APS consists of household- and plot-level data on 336 households in maize-growing areas of Jimma and Bako zones. This dataset consists of information about Meher production and inputs in 2016. dataset variables observations characterstics_all_plots_2016 18 2504 production_and_family_labor_meher 47 2078 input_cost_meher 9 3024 hired_services_meher 15 1286 There are two other linked data sets on Belg production and the Focal Plot Note that dates are in the Ethiopian calendar. see, https://en.wikipedia.org/wiki/Ethiopian_calendar"
The major objectives of this rice crop cuts and survey were to: (i) identify major rice yield determinants in western terai districts of Nepal and (ii) to identify major determinants that describe the variability in rice yield across farms thereby linking with farm characteristics and socio-economic gradients. This study uses Remote Sensing (RS) data particularly the NDVI (Normalized Difference Vegetative Index) value extracted from LandSat satellite images in each of the six districts (Kanchanpur, Kailali, Bardyia, Banke, K apilbastu and Rupendhai). Since the resolution of LandSat satellite was better than MODIS; we used LandSat derived NDVI values to capture the variability in standing green biomass (a proxy for yield) so that sample selected will represent this variability in NDVI values. In each of the districts we saw a normal distribution of NDVI and samples were selected randomly by stratifying the NDVI values into four quartiles of bell curve, so that selected sample will represent proportionally the bell curve quartiles. The study contains several optional modules questions and mandatory modules. The mandatory modules give the broader insights on input uses across farms while the optional module provides better insight on each input uses for example; fertilizer use details, irrigation dynamics, weed management and socio-economics gradients particularly based on income and expenditure of households. The optional module is accompanied by the crop cuts data which was done in three quadrants of each plot wit h 2*2=4 meter square area. The sample size for this survey is 1052 households and the inputs use were asked for largest rice grown plots as farms may have multiple plots and inputs use might be different in different plots. Out of the total samples of 1052; a set of (~12%; 126 samples) households participated in optional modules to get the detail data on irrigation dynamics, weed management and socio-economics parameters.
The advent of cheap smartphones in rural areas across the globe presents an opportunity to change the mode with which researchers engage hard-to-reach populations. In particular, smartphones allow researchers to connect with respondents more frequently than standard household surveys, opening a new window into important short-term variability in key measures of household and community wellbeing. In this paper, we present early results from a pilot study in rural Bangladesh using a ‘microtasks for micropayments’ model to collect a range of community and household living standards data using Android smartphones. We find that more frequent task repetition with shorter recall periods leads to more inclusive reporting, improved capture of intra-seasonal variability, and earlier signals of events such as illness. Payments in the form of mobile talk time and data provide a positive development externality in the form of expanded access to mobile internet and social networks. Taken to scale, programs such as this have potential to transform data collection in rural areas, providing near-real-time windows into the development of markets, the spread of illnesses, or the diffusion of ideas and innovations.
The objective of the Landscape Diagnostic Survey (LDS) for wheat is to bridge the existing data-gap around current production practices of wheat, and also to help in evidence-based planning. The LDS is designed in a way that data is collected from randomly selected farmers spread uniformly within the Feed the Future (FtF) districs. The data has been collected from farmers largest wheat plot for 2018, 2019, 2020 and 2021. The surveys for the year 2020, and 2021 were done via phone surveys due to COVID and can be used as panel data with the hhid. Survey questionnaire captures all production practices applied by farmers from land preparation to harvesting, including detailed sections on fertilizer use, weed control and irrigation application. Data is captured through electronically enabled Open Data Kit (ODK) tool on mobile phone or tablet. The sample size for this survey in 2018 is 1577 households, in 2019 is 1207 households, in 2020 is 1028 households, and 953 households for 2021. The inputs use were asked for largest rice grown plots as farms may have multiple plots and inputs use might be different in different plots.
The objective of the Landscape Diagnostic Survey (LDS) for rice is to bridge the existing data-gap around current production practices of rice, and also to help in evidence-based planning. The LDS is designed in a way that data is collected from randomly selected farmers spread uniformly within the Feed the Future (FtF) districs. Data has been collected from farmers largest rice plot for 2019, 2020 main (kharif) season . Survey questionnaire captures all production practices applied by farmers from land preparation to harvesting, including detailed sections on fertilizer use, weed control and irrigation application. Data is captured through electronically enabled Open Data Kit (ODK) tool on mobile phone or tablet. The sample size for this survey in 2019 is 2917 households, and 2122 households for 2020. The inputs use were asked for largest rice grown plots as farms may have multiple plots and inputs use might be different in different plots.
This data set presents the results of 121 focus group discussions with men and women, in randomly selected communities, therefore representative of the six major maize agroecological zones in Kenya. Topics include biotic and abiotic stresses, in particular storage pests, maize lethal necrose disease, fall army worm and drought. Communities were asked what the major stresses were, to estimate the losses, and describe control methods and coping strategies.
Landscape Diagnostic Survey (LDS) for rice contains farmer's data on current production practices they applied for cultivating rice during 2017 monsoon season. The dataset contains 6857 farmers’ information captured from Bihar, Uttar Pradesh and Odisha states from eastern part of India. The objective of collecting this data is to bridge the existing data-gap and to generate data-based evidence that can help in evidence-based planning. The LDS is designed in a way that data is collected from randomly selected farmers spread uniformly within a KVK (government extension system) domain/district. Survey questionnaire captures all production practices applied by farmers from land preparation to harvesting, including detailed sections on rice establishment, fertilizer use, weed control and irrigation application. Data is captured through electronically enabled Open Data Kit (ODK) tool on mobile phone or tablet.
At present nearly half of the world’s population is under some form of government restriction to curb the spread of COVID-19, an extremely contagious disease. In Bangladesh, in the wake of five deaths and 48 infections from COVID-19, between March 24 and May 30, 2020 the government imposed a nationwide lockdown. While this lockdown restricted the spread of COVID-19, in the absence of effective support, it can generate severe food and nutrition insecurity for daily wage-based workers. Of the 61 million employed labor force in Bangladesh, nearly 35% of them are paid on a daily basis. This study examines the food security and welfare impacts of the COVID-19 induced lockdown on daily wage workers both in the farm and nonfarm sectors in Bangladesh. Using information from more than 50,000 respondents complied from 2016-17 Household Income and Expenditure Survey (HIES) in Bangladesh, this study estimates daily wage rates as Bangladesh Taka (BDT) 272.2 in the farm sector and BDT 361.5 in the nonfarm sector. Using the estimated daily wages earnings, this study estimates that a one-day complete lockdown generates a US$64.2 million equivalent economic loss only considering the wage loss of the daily wage workers. After estimating the daily per capita food expenditure separately for farm and nonfarm households, this study estimates a minimum compensation package for the daily wage-based farm and nonfarm households around US $ 1 per day per household to ensure minimum food security for the daily wage-based worker households.
Replicated crop-cuts from farmers' fields at harvest at multiple locations in Tanzania (180 to 2400 m), and Soil analysis from 0-20 cm and 20-50 cm depths from crop-cut fields in Southern Highlands, Eastern and Northern Zones of Tanzania in 2015.
The survey was conducted in 2015 immediately after lentil harvest in six western Nepal districts: Surkhet, Dadeldhura (mid and far west hills) and Banke, Bardiya, Kailali, Kanchanpur from terai. These six districts were selected purposively for the survey and sub districts selection was based on lentil acreage. 600 samples were selected randomly.
