SOIL CLASSIFICATION AND CROP SUGGESTION BASED DEEP LEARNING

SOIL CLASSIFICATION AND CROP SUGGESTION BASED DEEP LEARNING

B. Kavyanjali, CH. Kavya Sri, J. Kavya, E. Kasi Viswanath Reddy and K. Keerthana

4Undergraduate students, Department of Computer Science, Mallar Reddy University

Prof. Sabyasachi Chakraborty., Department of Computer Science, Malla Reddy University

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Abstract— Agriculture is one of the most important components of our society. Soil is a critical factor for a successful agriculture. The composition of soil differs from soil to soil. The Growth of Crops is affected by these chemical features of soil. Choosing the right type of crops for that particular type of soil is also important.

Machine Learning techniques can be used to classify the soil series data. The results of such classification can further be combined with crop dataset to predict the crops that are suitable for the soil series of a particular region and its climatic conditions.

Soil dataset and crop dataset are used. The datasets comprise of chemical attributes and geographical attributes of soil and crops. Algorithms like SVM and Ensembling technique can be used to classify the soil series data and predict the suitable crops.

Index Terms— Soil, Crop, Agriculture, crop recommendation, soil classification, machine learning.