Climate and rainfed wheat yield

Abstract

Planning for precision agriculture requires a better understanding of the plant’s response to climate. The economy of Qorveh, in Iran, is severely affected by wheat yield fluctuations. In this study, multivariate statistical methods were used to identify important climatic factors affecting rainfed wheat yield and to simulate yield variations based on these impact factors. A new method was introduced to initiate seed germination. After determining the germination time, the wheat growth period was divided into seven stages based on the growing degree day (GDD). Forty-four climatic variables and indices related to the first six stages were used to perform factor analysis and to develop a model for predicting pre-harvest yield. The results showed that 91.5% of the total variance of 44 variables can be explained by 9 factors. Eighty-five percent of yield variations can be explained and modeled (R = 0.92) using five of these factors. This indicates that rainfed wheat yield is highly correlated with climate conditions, and this relationship is well simulated by statistical methods. According to the results, the significant trend of climatic variables was identified as the main reason for the yield growth trend in Qorveh. The yield showed a direct relationship with precipitation and relative humidity and an inverse relationship with air temperature and sunshine. The impact intensity of variables on yield included precipitation, relative humidity, sunshine, and air temperature, respectively. The results also showed that the yield was more affected by climatic variables of spring and May than other seasons and months, respectively.