Muhuddin Rajin Anwar1,2,*, Yash Chauhan3, Mark Richards1, Rosy Raman1, Maheswaran Rohan1, David J. Luckett2, Neroli Graham4, Kristy Hobson4
1NSW Department of Primary Industries, Wagga Wagga Agricultural Institute, PMB Wagga Wagga, NSW 2650, Australia
2Graham Centre for Agricultural Innovation (an alliance between NSW Department of Primary Industries and Charles Sturt University) Wagga Wagga, NSW 2650, Australia
3Department of Agriculture and Fisheries (DAF); Centre for Plant Science at the University of Queensland, Australia
4NSW Department of Primary Industries, 4 Marsden Park Rd, Tamworth, NSW 2340, Australia
*Corresponding author, Email: firstname.lastname@example.org
Cold temperatures at critical reproductive stages impacts chickpea yield, limiting its adaptation under diverse agro-climatic regions. Crop growth models provide an opportunity to predict yield performance under diverse climates and identify varieties for target environments. We examined the efficacy of the Agricultural Production Systems Simulator (APSIM) to simulate observed chickpea grain yields, and quantify the impact of low temperature stress on yield. It is difficult to easily define temperature stress, as low temperatures along with the duration of stress are likely to have a considerable effect on pod set and yield. Therefore, we developed seven chilling day-degrees indices to assess the effects of chilling temperatures in chickpeas. There was no significant correlation between chilling indices and observed grain yield suggesting that the current model does not predict the effect of chilling temperatures on yield. This is likely due to a combination of multiple abiotic stresses including frosts and other low temperatures. Using a Regression tree model, we assessed yield responses to chilling indices across 75 trials. Our analysis showed that the most severe chilling index (minimum threshold temperature <10oC) may have contributed to most of the variation in yield variability across the 75 locations. Consequently, this study identifies cool temperature damage as a valuable parameter for improving the chickpea yield prediction ability of the APSIM model.