DIGITAL AGRICULTURE EXPERT SYSTEMS USING IMAGE PROCESSING AND MACHINE LEARNING

Angebote / Angebote:

Paddy fields have been used for cultivation over thousands of years. But these paddy fields don't care much for replenishing. It has degraded the quality and productivity of the plants, fruits, and also led to the depletion of the soils. This is a serious problem that can be solved by using proper farming and technology. Most of the farmers often used traditional farming technology such as sickle, plow, spade, weeder, weed, rake, and ax, etc. [1]. The traditional system takes more time and human efforts to do farming [2]. But modern technologies help farmers to enhance the quality and productivity of farming. The urban farmers avail the facilities of modern technologies and laboratories, but the rural farmers often face difficulties due to the non-availability of modern farming technologies, and laboratories. The productivity of farming depends on the selection of physical and chemical properties of soil, selection of seed, a good amount of plant photosynthesis, and early detection of plant diseases, etc. These are the serious issues of farming. The developed system helps the farmer to classify the best soil for Assam citrus, predict the suitable soil pH for citrus farming, estimate the leaf chlorophyll for citrus health issues, and detect the citrus leaf diseases at the vegetative stage. The system shows the application of Linear Regression (LR), Artificial Neural Network (ANN), K Nearest Neighbour (KNN), Support Vector Machine (SVM), and Convolution Neural Network (CNN) in precision farming for the better yields of the citrus farming.