Using elemental profiles and stable isotopes to trace the origin of green coffee beans on the global market

Probabilistic Risk Assessment of Metals, Acrylamide and Ochratoxin A in Instant Coffee from Brazil, Colombia, Mexico and Peru

This study analysed the probabilistic risk to consumers associated with the presence of iAs, Cd, Cr, Hg, Pb, acrylamide (AA) and ochratoxin A (OTA) in instant coffee from Brazil, Colombia, Mexico and Peru. The results found iAs to be the metal with the highest concentrations (3.50 × 10-2 to 6.00 × 10-2 mg/kg), closely followed by Pb (1.70 × 10-2 to 2.70 × 10-2 mg/kg) and Cr (5.00 × 10-3 to 1.00 × 10-2 mg/kg), although these differences were not significant between countries. Cd and Hg were not detected. Focusing on AA, the concentrations ranged from 1.77 × 10-1 mg/kg (Peru) to 4.77 × 10-1 mg/kg (Brazil), while OTA ranged from 1.32 × 10-3 (Peru) to 1.77 × 10-3 mg/kg (Brazil) with significant differences between countries in both cases. As regards risk, the hazard quotient and hazard index were less than 1, meaning that the consumption of instant coffee represents a low level of concern for non-genotoxic effects. The results of the combination of margin of exposure and probability of exceedance indicated that the non-genotoxic effects of Pb, AA and OTA pose no threat. However, the probability values of suffering cancer from iAs and AA (between 1 × 10-6 and 1 × 10-4) indicated a moderate risk and that management measures should be taken.

Support vector regression for prediction of stable isotopes and trace elements using hyperspectral imaging on coffee for origin verification

The potential of using rapid and non-destructive near-infrared - hyperspectral imaging (HSI-NIR) for the prediction of an integrated stable isotope and multi-element dataset was explored for the first time with the help of support vector regression. Speciality green coffee beans sourced from three continents, eight countries, and 22 regions were analysed using a push-broom HSI-NIR (700-1700 nm), together with five isotope ratios (δ13C, δ15N, δ18O, δ2H, and δ34S) and 41 trace elements. Support vector regression with the radial basis function kernel was conducted using X as the HSI-NIR data and Y as the geochemistry markers. Model performance was evaluated using root mean squared error, coefficient of determination, and mean absolute error. Three isotope ratios (δ18O, δ2H, and δ34S) and eight elements (Zn, Mn, Ni, Mo, Cs, Co, Cd, and La) had an R2predicted 0.70 - 0.99 across all origin scales (continent, country, region). All five isotope ratios were well predicted at the country and regional levels. The wavelength regions contributing the most towards each prediction model were highlighted, including a discussion of the correlations across all geochemical parameters. This study demonstrates the feasibility of using HSI-NIR as a rapid and non-destructive method to estimate traditional geochemistry parameters, some of which are origin-discriminating variables related to altitude, temperature, and rainfall differences across origins.

Probabilistic Risk Characterization of Heavy Metals in Peruvian Coffee: Implications of Variety, Region and Processing

Heavy metals are chemical contaminants, toxic, potentially carcinogenic and/or mutagenic, stable, persistent and are of concern in the food chain. The risk to the consumer of the presence of inorganic arsenic (iAs), cadmium (Cd), chromium (Cr), mercury (Hg) and lead (Pb) in five varieties (Bourbon, Típica, Catimor, Caturra and Pache) of parchment coffee from five regions (Amazonas, Cajamarca, Cusco, Huánuco and San Martín) was investigated in this study. A predictive model of the stages of coffee bean hulling, roasting and infusion was built to simulate the process. The results by region showed significant differences in which San Martín had the highest iAs, Cr and Pb values. The variety was only significant for Cr, of which Pache presented the highest concentration. The Cd and Hg values were below the detection limits. The hazard index (HI) was less than 1 for iAs, Cd, Cr and Hg and the combination of margin of exposure and the probability of exceedance (MOE-POE) for Pb indicated that an adverse health effect was not likely. The cancer risk (CR) for iAs and Pb in the 95th percentile was considered as both high and acceptable, respectively.

Stable isotope and trace element analyses with non-linear machine-learning data analysis improved coffee origin classification and marker selection

BACKGROUND

This study investigated the geographical origin classification of green coffee beans from continental to country and regional levels. An innovative approach combined stable isotope and trace element analyses with non-linear machine learning data analysis to improve coffee origin classification and marker selection. Specialty green coffee beans sourced from three continents, eight countries, and 22 regions were analyzed by measuring five isotope ratios (δ¹³ C, δ¹⁵ N, δ¹⁸ O, δ² H, and δ³⁴ S) and 41 trace elements. Partial least squares discriminant analysis (PLS-DA) was applied to the integrated dataset for origin classification.

RESULTS

Origins were predicted well at the country level and showed promise at the regional level, with discriminating marker selection at all levels. However, PLS-DA predicted origin poorly at the continental and Central American regional levels. Non-linear machine learning techniques improved predictions and enabled the identification of a higher number of origin markers, and those that were identified were more relevant. The best predictive accuracy was found using ensemble decision trees, random forest and extreme gradient boost, with accuracies of up to 0.94 and 0.89 for continental and Central American regional models, respectively.

CONCLUSION

The potential for advanced machine learning models to improve origin classification and the identification of relevant origin markers was demonstrated. The decision-tree-based models were superior with their embedded variable identification features and visual interpretation. © 2023 The Authors. Journal of The Science of Food and Agriculture published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Near-infrared reflectance spectroscopy accurately predicted isotope and elemental compositions for origin traceability of coffee

Stable isotope ratios and trace elements are well-established tools that act as signatures of the product's environmental conditions and agricultural processes; but they involve time, money, and environmentally destructive chemicals. In this study, we tested for the first time the potential of near-infrared reflectance spectroscopy (NIR) to estimate/predict isotope and elemental compositions for the origin verification of coffee. Green coffee samples from two continents, 4 countries, and 10 regions were analysed for five isotope ratios (δ¹³C, δ¹⁵N, δ¹⁸O, δ²H, and δ³⁴S) and 41 trace elements. NIR (1100-2400 nm) calibrations were developed using pre-processing with extended multiplicative scatter correction (EMSC) and mean centering and partial-least squares regression (PLS-R). Five elements (Mn, Mo, Rb, B, La) and three isotope ratios (δ¹³C, δ¹⁸O, δ²H) were moderately to well predicted by NIR (R²: 0.69 to 0.93). NIR indirectly measured these parameters by association with organic compounds in coffee. These parameters were related to altitude, temperature and rainfall differences across countries and regions and were previously found to be origin discriminators for coffee.

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.

Inductively Coupled Plasma-Mass Spectrometry (ICP-MS), a Useful Tool in Authenticity of Agricultural Products' and Foods' Origin

Fraudulent practices are the first and foremost concern of food industry, with significant consequences in economy and human's health. The increasing demand for food has led to food fraud by replacing, mixing, blending, and mislabeling products attempting to increase the profits of producers and companies. Consequently, there was the rise of a multidisciplinary field which encompasses a large number of analytical techniques aiming to trace and authenticate the origins of agricultural products, food and beverages. Among the analytical strategies have been developed for the authentication of geographical origin of foodstuff, Inductively Coupled Plasma Mass Spectrometry (ICP-MS) increasingly dominates the field as a robust, accurate, and highly sensitive technique for determining the inorganic elements in food substances. Inorganic elements are well known for evaluating the nutritional composition of food products while it has been shown that they are considered as possible tracers for authenticating the geographical origin. This is based on the fact that the inorganic component of identical food type originating from different territories varies due to the diversity of matrix composition. The present systematic literature review focusing on gathering the research has been done up-to-date on authenticating the geographical origin of agricultural products and foods by utilizing the ICP-MS technique. The first part of the article is a tutorial about food safety/control and the fundaments of ICP-MS technique, while in the second part the total research review is discussed.

Simultaneously Verifying the Original Region of Green and Roasted Coffee Beans by Stable Isotopes and Elements Combined with Random Forest

Simultaneously verifying the original region of green and roasted coffee beans is very important for protecting legal interests of the stakeholder according to the chemical analyzing method. 131 green coffee bean samples are collected from six different original regions and pretreated with three degrees (green, middle, and dark roasted); five stable isotope ratios (δ13C, δ14N, δ18O, δ2H, and δ32S) and twelve elemental contents (Al, Cr, Ni, Zn, Ba, Cu, Na, Mn, Fe, Ca, K, and Mg) of green, middle, and dark roasted coffee bean samples (131×3) were analyzed. Fractionation of stable isotopes and variation of elemental contents were evaluated, only isotope hydrogen (2H) significantly fractionated, and elemental concentrations increased with a certain rate during the roasting process. One-way analysis of variance (ANOVA) was used to compare the stable isotope ratios and elemental concentrations of all coffee bean samples from six different original regions. Random forest (RF) was employed to build a discriminating model for simultaneously verifying the original regions of green and roasted coffee bean samples; this model provided 100% accuracy. Inclusion of this mathematical model for simultaneously verifying the original region of green and roasted coffee beans had powerful distinguishing capability and which will not be influenced by fractionation of hydrogen (2H) and variation of element contents during the roasted process.

Effects of phenotypic variability on the oxygen and hydrogen isotope compositions of grains in different winter wheat varieties

Stable isotope analyses are the leading method for geographic origin determination, especially of plant-based agricultural products. Origin analysis is typically done by comparing a suspicious sample to reference materials with known geographic origin. Reference materials are usually collected at the species level, assuming different varieties of a species to have comparable isotope compositions within a given location. We evaluated whether different phenotypes that are expressed in different varieties of winter wheat (Triticum aestivum L.) influence the oxygen (δ¹⁸O) and hydrogen (δ²H) isotope composition of plant tissue water and organic compounds. We found that mean δ¹⁸O and δ²H values among winter wheat varieties did not differ significantly in leaf water, however, differed significantly in bulk dried grain tissue. The differences in bulk dried grain δ¹⁸O and δ²H values among varieties can be related to differences in phenotypic trait expression among varieties. Despite this substantial phenotypic variability, the overall variability of bulk dried grain δ¹⁸O and δ²H values among varieties was small (SD 0.54 ‰ for oxygen, 3.60 ‰ for hydrogen). We thus conclude that reference materials collected at the species level should be sufficient for geographic origin analysis of winter wheat and possibly other cereals using δ¹⁸O and δ²H values.

The wastes of coffee bean processing for utilization in food: a review

A few million cubic tons of waste are generated annually as a result of coffee processing. As a beverage, coffee in itself is a rich source of melanoidins, phenolic compounds, and other phytonutrients which confer a wide range of health benefits. These wastes generated every year are usually discarded as landfill mass, mixed with animal fodder, or incinerated. Coffee wastes, due to their high content of tannins and caffeine, can degrade the soil quality and induce carcinogenicity when mixed with animal fodder. This review aims to identify the potential of coffee silver skin and spent coffee grounds, both generated as a result of the roasting process and instantization processes. Coffee husk and coffee flour are also well-known for their excellent bioactive roles. The proximate composition of coffee silverskin indicates a rich dietary fibre source and finds wide applications in bakery and other allied food products. This process could generate a value-added product and alleviate the disposing quality of remnant spent coffee grounds. Companies are exploring novel ideas of producing coffee flour obtained from drying and milling of coffee cherries for applications in day-to-day food products. Coffee and coffee waste combined with its high concentration of fibre, colorant pigments, and antioxidant compounds, has immense potential as a functional ingredient in food systems and needs to be explored further for its better utilization.

Carbon and Nitrogen Isotopic Analysis of Morphine from Opium and Heroin Samples Originating in the Four Major Heroin Producing Regions

The forensic analysis of stable isotopes is a valuable tool to geo-source natural or semi-synthetic drugs such as cocaine and heroin. The present study describes a novel methodology to isolate morphine from opium for isotopic analysis. Furthermore, this isotopic data from regional sources is corroborated with morphine data obtained from seized heroin (de-acetylated to morphine) from the same regions. All five primary alkaloids of opium, namely morphine, codeine, thebaine, noscapine and papaverine, were quantified using high performance liquid chromatography with PDA before the preparative experiment to gather a complete major alkaloidal profile. Morphine fractions of authentic opium submissions from Mexico, South America, Southwest Asia, and Southeast Asia were isolated and collected using preparative high performance liquid chromatography, and the collected morphine samples were subsequently analyzed by isotope ratio mass spectrometry. Carbon and nitrogen isotope data are presented. The data demonstrates that nitrogen ratios are capable of differentiating samples from Mexico and South America while carbon ratios are able to distinguish Southwest Asian samples from other source regions. Analogous results have routinely been observed (as part of Heroin Signature Program analysis) for morphine obtained from de-acetylated authentic heroin samples from the same source regions. The results suggest that the poppy growing region has a greater influence on the carbon and nitrogen isotope values than the heroin manufacturing processes employed. When utilized in conjunction with existing signature methodologies, carbon and nitrogen isotope ratio data can enhance the ability to geo-source heroin.

Coffee Infusions: Can They Be a Source of Microelements with Antioxidant Properties?

Coffee is a beverage that is very popular all over the world. Its pro-health effect has been demonstrated in many publications. This drink can counteract the effects of oxidative stress thanks to its antioxidant properties. The aim of this study was to collect data on the content of microelements with antioxidant activity (manganese, zinc, copper, iron) in coffee infusions, taking into account various factors. The study considered publications from the years 2000–2020 found in Google Scholar and PubMed databases. It was noted that coffee can provide up to 13.7% of manganese requirements per serving, up to 4.0% and 3.1% of zinc requirements for women and men, up to 2.7% and 2.1% of copper requirements for women and men, and up to 0.4% and 0.6% of iron requirements for women and men. Coffee infusions can also be a source of fluoride (up to 2.5%), chromium (up to 0.4% of daily intake for women and 0.2% for men), and cobalt (up to 0.1%). There are no data in the literature regarding the content of selenium in coffee infusions. The origin of coffee beans and the type of water used (especially regarding fluoride) may have an impact on the content of minerals in infusions. The brewing method does not seem to play an important role. As it is a very popular beverage, coffee can additionally enrich the diet with such micronutrients as manganese, zinc, and copper. This seems beneficial due to their antioxidant properties, however the bioavailability of these elements of coffee should be taken into account. It seems necessary to carry out more research in this area.

Selected Instrumental Techniques Applied in Food and Feed: Quality, Safety and Adulteration Analysis

This review presents an overall glance at selected instrumental analytical techniques and methods used in food analysis, focusing on their primary food science research applications. The methods described represent approaches that have already been developed or are currently being implemented in our laboratories. Some techniques are widespread and well known and hence we will focus only in very specific examples, whilst the relatively less common techniques applied in food science are covered in a wider fashion. We made a particular emphasis on the works published on this topic in the last five years. When appropriate, we referred the reader to specialized reports highlighting each technique's principle and focused on said technologies' applications in the food analysis field. Each example forwarded will consider the advantages and limitations of the application. Certain study cases will typify that several of the techniques mentioned are used simultaneously to resolve an issue, support novel data, or gather further information from the food sample.

Achieving Food Authenticity and Traceability Using an Analytical Method Focusing on Stable Isotope Analysis

High-value agricultural products are characterized by the geographical conditions of the production areas such as climatic and soil conditions. These products are protected by the geographical indication (GI) protection system, which has been introduced in more than 100 countries. Because GI products are expensive in the market, products are often mislabeled as GI. Thus, there is an urgent need for the development of analytical methods that enable the tracing of geographical origins of food materials. Stable isotope analysis is used to trace the geographical origin of food materials. In this study, we review the applications for tracing the geographical origin of agricultural products (especially rice, beef, and honey) focusing on an analytical method for analyzing stable isotopes (δD, δ13C, δ15N, δ18O, and δ34S).

Geographical origin differentiation of Chinese Angelica by specific metal element fingerprinting and risk assessment

Traceability offers significant information about the quality and safety of Chinese Angelica, a medicine and food homologous substance. In this study, a systematic four-step strategy, including sample collection, specific metal element fingerprinting, multivariate statistical analysis, and benefit-risk assessment, was developed for the first time to identify Chinese Angelica based on geographical origins. Fifteen metals in fifty-six Chinese Angelica samples originated from three provinces were analyzed. The multivariate statistical analysis model established, involving hierarchical cluster analysis (HCA), principal component analysis (PCA), and self-organizing map clustering analysis was able to identify the origins of samples. Furthermore, benefit-risk assessment models were created by combinational calculation of chemical daily intake (CDI), hazard index (HI), and cancer risk (CR) levels to evaluate the potential risks of Chinese Angelica using as traditional Chinese medicine (TCM) and food, respectively. Our systematic strategy was well convinced to accurately and effectively differentiate Chinese Angelica based on geographical origins.

Discrimination of the Indonesian Roasted Arabica Coffees using 1H NMR-based Metabolomics

In this report, the roasted Arabica coffees obtained from 4 Indonesian regions were analyzed with 1H NMR based-metabolomics. In total, 23 compounds were detected in the coffee 1H NMR spectra. Orthogonal projection to latent structure-discriminant analysis (OPLSDA) model successfully classified metabolites of the coffees based on their origins. S-plots of two-classes partial least square discriminant analysis (PLSDA) models successfully identified discriminant metabolites for every coffee. Chlorogenic acids, trigonelline, arabinoses were found as the discriminant compounds for Preanger-Java coffee. Lipids, acetic acid and lactic acid were discovered as the characteristic metabolites for Gayo-Sumatra coffee. γ-quinide was found as the most important marker for Bajawa-Flores coffee. Meanwhile, Toraja-Sulawesi coffee were characterized with a balance chemical composition indicating its well-balanced taste. The findings revealed the diversity of Indonesian Arabica coffees and shed more light on scientific information of Indonesian coffees.

A data fusion model merging information from near infrared spectroscopy and X-ray fluorescence. Searching for atomic-molecular correlations to predict and characterize the composition of coffee blends

This article aims to develop and validate a multivariate model for quantifying Robusta-Arabica coffee blends by combining near infrared spectroscopy (NIRS) and total reflection X-ray fluorescence (TXRF). For this aim, 80 coffee blends (0.0-33.0%) were formulated. NIR spectra were obtained in the wavenumber range 11100-4950 cm-1 and 14 elements were determined by TXRF. Partial least squares models were built using data fusion at low and medium levels. In addition, selection of predictive variables based on their importance indices (SVPII) improved results. The best model reduced the number of variables from 1114 to 75 and root mean square error of prediction from 4.1% to 1.7%. SVPII selected NIR regions correlated with coffee components, and the following elements were chosen: Ti, Mn, Fe, Cu, Zn, Br, Rb, Sr. The model interpretation took advantage of the data fusion between atomic and molecular spectra in order to characterize the differences between these coffee varieties.

A predictive spatial model for roasted coffee using oxygen isotopes of α-cellulose

RATIONALE

Fraudulent region-of-origin labeling is a concern for high-value, globally traded commodities such as coffee. The oxygen isotope ratio of cellulose is a useful geographic tracer, as it integrates climate and source water signals. A predictive spatial model ("isoscape") of the δ¹⁸ O values of coffee bean cellulose is generated to evaluate coffee region-of-origin claims.

METHODS

The oxygen isotope ratio of α-cellulose extracted from roasted coffee beans was measured via high-temperature conversion elemental analyzer/isotope ratio mass spectrometry (TC-EA/IRMS) and used to calculate the δ¹⁸ O value of coffee bean water. The ¹⁸ O enrichment of coffee bean water relative to the δ¹⁸ O value of local precipitation was modeled as a function of local temperature and humidity. This function was incorporated into a mechanistic model of cellulose δ¹⁸ O values to predict the δ¹⁸ O values of coffee bean cellulose across coffee-producing regions globally.

RESULTS

The δ¹⁸ O values of analyzed coffee bean cellulose ranged from approximately +22‰ to +42‰ (V-SMOW). As expected, coffees grown in the same region tended to have similar isotope ratios, and the δ¹⁸ O value of coffee bean cellulose was generally higher than the δ¹⁸ O value of modeled stem cellulose for the region. Modeled δ¹⁸ O values of coffee cellulose were within ±2.3‰ of the measured δ¹⁸ O value of coffee cellulose.

CONCLUSIONS

The oxygen isotope ratio of coffee bean cellulose is a useful indicator of region-of-origin and varies predictably in response to climatic factors and precipitation isotope ratios. The isoscape of coffee bean cellulose δ¹⁸ O values from this study provides a quantitative tool that can be applied to region-of-origin verification of roasted coffee at the point-of-sale.

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.

Combination of sugar and stable isotopes analyses to detect the use of nongrape sugars in balsamic vinegar must

"Aceto Balsamico di Modena" (ABM) is a protected geographical indication salad dressing obtained from cooked and/or concentrated grape must, with the addition of wine vinegar and a maximum of 2% caramel (EU Reg 583/2009). In this study, we investigated whether the combination of ¹³ C/¹² C of ethanol using isotope ratio mass spectrometry with ² H-site-specific natural isotope fractionation-nuclear magnetic resonance and minor sugars using ion chromatography with pulse amperometric and charged aerosol detection is able to improve detection of sugar addition to ABM must. A large selection of authentic Italian grape musts and different samples of balsamic vinegar with an increasing percentage of added beet, cane, and sugar syrups were considered. The possible degradation of sugars in the ABM matrix during shelf life was also investigated. While stable isotope ratios analysis remains the favoured method for determining cane and beet sugar addition, dosage of minor sugar (in particular maltose) proved to be very useful for detecting the addition of sugar syrup. Thanks to this innovative approach, 3 out of 27 commercial ABMs were identified as adulterated. A combination of stable isotope ratio and ion chromatography with pulse amperometric and charged aerosol detection analysis can be therefore proposed as a suitable tool for detecting the authenticity of ABM must.

Comparison of Attenuated Total Reflectance Mid-Infrared, Near Infrared, and 1H-Nuclear Magnetic Resonance Spectroscopies for the Determination of Coffee's Geographical Origin

The sensorial properties of Colombian coffee are renowned worldwide, which is reflected in its market value. This raises the threat of fraud by adulteration using coffee grains from other countries, thus creating a demand for robust and cost-effective methods for the determination of geographical origin of coffee samples. Spectroscopic techniques such as Nuclear Magnetic Resonance (NMR), near infrared (NIR), and mid-infrared (mIR) have arisen as strong candidates for the task. Although a body of work exists that reports on their individual performances, a faithful comparison has not been established yet. We evaluated the performance of ¹H-NMR, Attenuated Total Reflectance mIR (ATR-mIR), and NIR applied to fraud detection in Colombian coffee. For each technique, we built classification models for discrimination by species (C. arabica versus C. canephora (or robusta)) and by origin (Colombia versus other C. arabica) using a common set of coffee samples. All techniques successfully discriminated samples by species, as expected. Regarding origin determination, ATR-mIR and ¹H-NMR showed comparable capacity to discriminate Colombian coffee samples, while NIR fell short by comparison. In conclusion, ATR-mIR, a less common technique in the field of coffee adulteration and fraud detection, emerges as a strong candidate, faster and with lower cost compared to ¹H-NMR and more discriminating compared to NIR.

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.

Elemental composition of green coffee and its contribution to dietary intake

The concentration of twenty-seven elements (Li, Be, B, Mg, Al, P, K, Ca, Cr, Mn, Co, Ni, Cu, Zn, As, Se, Sr, Mo, Cd, Sn, Sb, Ba, Hg, Pb, Bi, Th, and U) in green coffee samples and their infusions were determined by using inductively coupled plasma-mass spectrometry (ICP-MS). Prior to analysis, green coffee samples were prepared by microwave digestion, while infusions were analyzed without any pre-treatment. The accuracy and precision of the proposed methods were verified by recovery experiments. Considering samples; K, Cu, and Al had the highest mean concentrations with 6714.5μgg(-1), 12.1μgg(-1), and 25.9μgg(-1) among major, trace and toxic elements, respectively. The impact of brewing type on leachability of elements was also studied and the results outlined that mean leachability of elements to Turkish coffee were greater than to mud coffee. Furthermore, dietary element intakes through green coffee consumption were also estimated. This is the first study presenting wide range of elements in green coffee brews and calculating dietary intakes.

Classification of Coffee Beans by GC-C-IRMS, GC-MS, and (1)H-NMR

In a previous work using (1)H-NMR we reported encouraging steps towards the construction of a robust expert system for the discrimination of coffees from Colombia versus nearby countries (Brazil and Peru), to assist the recent protected geographical indication granted to Colombian coffee in 2007. This system relies on fingerprints acquired on a 400 MHz magnet and is thus well suited for small scale random screening of samples obtained at resellers or coffee shops. However, this approach cannot easily be implemented at harbour's installations, due to the elevated operational costs of cryogenic magnets. This limitation implies shipping the samples to the NMR laboratory, making the overall approach slower and thereby more expensive and less attractive for large scale screening at harbours. In this work, we report on our attempt to obtain comparable classification results using alternative techniques that have been reported promising as an alternative to NMR: GC-MS and GC-C-IRMS. Although statistically significant information could be obtained by all three methods, the results show that the quality of the classifiers depends mainly on the number of variables included in the analysis; hence NMR provides an advantage since more molecules are detected to obtain a model with better predictions.

Elemental profiling and geographical differentiation of Ethiopian coffee samples through inductively coupled plasma-optical emission spectroscopy (ICP-OES), ICP-mass spectrometry (ICP-MS) and direct mercury analyzer (DMA)

This study was aimed to establish the elemental profiling and provenance of coffee samples collected from eleven major coffee producing regions of Ethiopia. A total of 129 samples were analyzed for forty-five elements using inductively coupled plasma (ICP)-optical emission spectroscopy (OES), ICP-mass spectrometry (MS) and direct mercury analyzer (DMA). Among the macro elements, K showed the highest levels whereas Fe was found to have the lowest concentration values. In all the samples, Ca, K, Mg, P and S contents were statistically significant (p<0.05). Micro elements showed the concentrations order of: Mn>Cu>Sr>Zn>Rb>Ni>B. Contents of the trace elements were lower than the permissible standard values. Inter-regions differentiation by cluster analysis (CA), linear discriminant analysis (LDA) and principal component analysis (PCA) showed that micro and trace elements are the best chemical descriptors of the analyzed coffee samples.

The content of Ca, Cu, Fe, Mg and Mn and antioxidant activity of green coffee brews

A simple and fast method of the analysis of green coffee infusions was developed to measure total concentrations of Ca, Cu, Fe, Mg and Mn by high resolution-continuum source flame atomic absorption spectrometry. The precision of the method was within 1-8%, while the accuracy was within -1% to 2%. The method was used to the analysis of infusions of twelve green coffees of different geographical origin. It was found that Ca and Mg were leached the easiest, i.e., on average 75% and 70%, respectively. As compared to the mug coffee preparation, the rate of the extraction of elements was increased when infusions were prepared using dripper or Turkish coffee preparation methods. Additionally, it was established that the antioxidant activity of green coffee infusions prepared using the mug coffee preparation was high, 75% on average, and positively correlated with the total content of phenolic compounds and the concentration of Ca in the brew.

Botanical traceability of commercial tannins using the mineral profile and stable isotopes

Commercial tannins are natural polyphenolic compounds extracted from different plant tissues such as gall, the wood of different species and fruit. In the food industry they are mainly used as flavourings and food ingredients, whereas in winemaking they are classified as clarification agents for wine protein stabilisation, although colour stabilisation, metal removal, unpleasant thiol removal and rheological correction are also well-known and desired effects. Due to their particular technical properties and very different costs, the possibility of correct identification of the real botanical origin of tannins can be considered a primary target in oenology research and in fulfilling the technical and economic requirements of the wine industry. For some categories of tannins encouraging results have already been achieved by considering sugar or polyphenolic composition. For the first time this work verifies the possibility of determining the botanical origin of tannins on the basis of the mineral element profile and analysis of the (13) C/(12) C isotopic ratio. One hundred two commercial tannins originating from 10 different botanical sources (grapes, oak, gall, chestnut, fruit trees, quebracho, tea, acacia, officinal plants and tara) were analysed to determine 57 elements and the (13) C/(12) C isotopic ratio, using inductively coupled plasma mass spectrometry and isotope-ratio mass spectrometry, respectively. Forward stepwise discriminant analysis provided good discrimination between the 8 most abundant groups, with 100% correct re-classification. The model was then validated five times on subsets of 10% of the overall samples, randomly extracted, achieving satisfactory results. With a similar approach it was also possible to distinguish toasted and untoasted oak tannins as well as tannins from grape skin and grape seeds.