In response to the challenges posed by population growth and climate change to food production security, current and past breeders have been working on sustainable green wheat breeding. Breeders have long focused on extending the duration of wheat green leaf area to achieve maximum carbon assimilation and increase yield. The functional stay-green (SG) sustaining photosynthetic competence during senescence is a novel trait to describe the duration of wheat green leaf area. Unmanned aerial vehicle (UAV) imagery is emerging as an effective high-throughput phenotyping tool that replaced the high costs and easily affected by subjective factors of traditional phenotyping. Based on specific colour characteristics, wavebands and wavelengths, UAV-based multispectral imagery allows the calculation of vegetation indices (VIs), which have been used as proxies to obtain information about SG. In this research, we dynamically monitored the morphological and physiological changes of 565 wheat accessions from florescence to late maturity at high-density time points using high-throughput UAV-based Vis. Then we draw the dynamic curves of different wheat accessions and analyzed the key nodes most associated with SG traits. Combining these phenotypic index data and resequencing genotypic data, we performed GWAS to dissect the genetic architecture of SG traits in these wheat accessions and detected a large number of dynamic QTL associated with SG traits in different growth periods. Most of these QTL were related to metabolites, hormones and enzymes in plant growth and development and senescence. Further, based on both RNA-seq and haplotype analysis, we preliminarily identified a candidate gene TraesCS5A02G550800 which encodes a subunit of NAC, BTF3. BTF3 or NAC plays an important role in the regulation of plant senescence in previous studies, and its specific regulatory effect is under way in our research. UAV-based high-throughput field phenotyping is advantageous for high temporal resolution observation of SG traits in wheat and multi-omics facilitates the discovery of relevant genes.