Tianjin International Joint Research & Development Center of Food Science and Engineering, Tianjin Key Laboratory of Food Biotechnology, College of Biotechnology and Food Science, Tianjin University of Commerce, Tianjin 300134, China.
Tianjin International Joint Research & Development Center of Food Science and Engineering, Tianjin Key Laboratory of Food Biotechnology, College of Biotechnology and Food Science, Tianjin University of Commerce, Tianjin 300134, China.
Fitoterapia. 2023 Apr;166:105469. doi: 10.1016/j.fitote.2023.105469. Epub 2023 Mar 11.
The authentication of traditional herbal medicines in powder form is of great significance, as they are always of high values but vulnerable to adulteration. Based on the distinct fluorescence of protein tryptophan, phenolic acids and flavonoids, front-face synchronous fluorescence spectroscopy (FFSFS) was applied for the fast and non-invasive authentication of Panax notoginseng powder (PP) adulterated with the powder of rhizoma curcumae (CP), maize flour (MF) and whole wheat flour (WF). For either single or multiple adulterants in the range of 5-40% w/w, prediction models were built based on the combination of unfolded total synchronous fluorescence spectra and partial least square (PLS) regression, and were validated by both five-fold cross-validation and external validation. The constructed PLS2 models simultaneously predicted the contents of multiple adulterants in PP and gave suitable results, with most of the determination coefficients of prediction (R) >0.9, the root mean square error of prediction (RMSEP) no >4% and residual predictive deviation (RPD) >2. The limits of detections (LODs) were 12.0, 9.1 and 7.6% for CP, MF and WF, respectively. All the relative prediction errors for simulated blind samples were between -22% and + 23%. FFSFS offers a novel alternative to the authentication of powdered herbal plants.
粉末状中药材的鉴别具有重要意义,因为其价值较高,但容易被掺假。基于蛋白质色氨酸、酚酸和类黄酮的独特荧光,本文采用前沿同步荧光光谱(FFSFS)法对三七粉(PP)中掺入姜黄粉(CP)、玉米粉(MF)和全麦粉(WF)的快速、非侵入性鉴别进行了研究。对于 5-40% w/w 范围内的单一或多种掺杂物,分别基于展开全同步荧光光谱和偏最小二乘(PLS)回归组合建立了预测模型,并通过五重交叉验证和外部验证进行了验证。所构建的 PLS2 模型同时预测了 PP 中多种掺杂物的含量,给出了合适的结果,大多数预测系数(R)>0.9,预测均方根误差(RMSEP)不超过 4%,预测能力离差(RPD)>2。CP、MF 和 WF 的检出限(LOD)分别为 12.0%、9.1%和 7.6%。模拟盲样的相对预测误差均在-22%和+23%之间。FFSFS 为粉末状植物药材的鉴别提供了一种新的选择。