Determination of Effective Weather Parameters on Rainfed Wheat Yield Using Backward Multiple Linear Regressions Based on Relative Importance Metrics

Mehdi Bahrami,Shohreh Didari,Ali Shabani,Mohammad Reza Mahmoudi,Mohamed Boutayeb

doi:10.1155/2020/6168252

Mehdi Bahrami, Shohreh Didari + Show 3 more

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https://doi.org/10.1155/2020/6168252

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Abstract

Wheat (Triticum aestivum L.) is the most imperative crop for man feeding and is planted in numerous countries under rainfed conditions in semiarid zones. It is necessary for decision-makers and governments to predict the yield of rainfed wheat before harvest and to determine the effect of the major factors on it. Different methods have been suggested for forecasting yield with various levels of accuracy. One of these approaches is the statistical regression model, which is simple and applicable for regions with scarce data available. Since the weather is the most important factor affecting the production of wheat, particularly in rainfed cultivation, regression models using weather parameters are very common. However, the coefficients of these models are location based and should be determined locally. Therefore, in this research, backward multiple linear regression (BMLR) technique based on relative importance metrics was used to determine the most important effective weather parameters (11 parameters) on rainfed wheat productions in Fars Province, south of Iran, during 2006–2013. The influence of each parameter in the final model was analyzed using the values of LMG relative importance metric. The result indicated that sunshine hours had the biggest LMG (34.73%) and, therefore, was the most effective parameter. Also, among the other considered parameters, rainy days, minimum relative humidity, and average relative humidity with LMG values of 21.97%, 21.69%, and 21.62%, respectively, had the most effects on rainfed wheat yield in the studied area. All parameters except for the sunshine hours positively affected rainfed wheat yield. The most important reason for the significance of these parameters can be the prevailing dry and semidry climate in the southern areas of Iran. The proposed model for determination of weather parameters effects on rainfed wheat could be a great guidance and aid for different stakeholders such as farmers, decision-makers, and governments.

Highlights

Climate recognition and study of the agricultural plants requirements are some of the most important factors contributing to crop productions
Wheat is a globally vital crop and a strategic product in Iran. e Fars province located in the south of Iran ranks first in the production of wheat in this country. e rainfed wheat cultivation includes a large portion of this production so that out of about 550000 hectares cultivated area under wheat in this region, 150000 hectares is rainfed farming [2]. e predominant climate of this province is dry and semidry, and water resources are limited [3]. erefore, identifying the effective weather parameters involved in plant growth and crop yield is necessary
Sabzevary et al investigated the effects of climatic parameters on rainfed and irrigated wheat yields using bivariate linear regression analysis in chosen stations of Hamedan State, Iran. ey concluded that the sensitivity of rainfed wheat yield index to atmospheric and agroclimatic factors was higher compared to irrigated wheat [6]

Summary

Introduction

Climate recognition and study of the agricultural plants requirements are some of the most important factors contributing to crop productions. Understanding and managing the effect of weather parameters on crop production could lead to increase in their yield. Erefore, identifying the effective weather parameters involved in plant growth and crop yield is necessary. Mumtaz et al estimated the wheat yield based on the weather parameters applying remote sensing information for Chakwal rainfed croplands, Punjab Province, and Pakistan [5]. Sabzevary et al investigated the effects of climatic parameters on rainfed and irrigated wheat yields using bivariate linear regression analysis in chosen stations of Hamedan State, Iran. Ey concluded that the sensitivity of rainfed wheat yield index to atmospheric and agroclimatic factors was higher compared to irrigated wheat [6] Sabzevary et al investigated the effects of climatic parameters on rainfed and irrigated wheat yields using bivariate linear regression analysis in chosen stations of Hamedan State, Iran. ey concluded that the sensitivity of rainfed wheat yield index to atmospheric and agroclimatic factors was higher compared to irrigated wheat [6]

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