Title: Application of fluorescence spectrometry combined with second-order correction algorithm in food pigment detection

Authors: Qing Yang; Yinghui Gu; Jinshuai Lu

Addresses: College of Applied Chemistry, Food and Drug, Weifang Engineer Vocational College, Qingzhou City, Shandong Province, China ' Flower College, Weifang Engineer Vocational College, Qingzhou City, Shandong Province, China ' College of Applied Chemistry and Food and Drug, Weifang Engineer Vocational College, Qingzhou City, Shandong Province, China

Abstract: Food pigment is a common food additive, but the abuse of pigment will produce serious food safety problems, which is not conducive to people's health and safety. With the development of modern science and technology, there are more and more kinds of synthetic pigments. The traditional pigment detection methods have the disadvantages of high cost, low efficiency and low accuracy. In this study, fluorescence spectrometry is proposed to detect food pigments, which can effectively classify and detect food pigments. By introducing the second-order correction algorithm to build the classification model of food pigments, we can quickly and non-destructively detect the pigments in food without any separation. Through the simulation analysis of three different drinks, it can be seen that the proposed method can quickly identify the types of pigments and judge the safety and compliance of pigment use.

Keywords: fluorescence spectrometry; second-order correction algorithm; food pigment; testing.

DOI: 10.1504/IJWMC.2023.131320

International Journal of Wireless and Mobile Computing, 2023 Vol.24 No.3/4, pp.303 - 311

Received: 05 May 2022
Received in revised form: 29 Nov 2022
Accepted: 30 Nov 2022
Published online: 06 Jun 2023 *

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