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FTIR spectroscopy and multivariate analysis were used in the chemical study of the terroirs of Coffea canephora. Conilon coffees from Espírito Santo and Amazon robusta from Matas of Rondônia, were separated by PCA, with lipids and caffeine being the markers responsible for the separation. Coffees from Bahia, Minas Gerais, and São Paulo did not exhibit separation, indicating that the botanical variety had a greater effect on the terroir than geographic origin. Thus, the genetic factor was investigated considering the conilon and robusta botanical varieties. This last group was composed of hybrid robusta and apoatã. The DD-SIMCA favored the identification of the genetic predominance of the samples. PLS-DA had a high classification performance regarding the conilon, hybrid robusta, and apoatã genetic nature. Lipids, caffeine, chlorogenic acids, quinic acid, trigonelline, proteins, amino acids, and carbohydrates were identified as chemical markers that discriminated the genetic groups.
Assuntos
Coffea , Coffea/genética , Coffea/química , Cafeína/análise , Brasil , Café/química , LipídeosRESUMO
Given rising traders and consumers concerns, the global food industry is increasingly demanding authentic and traceable products. Consequently, there is a heightened focus on verifying geographical authenticity as food quality assurance. In this work, we assessed pattern recognition approaches based on elemental predictors to discern the provenance of mandarin juices from three distinct citrus-producing zones located in the Northeast region of Argentina. A total of 202 samples originating from two cultivars were prepared through microwave-assisted acid digestion and analyzed by microwave plasma atomic emission spectroscopy (MP-AES). Later, we applied linear discriminant analysis (LDA), k-nearest neighbor (k-NN), support vector machine (SVM), and random forest (RF) to the element data obtained. SVM accomplished the best classification performance with a 95.1% success rate, for which it was selected for citrus samples authentication. The proposed method highlights the capability of mineral profiles in accurately identifying the genuine origin of mandarin juices. By implementing this model in the food supply chain, it can prevent mislabeling fraud, thereby contributing to consumer protection.
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New Brazilian Canephora coffees (Conilon and Robusta) of high added value from specific origins have been protected by geographical indication to guarantee their origin and quality. Recently, benchtop near-infrared (NIR) spectroscopy combined with chemometrics has demonstrated its usefulness to discriminate them. It was the first study, however, and therefore the possibility exists to develop a new portable NIR method for this purpose. This work assessed a miniaturized NIR as a cheaper spectrometer to discriminate and authenticate new Brazilian Canephora coffees with certified geographical origins and to differentiate them from specialty Arabica. Discriminant chemometric and class modeling techniques have been applied and have obtained good predictive ability on external test sets. In addition, models with similar classification purpose were compared with those obtained in previous research carried out with benchtop NIR for the same samples, obtaining comparable results. In this context, the portable method was used as a laboratory technique and has the advantage of being cheaper than benchtop NIR spectrometer. Furthermore, it brings a high possibility to be implemented in small coffee cooperatives, industries or control agencies in the future that do not have high economic resources.
Assuntos
Café , Rubiaceae , Brasil , Certificação , Coleta de Dados , GeografiaRESUMO
Coffee is a product whose quality and price are associated with its geographical, genetic and processing origin; therefore, the development of analytical techniques to authenticate the above mentioned is important to avoid adulteration. The objective of this study was to compare conventional analytical methods with NIR technology for the authentication of roasted and ground coffee samples from different producing regions in Mexico (origins) and different varieties. A second objective was to determine, under the same processing conditions, if roasting times can be differentiated by using this technology. A total of 120 samples of roasted and ground commercial coffee were obtained from the states of Chiapas, Oaxaca, Tabasco and Veracruz in Mexico, 30 locally available samples per state. Samples from Veracruz included three different varieties, grown on the same farm and processed under the same conditions. One of these varieties was selected to evaluate the chemical composition of samples roasted at 185 °C using four different roasting times (15, 17, 19 and 21 min). Samples from different producing regions showed significant differences (P < 0.05) in fat content (from 7.45 ± 0.42% in Tabasco to 18.40 ± 2.95% in Chiapas), which was associated with the altitude of coffee plantations (Pearson's r = 0.96). The results indicate that NIR technology generates sufficient useful information to authenticate roasted and ground coffee from different geographical origins in Mexico and different varieties from the same coffee plantation, with similar results to those obtained by conventional analytical methods.
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Spain dominates avocado production in Europe, with the Hass variety being the most prominent. Despite this, Spanish production satisfies less than 10% of the overall avocado demand in Europe. Consequently, the European avocado market heavily relies on imports from overseas, primarily sourced from Peru and Chile. Herein, a comprehensive characterization of the metabolic profile of Hass avocado fruits from Spain, Peru, and Chile, available in the European market throughout the year, was carried out. The determination of relevant substances was performed using high- and low-resolution RP-LC-MS. Remarkable quantitative differences regarding phenolic compounds, amino acids, and nucleosides were observed. Principal component analysis revealed a natural clustering of avocados according to geographical origin. Moreover, a specific metabolic pattern was established for each avocado-producing country using supervised partial least squares discriminant analysis. Spanish fruits exhibited high levels of coumaric acid malonyl-hexose II, coumaric acid hexose II, and ferulic acid hexose II, together with considerably low levels of pantothenic acid and uridine. Chilean avocado fruits presented high concentrations of abscisic acid, uridine, ferulic acid, succinic acid, and tryptophan. Fruits from Peru showed high concentrations of dihydroxybenzoic acid hexose, alongside very low levels of p-coumaric acid, ferulic acid, coumaric acid malonyl-hexose I, and ferulic acid hexose II.
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Tea (Camellia sinensis) fraud has been frequently identified and involves tampering with the labelling of inferior products or without geographical origin certification and even mixing them with superior quality teas to mask an adulteration. Consequently, economic losses and health damage to consumers are observed. Thus, a Chemometrics-assisted Color Histogram-based Analytical System (CACHAS) was employed a simple, cost-effective, reliable, and green analytical tool to screen the quality of teas. Data-Driven Soft Independent Modeling of Class Analogy was used to authenticate their geographical origin and category simultaneously, recognizing correctly all Argentinean and Sri Lankan black teas and Argentinean green teas. For the determination of moisture, total polyphenols, and caffeine, Partial Least Squares obtained satisfactory predictive abilities, with values of root mean squared error of prediction (RMSEP) of 0.50, 0.788, and 0.25 mg kg-1, rpred of 0.81, 0.902, and 0.81, and relative error of prediction (REP) of 6.38, 9.031, and 14.58%., respectively. CACHAS proved to be a good alternative tool for environmentally-friendly non-destructive chemical analysis.
Assuntos
Camellia sinensis , Quimiometria , Chá , Cafeína/análise , Polifenóis/análiseRESUMO
Tea (Camellia sinensis (L.) Kuntze-surname of German origin) is a popular beverage consumed worldwide due to its health benefits. Its quality depends on measuring features that may discriminate teas from distinct provenances. Protected designation of origin (PDO) is therefore a very useful label for tea quality evaluation. In the present work, antioxidant activity profiles obtained from microfluidic paper-based analytical devices (µPADs) were analyzed by chemometrics to determine the tea geographic origin. Based on the existing literature, we constructed a database containing chemical data from 26 samples and evaluated it by principal component analysis (PCA) coupled to linear discriminant analysis (LDA). Antioxidant activity was an effective LDA predictor for sample discrimination accomplishing accuracies from 75 to 82%. Modeling performance was favored by an external validation method. The best classification model was found using the first nine PCs as input variables. Training samples achieved a perfect success rate, while the test ones were predicted with 83% specificity, 100% sensitivity, and 90% overall accuracy. The modeling robustness was verified by integrating AUC (0.943) from ROC curve. The PCA-LDA approach taken here demonstrated that the teas coming from different countries can be correctly authenticated through µPADs, thus contributing to certificate samples PDO. Supplementary Information: The online version contains supplementary material available at 10.1007/s13197-022-05440-1.
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Abstract Colombian emeralds, 26 from Palo Arañado (eastern emerald zone, Chivor district, Boyacá, Colombia), and 28 from Santo Domingo - La Pava mine (western emerald zone, Muzo district, Boyacá, Colombia), together with 30 from Kafubu - Zambia, were studied by reflectance Fourier transform infrared spectroscopy, principal component analysis, clustering, and partial least squares -discriminant analysis, in order to differentiate them by geographical origin. The spectra were smoothed and a baseline correction was made. The principal component analysis showed that the wavenumbers 2,474; 2,640; 2,686; 2,818; 5,448, and 6,815 cm-' are the most significant in the first principal component and the most valuable in separating the emeralds by their geographical origin. This allowed us to completely discriminate emeralds from Santo Domingo and Zambia, while only five emeralds from Palo Arañado were '00 % differentiable from the other two groups of emeralds.
Resumen Se estudiaron (usando espectroscopia de reflectancia infrarroja con transformada de Fourier, análisis de componentes principales, agrupamientos y análisis discriminante por mínimos cuadrados parciales), 54 esmeraldas colombianas, 26 provenientes de Palo Arañado (zona esmeraldífera oriental, distrito de Chivor, Boyacá, Colombia), y 28 de Santo Domingo (mina La Pava, zona esmeraldífera occidental, distrito de Muzo, Boyacá, Colombia), junto a 30 esmeraldas de Kafubu (Zambia), con el fin de diferenciarlas por su origen geográfico. Los espectros fueron suavizados y se corrigió su línea base. El análisis de componentes principales permitió identificar que los números de onda 2474, 2640, 2686, 2818, 5448 y 68'5 cm-' son los de mayor contribución al primer componente principal y, por tanto, los más relevantes en la separación de los grupos de esmeraldas por su origen geográfico. Lo anterior hizo posible la discriminación completa entre las esmeraldas de Zambia y las de Santo Domingo, mientras que solo 5 muestras de Palo Arañado resultaron '00 % diferenciables de los otros dos grupos de esmeraldas estudiadas.
Resumo Um total de 54 esmeraldas colombianas, 26 originarias de Palo Arañado (região esmeraldífera oriental, distrito de Chivor, Boyacá, Colombia) e 28 de Santo Domingo, da mina La Pava (região esmeraldífera ocidental, distrito Muzo, Boyacá, Colombia), junto com 30 esmeraldas da Zâmbia (da região de Kafubu) foram estudadas para obter uma diferenciação por sua origem geográfica, usando espectroscopia de infravermelho por transformada de Fourier, análise de componentes principais, e agrupamento e análise discriminante de mínimos quadrados. Os espetros foram suavizados e a sua linha base foi corregida. A analise de componentes principais, permitiu identificar que os números de onda 2474, 2640, 2686, 2818, 5448 y 68'5 cm-' são os que mais contribuem ao primeiro componente principal e, por tanto, os mais importantes na separação dos grupos de esmeraldas por sua origem geográfica. Isto permitiu a completa discriminação entre as esmeraldas da Zâmbia e as de Santo Domingo, enquanto que apenas cinco amostras de Palo Arañado foram '00 % diferenciáveis dos outros dois grupos de esmeraldas estudadas.
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In this study, the aroma profile of 10 single origin Arabica coffees originating from eight different growing locations, from Central America to Indonesia, was analyzed using Headspace SPME-GC-MS as the analytical method. Their roasting was performed under temperature-time conditions, customized for each sample to reach specific sensory brew characteristics in an attempt to underline the customization of roast profiles and implementation of separate roastings followed by subsequent blending as a means to tailor cup quality. A total of 138 volatile compounds were identified in all coffee samples, mainly furan (~24-41%) and pyrazine (~25-39%) derivatives, many of which are recognized as coffee key odorants, while the main formation mechanism was the Maillard reaction. Volatile compounds' composition data were also chemometrically processed using the HCA Heatmap, PCA and HCA aiming to explore if they meet the expected aroma quality attributes and if they can be an indicator of coffee origin. The desired brew characteristics of the samples were satisfactorily captured from the volatile compounds formed, contributing to the aroma potential of each sample. Furthermore, the volatile compounds presented a strong variation with the applied roasting conditions, meaning lighter roasted samples were efficiently differentiated from darker roasted samples, while roasting degree exceeded the geographical origin of the coffee. The coffee samples were distinguished into two groups, with the first two PCs accounting for 73.66% of the total variation, attributed mainly to the presence of higher quantities of furans and pyrazines, as well as to other chemical classes (e.g., dihydrofuranone and phenol derivatives), while HCA confirmed the above results rendering roasting conditions as the underlying criterion for differentiation.
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Coffea/química , Café/química , Furanos/química , Odorantes/análise , Pirazinas/química , Compostos Orgânicos Voláteis/química , América Central , Coffea/metabolismo , Café/metabolismo , Etiópia , Furanos/classificação , Furanos/isolamento & purificação , Furanos/metabolismo , Cromatografia Gasosa-Espectrometria de Massas , Temperatura Alta , Humanos , Indonésia , Reação de Maillard , Análise de Componente Principal , Pirazinas/classificação , Pirazinas/isolamento & purificação , Pirazinas/metabolismo , Sementes/química , Paladar/fisiologia , Compostos Orgânicos Voláteis/classificação , Compostos Orgânicos Voláteis/isolamento & purificação , Compostos Orgânicos Voláteis/metabolismoRESUMO
In the present work, the provenance discrimination of Argentinian honeys was used as case study to compare the capabilities of three spectroscopic techniques as fast screening platforms for honey authentication purposes. Multifloral honeys were collected among three main honey-producing regions of Argentina over four harvesting seasons. Each sample was fingerprinted by FT-MIR, NIR and FT-Raman spectroscopy. The spectroscopic platforms were compared on the basis of the classification performance achieved under a supervised chemometric approach. Furthermore, low- mid- and high-level data fusion were attempted in order to enhance the classification results. Finally, the best-performing solution underwent to SIMCA modelling with the purpose of reproducing a food authentication scenario. All the developed classification models underwent to a "year-by-year" validation strategy, enabling a sound assessment of their long-term robustness and excluding any issue of model overfitting. Excellent classification scores were achieved by all the technologies and nearly perfect classification was provided by FT-MIR. All the data fusion strategies provided satisfying outcomes, with the mid- and high-level approaches outperforming the low-level data fusion. However, no significant advantage over the FT-MIR alone was obtained. SIMCA modelling of FT-MIR data produced highly sensitive and specific models and an overall prediction ability improvement was achieved when more harvesting seasons were used for the model calibration (86.7% sensitivity and 91.1% specificity). The results obtained in the present work suggested the major potential of FT-MIR for fingerprinting-based honey authentication and demonstrated that accuracy levels that may be commercially useful can be reached. On the other hand, the combination of multiple vibrational spectroscopic fingerprints represents a choice that should be carefully evaluated from a cost/benefit standpoint within the industrial context.
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Sixty-seven roasted coffee samples from different regions of Brazil cultivated using organic, conventional and biodynamic farming practices were analysed and quantified using high performance liquid chromatography coupled with mass spectrometry, and treated with supervised (PLS-DA) and unsupervised (PCA) multivariate statistical tools. The profile of the chlorogenic acids constituents were analysed by high resolution and tandem mass spectrometry, which allowed the identification of mono- caffeoyl-, feruloyl-, para-Coumaroylquinic acids and their respective regio-isomers. This study provides a comprehensive analysis of absolute quantitative data set of chlorogenic acids constituents (CQA, FQA and pCoQA isomers) in Brazilian coffee beans produced from different regions of the country. Variations in the chlorogenic acids compositions were observed if organic and conventional roasted coffee beans were compared. The use of multivariate statistical tools allowed the identification of suitable biomarkers for determining significant differences between the three coffee agricultural practices, while coffees produced from the diverse geographical regions showed no significant difference.
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Ácido Clorogênico/química , Coffea/química , Manipulação de Alimentos/métodos , Sementes/química , Agricultura , Brasil , Humanos , Estrutura MolecularRESUMO
Some minor constituents of honey samples were determined through a fluorometric-chemical characterization method and related multifactorially with their antibacterial activity against Staphylococcus aureus and Pseudomonas aeruginosa and with their geographical origin. Rotated principal component analysis identified five significant components in honey: three related to antibacterial activity and linked to phenolic compounds; Maillard products; proteins; the concentration of H2O2 at 3 and 24 h of incubation; and a tyrosine-containing entity. On the other hand, five constituents (phenolic compounds were the most relevant) allowed the classification of honey samples by geographical origin with 87% certainty. The results showed that phenolic compounds and Maillard products are related to the sustained production of H2O2 over time, which in turn boosts the antibacterial activity of honey. Native flora could promote this capability. The results showed the effect of geographic origin on the content of the analyzed minor constituents of honey, particularly phenolic compounds.
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Mel/análise , Antibacterianos/farmacologia , Fluorometria , Peróxido de Hidrogênio/análise , Testes de Sensibilidade Microbiana , Fenóis/análise , Pseudomonas aeruginosa/efeitos dos fármacos , Staphylococcus aureus/efeitos dos fármacosRESUMO
This work proposes the development of a simple, fast, and inexpensive methodology based on color histograms (obtained from digital images), and supervised pattern recognition techniques to classify red wines produced in the São Francisco Valley (SFV) region to trace geographic origin, winemaker, and grape variety. PCA-LDA coupled with HSI histograms correctly differentiated all of the SFV samples from the other geographic regions in the test set; SPA-LDA selecting just 10 variables in the Grayscale + HSI histogram achieved 100% accuracy in the test set when classifying three different SFV winemakers. Regarding the three grape varieties, SPA-LDA selected 15 variables in the RGB histogram to obtain the best result, misclassifying only 2 samples in the test set. Pairwise grape variety classification was also performed with only 1 misclassification. Besides following the principles of Green Chemistry, the proposed methodology is a suitable analytical tool; for tracing origins, grape type, and even (SFV) winemakers.
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Vitis/química , Vinho/análise , CorRESUMO
Maca has shown broad application prospects as a new food resource. The function of maca is directly affected by its geographical origin, and an effective method for studying traceability must be established. This study aimed to discriminate maca from different regions at large scales (Peru and China) and small scales (Yunnan, Xinjiang, and Tibet in China) through geographical authentication using the stable isotope ratio (SIR) (δ13C, δ15N, δ2H and δ18O) and mineral elemental fingerprints combined with chemometrics. For Peruvian and Chinese maca, overall discriminatory accuracy of 100% and 96.2% were obtained by applying SIR and the mineral element analysis, respectively. For maca obtained from different Chinese regions, the order of the discriminatory accuracy was mineral elements (80.2%) = SIR combined with mineral elements (80.2%) > SIR (71.9%). K, B, Mn, Fe, Mo, Cd and As were identified as the main discriminating indicators for identifying maca from different Chinese regions.
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Lepidium/química , Minerais/análise , China , Geografia , Isótopos/análise , PeruRESUMO
The aim of this work was to undertake a detailed analysis on chemical constituents of brown propolis, originating from four different states (Bahia, Minas Gerais, Paraná and Sergipe) of Brazil. The volatile profile was determined by using HS-SPME-GC-MS along with the determination of total phenolic compounds content, flavonoids and antioxidant activity. A total of 315 volatile compounds were identified, however, several of them have not been reported so far in the Brazilian brown propolis. The terpenes represented the major class with 40.92-84.66% of the total area in the chromatograms. PCA analysis of the majority of compounds successfully indicated the volatile profile of each propolis sample according to their geographical origin. The analysis of volatile compounds and its characterization also varied significantly and confirmed that these depended on the geographical area of collection of propolis. The data generated in this work may help in establishing criteria for quality control and tracking the specific region of propolis production in different states of Brazil.
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Própole/química , Controle de Qualidade , Antioxidantes/análise , Brasil , Flavonoides/análise , Cromatografia Gasosa-Espectrometria de Massas , Fenóis/análise , Análise de Componente Principal , Espectroscopia de Infravermelho com Transformada de Fourier , Terpenos/análise , Compostos Orgânicos Voláteis/análiseRESUMO
The aim of this work was to verify the usefulness of multielemental and isotopic fingerprint to differentiate the origin of milk samples from different areas, linking milk fingerprint with those corresponding to soil, water, and forage. Samples from four production areas in Argentina were analysed: 26 elements, δ2H, δ13C, δ15N and δ18O. Milk provenance was assessed using 16 variables (Na, Mg, Al, V, Co, Ni, As, Se, Rb, Sr, Mo, Hg, δ2H, δ18O, δ13C and K/Rb). Generalized Procrustes Analysis (GPA) demonstrated the consensus between soil, water, forage and milk, in addition to differences between studied areas. Canonical Correlation Analysis (CCA) demonstrated significant correlations between the milk-drinking water, milk-forage, and milk-soil. So far, we report a feasible method to establish the milk provenance, assessing the follow up from environmental matrixes (soilâ¯+â¯water) to dairy products through the food web (forage) by a combined chemical-isotopic fingerprint.
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Análise de Alimentos/métodos , Isótopos/análise , Metais/análise , Leite/química , Solo/química , Animais , Argentina , Água Potável/análise , Análise de Alimentos/estatística & dados numéricosRESUMO
Rice is one of the most important staple foods around the world. Authentication of rice is one of the most addressed concerns in the present literature, which includes recognition of its geographical origin and variety, certification of organic rice and many other issues. Good results have been achieved by multivariate data analysis and data mining techniques when combined with specific parameters for ascertaining authenticity and many other useful characteristics of rice, such as quality, yield and others. This paper brings a review of the recent research projects on discrimination and authentication of rice using multivariate data analysis and data mining techniques. We found that data obtained from image processing, molecular and atomic spectroscopy, elemental fingerprinting, genetic markers, molecular content and others are promising sources of information regarding geographical origin, variety and other aspects of rice, being widely used combined with multivariate data analysis techniques. Principal component analysis and linear discriminant analysis are the preferred methods, but several other data classification techniques such as support vector machines, artificial neural networks and others are also frequently present in some studies and show high performance for discrimination of rice.
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Análise de Alimentos , Oryza/química , Bases de Dados Factuais , Análise Discriminante , Processamento de Imagem Assistida por Computador , Análise Multivariada , Oryza/genética , Análise de Componente Principal , Espectrofotometria Atômica , Análise Espectral RamanRESUMO
The determination of the botanical/geographical origin of honey provides assurance of the product's quality. In the present work, honeys from different ecoregions of Argentina were analysed, and the possible link between the complete pollen profile of honey samples and their volatile composition was evaluated by multivariate statistical tools. A total of 110 volatile compounds were found and semiquantified in honey samples. Redundancy analysis showed significant correlations between the volatile profile of honeys and their production region (Pâ¯=â¯.0002). According to the present results, 3,8-p-menthatriene; cyclopropylidenemethylbenzene; 1,1,6-trimethyl-1,2-dihydronaphthalene; 1,2,4-trimethylbenzene; α-pinene; isopropyl 2-methylbutanoate; cymene; 2,6-dimethyl-1,6-octadiene; 3-methyloctane; 1-(1,4-dimethyl-3-cyclohexen-1-yl)ethanone; terpinolene; ethyl 2-phenylacetate; naphthalene and 7 unknown compounds could be used to classify Argentinean honeys according to their geographical origin with a prediction success of 96%. Moreover, it could be concluded that honeys with Eucalyptus sp., Aristotelia chilensis and T. Baccharis pollen types presented some characteristic volatile compounds which could be used as floral markers.
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Análise de Alimentos/métodos , Mel/análise , Pólen/química , Compostos Orgânicos Voláteis/análise , Argentina , Eucalyptus/químicaRESUMO
Paullinia cupana, commonly known as guarana, is an Amazonian fruit whose seeds are used to produce the powdered guarana, which is rich in caffeine and consumed for its stimulating activity. The metabolic profile of guarana from the two largest producing regions was investigated using UPLC-MS combined with multivariate statistical analysis. The principal component analysis (PCA) showed significant differences between samples produced in the states of Bahia and Amazonas. The metabolites responsible for the differentiation were identified by orthogonal partial least squares discriminant analysis (OPLS-DA). Fourteen phenolic compounds were characterized in guarana powder samples, and catechin, epicatechin, B-type procyanidin dimer, A-type procyanidin trimer and A-type procyanidin dimer were the main compounds responsible for the geographical variation of the samples.
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Cromatografia Líquida de Alta Pressão/métodos , Espectrometria de Massas/métodos , Paullinia/química , Fenóis/análise , Sementes/química , Biflavonoides/análise , Brasil , Cafeína , Catequina/análise , Proantocianidinas/análise , Teobromina , TeofilinaRESUMO
BACKGROUND: Macamides with a benzylalkylamide nucleus are characteristic and major bioactive compounds in the functional food maca (Lepidium meyenii Walp). The aim of this study was to explore variations in macamide content among maca from China and Peru. Twenty-seven batches of maca hypocotyls with different phenotypes, sampled from different geographical origins, were extracted and profiled by liquid chromatography with ultraviolet detection/tandem mass spectrometry (LC-UV/MS/MS). RESULTS: Twelve macamides were identified by MS operated in multiple scanning modes. Similarity analysis showed that maca samples differed significantly in their macamide fingerprinting. Partial least squares discriminant analysis (PLS-DA) was used to differentiate samples according to their geographical origin and to identify the most relevant variables in the classification model. The prediction accuracy for raw maca was 91% and five macamides were selected and considered as chemical markers for sample classification. CONCLUSION: When combined with a PLS-DA model, characteristic fingerprinting based on macamides could be recommended for labelling for the authentication of maca from different geographical origins. The results provided potential evidence for the relationships between environmental or other factors and distribution of macamides. © 2016 Society of Chemical Industry.