Geographical origin determination of the PDO hazelnut (cv. Giresun Tombul) by chemometric analysis of FT-NIR and Raman spectra acquired from shell and kernel.

Turkey is the leading producer of hazelnuts, contributing to 62% of the total global production. Among 18 distinct local hazelnut cultivars, Giresun Tombul is the only cultivar that has received Protected Designation of Origin denomination from the European Comission (EC). However, there is currently no practical objective method to ensure its geographic origin. Therefore, in this study NIR and Raman spectroscopy, along with chemometric methods, such as principal component analysis, PLS-DA (partial least squares-discriminant analysis), and SVM-C (support vector machine-classification), were used to determine the geographical origin of the Giresun Tombul hazelnut cultivar. For this purpose, samples from unique 118 orchards were collected from eight different regions in Turkey during the 2021 and 2022 growing seasons. NIR and Raman spectra were obtained from both the shell and kernel of each sample. The results indicated that hazelnut samples exhibited distinct grouping tendencies based on growing season regardless of the spectroscopic technique and sample type (shell or kernel). Spectral information obtained from hazelnut shells demonstrated higher discriminative power concerning geographical origin compared to that obtained from hazelnut kernels. The PLS-DA models utilizing FT-NIR (Fourier transform near-infrared) and Raman spectra for hazelnut shells achieved validation accuracies of 81.7% and 88.3%, respectively, while SVM-C models yielded accuracies of 90.9% and 86.3%. It was concluded that the lignocellulosic composition of hazelnut shells, indicative of their geographic origin, can be accurately assessed using FT-NIR and Raman spectroscopy, providing a nondestructive, rapid, and user-friendly method for identifying the geographical origin of Giresun Tombul hazelnuts. PRACTICAL APPLICATION: The proposed spectroscopic methods offer a rapid and nondestructive means for hazelnut value chain actors to verify the geographic origin of Giresun Tombul hazelnuts. This could definitely enhance consumer trust by ensuring product authenticity and potentially help in preventing fraud within the hazelnut market. In addition, these methods can also be used as a reference for future studies targeting the authentication of other shelled nuts.

Stable Isotope Ratio Analysis for the Geographic Origin Discrimination of Greek Beans "Gigantes-Elefantes" (Phaseolus coccineus L.).

Adulteration of high-value agricultural products is a critical issue worldwide for consumers and industries. Discrimination of the geographical origin can verify food authenticity by reducing risk and detecting adulteration. Between agricultural products, beans are a very important crop cultivated worldwide that provides food rich in iron and vitamins, especially for people in third-world countries. The aim of this study is the construction of a map of the locally characteristic isotopic fingerprint of giant beans, "Fasolia Gigantes-Elefantes PGI", a Protected Geographical Indication product cultivated in the region of Kastoria and Prespes, Western Macedonia, Greece, with the ultimate goal of the discrimination of beans from the two areas. In total, 160 samples were collected from different fields in the Prespes region and 120 samples from Kastoria during each cultivation period (2020-2021 and 2021-2022). The light element (C, N, and S) isotope ratios were measured using Isotope Ratio Mass Spectrometry (IRMS), and the results obtained were analyzed using chemometric techniques, including a one-way ANOVA and Binomial logistic regression. The mean values from the one-way ANOVA were δ15NAIR = 1.875‱, δ13CV-PDB = -25.483‱, and δ34SV-CDT = 4.779‱ for Kastoria and δ15NAIR = 1.654‱, δ13CV-PDB = -25.928‱, and δ34SV-CDT = -0.174‱ for Prespes, and showed that stable isotope ratios of C and S were statistically different for the areas studied while the Binomial logistic regression analysis that followed correctly classified more than 78% of the samples.

Using pollen DNA metabarcoding to trace the geographical and botanical origin of honey from Karangasem, Indonesia.

The unique floral fingerprint embedded within honey holds valuable clues to its geographical and botanical origin, playing a crucial role in ensuring authenticity and detecting adulteration. Honey from native Apis cerana and Heterotrigona itama bees in Karangasem, Indonesia, was examined utilizing pollen DNA metabarcoding for honey source identification. In this study, we used ITS2 amplicon sequencing to identify floral DNA in honey samples. The finding reveals distinct pollen signatures for each bee species. Results analysis showed A. cerana honey generated 179,267 sequence reads, assembled into Amplicon Sequence Variants (ASVs) with a total size of 485,932 bp and an average GC content of 59 %. H. itama honey generated 177,864 sequence reads, assembled into ASVs with a total size of 350,604 bp and an average GC content of 57 %. A. cerana honey exhibited a rich tapestry of pollen from eleven diverse genera, with Schleichera genus dominating at an impressive relative read abundance of 72.8 %. In contrast, H. itama honey displayed a remarkable mono-dominance of the Syzygium genus, accounting for a staggering 99.95 % of its pollen composition or relative read abundance, highlighting their distinct foraging preferences and floral resource utilization. Notably, all identified pollen taxa were indigenous to Karangasem, solidifying the geographical link between honey and its origin. This study demonstrates pollen DNA metabarcoding may identify honey floral sources. By using pollen profiles from different bee species and their foraging patterns, we may protect consumers against honey adulteration and promote sustainable beekeeping in Karangasem district. Future research could explore expanding the database of reference pollen sequences and investigating the influence of environmental factors on pollen composition in honey. Investigating this technology's economic and social effects on beekeepers and consumers may help promote fair trade and sustainable beekeeping worldwide.

Identifying the origin of Yemeni green coffee beans using near infrared spectroscopy: a promising tool for traceability and sustainability.

Yemeni smallholder coffee farmers face several challenges, including the ongoing civil conflict, limited rainfall levels for irrigation, and a lack of post-harvest processing infrastructure. Decades of political instability have affected the quality, accessibility, and reputation of Yemeni coffee beans. Despite these challenges, Yemeni coffee is highly valued for its unique flavor profile and is considered one of the most valuable coffees in the world. Due to its exclusive nature and perceived value, it is also a prime target for food fraud and adulteration. This is the first study to identify the potential of Near Infrared Spectroscopy and chemometrics-more specifically, the discriminant analysis (PCA-LDA)-as a promising, fast, and cost-effective tool for the traceability of Yemeni coffee and sustainability of the Yemeni coffee sector. The NIR spectral signatures of whole green coffee beans from Yemeni regions (n = 124; Al Mahwit, Dhamar, Ibb, Sa'dah, and Sana'a) and other origins (n = 97) were discriminated with accuracy, sensitivity, and specificity ≥ 98% using PCA-LDA models. These results show that the chemical composition of green coffee and other factors captured on the spectral signatures can influence the discrimination of the geographical origin, a crucial component of coffee valuation in the international markets.

Appearance quality, nutritional value, and aroma components of wild diguo (Ficus tikoua Bur.) fruit collected from southwest China.

Diguo (Ficus tikoua Bur.), an ancient wild fruit, is widely spread in southwest China. However, there is little information on the phenotypic traits, quality characteristics, and aroma compounds available to diguo fruit. The present study is an investigation into the effects of geographical origin on the phenotypic traits and quality characteristics of wild diguo fruit collected from southwest China. The volatile compounds in the mixed fruit samples were also investigated using gas chromatography-mass spectrometry. Our results indicated that significant variation existed among the sampling materials in all the phenotypic parameters. Fruit fresh weight ranged between 2.06 and 4.59 g. Moreover, significant variation existed among the selected materials in all macronutrients (dry matter, total soluble solids, crude protein, crude fat, and ash) and some nutritional parameters (glutamate, arginine, total soluble solids, maltose, and mannose, etc.). Regardless of their geographical origin, diguo fruit is relatively low in fat and fructose and high in fiber and glutamate. A total of 95 volatile constituents were identified in the frozen diguo fruit. In conclusion, diguo fruit with rich nutritional attributes has a promising future for commercial-scale production. The variability of the observed morphological and nutritional features of diguo fruit provides important characteristics for improving the breeding of diguo as a modern fruit crop.

[Taking origins into account in medical reasoning in infectious and tropical diseases? A critical look]. / Tenir compte des origines dans le raisonnement médical en maladies infectieuses et tropicales ? Un regard critique.

Healthcare discriminations based on one's ethnic background is increasingly being studied in medicine. The scale of the Covid-19 pandemic has played an important role in bringing them to light. Data, although scarce, exist in France. These discriminations have an impact on the care pathway and contribute to the renunciation of care by the most affected populations. The issue of discrimination is particularly relevant in infectious diseases. Although the epidemiology of infectious diseases is unevenly distributed worldwide, erroneous social representations are prevalent and expose to a harmful prejudice against migrants with regard to infectious diseases. The transmissible nature of some infectious diseases reinforces their stigmatizing potential. In this context, it seems important to discuss the dimension to be given to social determinants, geographical origin, phenotype, and ethnicity in teaching and medical reasoning. The English-speaking world uses the concept of "race" in a structural way, whereas this "international standard" has not been applied in France until now. To improve the care of people from minority groups, it seems important to better document and teach a more nuanced clinical reasoning based on origin, without neglecting the importance of collecting and taking into account social determinants of health and environmental factors.

Geographical origin identification of Khao Dawk Mali 105 rice using combination of FT-NIR spectroscopy and machine learning algorithms.

The mislabelled Khao Dawk Mali 105 rice coming from other geographical region outside the Thung Kula Rong Hai region is extremely profitable and difficult to detect; to prevent retail fraud (that adversely affects both the food industry and consumers), it is vital to identify geographical origin. Near infrared spectroscopy can be used to detect the specific content of organic moieties in agricultural and food products. The present study implemented the combinatorial method of FT-NIR spectroscopy with chemometrics to identify geographical origin of Khao Dawk Mali 105 rice. Rice samples were collected from 2 different region including the north and northeast of Thailand. NIR spectra data were collected in range of 12,500 - 4,000 cm-1 (800-2,500 nm). Five machine learning algorithms including linear discriminant analysis (LDA), partial least squares discriminant analysis (PLS-DA), C-support vector classification (C-SVC), backpropagation neural networks (BPNN), hybrid principal component analysis-neural network (PC-NN) and K-nearest neighbors (KNN) were employed to classify NIR data of rice samples with full wavelength and selected wavelength by Extremely Randomized Trees (Extra trees) algorithm. Based on the findings, geographical origin of rice could be specified quickly, cheaply, and reliably using combination of NIRS and machine learning. All models creating by full wavelength and selected wavelength exhibited accuracy between 65 and 100 % for identifying geographical region of rice. It was proven that NIR spectroscopy may be used for the quick and non-destructive identification of geographical origin of Khao Dawk Mali 105 rice.

Identifying the geographical origin and processing technology of Moyao () on the basis of near-infrared spectroscopy combined with chemometrics.

OBJECTIVE: To evaluate the quality of Moyao (Myrrh) in the identification of the geographical origin and processing of the products. METHODS: Raw Moyao (Myrrh) and two kinds of Moyao (Myrrh) processed with vinegar from three countries were identified using near-infrared (NIR) spectroscopy combined with chemometric techniques. Principal component analysis (PCA) was used to reduce the dimensionality of the data and visualize the clustering of samples from different categories. A classical chemometric algorithm (PLS-DA) and two machine learning algorithms [K-nearest neighbor (KNN) and support vector machine] were used to conduct a classification analysis of the near-infrared spectra of the Moyao (Myrrh) samples, and their discriminative performance was evaluated. RESULTS: Based on the accuracy, precision, recall rate, and F1 value in each model, the results showed that the classical chemometric algorithm and the machine learning algorithm obtained positive results. In all of the chemometric analyses, the NIR spectrum of Moyao (Myrrh) preprocessed by standard normal variation or Multivariate scattering correction combined with KNN achieved the highest accuracy in identifying the geographical origins, and the accuracy of identifying the processing technology established by the KNN method after first-order derivative pretreatment was the best. The best accuracy of geographical origin discrimination and processing technology discrimination were 0.9853 and 0.9706 respectively. CONCLUSIONS: NIR spectroscopy combined with chemometric technology can be an important tool for tracking the origin and processing technology of Moyao (Myrrh) and can also provide a reference for evaluations of its quality and the clinical use.

Geographical identification of Chinese wine based on chemometrics combined with mineral elements, volatile components and untargeted metabonomics.

Identifying the geographic origin of a wine is of great importance, as origin fakery is commonplace in the wine industry. This study analyzed the mineral elements, volatile components, and metabolites in wine using inductively coupled plasma-mass spectrometry, headspace solid phase microextraction gas chromatography-mass spectrometry, and ultra-high-performance liquid chromatography-quadrupole-exactive orbitrap mass spectrometry. The most critical variables (5 mineral elements, 13 volatile components, and 51 metabolites) for wine origin classification were selected via principal component analysis and orthogonal partial least squares discriminant analysis. Subsequently, three algorithms-K-nearest neighbors, support vector machine, and random forest -were used to model single and fused datasets for origin identification. These results indicated that fused datasets, based on feature variables (mineral elements, volatile components, and metabolites), achieved the best performance, with predictive rates of 100% for all three algorithms. This study demonstrates the effectiveness of a multi-source data fusion strategy for authenticity identification of Chinese wine.

Metabolomics analysis based on UHPLC-QqQ-MS/MS to discriminate grapes and wines from different geographical origins and climatological characteristics.

With the proliferation of the consumer's awareness of wine provenance, wines with unique origin characteristics are increasingly in demand. This study aimed to investigate the influence of geographical origins and climatological characteristics on grapes and wines. A total of 94 anthocyanins and 78 non-anthocyanin phenolic compounds in grapes and wines from five Chinese viticultural vineyards (CJ, WH, QTX, WW, and XY) were identified by UHPLC-QqQ-MS/MS. Chemometric methods PCA and OPLS-DA were established to select candidate differential metabolites, including flavonols, stilbenes, hydroxycinnamic acids, peonidin derivatives, and malvidin derivatives. CCA showed that malvidin-3-O-glucoside had a positive correlation with mean temperature, and quercetin-3-O-glucoside had a negative correlation with precipitation. In addition, enrichment analysis elucidated that the metabolic diversity in different origins mainly occurred in flavonoid biosynthesis. This study would provide some new insights to understand the effect of geographical origins and climatological characteristics on phenolic compounds in grapes and wines.

Effect of seed's geographical origin on cactus oil physico-chemical characteristics, oxidative stability, and antioxidant activity.

The aim of this study was the valorisation of cactus (or prickly pear, Opuntia ficus-indica) seeds growing in six different regions of Morocco. Moisture, proteins, lipids profile, total polyphenols content, oxidative stability, and antioxidant activity were investigated. The Folin-Ciocalteu test highlighted the abundant presence of phenolic compounds (165 to 225 mg EAG/100 g of extract) and a significant antioxidant capacity against DPPH free radicals. The seeds contained protein (7-9.25%) and lipids (2.7-5%). Cactus oil quality indices such as acidity and peroxide value were below 1.2% and 10 mEq.O2/kg, respectively. GC analysis revealed that linoleic and oleic acid percentages ranged from 57.1 to 63.8%, and 13.5 to 18.7%, respectively. Cactus seed oil was rich in tocopherols (500-680 mg/kg) and phytosterols (8000-11,100 mg/kg) with a predominance of γ-tocopherols and ß-sitosterol. Triacylglycerols, fatty acids and sterols composition showed small variation depending on the geographical origin, while the individual tocopherol profile was significantly influenced.

Geographical authentication of saffron by chemometrics applied to the ion mobility spectrometry data.

There is a lack of a reliable tool for quickly determining the geographical origins of saffron (SFR). Ion mobility spectrometry (IMS) has emerged as a promising method for rapid authentication. In this study, 232 Iranian SFR samples harvested in five distinct areas (Khorasan, Azerbaijan, Golestan, Fars, and Isfahan) were analyzed by IMS coupled with chemometric methods. The principal component analysis (PCA) was applied for analyzing the collected IMS data, utilizing three principle components (PCs) that accounted for 81 % of the explained variance. Moreover, the partial least squares-discriminant analysis (PLS-DA) demonstrated the average sensitivity and specificity rates, of 72.3 % to 92.5 % for the exernal test set and 75.5 % to 94.3 % for training set. The accuracy values were ≥ 85.0 % for the prediction set for all classes of samples. The results of this study revealed a successful application of IMS and chemometric methods for rapid geographical authentication of saffron samples in Iran.

Profiling of Metabolites in Organically Grown Plums from Norway: Does Location or Cultivar Matter?

The aim of this work was to investigate the influence of two locations and seven cultivars on the profiling of metabolites in organically grown plums (Prunus domestica L.) fruit in Norway. P, K, and Ca were most abundant in the studied fruits, while Ba and Sr formed a clear line between the locations. The most abundant sugars were glucose, fructose, sucrose, and sorbitol, which together accounted for up to 97.00%. Quinic acid and malic acid were the predominant organic acids, while chlorogenic acid, rutin, and kaempferol-3-O-glucoside were the most abundant polyphenols. Plums from Ullensvang were characterized by a higher content of minerals, sugars, organic acids, total polyphenol content (TPC), and radical scavenging activity (RSA), while plums from Telemark had a higher content of quantified polyphenols. The cultivar 'Mallard' had the highest mineral and radical scavenging activity, 'Opal' had the sweetest fruit, 'Jubileum' had the highest acidity, 'Excalibur' had the highest TPC content, and 'Valor' stored the highest content of quantified polyphenols, especially chlorogenic acid. These results provide comprehensive information on the chemical profiles of selected plum cultivars, suggesting that organic plums are a rich source of beneficial compounds that can have a positive impact on human health.

The Influence of the Soil Profile on the Formation of the Elemental Image of Grapes and Wine of the Cabernet Sauvignon Variety.

The features for assessing the authenticity of wines by region of origin are studied, based on the relationship between the mineral composition of the wine, the grapes, and the soil profile (0 to 160 cm) from the place of growth of Cabernet Sauvignon grapes. Soil, grape, and wine samples were taken from the territories of six vineyards in the Anapa district of Krasnodar Territory, Russia. Using the methods of ICP-OES, thermal, and X-ray phase analysis, the soils were differentiated into three groups, differing in mineralogical and mineral compositions. The soil samples of the first group contained up to 31% quartz, the second group up to 25% quartz and 19% mixed calcite, and the third group up to 32% calcite and 15% quartz. The formation of the elemental image of the grapes was studied, taking into account the total content and mobile forms of metals in the soil. The territorial proximity of the vineyards did not affect the extraction of elements from the soil into the grape berry, and the migration of metals for each territory was selective. According to the values of the biological absorption coefficient, the degree of transition of metals from the soil to a berry was estimated. For K, Ti, Zn, Rb, Cu, and Fe in all berries, the coefficient was higher than 1.00, which means that the berry extracts contained not only mobile-form, but also difficult-to-dissolve metal compounds. The migration of macro-components from the soil to the berry was low, and amounted to 6-7% for Ca, 0.8-3.0% for Na, and 25-70% for Mg of the concentration of their mobile forms. For all territories, the maximum correlation between metal concentrations in grapes and soil was observed for samples from a depth of 0-40 cm. The discriminant model based on concentrations of Rb, Al, K, Sr, Co, Na, Pb, Ca, and Ni showed the formation of clusters in the territories of vineyard cultivation. The developed model allow the problems of identifying wines by region to be solved with high accuracy, using their elemental image.

Explainable machine learning for predicting the geographical origin of Chinese Oysters via mineral elements analysis.

The traceability of geographic origin is essential for guaranteeing the quality, safety, and protection of oyster brands. However, the current outcomes of traceability lack credibility as they do not adequately explain the model's predictions. Consequently, we conducted a study to evaluate the efficacy of utilizing explainable machine learning combined with mineral elements analysis. The study findings revealed that 18 elements have the ability to determine regional orientation. Simultaneously, individuals should pay closer attention to the potential risks associated with oyster consumption due to the regional differences in essential and toxic elements they contain. Light gradient boosting machine (LightGBM) model exhibited indistinguishable performance, achieving flawless accuracy, precision, recall, F1 score and AUC, with values of 96.77%, 96.43%, 98.53%, 97.32% and 0.998, respectively. The SHapley Additive exPlanations (SHAP) method was used to evaluate the output of the LightGBM model, revealing differences in feature interactions among oysters from different provinces. Specifically, the features Na, Zn, V, Mg, and K were found to have a significant impact on the predictive process of the model. Consistent with existing research, the use of explainable machine learning techniques can provide insights into the complex connections between important product attributes and relevant geographical information.

Impact of floral and geographical origins on honey quality parameters in Saudi Arabian regions.

This article examined the effect of geographical (different climate conditions) and floral origins on some quality parameters of honey including the activity of diastase enzyme. Moreover, some non-quality parameters were investigated such as the pH, fructose, glucose, ratio of fructose/glucose and invertase. The honey samples were collected from Asir (cold climate) and Jazan (hot climate) regions at the southwestern part of Saudi Arabia. The geographical origin significantly affected the mean value moisture of the Acacia honey (p-value = 0.02), conductivity of the polyfloral honey (p-value = 0.03), sucrose of the Acacia honey (p-value = 0.02), diastase activity of the Acacia (p-value = 0.001), Ziziphus (p-value = 0.046) and polyfloral honey (p-value ≤ 0.001), fructose of the Acacia honey (p-value = 0.01), glucose of the Ziziphus honey (p-value = 0.03), fructose/ glucose ratio of the Ziziphus honey (p-value = 0.035), and invertase activity of the polyfloral honey (p-value ≤ 0.001). Regarding the effect of the floral origin of the honey from Asir region, the sucrose percentage of the Acacia honey was significantly more than that of the polyfloral honey (p- value = 0.003), the diastase activity of the Acacia honey was significantly more than its activity in the Ziziphus honey (p- value = 0.044), glucose percentage of the Ziziphus honey was significantly more the glucose percentage of the Acacia honey (p-value = 0.009) and the fructose/ glucose ratio of the Ziziphus honey was significantly more than that of the Acacia and polyforal honeys (p-value = 0.011 and p-value = 0.045, respectively). Concerning the significant effects of the floral origin on the quality parameters of the honey samples from Jazan region, the moisture of the Ziziphus honey was significantly increased when compared to the moisture of the Acacia honey (p-value = 0.038), the acidity of the polfloral honey was significantly more than the acidity of the Acacia honey (p-value = 0.049), the sum of fructose and glucose of the polyfloral honey was significantly increased compared to that of the Acacia honey (p-value = 0.015), the pH of the Ziziphus hiney was significantly more than the pH of the polyfloral honey (0.011) and the fructose of the polfloral honey was significantly more than that of the Acacia honey (p-value = 0.031). The effect of the geographical origin of the honey samples on their quality parameters depends on their floral origin and the effect of their floral origin differs according to their geographical origin. This article suggests considering collectively the geographical and floral origins effect when developing honey standards. However, the Codex standards for honey started considering this issue when it changed the standard concentration of HMF in honey from not more than 80-40 mg/Kg for honeys from cold climate and 80 mg/Kg for honeys from hot climates.

Authentication of selected white wines by geographical origin using ICP spectrometric and chemometric analysis.

An important aspect of assessing the authenticity of wines is its geographical origin. The aim of the work is to authenticate by geographical origin according to the data of the ICP-spectrometric and chemometric analysis of elemental "images" of wines produced from white grape varieties Chardonnay, Riesling and Muscat grown in four regions of the Krasnodar Territory, Russia. The difference in the contents of Al, Ba, Ca and Rb in wines was found depending on the variety, and Al, Ba, Rb, Fe, Li, Sr - depending on the region of grape growth. Different models of the experimental data processing were used for attribution of the produced varieties of wine to the area of the grape's growth. The criterion for the quality of the constructed models was the accuracy of the attribution of a wine variety to the area of the grape's growth (%). Analysis of the elemental analysis data of 153 wine samples showed that in terms of attribution accuracy, automated neural networks (100 %) are preferred among machine learning methods, followed by support vector machines (98.69 %) and general discriminant analysis (94.77 %). The applied mathematical models enabled the revealing of the cluster structure of the analyzed wine varieties and their attribution to the area of a grape growth with high accuracy. Sr, Li and Fe concentrations in wines were found as the dominating predictors in the constructed models for definition of the geographical origin of wines. The combination of ICP-spectrometric analysis data with the capabilities of statistical modeling of machine learning methods focused on large-dimensional data made it possible to successfully solve small-dimensional problems of the definition of the geographical origin of wines by their elemental composition and variety.

Revealing quality chemicals of Tetrastigma hemsleyanum roots in different geographical origins using untargeted metabolomics and random-forest based spectrum-effect analysis.

Tetrastigma hemsleyanum root is a popular functional food in China, and the price varies based on the origin of the product. The link between the origin, metabolic profile, and bioactivity of T. hemsleyanum must be investigated. This study compares the metabolic profiles of 254 samples collected from eight different areas with 49 potential key chemical markers using plant metabolomics. The metabolic pathways of the five critical flavonoid metabolites were annotated and enriched using the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway. Moreover, a random forest model aiding the spectrum-effect relationship analysis was developed for the first time indicating catechin and darendoside B as potential quality markers of antioxidant activity. The findings of this study provide a comprehensive understanding of the chemical composition and bioactive compounds of T. hemsleyanum as well as valuable information on the evaluation of the quality of various samples and products in the market.

Metabolomics applications for plant-based foods origin tracing, cultivars identification and processing: Feasibility and future aspects.

Metabolomics, the systematic study of metabolites, is dedicated to a comprehensive analysis of all aspects of plant-based food research and plays a pivotal role in the nutritional composition and quality control of plant-based foods. The diverse chemical compositions of plant-based foods lead to variations in sensory characteristics and nutritional value. This review explores the application of the metabolomics method to plant-based food origin tracing, cultivar identification, and processing methods. It also addresses the challenges encountered and outlines future directions. Typically, when combined with other omics or techniques, synergistic and complementary information is uncovered, enhancing the classification and prediction capabilities of models. Future research should aim to evaluate all factors affecting food quality comprehensively, and this necessitates advanced research into influence mechanisms, metabolic pathways, and gene expression.

Geographical traceability of flavor compounds in Chinese mitten crab (Eriocheir sinensis): Implications for quality differentiation, authenticity assessment, and mechanism research.

Geographical traceability plays a crucial role in ensuring quality assurance, brand establishment, and the sustainable development of the crab industry. In this study, we examined the possibility of using gas chromatography-ion mobility spectrometry with multivariate statistical authenticity analysis to identify the origin of crabs from five sites downstream of the Yangtze River. Significant variations were observed in the levels of alcoholic flavor compounds in the hepatopancreas and muscles of crabs from different geographical locations, and a support vector machine exhibited discriminant ability with 100% accuracy. These flavor variations exhibited significant correlations with the types and concentrations of elements within the crabs, as well as with free amino acids. This study offers a practical approach for determining the geographical traceability of Chinese mitten crabs and elucidates the role of elements in flavor modulation, thereby providing innovative strategies to enhance the efficiency of crab farming.