Non-destructive determination of ginsenosides in ginseng by combined hyperspectral and X-ray techniques based on ensemble learning.

The potential of hyperspectral imaging and X-ray techniques for the non-destructive determination of the ginsenosides Rg1 + Re and Rb1 in ginseng was investigated. The random forest (RF) models were established using spectral information extracted from hyperspectral data to predict ginsenosides content. The RF model was optimized by data pre-processing methods and feature screening methods.

Data fusion of near-infrared and mid-infrared spectroscopy for rapid origin identification and quality evaluation of Lonicerae japonicae flos.

A data fusion strategy based on near-infrared (NIR) and mid-infrared (MIR) spectroscopy techniques were developed for rapid origin identification and quality evaluation of Lonicerae japonicae flos (LJF). A high-level data fusion for origin identification was formed using the soft voting method. This data fusion model achieved accuracy, log-loss value and Kappa value of 95.

Laser-induced breakdown spectroscopy (LIBS) for the detection of exogenous contamination of metal elements in lily bulbs.

Natural products with the underground edible part have the risk of excessive heavy metals due to the influence of the growing environment. In this study, the content of five metal elements in lily bulbs was detected by laser-induced breakdown spectroscopy (LIBS). In view of the mutual interference among elements, multivariable analysis models were established to effectively eliminate the interference.