Discrimination between arabica and robusta coffee species on the basis of their amino acid enantiomers

The Determination of Triacylglycerols and Tocopherols Using UHPLC-CAD/FLD Methods for Assessing the Authenticity of Coffee Beans

The authenticity of coffee beans was addressed in this study using an analytical method with minimal sample preparation to achieve simple oil extraction and through the implementation of cost-effective equipment. For this purpose, methods using UHPLC with CAD and FLD detectors were applied to detect triglycerides and tocopherols in coffee, respectively. The coffee samples included two main varieties: Arabica from Brazil, Colombia, Ethiopia, and Uganda, as well as the Robusta variety from Cambodia, Guatemala, India, and Vietnam. The samples were either in their green state or subjected to different roasting levels. The used methods successfully distinguished the Arabica and Robusta variants targeted in this study based on their tocopherols and TAG profiles, with the latter being particularly effective for discriminating the origins of the Arabica coffee, while tocopherols excelled at differentiating the origin of the Robusta coffee. TAGs and tocopherols were not affected by the type of roasting, from medium to very dark, suggesting it is possible to distinguish between coffee varieties independently from their degree of roasting. The obtained results hold valuable implications for future research regarding coffee fraud and authenticity.

Effect of different drying airflows and harvest periods on the quality of specialty coffee (Coffea arabica L.)

Coffee is one of the most consumed commercial beverages worldwide, and coffee growers are constantly seeking innovative processing techniques to improve the quality of the final product. This study evaluated the influence of four drying airflows and three harvest periods on the chemical composition of green and roasted specialty coffee beans. The samples were obtained from the Hacienda La Papaya in Loja, Ecuador. Liquid and gas chromatographic techniques characterized the chemical profile of coffee beans, and sensory analysis was performed using the Specialty Coffee Association of America methodology. In total, 49 compounds were described, 29 in green beans and 20 in roasted beans. A significant (p<0.05) effect of the harvest period was observed in all phenolic compounds except for chlorogenic acid. The drying type significantly affected the levels of rutin and trigonelline. In addition, samples from different harvest periods observed significant differences in the levels of the amino acids serine, arginine, phenylalanine and leucine. Similarly, the drying type significantly influenced glycine, alanine, valine and isoleucine levels. For all drying-harvest combinations, the final cupping score was higher than 85/100, as the different drying processes slightly influenced the cupping attributes. Drying with minimal airflow was characterized by a low balance and intense flavor while drying with medium airflow presented a high ratio and soft body. The harvest period and drying type cannot be used as cupping predictors since no clear trends were observed to classify specialty coffee organoleptic attributes. Therefore, other variables involved in specialty coffee processing should be explored to evaluate higher sensitivity toward flavor prediction and innovation. Keywords: chromatographic analysis, Coffea arabica L., sensory analysis, specialty coffee.

Targeted and Non-Targeted HPLC Analysis of Coffee-Based Products as Effective Tools for Evaluating the Coffee Authenticity

Coffee is a very popular beverage worldwide. However, its composition and characteristics are affected by a number of factors, such as geographical and botanical origin, harvesting and roasting conditions, and brewing method used. As coffee consumption rises, the demands on its high quality and authenticity naturally grows as well. Unfortunately, at the same time, various tricks of coffee adulteration occur more frequently, with the intention of quick economic profit. Many analytical methods have already been developed to verify the coffee authenticity, in which the high-performance liquid chromatography (HPLC) plays a crucial role, especially thanks to its high selectivity and sensitivity. Thus, this review summarizes the results of targeted and non-targeted HPLC analysis of coffee-based products over the last 10 years as an effective tool for determining coffee composition, which can help to reveal potential forgeries and non-compliance with good manufacturing practice, and subsequently protects consumers from buying overpriced low-quality product. The advantages and drawbacks of the targeted analysis are specified and contrasted with those of the non-targeted HPLC fingerprints, which simply consider the chemical profile of the sample, regardless of the determination of individual compounds present.

Current strategies to guarantee the authenticity of coffee

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

Accurate Differentiation of Green Beans of Arabica and Robusta Coffee Using Nanofluidic Array of Single Nucleotide Polymorphism (SNP) Markers

Green (unroasted) coffee is one of the most traded agricultural commodities in the world. The Arabica (Coffea arabica L.) and Robusta (Coffea canephora Pierre ex A. Froehner) species are the two main types of coffees for commercial production. In general, Arabica coffee is known to have better quality in terms of sensory characteristics; thus, it has a higher market value than Robusta coffee. Accurate differentiation of green beans of the two species is, therefore, of commercial interest in the coffee industry. Using the newly developed single nucleotide polymorphism (SNP) markers, we analyzed a total of 80 single green bean samples, representing 20 Arabica cultivars and four Robusta accessions. Reliable SNP fingerprints were generated for all tested samples. Unambiguous differentiation between Robusta and Arabica coffees was achieved using multivariate analysis and assignment test. The SNP marker panel and the genotyping protocol are sufficiently robust to detect admixture of green coffee in a high-throughput fashion. Moreover, the multilocus SNP approach can differentiate every single bean within Robusta and 55% of Arabica samples. This advantage, together with the single-bean sensitivity, suggests a significant potential for practical application of this technology in the coffee industry.

Green coffee derived supplements and infusions as a source of polyamines and free amino acids

This work reports on monoamines (MA), diamines (DA) and polyamines (PA) as well as free amino acids (fAA) in nutritional supplements and infusions derived from green coffee beans. Samples were investigated using a ultra-high performance liquid chromatography UV/FLR method, which was validated regarding specificity, linearity, range, precision, accuracy and limits of detection and quantification. Nutritional supplements based on green coffee beans showed large amounts of total amines ranging from 1090 to 2593 mg/kg, with exceptional high levels of spermidine up to 724 mg/kg, and a content of fAA from 4004 to 12,389 mg/kg. Infusions brewed from green coffee beans showed much lower contents of amines (14–17 mg/L) and fAA (78–100 mg/L). However, if the customary edible portion was considered, infusions from green coffee were a mainly better source for MA and PA as well for fAA, compared to nutritional supplements. Tryptamine and tyramine were predominant as MA putrescine as DA, and spermidine as PA, respectively.

Graphic abstract

Heat-induced formation of N,N-dimethylpiperidinium (mepiquat) in Arabica and Robusta coffee

N,N-dimethylpiperidinium (mepiquat) is a new process-induced compound formed from natural constituents during the cooking process. Mepiquat was first found in coffee and cereal products, but its formation mechanism in coffee is still unclear. In the current study, Arabica and Robusta coffee beans were roasted at different temperatures (215, 220, and 230 °C) to study the effect of roasting process on mepiquat formation. The highest mepiquat content, 1,020 µg/kg, was found in dark roast (230 °C) Indonesia Wahana, while 430 µg/kg of mepiquat was detected in medium roast (220 °C) Vietnam Robusta. At the same roasting temperature, higher level of mepiquat was observed in Arabica than in Robusta. In both species, substances related to mepiquat formation, including betaine, choline, trigonelline, lysine, carnitine, pipecolic acid (PipAc), pipecolic acid betaine (PipBet), were also detected. The lysine-based Maillard reaction and decarboxylation in Arabica and Robusta promoted mepiquat formation through the degradation of choline and trigonelline, and the formation of intermediate products. Results from both the model system and selected commercial beans showed that choline and trigonelline had a significant correlation (P < 0.01) with mepiquat formation in Arabica. PRACTICAL APPLICATION: Mepiquat is considered as a new process-induced compound resulting from typical roasting conditions, but its formation mechanism in coffee is still unclear. This work demonstrates the formation mechanism of mepiquat by many precursor substances contained in Arabica and Robusta. It is very important to figure out how mepiquat is ''naturally" present in daily diets, especially in those processed at high temperatures.

Identification and Quantification of Adulterants in Coffee (Coffea arabica L.) Using FT-MIR Spectroscopy Coupled with Chemometrics

Food adulteration is an illegal practice performed to elicit economic benefits. In the context of roasted and ground coffee, legumes, cereals, nuts and other vegetables are often used to augment the production volume; however, these adulterants lack the most important coffee compound, caffeine, which has health benefits. In this study, the mid-infrared Fourier transform spectroscopy (FT-MIR) technique coupled with chemometrics was used to identify and quantify adulterants in coffee (Coffea arabica L.). Coffee samples were adulterated with corn, barley, soy, oat, rice and coffee husks, in proportions ranging from 1–30%. A discrimination model was developed using the soft independent modeling of class analogy (SIMCA) framework, and quantitative models were developed using such algorithms as the partial least squares algorithms with one variable (PLS1) and multiple variables (PLS2) and principal component regression (PCR). The SIMCA model exhibited an accuracy of 100% and could discriminate among all the classes. The quantitative model with the highest performance corresponded to the PLS1 algorithm. The model exhibited an R²c: ≥ 0.99, standard error of calibration (SEC) of 0.39–0.82, and standard error of prediction (SEP) of 0.45–0.94. The developed models could identify and quantify the coffee adulterants, and it was considered that the proposed methodology can be applied to identify and quantify the adulterants used in the coffee industry.

A simple and versatile authenticity assay of coffee products by single-nucleotide polymorphism genotyping

Interspecific single-nucleotide polymorphisms (SNPs) in the rbcL DNA barcode have been strictly validated and adopted as a designed SNP genotyping maker to discriminate between two major coffee species, Coffea arabica and C. canephora, and to estimate the mixing ratio of DNA from C. arabica/C. canephora in this study. The SNP genotyping is applicable to not only green (unroasted) coffee beans, but also processed coffee products (roasted coffee beans and instant coffee powder), in which genomic DNA is degraded, because the genotyping developed in this study requires only 10 copies of 63-bp-long DNA fragments of rbcL gene. The authenticity assay established in this study has several advantages: a high versatility to DNA sample conditions; simple and rapid procedures (only two steps; DNA extraction and SNP genotyping); the feasibility in coffee business for practical use to prevent false advertising and provide quality control. Abbreviations: SNP: single-nucleotide polymorphism; SBS: single base substitution; ISR: intergenic spacer region; INDEL: insertion-deletion.

Authentication of Coffea arabica according to Triacylglycerol Stereospecific Composition

Stereospecific analysis is an important tool for the characterization of lipid fraction of food products. In the present research, an approach to characterize arabica and robusta varieties by structural analysis of the triacylglycerol (TAG) fraction is reported. The lipids were Soxhlet extracted from ground roasted coffee beans with petroleum ether, and the fatty acids (FA) were determined as their corresponding methyl esters. The results of a chemical-enzymatic-chromatographic method were elaborated by a chemometric procedure, Linear Discriminant Analysis (LDA). According to the total and intrapositional FA composition of TAG fraction, the obtained results were able to characterize roasted pure coffee samples and coffee mixtures with 10% robusta coffee added to arabica coffee. Totally correct classified samples were obtained when the TAG stereospecific results of the considered coffee mixture (90 : 10 arabica/robusta) were elaborated by LDA procedure.

Characterization of Fatty Acid, Amino Acid and Volatile Compound Compositions and Bioactive Components of Seven Coffee (Coffea robusta) Cultivars Grown in Hainan Province, China

Compositions of fatty acid, amino acids, and volatile compound were investigated in green coffee beans of seven cultivars of Coffearobusta grown in Hainan Province, China. The chlorogenic acids, trigonelline, caffeine, total lipid, and total protein contents as well as color parameters were measured. Chemometric techniques, principal component analysis (PCA), hierarchical cluster analysis (HCA), and analysis of one-way variance (ANOVA) were performed on the complete data set to reveal chemical differences among all cultivars and identify markers characteristic of a particular botanical origin of the coffee. The major fatty acids of coffee were linoleic acid, palmitic acid, oleic acid, and arachic acid. Leucine (0.84 g/100 g DW), lysine (0.63 g/100 g DW), and arginine (0.61 g/100 g DW) were the predominant essential amino acids (EAAs) in the coffee samples. Seventy-nine volatile compounds were identified and semi-quantified by HS-SPME/GC-MS. PCA of the complete data matrix demonstrated that there were significant differences among all cultivars, HCA supported the results of PCA and achieved a satisfactory classification performance.

Identification of 3-methylbutanoyl glycosides in green Coffea arabica beans as causative determinants for the quality of coffee flavors

The quality of coffee green beans is generally evaluated by the sensory cupping test, rather than by chemical compound-based criteria. In this study, we examined the relationship between metabolites and cupping scores for 36 varieties of beans, using a nontargeted LC-MS-based metabolic profiling technique. The cupping score was precisely predicted with the metabolic information measured using LC-MS. Two markers that strongly correlated with high cupping scores were determined to be isomers of 3-methylbutanoyl disaccharides (3MDs; 0.01-0.035 g/kg of beans) by spectroscopic analyses after purification, and one of them was a novel structure. Further, both the 3MDs were determined to be precursors of 3-methylbutanoic acid that enhance the quality of coffee. The applicability of 3MDs as universal quality indicators was validated with another sample set. It was concluded that 3MDs are the causative metabolites determining beverage quality and can be utilized for green bean selection and as key compounds for improving the beverage quality.

Rapid approach to identify the presence of Arabica and Robusta species in coffee using 1H NMR spectroscopy

NMR spectroscopy was used to verify the presence of Arabica and Robusta species in coffee. Lipophilic extracts of authentic roasted and green coffees showed the presence of established markers for Robusta (16-O-methylcafestol (16-OMC)) and for Arabica (kahweol). The integration of the 16-OMC signal (δ 3.165 ppm) was used to estimate the amount of Robusta in coffee blends with an approximate limit of detection of 1-3%. The method was successfully applied for the analysis of 77 commercial coffee samples (coffee pods, coffee capsules, and coffee beans). Furthermore, principal component analysis (PCA) was applied to the spectra of lipophilic and aqueous extracts of 20 monovarietal authentic samples. Clusters of the two species were observed. NMR spectroscopy can be used as a rapid prescreening tool to discriminate Arabica and Robusta coffee species before the confirmation applying the official method.

On-line process monitoring of coffee roasting by resonant laser ionisation time-of-flight mass spectrometry: bridging the gap from industrial batch roasting to flavour formation inside an individual coffee bean

Resonance-enhanced multiphoton ionisation time-of-flight mass spectrometry (REMPI-TOFMS) enables the fast and sensitive on-line monitoring of volatile organic compounds (VOC) formed during coffee roasting. On the one hand, REMPI-TOFMS was applied to monitor roasting gases of an industrial roaster (1500 kg/h capacity), with the aim of determining the roast degree in real-time from the transient chemical signature of VOCs. On the other hand, a previously developed μ-probe sampling device was used to analyse roasting gases from individual coffee beans. The aim was to explore fundamental processes at the individual bean level and link these to phenomena at the batch level. The pioneering single-bean experiments were conducted in two configurations: (1) VOCs formed inside a bean were sampled in situ, i.e. via a drilled μ-hole, from the interior, using a μ-probe (inside). (2) VOCs were sampled on-line in close vicinity of a single coffee bean's surface (outside). The focus was on VOCs originating from hydrolysis and pyrolytic degradation of chlorogenic acids, like feruloyl quinic acid and caffeoyl quinic acid. The single bean experiments revealed interesting phenomena. First, differences in time-intensity profiles between inside versus outside (time shift of maximum) were observed and tentatively linked to the permeability of the bean's cell walls material. Second, sharp bursts of some VOCs were observed, while others did exhibit smooth release curves. It is believed that these reflect a direct observation of bean popping during roasting. Finally, discrimination between Coffea arabica and Coffea canephora was demonstrated based on high-mass volatile markers, exclusively present in spectra of Coffea arabica.

Chemometric discrimination of genetically modified Coffea arabica cultivars using spectroscopic and chromatographic fingerprints

Multivariate statistical design and principal component analysis (PCA) applied to RP-HPLC-DAD and FTIR spectroscopic data were performed to investigate the fingerprints of four coffee cultivars, traditional red bourbon and three genetically modified cultivars. The design and response surface results showed that extraction dependence on solvent composition of one of the genetically modified cultivars, IAPAR 59, was very similar to that found for the red bourbon standard. PCA of the FTIR spectra obtained from all the simplex centroid design mixtures indicated that the 1:1 binary ethanol-dichloromethane solution resulted in the best separation of the four cultivars. The IPR 108 cultivar has more intense vibrational bands in the 3200-3,600 cm(-1) and 1100-1,600 cm(-1) regions indicating higher acid and fat levels than those of the other cultivars. The UV absorptions close to 275 nm of the RP-HPLC-DAD spectra are correlated with the strengths of the infrared absorptions between 3400 and 3,460 cm(-1) and can be explained by varying caffeine concentrations in the four cultivars.

Characterization of chemical composition of bee pollen in China

Bee pollen has been praised for its good nutrition and therapeutic values. China is the largest producer in the world. Twelve common varieties of monofloral bee pollen collected from China's main producing regions were selected for nutritional composition analysis, including proximate contents, dietary fibers, amino acid distribution, fatty acid composition, and mineral elements. The proximate compositions mostly met the specifications regulating pollen load quality of China. Proline and glutamic acids were found to be the predominant amino acids in the form of both total amino and free amino acids. Lysine was the relative limiting amino acid. The percentage of total essential amino acids (TEAA) to total amino acids (TAA) reached the nutrition recommendation of the Food and Agricultural Organization (FAO). The major fatty acids, presented as mean values, were C18:3 (25.1%), C16:0 (19.6%), C18:1 (17.3%), C18:2 (8.78%), C22:0 (4.07%), and C18:0 (2.96%) acids. The proportions of C18:3 were generally higher than those of C18:2, and the ratio of total unsaturated fatty acids (TUS) to total saturated fatty acids (TS) was >1.0, except for Nelumbo nucifera Gaertn. pollen for the characteristic absence of C18:3 acids. High levels of beneficial elements such as K, Ca, Mg, Zn, Fe, Mn. and Cu were observed in pollen samples. The contents of detrimental trace elements of Cd, Pb, and Hg were primarily lower or not detected. However, more attention should be paid to a large amount of Al, with a concentration of >100 mg/kg DW in most samples. There were some significant differences between samples. On the whole, the Chinese bee pollen was evaluated as a good complement to diet.

Application of chemometrics in authentication of herbal medicines: a review

INTRODUCTION

Herbal medicines (HM) and their preparations have been widely used for hundreds of years all over the world. However, they have not been officially recognised due to a lack of adequate or accepted research methodology for their evaluation.

OBJECTIVE

To present a concise overview of the recent applications of chemometrics in solving the ambiguity of herbal medicine authentication during the last two decades.

METHODOLOGY

Studies involving the applications of chemometric analysis in combination with different analytical methods were classified according to the method of analysis used including chromatographic (HPLC, GC and CE), spectroscopic (NMR, IR, UV and ICP) and genetic analysis (RAPD). The purpose of each of these studies was classified into one of three main categories: taxonomic discrimination, quality assessment or classification between plants of different geographic origins.

RESULTS

This review comprises over 150 studies, covering the past two decades, emphasising the significance of chemometric methods in the discrimination of many herbs from closely related species and from adulterants, based on the principal bioactive components and phytochemical diversity. Furthermore, the differentiation between varieties and hybrids was achieved in addition to the prediction of the active components by quantitative methods of analysis. Discrimination according to geographical origin and localities, processing methods, DNA profiling and metabolomics were also efficiently investigated.

CONCLUSION

Chemometric methods have provided an efficient and powerful tool for the quality control and authentication of different herbs.

(13)C NMR-based metabolomics for the classification of green coffee beans according to variety and origin

(13)C NMR-based metabolomics was demonstrated as a useful tool for distinguishing the species and origins of green coffee bean samples of arabica and robusta from six different geographic regions. By the application of information on (13)C signal assignment, significantly different levels of 14 metabolites of green coffee beans were identified in the classifications, including sucrose, caffeine, chlorogenic acids, choline, amino acids, organic acids, and trigonelline, as captured by multivariate analytical models. These studies demonstrate that the species and geographical origin can be quickly discriminated by evaluating the major metabolites of green coffee beans quantitatively using (13)C NMR-based metabolite profiling.

Dipstick test for DNA-based food authentication. Application to coffee authenticity assessment

This paper reports DNA-based food authenticity assays, in which species identification is accomplished by the naked eye without the need of specialized instruments. Strongly colored nanoparticles (gold nanoparticles) are employed as reporters that enable visual detection. Furthermore, detection is performed in a low-cost, disposable, dipstick-type device that incorporates the required reagents in dry form, thereby avoiding multiple pipetting and incubation steps. Due to its simplicity, the method does not require highly qualified personnel. The procedure comprises the following steps: (i) PCR amplification of the DNA segment that flanks the unique SNP (species marker); (ii) a 15 min extension reaction in which DNA polymerase extends an allele-specific primer only if it is perfectly complementary with the target sequence; (iii) detection of the products of the extension reaction within a few minutes by the naked eye employing the dipstick. No purification is required prior to application of the extension products to the dipstick. The method is general and requires only a unique DNA sequence for species discrimination. The only instrument needed is a conventional thermocycler for PCR, which is common equipment in every DNA laboratory. As a model, the method was applied to the discrimination of Coffea robusta and arabica species in coffee authenticity assessment. As low as 5% of Robusta coffee can be detected in the presence of Arabica coffee.

Quantification of the Robusta fraction in a coffee blend via Raman spectroscopy: proof of principle

Among the 100 different known Coffea species, Coffea arabica L. (Arabica) and Coffea canephora Pierre (Robusta) are the only two of commercial interest. They differ in a range of agronomic, genetic, and chemical properties. Due to the significant price difference between Arabica and Robusta, there is an economic incentive to illicitly replace Arabica with Robusta. Therefore, it is crucial to have accurate methods to determine the Robusta-to-Arabica-ratio in blends. This paper presents the proof of principle of a new and fast approach to determine the Robusta fraction in a blend based on Raman spectroscopy. The oils of two references (a pure Robusta and pure Arabica coffee) and six blends thereof consisting of different Robusta and Arabica fractions were extracted using a Soxhlet system. The solutes were analyzed by means of Raman spectroscopy without further workup. Using the intensity ratio between two Raman peaks, one characteristic for kahweol and one characteristic for fatty acids, allowed determinination of the Robusta content in a given mixture. The intensity ratio is linearly dependent on the Robusta content of the compound. Above a Robusta content of 75 wt %, kahweol was not detectable. The Raman data are in agreement with results obtained from the very time-consuming multistep DIN 10777 procedures based on HPLC.

Feasibility study on chemometric discrimination of roasted Arabica coffees by solvent extraction and Fourier transform infrared spectroscopy

In this feasibility study, Fourier transform infrared (FTIR) spectroscopy and chemometric analysis were adopted to discriminate coffees from different geographical origins and of different roasting degrees. Roasted coffee grounds were extracted using two methods: (1) solvent alone (dichloromethane, ethyl acetate, hexane, acetone, ethanol, or acetic acid) and (2) coextraction using a mixture of equal volume of the solvent and water. Experiment results showed that the coextraction method resulted in cleaner extract and provided a greater amount of spectral information, which was important for sample discrimination. Principal component analysis of infrared spectra of ethyl acetate extracts for dark and medium roast coffees showed separated clusters according to their geographical origins and roast degrees. Classification models based on soft independent modeling of class analogy analysis were used to classify different coffee samples. Coffees from four different countries, which were roasted to dark, were 100% correctly classified when ethyl acetate was used as a solvent. The FTIR-chemometric technique developed here may serve as a rapid tool for discriminating geographical origin of roasted coffees. Future studies involving green coffee beans and the use of larger sample size are needed to further validate the robustness of this technique.

Discrimination of green arabica and Robusta coffee beans by Raman spectroscopy

This paper presents an approach that may be applied as an accurate and rapid tool for classifying coffee beans on the basis of the specific kahweol content. Using Fourier-transform Raman spectroscopy with 1064 nm excitation it is possible to monitor the characteristic Raman bands of kahweol in green coffee beans without chemical and physical processing of the beans. The procedure was optimized on the basis of 83 and 125 measurements of whole and ground beans, respectively, using coffee samples of two different species, Coffea arabica L. and Coffea canephora L. (var. Robusta), and different origins (Asia, Africa, and South America). The relative contribution of the kahweol in individual beans can be determined quantitatively by means of a component analysis of the spectra, yielding a spectral kahweol index (σka) that is proportional to the relative content of kahweol in a coffee bean. The reproducibility of the spectroscopic measurement and analysis was found to be 3.5%. Individual beans of the same type and origin reveal a scattering of the σka values. Nevertheless, an unambiguous distinction between Arabica and Robusta samples is possible on the basis of single-bean measurements as the σka values are greater than and less than 10 for Arabica and Robusta coffees, respectively. Measurements of whole and ground beans afforded very similar results, despite the heterogeneous distribution of kahweol within a bean. Unlike conventional analytical techniques, the single-bean sensitivity of the present approach may also allow for a rapid detection of unwanted admixtures of low-value Robusta coffee to high-quality and more expensive Arabica coffee.

Botanical and geographical characterization of green coffee (Coffea arabica and Coffea canephora): chemometric evaluation of phenolic and methylxanthine contents

Green coffee beans of the two main commercial coffee varieties, Coffea arabica (Arabica) and Coffea canephora (Robusta), from the major growing regions of America, Africa, Asia, and Oceania were studied. The contents of chlorogenic acids, cinnamoyl amides, cinnamoyl glycosides, free phenolic acids, and methylxanthines of green coffee beans were analyzed by liquid chromatography coupled with UV spectrophotometry to determine their botanical and geographical origins. The analysis of caffeic acid, 3-feruloylquinic acid, 5-feruloylquinic acid, 4-feruloylquinic acid, 3,4-dicaffeoylquinic acid, 3-caffeoyl-5-feruloylquinic acid, 3-caffeoyl-4-feruloylquinic acid, 3-p-coumaroyl-4-caffeoylquinic acid, 3-caffeoyl-4-dimethoxycinnamoylquinic acid, 3-caffeoyl-5-dimethoxycinnamoylquinic acid, p-coumaroyl-N-tryptophan, feruloyl-N-tryptophan, caffeoyl-N-tryptophan, and caffeine enabled the unequivocal botanical characterization of green coffee beans. Moreover, some free phenolic acids and cinnamate conjugates of green coffee beans showed great potential as means for the geographical characterization of coffee. Thus, p-coumaroyl-N-tyrosine, caffeoyl-N-phenylalanine, caffeoyl-N-tyrosine, 3-dimethoxycinnamoyl-5-feruloylquinic acid, and dimethoxycinnamic acid were found to be characteristic markers for Ugandan Robusta green coffee beans. Multivariate data analysis of the phenolic and methylxanthine profiles provided preliminary results that allowed showing their potential for the determination of the geographical origin of green coffees. Linear discriminant analysis (LDA) and partial least-squares discriminant analysis (PLS-DA) provided classification models that correctly identified all authentic Robusta green coffee beans from Cameroon and Vietnam and 94% of those from Indonesia. Moreover, PLS-DA afforded independent models for Robusta samples from these three countries with sensitivities and specificities of classifications close to 100% and for Arabica samples from America and Africa with sensitivities of 86 and 70% and specificities to the other class of 90 and 97%, respectively.

Comparison of the effectiveness of fatty acids, chlorogenic acids, and elements for the chemometric discrimination of coffee (Coffea arabica L.) varieties and growing origins

The objective of this work was to compare the effectiveness of three chemical families, namely, chlorogenic acids, fatty acids, and elements, for the discrimination of Arabica varieties (traditional versus modern introgressed lines) and potential terroirs within a given coffee-growing area. The experimental design included three Colombian locations in full combination with five (one traditional and four introgressed) Arabica varieties and two field replications. Chlorogenic acids, fatty acids, and elements were analyzed in coffee bean samples by HPLC, GC, and ICP-AES, respectively. Principal component analysis and discriminant analysis were carried out to compare the three methods. Although elements provided an excellent classification of the three locations studied, this chemical class was useless for Arabica variety discrimination. Chlorogenic acids gave satisfactory results, but fatty acids clearly offered the best results for the determination of both varieties and environments, with very high percentages of correct classification (79 and 90%, respectively).

Gamma-tocopherol as a marker of Brazilian coffee (Coffea arabica L.) adulteration by corn

The adulteration of coffee with cereals, coffee twigs, etc. is apparently widespread in Brazil with corn being considered the most widely used. No adequate methods are available to detect such contamination in commercial coffee. A new method, based on high-performance liquid chromatography (HPLC) tocopherol determination was developed to detect coffee adulteration by corn. Percentages of alpha-, beta-, gamma-, and delta-tocopherol determined by HPLC in six coffee varieties were 29.0, 61.7, 3.3, and 6.0, respectively. Similar values were obtained in six popular coffee brands. The percentages of alpha-, gamma-, and delta-tocopherol in six corn samples were 3.6, 91.3, and 5.1, respectively. These differences could be applied to detect corn in a pure coffee sample intentionally contaminated with corn with the best result obtained with gamma-tocopherol. With this methodology, one coffee brand was apparently adulterated (8.9%), most likely with corn. Tocopherol fingerprinting offers the potential to detect adulteration.

Factors influencing the norharman and harman contents in espresso coffee

Espresso coffee (EC) brews were analyzed for beta-carboline [norharman (NH) and harman (H)] contents, by RP-HPLC with fluorescence detection. The influence of the coffee species (arabica or robusta), the roast degree, and the brew length was studied. The results show that the content of NH and H in EC is dependent primarily on the coffee species, followed by brew length. The roast degree has only a minor influence on the final content of NH and H in EC. When compared with other coffee brews, EC has an amount of these beta-carbolines (in micrograms per liter) similar to that of mocha coffee, both being more concentrated than filter and press-pot coffees. Therefore, the consumer's preferences will determine the amount of NH and H ingested daily. For the caffeinated 30 mL of EC, the arabica coffees contain about 4.08 microg of NH and 1.54 microg of H. Commercial blends (usually with a maximum of 30% robusta) range from the cited arabica values to 10.37 microg of NH and 4.35 microg of H.

Mixture resolution according to the percentage of robusta variety in order to detect adulteration in roasted coffee by near infrared spectroscopy

Near infrared spectroscopy (NIRS), combined with multivariate calibration methods, has been used to quantify the robusta variety content of roasted coffee samples, as a means for controlling and avoiding coffee adulteration, which is a very important issue taking into account the great variability of the final sale price depending on coffee varietal origin. In pursuit of this aim, PLS regression and a wavelet-based pre-processing method that we have recently developed called OWAVEC were applied, in order to simultaneously operate two crucial pre-processing steps in multivariate calibration: signal correction and data compression. Several pre-processing methods (mean centering, first derivative and two orthogonal signal correction methods, OSC and DOSC) were additionally applied in order to find calibration models with as best a predictive ability as possible and to evaluate the performance of the OWAVEC method, comparing the respective quality of the different regression models constructed. The calibration model developed after pre-processing derivative spectra by OWAVEC provided high quality results (0.79% RMSEP), the percentage of robusta variety being predicted with a reliability notably better than that associated with the models constructed from raw spectra and also from data corrected by other orthogonal signal correction methods, and showing a higher model simplicity.

Authentication of coffee by means of PCR-RFLP analysis and lab-on-a-chip capillary electrophoresis

Coffee is one of the most important world food commodities, commercial trade consisting almost entirely of Arabica and Robusta varieties. The former is considered to be of superior quality and thus attracts a premium price. Methods to differentiate these coffee species could prove to be beneficial for the detection of either deliberate or accidental adulteration. This study describes a molecular genetics approach to differentiate Arabica and Robusta coffee beans. This employs a Polymerase Chain Reaction-Restriction Fragment Length Polymorphism to monitor a single nucleotide polymorphism within the chloroplastic genome. Samples were analyzed with a lab-on-a-chip capillary electrophoresis system. Coffee powder mixtures were analyzed with this technique, displaying a 5% limit of detection. The plastid copy number was found to be relatively constant across a wide range of bean samples, suggesting that this methodology can also be employed for the quantification of any adulteration of Arabica with Robusta beans.

Free and conjugated biogenic amines in green and roasted coffee beans

This work reports the composition of arabica and robusta coffees in terms of biogenic amines. The analyses were conducted before and after acid hydrolysis with the aim of the determining both free and conjugated forms in green and roasted coffee beans. The amines (putrescine, cadaverine, serotonin, tyramine, spermidine, and spermine) were determined by reverse-phase high-performance liquid chromatography (RP-HPLC) after derivatization with dansyl chloride. Multivariate analyses were applied in order to evaluate the possible use of these amines as chemical descriptors for arabica and robusta coffees. It was found that putrescine, the main biogenic amine present in the green beans, could be used in the discrimination of the referred species. There is also some evidence that these compounds can be used for discrimination between green coffees subjected to different postharvest processes and that tyramine can be considered a chemical marker for Angolan robustas. The variations in biogenic amine levels after roasts is also discussed, but the statistical significance for species discrimination is reduced.