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International Journal of Current Microbiology and Applied Sciences (IJCMAS)
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Original Research Articles                      Volume : 10, Issue:3, March, 2021

PRINT ISSN : 2319-7692
Online ISSN : 2319-7706
Issues : 12 per year
Publisher : Excellent Publishers
Email : editorijcmas@gmail.com /
submit@ijcmas.com
Editor-in-chief: Dr.M.Prakash
Index Copernicus ICV 2018: 95.39
NAAS RATING 2020: 5.38

Int.J.Curr.Microbiol.App.Sci.2021.10(3): 967-973
DOI: https://doi.org/10.20546/ijcmas.2021.1003.123


Statistical Models for Wheat Yield Forecasting using Discriminant Function Analysis of Weather Parameters
Ravi Prakash Gupta*, V. N. Rai, Sarvesh Kumar, K. K Mourya and Annu
Department of Agricultural Statistics, Narendra Deva University of Agriculture and Technology, Kumarganj, Ayodhya, Uttar Pradesh, India
*Corresponding author
Abstract:

The study was based on, an application of discriminant function analysis of Agroclimatic zone for developing suitable statistical models to forecast wheat yield in Ayodhya district of Eastern Utter Pradesh has been demonstrated. The study utilized the crop yield data and corresponding weekly weather data of last 27 years (1990-91 to 2016-17). The model development was carried out at 44th and 6th SMW (Standard Meteorological Week) for getting forecast well in advance of actual harvesting of the field crop. 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 the wheat yield for the year 2014-15, 2015-16 and 2016-17 which were not included in the development of the models. It has been found that most of the models provide reliable forecast of the wheat yield about two months before the harvest. However, the model-6 has been found to be the most suitable among all the models developed. It was observed high value of Adj. R2= 0.78 and low value of RMSE= 6.22. The model can be used in different crop for reliable and dependable forecast and these forecasts have significant value in agricultural planning and policy making.


Keywords: Pre harvest forecast, Wheat crop yield, weather indices, and discriminant function

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How to cite this article:

Ravi Prakash Gupta, V. N. Rai, Sarvesh Kumar, K. K Mourya and Annu. 2021. Statistical Models for Wheat Yield Forecasting using Discriminant Function Analysis of Weather Parameters.Int.J.Curr.Microbiol.App.Sci. 10(3): 967-973. doi: https://doi.org/10.20546/ijcmas.2021.1003.123
Copyright: This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike license.

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