Rice (Oryza sativa L.) ratooning, a sustainable production system involves regrowing a second rice crop and it is a very common practice in southwest United States. Employing modern tools such as genomic selection (GS) can enhance breeding efficiency by enabling early selection. The Louisiana State University Rice Breeding Program has traditionally focused on developing superior varieties for the Louisiana's rice industry, however ratoon (RT) performance has typically been considered only in the late breeding stages, when there is little genetic variability available, and all the previous selections were made based on other qualitative and quantitative traits. Therefore, we aimed to verify if our pipeline for variety development is efficient in simultaneously selecting top grain yield performance lines for both harvest seasons: the main crop (H1) and the RT. In this context, we tested the following approaches: 1) Selection index, 2) Indirect selection, and 3) GS. Grain yield data evaluated over three years and three locations from the MP6‐8 population was used in this study. The results highlighted the genetic potential to be explored and the reliability of the data quality. Despite the low phenotypic and genotypic correlations between the first and second harvests (0.11 and 0.12, respectively), the plant response indices proved inefficient for dual‐season selection. Consequently, genotype ranking changed between harvest seasons, suggesting their relative independence. In simpler terms, the genotype that yields the highest productivity for H1 may not necessarily be the same for RT. Our study highlights the feasibility of using GS tools to perform early selections for RT and underscores it as a target trait in the breeding decision‐making process.

中文翻译：

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基因组选择对水稻轮距早期性能的益处


水稻 （Oryza sativa L.） 种植，一种可持续的生产系统涉及重新种植第二季稻作物，这在美国西南部是一种非常普遍的做法。采用基因组选择 （GS） 等现代工具可以通过实现早期选择来提高育种效率。路易斯安那州立大学水稻育种计划传统上专注于为路易斯安那州的水稻行业开发优质品种，但通常只在育种后期考虑再生元 （RT） 性能，此时几乎没有可用的遗传变异性，并且之前的所有选择都是基于其他定性和定量性状进行的。因此，我们旨在验证我们的品种开发管道是否能有效地同时为两个收获季节选择最佳谷物产量表现线：主要作物 （H1） 和 RT。在此背景下，我们测试了以下方法：1） 选择指数，2） 间接选择，以及 3） GS。本研究使用了 MP6-8 种群的三个位置评估了三年来的谷物产量数据。结果突出了有待探索的遗传潜力和数据质量的可靠性。尽管第一次和第二次收获之间的表型和基因型相关性较低（分别为 0.11 和 0.12），但植物响应指数被证明对于双季选择效率低下。因此，基因型排名在收获季节之间发生变化，表明它们相对独立。简单来说，为 H1 产生最高生产率的基因型不一定与 RT 相同。我们的研究强调了使用 GS 工具进行 RT 早期选择的可行性，并强调它是育种决策过程中的目标性状。