Predicting crop using agricultural data

Abstract

India is an agricultural country. The agriculture industry in India needs to adopt the latest technology helping them in order to get better production, distribution and cost control. But now the country would need to produce more crops in order to achieve the demand due to increasing population. Moreover, major population is reliant on agriculture for the employment. Scienti c farming has become necessary increase the crop productivity. Crop productivity can be increased when all the factors which include climate parameters such as temperature, rainfall, humidity, vapour pressure, wind speed etc,soil properties such as soil nutrients, soil moisture, minerals, soil temperature etc. Fertilizers and pesticides a ect them too. If the crop is planted according to these factors then the productivity and yield could be better which would lead to farmers prosperity and ultimately the economy of the country would become better. So, if farmer can get the recommendations for crop plantation then he could plan his farming accordingly and get better output. In this research, rainfall prediction is done using simple linear regression by taking temperature as a predictor. Also, it is done using multiple linear regression where humidity, wind speed, vapour pressure, etc are taken into account along with tem perature. Yield prediction of two cereals bajra and wheat are done for Banaskantha, Anand and Ahmedabad. Crop recommendation is also done based on cardinal tem perature. It is also done for these three districts. Visualisation of data is done for e ective understanding of data.