Revealing the effects of withering methods and withering time on the active components of mulberry leaf tea using HS-SPME/GC-MS.

In this study, color difference analysis, headspace solid-phase microextraction coupled with gas chromatography-mass spectrometry and high-performance liquid chromatography with diode array detection were employed to systematically evaluate the effects of three withering methods-natural withering, sunlight withering (SW), and warm-air withering (WW)-as well as different withering durations (1-4 h), on the active components and appearance quality of mulberry leaf tea. The results demonstrated that, compared with other withering treatments, WW induced more pronounced changes in color, resulted in a higher tea polyphenols content, and more effectively preserved non-volatile compounds. In contrast, SW was associated with a higher total flavonoid content.

Rapid discriminant analysis for the origin of specialty yam based on multispectral data fusion strategies.

In order to achieve rapid and effective identification of Hebei yam, a qualitative discrimination model was constructed based on near infrared (NIR), mid infrared (MIR), and microscopic Raman spectra in combination with individual spectra and multispectral data fusion strategies. The results showed that the gray wolf optimizer-support vector machine (GWO-SVM) model constructed by mid-level fusion using the three feature spectra performed the best in distinguishing the geographic origin of the yam, with a prediction accuracy of 100.00% in both the training set and the test set, and an F1 score of 1.