Vol. 7, Issue 4 (2019)
Forecasting of pre-harvest wheat crop yield using discriminant function analysis (DFA) of meteorological parameters
Author(s): HG Singh, VN Rai, BVS Sissodi, V Nand, HY Singh and Sushil Kumar
Abstract: The present paper entitled “A study on crop yield weather relationship and yield forecast models of wheat for Barabanki district of Eastern U.P.†Time series data on yield of wheat and weekly data from 44th SMW of the previous year to 6th SMW of the following year on eight weather variables viz., Minimum Temperature, Maximum Temperature, Rainfall, Rainy days, Relative humidity 08.30hrs, Relative humidity 17.30hrs, and Wind-Velocity 08.30 Wind-Velocity 17.30hrs covering the period from 1990-91 to 2011-12 have been utilized for development of pre-harvest forecast model. Statistical methodologies using multiple regressions, discriminant functions analysis for developing pre-harvest forecast model have been described. In all, 13 models (one based on regression, six from discriminant and six from composite forecast) have been developed. The Model-A is based on weather indices and D1 to D6 are based on discriminant functions analysis and 6 composite forecast models have been developed on the basis of adjR2, RMSE and %SE, the best two models obtained by the application of discriminant and composite forecast analysis of weekly weather data are D3 & D4. However, the composite forecast models CF-1 & CF-3 have further reduced the percentage standard error of the forecast yield to some extent. These models can be used to get the reliable forecast of wheat yield two and half months before the harvest.
Pages: 2902-2906 | 270 Views 47 Downloads
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How to cite this article:
HG Singh, VN Rai, BVS Sissodi, V Nand, HY Singh, Sushil Kumar. Forecasting of pre-harvest wheat crop yield using discriminant function analysis (DFA) of meteorological parameters. Int J Chem Stud 2019;7(4):2902-2906.
