University of Tehran, Faculty of Chemistry, Department of Analytical Chemistry, Tehran 6718773654, Iran.
Food and Drug Control Laboratories and Food and Drug Laboratory Research Center, Tahran 1439956311, Iran.
J AOAC Int. 2022 Sep 6;105(5):1309-1318. doi: 10.1093/jaoacint/qsac052.
The increasing popularity of dietary supplements and, consequently, related adulteration emphasizes the rising need to examine the association of food supplements with fraud. Intentional or unintentional fraud in food supplements by hazardous chemicals compounds is a problem that many countries are struggling with. Much effort have been made to effectively and reliably control the quality of food supplements.
Due to the importance of the subject, an analytical method for the simultaneous and reliable detection and quantitative determination of three key adulterants in dietary food supplements was developed. The proposed method benefits from analytical methods and multivariate calibration methods to progress the determination of adulterants in a complex matrix.
HPLC assisted by multivariate curve resolution-alternating least square (MCR-ALS) analysis was used to detect adulterants in real samples after separation and preconcentration using novel mesoporous carbon nanoparticles. Solid-phase extraction (SPE) optimization was accomplished by central composite design (CCD). In order to obtain the best results, the MCR-ALS model was compared with the parallel factor analysis 2 (PARAFAC2) model and validated by estimation of linearity, detection limits, and recovery.
The detection limits and linear dynamics were calculated as 1.5, 4.27, and 4.77 µg/mL, and 1-50, 5-20, and 5-20 µg/mL for caffeine, ephedrine, and fluoxetine, respectively. Mean recovery for determination of caffeine, ephedrine, and fluoxetine using the developed method was reported as 101.75, 91.7, and 92.36, respectively.
The results showed that to avoid negative health outcomes associated with the excessive consumption of adulterated food supplements releasing such products should be carefully regulated. The developed method was validated using statistical factors and showed acceptable and reliable results.
(1) The application of MCR-ALS coupled with HPLC-Diode-Array Detection data sets allowed the simultaneous identification and quantification of three key adulterants (caffeine, ephedrine, and fluoxetine) in dietary food supplements. (2) A small amount of the novel adsorbent was successfully used to preconcentrate the trace amounts of adulterants in samples. (3) This method benefits from the chemometrics tools and experimental design to significantly reduce the use of toxic solvents and complicated instruments to propose a less time-consuming method for quantification of multicomponents in the presence of uncalibrated interferents.
膳食补充剂日益普及，随之而来的相关掺假问题也越发凸显，这使得对食品补充剂与欺诈之间关联的检测需求不断增加。食品补充剂中危险化学品的蓄意或非蓄意掺假是许多国家都在努力应对的问题。为了有效、可靠地控制食品补充剂的质量，各国已经付出了诸多努力。
鉴于该主题的重要性，本文开发了一种同时、可靠地检测和定量测定膳食食品补充剂中三种关键掺杂物的分析方法。该方法受益于分析方法和多元校准方法，可推进复杂基质中掺杂物的测定。
采用高效液相色谱-多变量曲线分辨交替最小二乘法（MCR-ALS）分析，在新型介孔碳纳米粒子分离和预浓缩后，对实际样品中的掺杂物进行检测。采用中心组合设计（CCD）对固相萃取（SPE）进行优化。为了获得最佳结果，将 MCR-ALS 模型与平行因子分析 2 （PARAFAC2）模型进行了比较，并通过线性、检测限和回收率的估算对其进行了验证。
检测限和线性动态范围分别计算为 1.5、4.27 和 4.77μg/mL，以及 1-50、5-20 和 5-20μg/mL，用于咖啡因、麻黄碱和氟西汀。采用所开发方法测定咖啡因、麻黄碱和氟西汀的平均回收率分别为 101.75%、91.7%和 92.36%。
结果表明，为避免与食用掺假食品补充剂相关的负面健康后果，应谨慎监管此类产品的释放。所开发的方法经过统计学因素验证，结果可靠。
（1）将 MCR-ALS 与 HPLC-二极管阵列检测数据集联用，可实现对膳食食品补充剂中三种关键掺杂物（咖啡因、麻黄碱和氟西汀）的同时识别和定量。（2）少量新型吸附剂成功用于预浓缩样品中的痕量掺杂物。（3）该方法受益于化学计量学工具和实验设计，可显著减少有毒溶剂的使用和复杂仪器的使用，提出一种在存在未校准干扰物的情况下用于多组分定量的耗时更短的方法。
