Multi-element and metabolite characterization of commercial Phyllanthi Fructus with geographical authentication and quality evaluation purposes

指纹(计算) 代谢组学 计算机科学 色谱法 化学 人工智能
作者
Qin Guan,Tingting Pu,Zhongyu Zhou,Min Fan,Conglong Xia,Yinglin Liu,Ping Zhou,Wei Yang,Baozhong Duan
出处
期刊:Food Control [Elsevier BV]
卷期号:151: 109787-109787 被引量:1
标识
DOI:10.1016/j.foodcont.2023.109787
摘要

Identifying the geographical origin of plant products is critical for assessing their quality. Phyllanthi Fructus (PF) is considered one of the most specific foods with nutritional and medicinal value, but, to the best of our knowledge, scientific insights concerning its quality evaluation, elemental profile, and authentication of its geographical provenance are still lacking. In the present research, HPLC and ICP-MS were applied together to establish fingerprint profiles of PF samples. Then, an appropriate quantitative method was chosen to assess their qualities, and chemometric methods were used to excavate their intrinsic characteristics. The results showed that the concentrations and proportions of phenolic compounds observed in the samples varied significantly, and ultrasonic extraction is the preferred pretreatment method for evaluating the quality of PF. Besides, elemental composition analysis revealed that PF is a selenium-rich, high-potassium, and low-sodium food. Sn, Cd, Mg, and K (VIP >1.5) are the best potential markers for differentiating the PF from different producing areas. In the multivariate analysis, OPLS-DA was efficient and was used to discriminate the geographical origin of PF. Moreover, the origin of unknown samples was successfully predicted with 100% accuracy based on the OPLS-DA model. Overall, this study provides a novel and reliable strategy for the quality assessment of PF, and ICP-MS data was most useful in determining regionality.
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