In this paper we humbly present a review of some applications of cluster analysis in the field of agriculture and allied sciences. A few applications among them, which have been discussed here includes hierarchical agglomerative clustering approach, fuzzy clustering, hierarchical divisive clustering and Kohonen self-organizing feature maps along with an application of each of these techniques in the field of agriculture is also presented. Data mining in agriculture is a relatively new research field and the use of cluster analysis has almost been just begun in this area. This is our strong belief that effective techniques can be carved out for solving different agricultural problems of various complexities by intelligent use of data mining and its tools such as cluster analysis.

Agriculture Data mining Fuzzy clustering Hierarchical agglomerative clustering Hierarchical divisive clustering Kohonen self-organizing feature maps