• Pratik Ghatte
• Tushar Madane
• Vedant Phadtare
• Chetan Kholgade
• Shrikant Shinde

Plant Health Monitoring and Disease Detection are the two main types of factors responsible for sustainable growth of agriculture. Effective plant disease detection technique can be used to reduce the use of toxic chemicals by leading to a better environment. In this paper we have used automated plant disease detection approach to identify the images of plant leaf as diseased or healthy and providing the accurate recommendation cure. Our paper mainly focuses on machine learning and deep learning approaches such as Convolutional Neural Networks to identify the diseases associated with the particular plant and recommending possible for the diseased plants. Our system performs image processing and the processes the images of plant leaf and extract features such as shape, size of the plants and the CNN model identifies the plants as healthy or diseased. If our system identifies the plant as diseased then it will give the pesticide to be used for disease cure in plants and it will also give the direction or action to be used to reduce the disease associated with the plants. Our system mainly uses the automated plant disease detection approach which will help the farmers for timely and accurate intervention of disease detection to improve crop health and the growth of sustainable agriculture

Plant Health Monitoring, Plant Disease, Image Processing, Deep Learning, CNN

"Plant Disease Detection and Cure Recommendation Using Machine Learning", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 5, page no.h140-h149, May-2024, Available :http://www.jetir.org/papers/JETIR2405717.pdf

"Plant Disease Detection and Cure Recommendation Using Machine Learning", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 5, page no. pph140-h149, May-2024, Available at : http://www.jetir.org/papers/JETIR2405717.pdf