Selection of wheat (Triticum aestivum) variety through expert system

SHAHNAWAZUL ISLAM; SUSHILA KUNDU; JAG SHORAN; NAVED SABIR; KIRTI SHARMA; SAMIR FAROOQI; RANDHIR SINGH; HARI OM AGARWAL; K K CHATURVEDI; R K SHARMA; A K SHARMA

doi:10.56093/ijas.v82i1.13871

Authors

SHAHNAWAZUL ISLAM Indian Agricultural Statistics Research Institute, New Delhi 110 012 India
SUSHILA KUNDU Indian Agricultural Statistics Research Institute, New Delhi 110 012 India
JAG SHORAN Indian Agricultural Statistics Research Institute, New Delhi 110 012 India
NAVED SABIR Indian Agricultural Statistics Research Institute, New Delhi 110 012 India
KIRTI SHARMA Indian Agricultural Statistics Research Institute, New Delhi 110 012 India
SAMIR FAROOQI Indian Agricultural Statistics Research Institute, New Delhi 110 012 India
RANDHIR SINGH Indian Agricultural Statistics Research Institute, New Delhi 110 012 India
HARI OM AGARWAL Indian Agricultural Statistics Research Institute, New Delhi 110 012 India
K K CHATURVEDI Indian Agricultural Statistics Research Institute, New Delhi 110 012 India
R K SHARMA Indian Agricultural Statistics Research Institute, New Delhi 110 012 India
A K SHARMA Indian Agricultural Statistics Research Institute, New Delhi 110 012 India

https://doi.org/10.56093/ijas.v82i1.13871

Keywords:

Expert System, Forward chaining, Inference engine, Knowledge base, Variety, Wheat

Abstract

Most of the released wheat (Triticum aestivum L. emend Fiori & Paol.) varieties have been documented for various characteristics that they possess. The challenge was to organize these varieties electronically so that the farmers of the country could be benefited from this information for increase in production. Researchers and students could use them for reference and include them in their future research programmes. An expert system on wheat crop management has been developed for this purpose. The system has an exclusive variety selection module with a scientific knowledge base in the background. The module suggests a variety of farmer’s/user’s choice based on location and desired characteristics like sowing condition, yield, protein content, response to diseases and insects. The system carries detailed information about 300 varieties that have been stored in its knowledge base.

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