Vol. 7, Issue 3 (2019)
Forecasting of pre-harvest rapeseed and mustard yield using discriminant function analysis of meteorological parameters
Author(s): Sarvesh Kumar, VN Rai, KK Mourya, Annu and Ravi Prakash Gupta
Abstract: An application of discriminant function analysis of meteorological parameters for developing suitable statistical models to forecast Rapeseed & Mustard yield in Sultanpur district of Eastern Utter Pradesh has been demonstrated. Time series data on Rapeseed & Mustard yield for 25 years (1990-91 to 2004-15) have been divided into three groups, viz. congenial, normal, and adverse based on de-trended yield distribution. Considering these groups as three populations, discriminant function analysis using weekly data of crop season on six meteorological parameters has been carried out. The discriminant scores obtained from this have been used as regressor variables along with time trend in development of statistical models. In all six procedures using weekly weather data have been proposed. The models developed have been used to forecast yield for the year 2012-13, 2013-14 and 2014-15 which were not included in the development of the models. It has been found that most of the models provide reliable forecast of the Rapeseed & Mustard yield about one and half months before the harvest. However, the model-5 has been found to be the most suitable among all the models developed.
Pages: 1897-1900 | 506 Views 131 Downloads
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How to cite this article:
Sarvesh Kumar, VN Rai, KK Mourya, Annu, Ravi Prakash Gupta. Forecasting of pre-harvest rapeseed and mustard yield using discriminant function analysis of meteorological parameters. Int J Chem Stud 2019;7(3):1897-1900.