Rapid and Sensitive Detection of Multi-Class Food Additives in Beverages for Quality Control by Using HPLC-DAD and Chemometrics Methods
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A rapid and sensitive analytical strategy combining high-performance liquid chromatography-diode array detection (HPLC-DAD) and chemometrics methods was developed for the determination of multi-class food additives in a variety of beverage samples. Different kinds of beverages, which contain diverse unknown interferences, can be directly injected into a chromatographic system after a simple dilution or pretreatment step, and the data were recorded in a short time under a simple gradient elution mode. Although peaks overlapped and changeable interferences existed in the dimension of the chromatographic and spectral in real beverages, all food additives were accurately resolved by using a second-order calibration method based on alternating trilinear decomposition (ATLD) algorithm, and accurate chromatographic profiles, spectral profiles, and concentration profiles were also obtained. Limits of detection for all additives were between 1.40 and 165.1 ng mL−1, while limits of quantitation ranged from 4.20 to 500.2 ng mL−1. The spiked recoveries were in the range of 87.3–103% (except amaranth) with RSDs less than 10.2%. Compared with the results obtained by classic HPLC method, our proposed method was more accurate. In all, the proposed method is fast, sensitive, and universal and could be used as a reliable tool to determine food additives and quality monitoring in different complex beverages.
KeywordsAlternating trilinear decomposition Beverages Food additives High-performance liquid chromatography-diode array detection Second-order calibration
China Food and Drug Administration
Alternating trilinear decomposition
Limit of detection
Limit of quantitation
This work was supported by the National Nature Science Foundation of China (Grant No. 21575039 and No. 21775039) and the Foundation for Innovative Research Groups of NSFC (Grant No. 21521063).
Compliance with Ethical Standards
Conflicts of Interest
Xiaodong Sun declares that he has no conflict of interest. Hailong Wu declares that he has no conflict of interest. Zhi Liu declares that he has no conflict of interest. Yue Chen declares that she has no conflict of interest. Qian Liu declares that she has no conflict of interest. Yujie Ding declares that she has no conflict of interest. Ruqin Yu declares that he has no conflict of interest.
This article does not contain any studies with animals performed by any of the authors.
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