Paper Details

Agriculture is the main source of Indian economy which includes cultivation of crops and produces the food[1]. While producing a crop, nutrients play a very important role in it. Nowadays, the yielding of crops is decreasing dayby day. This is due to nutrient deficiency. Farmers face the problems of nutrient deficiency and appropriate fertilizers forthe producing good crops. Earlier, it was impossible for the farmers to detect the deficiency of nutrients in crops. Due todeficiency of nutrients in plants, the plants get damaged and may die [1]. But in this 21st century, the world oftechnology, there are various techniques available to detect its deficiency and make good cultivation of crops. Variousalgorithms are also used to detect nutrient deficiency in different plant such as Kappa coefficient (0.96) in SIFTalgorithm to detect deficiency in coffee plant [8]. To differentiate complex background, deep sparse extreme learningmachines is used. Multiple methods are used to determine nutrient deficiency as it shows better performance for nutrientrecognition [9]. In the era of digital agriculture, digital images and machine learning is used combine to solve theproblems [5]. Nutrients play a very vital role in producing good crops. Plant deficiency affection is seen generally on theleaves [7]. Neural network makes it easy to detect nutrient deficiency by predicting accurately [6]. In this paper, westudy about those various methods which can detect the deficiency of nutrients in crops using machine learning. Thesemethods will help to improve the productivity and make better cultivation of crops. These methods will reduce theproblems of labor and farmers and can live a better life than before. Machine learning includes image processing aswell.

Parnal P. Pawade, Dr. A. S. Alvi, “A Survey of Crop Nutrients Deficiency Detection using Machine Learning”, International Journal of Advance Engineering and Research Development (IJAERD), Vol. 7, Issue 8, pp. 1-6, August 2020.