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New Delhi: Agriculture Secretary Devesh Chaturvedi on Thursday urged states to swiftly adopt and implement new technology-driven initiatives to improve farm production estimates and enhance data accuracy.
Addressing a national conference here, Chaturvedi emphasised the need for continuous collaboration between the central and state governments to enhance the quality of agricultural statistics, an official statement said.
The new initiatives include the Digital Crop Survey, Digital General Crop Estimation Survey (DGCES), and the revamped FASAL (Forecasting Agricultural Output using Space, Agro-meteorology, and Land-based Observations) programme.
The Digital Crop Survey is designed to provide plot-level data with geotagged areas of crops, serving as a single source of truth for accurate crop area estimation.
DGCES aims to calculate yield based on scientifically designed Crop Cutting Experiments for all major crops across the country.
The revamped FASAL programme leverages remote sensing technology to generate accurate crop maps and area estimation for 10 major crops.
The conference also highlighted the UPAg Portal, which allows for cross-verification of data from multiple sources, ensuring robust agricultural statistics.
The agriculture ministry said these initiatives are expected to provide near real-time and reliable data directly from the field, enabling more precise estimations of crop production.
The agriculture department is collaborating with various institutions, including the Space Application Centre and the Indian Agricultural Research Institute, to develop yield forecast models.
Additionally, the department is working with the Ministry of Statistics and Programme Implementation to increase the supervision of crop-cutting experiments by the National Sample Survey Office.
The conference concluded with a consensus on the importance of these reforms and a commitment from all states to strengthen the agricultural statistical framework.
Officials stressed that the adoption of digital surveys and advanced technologies will lead to more efficient data collection, reduce discrepancies, and ultimately contribute to better policy-making in the agricultural sector.