This study aimed to improve the traceability of rice-producing areas to address the increasing demand for accurate methods to confirm food quality and safety. Compound-specific δ13C of fatty acids, ...δ13C of starch and bulk of rice were measured. PCA, PLS-DA and VIP value analysis of the obtained data were performed to track the source of rice from the six regions. The PLS-DA model established with bulk δ13C, starch δ13C, and fatty acid δ13C, which clearly separated the rice from six regions. The VIP graph showed the value of starch, C18:0 and C18:2 δ13C values (VIP > 1) were important to distinguish the origin of rice. Also, according to loading plots the contribution of starch δ13C was the largest. The findings indicate that the introduction of starch δ13C improves the precision of rice traceability and provides an effective method for identifying rice origin.
•Stable isotope analysis is explored for rice traceability in China.•Various multivariate modeling methods were applied for origin traceability purpose.•The introduction of starch-δ13C was beneficial to trace the origin of rice.•This strategy is an efficient method for combating origin mislabeling in rice trade.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
This study investigates concentrations of toxic and potentially toxic elements (PTEs) in organic and conventional wheat flour and grains marketed in Las Vegas. Geographic origins of the samples were ...evaluated using Linear Discriminant Analysis (LDA). Monte Carlo Simulation technique was also employed to evaluate non-carcinogenic risk in four life stages. Concentrations of Al, As, Cd, Co, Cr, Cu, Fe, Mn, Mo, Ni, Pb, Se, Sr, and Zn were determined using inductively coupled plasma mass spectrometry (ICP-MS) following hot block-assisted digestion. Obtained results showed non-significant differences in contents of toxic and PTEs between conventional and organic wheat grains/flour. Using LDA, metal(loid)s were found to be indicative of geographical origin. The LDA produced a total correct classification rate of 95.8% and 100% for US and West Pacific Region samples, respectively. The results of the present study indicate that the estimated non-carcinogenic risk associated with toxic element intakes across the four life stages were far lower than the threshold value (Target Hazard Quotient (THQ) >1). However, the probability of exceeding the threshold value for Mn is approximately 32% in children aged between 5 and 8 years. The findings of this study can aid in understanding dietary Mn exposure in children in Las Vegas.
•This study investigated the elemental contents of wheat from the Las Vegas market.•The contents of metal(loid)s b/n organic and conventional wheat were comparable.•Metal(loid)s were used as descriptors to classify the geographic origin of wheat.•Monte Carlo Simulation technique was employed to evaluate non-carcinogenic risks.•Mean THQ values for Mn exceed the threshold value (THQ = 1) in two life stages.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Brand heritage identity (BHI) has been examined in single corporate cases, often of family firms, in a specific country, to reveal a deep theoretical understanding of the concept and how BHIs are ...created. Our study complements this research by providing a large-scale empirical study of BHI in family firms across countries. Specifically, using signaling theory as a framework, this study investigates how country-level importance of family values, as well as firm age, influence the use of BHI and drive marketing performance for family businesses. BHI is a signal that helps stakeholders resolve market asymmetries and this signal is bolstered in countries where family is deemed more important. Firm age is an important moderator. The findings demonstrate that in countries where family, as a key social unit, is more important, firms signal competitiveness via BHI, which in turn relates positively to marketing performance.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
This paper applies near-infrared spectroscopy (NIRS) and multiple chemometrics to efficiently distinguish the origins of fresh tea leaves. The key components were obtained using the partial least ...squares discriminant analysis (PLS-DA) method. PLS, synergy interval PLS (siPLS), principal component analysis (PCA), genetic algorithm (GA), and their combination methods were used to establish NIRS non-destructive discrimination models. Then, the practical application was examined using external samples. The study identified nine key components (variable importance for the projection (VIP) > 1): epigallocatechin, epicatechin, total sugar, water extracts, total catechins, gallocatechin gallate, tea polyphenols, gallocatechin, and epigallocatechin gallate. Of the six NIRS models, the siPLS-GA model that used 37 spectral data points produced the best results (Rp2 = 0.9706, RMSEP = 0.0772, RPD = 6.59). This model had a prediction accuracy of 96.67% for the prediction set samples and 93.33% for the external samples. It offers a rapid, precise, and non-invasive approach to monitor and regulate the illicit trade of fresh tea leaves, thereby guaranteeing the authenticity of Enshi Yulu products from the processing source and fostering the long-term prosperity and stability of the Enshi Yulu tea industry.
•There is a limited amount of research on using NIRS to trace the origin of fresh tea leaves.•PLS-DA was used to identify the origins of fresh tea leaves based on nine key components.•The NIRS-siPLS-GA digital combination model exhibits high robustness and wide adaptability.•It is a low-cost modeling solution effectively addresses the authenticity problem of Enshi Yulu.•The research findings suggest broad application prospects.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
This study aimed at evaluating physicochemical traits of olive oil (‘Haouzia’ and ‘Moroccan Picholine’) according to extraction technologies (ETs: super-pressure SP, 2-phase 2 P, and 3-phase 3 P) ...across eight climatically contrasted Moroccan agroclimatic areas (AA). Our samples were classified as extra virgin olive oil (EVOO), whose traits varied (p < 0.05) among ETs, cultivars, and AA. EVOO from SP had high records of basic indices, most phytosterols, and trans fatty acids (TFA) due to partial oxidation during extraction, while continuous ETs (2 P and 3 P) displayed a better oil quality as demonstrated by routinely measured parameters. ‘Haouzia’ had the greatest saturated (SFA), monounsaturated (MUFA), polyunsaturated fatty acids (PUFA), and TFA. However, it had a lesser stability revealed by a low MUFA/PUFA and oleic/linoleic (O/L) as compared to ‘Moroccan Picholine’. Arid climatic areas had the highest palmitoleic, oleic acid, MUFA, MUFA/PUFA, and O/L and therefore the best oil stability as compared to the remaining agroclimatic areas. These variations were confirmed by principal component analysis, cluster analysis, and artificial neural networks. Important simple and multiple regression models with strong correlations were highlighted among the studied variables. In conclusion, environmental conditions have a key role to be considered when assessing olive oil quality and authenticity.
•Olive oils were investigated across eight Moroccan agroclimatic areas (ACA).•Major extraction technologies (2-phase, 3-phase, and super-pressure) were studied.•Artificial neural network, clustering, correlations, PCA, and regressions were used.•ACA together with cultivar were the main variability drivers in our data.•As compared to other climates, more arid ACA had higher oil oxidative stability.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
The use of suitable analytical techniques for the detection of adulteration, falsification, deliberate substitution, and mislabeling of foods has great importance in the industrial, scientific, ...legislative, and public health contexts. This way, this work reports an integrative review with a current analytical approach for food authentication, indicating the main analytical techniques to identify adulteration and perform the traceability of chemical components in processed and non-processed foods, evaluating the authenticity and geographic origin. This work presents results from a systematic search in Science Direct® and Scopus® databases using the keywords “authentication” AND “food”, “authentication,” AND “beverage”, from published papers from 2013 to, 2024. All research and reviews published were employed in the bibliometric analysis, evaluating the advantages and disadvantages of analytical techniques, indicating the perspectives for direct, quick, and simple analysis, guaranteeing the application of quality standards, and ensuring food safety for consumers. Furthermore, this work reports the analysis of natural foods to evaluate the origin (traceability), and industrialized foods to detect adulterations and fraud. A focus on research to detect adulteration in milk and dairy products is presented due to the importance of these products in the nutrition of the world population. All analytical tools discussed have advantages and drawbacks, including sample preparation steps, the need for reference materials, and mathematical treatments. So, the main advances in modern analytical techniques for the identification and quantification of food adulterations, mainly milk and dairy products, were discussed, indicating trends and perspectives on food authentication.
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•A bibliometric review of analytical techniques in food authentication is shown.•Adulteration and traceability analysis in milk and dairy products are discussed.•Main analytical techniques used in the authentication of milk and dairy products.•Perspectives in authenticity analysis in milk and dairy products are provided.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
The geographical origin of black tea can affect commercial value and is highly susceptible to food fraud. In this study, nuclear magnetic resonance (NMR) spectroscopy was used for untargeted ...metabolomics analysis of 219 black tea samples from seven major black tea producing regions in China (Anhui, Yunnan, Fujian, and Guangdong), India (Darjeeling and Assam) and Sri Lanka (Kandy). Black tea from different geographical origins can be distinguished according to the variety and processing, among which caffeine and alanine were identified as the main differential metabolites of the variety, theaflavin 3, 3′-digallate and succinic acid were identified as the main differential metabolites of the processing. Several machine learning algorithms were used to identify the origin of black tea, and the test set accuracy results showed that the nonlinear model random forest (92.7%) and support vector machine (91.8%) algorithms were better than the linear model linear discriminant analysis (86.3%) and K-nearest neighbor (86.3%). The random forest model screened 14 black tea geographical origin marker metabolites, such as caffeine, malic acid, lysine and β-glucose, and based on these marker metabolites, the chemical fingerprint pattern of origin was drawn. Black tea origin marker metabolites proved that variety contributed more to the origin metabolite fingerprint than processing. The results support that 1H NMR metabolomics combined with machine learning can be used as an effective tool for the construction of black tea chemical fingerprints for quality assessment and fraud detection.
•219 black tea samples were analyzed by 1H NMR and 42 metabolites were identified.•Machine learning models (LDA, KNN, SVM, RF) were used for origin identification.•The discriminant rate of the random forest model for tea from 7 origins was 92.7%.•Caffeine, malic acid, lysine, and β-glucose identified as major chemical markers of origin.•Chemical fingerprinting of black tea varieties, processing, and origin was established.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
The traceability of mineral element fingerprints to mutton in a small area of China was studied. The element data of 104 sheep and 24 goat samples from Inner Mongolia were measured, and the data were ...analyzed by multivariate statistical analysis from different origins, species and feeding patterns. The results shows that 11 elements (Mg, Al, K, Ca, Mn, Fe, Cu, Zn, Rb, Sr, Ba) in sheep meat had significant differences between different regions (P < 0.05), and the results of linear discriminant analysis (LDA) showed that the accuracy of the original classification rate was 95.2%, and the cross-validation rate was 85.9%. Goat meat and sheep meat samples from Alxa League were also clearly identified with LDA results showing that the cross-validation accuracy of the two species was 70.2%. Then the feeding patterns of sheep meat were effectively classified. The results showed that the multi-element analysis has certain potential as a method to distinguish mutton in a small area.
•Mutton from different origins in Inner Mongolia of China were effectively identified.•It is feasible to trace the source of mutton in a small area by using elements.•Sheep meat in four regions was distinguished by elements.•Different feeding patterns of sheep were distinguished by elements.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Cocoa is a high-value commodity that appeals to the consumer's taste, but it is also renowned for its antioxidant and healthy properties. Many of these characteristics as well as flavour and its ...economic value depend on the geographic origin. This work reports the content of 56 macro-, micro- and trace-elements of 61 cocoa beans produced in 23 countries of East and West Africa, Asia and Central and South America using ICP-MS and tests the efficacy and robustness of a new chemometric approach of geographic traceability developed on the base of elemental profiles. The model based on the 29 elements (Ag, As, Ba, Be, Bi, Ca, Cd, Co, Cr, Cs, Cu, Fe, Ga, Hg, K, Li, Mg, Mn, Na, Ni, P, Rb, Se, Sr, Th, Tl, U, Y and Zn) indicated as the more predictive by the Discriminant Analysis provided an optimal discrimination among the 5 subcontinental origins, achieving 100% of correct re-classification. The model was cross-validated with satisfactory results (>85% correct reclassification). Finally, interesting opportunities were pointed out by the satisfactory application of this model in tracing back the subcontinental origin of 13 commercial samples of dark chocolate (77% correct reclassification).
•The composition of 56 macro-, micro and trace elements in cocoa beans is reported.•A new statistical model to identify cocoa origin using elemental profiles is developed.•The model is cross-validated with satisfactory results.•The model could be applied also for commercial dark chocolates.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK, ZRSKP
The quality and safety of food is one of the most important issues in our life. In this work, four different sample preparation methods, i.e., rice powder pellet with boric acid (RPPBA), rice powder ...pellet (RPP), rice grain pellet (RGP) and rice grain (RG), were carried out to study the adulteration problem in food industry. 20 kinds of rice from different geographic origins were classified by laser-induced breakdown spectroscopy (LIBS) coupled with principal component analysis (PCA) and support vector machine (SVM). PCA was used to reduce the input variables of SVM, and the classification accuracies by PCA and SVM combination for the four sample preparation methods were 92.70%, 95.70%, 98.80%, and 99.20%, respectively. In addition, the sample preparation times were 15, 12, 10, and 1 min, respectively. These results show that RG was simpler and more efficient sample preparation method for distinguishing different geographical origin of agricultural products than the other preparing methods of RPPBA, RPP, and RG. Modeling efficiency of SVM could be improved by reducing its input variables using PCA. It can be concluded that the LIBS technique combined with chemometric method should be a promising tool to rapidly distinguish different rice geographic origins.
•Rice classification according to their geographical origins using LIBS combined with support vector machine (SVM) was carried out.•Rice grain preparing method was found to be more efficient than the other preparing methods of rice powder pellet with boric acid, rice powder pellet, and rice grain pellet.•Modeling efficiency of SVM could be improved by reducing its input variables using principal component analysis.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK, ZRSKP
