Metabolic and elemental profiling as potential discriminating features among the black mahlab seeds (Monechma ciliatum) grown in three different regions.

INTRODUCTION: Black mahlab (Monechma ciliatum) seed is a rich source of metabolites and minerals and is usually believed to have a similar composition between different areas of cultivation. Until now, no studies have assessed changes in black mahlab seeds (BMSs) to determine those constituents that help to discriminate them according to geographical origin. OBJECTIVES: The present study attempted to compare the metabolomics and elemental profiles of BMSs of different geographical origins and identified the potential markers using ultrahigh-performance liquid chromatography quadrupole Orbitrap tandem mass spectrometry (UHPLC-Q-Orbitrap-MS2), and inductively coupled plasma mass spectrometry (ICP-MS) techniques and established the chemometric model to identify the potential markers and discriminate them according to cultivation sites. MATERIAL AND METHODS: In this work, data from metabolites analysis by UHPLC-Q-Orbitrap-MS2 and multi-elemental data obtained from ICP-MS were combined with chemometrics for tracing the geographical origin of BMSs. Principal component analysis (PCA) was used to evaluate the overall grouping of samples. In contrast, partial least squares-discriminant analysis (PLS-DA) and orthogonal partial least squares discriminant analysis (OPLS-DA) were employed for authentication. RESULTS: PLS-DA and OPLS-DA models were fully validated (R2Y and Q2 values > 0.5). Variable importance of various projections was applied to obtain valuable data about differential elements (seven markers were identified) and metabolites (23 markers were identified) with high discrimination potential. The outcomes presented in this study serve as an appropriate framework for developing novel discrimination approaches in food origin screening.

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.

Phenolic Profiles in Olive Leaves from Different Cultivars in Tuscany and Their Use as a Marker of Varietal and Geographical Origin on a Small Scale.

Olive leaves are a rich source of polyphenols with healthful properties and represent one of the most abundant waste products of olive oil production. The aims of this study were to explore the phenolic composition of olive leaves from the three main Tuscan cultivars (Leccino, Moraiolo and Frantoio) collected in Siena and Grosseto provinces and to investigate the possible use of these compounds as varietal and geographic origin markers. Discriminant factorial analysis (DFA) was used for distinguishing between different cultivars and locations. Apigenin and caffeoyl-secologanoside showed significant differences between cultivars. DFA showed that ligstroside, apigenin and luteolin have the most influence in determining the differences between sites, whereas total polyphenols, olacein and hydroxytyrosol acetate allowed for separation between leaves from the same province. The results of the present study indicate that concentrations of phenolic compounds, measured through high-resolution mass spectrometry, can be used as a marker for both the cultivar and of geographical origin of olive leaves, and possibly of olive-related products, as well as across small geographic scales (less than 50 km distance between sites).

Wheat authentication：An overview on different techniques and chemometric methods.

Wheat (Triticum aestivum L.) is one of the most important cereal crops and is consumed as a staple food around the globe. Wheat authentication has become a crucial issue over the last decades. Recently, many techniques have been applied in wheat authentication including the authentication of wheat geographical origin, wheat variety, organic wheat, and wheat flour from other cereals. This paper collected related literature in the last ten years, and attempted to highlight the recent studies on the discrimination and authentication of wheat using different determination techniques and chemometric methods. The stable isotope analysis and elemental profile of wheat are promising tools to obtain information regarding the origin, and variety, and to differentiate organic from conventional farming of wheat. Image analysis, genetic parameters, and omics analysis can provide solutions for wheat variety, organic wheat, and wheat adulteration. Vibrational spectroscopy analyses, such as NIR, FTIR, and HIS, in combination with multivariate data analysis methods, such as PCA, LDA, and PLS-DA, show great potential in wheat authenticity and offer many advantages such as user-friendly, cost-effective, time-saving, and environment friendly. In conclusion, analytical techniques combining with appropriate multivariate analysis are very effective to discriminate geographical origin, cultivar classification, and adulterant detection of wheat.

A review of conventional and rapid analytical techniques coupled with multivariate analysis for origin traceability of soybean.

Soybean has developed a reputation as a superfood due to its nutrient profile, health benefits, and versatility. Since 1960, its demand has increased dramatically, going from a mere 17 MMT to almost 358 MMT in the production year 2021/22. These extremely high production rates have led to lower-than-expected product quality, adulteration, illegal trade, deforestation, and other concerns. This necessitates the development of an effective technology to confirm soybean's provenance. This is the first review that investigates current analytical techniques coupled with multivariate analysis for origin traceability of soybeans. The fundamentals of several analytical techniques are presented, assessed, compared, and discussed in terms of their operating specifics, advantages, and shortcomings. Additionally, significance of multivariate analysis in analyzing complex data has also been discussed.

Current strategies to guarantee the authenticity of coffee.

As they become more health conscious, consumers are paying increasing attention to food quality and safety. In coffee production, fraudulent strategies to reduce costs and maximize profits include mixing beans from two species of different economic value, the addition of other substances and/or foods, and mislabeling. Therefore, testing for coffee authenticity and detecting adulterants is required for value assessment and consumer protection. Here we provide an overview of the chromatography, spectroscopy, and single-nucleotide polymorphism-based methods used to distinguish between the major coffee species Arabica and Robusta. This review also describes the techniques applied to trace the geographical origin of coffee, based mainly on the chemical composition of the beans, an approach that can discriminate between coffee-growing regions on a continental or more local level. Finally, the analytical techniques used to detect coffee adulteration with other foods and/or coffee by-products are discussed, with a look at the practice of adding pharmacologically active compounds to coffee, and their harmful effects on health.

Elemental Profile of Propolis from Different Areas of Serbia.

Propolis is a resinous natural substance collected by honeybees from different plant sources. The element content of propolis is influenced by the content of elements in the soil, climatic factors, and the degree of pollution. The aim of the study was to characterize element composition and content of toxic elements in 51 propolis collected from different locations in Serbia and to evaluate the differences among them. Determination of the 21 elements were performed using Inductively coupled plasma - optical emission spectrometry. K was the most abundant element, followed by Ca, Mg, Si, Fe, Zn, and Al. The microelements B, Ba, Mn, Na, Pb, and Ti were also present in propolis, while Co, Cr, Cu, Mo, Ni, Sr, and V were found in trace. Toxic elements such as Pb, As, and Cd were found in the trace. Kruskal-Wallis tests differentiate groups of samples by geographical origin. The presence of B, Fe, Sr, Ti, Zn, and As demonstrated statistical significance between six regions of Serbia.

Green Chemometric-Assisted Characterization of Common and Black Varieties of Celery.

Celery (Apium graveolens L., var. Dulce), is a biennial herbaceous plant belonging to the Apiaceae family, cultivated in humid soils in the Mediterranean basin, in Central-Southern Europe, and in Asia. Despite its wide diffusion and although it is well-known that cultivar/origin strongly influences plant composition, only a few studies have been carried out on the different types of celery. The present work aims to investigate four different Italian types of celery (two common, Elne and Magnum celery, and two black, Torricella Peligna Black and Trevi Black celery), and to test, whether the combination of FT-IR spectroscopy and chemometrics allows their ecotype discrimination. The peculiarity of this study lies in the fact that all the analyzed celeries were grown in the same experimental field under the same soil and climate conditions. Consequently, the differences captured by the FT-IR-based tool are mainly imputable to the different ecotypes. In order to achieve this goal, FT-IR profiles were handled by two diverse classifiers: sequential preprocessing through ORThogonalization (SPORT) and soft independent modeling by class analogy (SIMCA). Eventually, the highest classification rate (90%, on an external set of 100 samples) has been achieved by SPORT.

Can Rare Earth Elements Be Considered as Markers of the Varietal and Geographical Origin of Wines?

The possibility of establishing the varietal and territorial affiliation of wines by the content of rare earth elements (REE) in them was studied. ICP-OES and ICP-MS with subsequent chemometric processing of the results were applied to determine the elemental image of soils containing negligible REE amounts, grapes grown on these soils, and wine materials of Cabernet Sauvignon, Merlot, and Moldova varieties produced from these grapes. To stabilize and clarify wine materials, the traditional processing of wine materials with various types of bentonite clays (BT) was used, which turned out to be a source of REE in the wine material. Discriminant analysis revealed that the processed wine materials were homogeneous within one denomination and that those of different denominations were heterogeneous with respect to the content of REE. It was found that REE in wine materials were transferred from BT during the processing, and thus they can poorly characterize the geographical origin and varietal affiliation of wines. Analysis of these wine materials according to the intrinsic concentrations of macro- and microelements showed that they formed clusters according to their varietal affiliation. In terms of their influence on the varietal image of wine materials, REE are significantly inferior to macro- and microelements, but they enhance their influence to a certain extent when used together.

Comparative Analysis of Polyphenols in Lycium barbarum Fruits Using UPLC-IM-QTOF-MS.

Variety, geographical origin, and harvest season are important factors affecting the accumulation of polyphenols in Lycium barbarum. In this study, the effects of these factors on the polyphenolic components of this species were analyzed using ultra-performance liquid chromatography ion mobility quadrupole time-of-flight mass spectrometry. Moreover, the in vitro antioxidant activities of fruit extracts from this species were evaluated. The total polyphenolic contents of L. barbarum fruits from Jinghe County in Xinjiang and Zhongning County in Ningxia were 5.52-11.72 and 7.06-9.37 mg (gallic acid equivalent)/g dry weight, while the total flavonoid contents of L. barbarum fruits from these regions were 12.52-30.29 and 12.67-20.77 mg (rutin equivalent)/g dry weight, respectively. Overall, 39 types of polyphenols were identified in the fruit extracts, including 26 flavonoids, 10 phenolic acids, and three tannins. Of these, 11 polyphenols were quantitatively analyzed, which revealed rutin to be the most dominant polyphenolic component in fruits from Jinghe and Zhongning. There were significant differences (p < 0.05) in the polyphenolic contents and antioxidant activities of L. barbarum fruit extracts, depending on the geographical origin, variety, and harvest season. The antioxidant activity of this species was found to be significantly positively correlated with the polyphenolic contents. This study provided scientific guidance for comprehensive applications of polyphenols from different varieties of L. barbarum from separate geographical origins.

Characterization of Beef Coming from Different European Countries through Stable Isotope (H, C, N, and S) Ratio Analysis.

The need to guarantee the geographical origin of food samples has become imperative in recent years due to the increasing amount of food fraud. Stable isotope ratio analysis permits the characterization and origin control of foodstuffs, thanks to its capability to discriminate between products having different geographical origins and derived from different production systems. The Framework 6 EU-project "TRACE" generated hydrogen (2H/1H), carbon (13C/12C), nitrogen (15N/14N), and sulphur (34S/32S) isotope ratio data from 227 authentic beef samples. These samples were collected from a total of 13 sites in eight countries. The stable isotope analysis was completed by combining IRMS with a thermal conversion elemental analyzer (TC/EA) for the analysis of δ(2H) and an elemental analyzer (EA) for the determination of δ(13C), δ(15N), and δ(34S). The results show the potential of this technique to detect clustering of samples due to specific environmental conditions in the areas where the beef cattle were reared. Stable isotope measurements highlighted statistical differences between coastal and inland regions, production sites at different latitudes, regions with different geology, and different farming systems related to the diet the animals were consuming (primarily C3- or C4-based or a mixed one).

Differentiation of Medicinal Plants According to Solvents, Processing, Origin, and Season by Means of Multivariate Analysis of Spectroscopic and Liquid Chromatography Data.

Effects of processing and extraction solvents on antioxidant properties and other characteristics were evaluated for ten medicinal plant species originating from two different localities and two production years. A combination of spectroscopic and liquid chromatography techniques possessed data for multivariate statistics. Water, 50% (v/v) ethanol, and dimethyl sulfoxide (DMSO) were compared to select the most suitable solvent for the isolation of functional components from the frozen/dried medicinal plants. DMSO and 50% (v/v) ethanol were evaluated as more efficient for phenolic compounds and colorants extraction, while water was more useful for element extraction. Drying and extraction of herbs with 50% (v/v) ethanol was the most appropriate treatment to ensure a high yield of most compounds. The satisfactory differentiation of herbs (61.8-100%) confirmed the significant effect of the processing, geographical, and seasonal factors on target functional component concentrations. Total phenolic and total flavonoid compounds content, total antioxidant activity expressed as TAA, yellowness, chroma, and browning index were identified as the most important markers for medicinal plant differentiation.

NMR-Based Metabolite Profiling and the Application of STOCSY toward the Quality and Authentication Assessment of European EVOOs.

Extra virgin olive oil (EVOO) possesses a high-value rank in the food industry, thus making it a common target for adulteration. Hence, several methods have been essentially made available over the years. However, the issue of authentication remains unresolved with national and food safety organizations globally struggling to regulate and control its market. Over the course of this study, the aim was to determine the origin of EVOOs suggesting a high-throughput, state-of-the-art method that could be easily adopted. A rapid, NMR-based untargeted metabolite profiling method was applied and complemented by multivariate analysis (MVA) and statistical total correlation spectroscopy (STOCSY). STOCSY is a valuable statistical tool contributing to the biomarker identification process and was employed for the first time in EVOO analysis. Market samples from three Mediterranean countries of Spain, Italy, and Greece, blended samples from these countries, as well as monocultivar samples from Greece were analyzed. The NMR spectra were collected, with the help of chemometrics acting as "fingerprints" leading to the discovery of certain chemical classes and single biomarkers that were related to the classification of the samples into groups based on their origin.

[Origin identification of Polygonatum cyrtonema based on hyperspectral data].

In this study, visual-near infrared(VNIR), short-wave infrared(SWIR), and VNIR + SWIR fusion hyperspectral data of Polygonatum cyrtonema from different geographical origins were collected and preprocessed by first derivative(FD), second derivative(SD), Savitzky-Golay smoothing(S-G), standard normalized variate(SNV), multiplicative scatter correction(MSC), FD+S-G, and SD+S-G. Three algorithms, namely random forest(RF), linear support vector classification(LinearSVC), and partial least squares discriminant analysis(PLS-DA), were used to establish the identification models of P. cyrtonema origin from three spatial scales, i.e., province, county, and township, respectively. Successive projection algorithm(SPA) and competitive adaptive reweighted sampling(CARS) were used to screen the characteristic bands, and the P. cyrtonema origin identification models were established according to the selected characteristic bands. The results showed that(1)after FD preprocessing of VNIR+SWIR fusion hyperspectral data, the accuracy of recognition models established using LinearSVC was the highest, reaching 99.97% and 99.82% in the province origin identification model, 100.00% and 99.46% in the county origin identification model, and 99.62% and 98.39% in the township origin identification model. The accuracy of province, county, and township origin identification models reached more than 98.00%.(2)Among the 26 characteristic bands selected by CARS, after FD pretreatment, the accuracy of origin identification models of different spatial scales was the highest using LinearSVC, reaching 98.59% and 97.05% in the province origin identification model, 97.79% and 94.75% in the county origin identification model, and 90.13% and 87.95% in the township origin identification model. The accuracy of identification models of different spatial scales established by 26 characteristic bands reached more than 87.00%. The results show that hyperspectral imaging technology can realize accurate identification of P. cyrtonema origin from different spatial scales.

Special Issue on the Pathobiology of Laboratory Nonhuman Primates: A Review of Species, Substrain, Geographical Origin, Age, and Modality-Related Factors.

Nonhuman primates (NHPs) are utilized in nonclinical safety testing due to their phylogenetic proximity to humans and similarity in physiology and anatomy. However, ethical considerations and the increased demand for NHPs, coupled with the current shortage in their supply, have increased the calls to minimize their use. In addition, the increased demand and supply shortage of NHPs have increased the use of animals sourced from different geographical origins, and animals of different ages, which can complicate the interpretation of study results. Coupled with the relative uniqueness of findings induced by novel therapeutic modalities, there is an increasing need for a deeper understanding of the systemic pathobiology of NHPs. Here we provide a brief preview of the two main themes discussed in this special issue, which include the influence of geographical origin, age, and sex on background pathology, clinical pathology reference values, other relevant toxicology endpoints, and organ system pathology.

The Influence of Geographical Origin, Age, Sex, and Animal Husbandry on the Spontaneous Histopathology of Laboratory Cynomolgus Macaques (Macaca Fascicularis): A Contemporary Global and Multisite Review of Historical Control Data.

To investigate the influence of geographical origin, age, and sex on toxicologically relevant spontaneous histopathology findings in cynomolgus macaques (Macaca fascicularis), we performed a comparative analysis of historical control data (HCD) from 13 test sites that included 3351 animals (1645 females and 1706 males) sourced from Mauritius, China, Vietnam, and Cambodia, aged from 2 to 9.5 years, and from 446 toxicology studies evaluated between 2016 and 2021. The most common findings were mononuclear infiltrates in the kidney, liver, brain, and lung, which showed highest incidences in Mauritian macaques, and heart, salivary glands, and gastrointestinal tract (GIT), which showed highest incidences of mononuclear infiltrates in mainland Asian macaques. Developmental and degenerative findings were more common in Mauritian macaques, while lymphoid hyperplasia and lung pigment showed higher incidences in Asian macaques. Various sex and age-related differences were also present. Despite origin-related differences, the similarities in the nature and distribution of background lesions indicate that macaques from all geographical regions are suitable for toxicity testing and show comparable lesion spectrum. However, in a toxicity study, it is strongly recommended to use animals from a single geographical origin and to follow published guidelines when using HCD to evaluate and interpretate commonly diagnosed spontaneous lesions.

Performance Optimization of a Developed Near-Infrared Spectrometer Using Calibration Transfer with a Variety of Transfer Samples for Geographical Origin Identification of Coffee Beans.

This research aimed to improve the classification performance of a developed near-infrared (NIR) spectrometer when applied to the geographical origin identification of coffee bean samples. The modification was based on the utilization of a collection of spectral databases from several different agricultural samples, including corn, red beans, mung beans, black beans, soybeans, green and roasted coffee, adzuki beans, and paddy and white rice. These databases were established using a reference NIR instrument and the piecewise direct standardization (PDS) calibration transfer method. To evaluate the suitability of the transfer samples, the Davies-Bouldin index (DBI) was calculated. The outcomes that resulted in low DBI values were likely to produce better classification rates. The classification of coffee origins was based on the use of a supervised self-organizing map (SSOM). Without the spectral modification, SSOM classification using the developed NIR instrument resulted in predictive ability (% PA), model stability (% MS), and correctly classified instances (% CC) values of 61%, 58%, and 64%, respectively. After the transformation process was completed with the corn, red bean, mung bean, white rice, and green coffee NIR spectral data, the predictive performance of the SSOM models was found to have improved (67-79% CC). The best classification performance was observed with the use of corn, producing improved % PA, % MS, and % CC values at 71%, 67%, and 79%, respectively.

Multi-Elemental Analysis as a Tool to Ascertain the Safety and the Origin of Beehive Products: Development, Validation, and Application of an ICP-MS Method on Four Unifloral Honeys Produced in Sardinia, Italy.

Despite unifloral honeys from Sardinia, Italy, being appreciated worldwide for their peculiar organoleptic features, their elemental signature has only partly been investigated. Hence, the principal aim of this study was to measure the concentration of trace and toxic elements (i.e., Ag, As, Ba, Be, Bi, Cd, Co, Cr, Cu, Fe, Hg, Li, Mn, Mo, Ni, Pb, Sb, Sn, Sr, Te, Tl, V, and Zn) in four unifloral honeys produced in Sardinia. For this purpose, an original ICP-MS method was developed, fully validated, and applied on unifloral honeys from asphodel, eucalyptus, strawberry tree, and thistle. Particular attention was paid to the method's development: factorial design was applied for the optimization of the acid microwave digestion, whereas the instrumental parameters were tuned to minimize the polyatomic interferences. Most of the analytes' concentration ranged between the relevant LoDs and few mg kg-1, while toxic elements were present in negligible amounts. The elemental signatures of asphodel and thistle honeys were measured for the first time, whereas those of eucalyptus and strawberry tree honeys suggested a geographical differentiation if compared with the literature. Chemometric analysis allowed for the botanical discrimination of honeys through their elemental signature, whereas linear discriminant analysis provided an accuracy level of 87.1%.

Rapid identification of the geographic origin of Taiping Houkui green tea using near-infrared spectroscopy combined with a variable selection method.

BACKGROUND: Most studies focus on the geographically larger production areas in tea traceability. However, famous high-quality tea is often produced in a narrow range of origins, which makes traceability a challenge. In this study, Taiping Houkui (TPHK) green tea of narrow geographical origin was rapidly identified using Fourier-transform near-infrared (FT-NIR) spectroscopy. RESULTS: First, spectral information of 114 TPHK samples from four production areas was acquired. Second, the synthetic minority over-sampling technique (SMOTE) was used to balance the sample data set, and three different spectral pre-processing methods were compared. Third, three feature variable selection algorithms were used to obtain the pre-processed spectral features. Finally, extreme learning machine (ELM) models based on the variables obtained from the selected features were established to trace the TPHK origin. The optimized ELM model achieves 95.35% classification accuracy in the test set. CONCLUSION: The present study demonstrates that the optimized variable selection method in combination with NIR spectroscopy represents a suitable strategy for tea traceability in narrow regions. © 2022 Society of Chemical Industry.

[Application and prospect of stable isotope technology in tracing geographical origin of Chinese herbal medicines].

As a unique medical resource in China, Chinese herbal medicine plays a key role in the prevention and treatment of human diseases. With the gradual expansion of applications, the quality of Chinese herbal medicine has become the focus of attention. The quality of Chinese herbal medicines depends largely on their source authenticity. Tracing the origin of Chinese herbal medicines plays an important role in ensuring their quality and efficacy and reducing the mixing and adulteration of Chinese herbal medicines from different regions. Stable isotope technology, as a key technology for origin tracing of agricultural products and food, has been used in the research of Chinese herbal medicines from multiple sources and origins in recent years. This new technological means contributes to standardizing the origin of Chinese herbal medicines and controlling their quality from the source. Apart from introducing the basic principles of stable isotope technology and the characteristics of common stable isotopes, this study reviewed the application status of light and heavy stable isotopes in the origin tracing of Chinese herbal medicines and their correlation with ecological factors, and forecasted the application prospect of this technology in the authentication of Chinese herbal medicines, aiming to provide reference for the geographical origin tracing of Chinese herbal medicines and promote the sustainable development of traditional Chinese medicine.