This research paper attempts to identify the classification of Agriculture Productivity Index (API) with the help of fourteen major crops of Tamilnadu using four hierarchical clustering methods, viz complete , single, weighted and average linkage methods. The secondary database was collected from the Department of Economics and Statistics for a period of ten years from 2003 to 2012. The crops are categorized as cereals, pulses, oilseeds and cash crops. The states consist of thirty two districts with various agro climatic zones. Agriculture Productivity Index (API) is calculated with the use of Enedy'l method. In this paper, the Orange data mining software is used which is an open source data visualization and data analysis for learner and experts. Interactive work flows with a large toolbox using Python programming language. In addition, to cross validate the API, the orange data mining hierarchical clustering techniques is used. The results of cluster analysis generated five clusters based on API and they are labelled as Very High, High, Moderate, Low, Very Low. They are plotted in dendrogram and are highlighted with different colours of five clusters.