Chrysanthemum morifolium Ramat. is one of the most important medicinal and edible herbs in daily life. However, post-harvesting preservation has often been confined to the high moisture content and perishable nature of fresh chrysanthemum. Drying has been widely used to reduce microbial growth via dehydration, particularly for the long shelf life. Drying approaches also share significant impacts on the quality and flavor profiles of chrysanthemum. In this study, three drying approaches were employed to dehydrate chrysanthemum, namely hot air drying (HD), infrared combined hot air drying (IHD), and vacuum drying (VD). A systematic analysis was also conducted to explore their effects on drying behavior, color, nutritional quality, microstructure, and flavor components. Results showed that the IHD exhibited the shortest drying time (7.3 h), followed by HD (8.8 h) and VD (18.6 h). Page and Weibull models best described the drying behavior (R² > 0.997). Drying constant a in the Page model was the highest for IHD (0.5722) and the lowest for VD (0.1661), indicating the highest moisture diffusion in IHD. Furthermore, the IHD and HD yielded significantly higher L* and b* values than the VD (P < 0.05), indicating better color retention. Microstructural observation revealed that the VD best preserved cellular integrity with honeycomb-like structures, followed by IHD with moderate porosity, while HD shared severe structural shrinkage. Moreover, the IHD achieved the highest soluble sugar content (42.27 ± 2.04 mg/g), 19.34% and 88.54% higher than HD and VD, respectively. Shorter drying time was attributed to minimum Maillard consumption. Total contents of phenolic and flavonoid followed the descending order of IHD > HD > VD (P < 0.05). High-performance liquid chromatography (HPLC) analysis revealed that total content of six characteristic bioactive compounds (chlorogenic acid, luteoloside, isochlorogenic acid, apigenin, luteolin, and buddleoside) maintained the trend of IHD > HD > VD. Among them, chlorogenic acid, luteoloside, and isochlorogenic acid were highest in IHD, while luteolin and apigenin were highest in VD, due to prolonged β-glucosidase activation under longer drying duration. E-nose principal component analysis (PCA) showed that three drying groups were detected with 91.3% cumulative contribution (PC1 = 60.1%, and PC2 = 31.2%). Gas chromatography–ion mobility spectrometry (GC-IMS) identified 68 volatile compounds among all samples. Hierarchical clustering revealed that there were five characteristic regions of compound distributions. For instance, IHD exhibited the highest abundance of floral and fruity compounds, such as pentanal and β-myrcene, while VD shared the highest levels of acetoin and 2-formyl-5-methylthiophene, and HD presented high levels of terpenes, such as α-pinene. Additionally, 208 volatile compounds were also identified, where the HD, IHD, and VD contained 172, 183, and 179 compounds, respectively. The volatile profile was then composed of 105 common compounds. Total volatile concentration was highest in IHD (421.11 mg/kg), thus exceeding HD (355.88 mg/kg) and VD (397.24 mg/kg). Terpenes (87 compounds) and alcohols (49 compounds) dominated all samples. Partial Least Squares Discriminant Analysis (PLS-DA) identified 20 key differential volatile markers (VIP > 1), including terpenes and alcohols, including 3,4,4-trimethyl-2-cyclohexen-1-one, α-farnesene, β-myrcene, and β-vetivenene. Most VIP markers were common compounds, indicating that drying approaches modulated abundance rather than generating unique compounds. In characteristic flavor profiles, HD was featured by herbal, cooling, and woody notes (high eucalyptol and camphene); IHD exhibited roasted, spicy, and caramel-like aromas (elevated furans, esters, and phenolics) from Maillard reactions; VD delivered fruity, sweet, and floral notes (high terpenes) closest to fresh chrysanthemum. Alcohols were often correlated with floral/fruity notes, while terpenes contributed herbal/green characteristics, which were consistent with E-nose observations. In conclusion, the optimal IHD can offer superior drying efficiency, better retention of nutritional components and most bioactive compounds, and the highest total volatile concentration with desirable roasted and spicy notes. Synergistic infrared and hot air heating can accelerate drying behavior to promote compound release. These findings can also provide a scientific basis to optimize industrial chrysanthemum drying for the quality attributes of high-value products. Therefore, the infrared and vacuum drying can be promising for the constant temperature during drying.

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.