Feasibility of using terahertz spectroscopy to detect seven different pesticides in wheat flour

Predicting wheat gluten concentrations in potato starch using GPR and SVM models built by terahertz time-domain spectroscopy

The purpose of this study was for the first time to explore the feasibility of terahertz (THz) spectral imaging for the detection of gluten contents in food samples. Based on the obtained 80 THz spectrum data, Gaussian process regression (GPR) and support vector machine (SVM) models were established to predict wheat gluten concentrations in 40 potato starch mixture samples. The prediction performances of GPR and SVM obtained were R2 = 0.859 and RMSE = 0.070, and R2 = 0.715 and RMSE = 0.101 in the gluten concentration range of 1.3%-100%, respectively, showing that the linear SVM algorithm had better prediction performance. The results indicated that THz spectral imaging combined with GPR could be used to predict the gluten content in food samples. It is thus hoped that this research should provide a novel technique for gluten content detection to ensure gluten-free food samples.

Multiband terahertz metamaterial perfect absorber for microorganisms detection

We report a multi-resonant terahertz (THz) metamaterial perfect absorber (MPA)-based biosensor in the working frequency range of [Formula: see text] for sensing of microorganisms (such as fungi, yeast) and wheat pesticides. Nearly [Formula: see text] absorption is realized at [Formula: see text] and [Formula: see text]. We designed our THz MPA sensor making resonators' gap area compatible with the microorganisms' size. To obtain optimum performance of the MPA, a mapping of amplitudes and shifts in the absorption resonance peaks with different structural parameters of the resonators is carried out. A very high-frequency shift is obtained for microorganisms such as Penicillium chrysogenum (fungi), yeast, and pesticides (Imidacloprid, N, N-Diethyldithiocarbamate sodium salt trihydrate, Daminozide, N, N-Diethyldithiocarbamate sodium salt hydrate, and Dicofol). An equivalent circuit model using Advance Design System (ADS) software is developed. The calculated results through the model show similar trends as obtained in the simulations using CST. Investigations of the effect of incidence angle of THz wave on the absorption spectra of the MPA are also carried out. It is found that incidence angle does not impact the stability of the lower resonance absorption peak (1.79THz). Due to the wide working frequency range, the proposed sensor is extremely suitable for the detection of all range of pesticides because their specific absorption fingerprint lies in the frequency range of 0-3.8THz. We believe that our sensor could be a potential detection tool for detecting pesticide residues in agriculture and food products. The THz MPA-based biosensor is capable of detecting a very small change in the effective dielectric constant of the MPA environment. Therefore, it can also offer huge opportunities in label-free biosensing for future biomedical applications.

Wavelength selection of terahertz time-domain spectroscopy based on a partial least squares model for quantitative analysis

Terahertz spectroscopy, combined with chemometric methods, has proved to be an effective tool in the quantitative analysis of many substances. However, current research has mainly focused on comparing different algorithms under the full spectrum. In fact, the full spectrum is not only composed of characteristic features of the samples, but also many types of noises. Hence, the accuracy of the quantitative analysis may be unsatisfactory if the full spectrum is selected. In this paper, a wavelength selection method based on partial least squares and absorption peak was proposed and an efficient frequency band was determined in the quantitative analysis of three types of pesticides, i.e., 6-benzylaminopurine, 2, 6-dichlorobenzonitrile, and imidacloprid. By introducing two parameters, the sum of peak intervals (Si) and peak width, the most efficient peak was selected from multiple peaks and the specific peak width was given with the aid of particle swarm optimization. We concluded that the most efficient absorption peak for quantitative analysis corresponding to the largest Si and full width near one-half maximum could characterize full spectrum information precisely. Comparing before and after wavelength selection, the correlation coefficient (R) of the three pesticides have increased from 0.9671, 0.9705, 0.9884 to 0.9921, 0.9934, and 0.9957. In conclusion, the proposed wavelength selection method was demonstrated to be very efficient for the quantitative analysis of the pesticide mixtures, which also could be helpful in the analysis of other multicomponent mixtures with absorption peaks.

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

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 (R_p) 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.

Trace Identification and Visualization of Multiple Benzimidazole Pesticide Residues on Toona sinensis Leaves Using Terahertz Imaging Combined with Deep Learning

Molecular spectroscopy has been widely used to identify pesticides. The main limitation of this approach is the difficulty of identifying pesticides with similar molecular structures. When these pesticide residues are in trace and mixed states in plants, it poses great challenges for practical identification. This study proposed a state-of-the-art method for the rapid identification of trace (10 mg·L⁻¹) and multiple similar benzimidazole pesticide residues on the surface of Toona sinensis leaves, mainly including benzoyl (BNL), carbendazim (BCM), thiabendazole (TBZ), and their mixtures. The new method combines high-throughput terahertz (THz) imaging technology with a deep learning framework. To further improve the model reliability beyond the THz fingerprint peaks (BNL: 0.70, 1.07, 2.20 THz; BCM: 1.16, 1.35, 2.32 THz; TBZ: 0.92, 1.24, 1.66, 1.95, 2.58 THz), we extracted the absorption spectra in frequencies of 0.2–2.2 THz from images as the input to the deep convolution neural network (DCNN). Compared with fuzzy Sammon clustering and four back-propagation neural network (BPNN) models (TrainCGB, TrainCGF, TrainCGP, and TrainRP), DCNN achieved the highest prediction accuracies of 100%, 94.51%, 96.26%, 94.64%, 98.81%, 94.90%, 96.17%, and 96.99% for the control check group, BNL, BCM, TBZ, BNL + BCM, BNL + TBZ, BCM + TBZ, and BNL + BCM + TBZ, respectively. Taking advantage of THz imaging and DCNN, the image visualization of pesticide distribution and residue types on leaves was realized simultaneously. The results demonstrated that THz imaging and deep learning can be potentially adopted for rapid-sensing detection of trace multi-residues on leaf surfaces, which is of great significance for agriculture and food safety.

Terahertz fingerprint characterization of 2,4-dichlorophenoxyacetic acid and its enhanced detection in food matrices combined with spectral baseline correction

Rapid and accurate detection of pesticide residues in food matrices are of great significance to food safety. This study aimed to characterize the fingerprint peaks of 2,4-dichlorophenoxyacetic acid (2,4-D) and to enhance its detection accuracy in food matrices by using terahertz (THz) time-domain spectroscopy. Density functional theory was used to simulate molecular dynamics of 2,4-D peaks (1.35, 1.60, 2.37 and 3.00 THz). Four baseline correction methods, including asymmetric least squares smoothing (AsLS), adaptive iteratively reweighted penalized least squares (AirPLS), background correction (Backcor), baseline estimation and denoising with sparsity (BEADS) were compared and used to eliminate spectral baselines of Zizania latifolia (ZIZLA), rice and maize containing 2,4-D residues, from 0.1 to 4 THz. Based on the peak information of 1.35 THz, the detection limit and accuracy of 2,4-D residues in these food matrices were significantly improved after THz spectral baseline correction, providing a new feasibility for food safety and agricultural applications.

Rapid analysis of a doxycycline hydrochloride solution by metallic mesh device-based reflection terahertz spectroscopy

Terahertz (THz) spectroscopy has the advantages of non-ionization and spectroscopic fingerprint, which can be used for biological and chemical compound analysis. However, because of the strong absorption of water in the THz region, it is still a challenge for THz waves to realize aqueous solution detection. In this study, taking a doxycycline hydrochloride (DCH) aqueous solution as the target, we proposed a THz metallic mesh device (MMD) based reflection platform for the first time for sensing. The angle characteristics of the THz MMD was investigated through numerical simulations and experimental measurements to get an optimized configuration for the platform. When the projection of THz electric field polarization onto the MMD plane gets parallel to latitudinal direction of the MMD apertures, a strong resonant surface mode can be achieved, and our proposed platform can be successfully used to detect the DCH solution with a concentration as low as 1 mg L^-1. The sensing mechanism of our platform was also explored by analyzing the influences of the immersion depth into the MMD holes and the extinction coefficient of droplets on the reflection spectra. Our work presents a rapid, low-cost, and practical platform for antibiotic solution sensing using THz radiation, which opens new avenues for the microanalysis of chemicals or biomolecules in strongly absorptive solutions in the THz region.

Studies on qualitative and quantitative detection of trehalose purity by terahertz spectroscopy

Terahertz spectroscopy was used to qualitatively and quantitatively analyze four samples (three brands) of trehalose produced in China and other countries. The results show that the main characteristic peak was greatly affected by concentration, and the optimal detection concentration of trehalose was determined to be 25%-55% by transmission scanning. There were six significant characteristic absorption peaks in the trehalose spectrum, meaning that terahertz spectroscopy can be used for qualitative analysis, analogous to infrared spectroscopy. Moreover, the terahertz spectrum can effectively distinguish the three isomers of trehalose, whereas infrared spectroscopy cannot. Thus, it was found that the current commercially available trehalose is the α,α-isomer. Quantitative analysis of the three brands of trehalose using terahertz spectroscopy matched the purity trends found by high-performance liquid chromatography analysis, with the order of purity from highest to lowest being TREHA, Pioneer, and Huiyang. The actual quantitative values did differ between the two detection methods, but the variation in the values from the same sample obtained by the two detection methods was less than 5%, confirming that terahertz spectroscopy is very suitable for the rapid and relative quantitative detection of trehalose.

Temperature-dependent terahertz vibrational spectra of tetracycline and its degradation products

Terahertz (THz) spectroscopy has emerged as an attractive technique for qualitative and quantitative detection. Analysis of these chemicals in the THz range under various temperatures can yield detailed information on molecular vibrational modes, which is of utmost importance for effective detection. Here we report the use of THz time-domain spectroscopy (THz-TDS) to measure tetracyclines hydrochloride (TCH) and its degradation products including epitetracycline hydrochloride (ETCH), anhydrotetracycline hydrochloride (ATCH), and epianhydrotetracycline hydrochloride (EATCH) over the temperature range of 4.5-300 K for the first time. The results showed that these four tetracyclines exhibited numerous distinct spectral features in frequency-dependent absorption spectra, which demonstrated the qualitative capacity of THz-TDS. Through density functional theory (DFT) calculations and analysis of temperature-dependent absorption spectra, the origin of the observed terahertz absorption peaks of these four tetracyclines were well interpreted. This study could lay the foundation for high-performance analysis of biological and chemical molecules by THz spectroscopy, which is essential for sensing application.

Spectral Characterization and Molecular Dynamics Simulation of Pesticides Based on Terahertz Time-Domain Spectra Analyses and Density Functional Theory (DFT) Calculations

This work provides the experimental and theoretical fundamentals for detecting the molecular fingerprints of six kinds of pesticides by using terahertz (THz) time-domain spectroscopy (THz-TDS). The spectra of absorption coefficient and refractive index of the pesticides, chlorpyrifos, fipronil, carbofuran, dimethoate, methomyl, and thidiazuron are obtained in frequencies of 0.1–3.5 THz. To accurately describe the THz spectral characteristics of pesticides, the wavelet threshold de-noising (WTD) method with db 5 wavelet fucntion, 5-layer decomposition, and soft-threshold de-noising was used to eliminate the spectral noise. The spectral baseline correction (SBC) method based on asymmetric least squares smoothing was used to remove the baseline drift. Spectral results show that chlorpyrifo had three characteristic absorption peaks at 1.47, 1.93, and 2.73 THz. Fipronil showed three peaks at 0.76, 1.23, and 2.31 THz. Carbofuran showed two peaks at 2.72 and 3.06 THz. Dimethoate showed three peaks at 1.05, 1.89, and 2.92 THz. Methomyl showed five peaks at 1.01, 1.65, 1.91, 2.72, and 3.20 THz. Thidiazuron showed four peaks at 0.99, 1.57, 2.17, and 2.66 THz. The density functional theory (DFT) of B3LYP/6-31G+(d,p) was applied to simulate the molecular dynamics for peak analyzing of the pesticides based on isolated molecules. The theoretical spectra are in good agreement with the experimental spectra processed by WTD + SBC, which implies the validity of WTD + SBC spectral processing methods and the accuracy of DFT spectral peak analysis. These results support that the combination of THz-TDS and DFT is an effective tool for pesticide fingerprint analysis and the molecular dynamics simulations.

Mechanisms and applications of terahertz metamaterial sensing: a review

Terahertz (THz) technology has attracted great worldwide interest and novel high-intensity THz sources and plasmonics are two of the most active fields of recent research. Being situated between infrared light and microwave radiation, the absorption of THz rays in molecular and biomolecular systems is dominated by the excitation of intramolecular and intermolecular vibrations. This indicates that THz technology is an effective tool for sensing applications. However, the low sensitivity of free-space THz detection limits the sensing applications, which gives a great opportunity to metamaterials. Metamaterials are periodic artificial electromagnetic media structured with a size scale smaller than the wavelength of external stimuli. They present localized electric field enhancement and large values of quality factor (Q factor) and show high sensitivity to minor environment changes. In the present work, the mechanism of THz metamaterial sensing and dry sample and microfluidic sensing applications based on metamaterials are introduced. Moreover, new directions of THz metamaterial sensing advancement and introduction of two-dimensional materials and nanoparticles for future THz applications are summarized and discussed.