Wheat yield prediction in relation to climatic parameters using statistical model for Ludhiana district of central Punjab

Authors

  • MAHESH CHAND SINGH Department of Soil and Water Engineering, Punjab Agricultural University, Ludhiana, Punjab, India
  • VAJINDER PAL Department of Agronomy, Punjab Agricultural University, Ludhiana, Punjab, India
  • SOM PAL SINGH Dept of Climate Change & Agril. Meteorology, Punjab Agricultural University, Ludhiana, India
  • SANJAY SATPUTE Department of Soil and Water Engineering, Punjab Agricultural University, Ludhiana, Punjab, India

DOI:

https://doi.org/10.54386/jam.v23i1.97

Keywords:

Statistical model, climate,, wheat,, regression analysis

Abstract

Climate change which is one of the main determinants of agricultural production has started affecting the crop growth pattern and yield from past couple of decades in various agro-climatic zones globally. Under such scenario, the prior forecasting of yield of field crops such as wheat via modeling techniques can help in simplifying the crop production management system starting from farmer’s level to policy makers. The present study was thus undertaken to model the wheat yield of Ludhiana district of  Indian Punjab through regression analysis of historical data (1993-2017) of wheat yield and climatic conditions in the area. The developed model was successfully validated with a strong positive correlation (R2=0.81) between predicted and observed data. Both observed and predicted yields were having similar trend with a minimum and maximum absolute differential error of 0.1 and 13.9% respectively. The developed model may serve as a powerful tool for predicting the future yield of wheat crop with available futuristic climatic data of the study area.

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Published

01-03-2021

How to Cite

MAHESH CHAND SINGH, VAJINDER PAL, SOM PAL SINGH, & SANJAY SATPUTE. (2021). Wheat yield prediction in relation to climatic parameters using statistical model for Ludhiana district of central Punjab. Journal of Agrometeorology, 23(1), 122–126. https://doi.org/10.54386/jam.v23i1.97

Issue

Vol. 23 No. 1 (2021): March

Section

Research Paper

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