Optimal Crop Recommendation by Soil Extraction and Classification Techniques Using Machine Learning

Soil determines importance of food especially in farming and agriculture. Various soils are used by various crops. Many researchers published on types of soils and recommendations of soils. To recommend a soil deep study is required based on many parameters. Machine learning is the concept which can be applied in wide applications. Measuring the characteristics of soil can be done through machine learning. Many algorithms are available in the machine learning which are used for various processes. This paper focuses on using machine learning algorithms for extraction, selection, model design and feature classification of the parameters of soil. Based on the classifications of soil suitable algorithms like HMM-based DNN are considered which have given best results in terms of extraction and classification. Promisingly, the accuracy was more than 90%. This model helps the farmers to adequately improve their analysis in selection of crop.