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在植物育种计划中大规模实施表型组学面临的挑战。

Challenges for a Massive Implementation of Phenomics in Plant Breeding Programs.

机构信息

Plant Breeding and Phenomics Center, Faculty of Agricultural Sciences, Universidad de Talca, Talca, Chile.

Department of Agricultural Sciences, Universidad Católica del Maule, Curico, Chile.

出版信息

Methods Mol Biol. 2022;2539:135-157. doi: 10.1007/978-1-0716-2537-8_13.

Abstract

Due to climate change and expected food shortage in the coming decades, not only will it be necessary to develop cultivars with greater tolerance to environmental stress, but it is also imperative to reduce breeding cycle time. In addition to yield evaluation, plant breeders resort to many sensory assessments and some others of intermediate complexity. However, to develop cultivars better adapted to current/future constraints, it is necessary to incorporate a new set of traits, such as morphophysiological and physicochemical attributes, information relevant to the successful selection of genotypes or parents. Unfortunately, because of the large number of genotypes to be screened, measurements with conventional equipment are unfeasible, especially under field conditions. High-throughput plant phenotyping (HTPP) facilitates collecting a significant amount of data quickly; however, it is necessary to transform all this information (e.g., plant reflectance) into helpful descriptors to the breeder. To the extent that a holistic characterization of the plant (phenomics) is performed in challenging environments, it will be possible to select the best genotypes (forward phenomics) objectively but also understand why the said individual differs from the rest (reverse phenomics). Unfortunately, several elements had prevented phenomics from developing as desired. Consequently, a new set of prediction/validation methodologies, seasonal ambient information, and the fusion of data matrices (e.g., genotypic and phenotypic information) need to be incorporated into the modeling. In this sense, for the massive implementation of phenomics in plant breeding, it will be essential to count an interdisciplinary team that responds to the urgent need to release material with greater capacity to tolerate environmental stress. Therefore, breeding programs should (i) be more efficient (e.g., early discarding of unsuitable material), (ii) have shorter breeding cycles (fewer crosses to achieve the desired cultivar), and (iii) be more productive, increasing the probability of success at the end of the breeding process (percentage of cultivars released to the number of initial crosses).

摘要

由于气候变化和未来几十年预计的粮食短缺,不仅有必要开发对环境胁迫具有更大耐受性的品种,而且还必须减少育种周期时间。除了产量评估外,植物育种者还诉诸于许多感官评估和一些其他中等复杂程度的评估。然而,为了开发更好地适应当前/未来限制的品种,有必要引入一组新的性状,例如形态生理和物理化学特性,与基因型或亲本成功选择相关的信息。不幸的是,由于需要筛选的基因型数量众多,使用常规设备进行测量是不可行的,特别是在田间条件下。高通量植物表型分析(HTPP)便于快速收集大量数据;但是,有必要将所有这些信息(例如,植物反射率)转换为对育种者有用的描述符。在具有挑战性的环境中对植物进行整体表征(表型组学)的程度,就有可能客观地选择最佳基因型(正向表型组学),也可以了解为什么该个体与其他个体不同(反向表型组学)。不幸的是,有几个因素阻止了表型组学的发展。因此,需要将一组新的预测/验证方法、季节性环境信息以及数据矩阵(例如,基因型和表型信息)的融合纳入到建模中。从这个意义上说,为了在植物育种中大规模实施表型组学,必须有一个跨学科的团队来响应释放具有更大环境胁迫耐受性能力的材料的紧迫需求。因此,育种计划应该:(i)更高效(例如,早期淘汰不合适的材料);(ii)缩短育种周期(实现所需品种的杂交次数减少);(iii)更具生产力,增加育种过程结束时成功的概率(释放的品种数量与初始杂交数量的百分比)。

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