Rapid determination of total flavonoid content, xanthine oxidase inhibitory activities, and antioxidant activity in Prunus mume by near-infrared spectroscopy

Evaluating the quality of herbal medicine based on the content and activity of its main components is highly beneficial. Developing an eco-friendly determination method has significant application potential. In this study, we propose a new method to simultaneously predict the total flavonoid content (TFC), xanthine oxidase inhibitory (XO) activity, and antioxidant activity (AA) of Prunus mume using near-infrared spectroscopy (NIR). Using the sodium nitrite-aluminum nitrate-sodium hydroxide colorimetric method, uric acid colorimetric method, and 2,2-diphenyl-1-picrylhydrazyl radical (DPPH) free radical scavenging activity as reference methods, we analyzed TFC, XO, and AA in 90 P. mume samples collected from different locations in China. The solid samples were subjected to NIR. By employing spectral preprocessing and optimizing spectral bands, we established a rapid prediction model for TFC, XO, and AA using partial least squares regression (PLS). To improve the model's performance and eliminate irrelevant variables, competitive adaptive reweighted sampling (CARS) was used to calculate the pretreated full spectrum. Evaluation model indicators included the root mean square error of cross-validation (RMSECV) and determination coefficient (R2) R 2 ) values. The TFC, XO, and AA model, combining optimal spectral preprocessing and spectral bands, had RMSECV values of 0.139, 0.117, and 0.121, with R CV 2 values exceeding 0.92. The root mean square error of prediction (RMSEP) for the TFC, XO, and AA model on the prediction set was 0.301, 0.213, and 0.149, with determination coefficient (RP2) R P 2 ) values of 0.915, 0.933, and 0.926. The results showed a strong correlation between NIR with TFC, XO, and AA in P. mume. . Therefore, the established model was effective, suitable for the rapid quantification of TFC, XO, and AA. The prediction method is simple and rapid, and can be extended to the study of medicinal plant content and activity.