Sugarcane Production Modeling Using Machine Learning in Western Maharashtra

Chhaya Gunaji Narvekar(1*), Madhuri Rao(2),

(1) Xavier Institute Of Engineering
(2) Thadomal Shahani Engineering College , Mumbai, India
(*) Corresponding Author

Abstract


Agriculture is the most important sector in the Indian economy. India is the world's second-largest producer of sugarcane. Study is undertaken at Shirol tehsil. Kolhapur district, Maharashtra state, India with the aim of modeling sugarcane production forecasting using supervised machine learning algorithms. Sugarcane is mostly cultivated crop in this area. We applied supervised machine learning for forecasting the productivity of sugarcane village wise based on the ten year’s data about sugarcane production from the year 2010 to 2020. Productivity prediction accuracy for all algorithm  is greater than 92%. Whereas sugarcane yield prediction accuracy is around 65% , which is only based on features provided by sugar factory.

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References


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DOI: https://doi.org/10.24071/ijasst.v4i2.4636

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