Efficient measurement of photosynthetic traits, such as the maximum carboxylation rate of Rubisco (Vcmax) and electron transport rate (Jmax), is essential for advancing research and breeding aimed at enhancing crop productivity. Traditional methods are time-intensive, which limits their scalability. Remote sensing presents an opportunity for estimating these traits; however, it often lacks an affordable platform for effective spatial mapping, a critical aspect of phenotyping. This study explored the use of unmanned aerial vehicle (UAV) multispectral data to estimate and spatially map photosynthetic traits in tea chrysanthemums during the branching and budding stages under an open canopy. Over six field experiments across varieties conducted in 2022–2023, we captured canopy reflectance using UAV-mounted multispectral sensors, calculated spectral indices, and measured the photosynthetic traits of the upper leaves using a portable photosynthesis system. The results indicated that certain indices, particularly those incorporating green and red-edge bands, effectively estimated photosynthetic traits, with the simplified canopy chlorophyll content index (SCCCI) yielding the most accurate Vcmax estimates (R² ​= ​0.52) and the chlorophyll vegetation index (CVI) providing the best estimates for Jmax (R² ​= ​0.38). The integration of variable selection with partial least squares regression (PLSR) modeling further enhanced the precision of the model (Vcmax: R² ​= ​0.70; Jmax: R² ​= ​0.63). Our findings demonstrate that UAV-acquired multispectral data can effectively map photosynthetic traits with high spatial resolution, establishing it as a valuable tool for rapid phenotyping and spatial assessment of photosynthetic capacity in crop fields.

Waterlogging is a major stress that impacts the chrysanthemum industry. Large-scale germplasm screening for identifying waterlogging-tolerant resources in a quick and accurate manner is essential for developing new cultivars with improved waterlogging tolerance. To overcome this phenotyping bottleneck, consumer-grade digital cameras have been used to acquire the red-green-blue (RGB) images of 180 chrysanthemum cultivars and their wild relatives under waterlogging stress and well-watered conditions. A total of 103 image-based digital traits (i-traits), including 10 morphological i-traits and 93 texture i-traits, were extracted and systematically analyzed. Most of these i-traits presented high coefficients of variation (CVs) and broad-sense heritability (H²), with an average CV of 34.04 ​% and an average H² of 0.93. We identified several novel texture i-traits associated with the hue (H) component, which strongly correlated with the traditional waterlogging tolerance index, the membership function value of waterlogging (MFVW) (R ​= ​0.63–0.77). We further employed the random forest (RF) and gradient boosting tree (GBT) machine learning algorithms to predict aboveground biomass and MFVW on the basis of different i-trait datasets. The RF model achieved superior predictive performance, with a coefficient of determination (R²) of up to 0.88 for shoot weight and 0.86 for MFVW. Moreover, a subset of the top 13 most important i-traits could accurately predict MFVW (R² ​> ​0.80) via the cross-validation method. A total of 10 highly tolerant resources were selected by traditional and RGB-based evaluation, and 50 ​% belonged to Artemisia. Our findings confirmed that RGB-based technology provides a promising novel approach for quantifying waterlogging response that contributes to future breeding programs and genetic dissection for waterlogging tolerance.

Color fading caused by a decrease in anthocyanin accumulation during the post-flowering stage significantly affects postharvest quality of chrysanthemum. However, the underlying mechanism by which anthocyanin accumulation decreases during the post-flowering stage still unclear, which greatly restricts design of molecular breeding in chrysanthemum. Here, a chrysanthemum SG7 R2R3 MYB transcription factor (TF), CmMYB3-like, was identified to have a function in regulating anthocyanin biosynthesis during the post-flowering stage. Quantitative real time PCR (qRT-PCR) assays showed that the expression of CmMYB3-like was gradually downregulated when anthocyanin content increased during the flowering stage and was significantly upregulated during the post-flowering stage. Genetic transformation of chrysanthemum and dual-luciferase assays in N. benthamiana leaves showed that CmMYB3-like suppressed anthocyanin accumulation by inhibiting the transcription of CmCHS and CmANS directly and that of CmF3H indirectly. However, overexpression or suppression of CmMYB3-like did not affect the biosynthesis of flavones or flavonols. Genetic transformation of chrysanthemum revealed that the overexpression of CmMYB3-like inhibited anthocyanin accumulation, but its suppression prevented the decrease in anthocyanin accumulation during the post-flowering stage. Our results revealed a crucial role of CmMYB3-like in regulating the color of petals during the post-flowering stage and provided a target gene for molecular design breeding to improve the postharvest quality of chrysanthemum.