Fine tuning crop development is a major breeding avenue to increase crop yield and for adaptation to climate change. We used an ecophysiological model that integrates our current understanding of the physiology of wheat phenology to predict the development and anthesis date of 91 recombinant inbreed lines (RILs) of durum wheat with genotypic parameters controlling vernalization requirement, photoperiod sensitivity, and earliness per se estimated using leaf stage, final leaf number, anthesis date data from a pot experiment with vernalized and nonvernalized treatments combined with short- and long-day length. Predictions of final leaf number and anthesis date of the QTL-based model was evaluated for the whole population of RILs in a set of independent field trials and for the two parents, which were not used to estimate the parameter values. Our novel approach reduces the number of environments and the time required to obtain the required data sets to develop a QTL-based prediction of model parameters. Moreover, the use of a physiologically based model of phenology gives new insight into genotype-phenology relations for wheat. We discuss the approach we used to estimate the parameters of the model and their association with QTL and major phenology genes that collocate at QTL.

中文翻译：

---

使用基于 QTL 的模型剖析硬粒小麦开花时间到生理性状


微调作物生长是提高作物产量和适应气候变化的主要育种途径。我们使用了一个生态生理学模型，该模型整合了我们目前对小麦物候生理学的理解，以预测 91 个硬粒小麦重组近交系 （RIL） 的发育和开花日期，其基因型参数控制春化要求、光周期敏感性和早熟性本身使用叶期、最终叶号、开花日期数据估计来自春化和非春化处理结合短日和长日长度的盆栽实验数据。 在一组独立的田间试验中，对整个 RILs 群体和两个亲本评估了基于 QTL 的模型的最终叶片数和开花日期的预测，这些预测不用于估计参数值。我们的新方法减少了环境数量和获得所需数据集所需的时间，以开发基于 QTL 的模型参数预测。此外，使用基于生理学的物候模型为小麦的基因型-物候关系提供了新的见解。我们讨论了我们用来估计模型参数的方法以及它们与 QTL 和在 QTL 搭配的主要物候基因的关联。