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

表型分析的挑战是开发高通量的精确表型分析技术，这是改进农业实践育种研究的瓶颈之一。在保证小麦产量稳定和品质的前提下，获得较高的籽粒蛋白质含量是小麦遗传改良的关键生理性状。因此，我们的假设是，灌浆期间生物量和籽粒产量形成的植物性状随时间的高通量光谱表型可以评估Nrem/Nup和库源关系，从而实现较高的氮素利用效率，提高小麦育种中产量和蛋白质含量的选择效率。最终目的是获得足够的知识，以确定籽粒灌浆过程中控制籽粒氮沉积过程的Nrem （N再动员）、Nup （N吸收）、nto （N储存）和库源关系的潜在性状，从而利用高通量和高成本效益的表型技术，在不影响籽粒产量的情况下，为籽粒蛋白质浓度的遗传改良提供关键生理性状。具体目标是：i)评估在最佳土壤氮水平和一系列气气带条件下，籽粒灌浆过程中，光谱指数和/或其他检测基因型对籽粒总氮沉降、Nrem、Nup、nto和库源关系影响的敏感性；ii)评估光谱指数和其他算法作为全粒氮沉积、Nrem、Nup、nto和库源关系的潜在高通量表型技术的有效性；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遗传图谱联系起来，以便更好地了解籽粒灌浆过程中基因座对籽粒产量和氮素利用效率的重要性。意义：1)利用光谱传感器进行高通量表型分析，有助于更好地了解籽粒氮沉积机制，并找到所需性状的合适措施，从而在气候变化背景下获得高产潜力和高氮浓度的冬小麦；ii)高通量精确表型技术在田间育种中的成功实施将缩小我们目前基因分型和表型分型能力之间的差距；iii)在不同气候带中确定的具有高产潜力和高籽粒蛋白浓度的植物性状将迎接未来的挑战，这需要大规模的量子进展来应对未来气候变化中所看到的生理变化。

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.