High-throughput phenotyping of nitrogen and biomass partitioning of central European wheat cultivars and breeding lines during grain filling in different climatic zones

表型分析的挑战是发展高通量精确的表型分析技术，这是改进农业实践的育种研究的瓶颈之一。在不降低小麦产量的前提下，获得较高的蛋白质含量是小麦品质遗传改良的关键。因此，我们的假设是，高通量光谱表型的植物性状的生物量和籽粒产量形成随着时间的推移，在灌浆过程中可以评估Nrem/Nup和库/源关系之间的关系，以实现高氮利用效率，并提高产量和蛋白质含量在小麦育种的选择效率。 最终目的是获得足够的知识，以确定潜在的Nrem（N再动员），Nup（N吸收），Nsto（N存储）和库源关系，控制籽粒灌浆过程中的氮沉积过程中，从而提供关键的生理性状，籽粒蛋白质浓度的遗传改良，而不影响籽粒产量的高通量和成本效益的表型技术。具体目标是：i）评估光谱指数和/或其他算法的敏感性，以检测在最佳土壤氮水平和一系列气候带下灌浆期间对总谷物氮沉积、Nrem、Nup、Nsto和库源关系的基因型效应; ii）评估光谱指数和其他算法作为一种潜在的高通量表型分析技术的有效性，用于总谷物N沉积，Nrem，Nup，NSTO和库源关系; iii）与基于图像的方法进行比较; iv）将光谱指数/最佳算法与小麦基因组的遗传图谱联系起来，以便更好地了解基因座对籽粒产量和冬小麦灌浆期间氮素利用效率的重要性。重要性：i）这一知识将最终导致一种更合理和有效的方法，使用光谱传感器进行高通量表型分析，以更好地了解谷物氮沉积机制，并找到所需性状的适当措施，以便在气候变化的背景下获得冬小麦的高产潜力和高氮浓度; ii）在田间定向育种中成功实施高通量精确表型分型技术将缩小我们目前基因分型和表型分型能力之间的差距;在不同气候带鉴定的高产潜力和高谷物蛋白质浓度的植物性状将迎接未来的挑战，这需要在未来气候变化中看到的生理变化的量子进步的规模。

The challenge to phenotyping - one of the bottlenecks in breeding research in improvement of agricultural practices - is to develop high-throughput precision phenotyping techniques. To ensure wheat yield stability and grain quality, the key physiological traits for genetic improvement are to obtain high grain protein content without a decrease in grain yield of wheat. Therefore, our hypothesis is that high-throughput spectral phenotyping of plant traits of biomass and grain yield formation over time during grain filling can assess the relationships between Nrem/Nup and sink/source relations to achieve high N use efficiency and to improve selection efficiency for yield and protein content in wheat breeding. The ultimate objective is to obtain sufficient knowledge to identify the potential traits of Nrem (N remobilization), Nup (N uptake), Nsto (N storage) and sink-source relations which control the processes of grain N deposition during grain filling, thereby providing the key physiological traits for genetic improvement of grain protein concentration without affecting grain yield of wheat using high-throughput and cost-effective phenotyping techniques. The specific objectives are: i) to assess the sensitivity of spectral indices and/or other algorithms for detecting genotypic effects on total grain N deposition, Nrem, Nup, Nsto and sink-source relations during the grain filling at optimal soil N levels and under a range of climatic zones; ii) to evaluate the validity of spectral indices and other algorithms as a potential high-throughput phenotyping technique for total grain N deposition, Nrem, Nup, Nsto and sink-source relations; iii) to compare with image-based approaches; and iv) to link spectral indices/best algorithms with the genetic map of the wheat genome allowing a better understanding of the importance of loci for grain yield and N use efficiency of winter wheat during grain filling. Significance: i) This knowledge will ultimately lead to a more rational and effective approach to high-throughput phenotyping using spectral sensors for a better understanding of grain N deposition mechanisms and to find the suitable measures for the desired traits in order to obtain high yielding potential and high N concentrations of winter wheat within the context of climate changes; ii) The successful implementation of high-throughput precision phenotyping technologies in field-oriented breeding will narrow the gap between our current genotyping and phenotyping capabilities; and iii) Plant traits identified in different climatic zones for high yielding potential and high grain protein concentration will meet the challenges ahead, which requires the scale of quantum advances for the physiological changes being seen in future climate changes.