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

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...

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Detalles Bibliográficos
Autores principales: 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
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8727402/
https://www.ncbi.nlm.nih.gov/pubmed/34609561
http://dx.doi.org/10.1007/s00484-021-02197-8
Descripción
Sumario: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; R(2) = 0.97), and grain yield (n = 22; R(2) = 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. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s00484-021-02197-8.