A Review Technique of Data Mining in the Agronomy field - Singh, U; Garg, K (International Journal of Computer Sciences and Engineering, 2025)
Agriculture is the main source of income in India. India produces various crops such as jute, wheat, rice, sugarcane, cotton, mustard, pulses and many more. Today India acquires 2nd rank worldwide in farming production. In 16 century, 99% of world crop productions are produced by India, Now, it is only produces 23% of agriculture products. However, there are some critical factors that influence the agriculture such as in efficient use of fertilizers, Chemicals, Heavy Rainfall, Degradation/Increment in temperature, PH value, less components value present in soil. This paper provides a systematic analysis by employing data mining techniques. This paper includes some techniques of Supervised and Unsupervised learning methods. In Agriculture domain, multiple linear regressions (MLR), Support vector machine (SVM), K nearest neighbor (KNN), Density-based spatial clustering applications with noise (DBSCAN) are the most widely used data mining algorithm which aimed to solve the issues of the agriculture up to some extent.