Modelling the effects of cold temperature during the reproductive stage on the yield of chickpea (Cicer arietinum L.)

Abstract

During the reproductive stage, chilling temperatures and frost reduce the yield of chickpea and limit its adaptation. The adverse effects of chilling temperature and frost in terms of the threshold temperatures, impact of cold duration, and genotype-by-environment-by-management interactions are not well quantified. Crop growth models that predict flowering time and yield under diverse climates can identify combinations of cultivars and sowing time to reduce frost risk in target environments. The Agricultural Production Systems Simulator (APSIM-chickpea) model uses daily temperatures to model basic crop growth but does not include penalties for either frost damage or cold temperatures during flowering and podding stages. Regression analysis overcame this limitation of the model for chickpea crops grown at 95 locations in Australia using 70 years of historic data incorporating three cultivars and three sowing times (early, mid, and late). We modified model parameters to include the effect of soil water on thermal time calculations, which significantly improved the prediction of flowering time. Simulated data, and data from field experiments grown in Australia (2013 to 2019), showed robust predictions for flowering time (n = 29; R2 = 0.97), and grain yield (n = 22; R2 = 0.63–0.70). In addition, we identified threshold cold temperatures that significantly affected predicted yield, and combinations of locations, variety, and sowing time where the overlap between peak cold temperatures and peak flowering was minimal. Our results showed that frost and/or cold temperature–induced yield losses are a major limitation in some unexpected Australian locations, e.g., inland, subtropical latitudes in Queensland. Intermediate sowing maximise yield, as it avoids cold temperature, late heat, and drought stresses potentially limiting yield in early and late sowing respectively.

Relationships of frequencies of extreme low temperatures with grain yield of some Australian commercial chickpea cultivars

“…As both lowtemperature days and post-flowering frosts were significantly related because they seem to co-occur, separate studies will be required to clarify whether their effects are distinct. Croser et al (2003) considered them independent abiotic stress factors impacting chickpea yield, while Anwar et al (2022) clubbed them to analyse their combined effects as the chilling effects. Frost can damage cells and kill the tissue, while low temperatures could reduce pod set by affecting pollen viability and fertilisation.…”

“…Because of this, the environments where these temperature-related stresses occur tend to have greater observed and modelled grain yield discrepancies. Correction of simulated yield using these estimates improved grain yield prediction by the APSIM chickpea model (Anwar et al 2022). Lake and Sadras (2014) considered improving abiotic stress tolerance in chickpea during the critical period, which they defined as 800°Cd long, with only 2/3rd of this period falling after flowering.…”

“…The current improvement efforts on temperature extremes are primarily focused on heat stress, mainly due to the heightened threat of climate change (Jeffrey et al 2021). However, as a winter crop, chickpea's vulnerability to low-temperature stress also requires attention (Maqbool et al 2010;Dreccer et al 2018;Anwar et al 2022). Losses in grain yield attributed to extreme low-temperature events, including frosts and low ambient temperatures, are recognised to be a significant problem for chickpea grown in subtropical and temperate environments (Dalal et al 1998;Croser et al 2003;Gowda et al 2009;Chauhan and Ryan 2020;Singh et al 2016).…”

Impact of Sowing Time and Genotype on Water Use Efficiency of Lentil (Lens culinaris Medick.)

“…Rainfall, evapotranspiration (ET), runoff and drainage are important water parameters [30] that influence water availability to crops [31,32]. Temperature, rainfall, initial soil water and soil water at harvest were measured, and these data were used as the basis for calculating water parameters for this study [33,34] following the procedure of [35] to determine the soil water balance. The farming systems model APSIM [36] version 7.10 was used to calculate the hydraulic parameters (starting and ending daily soil water content, water use, runoff, drainage and soil evaporation).…”

“…The farming systems model APSIM [36] version 7.10 was used to calculate the hydraulic parameters (starting and ending daily soil water content, water use, runoff, drainage and soil evaporation). The parameters in the Soil Water module of APSIM are the same as those used in [33,34]. We assumed that the initial soil water was equal to LL15 (water content at 15 bar suction) on 1 January 2009.…”