Abstract: Food production in India is largely dependent on cereal crops including rice, wheat and various pulses.The sustainability and productivity of crops growing areas is dependent on suitable climatic conditions.Variability in seasonal climate conditions can have detrimental effects, with incidents of drought reducing production. Developing better techniques to predict crop productivity in different climatic conditions can assist farmers in better decision making in terms of agronomy and crop choice. Machine learning techniques can be used to improve prediction of crop yield under different climatic scenarios. This paper presents the review on use of such machine learning techniques for cropping areas.

 
Keywords: Machine Learning, Linear Regression, Random Forest Regression, Prediction.

 

| DOI: 10.17148/IJIREEICE.2020.8416