Cotton is most important fibre crop which plays very important role in economic and social affairs of people, especially in India, but if disease like Alternaria Leaf Spot and deficiency of some major nutrients goes undetected in early stage then it can reduce as much as 25% of total production. In this paper, Various methods and algorithm has been discussed and compared for the detection of above. Since thousands of years, farmers have been detecting these defects in cotton. Number of methods has been proposed by various researchers which vary largely in technology. Earlier visual symptoms were the main source for defect detection in every plant, but then researchers have come with technologies like Image Processing, Optical Sensor, and Spectroscopic Determination etc. Ultimate goal of our research is to detect disease and nutrient deficiency in cotton plant. These techniques and methodologies have been studied thoroughly and then compared to get a single view in this paper
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