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.

White rust caused by Puccinia horiana is a destructive disease of chrysanthemum plants. To better understand the resistance mechanisms of composite species to this disease, the leaf cuticular traits, antioxidant and defensive enzymes activities of immune (Chrysanthemum makinoi var. wakasaense) and highly susceptible (Ajania shiwogiku var. kinokuniense) species were compared. Trichome density of two species was markedly different, negatively associated with plant resistance to P. horiana. Total wax load in C. makinoi var. wakasaense was two times more than that in A. shiwogiku var. kinokuniense. The wax composition in immune one was abundant in esters and primary alcohols. Superoxide dismutase (SOD, EC 1.15.1.1), peroxidase (POD, EC 1.11.1.7), polyphenoloxidase (PPO, EC 1.14.18.1 or EC 1.10.3.2) and phenylalanine ammonia lyase (PAL, EC 4.3.1.5) activities were investigated. In C. makinoi var. wakasaense, the activity of SOD and POD increased rapidly after inoculation, which might be non-host induced reactive oxygen species (ROS) activated antioxidant enzymes, however SOD and POD remained a low and steady level in the highly susceptible one after inoculation. Quick increase in PPO activities after inoculation was observed in both species, however it remained higher in C. makinoi var. wakasaense at the late period of inoculation. PAL in C. makinoi var. wakasaense was induced after pathogen inoculation, but not in A. shiwogiku var. kinokuniense, suggesting that these two enzymes might contribute to the resistance to P. horiana.