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InfoCrop v2.1: Indigenous Crop Simulator

Note4Students

From UPSC perspective, the following things are important :

Prelims level : InfoCrop v2.1

Mains level : Use of AI in agriculture

infocrop

Central idea: Scientists at the Indian Agricultural Research Institute conducted an experiment using InfoCrop version 2.1 to quantify the impact of hot weather on crop yield in Punjab and Haryana.

What is InfoCrop v2.1?

  • InfoCrop version 2.1 is India’s only dynamic crop simulation model developed and released by the IARI in 2015 to study the long-term impact of climate change and crop management practices on yield.
  • InfoCrop is more suited for India as it has the life cycle data for almost all the local varieties of 11 crops: paddy, wheat, maize, sorghum, pearl millet, pigeon pea, chickpea, soybean, groundnut, potato and cotton.

How does it work?

  • In InfoCrop, the parameters are already calibrated to Indian crop varieties and they are updated at regular intervals by the institute.
  • The parameters deal with aspects of-
  1. Weather (precipitation, temperature, radiation and others)
  2. Crop growth (phenology, grain characteristics, leaf growth, temperature and flooding sensitivity and others)
  3. Soil (texture and organic carbon, water holding characteristics and pH levels) and
  4. Pests and crop management (organic matter, fertiliser and irrigation).

Efficiency of InfoCrop model

  • The model has an 85 per cent accuracy rate.
  • This is on par with widely used dynamic models such as the Decision Support System for Agrotechnology Transfer model, developed by the US, and Agriculture Production Systems sIMulator, developed by Australia.

Utility of this tool

  • Prevent on-field corruption: India currently relies on field trials, which are expensive and resource-intensive as well as highly corrupt practise.
  • Crop insurance prediction: Government and insurance companies can use this for climate impact projections and for pre- or in-season crop yield forecasts to improve accuracy.
  • Assess crop loss: Besides forecasting, simulation models can be used to assess crop loss in the aftermath of an extreme weather event, which can then be used to provide relief packages.

 

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