Crop and Fertilizer Prediction and Disease Detection Using Data Science

• Author(s): M Goutham ; Konaganti Pravalya ; G. Naga Vamsi ; Royyuru Srikanth
• Paper ID: 1704150
• Page: 67-72
• Published Date: 14-03-2023
• Published In: Iconic Research And Engineering Journals
• Publisher: IRE Journals
• e-ISSN: 2456-8880
• Volume/Issue: Volume 6 Issue 9 March-2023

Abstract

One of the key industries that affect a nation's economic development is agriculture. The bulk of people in countries like India relies on agriculture for their livelihood. For growth and increased output, plants require nutrients. Plants can get the nutrients they need from fertilizers, manure, and soil. By putting the plant under both abiotic and biotic stress, climate change and global warming were found to be the primary causes of crop loss. One of the main areas of focus for academics globally is figuring out the causes of and solutions to the issues associated with crop loss [1], it is not only causing crop loss but is now affecting food production and crop prediction, which will have a detrimental effect on farmers' economies by lowering yields and making them less skilled at predicting future harvests. This research project helps inexperienced farmers (Tech farmers) plant the right crops by utilizing Data Science, one of the most advanced technologies in mining and forecasting. To produce more agricultural products with less waste, the agricultural sector needs technological advancements. Therefore, our major goal is to make it simple for farmers or other users to work on their farms by developing a website that includes crop and fertilizer forecasting as well as plant disease detection. Overall, the integration of crop prediction, fertilizer prediction, and disease detection using Data science can improve agricultural sustainability, productivity, and profitability. By leveraging these technologies, farmers can reduce crop loss due to disease outbreaks, increase crop yield and quality, and minimize the negative impact of agriculture on the environment.

Keywords

Decision Trees, Flask, Forecasting, Random Forests, Residual Network, Support Vector Machine, Web Technologies.

Citations

IRE Journals:
M Goutham , Konaganti Pravalya , G. Naga Vamsi , Royyuru Srikanth "Crop and Fertilizer Prediction and Disease Detection Using Data Science" Iconic Research And Engineering Journals Volume 6 Issue 9 2023 Page 67-72

IEEE:
M Goutham , Konaganti Pravalya , G. Naga Vamsi , Royyuru Srikanth "Crop and Fertilizer Prediction and Disease Detection Using Data Science" Iconic Research And Engineering Journals, 6(9)