The selection and promotion of high-yielding and nitrogen-efficient wheat varieties can reduce nitrogen fertilizer application while ensuring wheat yield and quality and contribute to the sustainable development of agriculture; thus, the mining and localization of nitrogen use efficiency (NUE) genes is particularly important, but the localization of NUE genes requires a large amount of phenotypic data support. In view of this, we propose the use of low-altitude aerial photography to acquire field images at a large scale, generate 3-dimensional (3D) point clouds and multispectral images of wheat plots, propose a wheat 3D plot segmentation dataset, quantify the plot canopy height via combination with PointNet++, and generate 4 nitrogen utilization-related vegetation indices via index calculations. Six height-related and 24 vegetation-index-related dynamic digital phenotypes were extracted from the digital phenotypes collected at different time points and fitted to generate dynamic curves. We applied height-derived dynamic numerical phenotypes to genome-wide association studies of 160 wheat cultivars (660,000 single-nucleotide polymorphisms) and found that we were able to locate reliable loci associated with height and NUE, some of which were consistent with published studies. Finally, dynamic phenotypes derived from plant indices can also be applied to genome-wide association studies and ultimately locate NUE- and growth-related loci. In conclusion, we believe that our work demonstrates valuable advances in 3D digital dynamic phenotyping for locating genes for NUE in wheat and provides breeders with accurate phenotypic data for the selection and breeding of nitrogen-efficient wheat varieties.

Frequent drought events severely restrict global crop productivity, especially those occurring in the reproductive stages. Moderate drought priming during the earlier growth stages is a promising strategy for allowing plants to resist recurrent severe drought stress. However, the underlying mechanisms remain unclear. Here, we subjected wheat plants to drought priming during the vegetative growth stage and to severe drought stress at 10 days after anthesis. We then collected leaf samples at the ends of the drought priming and recovery periods, and at the end of drought stress for transcriptome sequencing in combination with phenotypic and physiological analyses. The drought-primed wheat plants maintained a lower plant temperature, with higher stomatal openness and photosynthesis, thereby resulting in much lower 1,000-grain weight and grain yield losses under the later drought stress than the non-primed plants. Interestingly, 416 genes, including 27 transcription factors (e.g., MYB, NAC, HSF), seemed to be closely related to the improved drought tolerance as indicated by the dynamic transcriptome analysis. Moreover, the candidate genes showed six temporal expression patterns and were significantly enriched in several stress response related pathways, such as plant hormone signal transduction, starch and sucrose metabolism, arginine and proline metabolism, inositol phosphate metabolism, and wax synthesis. These findings provide new insights into the physiological and molecular mechanisms of the long-term effects of early drought priming that can effectively improve drought tolerance in wheat, and may provide potential approaches for addressing the challenges of increasing abiotic stresses and securing food safety under global warming scenarios.