• Rajas Bhande
• Aditya Godambe
• Jayant Karale
• Rahul Padalkar

Crop prediction and disease detection are two important areas in agriculture that have received significant attention in recent years. Crop prediction involves forecasting the expected yield of a particular crop in a given season, which can help farmers to plan their activities and make informed decisions. Disease detection, on the other hand, it has identifiers and diagnoses diseases which affect the crop, which helps us to manage the disease. The prediction and detection process has been carried out mainly by machine learning algorithm and CNN. The research paper presents solution to above problem by developing a web page with the help of HTML, CSS , JavaScript for front end and Python and it’s framework Flask for other aspects of the websites. In this paper. We have proposed a website, which gives a system where a user can give his/her details of the soil, in the form fields as inputs. And then by using some machine learning algorithms and CNN modules. We recommend the best crop to grow in the soil. The Fertilizer which should be used to maintain the hygiene of the crop. And if the crop has some disease. Then with the help of different machine learning algorithms and modules, we detect the type of disease the crop has suffered from.

"Crop Harvest Prediction And Disease Detection Using Machine Learning ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.10, Issue 5, page no.j88-j93, May-2023, Available :http://www.jetir.org/papers/JETIR2305959.pdf

"Crop Harvest Prediction And Disease Detection Using Machine Learning ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.10, Issue 5, page no. ppj88-j93, May-2023, Available at : http://www.jetir.org/papers/JETIR2305959.pdf