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.
