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By Rowena Castillo, Benedict Jardinero and Kazuki Saito
International Rice Research Institute (IRRI)

Indonesian farmer looking at the recommendation provided by Layanan Konsultasi Padi (Rice Crop Manager for Indonesia) through her mobile phone. (Photographed by Jo Anne Holly Torres-Ilagan)

When smallholder rice farmers open a text message on their mobile phone and see a tailored fertilizer and crop management recommendation just for their field, they are benefiting from over three decades of agricultural science research, innovation, collaboration and partnership. That simple text, which is easy to read, timely, and field-specific is the product of a quiet revolution in rice farming: the Rice Crop Manager (RCM). RCM empowers farmers not just to follow recommendations, but to make informed choices about what to apply, when, and how much based on their own field conditions.

Since its inception in 2013, RCM has generated more than 4 million field-specific crop and nutrient management recommendations across five countries in Asia including Bangladesh, India, Indonesia, the Philippines, and Vietnam. This is more than just numbers. It represents better harvests, higher incomes, better and efficient use of resources and lower pollution for millions of rice farmers.

The seeds of innovation: Site-Specific Nutrient Management (SSNM)

The scientific backbone of RCM is the Site-Specific Nutrient Management (SSNM) approach, developed by IRRI and its partners in the early 1990s for smallholder rice production systems in Asia to address large variability among farms and fields in their seasonal plant nutrition needs. Instead of blanket fertilizer advice, it offered tailor-made recommendations based on each field’s estimated crop response to applied nutrients, soil nutrient supplies, climate, crop variety, and farmer’s practices.

SSNM offered effective nutrient management recommendations, but it required a delivery mechanism to reach farmers. Advances in information technology and mobile communications that utilize decision trees and algorithms made it possible to generate field-specific recommendations by using web- and smartphone-based app like RCM.

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