Prediction of soybean productivity based on the photothermal quotient

Abstract

Climatic variables affect soybean yield components. Understanding how they are interrelated is essential for planning and boosting crop productivity. The aim of this study was to evaluate whether the photothermal quotient can be used to predict the productivity and 1000-grain weight of soybean. Five experiments were carried out at the Federal University of Santa Maria in growing seasons of 2013/14 to 2017/18 using the main cultivars (154) sown in the state of Rio Grande do Sul (RS), Brazil. The experiments were organized in a randomized block design with four replicates, evaluating grain productivity and 1000-grain weight. The results showed that years with the highest grain productivity and 1000-grain weight were associated with regular rainfall and high photothermal quotients (approximately 2.3 MJ m-2). There was a positive and significant correlation between grain productivity and the average number of days without rainfall (r = 0.98). In addition, there was a negative correlation with air temperature (r = -0.8). Air temperature and days without rain are decisive factors for yield and grain weight. The photothermal quotient can be used as a basis for predicting soybean grain productivity.