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2023, Vol. 8, Issue 2, Part A

Potato yield forecast models for Sultanpur district of eastern Uttar Pradesh using discriminant function analysis


Author(s): Snehdeep, BVS Sisodia and VN Rai

Abstract: The development of the pre-harvest forecast model has made use of time series data on potato yield as well as weekly data on five weather variables, including Minimum Temperature, Maximum Temperature, Relative Humidity 08.30 hrs, Relative Humidity 17.30 hrs, and Wind-Velocity, for the period from 1990-91 to 2011-2012. For the development of a pre-harvest forecast model, statistical approaches utilising discriminant functions analysis have been described. Six models have been created altogether using discriminant functions analysis. The two best models produced by using weekly weather data are Model- II and Model- Vth, based on adjR2, RMSE percent deviation, and % SE. Two and a half months prior to harvest, these models can be utilised to obtain a trustworthy forecast of potato productivity.

DOI: 10.22271/maths.2023.v8.i2a.943

Pages: 39-42 | Views: 239 | Downloads: 20

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International Journal of Statistics and Applied Mathematics
How to cite this article:
Snehdeep, BVS Sisodia, VN Rai. Potato yield forecast models for Sultanpur district of eastern Uttar Pradesh using discriminant function analysis. Int J Stat Appl Math 2023;8(2):39-42. DOI: 10.22271/maths.2023.v8.i2a.943

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