.1 Did the farm grow Temporary Crops during the 2007/08 Agr 4.1 Did the farm grow Temporary Crops during the 2007/08 Agr 4.1 Did the farm grow Temporary Crops during the 2007/08 Agr 4.1 Did the farm grow Temporary Crops during the 2007/08 Agr 4.1 Did the farm grow Temporary Crops during the 2007/08 Agr 1 Yes 2 No 4.2.1 Did the farm grow Temporary Crops during the 2007/08 A 4.2.1 Did the farm grow Temporary Crops during the 2007/08 A 4.2.1 Did the farm grow Temporary Crops during the 2007/08 A 4.2.1 Did the farm grow Temporary Crops during the 2007/08 A 4.2.1 Did the farm grow Temporary Crops during the 2007/08 A 1 Yes 2 No 4.3.1 Did the farm have any mature/fruit bearing Permanent C 4.3.1 Did the farm have any mature/fruit bearing Permanent C 4.3.1 Did the farm have any mature/fruit bearing Permanent C 4.3.1 Did the farm have any mature/fruit bearing Permanent C 4.3.1 Did the farm have any mature/fruit bearing Permanent C 1 Yes 2 No 5.1 Did you use Secondary Products from any of your crops du 5.1 Did you use Secondary Products from any of your crops du 5.1 Did you use Secondary Products from any of your crops du 5.1 Did you use Secondary Products from any of your crops du 5.1 Did you use Secondary Products from any of your crops du 1 Yes 2 No 5.2 Did the farm process any of the products harvested on th 5.2 Did the farm process any of the products harvested on th 5.2 Did the farm process any of the products harvested on th 5.2 Did the farm process any of the products harvested on th 5.2 Did the farm process any of the products harvested on th 1 Yes 2 No 6.1 During the year 2007/08 did the farmer borrow money for 6.1 During the year 2007/08 did the farmer borrow money for 6.1 During the year 2007/08 did the farmer borrow money for 6.1 During the year 2007/08 did the farmer borrow money for 6.1 During the year 2007/08 did the farmer borrow money for 1 Received Credit 2 Did not Receive Credit Source A Source A Source A Source A Source A 1 Company owning the farm 2 Commercial Bank 3 Savings and Credit Soc. 4 Religious Organisation/NGO/Project 8 Other (Specify) Source B Source B Source B Source B Source B 1 Company owning the farm 2 Commercial Bank 3 Savings and Credit Soc. 4 Religious Organisation/NGO/Project 8 Other (Specify) Source C Source C Source C Source C Source C 1 Company owning the farm 2 Commercial Bank 3 Savings and Credit Soc. 4 Religious Organisation/NGO/Project 8 Other (Specify) 6.3 If the answer to question 6.1 above is NO what is the 6.3 If the answer to question 6.1 above is NO what is the 6.3 If the answer to question 6.1 above is NO what is the 6.3 If the answer to question 6.1 above is NO what is the 6.3 If the answer to question 6.1 above is NO what is the 1 Not needed 2 Not available 3 Did not want to go into credit 4 Interest rate/cost too high 5 Credit granted too late 6 Difficult bureacratic procedure 8 Other 8.1 Crop Code A 8.1 Crop Code A 8.1 Crop Code A 8.1 Crop Code A 8.1 Crop Code A 8.2 Crop Code B 8.2 Crop Code B 8.2 Crop Code B 8.2 Crop Code B 8.2 Crop Code B 8.3 Crop Code C 8.3 Crop Code C 8.3 Crop Code C 8.3 Crop Code C 8.3 Crop Code C 9.1 Did the farm own, raise or manage any CATTLE during 2007 9.1 Did the farm own, raise or manage any CATTLE during 2007 9.1 Did the farm own, raise or manage any CATTLE during 2007 9.1 Did the farm own, raise or manage any CATTLE during 2007 9.1 Did the farm own, raise or manage any CATTLE during 2007 1 Yes 2 No 9.2 Did the farm own, raise or manage any GOATS during the 2 9.2 Did the farm own, raise or manage any GOATS during the 2 9.2 Did the farm own, raise or manage any GOATS during the 2 9.2 Did the farm own, raise or manage any GOATS during the 2 9.2 Did the farm own, raise or manage any GOATS during the 2 1 Yes 2 No 9.3 Did the farm own, raise or manage any SHEEP during the 2 9.3 Did the farm own, raise or manage any SHEEP during the 2 9.3 Did the farm own, raise or manage any SHEEP during the 2 9.3 Did the farm own, raise or manage any SHEEP during the 2 9.3 Did the farm own, raise or manage any SHEEP during the 2 1 Yes 2 No 9.4 Did the farm own, raise or manage any PIGS during the 20 9.4 Did the farm own, raise or manage any PIGS during the 20 9.4 Did the farm own, raise or manage any PIGS during the 20 9.4 Did the farm own, raise or manage any PIGS during the 20 9.4 Did the farm own, raise or manage any PIGS during the 20 1 Yes 2 No 9.6.1 Did you deworm your animals during 2007/08 9.6.1 Did you deworm your animals during 2007/08 9.6.1 Did you deworm your animals during 2007/08 9.6.1 Did you deworm your animals during 2007/08 9.6.1 Did you deworm your animals during 2007/08 1 Yes 2 No CATTLE CATTLE CATTLE CATTLE CATTLE 1 Yes 2 No 3 Not applicable GOATS GOATS GOATS GOATS GOATS 1 Yes 2 No 3 Not applicable SHEEP SHEEP SHEEP SHEEP SHEEP 1 Yes 2 No 3 Not applicable PIGS PIGS PIGS PIGS PIGS 1 Yes 2 No 3 Not applicable 9.6.3 Do you normally encounter a tick problem? 9.6.3 Do you normally encounter a tick problem? 9.6.3 Do you normally encounter a tick problem? 9.6.3 Do you normally encounter a tick problem? 9.6.3 Do you normally encounter a tick problem? 1 Yes 2 No 3 Not applicable 9.6.4 Which methods of tick control did you use? 9.6.4 Which methods of tick control did you use? 9.6.4 Which methods of tick control did you use? 9.6.4 Which methods of tick control did you use? 9.6.4 Which methods of tick control did you use? 1 Spraying 2 Dipping 3 Smearing 4 None 8 Other........ 9.6.5 Do you normally encounter a tsetse fly problem? 9.6.5 Do you normally encounter a tsetse fly problem? 9.6.5 Do you normally encounter a tsetse fly problem? 9.6.5 Do you normally encounter a tsetse fly problem? 9.6.5 Do you normally encounter a tsetse fly problem? 1 Yes 2 No 3 Not applicable 9.6.6 Which methods of control did you use? 9.6.6 Which methods of control did you use? 9.6.6 Which methods of control did you use? 9.6.6 Which methods of control did you use? 9.6.6 Which methods of control did you use? 1 Spraying 2 Dipping 3 Smearing 4 None 8 Other........ 9.6.7 Foot and Mouth disease 9.6.7 Foot and Mouth disease 9.6.7 Foot and Mouth disease 9.6.7 Foot and Mouth disease 9.6.7 Foot and Mouth disease 1 Yes 2 No 3 Not applicable 9.6.8 Lumpyskin 9.6.8 Lumpyskin 9.6.8 Lumpyskin 9.6.8 Lumpyskin 9.6.8 Lumpyskin 1 Yes 2 No 3 Not applicable 11.1 Does the farm provide services to small holder farmers 11.1 Does the farm provide services to small holder farmers 11.1 Does the farm provide services to small holder farmers 11.1 Does the farm provide services to small holder farmers 11.1 Does the farm provide services to small holder farmers 1 Yes 2 No Interview Day Interview Day Interview Day Interview Day Interview Day Interview Month Interview Month Interview Month Interview Month Interview Month Interview Year Interview Year Interview Year Interview Year Interview Year 2009 Year Starting Time Starting Time Starting Time Starting Time Starting Time Starting Minutes Starting Minutes Starting Minutes Starting Minutes Starting Minutes End Time End Time End Time End Time End Time End Minutes End Minutes End Minutes End Minutes End Minutes TOTAL Q3.1 TOTAL Q3.1 TOTAL Q3.1 TOTAL Q3.1 TOTAL Q3.1 TOTAL Q3.2 TOTAL Q3.2 TOTAL Q3.2 TOTAL Q3.2 TOTAL Q3.2 TOTAL Q9.1 TOTAL Q9.1 TOTAL Q9.1 TOTAL Q9.1 TOTAL Q9.1 TOTAL Q9.2 TOTAL Q9.2 TOTAL Q9.2 TOTAL Q9.2 TOTAL Q9.2 TOTAL Q9.3 TOTAL Q9.3 TOTAL Q9.3 TOTAL Q9.3 TOTAL Q9.3 TOTAL Q9.4 TOTAL Q9.4 TOTAL Q9.4 TOTAL Q9.4 TOTAL Q9.4 Q094 ~= xx (FILTER) Q094 ~= xx (FILTER) Q094 ~= xx (FILTER) Q094 ~= xx (FILTER) Q094 ~= xx (FILTER) Not Selected 1 Selected Farm Serial Number Farm Serial Number Farm Serial Number Farm Serial Number Farm Serial Number Region Region Region Region Region 01 Dodoma 02 Arusha 03 Kilimanjaro 04 Tanga 05 Morogoro 06 Pwani 07 Dar es salaam 08 Lindi 09 Mtwara 10 Ruvuma 11 Iringa 12 Mbeya 13 Singida 14 Tabora 15 Rukwa 16 Kigoma 17 Shinyanga 18 Kagera 19 Mwanza 20 Mara 21 Manyara 51 North Unguja 52 South Unguja 53 Urban West 54 North Pemba 55 South Pemba Area owned by Area owned by Area owned by Area owned by Area owned by 1 Area Leased/Certified of ownership 2 Area owned under Customary Law 3 Area Bought from others(not leased/certified) 4 Area Rented from others 5 Area Borrowed from others 6 Area under Compulsory Acquisition Area in Hectare Area in Hectare Area in Hectare Area in Hectare Area in Hectare 2.1 Using the options below indicate the type of farm owners 2.1 Using the options below indicate the type of farm owners 2.1 Using the options below indicate the type of farm owners 2.1 Using the options below indicate the type of farm owners 2.1 Using the options below indicate the type of farm owners 1 Government 2 Parastatal 3 Private registered 4 Private Non- registered 5 Other Farm Serial Number Farm Serial Number Farm Serial Number Farm Serial Number Farm Serial Number Region Region Region Region Region 01 Dodoma 02 Arusha 03 Kilimanjaro 04 Tanga 05 Morogoro 06 Pwani 07 Dar es salaam 08 Lindi 09 Mtwara 10 Ruvuma 11 Iringa 12 Mbeya 13 Singida 14 Tabora 15 Rukwa 16 Kigoma 17 Shinyanga 18 Kagera 19 Mwanza 20 Mara 21 Manyara 51 North Unguja 52 South Unguja 53 Urban West 54 North Pemba 55 South Pemba Forms of Land Use Forms of Land Use Forms of Land Use Forms of Land Use Forms of Land Use 1 Area under Temporary Mono-crops (eg maize only) 2 Area under Temporary Mixed crops (eg maize & beans) 3 Area under Permanent Mono-crops (eg Sisal only) 4 Area under Permanent Mixed crops (eg bananas & coffee) 5 Area under Permanent/Annual mix (eg bananas & maize) 6 Area under Permanent/Pasture mix (eg orange & pasture) 7 Area under Pasture only 8 Area under Fallow 9 Area under Natural Bush 10 Area under Planted Timber Trees 11 Area Rented to others 12 Area Unusable 13 Area of Uncultivated Usable land (excluding fallow) Area in Hectares Area in Hectares Area in Hectares Area in Hectares Area in Hectares 2.1 Using the options below indicate the type of farm owners 2.1 Using the options below indicate the type of farm owners 2.1 Using the options below indicate the type of farm owners 2.1 Using the options below indicate the type of farm owners 2.1 Using the options below indicate the type of farm owners 1 Government 2 Parastatal 3 Private registered 4 Private Non- registered 5 Other Region Region Region Region Region 01 Dodoma 02 Arusha 03 Kilimanjaro 04 Tanga 05 Morogoro 06 Pwani 07 Dar es salaam 08 Lindi 09 Mtwara 10 Ruvuma 11 Iringa 12 Mbeya 13 Singida 14 Tabora 15 Rukwa 16 Kigoma 17 Shinyanga 18 Kagera 19 Mwanza 20 Mara 21 Manyara 51 North Unguja 52 South Unguja 53 Urban West 54 North Pemba 55 South Pemba Farm Serial Number Farm Serial Number Farm Serial Number Farm Serial Number Farm Serial Number Crop Code Crop Code Crop Code Crop Code Crop Code 11 Maize 12 Paddy 13 Sorghum 14 Bulrush Millet 15 Finger Millet 16 Wheat 17 Barley 21 Cassava 22 Sweet potatoes 23 Irish Potatoes 24 Yams 25 Cocoyams 26 Onions 27 Ginger 30 Giligilani 31 Beans 32 Cowpeas 33 Green Grums 34 Mbaazi 35 Dengu 36 Njugu mawe 37 Njegere 38 Seed Beans 39 Green Beans 41 Sunflower 42 Ufuta 43 Groundnuts 47 Soya 48 Nyonyo 50 Cotton 51 Tobbacco 52 Pyrethrum 54 Coffee 55 Tea 60 Flowers (Seeds) 61 Flowers(Kukata) 62 Nyasi 63 Mikunde 75 Nanasi 81 Plums 82 Apples 83 Pears 84 Pithes 86 Cabbage 87 Tomatoes 88 Spinach 89 Carrots 90 Chillie 91 mchicha 92 Boga 93 Tango 94 Mabilinganya 95 Matikiti maji 96 Cauliflower 98 Kartam Area Planned Area Planned Area Planned Area Planned Area Planned Area Planted Area Planted Area Planted Area Planted Area Planted Area Harvested Area Harvested Area Harvested Area Harvested Area Harvested Irrigation Irrigation Irrigation Irrigation Irrigation 1 Used for the whole crop 2 Used on 3/4 of whole crop 3 Used on 1/2 of whole crop 4 Used on 1/4 of whole crop 5 Used on less than 1/4 of whole crop 6 Not used Amount Harvested Amount Harvested Amount Harvested Amount Harvested Amount Harvested Amount Stored Amount Stored Amount Stored Amount Stored Amount Stored Amount Marketed Amount Marketed Amount Marketed Amount Marketed Amount Marketed Transport to Market Transport to Market Transport to Market Transport to Market Transport to Market 1 Own Transport 2 Contract transport 3 Other Large scale Farm at farm gate 8 Other (specify) 9 Not applicable Main Market Main Market Main Market Main Market Main Market 1 Secondary Market 2 Cooperative 3 Trade at farm 4 Factory 5 Other Large Scale Farm 6 Exported market 8 Other 9 Not applicable Main marketing problem Main marketing problem Main marketing problem Main marketing problem Main marketing problem 1 Price too low 2 No transport 3 Transport cost too high 4 No buyer 5 Farmers association problems 6 Cooperative problems 7 Government Regulatory board problems 8 Lack of marketing information 9 Not applicable Region Region Region Region Region 01 Dodoma 02 Arusha 03 Kilimanjaro 04 Tanga 05 Morogoro 06 Pwani 07 Dar es salaam 08 Lindi 09 Mtwara 10 Ruvuma 11 Iringa 12 Mbeya 13 Singida 14 Tabora 15 Rukwa 16 Kigoma 17 Shinyanga 18 Kagera 19 Mwanza 20 Mara 21 Manyara 51 North Unguja 52 South Unguja 53 Urban West 54 North Pemba 55 South Pemba Farm Serial Number Farm Serial Number Farm Serial Number Farm Serial Number Farm Serial Number Crop Code Crop Code Crop Code Crop Code Crop Code 18 pilipili manga 21 Cassava 34 Pigeon pea 38 Matofaa 39 Embe ng'o/sakuwa 44 Coconut 45 Cashewnut 46 Palm oil 53 Sisal 54 Coffee 55 Tea 56 Cacao 57 Rubber 58 Wattle 59 Kapok 60 Sugarcane 61 Cardamon 62 Jute 63 Kenaf 64 Mdalasini 65 Kungumanga 66 Clove 67 Mashelisheli 68 Mbalungi 69 Fenesi 71 Banana 72 Avocado 73 Mangoes 74 Pawpaw 75 Minanasi 76 Oranges 77 Grapefruit 78 Grapes 79 Mandarine 80 Guaves 81 Matunda Damu 82 Apples 83 Peasi 84 Mifyoksi 85 Lemon 97 Doriani 98 Mbirimbi 99 Shokshoki TOTAL number of plants/ trees/bushes TOTAL number of plants/ trees/bushes TOTAL number of plants/ trees/bushes TOTAL number of plants/ trees/bushes TOTAL number of plants/ trees/bushes Number of mature plants/trees/bushes in MONO CROP. Number of mature plants/trees/bushes in MONO CROP. Number of mature plants/trees/bushes in MONO CROP. Number of mature plants/trees/bushes in MONO CROP. Number of mature plants/trees/bushes in MONO CROP. Area (ha) of mature plants/trees/bushes in MONO CROP. Area (ha) of mature plants/trees/bushes in MONO CROP. Area (ha) of mature plants/trees/bushes in MONO CROP. Area (ha) of mature plants/trees/bushes in MONO CROP. Area (ha) of mature plants/trees/bushes in MONO CROP. Irrigated area (ha) Irrigated area (ha) Irrigated area (ha) Irrigated area (ha) Irrigated area (ha) Number of mature plants/trees/bushes in MIXED CROP. Number of mature plants/trees/bushes in MIXED CROP. Number of mature plants/trees/bushes in MIXED CROP. Number of mature plants/trees/bushes in MIXED CROP. Number of mature plants/trees/bushes in MIXED CROP. Irrigation Irrigation Irrigation Irrigation Irrigation 1 Used for the whole crop 2 Used on 3/4 of whole crop 3 Used on 1/2 of whole crop 4 Used on 1/4 of whole crop 5 Used on less than 1/4 of whole crop 6 Not used Amount Harvested Amount Harvested Amount Harvested Amount Harvested Amount Harvested Amount Stored Amount Stored Amount Stored Amount Stored Amount Stored Amount Marketed Amount Marketed Amount Marketed Amount Marketed Amount Marketed Transport to market Transport to market Transport to market Transport to market Transport to market 1 Own Transport 2 Contract transport 3 Other Large scale Farm at farm gate 8 Other (specify) 9 Not applicable Main market Main market Main market Main market Main market 1 Secondary Market 2 Cooperative 3 Trade at farm 4 Factory 5 Other Large Scale Farm 6 Exported by farm 8 Other 9 Not applicable Main marketing problem Main marketing problem Main marketing problem Main marketing problem Main marketing problem 1 Price too low 2 No transport 3 Transport cost too high 4 No buyer 5 Farmers association problems 6 Cooperative problems 7 Government Regulatory board problems 8 Lack of marketing information 9 Not applicable Farm Serial Number Farm Serial Number Farm Serial Number Farm Serial Number Farm Serial Number Region Region Region Region Region 01 Dodoma 02 Arusha 03 Kilimanjaro 04 Tanga 05 Morogoro 06 Pwani 07 Dar es salaam 08 Lindi 09 Mtwara 10 Ruvuma 11 Iringa 12 Mbeya 13 Singida 14 Tabora 15 Rukwa 16 Kigoma 17 Shinyanga 18 Kagera 19 Mwanza 20 Mara 21 Manyara 51 North Unguja 52 South Unguja 53 Urban West 54 North Pemba 55 South Pemba Order of most importance Order of most importance Order of most importance Order of most importance Order of most importance 1 most important 2 2nd most important 3 3rd most important 4 4th most important 5 5the most important Constraint Constraint Constraint Constraint Constraint 1 AMOUNT OF LAND 2 OWNERSHIP OF LAND 3 COST OF LAND 4 LENGTH OF LAND TENURE 5 SOIL CULTIVATION 6 SOIL FERTILITY 7 ACCESS TO IMPROVED SEED 8 IRRIGATION FACILITIES 9 ACCESS TO CHEMICAL INPUTS 10 COST OF INPUTS 11 EXTENSION SERVICES 12 ACCESS TO FOREST RESOURCES 13 GOVERNMENT REGULATIONS 14 ACCESS TO CREDIT 15 HARVESTING 16 THRESHING 17 STORAGE 18 PROCESSING 19 MARKET INFORMATION 20 TRANSPORT COSTS 21 DISTRUCTION BY ANIMALS 22 STEALING 23 PESTS AND DISEASES 24 LOCAL GOVERNMENT TAXATION 25 ACCESS TO OFF-FARM INCOME 26 COST OF MACHINERY 27 AVAILABILITY OF LIVESTOCK DRUGS 28 LIVESTOCK DISEASES 29 AVAILABILITY OF PASTURE 30 KIANGAZI CHA MUDA MREFU 31 UGOMVI KATI YA WAKULIMA NA WAFUGAJI Farm Serial Number Farm Serial Number Farm Serial Number Farm Serial Number Farm Serial Number Region Region Region Region Region 01 Dodoma 02 Arusha 03 Kilimanjaro 04 Tanga 05 Morogoro 06 Pwani 07 Dar es salaam 08 Lindi 09 Mtwara 10 Ruvuma 11 Iringa 12 Mbeya 13 Singida 14 Tabora 15 Rukwa 16 Kigoma 17 Shinyanga 18 Kagera 19 Mwanza 20 Mara 21 Manyara 51 North Unguja 52 South Unguja 53 Urban West 54 North Pemba 55 South Pemba Operation/inputs Operation/inputs Operation/inputs Operation/inputs Operation/inputs 1 Soil preparation & planting 2 Seed/planting material 3 Inorganic fertiliser 4 Organic fertiliser 5 Herbicides 6 Fungicides 7 Pesticides 8 Harvesting/threshing 9 Drying costs 10 Labour costs 11 Transportation cost Used Used Used Used Used 1 Used for the whole crop 2 Used on 3/4 of whole crop 3 Used on 1/2 of whole crop 4 Used on 1/4 of whole crop 5 Used on less than 1/4 of whole crop 6 Not used Cost/hectare Cost/hectare Cost/hectare Cost/hectare Cost/hectare Used Used Used Used Used 1 Used for the whole crop 2 Used on 3/4 of whole crop 3 Used on 1/2 of whole crop 4 Used on 1/4 of whole crop 5 Used on less than 1/4 of whole crop 6 Not used Cost/hectare Cost/hectare Cost/hectare Cost/hectare Cost/hectare Used Used Used Used Used 1 Used for the whole crop 2 Used on 3/4 of whole crop 3 Used on 1/2 of whole crop 4 Used on 1/4 of whole crop 5 Used on less than 1/4 of whole crop 6 Not used Cost/hectare Cost/hectare Cost/hectare Cost/hectare Cost/hectare Main Source of inputs Main Source of inputs Main Source of inputs Main Source of inputs Main Source of inputs 1 Imported by farm 2 Purchased from tanzania factory 3 Produced on farm 4 Private seller/NGO 5 Government Institution 8 Other Region Region Region Region Region 01 Dodoma 02 Arusha 03 Kilimanjaro 04 Tanga 05 Morogoro 06 Pwani 07 Dar es salaam 08 Lindi 09 Mtwara 10 Ruvuma 11 Iringa 12 Mbeya 13 Singida 14 Tabora 15 Rukwa 16 Kigoma 17 Shinyanga 18 Kagera 19 Mwanza 20 Mara 21 Manyara 51 North Unguja 52 South Unguja 53 Urban West 54 North Pemba 55 South Pemba Farm Serial Number Farm Serial Number Farm Serial Number Farm Serial Number Farm Serial Number Product Product Product Product Product 1 Eggs 2 Hides 3 Skins Number Sold Number Sold Number Sold Number Sold Number Sold Average price/unit sold Average price/unit sold Average price/unit sold Average price/unit sold Average price/unit sold Number Consumed/utilised Number Consumed/utilised Number Consumed/utilised Number Consumed/utilised Number Consumed/utilised Average price/unit consumed/utilised Average price/unit consumed/utilised Average price/unit consumed/utilised Average price/unit consumed/utilised Average price/unit consumed/utilised Region Region Region Region Region 01 Dodoma 02 Arusha 03 Kilimanjaro 04 Tanga 05 Morogoro 06 Pwani 07 Dar es salaam 08 Lindi 09 Mtwara 10 Ruvuma 11 Iringa 12 Mbeya 13 Singida 14 Tabora 15 Rukwa 16 Kigoma 17 Shinyanga 18 Kagera 19 Mwanza 20 Mara 21 Manyara 51 North Unguja 52 South Unguja 53 Urban West 54 North Pemba 55 South Pemba Farm Serial Number Farm Serial Number Farm Serial Number Farm Serial Number Farm Serial Number Importance of outlet Importance of outlet Importance of outlet Importance of outlet Importance of outlet 1 1st 2 2nd 3 3rd 4 4th 5 5th Outlet for Cattle Outlet for Cattle Outlet for Cattle Outlet for Cattle Outlet for Cattle 1 Trader at farm 2 Local Market 3 Secondary market/auction. 4 Abattoir 5 Another farmer 8 Other (Specify) Outlet for Goat Outlet for Goat Outlet for Goat Outlet for Goat Outlet for Goat 1 Trader at farm 2 Local Market 3 Secondary market/auction. 4 Abattoir 5 Another farmer 8 Other (Specify) Outlet for Sheep Outlet for Sheep Outlet for Sheep Outlet for Sheep Outlet for Sheep 1 Trader at farm 2 Local Market 3 Secondary market/auction. 4 Abattoir 5 Another farmer 8 Other (Specify) Outlet for Chickens Outlet for Chickens Outlet for Chickens Outlet for Chickens Outlet for Chickens 1 Trader at farm 2 Local Market 3 Secondary market/auction. 4 Abattoir 5 Another farmer 8 Other (Specify) Outlet for Pigs Outlet for Pigs Outlet for Pigs Outlet for Pigs Outlet for Pigs 1 Trader at farm 2 Local Market 3 Secondary market/auction. 4 Abattoir 5 Another farmer 8 Other (Specify) Farm Serial Number Farm Serial Number Farm Serial Number Farm Serial Number Farm Serial Number Region Region Region Region Region 01 Dodoma 02 Arusha 03 Kilimanjaro 04 Tanga 05 Morogoro 06 Pwani 07 Dar es salaam 08 Lindi 09 Mtwara 10 Ruvuma 11 Iringa 12 Mbeya 13 Singida 14 Tabora 15 Rukwa 16 Kigoma 17 Shinyanga 18 Kagera 19 Mwanza 20 Mara 21 Manyara 51 North Unguja 52 South Unguja 53 Urban West 54 North Pemba 55 South Pemba 2.1 Using the options below indicate the type of farm owners 2.1 Using the options below indicate the type of farm owners 2.1 Using the options below indicate the type of farm owners 2.1 Using the options below indicate the type of farm owners 2.1 Using the options below indicate the type of farm owners 1 Government 2 Parastatal 3 Private registered 4 Private Non- registered 5 Other Staff/employee type Staff/employee type Staff/employee type Staff/employee type Staff/employee type 1 General manager/Financial managers/accountants 2 Clerical/typest/receptionist staff 3 Mechanical/workshop/parts stores manage 4 Crop/livestock husbandry managers/agronomists 5 Irrigation engineers 6 Product Stores managers 7 Agroprocessing/Mill managers 8 Other Professoinal staff 9 Supervisor staff 10 Labourers Number of permanent employee (Male) Number of permanent employee (Male) Number of permanent employee (Male) Number of permanent employee (Male) Number of permanent employee (Male) Number of permanent employee (Female) Number of permanent employee (Female) Number of permanent employee (Female) Number of permanent employee (Female) Number of permanent employee (Female) Number of part time employees (Male) Number of part time employees (Male) Number of part time employees (Male) Number of part time employees (Male) Number of part time employees (Male) Number of part time employees (Female) Number of part time employees (Female) Number of part time employees (Female) Number of part time employees (Female) Number of part time employees (Female) Farm Serial Number Farm Serial Number Farm Serial Number Farm Serial Number Farm Serial Number Region Region Region Region Region 01 Dodoma 02 Arusha 03 Kilimanjaro 04 Tanga 05 Morogoro 06 Pwani 07 Dar es salaam 08 Lindi 09 Mtwara 10 Ruvuma 11 Iringa 12 Mbeya 13 Singida 14 Tabora 15 Rukwa 16 Kigoma 17 Shinyanga 18 Kagera 19 Mwanza 20 Mara 21 Manyara 51 North Unguja 52 South Unguja 53 Urban West 54 North Pemba 55 South Pemba Type of Service Type of Service Type of Service Type of Service Type of Service 1 Cultivation /soil preparation 2 Weeding and Herbicides 3 Harvesting Provides service to outgrowers Provides service to outgrowers Provides service to outgrowers Provides service to outgrowers Provides service to outgrowers 1 Yes 2 No Number of Outgrower farms Number of Outgrower farms Number of Outgrower farms Number of Outgrower farms Number of Outgrower farms Area which got service (hectare) Area which got service (hectare) Area which got service (hectare) Area which got service (hectare) Area which got service (hectare) Is this service paid? Is this service paid? Is this service paid? Is this service paid? Is this service paid? 1 Yes 2 No Average cost (Per hectare) Average cost (Per hectare) Average cost (Per hectare) Average cost (Per hectare) Average cost (Per hectare) Q1111_C2=1 (FILTER) Q1111_C2=1 (FILTER) Q1111_C2=1 (FILTER) Q1111_C2=1 (FILTER) Q1111_C2=1 (FILTER) Not Selected 1 Selected Region Region Region Region Region 01 Dodoma 02 Arusha 03 Kilimanjaro 04 Tanga 05 Morogoro 06 Pwani 07 Dar es salaam 08 Lindi 09 Mtwara 10 Ruvuma 11 Iringa 12 Mbeya 13 Singida 14 Tabora 15 Rukwa 16 Kigoma 17 Shinyanga 18 Kagera 19 Mwanza 20 Mara 21 Manyara 51 North Unguja 52 South Unguja 53 Urban West 54 North Pemba 55 South Pemba Type of Service Type of Service Type of Service Type of Service Type of Service 1 Storing 2 Crop processing 3 Cattle fattening 4 Crop marketing 5 Livestock facilities 6 Livestock products 7 Livestock marketing 8 Extension services 9 Dipping services Provides service to outgrowers Provides service to outgrowers Provides service to outgrowers Provides service to outgrowers Provides service to outgrowers 1 Yes 2 No Number of Outgrower farms Number of Outgrower farms Number of Outgrower farms Number of Outgrower farms Number of Outgrower farms Crop Quantity(tonne) Crop Quantity(tonne) Crop Quantity(tonne) Crop Quantity(tonne) Crop Quantity(tonne) Is this service paid? Is this service paid? Is this service paid? Is this service paid? Is this service paid? 1 Yes 2 No Average cost (Shilling per metric tonne) Average cost (Shilling per metric tonne) Average cost (Shilling per metric tonne) Average cost (Shilling per metric tonne) Average cost (Shilling per metric tonne) Farm Serial Number Farm Serial Number Farm Serial Number Farm Serial Number Farm Serial Number Q1111_C2=1 (FILTER) Q1111_C2=1 (FILTER) Q1111_C2=1 (FILTER) Q1111_C2=1 (FILTER) Q1111_C2=1 (FILTER) Not Selected 1 Selected Farm Serial Number Farm Serial Number Farm Serial Number Farm Serial Number Farm Serial Number Region Region Region Region Region 01 Dodoma 02 Arusha 03 Kilimanjaro 04 Tanga 05 Morogoro 06 Pwani 07 Dar es salaam 08 Lindi 09 Mtwara 10 Ruvuma 11 Iringa 12 Mbeya 13 Singida 14 Tabora 15 Rukwa 16 Kigoma 17 Shinyanga 18 Kagera 19 Mwanza 20 Mara 21 Manyara 51 North Unguja 52 South Unguja 53 Urban West 54 North Pemba 55 South Pemba Type of Service Type of Service Type of Service Type of Service Type of Service 1 Storing 2 Crop processing 3 Cattle fattening 4 Crop marketing 5 Livestock facilities 6 Livestock products 7 Livestock marketing 8 Extension services 9 Dipping services Provides service to outgrowers Provides service to outgrowers Provides service to outgrowers Provides service to outgrowers Provides service to outgrowers 1 Yes 2 No Number of Outgrower farms Number of Outgrower farms Number of Outgrower farms Number of Outgrower farms Number of Outgrower farms Crop Quantity(tonne) Crop Quantity(tonne) Crop Quantity(tonne) Crop Quantity(tonne) Crop Quantity(tonne) Is this service paid? Is this service paid? Is this service paid? Is this service paid? Is this service paid? 1 Yes 2 No Average cost (Shilling per metric tonne) Average cost (Shilling per metric tonne) Average cost (Shilling per metric tonne) Average cost (Shilling per metric tonne) Average cost (Shilling per metric tonne) Region Region Region Region Region 01 Dodoma 02 Arusha 03 Kilimanjaro 04 Tanga 05 Morogoro 06 Pwani 07 Dar es salaam 08 Lindi 09 Mtwara 10 Ruvuma 11 Iringa 12 Mbeya 13 Singida 14 Tabora 15 Rukwa 16 Kigoma 17 Shinyanga 18 Kagera 19 Mwanza 20 Mara 21 Manyara 51 North Unguja 52 South Unguja 53 Urban West 54 North Pemba 55 South Pemba Farm Serial Number Farm Serial Number Farm Serial Number Farm Serial Number Farm Serial Number Crop Code Crop Code Crop Code Crop Code Crop Code 11 Maize 12 Paddy 13 Sorghum 14 Bulrush Millet 15 Finger Millet 16 Wheat 17 Barley 21 Cassava 22 Sweet potatoes 23 Irish Potatoes 24 Yams 25 Cocoyams 26 Onions 27 Ginger 30 Giligilani 31 Beans 32 Cowpeas 33 Green Grums 34 Mbaazi 35 Dengu 36 Njugu mawe 37 Njegere 38 Seed Beans 39 Green Beans 41 Sunflower 42 Ufuta 43 Groundnuts 47 Soya 48 Nyonyo 50 Cotton 51 Tobbacco 52 Pyrethrum 54 Coffee 55 Tea 60 Flowers (Seeds) 61 Flowers(Kukata) 62 Nyasi 63 Mikunde 75 Nanasi 81 Plums 82 Apples 83 Pears 84 Pithes 86 Cabbage 87 Tomatoes 88 Spinach 89 Carrots 90 Chillie 91 mchicha 92 Boga 93 Tango 94 Mabilinganya 95 Matikiti maji 96 Cauliflower 98 Kartam Area Planned Area Planned Area Planned Area Planned Area Planned Area Planted Area Planted Area Planted Area Planted Area Planted Area Harvested Area Harvested Area Harvested Area Harvested Area Harvested Irrigation Irrigation Irrigation Irrigation Irrigation 1 Used for the whole crop 2 Used on 3/4 of whole crop 3 Used on 1/2 of whole crop 4 Used on 1/4 of whole crop 5 Used on less than 1/4 of whole crop 6 Not used Amount Harvested Amount Harvested Amount Harvested Amount Harvested Amount Harvested Amount Stored Amount Stored Amount Stored Amount Stored Amount Stored Amount Marketed Amount Marketed Amount Marketed Amount Marketed Amount Marketed Transport to market Transport to market Transport to market Transport to market Transport to market 1 Own Transport 2 Contract transport 3 Other Large scale Farm at farm gate 8 Other (specify) 9 Not applicable Main Market Main Market Main Market Main Market Main Market 1 Secondary Market 2 Cooperative 3 Trade at farm 4 Factory 5 Other Large Scale Farm 6 Exported market 8 Other 9 Not applicable Main marketing problem Main marketing problem Main marketing problem Main marketing problem Main marketing problem 1 Price too low 2 No transport 3 Transport cost too high 4 No buyer 5 Farmers association problems 6 Cooperative problems 7 Government Regulatory board problems 8 Lack of marketing information 9 Not applicable Region Region Region Region Region 01 Dodoma 02 Arusha 03 Kilimanjaro 04 Tanga 05 Morogoro 06 Pwani 07 Dar es salaam 08 Lindi 09 Mtwara 10 Ruvuma 11 Iringa 12 Mbeya 13 Singida 14 Tabora 15 Rukwa 16 Kigoma 17 Shinyanga 18 Kagera 19 Mwanza 20 Mara 21 Manyara 51 North Unguja 52 South Unguja 53 Urban West 54 North Pemba 55 South Pemba Farm Serial Number Farm Serial Number Farm Serial Number Farm Serial Number Farm Serial Number Crop Code Crop Code Crop Code Crop Code Crop Code 11 Maize 12 Paddy 13 Sorghum 14 Bulrush Millet 15 Finger Millet 16 Wheat 17 Barley 21 Cassava 22 Sweet Potatoes 23 Irish potatoes 24 Yams 25 Cocoyams 26 Onions 27 Ginger 31 Beans 32 Cowpeas 33 Green gram 34 Pigeon peas 35 Chick peas 36 Bambara nuts 41 Sunflower 42 Simsim 43 Groundnut 44 Oil Palm 45 Coconut 46 Cashewnut 47 Soya beans 48 Caster seed 50 Cotton 51 Tobacco 52 Sisal 53 Pyrethrum 54 Coffee 55 Tea 56 Cocoa 57 Rubber 58 Wattle 59 Kapok 60 Sugar Cane 61 Cardamom 62 Jute 71 Banana 72 Avocado 73 Mango 74 Paw paw 75 Pineapple 76 Orange 77 Grape fruit 78 Grapes 79 Mandarin 80 Guava 81 Plums 82 Apples 83 Pears 84 Peaches 85 Lime/Lemon 86 Cabbage 87 Tomatoes 88 Spinach 89 Carrot 90 Chillies 91 Amaranths 92 Pumpkins 93 Cucumber 94 Egg Plant 95 Water Mellon 96 Cauliflower Used for Used for Used for Used for Used for 1 Feeding to livestock 2 Building material 3 Fuel 4 Used for processing 5 Composting 8 Other Unit Unit Unit Unit Unit 1 Loose Bundle/bunch 2 Compressed bunch/Bail 3 Metric tonne 4 Kilogram 5 Litre 8 Other(specify) Total no. of Units Total no. of Units Total no. of Units Total no. of Units Total no. of Units Number of Units sold Number of Units sold Number of Units sold Number of Units sold Number of Units sold Total value per unit (Tsh.) Total value per unit (Tsh.) Total value per unit (Tsh.) Total value per unit (Tsh.) Total value per unit (Tsh.) Total value of sold units Total value of sold units Total value of sold units Total value of sold units Total value of sold units Region Region Region Region Region 01 Dodoma 02 Arusha 03 Kilimanjaro 04 Tanga 05 Morogoro 06 Pwani 07 Dar es salaam 08 Lindi 09 Mtwara 10 Ruvuma 11 Iringa 12 Mbeya 13 Singida 14 Tabora 15 Rukwa 16 Kigoma 17 Shinyanga 18 Kagera 19 Mwanza 20 Mara 21 Manyara 51 North Unguja 52 South Unguja 53 Urban West 54 North Pemba 55 South Pemba Farm Serial Number Farm Serial Number Farm Serial Number Farm Serial Number Farm Serial Number Crop Code Crop Code Crop Code Crop Code Crop Code 11 Maize 12 Paddy 13 Sorghum 14 Bulrush Millet 15 Finger Millet 16 Wheat 17 Barley 21 Cassava 22 Sweet Potatoes 23 Irish potatoes 24 Yams 25 Cocoyams 26 Onions 27 Ginger 31 Beans 32 Cowpeas 33 Green gram 34 Pigeon peas 35 Chick peas 36 Bambara nuts 41 Sunflower 42 Simsim 43 Groundnut 44 Oil Palm 45 Coconut 46 Cashewnut 47 Soya beans 48 Caster seed 50 Cotton 51 Tobacco 52 Sisal 53 Pyrethrum 54 Coffee 55 Tea 56 Cocoa 57 Rubber 58 Wattle 59 Kapok 60 Sugar Cane 61 Cardamom 62 Jute 67 Makadamia 71 Banana 72 Avocado 73 Mango 74 Paw paw 75 Pineapple 76 Orange 77 Grape fruit 78 Grapes 79 Mandarin 80 Guava 81 Plums 82 Apples 83 Pears 84 Peaches 85 Lime/Lemon 86 Cabbage 87 Tomatoes 88 Spinach 89 Carrot 90 Chillies 91 Amaranths 92 Pumpkins 93 Cucumber 94 Egg Plant 95 Water Mellon 96 Cauliflower Quantity of Farm Produce (tonne) Quantity of Farm Produce (tonne) Quantity of Farm Produce (tonne) Quantity of Farm Produce (tonne) Quantity of Farm Produce (tonne) Quantity of Outgrower/other farmer's produce (t) Quantity of Outgrower/other farmer's produce (t) Quantity of Outgrower/other farmer's produce (t) Quantity of Outgrower/other farmer's produce (t) Quantity of Outgrower/other farmer's produce (t) Main Product code Main Product code Main Product code Main Product code Main Product code 1 Flour/meal 2 Grain 3 Oil 4 Juice 5 Fiber 8 Other(specify) Used for Used for Used for Used for Used for 1 Sale 2 Animal consumption 3 On farm factory processing 8 Other (specify) Unit Unit Unit Unit Unit 1 Loose bundle/bunch 2 Compressed bunch/bail 3 Metric tonne 4 Kilogram 5 Litre 8 Other (specify) Quantity of main product Quantity of main product Quantity of main product Quantity of main product Quantity of main product Where processed Where processed Where processed Where processed Where processed 1 On-Farm machine 2 Cooperative Union factory 3 Other Large scale farm 4 Private factory/Mill 8 Other (specify) Where sold Where sold Where sold Where sold Where sold 1 Secondary Market 2 Marketing Coop 3 Other Largescale farm 4 Trader at farm 5 Factory/Mill 6 Exported by farm 8 Other (specify) bi-product code bi-product code bi-product code bi-product code bi-product code 1 Bran 2 Cake 3 Husk 4 Juice 5 Fiber 6 Pulp 7 Oil 8 Other(specify) 9 Shell Used Used Used Used Used 1 Sale 2 Animal consumption 3 On farm factory processing 8 Other (specify) Unit Unit Unit Unit Unit 1 Loose bundle/bunch 2 Compressed bunch/bail 3 Metric tonne 4 Kilogram 5 Litre 8 Other (specify) Quantity Quantity Quantity Quantity Quantity Quantity sold Quantity sold Quantity sold Quantity sold Quantity sold bi-product code bi-product code bi-product code bi-product code bi-product code 1 Bran 2 Cake 3 Husk 4 Juice 5 Fiber 6 Pulp 7 Oil 8 Other(specify) 9 Shell Used Used Used Used Used 1 Sale 2 Animal consumption 3 On farm factory processing 8 Other (specify) Unit Unit Unit Unit Unit 1 Loose bundle/bunch 2 Compressed bunch/bail 3 Metric tonne 4 Kilogram 5 Litre 8 Other (specify) Quantity Quantity Quantity Quantity Quantity Quantity sold Quantity sold Quantity sold Quantity sold Quantity sold Region Region Region Region Region 01 Dodoma 02 Arusha 03 Kilimanjaro 04 Tanga 05 Morogoro 06 Pwani 07 Dar es salaam 08 Lindi 09 Mtwara 10 Ruvuma 11 Iringa 12 Mbeya 13 Singida 14 Tabora 15 Rukwa 16 Kigoma 17 Shinyanga 18 Kagera 19 Mwanza 20 Mara 21 Manyara 51 North Unguja 52 South Unguja 53 Urban West 54 North Pemba 55 South Pemba Farm Serial Number Farm Serial Number Farm Serial Number Farm Serial Number Farm Serial Number Crop Code Crop Code Crop Code Crop Code Crop Code 11 Maize 12 Paddy 13 Sorghum 14 Bulrush Millet 15 Finger Millet 16 Wheat 17 Barley 21 Cassava 22 Sweet Potatoes 23 Irish potatoes 24 Yams 25 Cocoyams 26 Onions 27 Ginger 31 Beans 32 Cowpeas 33 Green gram 34 Pigeon peas 35 Chick peas 36 Bambara nuts 41 Sunflower 42 Simsim 43 Groundnut 44 Oil Palm 45 Coconut 46 Cashewnut 47 Soya beans 48 Caster seed 50 Cotton 51 Tobacco 52 Sisal 53 Pyrethrum 54 Coffee 55 Tea 56 Cocoa 57 Rubber 58 Wattle 59 Kapok 60 Sugar Cane 61 Cardamom 62 Jute 71 Banana 72 Avocado 73 Mango 74 Paw paw 75 Pineapple 76 Orange 77 Grape fruit 78 Grapes 79 Mandarin 80 Guava 81 Plums 82 Apples 83 Pears 84 Peaches 85 Lime/Lemon 86 Cabbage 87 Tomatoes 88 Spinach 89 Carrot 90 Chillies 91 Amaranths 92 Pumpkins 93 Cucumber 94 Egg Plant 95 Water Mellon 96 Cauliflower Quantity of Farm Produce (tonne) Quantity of Farm Produce (tonne) Quantity of Farm Produce (tonne) Quantity of Farm Produce (tonne) Quantity of Farm Produce (tonne) Quantity of Outgrower/other farmer's produce (t) Quantity of Outgrower/other farmer's produce (t) Quantity of Outgrower/other farmer's produce (t) Quantity of Outgrower/other farmer's produce (t) Quantity of Outgrower/other farmer's produce (t) Main Product code Main Product code Main Product code Main Product code Main Product code 1 Flour/meal 2 Grain 3 Oil 4 Juice 5 Fiber 8 Other(specify) Used for Used for Used for Used for Used for 1 Sale 2 Animal consumption 3 On farm factory processing 8 Other (specify) Unit Unit Unit Unit Unit 1 Loose bundle/bunch 2 Compressed bunch/bail 3 Metric tonne 4 Kilogram 5 Litre 8 Other (specify) Quantity of main product Quantity of main product Quantity of main product Quantity of main product Quantity of main product Where processed Where processed Where processed Where processed Where processed 1 On-Farm machine 2 Cooperative Union factory 3 Other Large scale farm 4 Private factory/Mill 8 Other (specify) Where sold Where sold Where sold Where sold Where sold 1 Secondary Market 2 Marketing Coop 3 Other Largescale farm 4 Trader at farm 5 Factory/Mill 6 Exported by farm 8 Other (specify) bi-product code bi-product code bi-product code bi-product code bi-product code 1 Bran 2 Cake 3 Husk 4 Juice 5 Fiber 6 Pulp 7 Oil 8 Other(specify) 9 Shell Used Used Used Used Used 1 Sale 2 Animal consumption 3 On farm factory processing 8 Other (specify) Unit Unit Unit Unit Unit 1 Loose bundle/bunch 2 Compressed bunch/bail 3 Metric tonne 4 Kilogram 5 Litre 8 Other (specify) Quantity Quantity Quantity Quantity Quantity Quantity sold Quantity sold Quantity sold Quantity sold Quantity sold bi-product code bi-product code bi-product code bi-product code bi-product code 1 Bran 2 Cake 3 Husk 4 Juice 5 Fiber 6 Pulp 7 Oil 8 Other(specify) 9 Shell Used Used Used Used Used 1 Sale 2 Animal consumption 3 On farm factory processing 8 Other (specify) Unit Unit Unit Unit Unit 1 Loose bundle/bunch 2 Compressed bunch/bail 3 Metric tonne 4 Kilogram 5 Litre 8 Other (specify) Quantity Quantity Quantity Quantity Quantity Quantity sold Quantity sold Quantity sold Quantity sold Quantity sold Farm Serial Number Farm Serial Number Farm Serial Number Farm Serial Number Farm Serial Number Region Region Region Region Region 01 Dodoma 02 Arusha 03 Kilimanjaro 04 Tanga 05 Morogoro 06 Pwani 07 Dar es salaam 08 Lindi 09 Mtwara 10 Ruvuma 11 Iringa 12 Mbeya 13 Singida 14 Tabora 15 Rukwa 16 Kigoma 17 Shinyanga 18 Kagera 19 Mwanza 20 Mara 21 Manyara 51 North Unguja 52 South Unguja 53 Urban West 54 North Pemba 55 South Pemba Use of credit on Machine/Equipments Use of credit on Machine/Equipments Use of credit on Machine/Equipments Use of credit on Machine/Equipments Use of credit on Machine/Equipments 1 Labour 2 Seeds 3 Fertilisers 4 Agrochemicals 5 Livestock purchase 6 Livestock Feed 7 Tools 8 Fences 9 Stores 10 Irrigation structures 11 Machinery 12 Other Source A Source A Source A Source A Source A 1 Company owning the farm 2 Commercial Bank 3 Savings and Credit Soc. 4 Religious Organisation/NGO/Project 8 Other (Specify) Source B Source B Source B Source B Source B 1 Company owning the farm 2 Commercial Bank 3 Savings and Credit Soc. 4 Religious Organisation/NGO/Project 8 Other (Specify) Source C Source C Source C Source C Source C 1 Company owning the farm 2 Commercial Bank 3 Savings and Credit Soc. 4 Religious Organisation/NGO/Project 8 Other (Specify) Farm Serial Number Farm Serial Number Farm Serial Number Farm Serial Number Farm Serial Number Region Region Region Region Region 01 Dodoma 02 Arusha 03 Kilimanjaro 04 Tanga 05 Morogoro 06 Pwani 07 Dar es salaam 08 Lindi 09 Mtwara 10 Ruvuma 11 Iringa 12 Mbeya 13 Singida 14 Tabora 15 Rukwa 16 Kigoma 17 Shinyanga 18 Kagera 19 Mwanza 20 Mara 21 Manyara 51 North Unguja 52 South Unguja 53 Urban West 54 North Pemba 55 South Pemba Value of Credit Value of Credit Value of Credit Value of Credit Value of Credit 13 Value of Credit 14 Value of Repayment Source A Source A Source A Source A Source A Source B Source B Source B Source B Source B Source C Source C Source C Source C Source C Farm Serial Number Farm Serial Number Farm Serial Number Farm Serial Number Farm Serial Number Region Region Region Region Region 01 Dodoma 02 Arusha 03 Kilimanjaro 04 Tanga 05 Morogoro 06 Pwani 07 Dar es salaam 08 Lindi 09 Mtwara 10 Ruvuma 11 Iringa 12 Mbeya 13 Singida 14 Tabora 15 Rukwa 16 Kigoma 17 Shinyanga 18 Kagera 19 Mwanza 20 Mara 21 Manyara 51 North Unguja 52 South Unguja 53 Urban West 54 North Pemba 55 South Pemba Type of structure/accessory Type of structure/accessory Type of structure/accessory Type of structure/accessory Type of structure/accessory 1 Cattle Dip 2 Spray Race 3 Hand powered sprayer 4 Cattle crush 5 Primary Market 6 Secondary Market 7 Abattoir 8 Slaughter Slab 9 Hide/skin shed 10 Input supply 11 Veterinary Clinic 12 Holding ground 13 Watering point/dam 14 Drencher Source of structure Source of structure Source of structure Source of structure Source of structure 1 Owns 2 Cooperative 3 Local farmers association 4 Govt extension/veterinary 5 Development project 6 NGO 7 Large scale farm. 8 Other 9 Not applicable Distance to structure Distance to structure Distance to structure Distance to structure Distance to structure Distance to nearest functional structure/Service Distance to nearest functional structure/Service Distance to nearest functional structure/Service Distance to nearest functional structure/Service Distance to nearest functional structure/Service 1 Less than 5 2 5 - 9 3 10 - 14 4 15 - 19 5 20 - 29 6 30 - 49 7 More than 50 Farm Serial Number Farm Serial Number Farm Serial Number Farm Serial Number Farm Serial Number Region Region Region Region Region 01 Dodoma 02 Arusha 03 Kilimanjaro 04 Tanga 05 Morogoro 06 Pwani 07 Dar es salaam 08 Lindi 09 Mtwara 10 Ruvuma 11 Iringa 12 Mbeya 13 Singida 14 Tabora 15 Rukwa 16 Kigoma 17 Shinyanga 18 Kagera 19 Mwanza 20 Mara 21 Manyara 51 North Unguja 52 South Unguja 53 Urban West 54 North Pemba 55 South Pemba 2.1 Using the options below indicate the type of farm owners 2.1 Using the options below indicate the type of farm owners 2.1 Using the options below indicate the type of farm owners 2.1 Using the options below indicate the type of farm owners 2.1 Using the options below indicate the type of farm owners 1 GOVERNMENT 2 PARASTATAL 3 PRIVATE REGISTERED 4 PRIVATE NON- REGISTERED 5 OTHER Cattle type Cattle type Cattle type Cattle type Cattle type 1 Castrated Bulls(Oxen) 2 Uncastred Bulls 3 Cows 4 Steers 5 Heifers 6 Male Calves 7 Female Calves Number of Indigenous Number of Indigenous Number of Indigenous Number of Indigenous Number of Indigenous Number of Improved Beef Number of Improved Beef Number of Improved Beef Number of Improved Beef Number of Improved Beef Number of Improved Dairy Number of Improved Dairy Number of Improved Dairy Number of Improved Dairy Number of Improved Dairy Total Total Total Total Total Region Region Region Region Region 01 Dodoma 02 Arusha 03 Kilimanjaro 04 Tanga 05 Morogoro 06 Pwani 07 Dar es salaam 08 Lindi 09 Mtwara 10 Ruvuma 11 Iringa 12 Mbeya 13 Singida 14 Tabora 15 Rukwa 16 Kigoma 17 Shinyanga 18 Kagera 19 Mwanza 20 Mara 21 Manyara 51 North Unguja 52 South Unguja 53 Urban West 54 North Pemba 55 South Pemba Farm Serial Number Farm Serial Number Farm Serial Number Farm Serial Number Farm Serial Number Type of livestock/Product Type of livestock/Product Type of livestock/Product Type of livestock/Product Type of livestock/Product 1 Milk (Indigenous cattle) 2 Milk (Improved cattle) Amount of milk obtained during 2007/08 Amount of milk obtained during 2007/08 Amount of milk obtained during 2007/08 Amount of milk obtained during 2007/08 Amount of milk obtained during 2007/08 Number Livestock milked 2007/08 Number Livestock milked 2007/08 Number Livestock milked 2007/08 Number Livestock milked 2007/08 Number Livestock milked 2007/08 Average price per litre 2007/08 Average price per litre 2007/08 Average price per litre 2007/08 Average price per litre 2007/08 Average price per litre 2007/08 Place sold Place sold Place sold Place sold Place sold 1 Neighbour 2 Local Market 3 Secondary Market 4 Processing industry 5 Largescale farm 6 Trader at Farm 7 Did not sell 8 Other (specify) Farm Serial Number Farm Serial Number Farm Serial Number Farm Serial Number Farm Serial Number Region Region Region Region Region 01 Dodoma 02 Arusha 03 Kilimanjaro 04 Tanga 05 Morogoro 06 Pwani 07 Dar es salaam 08 Lindi 09 Mtwara 10 Ruvuma 11 Iringa 12 Mbeya 13 Singida 14 Tabora 15 Rukwa 16 Kigoma 17 Shinyanga 18 Kagera 19 Mwanza 20 Mara 21 Manyara 51 North Unguja 52 South Unguja 53 Urban West 54 North Pemba 55 South Pemba Goat type Goat type Goat type Goat type Goat type 1 Ram 2 Castrated Goat 3 She Goat 4 Male Kid 5 She Kid Number of Indigenous Number of Indigenous Number of Indigenous Number of Indigenous Number of Indigenous Number of Improved goat for meat Number of Improved goat for meat Number of Improved goat for meat Number of Improved goat for meat Number of Improved goat for meat Number of Improved goat Dairy Number of Improved goat Dairy Number of Improved goat Dairy Number of Improved goat Dairy Number of Improved goat Dairy Total Total Total Total Total 2.1 Using the options below indicate the type of farm owners 2.1 Using the options below indicate the type of farm owners 2.1 Using the options below indicate the type of farm owners 2.1 Using the options below indicate the type of farm owners 2.1 Using the options below indicate the type of farm owners 1 GOVERNMENT 2 PARASTATAL 3 PRIVATE REGISTERED 4 PRIVATE NON- REGISTERED 5 OTHER Region Region Region Region Region 01 Dodoma 02 Arusha 03 Kilimanjaro 04 Tanga 05 Morogoro 06 Pwani 07 Dar es salaam 08 Lindi 09 Mtwara 10 Ruvuma 11 Iringa 12 Mbeya 13 Singida 14 Tabora 15 Rukwa 16 Kigoma 17 Shinyanga 18 Kagera 19 Mwanza 20 Mara 21 Manyara 51 North Unguja 52 South Unguja 53 Urban West 54 North Pemba 55 South Pemba Farm Serial Number Farm Serial Number Farm Serial Number Farm Serial Number Farm Serial Number Season Season Season Season Season 1 Wet Season 2 Dry Season Amount of milk obtained during 2007/08 Amount of milk obtained during 2007/08 Amount of milk obtained during 2007/08 Amount of milk obtained during 2007/08 Amount of milk obtained during 2007/08 Number of goats milked 2007/08 Number of goats milked 2007/08 Number of goats milked 2007/08 Number of goats milked 2007/08 Number of goats milked 2007/08 Average price per litre 2007/08 Average price per litre 2007/08 Average price per litre 2007/08 Average price per litre 2007/08 Average price per litre 2007/08 Place sold Place sold Place sold Place sold Place sold 1 Neighbour 2 Local Market 3 Secondary Market 4 Processing industry 5 Largescale farm 6 Trader at Farm 7 Did not sell 8 Other (specify) Farm Serial Number Farm Serial Number Farm Serial Number Farm Serial Number Farm Serial Number Region Region Region Region Region 01 Dodoma 02 Arusha 03 Kilimanjaro 04 Tanga 05 Morogoro 06 Pwani 07 Dar es salaam 08 Lindi 09 Mtwara 10 Ruvuma 11 Iringa 12 Mbeya 13 Singida 14 Tabora 15 Rukwa 16 Kigoma 17 Shinyanga 18 Kagera 19 Mwanza 20 Mara 21 Manyara 51 North Unguja 52 South Unguja 53 Urban West 54 North Pemba 55 South Pemba Sheep type Sheep type Sheep type Sheep type Sheep type 1 Ram 2 Castrated Sheep 3 She Sheep 4 Male lamb 5 She lamb Number of sheeps Number of sheeps Number of sheeps Number of sheeps Number of sheeps Farm Serial Number Farm Serial Number Farm Serial Number Farm Serial Number Farm Serial Number Region Region Region Region Region 01 Dodoma 02 Arusha 03 Kilimanjaro 04 Tanga 05 Morogoro 06 Pwani 07 Dar es salaam 08 Lindi 09 Mtwara 10 Ruvuma 11 Iringa 12 Mbeya 13 Singida 14 Tabora 15 Rukwa 16 Kigoma 17 Shinyanga 18 Kagera 19 Mwanza 20 Mara 21 Manyara 51 North Unguja 52 South Unguja 53 Urban West 54 North Pemba 55 South Pemba Pig type Pig type Pig type Pig type Pig type 1 Boar 2 Castrated male 3 Sow/Gilt 4 Male piglet 5 She piglet Number of pigs Number of pigs Number of pigs Number of pigs Number of pigs 2.1 Using the options below indicate the type of farm owners 2.1 Using the options below indicate the type of farm owners 2.1 Using the options below indicate the type of farm owners 2.1 Using the options below indicate the type of farm owners 2.1 Using the options below indicate the type of farm owners 1 Government 2 Parastatal 3 Private registered 4 Private Non- registered 5 Other Region Region Region Region Region 01 Dodoma 02 Arusha 03 Kilimanjaro 04 Tanga 05 Morogoro 06 Pwani 07 Dar es salaam 08 Lindi 09 Mtwara 10 Ruvuma 11 Iringa 12 Mbeya 13 Singida 14 Tabora 15 Rukwa 16 Kigoma 17 Shinyanga 18 Kagera 19 Mwanza 20 Mara 21 Manyara 51 North Unguja 52 South Unguja 53 Urban West 54 North Pemba 55 South Pemba Farm Serial Number Farm Serial Number Farm Serial Number Farm Serial Number Farm Serial Number Type of livestock/product Type of livestock/product Type of livestock/product Type of livestock/product Type of livestock/product 1 Live cattle 2 Live goats/sheep 3 Live pigs Number Sold during 2007/08 Number Sold during 2007/08 Number Sold during 2007/08 Number Sold during 2007/08 Number Sold during 2007/08 Average price per unit 2007/08 Average price per unit 2007/08 Average price per unit 2007/08 Average price per unit 2007/08 Average price per unit 2007/08 Place sold Place sold Place sold Place sold Place sold 1 Neighbour 2 Local Market 3 Secondary Market 4 Processing industry 5 Largescale farm 6 Trader at farm 7 Did not sell 8 Other Region Region Region Region Region 01 Dodoma 02 Arusha 03 Kilimanjaro 04 Tanga 05 Morogoro 06 Pwani 07 Dar es salaam 08 Lindi 09 Mtwara 10 Ruvuma 11 Iringa 12 Mbeya 13 Singida 14 Tabora 15 Rukwa 16 Kigoma 17 Shinyanga 18 Kagera 19 Mwanza 20 Mara 21 Manyara 51 North Unguja 52 South Unguja 53 Urban West 54 North Pemba 55 South Pemba Farm Serial Number Farm Serial Number Farm Serial Number Farm Serial Number Farm Serial Number Type of livestock/product Type of livestock/product Type of livestock/product Type of livestock/product Type of livestock/product 1 Beef 2 Goat meat/Mutton 3 Pig meat Quantity Sold during 2007/08 Quantity Sold during 2007/08 Quantity Sold during 2007/08 Quantity Sold during 2007/08 Quantity Sold during 2007/08 Number of livestock slaughtered Number of livestock slaughtered Number of livestock slaughtered Number of livestock slaughtered Number of livestock slaughtered Average price per tonne 2007/08 Average price per tonne 2007/08 Average price per tonne 2007/08 Average price per tonne 2007/08 Average price per tonne 2007/08 Place sold Place sold Place sold Place sold Place sold 1 Neighbour 2 Local Market 3 Secondary Market 4 Processing industry 5 Largescale farm 6 Trader at farm 7 Did not sell 8 Other Region Region Region Region Region 01 Dodoma 02 Arusha 03 Kilimanjaro 04 Tanga 05 Morogoro 06 Pwani 07 Dar es salaam 08 Lindi 09 Mtwara 10 Ruvuma 11 Iringa 12 Mbeya 13 Singida 14 Tabora 15 Rukwa 16 Kigoma 17 Shinyanga 18 Kagera 19 Mwanza 20 Mara 21 Manyara 51 North Unguja 52 South Unguja 53 Urban West 54 North Pemba 55 South Pemba Farm Serial Number Farm Serial Number Farm Serial Number Farm Serial Number Farm Serial Number Animal type Animal type Animal type Animal type Animal type 1 Indigenous Chicken 2 Layer 3 Broiler 4 Ducks 5 Turkeys 6 Rabbits 7 Donkeys 8 Horses 9 Other(specify) …………… Current Number Current Number Current Number Current Number Current Number Number sold Number sold Number sold Number sold Number sold Average Price/head Average Price/head Average Price/head Average Price/head Average Price/head Kilogram Slaughtered Kilogram Slaughtered Kilogram Slaughtered Kilogram Slaughtered Kilogram Slaughtered Average price/kg Average price/kg Average price/kg Average price/kg Average price/kg 2.1 Using the options below indicate the type of farm owners 2.1 Using the options below indicate the type of farm owners 2.1 Using the options below indicate the type of farm owners 2.1 Using the options below indicate the type of farm owners 2.1 Using the options below indicate the type of farm owners 1 Government 2 Parastatal 3 Private registered 4 Private Non- registered 5 Other Region Region Region Region Region 01 Dodoma 02 Arusha 03 Kilimanjaro 04 Tanga 05 Morogoro 06 Pwani 07 Dar es salaam 08 Lindi 09 Mtwara 10 Ruvuma 11 Iringa 12 Mbeya 13 Singida 14 Tabora 15 Rukwa 16 Kigoma 17 Shinyanga 18 Kagera 19 Mwanza 20 Mara 21 Manyara 51 North Unguja 52 South Unguja 53 Urban West 54 North Pemba 55 South Pemba Farm Serial Number Farm Serial Number Farm Serial Number Farm Serial Number Farm Serial Number Chicken Diseases Chicken Diseases Chicken Diseases Chicken Diseases Chicken Diseases 1 Newcastle Disease 2 Gumboro 3 Coccidiosis 4 Chorysa 5 Fowl typhoid Number Infected Number Infected Number Infected Number Infected Number Infected Number Treated Number Treated Number Treated Number Treated Number Treated Number Died Number Died Number Died Number Died Number Died Number Recovered Number Recovered Number Recovered Number Recovered Number Recovered