Heterogeneity in soils, hydrology, climate, and rapid changes in rural economies including fluctuating prices, aging and declining labor forces, agricultural feminization, and uneven market access are among the many factors that constrain climate-smart agriculture (CSA) in South Asia’s cereal-based farming systems. Most previous research on CSA has employed manipulative experiments analyzing agronomic variables, or survey data from project-driven initiatives. This can obscure identification of relevant factors, limiting of contributing CSA in farmers’ own fields, leading to inappropriate extension, policy, and inadequate institutional alignments to address and overcome limitations. Alternative approaches utilizing heterogeneous datasets, however, remain insufficiently explored, though they can represent a powerful source of technology and management practice performance information.
In partnership with national research systems and the private sector in India, Nepal and Bangladesh, the Big data analytics for climate-smart agriculture in South Asia (Big Data2 CSA) project responds by developing digital data collection systems to source, data-mine and interpret a wide variety of primary agronomic management and socioeconomic data from tens of thousands of smallholder rice and wheat farmers. The project team analyzes these data by stacking them with spatially-explicit secondary environmental, climatic and remotely sensed data products, after which machine learning techniques are used to identify key factors contributing to patterns in yield, profitability, simulated greenhouse gas emissions intensity, and resilience. Research must be practical to be useful in agricultural development and policy. The project’s analytical results will be represented through interactive web-based dashboards, with gender-appropriate crop management advisories deployed through interactive voice recognition technologies at a large-scale to farmers in India, Bangladesh and Nepal.
- Big Data2 CSA is scaling-up the use of digital tools among national research and extension partners in India, Bangladesh and Nepal to collect detailed information using digital survey techniques on farmers’ crop management practices, yield and profitability outcomes, resilience enhancing practices, and to simulate greenhouse gas (GHG) emissions.
- Through Big Data2 CSA, actionable CSA management advisories are being developed through use of data mining and machine learning analytical techniques. These
- Big Data2 CSA is working closely with partners to develop telephone and IVR platforms to rapidly collect data on farmers’ management practices at a large-scale. These platforms are also being used to push CSA advice to farmers while simultaneously collecting data. Advisories on actionable climate-smart practices will be packaged in easy-to-understand and relevant formats and pushed to an anticipated 0.5 million farmers through telephone networks.
- Big Data2 CSA is building interactive and customizable web-based dashboards presenting post-season research results and providing CSA management recommendations.
- The project will develop policy briefings on the status of farmers’ prevailing management practices and opportunities for improved and climate-smart management.
Project Timeline: April 2019 – December 2021
- This project will initially make use of large-scale established datasets of crop monitoring and management information from which indicators on the performance of factors contributing to the success or failure of CSA practices will be analyzed. Large-scale digital, telephone and IVR surveys will also be implemented. Data will be mined to identify how farmers' practices contribute to yield, profitability, resource use efficiencies, and CSA indicators. We expect that least promising 10 CSA-relevant practices will be identified and ‘tested’ on a virtual basis through data mining, with practices and resulting advisories targeted in consideration of their performance across gender and age groups.
- Web-based dashboards representing analytical outputs from management survey analytics will be developed in at least prototype – if not finalized form – in India, Bangladesh and Nepal.
- Rapid post-season access and interactive data representation are expected to assist in increasingly relevant and data-driven farm policy decisions.
- At least two policy decisions are expected to be taken that are partly based on this project’s engagement with partners and through the generation of research evidence.
Gender & Youth
Crop monitoring and farmer survey programs led by national research and extension system in South Asia were reviewed through key informant interviews, supplemented by expert knowledge of national agricultural research and extension organizations. This overview highlighted a significant gap in terms survey collection of crop management data from women, in addition to a dearth of gender- and age-differentiated information at the farm household level. This research responds by increasing the rate of data collection from women and youth in rural India, Nepal and Bangladesh. Subsequent analyses will examine farmers’ management patterns and develop responsive and actionable CSA advisories differentiated by gender and age group. This opens new doors to farmer-to-farmer exchange. High-performing farmers identified in survey datasets can subsequently be empowered by extension services and partners as positive examples and spokespersons to popularize appropriate CSA practices.
- Indian Council of Agricultural Research
- Nepal Agricultural Research Council – Socioeconomics Division
- Nepal Prime Minister’s Agricultural Modernization Project
- Bangladesh Department of Agricultural Extension
- Precision Agriculture for Development
- Bi-laterally aligned project 1: Climate Services for Resilient Development (CSRD) in South Asia
- Bi-laterally aligned project 2: Cereal Systems Initiative for South Asia (CSISA)
- Bi-laterally aligned project 3: Soil Intelligence System for India
- Bi-laterally aligned project 4: Understanding and improving Scaling Readiness of Climate Smart, Nutrient Management decision support tools in different institutional environments
For more information, please contact project leader Dr. Timothy J. Krupnik, International Maize and Wheat Improvement Center | Sustainable Intensification Program. (Email: firstname.lastname@example.org)
Funding for this project is provided by: