MACHINE LEARNING IMPLEMENTATION ON AGRICULTURAL DATASETS FOR SMART FARM ENHANCEMENT TO IMPROVE YIELD BY PREDICTING PLANT DISEASE AND SOIL QUALITY

Abstract
As agriculture struggles to support the rapidly growing global population, plant disease reduces the production and quality of food, fiber and biofuel crops and farmers are also not aware about the crop which suits their soil quality, soil nutrients and soil composition. The purpose of this review is to present the application of machine learning in plant resistance genes discovery and plant diseases classification and helps the system focuses on checking the soil quality to predict the crop suitable for cultivation according to their soil type which maximize the crop yield depending on the analysis done based on machine learning approach.

Authors
G Kavitha, M Ganthimathi, K Sudha, M Ramya
National Institute of Technology, Tiruchirappalli, India

Keywords
Crop Yield, Soil Quality, Plant Disease, Machine Learning
Published By :
ICTACT
Published In :
ICTACT Journal on Data Science and Machine Learning
( Volume: 1 , Issue: 1 )
Date of Publication :
December 2019

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