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Chrysanthemi Flos 'Hangbaiju' (HBJ) is a common Chinese medicinal material with the same origin as the medicinal and edible cognate plant in China, whose quality is seriously affected by the place of origin. In this study, four stable isotope ratios (δ15N, δ2H, δ13C, and δ18O) and 44 elements were detected and analyzed in 191 HBJ flower samples from six locations in China to trace the origin of HBJ. An ANOVA analysis of δ15N, δ2H, δ13C, and δ18O values, as well as milti-elements, showed that there were significant differences among the six places of origin. Partial least squares discriminant analysis (PLSDA) and one-class partial least squares discriminant analysis (OPLS-DA) models were established to trace the origin of HBJ from these six locations. The results showed that the classification effect of the PLSDA model is poor; however, the established OPLS-DA model can distinguish between products of national geographic origin (Tongxiang City, Zhejiang Province, China) and samples from other origins, among which Ni, Mo, δ13C, Cu, and Ce elements (VIP > 1) contribute the most to this classification. Therefore, this study provides a new method for tracing the origins of HBJ, which is of great significance for the protection of origin labeling of products. [ABSTRACT FROM AUTHOR]

Fupenzi (Rubus chingii Hu) is a dried and immature fruit in East China, which has effects of nourishing kidneys, solidifying essence, and otherwise. Because Fupenzi was often adulterated and replaced with inferior things, this paper had researched Fupenzi and its adulterant raspberry. A new type of visible sensor was constructed by using Au nanoparticles (AuNPs), which was modified by the surface-active agent and combined with the ultraviolet-visible (UV-vis) spectrum technology. It was found that the change in particle size after the interaction of AuNPs and adulterants will lead to color change. In this paper, the RGB (red, green, and blue) values of the solution were extracted to correlate the color with the concentration of adulterants, and the relationship between the absorption peak intensity and the concentration of adulterants was established. The results showed that the intensity of an absorption peak is related to adulteration concentration, and the color of the solution changed from red to gray as the particle size changed. The visual sensor constructed based on the above principle is a fast and precise method to detect adulteration with different concentrations, which has a potential application value in real-time and rapid detection of Fupenzi's quality. [ABSTRACT FROM AUTHOR]

Lilii bulbus is an important food in China with medicinal and edible functions, and its quality and price are closely related to its geographical origin. In this work, 4 stable isotopes (δ13C, δ15N, δ2H and δ18O) and 41 mineral elements of lilii bulbus samples from 11 origins and 4 species were collected and combined with chemometrics to identify origins and species. ANOVA and principal component analysis (PCA) showed significant differences (P < 0.05) in stable isotopes and multiple elements in lilii bulbus samples from different origins, and Cu, Zn, K, δ18O, Sr and Li are important contributors to the classification. Partial least squares discriminant analysis (PLS-DA) and orthogonal partial least squares discriminant analysis (OPLS-DA) were used to classify different species of lilii bulbus with good classification performance, while indicating that K, Ca, Na and Mg elements could be used as effective elements for species classification. The external validation model of OPLS-DA showed high accuracy (>89%) for lilii bulbus species classification. This study shows that stable isotopes and multi-elemental combined chemometrics provide an effective method for lilii bulbus origin and species identification. [Display omitted] • Geographic identification of lilii bulbus with stable isotopes and elements is feasible. • δ18O are useful factors for identifying lilii bulbus's geographical origin. • K, Ca, Na and Mg are important factors to distinguish different species of lilii bulbus samples. • The accuracy of OPLS-DA in discriminating lilii bulbus species is more than 89.61%. [ABSTRACT FROM AUTHOR]

The concentration of advanced glycation end products (AGEs) in foods, which are formed by Maillard reaction, has demonstrated as risk factors associated with many chronic diseases. The AGEs inhibitory activities of five common phenolic acids (protocatechuic acid, dihydroferulic acid,p-coumaric acid,p-hydroxybenzoic acid and salicylic acid) with different chemical properties had been investigated in two food simulation systems (glucose-bovine serum albumin (BSA) and oleic acid-BSA). The results substantiated that the AGEs inhibitory abilities of phenolic acids in the oleic acid BSA system were much better than the glucose-BSA system for their strong reducing powers and structures. Among them, dihydrogenferulic acid showed strong inhibition of AGEs formation in oleic acid-BSA system at 0.01 mg/mL compared to nonsignificant AGEs inhibitory effect in oleic acid-BSA system at 10-fold higher concentration (0.1 mg/mL). This study suggests that edible plants rich in phenolic acids may be used as AGEs inhibitor during high-fat cooking. [ABSTRACT FROM PUBLISHER]

[Display omitted] • Stable isotope and multi-element compositions of Huangjing was used for its origin traceability. • OPLS-DA significantly enhanced the traceability capability for Qingyang Huangjing products. • The discrimination accuracies of Qingyang (PGI products) were 100 % compared with other products. • Regional and farming patterns the correlations with eco-environment were discussed. • The strategy can be applied to combat mislabeling of PGI Huangjing products and ensure food safety. Huangjing (Polygonati Rhizoma) is a high-value homology of medicine and food in China, for which the geographical origins (i.e., geoherbalism) and farming patterns (natural or farmed) are decisive in its functions and selling price. In this study, five stable isotope ratios (δ 13C, δ 15N, δ 18O, δ 2H, and 87Sr/86Sr) and 48 multi-element signatures of 238 Huangjing samples collected from seven main production areas in China were analyzed together for origin traceability and farming authentication purposes. An analysis of variance (ANOVA) for each variable revealed that δ 18O, δ 2H, 87Sr/86Sr, Fe, and rare earth elements were significantly different among origins. The orthogonal partial least squares discriminant analysis (OPLS-DA) modeling of all variables indicated that K, Ca, Mg, Fe, and Mn were the most important variables (VIP > 1) for identifying Qingyang Huangjing protected geographical indication (PGI) from those of other origins, and discriminant accuracy reached 100 %. Moreover, ANOVA and OPLS-DA demonstrated that δ 15N, K, Ca, and Mg were the elements that effectively distinguished natural and farmed Huangjing. Therefore, the strategy may be an important alternative tool for authenticity management, which is significant for combating origin mislabeling and the fraudulent conducts of Huangjing products. [ABSTRACT FROM AUTHOR]

• GO-TAP-based mid-infrared spectroscopy for Pu-erh teas analysis was developed. • Nano-effect MIR spectra method was superior to the traditional MIR spectra method. • Twelve categories of Pu-erh teas were successfully classified by PLSDA model. • The age prediction of Pu-erh teas was satisfactorily achieved by PLSR model. Pu-erh tea is a unique post-fermented tea with special quality and unique aroma characteristics, which are achieved by aging as part of the tea-making processing in China. In this work, we developed a new method, based on the combination of the mid-infrared (MIR) spectroscopy of graphene oxide-5,10,15,20-mesotetra (4-aminophenyl) porphyrin hybrid (GO-TAP), with chemometrics, for the variety identification and age prediction of twelve Pu-erh teas. Partial least squares discriminant analysis (PLSDA) and partial least squares regression (PLSR) models were respectively employed to classify the variety of and predict the age of Pu-erh teas based on the collected MIR spectra. Compared with traditional MIR spectroscopy, MIR spectroscopy based on GO-TAP gave better accuracy and specificity in variety classification and age prediction. The GO-TAP complex-based MIR spectroscopy sensor coupled with chemometrics could achieve 100% accuracy for variety classification and predicts storage time of Pu-erh tea. This method can be applied for the accurate identification and prediction of Pu-erh tea storage time, and it might have enormous potential for the application in storage time identification of other food stuff. [ABSTRACT FROM AUTHOR]

Chrysanthemum is a common medicinal and edible Chinese herbal product, and its growth environment affects its quality and market sale price. So it has high practical value and relevance to establish an efficient, rapid and accurate approach to identify the origin of chrysanthemums. In this study, we collected chrysanthemum samples from six geographical indication (GI) production areas in China and analyzed the four stable isotope ratios (δ 13C, δ 15N, δ 18O, and δ 2H) and 44 mineral element signatures of chrysanthemums to classify chrysanthemum. An analysis of variance (ANVOA) indicated that stable isotope ratios and mineral elements differed significantly between origins. The accuracies of the training set and prediction set of the random forest (RF) algorithm were 100% and 98.3%, respectively, while those of the partial least squares discriminant algorithm (PLS-DA) were 96.9% and 96.7%, respectively; the results of the RF algorithm were slightly better than those of the PLS-DA. Combining stable isotopes and mineral elements could enhance the accuracy of origin identification. Moreover, the OPLS-DA (orthogonal partial least squares discriminant analysis) models for stable isotopes and mineral elements indicated that δ 2H, δ 18O, Cd, Zn, Mg, Ca, Tm, As, and Tl were the elements that could most effectively distinguish the origins of chrysanthemum, and the discriminant accuracy reached 100%. Therefore, the proposed strategy can offer a simple, rapid, and dependable approach for classifying the geographic origin of chrysanthemums. • Chrysanthemum samples were collected from 6 GI production areas in China. • Geographic identification of chrysanthemum with stable isotopes and elements is feasible. • Cd, Zn, Mg, Tm, As, Ca, and Tl play an important role in classification. • OPLS-DA significantly enhanced the traceability capability for chrysanthemum products. [ABSTRACT FROM AUTHOR]

[Display omitted] • Untargeted metabolomics was used to reveal the chemical differences of Hangbaiju. • Influence of soil mineral elements on the content of differential metabolites was investigated. • Relationship between metabolites and mineral elements was explored by chemometric analysis. • Differential metabolites were significantly correlated with mineral elements in planting soils. • This work provides new insights for better understanding geographical differences of Hangbaiju. Chrysanthemum morifolium Ramat cv. "Hangbaiju" (HBJ), known as one of the "eight flavors of Zhejiang", is commonly used as a classical tea material for both food and medicine over three thousand years in China. The quality of HBJ is closely related to its geographical origins. However, the mechanism underlying the geographical differences of HBJ remains to be elucidated. In this study, an untargeted metabolomic strategy based on UHPLC-QTOF-MS was established to discover the differential metabolites in HBJ samples from four different origins and explore the possible relationship with mineral elements in planting soils by chemometric analysis. Eight compounds were screened and identified as the key differential metabolites in HBJ samples from different origins. Among them, four important pharmacodynamic compounds including L-arginine, rutin, chlorogenic acid and apigenin-7-O-glucoside are the most abundant in HBJ samples from Tongxiang region, which suggests that HBJ planted in Tongxiang has higher medicinal values. Pearson correlation analysis revealed that the contents of soil mineral elements are positively correlated with those of chlorogenic acid, rutin, apigenin-7-O-glucoside in HBJ samples. Furthermore, an interrelationship model based on random forest algorithm was established to successfully predict the contents of differential metabolites in HBJ samples by soil mineral elements. All these results indicated that the contents of differential metabolites in HBJ samples seemed to be affected by soil mineral elements and therefore resulted in the geographical differences of HBJ. [ABSTRACT FROM AUTHOR]

In this work, a rapid and accurate strategy for classification of Chinese traditional cereal vinegars (CTCV) and antioxidant property predication was proposed by using the combination fluorescence spectroscopy and machine learning. Three characteristic fluorescent components were extracted by parallel factor analysis (PARAFAC), which have correlations greater than 0.8 with antioxidant activity of CTCV obtained by Pearson correlation analysis. Machine learning methods, including linear discriminant analysis (LDA), partial least squares-discriminant analysis (PLS-DA) and N-way partial least squares discriminant analysis (N-PLS-DA), were used for the classification of different types of CTCV, and the correct classification rates was higher than 97%. The antioxidant property of CTCV were further quantified by using optimized variable-weighted least-squares support vector machine based on particle swarm optimization (PSO-VWLS-SVM). The proposed strategy provides a basis for further research on antioxidant active ingredients and antioxidant mechanisms of CTCV, and enable the continued exploration and application of CTCV from different types., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

Baijiu is a distilled liquor of great importance in the food industry. Various aroma types, brands, and grades of Baijiu have filled the market; thus, discrimination for quality control is required. Herein, we constructed a novel colorimetric sensor array based on the redox reaction between silver nitrate and o-phenylenediamine or its derivatives for the discrimination of carbonyl flavor compounds (CFCs) and Baijius. The specific colored products were changed by CFCs depending on the influence of silver nanoparticle aggregation and chemical reactions. The array was used to qualitatively and quantitatively identify 21 CFCs with fast response (<14 min), wide linear range (0.025-25 mmol/L), and low detection limits (<60 μmol/L, 29 nmol/L for carboxylic acids). Finally, the array was successfully applied to the discrimination of 56 Baijius. The method proposed in this study is simple, fast, reliable, and has good application potential for the visual determination of Chinese Baijiu., (Copyright © 2021 Elsevier Ltd. All rights reserved.)

Baijiu quality control has always been a major challenge for researchers. In this paper, taking furfural which is closely related to baijiu brewing process and organic acids related to baijiu fermentation process and microorganism types as the main discriminating factors, a carbon dot (CDs) sensor array targeting furfural and organic acids was constructed to identify 41 kinds of baijiu. Through the fluorescence response investigation of CDs synthesized by isomers of benzenediol, aminophenol, and phenylenediamine to different baijiu, two CDs synthesized by meta-benzene substitutions containing -NH 2 were selected to build a fluorescence sensor array. Due to the aggregation-induced enhancement effect between furfural and the CDs, and the protonation of organic acid and the CDs, different fluorescence changes were observed, the sensor array combined with partial least squares regression could quantitatively analyze furfural and organic acids. What is more, semi-quantitative analysis of furfural and lactic acid in baijiu was performed. Owing to the interaction of the two CDs with furfural and organic acids in baijiu, the sensor array could accurately identify different baijiu through linear discriminant analysis. This sensor array has potential applications in the quantitative analysis of flavor substances in other alcoholic beverages, moreover, this method could provide a quick response and practical tool for real-time quality control monitoring in the baijiu industry., (© 2021 Institute of Food Technologists®.)

As a special carrier of traditional Chinese culture, baijiu is rich in terms of types and ingredients. Its quality analysis and control are always important and complex issues that urgently need reliable evaluation methods. In this study, four different modified CdTe quantum dots (QDs) were used to characterize their sensing performance to various baijiu. A sensor array was then constructed through the complementary properties of differential fluorescence signals. To achieve an accurate and rapid evaluation of different baijiu types, a linear discriminant analysis (LDA) was introduced to extract and process spectral information. And the array was able to distinguish commercial baijiu samples with different aroma-types, brands, qualities and storage years with a recognition rate of 100%. In addition, according to the heat map, the organic acids in baijiu were shown to be the main components causing the fluorescence change through electron transfer (hydrogen bond) and resonance energy transfer among QDs and acids. Furthermore, using the partial least squares regression (PLSR) model, five representative organic acids were accurately quantified with a quantitative range of 10 μmol/L-80 μmol/L with a high selectivity. This QDs fluorescence sensing strategy provides an accurate, simple, and fast baijiu sensing method, which provides a potential use for on-line baijiu monitoring., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2021 Elsevier B.V. All rights reserved.)

To enhance the power of untargeted detection, a "turn-off" fluorescent probe with double quantum dots (QDs) was developed and coupled with chemometrics for rapid detection of multiple adulterants in an herbal (Rhus chinensis Mill., RCM) honey. The double water-soluble ZnCdSe-CdTe QDs have two separate and strong fluorescent peaks, which can be quenched by honey and extraneous adulterants with varying degrees. Class models of pure RCM honey samples collected from 6 different producing areas (n = 122) were developed using one-class partial least squares (OCPLS). Four extraneous adulterants, including glucose syrup, sucrose syrup, fructose syrup, and glucose-fructose syrup were added to pure honey samples at the levels of 0.5% to 10% (w/w). As a result, the OCPLS model using the second-order derivative (D2) spectra could detect 1.0% (w/w) of different syrups in RCM honey, with a sensitivity of 0.949. The double water-soluble QDs, which can be adjusted for analysis of other water-soluble food samples, has largely extended the capability of traditional fluorescence and will provide a potentially more sensitive and specific analysis method for food frauds., (Copyright © 2019. Published by Elsevier B.V.)