Authors : Spoorthi A. Hunshal; Sanjana R.; Himani Pitta; Shiva Kumar R. Naik

Volume/Issue : Volume 9 - 2024, Issue 5 - May

Google Scholar : https://tinyurl.com/mvf82fym

Scribd : https://tinyurl.com/4edzwh3r

DOI : https://doi.org/10.38124/ijisrt/IJISRT24MAY215

Abstract : In the recent years ensuring food security plays a major role in the agricultural sector and contributing towards the nations growth. This paper presents a communal system that makes use of elegant machine learning techniques and models to forecast accurate yield of the selected crop and advocates the felicitous fertiliser. By exploiting the agricultural datasets, our system employs the Extra Trees Regressor trees which helps for the prediction of the yield and to analyse the most recommendable fertilizer it makes use of the Gaussian Naïve Bayes algorithm. This dormant system provides the us with powerful insights. Our sight is to reshape the conventional agricultural practices with the help of these powerful insights to redefine the farming practices and to increase the productivity, therefore ensuring the legitimate agricultural practices.

Keywords : Crop Yield Prediction, Fertilizer Recommendation, Machine Learning Algorithms, Extra Trees Regressor (ETR), Gaussian Naïve Bayes (GNB).

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