AgriBio, Centre for AgriBioscience, Agriculture Victoria Research, Bundoora, VIC, 3083, Australia.
Hamilton Centre, Agriculture Victoria Research, Hamilton, VIC, 3300, Australia.
Theor Appl Genet. 2023 Mar 10;136(3):44. doi: 10.1007/s00122-023-04263-8.
Breeding target traits can be broadened to include nutritive value and plant breeder's rights traits in perennial ryegrass by using in-field regression-based spectroscopy phenotyping and genomic selection. Perennial ryegrass breeding has focused on biomass yield, but expansion into a broader set of traits is needed to benefit livestock industries whilst also providing support for intellectual property protection of cultivars. Numerous breeding objectives can be targeted simultaneously with the development of sensor-based phenomics and genomic selection (GS). Of particular interest are nutritive value (NV), which has been difficult and expensive to measure using traditional phenotyping methods, resulting in limited genetic improvement to date, and traits required to obtain varietal protection, known as plant breeder's rights (PBR) traits. In order to assess phenotyping requirements for NV improvement and potential for genetic improvement, in-field reflectance-based spectroscopy was assessed and GS evaluated in a single population for three key NV traits, captured across four timepoints. Using three prediction approaches, the possibility of targeting PBR traits using GS was evaluated for five traits recorded across three years of a breeding program. Prediction accuracy was generally low to moderate for NV traits and moderate to high for PBR traits, with heritability highly correlated with GS accuracy. NV did not show significant or consistent correlation between timepoints highlighting the need to incorporate seasonal NV into selection indexes and the value of being able to regularly monitor NV across seasons. This study has demonstrated the ability to implement GS for both NV and PBR traits in perennial ryegrass, facilitating the expansion of ryegrass breeding targets to agronomically relevant traits while ensuring necessary varietal protection is achieved.
通过田间回归光谱表型分析和基因组选择,可以将牧草的目标特性拓宽至营养价值和植物育种者权利特性。黑麦草的选育一直侧重于生物量产量,但为了使畜牧业受益,同时为品种保护提供知识产权支持,需要将选育目标扩展到更广泛的特性。随着基于传感器的表型组学和基因组选择 (GS) 的发展,许多选育目标可以同时得到实现。特别值得关注的是营养价值 (NV),由于传统的表型分析方法难以测量,且成本高昂,因此迄今为止对其进行的遗传改良有限,而获得品种保护所需的特性,即植物育种者权利 (PBR) 特性。为了评估提高 NV 和遗传改良潜力的表型分析要求,本研究评估了田间反射率光谱法,并在单个群体中对三个关键 NV 特性进行了 GS 评估,这些特性在四个时间点进行了采集。使用三种预测方法,评估了在三年的选育计划中记录的五个特性的 GS 对 PBR 特性的靶向可能性。对于 NV 特性,预测准确性通常较低到中等,对于 PBR 特性,预测准确性中等到较高,遗传力与 GS 准确性高度相关。NV 特性在时间点之间没有显示出显著或一致的相关性,这突出表明需要将季节性 NV 纳入选择指数,并能定期监测整个季节的 NV。本研究证明了在黑麦草中实施 GS 对 NV 和 PBR 特性的能力,促进了黑麦草选育目标向与农艺学相关的特性扩展,同时确保了必要的品种保护。