The Role of Machine Learning in Enhancing Wheat Crop Yield Predictions

Abstract

Agriculture is the key concern and promising field to explore in every country. In India, the population is growing rapidly; with the increase in population, the need for food is also rising. In this field, farmers and agriculture is  have to take several decisions day by day , and sophisticated complexities involve the factors affecting them. An important concern for agricultural planning is the precise crop yield prediction and evaluation for a variety of types of crops involved in the planning. Machine learning techniques are the essential approach for achieving the competent solutions for these problems. Therefore, agriculture has been an obvious goal for big data. Environmental conditions, unpredictability in soil types, soil nutrients, rainfall, fertilizers, have made it all the more relevant for farmers to use the information and this information used to make censorious farming decisions. In the proposed work various machine learning algorithms like multiple linear regressions, ridge regression, lasso regression and, random forests are used. The lasso regression technique provides the better prediction results in comparison of others.