Research on Enhanced Detection of Benzoic Acid Additives in Liquid Food Based on Terahertz Metamaterial Devices

Abstract

It is very important for human health to supervise the use of food additives, because excessive use of food additives will cause harm to the human body, especially lead to organ failures and even cancers. Therefore, it is important to realize high-sensibility detection of benzoic acid, a widely used food additive. Based on the theory of electromagnetism, this research attempts to design a terahertz-enhanced metamaterial resonator, using a metamaterial resonator to achieve enhanced detection of benzoic acid additives by using terahertz technology. The absorption peak of the metamaterial resonator is designed to be 1.95 THz, and the effectiveness of the metamaterial resonator is verified. Firstly, the original THz spectra of benzoic acid aqueous solution samples based on metamaterial are collected. Secondly, smoothing, multivariate scattering correction (MSC), and smoothing combined with first derivative (SG + 1 D) methods are used to preprocess the spectra to study the better spectral pretreatment methods. Then, Uninformative Variable Elimination (UVE) and Competitive Adaptive Reweighted Sampling (CARS) are used to explore the optimal terahertz band selection method. Finally, Partial Least Squares (PLS) and Least square support vector machine (LS-SVM) models are established, respectively, to realize the enhanced detection of benzoic acid additives. The LS-SVM model combined with CARS has the best effect, with the correlation coefficient of prediction set (Rp) is 0.9953, the root mean square error of prediction set (RMSEP) is 7.3 × 10−6, and the limit of detection (LOD) is 2.3610 × 10−5 g/mL. The research results lay a foundation for THz spectral analysis of benzoic acid additives, so that THz technology-based detection of benzoic acid additives in food can reach requirements stipulated in the national standard. This research is of great significance for promoting the detection and analysis of trace additives in food, whose results can also serve as a reference to the detection of antibiotic residues, banned additives, and other trace substances.

Detection of Benzoic Acid Additive Based on a Terahertz Metasurface Sensor

“…The equivalent circuit model is shown in Figure 4. The finite integration method [14] was used to analyze the transmission performance of the proposed metasurface sensor. First, the optimal parameters were selected according to Figure 3, with of 7 µm and (L) of 108 µm, and it was found that the resonant peak frequencies were all around 0.93 THz.…”

Study on qualitative identification of aflatoxin solution based on terahertz metamaterial enhancement

“…The region with the largest electric field intensity is called terahertz hot spot. 27 In the research related to terahertz, it tends to produce larger signal enhancement. The analysis of the simulation results can provide a theoretical basis for the selection of the optimal excitation frequency.…”

“…In 2022, Zhu et al 24 proposed a metamaterial sensor composed of a graphene four-open square ring and a golden hemisphere, and combined with THz-TDS technology to identify four amino acids of proline, glycine, arginine and methionine, and the recognition accuracy reached 100%. In 2022, Hu et al 25 designed a terahertz enhanced metamaterial absorber based on the electromagnetic theory and applied it to the effective detection of benzoic acid samples. The detection limit of benzoic acid was 2.36 × 10 −5 g ml −1 , which promoted the rapid detection of benzoic acid additives in food and was of great significance for promoting the detection and analysis of trace additives in food.…”

Design and application of skin disease biosensor based on terahertz metasurface

“…If the dielectric parameter of the analytes on the surface varies, it can be sensed by the spectrum. Examples include cell growth process monitoring, drug trace detection, cancer marker identification, and auxiliary diagnosis of cancerous tissue [15][16][17][18] . Low sensing performance due to structure and procedure is the major challenge with MS sensors.…”