Physiological & Genetic Mechanisms Underlying Grain Yield - Development of Novel Phenotyping Methods

生理

• 批准号: RGPIN-2019-05137
• 负责人: Lee, Elizabeth
• 金额: $ 2.4万
• 依托单位: University of Guelph
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2022
• 资助国家: 加拿大
• 起止时间: 2022-01-01 至 2023-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=763545
• 关键词: Physiological; Genetic; Mechanisms; Underlying; Grain

Many of the world's staple crops including maize are approaching yield plateaus meaning that it will be necessary to exploit other means (both genetic & physiological) for continuing to make yield advances. Yield plateaus arise due to biological limits being reached, lack of useful genetic variation within the germplasm pool, or a combination of both. Overcoming yield plateaus will rely on creating novel genetic variation and potentially altering the biology underlying grain yield. In maize there are two potential targets for altering the biology underlying grain yield: (1) Increasing the proportion of the total biomass that ends up in the grain, which is referred to as harvest index. (2) Manipulating the length of the grain-filling period, which is the period of time between flowering and physiological maturity. The aim of the proposed research is to develop spectral reflectance-based phenotyping methods for these two difficult to phenotype traits: (1) physiological maturity and (2) harvest index. Currently phenotyping these two attributes is highly labour intensive and requires destructive sampling of the plants, which makes it impossible to phenotype in a high-throughput manner. To overcome the current phenotyping challenges, we are proposing to utilize a spectral reflectance based approach for determining when a genotype is approaching physiological maturity and for determining the biomass at physiological maturity. The biomass at physiological maturity will then be combined with machine harvestable grain weight to generated HI estimates. By being able to phenotype physiological maturity and HI efficiently we can then examine the genetics governing the traits, identify novel genetic variation for them, and examine how genotype-by-environment (GxE) influences them. While this research proposal involves maize, the approach and concepts are applicable to all crop species.

世界上许多包括玉米在内的主食都在接近产量高原，这意味着有必要利用其他手段（遗传和生理学）继续取得收益率。由于达到生物学极限，在种质池内缺乏有用的遗传变异或两者的组合而产生的产量高原。克服产量的高原将依赖于创造新的遗传变异，并可能改变谷物产量的生物学。在玉米中，有两个潜在的靶标可以改变谷物产量的基本生物学：（1）增加最终在谷物中的总生物量的比例，这被称为收获指数。 （2）操纵谷物填充期的长度，这是开花和生理成熟之间的时间。拟议的研究的目的是为这两种难以表型特征开发基于光谱反射率的表型方法：（1）生理成熟度和（2）收获指数。目前，将这两个属性表型是高度强度的，需要对植物进行破坏性采样，这使得无法以高通量方式表型。为了克服当前的表型挑战，我们提议利用基于光谱反射率的方法来确定基因型何时接近生理成熟度并确定生理成熟时的生物量。然后，生理成熟度的生物量将与机器可获得的晶粒重量结合到产生的HI估计值。通过能够表现出生理成熟和高效，我们可以检查控制特征的遗传学，确定它们的新遗传变异，并检查基因型逐个环境（GXE）如何影响它们。尽管该研究建议涉及玉米，但方法和概念适用于所有农作物物种。