Panax notoginseng, a traditional medicinal and edible plant, is widely used in medicine, health care, cosmetics and other industries. Affected by the discrepancy between market supply and demand and price, the adulteration of P. notoginseng products with other plant-derived ingredients occurs at times. With the continuous development of technologies such as spectroscopy, chromatography, and DNA barcoding, the detection techniques for rapid and sensitive determination of the authenticity identification and origin of P. notoginseng have become more diversified to meet the needs of different regulatory goals and could effectively control practices that mislead consumers and promote false labeling. This review analyzes and summarizes the existing technologies for determining the authenticity and origin of P. notoginseng from these three aspects: morphological, chemical and molecular biology methods from the literature since 2001; on this basis, the current problems and future research directions are discussed to provide a reference for the establishment of rapid and accurate methods to verify authenticity and origin to promote the further development and improvement of quality control technology systems for P. notoginseng.

As sensor parameters and atmospheric conditions create uncertainties for at−sensor radiation detection, radiometric consistency among satellite images is difficult to achieve. Relative radiometric normalization is a method that can improve multi−image consistency with accurate pseudo−invariant features (PIFs), especially over large areas or long time series satellite images. Although there are algorithms that manually or automatically select PIFs, the spatial mismatch of satellite images can affect PIF extraction, particularly with artificial pixels. To alleviate this problem, we proposed to use Landsat−8 OLI as the reference image and Sentinel−2A as the subject image, to apply pseudo−invariant features−based algorithms with polygon features through the single−band and multiple−band regression. Compared to pseudo−invariant point features, hyperspectral library, and histogram matching approaches, the results demonstrate the superiority of the proposed algorithms with correlation coefficients of 0.9948 and 0.9945, and an RMSE of 0.0097 and 0.0095 with multiple− and single−band regression, respectively. We also found more accurate linear fitting and better shape matching through band scattering and reflectance frequency analysis. The proposed algorithms are a significant improvement in radiometric normalization, within artificial pixels, achieving spectral signature consistency.

Dencichine is a nonprotein amino acid, an effective ingredient in Panax notoginseng with hemostatic and anti-inflammatory effects. There are few studies on the effects of regions and cultivation models on the accumulation of dencichine. In the current study, the content of dencichine in P. notoginseng collected from its global cultivation and trading center Yunnan, China, (>640 samples) was determined using an optimized high-performance liquid chromatography method coupled with a diode array detector but without derivatization. The recovery rate of this method was 80–110%, the relative standard deviation was <10%, and the limits of detection and quantification were 0.003% (w/w) and 0.01% (w/w), respectively. The content of dencichine in each part of P. notoginseng was as follows: rootlets (39.59%) > main roots (29.91%) > leaves (16.21%) > stems (14.29%). For leaves, P. notoginseng in the forest (5.52 ± 2.26 mg/g) was significantly higher than that in the field (3.93 ± 1.72 mg/g) but opposite for main roots. The origins and altitudes made different contributions to the accumulation of dencichine in P. notoginseng. This study provides an effective analytical method to determine dencichines in various parts of P. notoginseng from different origins and altitudes and supports quality control and product development of P. notoginseng.