Python
Aim:
To detect the plant leaf disease and to recommend the crop using Machine and Deep learning.
Abstract:
India is one of the leading countries worldwide in terms of farm output. Even after being a leading producer of agricultural products, India still lacks farm productivity. Farmers have very less income because of the lack of farm productivity. Identification of leaf disease is very difficult in agriculture field. If identification is incorrect then there is a huge loss on the production of crop and economical value of market. To increase productivity, farmers should know which crop would suit the specific piece of land. If the right type of crop is cultivated in that piece of land, then automatically, the yield of the crop will increase. Hence, crop recommendation systems can be very beneficial for farmers. We use machine learning algorithm for crop recommendation and deep learning for plant disease identification. Leaf disease detection requires huge amount of work, knowledge in the plant diseases, and require the more processing time. Therefore, we can use image processing for identification of leaf disease. The system has been tested with the different numbers of test data set collected from different regions. We combine the both crop recommendation and plant disease identification. We can able to find the output in the Web-app.
Proposed System:
Now a day’s, dilettante farmers are hard to understand the plant disease, cultivation process, crop type, climate change, etc. Farming is that the spine for every nation’s economy. Future agriculture depends on dilettante formers. But new farmers not so strong at farming, So Machine learning and deep learning help to solve their problems. We combine plant disease identification and Crop recommendation system in this single project to make it user friendly.
We use machine learning algorithm(random forest) for crop recommendation. And we use Convolutional neural network for plant disease identification.
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