Paper Key : IRJ************467
Author: Samruddha Somani,Ayush Dubey,Kautilya Singh,Nitesh Addagatla,Prof. Randeep Kaur Kahlon
Date Published: 04 Mar 2023
Abstract: In India, the farming sector is highly crucial for the economic growth of the country. In India, agriculture provides a living for approximately 51% of the people. Agriculture provides the various opportunities for the villagers to work and contribute widely to the development of our country on a very huge scale, as well as it gives a massive boost to the economy. The research aims to assist the farmers in determining the quality of the soil and assessing its many parameters, as well as recommending crops and fertilizers depending on the outcomes acquired through machine learning technique. To improve the effectiveness of the Crop Recommendations Systems and Fertilizer Recommendation System, the system employs a number of Classification techniques. The assigned soil and fieldwork to anticipate a list of crops that is suited for the soil, as well as the knowledge on minerals that are insufficient in the soil. As a result, the user is free to choose which crop to plant. As a result, the approach aids farmers in gaining information. This research uses soil and PH data as inputs and uses a website to forecast which crops are suited for the soil and which fertilizers can be used as a remedy. The research also aims to assist the farmers by determining the disease occurring in the plant where the user just needs to click the picture of the leaf of the plant which is having the disease and the system predicts that what type of disease it is and what are the organic techniques to mitigate that plant disease and save the remaining crops.Keywords: Agriculture, Crop Recommendation, Fertilizer Recommendation, Machine Learning, Plant Disease Detection, Recommendation System
DOI LINK : 10.56726/IRJMETS34062
Paper File to download :