부산대학교 도서관

Potato is one of India's main agricultural crops. In recent years, potato farms have become increasingly popular in India. However, a variety of ailments are driving up farmers' costs in the production of potatoes. Nevertheless, a number of diseases that are harming the crop are mostly to blame for the high cost of potato production. What is disrupting the farmer's schedule? Automation has been used to modernize the potato business and expedite illness diagnosis. Despite assertions, but potato leaf disease is a severe problem that has the potential to significantly lower crop production. Infected potato plants will exhibit on their leaves, the diseases early blight, Septoria blight, late blight, and others can be seen. If such outbreaks are detected early and sufficient intervention is carried out, farmers won't be at risk of suffering significant financial losses. A new model is released for precisely recognizing and diagnosing diseases in potato leaf stands in light of the experiment's findings. Making use of quaternion neural networks. While a variety of techniques, including the CNN model may be used in machine learning. For the purpose of identifying the disease in photographs of potato leaves, we developed an improved CNN model. In order to forecast the illness of potato leaves, this study adopts a sequential model based on Quaternion CNN. On this model, this study's model accuracy was 96.2%. To differentiate between the two, the proposed model was checked on both healthy and sick potato leaves. The potato tree leaf is categorized as healthy and sick after the algorithm has been applied to the photos.