Multi-element, multi-compound isotope profiling as a means to distinguish the geographical and varietal origin of fermented cocoa (Theobroma cacao L.) beans

Integrative metagenomics, volatilomics and chemometrics for deciphering the microbial structure and core metabolic network during Chinese rice wine (Huangjiu) fermentation in different regions

Huangjiu is a spontaneously fermented alcoholic beverage, that undergoes intricate microbial compositional changes. This study aimed to unravel the flavor and quality formation mechanisms based on the microbial metabolism of Huangjiu. Here, metagenome techniques, chemometrics analysis, and headspace solid-phase microextraction gas chromatography-mass spectrometry (HS-SPME-GC-MS) metabolomics combined with microbial metabolic network were employed to investigate the distinctions and relationship between the microbial profiles and the quality characteristics, flavor metabolites, functional metabolic patterns of Huangjiu across three regions. Significant variations (P < 0.05) were observed in metabolic rate of physicochemical parameters and biogenic amine concentration among three regions. 8 aroma compounds (phenethyl acetate, phenylethyl alcohol, isobutyl alcohol, ethyl octanoate, ethyl acetate, ethyl hexanoate, isoamyl alcohol, and diethyl succinate) out of 448 volatile compounds were identified as the regional chemical markers. 25 dominant microbial genera were observed through metagenomic analysis, and 13 species were confirmed as microbial markers in three regions. A metabolic network analysis revealed that Saccharomycetales (Saccharomyces), Lactobacillales (Lactobacillus, Weissella, and Leuconostoc), and Eurotiales (Aspergillus) were the predominant populations responsible for substrate, flavor (mainly esters and phenylethyl alcohol) metabolism, Lactobacillales and Enterobacterales were closely linked with biogenic amine. These findings provide scientific evidence for regional microbial contributions to geographical characteristics of Huangjiu, and perspectives for optimizing microbial function to promote Huangjiu quality.

Proximate Composition and Bioactive Compounds of Cocoa Bean Shells as a By-Product from Cocoa Industries in Indonesia

Cocoa bean shell (CBS) is a by-product from cocoa processing which is abundant in Indonesia, one of the largest cocoa-producing countries. It has a great potential for being processed into food ingredients due to its comparable composition to cocoa nibs. The present study was conducted to identify the proximate composition and bioactive compounds in CBS produced at several cocoa industries in Indonesia utilizing different cocoa varieties (Criollo and Forastero) and processing techniques (fermented, non-fermented, pulp washing, and drying), which remain unknown. The results showed that the CBS derived from roasted Criollo cocoa pods in the Kendeng Lembu cocoa industry had ash and protein content of about 8.21% and 18.79%, respectively, which was higher than other industries. Additionally, the concentration of bioactive substances was higher here than it was elsewhere. This included total phenolic (136.2 mg GAE g-1) and theobromine (22.50 mg g-1). The lowest ash and protein concentration found in CBS was from Forastero cocoa pods, non-fermented like Sulawesi cocoa. These values were 6.48% and 15.70%, respectively. The concentration of theobromine (15.40 mg g-1) was also lower compared to other industries.

Authentication of Cocoa Products Based on Profiling and Fingerprinting Approaches: Assessment of Geographical, Varietal, Agricultural and Processing Features

Cocoa and its derivative products, especially chocolate, are highly appreciated by consumers for their exceptional organoleptic qualities, thus being often considered delicacies. They are also regarded as superfoods due to their nutritional and health properties. Cocoa is susceptible to adulteration to obtain illicit economic benefits, so strategies capable of authenticating its attributes are needed. Features such as cocoa variety, origin, fair trade, and organic production are increasingly important in our society, so they need to be guaranteed. Most of the methods dealing with food authentication rely on profiling and fingerprinting approaches. The compositional profiles of natural components -such as polyphenols, biogenic amines, amino acids, volatile organic compounds, and fatty acids- are the source of information to address these issues. As for fingerprinting, analytical techniques, such as chromatography, infrared, Raman, and mass spectrometry, generate rich fingerprints containing dozens of features to be used for discrimination purposes. In the two cases, the data generated are complex, so chemometric methods are usually applied to extract the underlying information. In this review, we present the state of the art of cocoa and chocolate authentication, highlighting the pros and cons of the different approaches. Besides, the relevance of the proposed methods in quality control and the novel trends for sample analysis are also discussed.

Amazonian cacao-clone nibs discrimination using NIR spectroscopy coupled to naïve Bayes classifier and a new waveband selection approach

Near-Infrared Spectroscopy (NIRS) has shown to be helpful in the study of rice, tea, cocoa, and other foods due to its versatility and reduced sample treatment. However, the high complexity of the data produced by NIR sensors makes necessary pre-treatments such as feature selection techniques that produce compact profiles. Supervised and unsupervised techniques have been tested, creating different subsets of features for classification, which affect the performance of the classifiers based on such compact profiles. In this sense, we propose and test a new covering array feature selection (CAFS) algorithm coupled to the naïve Bayes classifier (NBC) to discriminate among Amazonian cacao nibs from six cacao clones. The CAFS wrapper approach looks for the wavebands that maximize the F₁-score, and then, are more relevant for classification. For this purpose, cacao pods of six varieties were collected, and their grains were extracted and processed (fermented, dried, roasted, and milled) to obtain cacao nibs. Then from each clone NIR spectral profiles in the range of 1100-2500 nm were extracted, and relevant wavebands were selected using the proposed CAFS algorithm. For comparison, two standard feature selection techniques were implemented the multi-cluster feature selection MCFS and the eigenvector centrality feature selection ECFS. Then, based on the different selected variables, three NBCs were built and compared among them through statistical metrics. The results showed that using the wavebands selected by CAFS, the NBC performed an average accuracy of 99.63%; being this superior to the 94.92% and 95.79% for ECFS and MCFS respectively. These results showed that the wavebands selected by the proposed CAFS algorithm allowed obtaining a better fit concerning other feature selection methods reported in the literature.

Traceability of the geographical origin of Siraitia grosvenorii based on multielement contents coupled with chemometric techniques

Siraitia grosvenorii (LHG) is widely used as a medicinal and edible material around the world. The objective of this study was to develop an effective method for the authentication of the geographical origin of LHG in its main producing area Guangxi, China, which is identified as Chinese Protected Designation of Origin product, against other producing regions in China. The content of 14 elements (K, Na, Ca, P, Mg, Al, B, Ba, Cu, Fe, Mn, Ni, Zn, and Sr) of 114 LHG samples was determined by inductively coupled plasma optical emission spectrometry. Multivariate analysis was then performed to classify the geographical origin of LHG samples. The contents of multielement display an obvious trend of clustering according to the geographical origin of LHG samples based on radar plot and principal component analysis. Finally, three supervised statistical techniques, including linear discriminant analysis (LDA), k-nearest neighbours (k-NN), and support vector machine (SVM), were applied to develop classification models. Finally, 40 unknown LHG samples were used to evaluate the predictive ability of model and discrimination rate of 100%, 97.5% and 100% were obtained for LDA, k-NN, and SVM, respectively. This study indicated that it is feasible to attribute unknown LHG samples to its geographical origin based on its multielement content coupled with chemometric techniques.

Functional role of yeasts, lactic acid bacteria and acetic acid bacteria in cocoa fermentation processes

Cured cocoa beans are obtained through a post-harvest, batchwise process of fermentation and drying carried out on farms in the equatorial zone. Fermentation of cocoa pulp-bean mass is performed mainly in heaps or boxes. It is made possible by a succession of yeast, lactic acid bacteria (LAB) and acetic acid bacteria (AAB) activities. Yeasts ferment the glucose of the cocoa pulp into ethanol, perform pectinolysis and produce flavour compounds, such as (higher) alcohols, aldehydes, organic acids and esters. LAB ferment the glucose, fructose and citric acid of the cocoa pulp into lactic acid, acetic acid, mannitol and pyruvate, generate a microbiologically stable fermentation environment, provide lactate as carbon source for the indispensable growth of AAB, and contribute to the cocoa and chocolate flavours by the production of sugar alcohols, organic acids, (higher) alcohols and aldehydes. AAB oxidize the ethanol into acetic acid, which penetrates into the bean cotyledons to prevent seed germination. Destruction of the subcellular seed structure in turn initiates enzymatic and non-enzymatic conversions inside the cocoa beans, which provides the necessary colour and flavour precursor molecules (hydrophilic peptides, hydrophobic amino acids and reducing sugars) for later roasting of the cured cocoa beans, the first step of the chocolate-making.

Multi-block classification of chocolate and cocoa samples into sensory poles

The present study aims at developing an analytical methodology which allows correlating sensory poles of chocolate to their chemical characteristics and, eventually, to those of the cocoa beans used for its preparation. Trained panelists investigated several samples of chocolate, and they divided them into four sensorial poles (characterized by 36 different descriptors) attributable to chocolate flavor. The same samples were analyzed by six different techniques: Proton Transfer Reaction-Time of Flight-Mass Spectrometry (PTR-ToF-MS), Solid Phase Micro Extraction-Gas Chromatography-Mass Spectroscopy (SPME-GC-MS), High-Performance Liquid Chromatography (HPLC) (for the quantification of eight organic acids), Ultra High Performance Liquid Chromatography coupled to triple-quadrupole Mass Spectrometry (UHPLC-QqQ-MS) for polyphenol quantification, 3D front face fluorescence Spectroscopy and Near Infrared Spectroscopy (NIRS). A multi-block classification approach (Sequential and Orthogonalized-Partial Least Squares - SO-PLS) has been used, in order to exploit the chemical information to predict the sensorial poles of samples. Among thirty-one test samples, only two were misclassified.

LC-MS and Spectrophotometric Approaches for Evaluation of Bioactive Compounds from Peru Cocoa By-Products for Commercial Applications

Peru is one of the main areas where there are large cocoa crops with special relevance to the economy of this country. In fact, cocoa is a major, economically important, international crop which has been linked to several benefits, such as anti-allergenic, anti-atherogenic, anti-inflammatory, anti-microbial, anti-oxidant, anti-thrombotic, cardioprotective and vasodilatory properties, relating to its bioactive compound content. However, in cocoa industrial processing, several residues or wastes, which are commonly discarded generating a negative impact on the environment, are produced in large amounts. Some of the cocoa by-products, which go underutilized, could be a good source of bioactive compounds with high utility for the development of innovative products in nutraceutical, medical or pharmaceutical industries. For this reason, the aim of this study is to qualitatively determine the phytochemical composition of husk and bean extracts from different cocoa-growing areas and processes from Peru by high performance liquid chromatography coupled to mass spectrometry. Furthermore, we aim to evaluate their phenolic and flavan-3-ol contents and antioxidant capacities for the purpose of highlighting the potential of cocoa by-products from these cultivars as functional ingredients. In total, 49 chemical compounds were detected in the analyzed extracts. Comparing both husks and beans, bean extracts were characterized by high content in flavonoids whereas husk extracts had a higher content of phenolic acids. The presence of these compounds together with the bioactivity results suggest that these matrices may be further studied for their revaluation in the development of high added-value products in nutraceutical, medical, and pharmaceutical industries.

Cocoa Bean Shell-A By-Product with Nutritional Properties and Biofunctional Potential

Cocoa bean shells (CBS) are one of the main by-products from the transformation of cocoa beans, representing 10%‒17% of the total cocoa bean weight. Hence, their disposal could lead to environmental and economic issues. As CBS could be a source of nutrients and interesting compounds, such as fiber (around 50% w/w), cocoa volatile compounds, proteins, minerals, vitamins, and a large spectrum of polyphenols, CBS may be a valuable ingredient/additive for innovative and functional foods. In fact, the valorization of food by-products within the frame of a circular economy is becoming crucial due to economic and environmental reasons. The aim of this review is to look over the chemical and nutritional composition of CBS and to revise the several uses that have been proposed in order to valorize this by-product for food, livestock feed, or industrial usages, but also for different medical applications. A special focus will be directed to studies that have reported the biofunctional potential of CBS for human health, such as antibacterial, antiviral, anticarcinogenic, antidiabetic, or neuroprotective activities, benefits for the cardiovascular system, or an anti-inflammatory capacity.

Complementary use of 1H NMR and multi-element IRMS in association with chemometrics enables effective origin analysis of cocoa beans (Theobroma cacao L.)

Within the cocoa market (Theobroma cacao L.), quality and prices are often determined by geographical origin, making traceability indispensable. Therefore, to investigate possibilities of tracing by analytical methods, 48 carefully selected cocoa samples from 20 countries have been profiled using a combination of stable isotope-ratio mass spectrometry (IRMS) and proton nuclear magnetic resonance (¹H NMR). Chemometric analysis of combined data sets from both, stable isotope data (δ¹³C, δ¹⁵N, δ¹⁸O, δ²H, %C, %N, %O, %H) and ¹H NMR fingerprints, achieved good separation with increased classification rates compared to classification with data of the isolated methods. IRMS contributed primarily to discrimination between countries, while ¹H NMR significantly contributed to separation of varieties, but also the regions within individual countries. This study thus demonstrates that combination of two analytical methods is an effective tool to enhance both, accuracy and precision, in authenticity testing of cocoa.

Geographic authentication of the traditional Chinese medicine Atractylodes macrocephala Koidz. (Baizhu) using stable isotope and multielement analyses

RATIONALE

Atractylodes macrocephala Koidz (Baizhu) is a valuable traditional Chinese medicine, and medicines of that type originating from Zhejiang province are the most famous and much more expensive than those from other regions. Driven by the great difference in prices, fraudulent labeling often occurs. In order to protect the interests of consumers, producers and honest traders, reliable techniques for the geographic authentication of Baizhu are needed urgently.

METHODS

The stable isotope ratios of five light elements (C, N, H, O and S) in Baizhu samples originating from four provinces of China were determined with an elemental analyzer coupled to isotope ratio mass spectrometry, and the concentrations of 45 elements in these samples were measured using inductively coupled plasma mass spectrometry. Chemometric approaches including principal component analysis (PCA) and orthodox partial least squares discriminant analysis (OPLS-DA) were applied to the obtained data.

RESULTS

The PCA results showed that the techniques enabled clear classification of the Baizhu samples into three clusters: A (Zhejiang province), B (Shaanxi province) and C (Hebei and Ahui provinces). Furthermore, OPLS-DA using 27 key variables provided 100% correct discrimination between samples originating from Zhejiang province and those from the other three provinces.

CONCLUSIONS

Stable isotope ratio and multielement analyses in combination with chemometric approaches showed great potential for the geographic authentication of Baizhu, providing a promising method for the control of fraudulent labeling that frequently occurs with traditional herbal medicines in China.

Geographical traceability of Chinese green tea using stable isotope and multi-element chemometrics

RATIONALE

Deliberate and fraudulent origin mislabeling of Chinese green tea motivated by large price differences often brings significant food safety risks and damages consumer trust. Currently, there is no reliable method to verify the origin of green tea produced in China. Stable isotope and multi-element analyses combined with statistical models are widely acknowledged as useful traceability techniques for many agro-products, and could be developed to confirm the geographical origin of Chinese green tea and, more importantly, combat illegal green tea mislabeling and fraud.

METHODS

An analytical strategy combining elemental analyzer/isotope ratio mass spectrometry (EA/IRMS) and inductively plasma coupled mass spectrometry (ICP-MS) with chemometrics tools was used to confirm the origin of green tea grown in the main tea production provinces around China. Stable C, N, H, O isotope ratios and twenty elements were measured to build mathematical discriminant models using unsupervised principal component analysis (PCA) and supervised linear discriminant analysis (LDA). Two main problems: (i) tracing the origin of Chinese green tea from different tea growing provinces (Zhejiang, Shandong, and other provinces); (ii) authentication of high-value Westlake Longjing tea from the Westlake region and surrounding areas in Zhejiang province, were investigated and assessed.

RESULTS

The results demonstrated that PCA and follow-up LDA based on stable isotope and multi-element signatures can verify the geographical origin of Chinese green tea from different provinces, and even localized zones in the same province could be distinguishable, with discrimination accuracies higher than 92.3% and 87.8%, respectively.

CONCLUSIONS

Geochemical fingerprinting techniques coupled with chemometric tools offer an accurate and effective verification method for the geographical origin of Chinese green tea, providing a promising tool to combat fraudulent mislabeling of high-value green tea.

Using stable isotope signatures to delineate the geographic point-of-origin of Keemun black tea

BACKGROUND

Confirmation of food labeling that claims production in a small geographic region is critical to traceability, quality control and brand protection. In the current study, isotope ratio mass spectrometry (IRMS) was used to generate profiles of δ¹³ C and δ¹⁵ N to determine if the stable isotope signatures of Keemun black tea differ within the three counties that claim production. Other factors (cultivar type, leaf maturity and manufacturing process) were considered for their potential effects.

RESULTS

Both cultivar type and leaf maturity have remarkable impact on the δ¹⁵ N values of tea leaves, and that the cultivar influenced the δ¹³ C values. Keemun black tea from Qimen county could be easily discriminated from samples from Dongzhi and Guichi counties based on δ¹⁵ N signatures. The k-NN model was cross-validated with an accuracy of 91.6%. Environmental factors and/or genotype seem to be the major reasons for δ¹⁵ N differences in Keemun black tea from the selected regions.

CONCLUSION

This article provides a potential effective method to delineate the geographic point-of-origin of Keemun black tea based on δ¹⁵ N signatures. © 2018 Society of Chemical Industry.

Determining the geographical origin of common buckwheat from China by multivariate analysis based on mineral elements, amino acids and vitamins

This study aimed to establish a method for distinguishing the geographical origin of common buckwheat from Inner Mongolia, Shanxi and Shaanxi Provinces in China. Three chemical families including mineral elements, vitamins and amino acids of 48 samples from different geographical origins were analyzed by principal component analysis (PCA), cluster analysis (CA) and linear discriminate analysis (LDA) for this purpose. LDA clearly discriminated the geographical origin of common buckwheat samples grown in three regions, and gave a high correct classification rate of 95.8% and satisfactory cross-validation rate of 91.7%. Some variables (Mn, VPP, Se, Gly, Cu, Asp, Fe, and Ala) significantly contributed to the ability to discriminate the geographical origin of the common buckwheat. These results demonstrated that the proposed method is a powerful tool for controlling the geographical origin of common buckwheat by governmental administration and protecting consumers from improper domestic labeling. However, the discriminant method still needs to be further validated using more reliable data.

Origin-based polyphenolic fingerprinting of Theobroma cacao in unfermented and fermented beans

A comprehensive analysis of cocoa polyphenols from unfermented and fermented cocoa beans from a wide range of geographic origins was carried out to catalogue systematic differences based on their origin as well as fermentation status. This study identifies previously unknown compounds with the goal to ascertain, which of these are responsible for the largest differences between bean types. UHPLC coupled with ultra-high resolution time-of-flight mass spectrometry was employed to identify and relatively quantify various oligomeric proanthocyanidins and their glycosides amongst several other unreported compounds. A series of biomarkers allowing a clear distinction between unfermented and fermented cocoa beans and for beans of different origins were identified. The large sample set employed allowed comparison of statistically significant variations of key cocoa constituents.

Multivariate analysis to discriminate the origin of sesame seeds by multi-element analysis inductively coupled plasma-mass spectrometry

In this study, inductively coupled plasma-mass spectrometry (ICP-MS) was used to determine the concentration of 15 elements (Mg, Al, K, Ca, Cr, Mn, Co, Ni, Cu, Zn, Rb, Sr, Cd, Ba, and Pb) of sesame seeds. Multivariate analysis was then performed to discriminate the origin of sesame seeds. Korean (48), Chinese (44), and Indian (21) samples were used to develop the calibration model. Another 10 samples were used to validate this model. All elements were significantly different (p<0.05) among the samples from three countries, and all elements were subjected to both principal component analysis (PCA) and discriminant analysis. The concentrations of multi-element showed a trend of clustering according to the origin of samples based on PCA. They showed a discrimination rate of 92.0% in the discriminant analysis. The results demonstrated that a combination of ICP-MS multi-element determination and multivariate analysis could be used to discriminate the sesame seed origin.

Accelerated solvent extraction method for the quantification of polycyclic aromatic hydrocarbons in cocoa beans by gas chromatography-mass spectrometry

An accelerated solvent extraction (ASE) procedure for use with gas chromatography-mass spectrometry (GC-MS) was optimized for the determination of eight polycyclic aromatic hydrocarbons (PAHs) in cocoa beans. Plackett-Burman and rotatable central composite design (RCCD) indicated that three variables affected the recoveries of PAHs during the extraction and purification steps: agitation time in the second liquid-liquid partition, weight of silica gel in the column, and volume of hexane for PAH elution from the column. After obtaining the optimal conditions, a single laboratory method validation was performed. Linearity was demonstrated for benzo[a]pyrene in the concentration range from 0.5 to 8.0mgkg^-1 of sample, corresponding to 1.25-20.0μgkg^-1 of cocoa on a fat basis. For the other analytes, linearity was observed from 0.75 to 8.0μgkg^-1 of sample (1.88-20.0μgkg^-1 of cocoa on a fat basis). Significant matrix effects were found for chrysene and benzo[b]fluoranthene. The precision of the method was verified with relative standard deviations (RSDs) ranging from 2.57 to 14.13% and from 4.36 to 19.77% under repeatability and intermediate precision conditions, respectively. The average recoveries of the eight PAHs ranged from 74.99 to 109.73%. These parameters, limits and measurement uncertainties met the performance criteria established by European Union regulations, except for the theoretical limit of detection for chrysene. The method was applied to the analysis of samples of Brazilian cocoa beans, and only one sample was found to have a PAH content above the maximum limit defined by the European Union legislation. This optimized and validated method is intended to be used as part of the official Brazilian monitoring programs investigating contaminants and residues in food.

Stable isotope composition of cocoa beans of different geographical origin

The isotopic profile (δ(13) C, δ(15) N, δ(18) O, δ(2) H, δ(34) S) was used to characterise a wide selection of cocoa beans from different renowned production areas (Africa, Asia, Central and South America). The factors most influencing the isotopic signatures of cocoa beans were climate and altitude for δ(13) C and the isotopic composition of precipitation water for δ(18) O and δ(2) H, whereas δ(15) N and δ(34) S were primarily affected by geology and fertilisation practises. Multi-isotopic analysis was shown to be sufficiently effective in determining the geographical origin of cocoa beans, and combining it with Canonical Discriminant Analysis led to more than 80% of samples being correctly reclassified. Copyright © 2016 John Wiley & Sons, Ltd.

Distinction of Ecuadorian varieties of fermented cocoa beans using Raman spectroscopy

Cocoa (Theobroma cacao) is a crop of economic importance. In Ecuador, there are two predominant cocoa varieties: National and CCN-51. The National variety is the most demanded, since its cocoa beans are used to produce the finest chocolates. Raman measurements of fermented, dried and unpeeled cocoa beans were performed using a handheld spectrometer. Samples of the National and CCN-51 varieties were collected from different provinces and studied in this work. For each sample, 25 cocoa beans were considered and each bean was measured at 4 different spots. The most important Raman features of the spectra were assigned and discussed. The spectroscopic data were processed using chemometrics, resulting in a distinction of varieties with 91.8% of total accuracy. Differences in the average Raman spectra of cocoa beans from different sites but within the same variety can be attributed to environmental factors affecting the cocoa beans during the fermentation and drying processes.