Analysis of trends in area, production and yield of important crops of India

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Research Paper 01/07/2015
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Analysis of trends in area, production and yield of important crops of India

Ramandeep Kaur M. Malhi, G. Sandhya Kiran
Int. J. Agron. & Agric. Res. 7(1), 86-92, July 2015.
Keywords: Area, Crop, Production, Trend, Yield
Copyright Statement: Copyright 2015; The Author(s).
License: CC BY-NC 4.0

Abstract

Information related to trends in different crops can aid the policy makers in recommending policies leading to sustainable increase in the food production. The present study was aimed at analyzing the trends in area, production and yield of important crops viz. Cotton, Castor and Banana of India. A time series data from 2000-01 to 2011-12 (12 years) regarding the area, production and yield of these crops were collected. The trend analysis in terms of area (at country (India), state (Gujarat) and district (Vadodara) level); production (at state (Gujarat) and district (Vadodara) level); and yield (at district (Vadodara) level) of three crops namely Cotton, Castor and Banana exhibited variations. Cotton crop showed an increasing trend in area under crop at both country and state level while slight ups and downs were observed at district level. Production of cotton also showed overall increasing trend at state and district level and its yield showed upward trend at district level. Area under castor crop showed an increasing trend at country level and variations were found at state and district level. Its production also showed instability but on average increase was observed at state and district level. Yield of castor crop also showed variations but on average an increasing trend was observed. Area under banana crop showed variations at all three levels. Its production showed annual instability at state level but overall decrease at district level. Its yield also showed decreasing trend at district level. The study can aid the planners in deciding the growth rates to be achieved in accordance with the planned targets. Further, it can contribute towards basis for predicting the future supply.

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