Impact of Climate on Sugarcane Yield over Gorakhpur District, U.P. using Statistical Model

Abstract

The impact of climate on agriculture could result in problems with food security and may threaten the livelihood
activities upon which much of the population depends. In the present study, the development of a statistical yield
forecast model has been carried out for sugarcane production over Gorakhpur district using weather variables
of crop growing season and past observed yield data for the period of 1971 to 2010. The study shows that this
type of statistical yield forecast model could efficiently forecast yield 5 weeks and even 10 weeks in advance of
the harvest for sugarcane within acceptable limit of error.The performance of the model in predicting yields at
district level for sugarcane crop is found quite satisfactory for both validation (2007 and 2008) as well as
forecasting (2009 and 2010). In addition to the above study, the climate variability of the area has also been
studied and hence, the data series was tested for Mann Kendall Rank Statistical Test. The maximum and
minimum temperatures were found to be significant with opposite trends (decreasing trend in maximum and
increasing in minimum temperature) while other three are found insignificant with different trends (rainfall and
evening time relative humidity with increasing trend andmorning time relative humidity with decreasing trend).