Abstract We developed a photoperiod-corrected thermal model that can predict wheat phenology based solely on the combination of photoperiod (Ppd) and vernalisation (Vrn) alleles to identify the phenological suitability of germplasm across the cropping region in southern Australia. More than 200 wheat genotypes that vary in combinations of Ppd and Vrn alleles were grown at 17 locations spanning 11° Latitude, thus providing a wide range in temperature and daylength gradients. The phenological sensitivities of a genotype to varying basic temperature, photoperiod and vernalisation requirement was adjusted via optimisation to minimise the least square difference between the measured and predicted dates of both terminal spike (TS) and flowering (AN). The model predicted dates of TS and AN to within 5 days of the field values. Information was used to identify the alleles required to achieve a wheat ideotype defined in a previous study. The optimum allelic combinations required to target the optimum flowering period for different locations when sown on different dates were also identified. The use of allelic based phenological models has the potential to reduce the costs to breeding programs and accelerate the release of better adapted germplasm to new and changing environments.

中文翻译：

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基于等位基因的预测小麦阶段发育的物候模型 (Triticum aestivum L.)

摘要 我们开发了一种光周期校正的热模型，该模型可以仅基于光周期 (Ppd) 和春化 (Vrn) 等位基因的组合来预测小麦物候，以确定澳大利亚南部种植区种质的物候适宜性。超过 200 种不同 Ppd 和 Vrn 等位基因组合的小麦基因型在跨越 11°纬度的 17 个地点生长，因此提供了广泛的温度和日长梯度。通过优化调整基因型对变化的基本温度、光周期和春化要求的物候敏感性，以最小化终端穗 (TS) 和开花 (AN) 的测量日期和预测日期之间的最小二乘差异。该模型预测 TS 和 AN 的日期在字段值的 5 天内。信息用于鉴定实现先前研究中定义的小麦基因型所需的等位基因。还确定了在不同日期播种时针对不同地点的最佳开花期所需的最佳等位基因组合。使用基于等位基因的物候模型有可能降低育种计划的成本，并加速将更适应的种质释放到新的和不断变化的环境中。