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.

包括玉米在内的世界上许多主要作物正在接近产量平台，这意味着有必要利用其他手段（遗传和生理手段）来继续提高产量。由于达到生物学极限、种质库内缺乏有用的遗传变异或两者兼而有之，产量停滞不前。克服产量平台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基础。在玉米中，改变谷物产量的生物学有两个潜在目标：（1）增加最终形成谷物的总生物量的比例，这被称为收获指数。 (2) 控制灌浆期的长度，灌浆期是从开花到生理成熟之间的时间段。本研究的目的是针对这两个难以表型的性状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，对这两个属性进行表型分析是高度劳动密集型的，并且需要对植物进行破坏性采样，这使得不可能以高通量方式进行表型分析。为了克服当前表型分析的挑战，我们建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并确定生理成熟时的生物量。然后，将生理成熟度的生物量与机器可收获的谷物重量相结合，生成 HI 估计值。通过能够有效地对生理成熟度和 HI 进行表型分析，我们可以检查控制性状的遗传学，识别它们的新遗传变异，并检查基因型与环境 (GxE) 如何影响它们。虽然这项研究提案涉及玉米，但该方法和概念适用于所有作物品种。