Non‑Tableting Quantitative Detection Method for Powder Mixtures Based on Terahertz Spectroscopy

Rivaroxaban, as a direct oral anticoagulant, has been widely used in the treatment and prevention of thrombosis disease (TD). However, even if the same dose of rivaroxaban is taken, different pathophysiological characteristics of TD patients determine the differences in plasma concentrations between individuals, leading to the difficulties of dosage selection and plasma concentration control. Conventional rivaroxaban detection methods, including prothrombin time method, anti-Xa assay and liquid chromatography-tandem mass spectrometry (LC-MS/MS), are not widely used in clinical practice due to the limitations of accuracy, speed and cost. Here, we present a simple quantitative detection method for rivaroxaban by terahertz (THz) spectroscopy. Combining density functional theory (DFT) method and THz spectroscopy, the THz absorption peaks of rivaroxaban and the corresponding low-frequency vibrational modes are studied theoretically and experimentally. We find linear relationships between the amplitudes of these characteristic peaks and the concentrations of rivaroxaban. Based on these linear functions, we can analyse the rivaroxaban concentration with a detection time of 1 minute per test and the lowest detection limit of 2 μmol mL-1. As compared to Raman spectroscopy method (its detection limit is about 80 μmol mL-1), our method has more potential and is practical for the clinical quantitative detection of rivaroxaban as well as other direct oral anticoagulants.

Detection of heavy metals in vegetable soil based on THz spectroscopy

As one of the main functional substances, carbohydrates account for a large proportion of the human diet. Conventional analysis and detection methods of dietary carbohydrates and related products are destructive, time-consuming, and labor-intensive. In order to improve the efficiency of measurement and ensure food nutrition and consumer health, rapid and nondestructive quality evaluation techniques are needed. In recent years, terahertz (THz) spectroscopy, as a novel detection technology with dual characteristics of microwave and infrared, has shown great potential in dietary carbohydrate analysis. The current review aims to provide an up-to-date overview of research advances in using the THz spectroscopy technique in analysis and detection applications related to dietary carbohydrates. In the review, the principles of the THz spectroscopy technique are introduced. Advances in THz spectroscopy for quantitative and qualitative analysis and detection in dietary carbohydrate-related research studies from 2013 to 2022 are discussed, which include analysis of carbohydrate concentrations in liquid and powdery foods, detection of foreign body and chemical residues in carbohydrate food products, authentication of natural carbohydrate produce, monitoring of the fermentation process in carbohydrate food production and examination of crystallinity in carbohydrate polymers. In addition, applications in dietary carbohydrate-related detection research using other spectroscopic techniques are also briefed for comparison, and future development trends of THz spectroscopy in this field are finally highlighted.

For enforcement of the recently introduced labeling threshold for genetically modified organisms (GMOs) in food ingredients, quantitative detection methods such as quantitative competitive (QC-PCR) and real-time PCR are applied by official food control laboratories. The experiences of 3 European food control laboratories in validating such methods were compared to describe realistic performance characteristics of quantitative PCR detection methods. The limit of quantitation (LOQ) of GMO-specific, real-time PCR was experimentally determined to reach 30-50 target molecules, which is close to theoretical prediction. Starting PCR with 200 ng genomic plant DNA, the LOQ depends primarily on the genome size of the target plant and ranges from 0.02% for rice to 0.7% for wheat. The precision of quantitative PCR detection methods, expressed as relative standard deviation (RSD), varied from 10 to 30%. Using Bt176 corn containing test samples and applying Bt176 specific QC-PCR, mean values deviated from true values by -7to 18%, with an average of 2+/-10%. Ruggedness of real-time PCR detection methods was assessed in an interlaboratory study analyzing commercial, homogeneous food samples. Roundup Ready soybean DNA contents were determined in the range of 0.3 to 36%, relative to soybean DNA, with RSDs of about 25%. Taking the precision of quantitative PCR detection methods into account, suitable sample plans and sample sizes for GMO analysis are suggested. Because quantitative GMO detection methods measure GMO contents of samples in relation to reference material (calibrants), high priority must be given to international agreements and standardization on certified reference materials.

As antibiotic residue becomes more and more serious all over the world, a rapid and effective detection method is needed to evaluate the antibiotic residue in feed matrices to ensure food safety for consumers. In this study, three different kinds of fluoroquinolones (norfloxacin, enrofloxacin, and ofloxacin) in feed matrices were analyzed using terahertz (THz) spectroscopy, respectively. Meanwhile, pure fluoroquinolones and pure feed matrices were also measured in the same way. Then, the absorption spectra of all of the samples were extracted in the transmission mode. Pure norfloxacin has two absorption peaks at 0.825 and 1.187THz, and they could still be observed when mixing norfloxacin with feed matrices. Also, there was an obvious and strong absorption peak for ofloxacin at 1.044THz. However, no obvious absorption peak for enrofloxacin was observed, and only a weak absorption peak was located at 0.8THz. Then, the different models were established with different chemometrics to identify the fluoroquinolones in feed matrices and determined the fluoroquinolones content in the feed matrices. The least squares support vector machines, Naive Bayes, Mahalanobis distance, and back propagation neural network (BPNN) were used to build the identification model with a Savitzky-Golay filter and standardized normal variate pretreatments. The results show that the excellent classification model was acquired with the BPNN combined with no pretreatment. The optimal classification accuracy was 80.56% in the testing set. After that, multiple linear regression and stepwise regression were used to establish the quantitative detection model for different kinds of fluoroquinolones in feed matrices. The optimal correlation coefficients for norfloxacin, enrofloxacin, and ofloxacin in the prediction set were obtained with multiple linear regression that combined absorption peaks with wavelengths selected by stepwise regression, which were 0.867, 0.828, and 0.964, respectively. Overall, this research explored the potential of identifying the fluoroquinolones in feed matrices using THz spectroscopy without a complex pretreatment process and then quantitatively detecting the fluoroquinolones content in feed matrices. The results demonstrate that THz spectra could be used to identify fluoroquinolones in feed matrices and also detect their content quantitatively, which has great significance for the food safety industry.

Quantitative analysis of soybean protein content by terahertz spectroscopy and chemometrics

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

The pharmaceutical industry requires a simple nondestructive quantitative inspection technique that does not change the characteristic properties of the target of inspection. Terahertz (THz) spectroscopy has potential as a nondestructive inspection technique because of the high transmittance of inspected materials and the absorption peaks related to some active pharmaceutical ingredients (APIs) in THz frequency regions. We have developed a compact terahertz spectroscopy system that uses an injection-seeded terahertz parametric generator (is-TPG) as a THz light source for the inspection and quantitative analysis of pharmaceutical tablets. Using this system, acetylsalicylic acid, acetaminophen, tranexamic acid, loxoprofen sodium, and caffeine included in over-the-counter (OTC) medicine tablets were identified as APIs by their specific absorption peaks. We also conducted a quantitative analysis of acetaminophen in one of the medicines by performing multivariate analyses. The root-mean-squared error of cross-validation (RMSECV) was 0.297 wt%. The limit of detection (LOD) and limit of quantitation (LOQ) were 0.990 wt% and 3.00 wt%, respectively. These results indicate that this is-TPG system could be applied as an inspection and quantitative analysis technique for OTC medicine tablets.

Using terahertz spectroscopy to quantify bioactive flavonoids in Moxa Wool as predictor of rheumatoid arthritis treatment outcomes

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.

The development of new spectral analysis methods in bio thin-film detection has generated intense interest in terahertz (THz) spectroscopy and its application in a wide range of fields. In this paper, it is the first time that machine learning methods are applied to the quantitative characterization of bovine serum albumin (BSA) deposited thin-films detected by terahertz time-domain spectroscopy. The spectra data of BSA thin-films prepared by solutions with concentrations ranging from 0.5 to 35 mg/ml are analyzed using the support vector regression method to learn the underlying model of the frequency against the target concentration. The learned mode successfully predicts the concentrations of the unknown test samples with a coefficient of determination R2 = 0.97932. Furthermore, aiming to identify the relevance of each frequency to the concentration, the maximal information coefficient statistical analysis is used and the three most discriminating frequencies in THz frequency are identified at 1.2, 1.1 and 0.5 THz respectively, which means a good prediction for BSA concentration can be achieved by using the top three relevant frequencies. Moreover, the top discriminating frequencies are in good agreement with the frequencies predicted by a long-wavelength elastic vibration model for BSA protein.

Norfloxacin is a kind of quinolone bactericide which is widely used in food industry, livestock feed and medicine area. At present, how to develop a rapid, convenient and accurate technique for qualitative and quantitative detection of norfloxacin is still a challenge. In this study, Terahertz Time-domain Spectroscopy technology (THz-TDS) was used to explore qualitative and quantitative analysis of norfloxacin. Forty-five norfloxacin samples with different levels were prepared. The pure norfloxacin powder was mixed with polyethylene (PE) powder together and made into tablets by tablet-making machine. The minimum detection concentration was 10% and the maximum detection concentration evaluated in the paper was 90%. Then, terahertz (THz) spectra of each sample were measured on K15 THz-TDS equipment. The multiple linear regressions and the partial least squares regression algorithms were used to establish a model to make quantitative analysis. From the results, two typical fingerprint peaks of norfloxacin in terahertz band were observed at 0.944 THz and 1.206 THz, and the correlation coefficient and the root mean square error of the established model reached 0.9908 and 0.0481, respectively, which showed that the model performed well for the prediction. This preliminary study indicates that THz spectroscopy has great potential for future screening applications to detect the presence of norfloxacin residues in food, livestock feed and medicine industries. Keywords: Terahertz spectroscopy, norfloxacin, qualitative and quantitative detection, model, correlation coefficient DOI: 10.25165/j.ijabe.20171005.2962 Citation: Long Y, Li B. Preliminary study on qualitative and quantitative detection of norfloxacin based on terahertz spectroscopy. Int J Agric & Biol Eng, 2017; 10(5): 262–268.

Caffeine is an alkaloid and may be the most commonly ingested pharmacologically active substance in the world, but continuous abuse may lead to “caffeine poisoning”. In this study, we propose a method for the qualitative and quantitative analysis of caffeine in various medicines using terahertz spectroscopy combined with chemometrics. By comparing this terahertz (THz) spectroscopy technology (Fourier transform infrared instrument, FTIR) with high performance liquid chromatography (HPLC) and Raman spectroscopy, we prove that there is less than a 5% difference between the THz and HPLC results, which is far superior to the nondestructive testing results obtained using Raman spectroscopy. In addition, the quantitative analysis of caffeine in 86 medicines was conducted using the support vector regression (SVR) chemometric method, and the correlation coefficient R achieves 99.61%. Therefore, we have effectively proven that THz spectroscopy technology combined with chemometric can achieve nondestructive, fast, and efficient qualitative and quantitative detection of key ingredients in medicines.

The detection of the wheat moisture content plays a key role in grain storage and classification. Harvested wheat grains were taken as samples in the current research. A total of 240 reaped wheat samples with different moisture contents were tested by applying terahertz (THz) spectroscopy. The frequency domain spectra and absorption coefficient spectra of wheat were obtained in the band of 0.1-1.2 THz, and the spectra were pretreated by mean centering, Savitzky-Golay (S-G), Multiplicative Scatter Correction (MSC) and Stand Normal Variate (SNV), respectively. Then a special algorithm of Tabu Search (TS) was used to find out the effective variables and remove the useless variables from the terahertz spectrum of the sample. Finally, the partial least squares (PLS) of chemometrics were used for quantitative model building and prediction. The correlation coefficient of calibration (Rc) is 0.9522. The root mean square error of calibration (RMSEC) is 0.4730. The correlation coefficient of prediction (Rp) is 0.9531. The root mean square error of prediction (RMSEP) is 0.5396. The results demonstrated that an accurate quantitative analysis of moisture in wheat samples could be achieved by terahertz time-domain spectroscopy combined with the TS algorithm. In addition, the results show that the model S-G + MSC + TS + PLS can effectively predict wheat moisture, and provide a rapid quantitative detection and analysis method for the detection of wheat moisture.

Salmonella is a pathogen that comes from different animal-originated foods and poses a significant threat to human health. The present detection methods for Salmonella are time-consuming and labor-intensive and requires skilled workers and specialized instruments. In this study, the conservative invA was selected as the target gene, and a quantitative detection method for Salmonella with wide availability and user-friendliness was established based on CRISPR Cas12a and a personal glucose meter (PGM). The indirect signal transformation from the original target DNA to the final glucose signal was achieved through RAA, CRISPR Cas12a reaction, enzymic reaction, and glucose signal reading by a PGM (accu-chek type from Roche). This PGMs-CRISPR assay showed a detection sensitivity of Salmonella as low as 5 colony-forming units (CFU)/reaction in either pure culture or artificially contaminated food samples and exhibited specificity between Salmonella isolates and non-Salmonella isolates. Furthermore, quantitative detection of Salmonella in spiked milk samples was also achieved within the range from 1 to 1 × 103 CFU/reaction. Subsequently, the correlation and consistency between the PGMs-CRISPR assay and quantitative polymerase chain reaction (qPCR) in detection of Salmonella in spiked milk samples were achieved. Therefore, a highly sensitive, portable, quantitative, and user-friendly detection method based on CRISPR Cas12a and PGMs was developed in this study for Salmonella detection and identification. PRACTICAL APPLICATION: A sensitive, rapid, user-friendly, and quantitative detection method based on CRISPR Cas12a for Salmonella in food has been developed in this study, which is of great significance to food safety supervision and management.