Abstract
Cold, heat and soil water deficit, are major abiotic stresses that cause spatial and temporal variation in chickpea yield. Yield losses depend on the stress intensity in relation to the crop’s phenological development. Adjustment of sowing time has been anecdotally used to manipulate flowering time, the most
sensitive stage of the crop. However, this approach has limitations since flowering also interacts with soil water and within-season rainfall. In this study, the APSIM-Chickpea model was validated using field experiments. We demonstrate how accounting for improved predictions in flowering time can be used to minimise yield losses. Simulated chickpea crops were “sown” at 10-day intervals from 1-March to 29-July over a 71-year period. Thresholds of cold temperature, seasonal water supply, and extremes of temperature were then examined with respect to chickpea yields. We identified optimal sowing windows that will minimise overlap between flowering, extreme temperatures, and terminal soil water stress, leading to potential improved yields.
sensitive stage of the crop. However, this approach has limitations since flowering also interacts with soil water and within-season rainfall. In this study, the APSIM-Chickpea model was validated using field experiments. We demonstrate how accounting for improved predictions in flowering time can be used to minimise yield losses. Simulated chickpea crops were “sown” at 10-day intervals from 1-March to 29-July over a 71-year period. Thresholds of cold temperature, seasonal water supply, and extremes of temperature were then examined with respect to chickpea yields. We identified optimal sowing windows that will minimise overlap between flowering, extreme temperatures, and terminal soil water stress, leading to potential improved yields.
Original language | English |
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Title of host publication | Proceedings of the 20th Australian Agronomy Conference |
Publisher | Australian Society of Agronomy |
Pages | 1-4 |
Number of pages | 4 |
Publication status | Published - 2022 |