Pre-harvest forecast of kharif rice yield using PCA and MLR technique in Navsari district of Gujarat

Authors

  • K.B. BANAKARA Department of Agricultural Statistics, Navsari Agricultural University, Navsari, Gujarat – 396 450
  • H.R. PANDYA Department of Agricultural Statistics, Navsari Agricultural University, Navsari, Gujarat – 396 450
  • Y.A. GARDE Department of Agricultural Statistics, College of Agriculture, Navsari Agricultural University, Waghai, Dang, Gujarat – 394 730

DOI:

https://doi.org/10.54386/jam.v21i3.256

Keywords:

Weather indices, MLR techniques, PCA, forecast

Abstract

In this paper Principal Components (PC) and Multiple Linear Regression (MLR) Technique were used for development of pre-harvest model for rice yield in the Navsari district of south Gujarat. The weather indices were developed and utilized for development of pre-harvest forecast models. The data of rice yield and weather parameters from 1990 to 2012 were utilized. The cross validation of the developed forecast model were confirmed using data of the years 2013 to 2016. It was observed that value of Adj. R2 varied from 89 to 96. The appropriate forecast model was selected based on high value of Adj. R2. Based on the outcomes in Navsari district, MLR techniques found to be better than PCA for pre harvest forecasting of rice crop yield. The Model-2 found competent to forecast rice yield in Navsari district before eight weeks of actual harvest of crop (37th SMW) i.e during reproductive stage of the crop growth period.

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Published

01-09-2019

How to Cite

K.B. BANAKARA, H.R. PANDYA, & Y.A. GARDE. (2019). Pre-harvest forecast of kharif rice yield using PCA and MLR technique in Navsari district of Gujarat. Journal of Agrometeorology, 21(3), 336–343. https://doi.org/10.54386/jam.v21i3.256

Issue

Vol. 21 No. 3 (2019): September

Section

Research Paper

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