A chemometric-assisted method for automatic, rapid and non-targeted detection of multi-pesticides in plant-derived foods by gas chromatography-mass spectrometry.

An automatic, rapid and non-targeted detection method for multi-pesticides in plant-derived foods was developed by gas chromatography-mass spectrometry and chemometrics. In this method, a novel algorithm named moving window iterative target transformation factor analysis was proposed. Although there are challenges of peak overlapping and background interference, the retention time and corrected mass spectra of unknown pesticides can be automatically obtained through iteration calculation in the 'moving window' with reference to the pesticide mass spectral library. One mixed pesticide standard and nine varieties of plant-derived foods were investigated with the proposed method. By contrast, a fast temperature programme was used to shorten detection time compared to the standard temperature programme. For the mixed standard, the mass spectra and retention times of all 39 pesticides were successfully obtained from the overlapping signal. Furthermore, all spiked pesticides were successfully detected in plant-derived foods within 10 min using a fast temperature programme.

Targeted Removal of Galloylated Flavanols to Adjust Wine Astringency by Using Molecular Imprinting Technology.

Excessive galloylated flavanols not only cause instability in the wine but also lead to unbalanced astringency. Although clarification agents are always used to precipitate unstable tannins in wine, the non-specific adsorption of tannins results in the failure to precisely regulate the tannin composition of the wine. In this work, molecularly imprinted polymers (MIPs) with template molecules of galloylated flavanols were designed to specifically adsorb gallotannins to reduce wine astringency. The results showed that the "pores" on the surface of the MIPs are the structural basis for the specific adsorption of the target substances, and the adsorption process is a chemically driven single-molecule layer adsorption. Moreover, in the mono/oligomeric gallotannin-rich model solution, the adsorption of gallotannins by I-MIPs prepared as single template molecules reached 71.0%, and the adsorption capacity of MIPs for monomeric gallotannins was about 6.0 times higher than polymeric gallotannins. Given the lack of technology for the targeted adsorption of tannins from wine, this work explored the targeted modulation of wine astringency by using molecular imprinting techniques.

The role of Arabic gum on astringency by modulating the polyphenol fraction-protein reaction in model wine.

The potential contribution of Arabic gum to wine astringency was discussed in this study. Two universally used Arabic gum (concentration of 0.2-1.2 g/L) were investigated in model wine based on the polyphenol fractions (phenolic acids, monomeric/oligomeric, and polymeric procyanidin) and protein interaction system. Both physicochemical analyses and sensory evaluation revealed that the modulation of Arabic gum on astringency was affected by the structural properties and concentration of Arabic gum and polyphenolic fractions. Arabic gum at 0.2 g/L appeared as the optimal dose to reduce astringency compared to 0.6 and 1.2 g/L. It inhibited astringency induced by polymeric procyanidin more than that of oligomeric procyanidins and phenolic acids mainly by forming soluble ternary complexes with polyphenols and proteins, and preferentially binding proteins/polyphenols to decrease polyphenol-protein reactions. Arabic gum also inhibited the self-aggregation of polyphenols, exhibiting more binding sites when its higher molecular weight and more/longer branches, leading to competition with polyphenols for bind proteins.

Investigating wine astringency profiles by characterizing tannin fractions in Cabernet Sauvignon wines and model wines.

Contribution of various phenols on wine astringency profiles was far from clear explanations. To effectively describe wine astringency profiles and determined the function of tannins/matrix (pH and ethanol), multiple chemical analyses combined RATA (Rate-all-that-apply) sensory method were applied in Cabernet Sauvignon and model wines. Results showed that polymeric flavanols determined the bulk of wine astringency intensity, oligomeric tannins enriched the smoothness and periodontium astringency, and monomeric phenol enhanced overall astringency intensity through synergistic effect. Astringency balance was effectively quantification, and its potential correlation relationship with epicatechin extension subunit (0.83) and fluorescence peak shift (0.75) cannot be ignored. The astringency profiles of condensed tannins with anthocyanins were enhanced. Low-pH (from 3.8 to 3.0) enhanced astringency by increasing the tannins affinity to proteins, while ethanol (from 10.0 % âˆ¼ 15.0 %) decreased the hydrophobicity bond between tannins-protein interaction. This paper provided new insights to explain wine astringency profiles and a reference for astringency modification during winemaking.

Visual characterization of microplastics in corn flour by near field molecular spectral imaging and data mining.

As potential hazard to human health, microplastics have attracted increasing attention. Most current studies have addressed the characterization of microplastics from the environment. For microplastics in food, most detections focused on liquid systems such as alcohol, beverages, etc., while there has been quite rare research on microplastics in solid foods with complex matrices. Thus, this study attempted to use three molecular spectral imaging approaches, namely, Fourier transform infrared (FTIR), optical photothermal resonance infrared (O-PTIR), and confocal Raman spectral imaging, combined with chemometrics to characterize the presence of microplastics in corn flour. The results demonstrated that O-PTIR imaging can rapidly sense the presence of microplastics, but its data integrity and visualization were limited. By decomposing the image, FTIR and Raman acquired a more integral distribution. Wherein, microplastics were well depicted by Raman imaging coupled with independent component analysis. Moreover, O-PTIR imaging can quickly detect contaminants at low concentrations but with a low detection rate. Raman imaging underperformed in low-concentration samples but provided a better visualization in mid-concentration samples. Overall, the results confirmed that the visual detection of microplastics in powdered food can be realized by molecular spectral imaging coupled with data mining, which can provide a reference for the detection of microplastics in other foods.

Investigating the role of tartaric acid in wine astringency.

Previous studies acknowledged that tartaric acid-imparted low-pH contributed to the enhancement of astringency, but in-depth studies are lacking and the underlying mechanisms are not clearly understood. This work introduced new insight into the effect of tartaric acid on astringency perception from the perspectives of complex formation, protein secondary structure, chemical bond type and salivary layer fluidity by establishing models using proteins (α-amylase, salivary proteins) and tannic acid. Results demonstrated that tartaric acid affects wine astringency by two mechanisms: a) Tartaric acid compound directly affects the wine astringency by forming ternary complexes and causing the protein structure to stretch by changing the hydrogen bond and hydrophobic bond between protein-polyphenol complexes. b) pH affected astringency by increasing the fluidity of the salivary layer rather than increasing the consumption of the salivary layer. The findings provide valuable information to the wine industry to regulate wine astringency by the management of tartaric acid.

Developing novel oenological tannins from 44 plants sources by assessing astringency and color in model wine.

BACKGROUND: Oenological tannins are commercial natural products extracted from different botanical sources, which were widely reported as prominent contributors to wine quality. Research on wine quality affected by tannins extracts promoted the development of new oenological products with low cost and high accessibility. In the present study, the structure and concentration of tannin in polyphenol extracts, as well as their correlation with astringency and the color of model wine, was investigated by UV spectrophotometer, HPLC, fluorescence quenching, sodium dodecylsulfate-polyacrylamide gel electrophoresis, colorimeter and sensory evaluation. RESULTS: Resource extracts from 16 of 44 plants were screened as wine oenological tannins, according to the total polyphenol and total flavanol, as well as the intensity of astringency and bitterness. Polyphenols extracted from grape seeds and green tea were more effective in increasing the wine astringency compared to other plant tannins. CONCLUSION: Total flavanol content and tannin activity showed a strong correlation with wine astringency. Condensed tannins with mean degree of polymerization also exhibited strong color stability, and the concentrations of (-)-epigallocatechin were associated with the a* value, a negative qualitative factor for wine color. The present study provides new clues regarding the development of low-cost and highly accessible sources of polyphenol extracts and lays a theoretical foundation for the development of the oenological product. © 2022 Society of Chemical Industry.

Investigation of exposure biomarkers in human plasma following differing levels of tobacco-specific N-nitrosamines and nicotine in cigarette smoke.

Tobacco-specific N-nitrosamines (TSNAs) are strong carcinogens widely found in tobacco products, environmental tobacco smoke, lake, and wastewater. The main objective of this study was to investigate the effects of cigarette smoke with different yields of TSNAs (NNK, NNN, NAT, NAB) and nicotine on the levels of biomarkers of exposure in smokers' plasma. Three hundred healthy volunteers were recruited comprising 60 smokers of each of 3 mg, 8 mg and 10 mg ISO tar yield cigarettes and 60 smokers who smoked 10 mg, 8 mg, and 3 mg for 14 days sequentially and 60 non-smokers. All study participants were male, aged from 21 to 45 years old, and were recruited from a same unit in Hebei, China. We measured the levels of NNAL, NAT, NNN, NAB and cotinine in plasma from 240 smokers and 60 non-smokers using a novel method established by online two-dimensional solid phase extraction-liquid chromatography-tandem mass spectrometry. The results showed that NNAL, NAT, NNN, NAB and cotinine in the plasma of smokers smoking cigarette with low TSNAs and nicotine were lower than that with high TSNAs and nicotine. When smokers switched from higher to lower TSNA yields of cigarettes, their plasma NNAL, NAT, NNN, NAB levels significantly decreased. The plasma concentrations of NNAL were significantly correlated with those of cotinine, NNN, NAT and NAB for smokers (p < 0.001). Similarly, the plasma concentrations of cotinine were significantly correlated with those of NNN, NAT and NAB for smokers (p < 0.001). The plasma NNAL, NAT, NNN, NAB and cotinine levels for smokers were significantly higher than those for non-smokers. These findings suggested that the total NNAL, NNN, NAT, NAB and cotinine in plasma were valid and reliable biomarkers for human exposure to TSNAs and nicotine.

Correction to: Rapid spectral analysis of agro-products using an optimal strategy: dynamic backward interval PLS-competitive adaptive reweighted sampling.

The authors would like to call the reader's attention to the fact that, unfortunately, there was a mistake regarding the affiliations of three of the authors in this manuscript; please find the correct information below.

A simple and nondestructive approach for the analysis of soluble solid content in citrus by using portable visible to near-infrared spectroscopy.

A simple and nondestructive method for the analysis of soluble solid content in citrus was established using portable visible to near-infrared spectroscopy (Vis/NIRS) in reflectance mode in combination with appropriate chemometric methods. The spectra were obtained directly by the portable Vis/NIRS without destroying samples. Outlier detection was performed by using leave-one-out cross-validation (LOOCV) with the 3σ criterion, and the calibration models were established by partial least squares (PLS) algorithm. Besides, different data pretreatment methods were used to eliminate noise and background interference before calibration, to determine the one that will lead to better model accuracy. However, the correlation coefficients are all <0.62 and the results of all pretreatments are still unsatisfactory. Variable selection methods were discussed for improving the accuracy, and variable adaptive boosting partial least squares (VABPLS) method was used to get higher robustness models. The results show that standard normal variate (SNV) transformation is the best pretreatment method, while VABPLS can significantly simplify the calculation and improve the result even without pretreatment. The correlation coefficient of the best prediction models is 0.82, while the value is 0.48 for the raw data. The high performance shows the feasibility of portable Vis/NIRS technology combination with appropriate chemometric methods for the determination of citrus soluble solid content.

A Rapid and Nondestructive Approach for the Classification of Different-Age Citri Reticulatae Pericarpium Using Portable Near Infrared Spectroscopy.

Citri Reticulatae Pericarpium (CRP), has been used in China for hundreds of years as a functional food and medicine. However, some short-age CRPs are disguised as long-age CRPs by unscrupulous businessmen in order to obtain higher profits. In this paper, a rapid and nondestructive method for the classification of different-age CRPs was established using portable near infrared spectroscopy (NIRS) in diffuse reflectance mode combination with appropriate chemometric methods. The spectra of outer skin and inner capsule of CRPs at different storage ages were obtained directly without destroying the samples. Principal component analysis (PCA) with single and combined spectral pretreatment methods was used for the classification of different-age CRPs. Furthermore, the data were pretreated with the PCA method, and Fisher linear discriminant analysis (FLD) with optimized pretreatment methods was discussed for improving the accuracy of classification. Data pretreatment methods can be used to eliminate the noise and background interference. The classification accuracy of inner capsule is better than that of outer skin data. Furthermore, the best results with 100% prediction accuracy can be obtained with FLD method, even without pretreatment.

Rapid spectral analysis of agro-products using an optimal strategy: dynamic backward interval PLS-competitive adaptive reweighted sampling.

A novel strategy of variable selection approach named dynamic backward interval partial least squares-competitive adaptive reweighted sampling (DBiPLS-CARS) was proposed in this study. Near-infrared data sets of three different agro-products, namely corn, crop processing lamina, and plant leaf samples, were collected to investigate the performance of the proposed method. Weak relevant variables were first removed by DBiPLS and a refined selection of the remaining variables was then conducted by CARS. The Monte Carlo uninformative variable elimination (MCUVE) was used as a classical beforehand uninformative variable elimination method for comparison. Results showed that DBiPLS can select informative variables more continuously than MCUVE. Some synergistic variables which may be omitted by MCUVE can be retained by DBiPLS. By contrast, MCUVE can hardly avoid the disturbance of certain weak relevant variables as a result of its calculation based on the full spectrum regression. Therefore, DBiPLS exhibited the advantage of removing the weak relevant variables before CARS, and simultaneously improved the prediction performance of CARS.

Phenolic composition of apple products and by-products based on cold pressing technology.

Cold pressing technology is a new technology using during the apple juice processing, which involved peeling and deseeding of apples at low temperature. The phenolics of apple juice, apple vinegar and apple pomace generated by cold pressing and traditional process were investigated. The results showed that the total phenols and flavanols of cold pressing apple juice were lower than those of traditional process. The total phenols content of peel pomace extract was significantly higher than that of the pulp pomace by almost tenfold, which showed that the peels and seeds were valuable sources of phenolic compounds. The total phenols of apple vinegars were significantly different. The predominant compounds in apple products were phloridzin and chlorogenic acid, while the apple pomaces based on cold pressing technology had significantly high content of phenolic compounds, indicating that the cold pressing technology could facilitated the use of apple pomace for bioactive compounds.

Identification of aminoglycoside antibiotics in milk matrix with a colorimetric sensor array and pattern recognition methods.

Aminoglycoside antibiotics (AAs) abused in animal husbandry can cause antibiotic residues in animal-derived foods, which do harm to human beings' health. Therefore the detection of AAs residues in the animal-origin foods, such as milk, eggs and meat is necessary. We used two single-stranded DNA (ssDNA) oligonucleotides as nonspecific receptors to develop a simple colorimetric sensor array based on gold nanoparticles (AuNPs) for identification and quantification the AAs. Different AA addition triggered the DNA detaching from AuNPs then resulted in different degree salt induced aggregation of AuNPs. The aggregation induced spectral changes of AuNPs with five AA addition were analyzed based on pattern recognition techniques, fisher linear discriminant analysis (FLD) and hierarchical cluster analysis (HCA). The results indicated that colorimetric sensor array has successfully identified five AAs at a concentration range of 120-280 nM. Five AAs in aqueous solution and complex milk matrix can be identified with an accuracy of 100%. More importantly, our developed sensor array is sufficiently sensitive for the discrimination of pure streptomycin (STR), binary mixtures of STR and gentamicin (GEN) at a total concentration of 120 nM.

Distribution assessment and quantification of counterfeit melamine in powdered milk by NIR imaging methods.

This paper presents a rapid calculation method for the imaging process in the identification and quantification of prohibited additives in milk. Data abstraction methods such as principal component analysis (PCA), classical least squares regression (CLS), and alternative least squares regression (ALS) were used. Different multivariate calculations provided possibilities of quantifying near-infrared (NIR) spectral data cube obtained from the surface of the complex mixture. The results of principal component decomposition confirmed that sample mixture identification is feasible using the PCA-CCI methods. Subsequently, CLSI was used for the direct quantitative analysis of the specific component. Behaving more conveniently than PLS without modeling, CLSI can obtain quantitative information as that melamine generally distribute at the low concentration range of 0-0.5 w/w. Moreover, ALSI can quantify the target component with higher accuracy than CLSI. Standard error of residue to predicted value is 0.0838. Lack of fit is 0.0841. Explanation of variables in the mixture is 99.30%, illustrating that the selective lack of rank is insignificant. Obviously, the most intuitive distribution images are constructed by ALSI among four imaging methods.

Rapid and nondestructive analysis of pharmaceutical products using near-infrared diffuse reflectance spectroscopy.

Near-infrared diffuse reflectance spectroscopy (NIRDRS) was applied to classification and quantification of azithromycin tablets with the aid of chemometric multivariate analysis. Repeatability was investigated by repeated measurements, and the effect of morphology was examined by preparing the tablets in four forms, i.e. tablet product, tablet without coating, powder of tablet without coating, and powder of tablet. Furthermore, baseline elimination by continuous wavelet transform (CWT) and wavenumber selection was discussed for improving the repeatability and accuracy of the method. The results show that the spectra of the samples in the four forms can be measured with an acceptable repeatability, and classification of manufacture sites and quantitative analysis of the active pharmaceutical ingredient (API) can be achieved by principal component analysis (PCA) and partial least squares (PLS) regression, respectively. More importantly, baseline elimination and wavenumber selection can significantly simplify the calculation and improve the results.