Model Approach of Crop Classification Using Logistic Regression

Relation between agriculture and the human development is very old. From the beginning era all participant of food chain in second stage depends on agriculture. At the beginning state life was natural and moving. With the stability of humans use of specific land increased and now stage is , where , humans are useable to chemical products for increasing the quantity of crop production in the land. Though the use of external chemicals result in quantitative growth of crop, but internally soil health get suffer from it and one –day it might be loss her fertility. Soil testing tools has a vital role in testing the soil for nutrient in soil and test its productivity. Easy classification of soil on the basis of its different features and also from testing the quality of soil to suggest the additional supplement to improve the health and nutrient in the soil. Key objective of this paper is to capture soil health in concern of nutrient. In this paper we have shown the classification approach of soil nutrient and detecting the soil health. We have built model using machine leaning algorithm (Logistic Regression) in Python. Results are compared with standard chart of soil health contains from the agriculture laboratory. Our detection accuracy lies between 95 to 99%.