Crop Selection Using Artificial Intelligence & Machine Learning

Crop Selection Using Artificial Intelligence & Machine Learning

- A Project in Partnership with NABARD

Unlock the insights and discover how technology can revolutionize agricultural practices, empowering farmers worldwide.

In June 2020, AgWise (a division of Digite Infotech,) NABARD, and a NGO called Aavishkar joined forces in a collaborative effort to address a critical question faced by Indian farmers: "What crop should I sow to maximize agricultural income this season?"

The project aimed to unlock patterns within crop, environment, and economic data to formulate hyper-local crop selection advisories, fostering climate-resilient agriculture practices and increasing farmers' income. The project addressed the complexity of crop selection by considering factors such as soil moisture, temperature, historical cost of cultivation, and farm gate prices.

The study underscores the importance of understanding local environmental conditions, management practices, and traditional preferences in making successful crop selection recommendations. It also highlights the potential of advanced IoT and AI/ML technologies to enhance agriculture practices, increase incomes, and mitigate risks for farmers across India, particularly in regions with small land holdings, rainfed cultivation, and poor soil conditions. The project's success emphasizes the need for a nuanced and context-specific approach in leveraging technology to address fundamental agricultural challenges.

PROJECT REPORT

Crop Selection Using Artificial Intelligence & Machine Learning

Discover how AgWise’s Crop X Environment X Economy framework, powered by AI/ML algorithms, was used to run simulations across 1000’s of different soil, weather and economic conditions to arrive at advisories on environmental suitability and financial riskwhich scale from field specific advisories to a general recommendation for the entire watershed.

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