RESUMO
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.
Assuntos
Cicer , Agricultura , Austrália , Temperatura Baixa , Grão ComestívelRESUMO
Waterlogging remains a significant constraint to cereal production across the globe in areas with high rainfall and/or poor drainage. Improving tolerance of plants to waterlogging is the most economical way of tackling the problem. However, under severe waterlogging combined agronomic, engineering and genetic solutions will be more effective. A wide range of agronomic and engineering solutions are currently being used by grain growers to reduce losses from waterlogging. In this scoping study, we reviewed the effects of waterlogging on plant growth, and advantages and disadvantages of various agronomic and engineering solutions which are used to mitigate waterlogging damage. Further research should be focused on: cost/benefit analyses of different drainage strategies; understanding the mechanisms of nutrient loss during waterlogging and quantifying the benefits of nutrient application; increasing soil profile de-watering through soil improvement and agronomic strategies; revealing specificity of the interaction between different management practices and environment as well as among management practices; and more importantly, combined genetic, agronomic and engineering strategies for varying environments.