Large survey dataset of rice production practices applied by farmers on their largest farm plot during 2018 in India

This dataset provides detailed information on rice production practices being applied by farmers during 2018 rainy season in India. Data was collected through computer-assisted personal interview of farmers using the digital platform Open Data Kit (ODK). The dataset, n = 8355, covers eight Indian st...

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Detalles Bibliográficos
Autores: Anurag Ajay, Craufurd, P., Kumar, V., Samaddar, A., Malik, R., Sharma, S., Ranjan, H., Singh, A.K., Paudel, G., Pundir, A., Poonia, S. P., Kumar, A., Kumar, Pankaj, Singh, D.K., Singh, M., Iftikar, W., Ignatius, M., Banik, N.C., Mohapatra, B.K., Sagwal, P.K., Yadav, A.K., Munshi, S., Peramaiyan, P., Mcdonald, A.
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2022
País:México
Institución:Centro Internacional de Mejoramiento de Maíz y Trigo
Repositorio:Repositorio Institucional de Publicaciones Multimedia del CIMMYT
OAI Identifier:oai:repository.cimmyt.org:10883/22313
Acceso en línea:https://hdl.handle.net/10883/22313
Access Level:acceso abierto
Palabra clave:AGRICULTURAL SCIENCES AND BIOTECHNOLOGY
Farmer Survey
Production Practices
AGRONOMY
RICE
PRODUCTION
Sustainable Agrifood Systems
Descripción
Sumario:This dataset provides detailed information on rice production practices being applied by farmers during 2018 rainy season in India. Data was collected through computer-assisted personal interview of farmers using the digital platform Open Data Kit (ODK). The dataset, n = 8355, covers eight Indian states, viz., Andhra Pradesh, Bihar, Chhattisgarh, Haryana, Odisha, Punjab, Uttar Pradesh and West Bengal. Sampling frames were constructed separately for each district within states and farmers were selected randomly. The survey was deployed in 49 districts with a maximum of 210 interviews per district. The digital survey form was available on mobile phones of trained enumerators and was designed to minimize data entry errors. Each survey captured approximately 225 variables around rice production practices of farmers’ largest plot starting with land preparation, establishment method, crop variety and planting time through to crop yield. Detailed modules captured fertilizer application, irrigation, weed management, biotic and abiotic stresses. Additional information was gathered on household demographics and marketing. Geo-points were recorded for each surveyed plot with an accuracy of <10 m. This dataset is generated to bridge a data-gap in the national system and generates information about the adoption of technologies, as well as enabling prediction and other analytics. It can potentially be the basis for evidence-based agriculture programming by policy makers.

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