Seasonal Variations in Sugar Accumulation Patterns of Dendrobium officinale: Integrated Analysis via Machine Learning, Physiology, and Transcriptomics.

The genus Dendrobium, the largest within the Orchidaceae family, includes Dendrobium officinale, a dual-purpose medicinal and edible functional food experiencing substantial market demand in Asia. The accumulation patterns and molecular regulatory networks of sugars in its stems and leaves are influenced by seasonal temperature and humidity variations. Understanding these patterns and mechanisms is essential for ensuring high-quality D. officinale production. Based on dynamic monitoring and machine learning models over 2 years involving 2318 data points, this study discovered seasonal variations in glucose, sucrose, fructose, mannose, galactose, and galacturonic acid in stems and leaves conformed to a polynomial regression model (R² = 0.742). The model revealed sugar content in stems primarily accumulated from October to April of the following year, with a rapid accumulation from October to February of the subsequent year. Combined with transcriptomic profiling at three critical growth stages, the differentially expressed genes related to sugar metabolism and abiotic stress in leaves and stems were mainly enriched in pathways such as plant-pathogen interaction, photosynthesis, and starch and sucrose metabolism. Additionally, 15 hub genes (e.g., RPS5, RPL23A, PSBO, etc.) were screened using weighted gene co-expression correlation network analysis, which may regulate photosynthesis-related pathways by responding to low-temperature and drought stresses, thereby facilitating normal sugar metabolism in D. officinale to adapt to environmental changes. In summary, these findings elucidate the seasonal variation models and molecular regulatory mechanisms of six sugars in D. officinale, offering scientific guidance for its harvesting and molecular breeding.