Crop Prediction Methods: A Comparative Study
I. L. Shahana
Department of CS, College of Agriculture, Padannakkad, Kerala, India.
V. P. Nijth Kamal
Department of CS, College of Agriculture, Padannakkad, Kerala, India.
R. L. Anoop *
Department of Agri. Extension, College of Agriculture, Padannakkad, Kerala, India.
Ancy Francis
Department of Agronomy, College of Agriculture, Padannakkad, Kerala, India.
*Author to whom correspondence should be addressed.
Abstract
In India 58% of the population depend upon agriculture and agriculture contributes about 18% of the gross domestic product. But the farmers face numerous challenges in agriculture due to various reasons. The farmers’ crop selection criteria generally depended upon their traditional base and testimonials of the success stories. The failure of selecting appropriate crop for a particular area makes them vulnerable to other vagaries also. Scientifically crop selection depends upon various factors like soil parameter (Ex: Soil moisture), weather parameters (Ex: Rainfall, temperature, Humidity), Geographical parameters (Ex: Slope) etc. Farmers and those who are venturing into farming requires a crop prediction model or a technique for the best crop selection decision in order to cope up and tide over exigencies like climate change, flood, drought etc which occur globally. The model will be accurate to tackle the issues arised by the climate change and also gives reasonable results to the farmers. This paper review on the existing crop prediction model and also their implication on the farming community.
Keywords: Crop prediction, soil parameter, topography, machine learning, big data analytics