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

包括玉米在内的许多世界主要农作物正在接近产量平台期，这意味着必须利用其他手段(包括遗传和生理手段)来继续提高产量。产量停滞不前是由于达到了生物极限，种质库中缺乏有用的遗传变异，或者两者兼而有之。克服产量停滞不前将取决于创造新的遗传变异，并潜在地改变谷物产量的生物学基础。在玉米中，有两个潜在的目标来改变谷物产量的生物学基础：(1)增加最终进入谷物中的总生物量的比例，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一段时间。这项研究的目的是建立基于光谱反射率的表型鉴定方法，用于这两个难以表型的性状：(1)生理成熟度和(2)收获指数。目前，这两个属性的表型鉴定是高度劳动密集型的，需要对植物进行破坏性采样，这使得不可能以高通量的方式进行表型鉴定。为了克服目前的表型挑战，我们建议利用一种基于光谱反射的方法来确定一个基因何时接近生理成熟，并确定生理成熟时的生物量。然后将生理成熟时的生物量与机器可收获的谷粒重量相结合，生成HI估计。通过能够有效地对生理成熟度和HI进行表型，我们可以检查控制这些性状的遗传学，识别它们的新的遗传变异，并检查不同环境(GxE)对它们的影响。虽然这项研究方案涉及玉米，但其方法和概念适用于所有作物种类。

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.