Author:
Anwar Muhuddin Rajin,Luckett David J.,Chauhan Yashvir S.,Ip Ryan H. L.,Maphosa Lancelot,Simpson Marja,Warren Annie,Raman Rosy,Richards Mark F.,Pengilley Georgina,Hobson Kristy,Graham Neroli
Abstract
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.
Funder
Grains Research and Development Corporation
Publisher
Springer Science and Business Media LLC
Subject
Health, Toxicology and Mutagenesis,Atmospheric Science,Ecology
Reference53 articles.
1. ABARES (2020) Australian crop report, Australian Bureau of Agricultural and Resource Economics and Sciences, Canberra, June. CC BY 4.0. https://doi.org/10.25814/5ec20eb43b2b7
2. Abbo S, Shtienberg D, Lichtenzveig J, Lev-Yadun S, Gopher A (2003) The chickpea, summer cropping, and a new model for pulse domestication in the ancient near east. Q Rev Biol 78:435–448. https://doi.org/10.1086/378927
3. Anwar MR, Chauhan YS, Richards MF, Luckett D, Raman R, Graham N (2019) Predictions of optimal chickpea flowering time for better yield. Australian Pulse Conference, 15–17 October 2019, Horsham, Victoria, Australia, https://apc2019.com.au/abstracts/
4. Berger JD, Kumar S, Nayyar H, Street KA, Sandhu JS, Henzell JM, Kaur J, Clarke HC (2012) Temperature-stratified screening of chickpea (Cicer arietinum L.) genetic resource collections reveals very limited reproductive chilling tolerance compared to its annual wild relatives. Field Crop Res 126:119–129. https://doi.org/10.1016/j.fcr.2011.09.020
5. Berger JD, Turner NC, Siddique KHM, Knights EJ, Brinsmead RB, Mock I, Edmondson C, Khan TN (2004) Genotype by environment studies across Australia reveal the importance of phenology for chickpea (Cicer arietinum L.) improvement. Aust J Agr Res 55:1071–1084. https://doi.org/10.1071/Ar04104