Environmental stresses from climate change can alter source–sink relations during plant maturation, leading to premature senescence and decreased yields. Elucidating the genetic control of natural variations for senescence in wheat (Triticum aestivum) can be accelerated using recent developments in unmanned aerial vehicle (UAV)-based imaging techniques. Here, we describe the use of UAVs to quantify senescence in wheat using vegetative indices (VIs) derived from multispectral images. We detected senescence with high heritability, as well as its impact on grain yield (GY), in a doubled-haploid population and parent cultivars at various growth time points (TPs) after anthesis in the field. Selecting for slow senescence using a combination of different UAV-based VIs was more effective than using a single ground-based vegetation index. We identified 28 quantitative trait loci (QTL) for vegetative growth, senescence, and GY using a 660K single-nucleotide polymorphism array. Seventeen of these new QTL for VIs from UAV-based multispectral imaging were mapped on chromosomes 2B, 3A, 3D, 5A, 5D, 5B, and 6D; these QTL have not been reported previously using conventional phenotyping methods. This integrated approach allowed us to identify an important, previously unreported, senescence-related locus on chromosome 5D that showed high phenotypic variation (up to 18.1%) for all UAV-based VIs at all TPs during grain filling. This QTL was validated for slow senescence by developing kompetitive allele-specific PCR markers in a natural population. Our results suggest that UAV-based high-throughput phenotyping is advantageous for temporal assessment of the genetics underlying for senescence in wheat.

中文翻译：

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使用无人机的多光谱成像和 QTL 映射量化面包小麦的衰老

气候变化带来的环境压力可以改变植物成熟过程中的源库关系，导致过早衰老和产量下降。利用基于无人机 (UAV) 的成像技术的最新发展，可以加速阐明小麦 (Triticum aestivum) 衰老的自然变异的遗传控制。在这里，我们描述了使用无人机使用从多光谱图像中得出的植物指数 (VI) 来量化小麦的衰老。我们在田间开花后的不同生长时间点 (TPs) 检测到双单倍体种群和亲本品种具有高遗传力的衰老及其对籽粒产量 (GY) 的影响。使用不同的基于无人机的 VI 组合来选择缓慢衰老比使用单一的基于地面的植被指数更有效。我们使用 660K 单核苷酸多态性阵列鉴定了营养生长、衰老和 GY 的 28 个数量性状基因座 (QTL)。来自基于无人机的多光谱成像的 VI 的这些新 QTL 中有 17 个被映射到染色体 2B、3A、3D、5A、5D、5B 和 6D；这些 QTL 以前没有使用传统的表型分析方法报道过。这种综合方法使我们能够在 5D 染色体上识别出一个重要的、以前未报告的、与衰老相关的基因座，该基因座在谷物灌浆期间在所有 TP 处显示所有基于无人机的 VI 的高表型变异（高达 18.1%）。通过在自然群体中开发竞争性等位基因特异性 PCR 标记，验证了该 QTL 的缓慢衰老。