Modelling the impacts of climate change and air pollutants on the agricultural production yields in Malaysia using Random-Effects Error Components Regression model

Authors

  • Z.L. Chuan Centre for Mathematical Sciences, College of Computing and Applied Sciences, Universiti Malaysia Pahang, Lebuhraya Persiaran Tun Khalil Yaakob, 26300, Kuantan, Pahang, Malaysia.
  • S.F. Fam Technopreneurship Department, Faculty of Technology Management and Technopreneurship, Universiti Teknikal Melaka Malaysia, Hang Tuah Jaya, 76100 Melaka, Malaysia.
  • Q.H. Lee Faculty of Industrial Sciences and Technology, College of Computing and Applied Sciences, Universiti Malaysia Pahang, Lebuhraya Persiaran Tun Khalil Yaakob, 26300, Kuantan, Pahang, Malaysia.
  • J.S. Kok Faculty of Industrial Sciences and Technology, College of Computing and Applied Sciences, Universiti Malaysia Pahang, Lebuhraya Persiaran Tun Khalil Yaakob, 26300, Kuantan, Pahang, Malaysia.
  • M.N.B.M. Azam Centre for Mathematical Sciences, College of Computing and Applied Sciences, Universiti Malaysia Pahang, Lebuhraya Persiaran Tun Khalil Yaakob, 26300, Kuantan, Pahang, Malaysia.

DOI:

https://doi.org/10.15282/daam.v3i2.7755

Keywords:

Agricultural yields, Climate change, Climate variable, Air pollutants, Food security

Abstract

The occurrence of climate change is attributable to anthropogenic emissions of greenhouse gases (GHG) which have affected the C3 plants’ agricultural production yields in past decades. Therefore, this article aims to model the linear association among these C3 plants’ agricultural production yields with several climatic and non-climatic explanatory variables using one-way random-effects error components regression model. To be congruent with the main objective of this study, the balanced longitudinal dataset period 1980 to 2018 under big data was acquired. The analysis results revealed that merely maximum temperature (

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Published

2022-09-30