SPATIAL CHANGES OF AGRICULTURE REGIONALIZATION IN TAMIL NADU STATE (INDIA) – 2006 - 07 TO 2016 - 17

Abstract

The concept of agriculture regionalization has been widely used to explain the spatial organisation and pattern of agriculture. The measurement of agriculture regionalisation helps knowing the areas that are performing rather than higher or less efficiency in comparison with the nearby areas. The Doi's (1959) method of combination has been applied in the Tamil Nadu to explore the various combinations of that optimize the agriculture regionalization in decadal changes of 2006 - 2007 to 2016 - 2017. Therefore, it may be useful as a tool for planning in a given region. These studies generally grown in combinations that show the relative positions of different agriculture crop on regional scale of particular cropped is normally region-specific and season-specific as agriculture ecology depends upon the nature of physical geography in addition to various socio-economic factors. The objective of the study is to analyses the spatial variation of agricultural regionalization pertaining in the study area and to compare the decadal year of 2006 - 07 and 2016 – 17. The present study falls between 13 56' N- 8 07'N and the 78 23'- 80 33'E longitude. In this study based on secondary data and data relating to agricultural crop area in use were collected from statistical office. The study areas of Tamil Nadu were divided into 32 districts. The study area is of agriculture crops most resourceful and the major agriculture crops are Paddy, Maize, Cholam, Cumbu, Ragi, Other Cereals, Bengal Gram, Red gram, Green Gram, Black Gram, Horse gram other Pulses, Sugar-cane, Cotton, Ground nut , Gingelly and Castor. In total, eight crop combinations in 2016 - 17 were found in this area against two combinations in 2006 - 2007. It can be used to explore a agriculture regionalization to increase income. The importance of breeding crops for poor farmers is to provide a stable income for poor crop farmers. The present research work is an attempt to generate inputs by processing the data using recent technologies like GIS software’s along with in situ observations.