Multi-regional HPLC fingerprinting of Nelumbinis stamen flavonoids in China and machine learning-guided analysis of geographical environment factors

Nelumbinis stamen (NS), the dried stamen of the aquatic vegetable lotus, is consumed as a popular herbal tea rich in bioactive flavonoids. Given limited research on NS flavonoid determination, a validated HPLC method was established for the simultaneous quantification of ten major flavonoids: rutin, hyperoside, isoquercitrin, trifolin, narcissin, astragalin, isorhamnetin-3- O -glucoside, kaempferol, quercetin, and isorhamnetin. The flavonoids in NS from 18 geographic origins across China were analyzed. HPLC fingerprints comprising 18 common peaks were established for similarity assessment and clustering, which classified the samples into two distinct clusters. The classification was primarily driven by trifolin, isorhamnetin-3- O -glucoside, astragalin, narcissin, and isoquercitrin. Machine learning (Random Forest / XGBoost) identified the seasonal contrast index, e.g. the discrepancy between summer and annual precipitation / temperature, as the key environmental driver. Correlation analysis confirmed that high June precipitation negatively impacts flavonoid accumulation. The HPLC method enables robust chemical characterization of NS, while the environmental insights provide actionable guidance for its cultivation. • An HPLC method was established for quantifying ten flavonoids in Nelumbinis stamen. • Flavonoid profiling was performed on 18 NS samples from multiple regions in China. • HPLC fingerprints plus chemometrics classified NS samples into two clusters. • Machine learning identified key environmental drivers of geographical variation. • Seasonal contrast index and June precipitation may affect the flavonoid content.