Preharvest sprouting (PHS) resistance is essential in malting barley (Hordeum vulgare L.) production to prevent damage caused by late season moisture but may be negatively correlated with malting quality traits. The germination percentage and germination rate (GI) in malting barley are measures of both PHS resistance and suitability for malting. Functional principal component analysis (FPCA) and logistic regression on time series spring malting barley GE and GI were performed to identify genetic regions associated with germination trait changes from 0 to 22 wk after maturity. Both analysis methods identified the SD1 and SD2 regions known to affect germination traits, as well as one novel locus on chromosome 6H at 473 Mbp. Several other associations were detected with a single analysis method. Genomic prediction (GP) was used in conjunction with the time series models to test GE and GI predictability over time. Germination traits of unobserved lines at unobserved times were predicted with high accuracy using ridge regression GP coupled with FPCA or logistic regression. The results demonstrate applicability of time series data analysis in determining genetics of germination trait changes in malting barley and that time series germination is predictable. Threshold traits calculated with these time series models, such as the after-ripening time needed until a line achieves a GE of 95%, can be used as an estimate for dormancy duration, which will be useful in breeding for combined PHS resistance and malting quality.

中文翻译：

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时间序列大麦发芽是可预测的，并且与已知的种子休眠位点相关

收获前发芽 (PHS) 抗性对于麦芽大麦 ( Hordeum vulgare L.) 生产至关重要，可防止晚季水分造成的损害，但可能与麦芽品质性状呈负相关。发芽大麦的发芽率和发芽率 (GI) 是衡量 PHS 抗性和发芽适宜性的指标。对时间序列春季麦芽大麦 GE 和 GI 进行功能主成分分析 (FPCA) 和逻辑回归，以确定与成熟后 0 至 22 周的发芽性状变化相关的遗传区域。两种分析方法都确定了SD1和SD2已知影响发芽性状的区域，以及染色体 6H 上 473 Mbp 的一个新基因座。使用单一分析方法检测到其他几个关联。基因组预测 (GP) 与时间序列模型结合使用，以测试 GE 和 GI 随时间的可预测性。使用岭回归 GP 与 FPCA 或逻辑回归相结合，可以高精度地预测未观察到的系在未观察到的时间的发芽性状。结果证明了时间序列数据分析在确定大麦发芽性状变化的遗传学方面的适用性，并且时间序列发芽是可预测的。使用这些时间序列模型计算的阈值性状，例如直到一条线达到 95% 的 GE 所需的后熟时间，可以用作休眠持续时间的估计值，