High-performance liquid chromatography with fluorescence detection fingerprints as chemical descriptors to authenticate the origin, variety and roasting degree of coffee by multivariate chemometric methods

Bioactive compounds in coffee and their role in lowering the risk of major public health consequences: A review

This article addresses the bioactive components in coffee aroma, their metabolism, and the mechanism of action in lowering the risk of various potential health problems. The main bioactive components involved in the perceived aroma of coffee and its related health benefits are caffeine, chlorogenic acid (CGA), trigonelline, diterpenes, and melanoids. These compounds are involved in various physiological activities. Caffeine has been shown to have anticancer properties, as well as the ability to prevent the onset and progression of hepatocellular carcinoma and to be anti-inflammatory. CGA exhibits antioxidant action and is implicated in gut health, neurodegenerative disease protection, type 2 diabetes, and cardiovascular disease prevention. Furthermore, together with diterpenes, CGA has been linked to anticancer activity. Trigonelline, on the other side, has been found to lower oxidative stress by increasing antioxidant enzyme activity and scavenging reactive oxygen species. It also prevents the formation of kidney stones. Diterpenes and melanoids possess anti-inflammatory and antioxidant properties, respectively. Consuming three to four cups of filtered coffee per day, depending on an individual's physiological condition and health status, has been linked to a lower risk of several degenerative diseases. Despite their health benefits, excessive coffee intake above the recommended daily dosage, calcium and vitamin D deficiency, and unfiltered coffee consumption all increase the risk of potential health concerns. In conclusion, moderate coffee consumption lowers the risk of different noncommunicable diseases.

Liquid Chromatography-High-Resolution Mass Spectrometry (LC-HRMS) Fingerprinting and Chemometrics for Coffee Classification and Authentication

Nowadays, the quality of natural products is an issue of great interest in our society due to the increase in adulteration cases in recent decades. Coffee, one of the most popular beverages worldwide, is a food product that is easily adulterated. To prevent fraudulent practices, it is necessary to develop feasible methodologies to authenticate and guarantee not only the coffee's origin but also its variety, as well as its roasting degree. In the present study, a C18 reversed-phase liquid chromatography (LC) technique coupled to high-resolution mass spectrometry (HRMS) was applied to address the characterization and classification of Arabica and Robusta coffee samples from different production regions using chemometrics. The proposed non-targeted LC-HRMS method using electrospray ionization in negative mode was applied to the analysis of 306 coffee samples belonging to different groups depending on the variety (Arabica and Robusta), the growing region (e.g., Ethiopia, Colombia, Nicaragua, Indonesia, India, Uganda, Brazil, Cambodia and Vietnam), and the roasting degree. Analytes were recovered with hot water as the extracting solvent (coffee brewing). The data obtained were considered the source of potential descriptors to be exploited for the characterization and classification of the samples using principal component analysis (PCA) and partial least squares-discriminant analysis (PLS-DA). In addition, different adulteration cases, involving nearby production regions and different varieties, were evaluated by pairs (e.g., Vietnam Arabica-Vietnam Robusta, Vietnam Arabica-Cambodia and Vietnam Robusta-Cambodia). The coffee adulteration studies carried out with partial least squares (PLS) regression demonstrated the good capability of the proposed methodology to quantify adulterant levels down to 15%, accomplishing calibration and prediction errors below 2.7% and 11.6%, respectively.

Metabolomics: A suitable foodomics approach to the geographical origin traceability of Ethiopian Arabica specialty coffees

Coffee arabica, originated in Ethiopia, is considered a quality bean for its high sensory qualities, and has a special price in the world coffee market. The country is a pool of genetic diversity for Arabica coffee, and coffee from different regions has a distinct flavor profile. Their exceptional quality is attributed to their genetic diversity, favorable environmental conditions, and agroforestry-based production system. However, the country still needs to benefit from its single-origin product due to a lack of appropriate traceability information to register for its geographical indication. Certification of certain plants or plant-derived products emerged to inform consumers about their exceptional qualities due to their geographical origin and protect the product from fraud. The recently emerging foodomics approaches, namely proteomics, genomics, and metabolomics, are reported as suitable means of regional agri-food product authentication and traceability. Particularly, the metabolomics approach provides truthful information on product traceability. Despite efforts by some researchers to trace the geographical origin of Ethiopian Arabica coffees through stable isotope and phenolic compound profiling and elemental analysis, foodomics approaches are not used to trace the geographical origin of Arabica specialty coffees from various parts of the country. A metabolomics-based traceability system that demonstrates the connection between the exceptional attributes of Ethiopian Arabica specialty coffees and their geographic origin is recommended to maximize the benefit of single-origin coffees.

Specialty and high-quality coffee: discrimination through elemental characterization via ICP-OES, ICP-MS, and ICP-MS/MS of origin, species, and variety

BACKGROUND

This study aimed to establish the elemental profiling and origin combined with the genetic asset of coffee samples collected from major coffee-producing countries. A total of 76 samples were analysed for 41 elements using inductively coupled plasma-optical emission spectroscopy (ICP-OES), inductively coupled plasma-mass spectrometry (ICP-MS), and inductively coupled plasma-triple quadrupole mass spectrometry (ICP-MS/MS). The mineral composition of the silver skin detachment during the roasting process was also evaluated to verify the loss of minerals during roasting, differences in composition with beans, and between species.

RESULTS

Application of linear discriminant analysis provided models with an accuracy of 93.3% for continents, 97.8% for countries of cultivation, and 100% for species. Discrimination between Arabica, Canephora coffee, and Eugenoides, and different varieties of Arabica species were identified in both models with calcium (Ca), barium (Ba), cadmium (Cd), rubidium (Rb), and strontium (Sr) as significant discriminant elements. Rb, Sr, sulphur (S), and thulium (Tm) were significant discriminant elements in both models for geographical distinction at different scales. Most of the elements had significantly higher values in silver skin than those in roasted coffee at different magnitudes, with exceptions of P and Rb.

CONCLUSION

In summary, determination of mineral elements, processed by multivariate statistical analysis, was demonstrated to be discriminant for different coffee species. Linear discriminant analysis of the elemental analysis of samples from the seven major producing countries provided a reliable prediction model. Elemental analysis of major and minor elements is relatively easy and can be used together with other traceability systems and sensory evaluations to authenticate the origin of roasted coffee, different species, and varieties. © 2023 The Authors. Journal of The Science of Food and Agriculture published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Preliminary Analysis of Unsaturated Fatty Acid Profiles of Coffea arabica L., in Samples with a Denomination of Origin and Speciality of Oaxaca, Mexico

In February 2020, Coffea arabica L. grown on the coast and in the Southern Sierra Madre of the state of Oaxaca, Mexico obtained the denomination of origin. Which does not have data on color and chemical composition, the first associated with the degree of roasting and the second with lipids (17-18%), as the group of compounds responsible, in part, for flavor, consistency, and may contribute to health benefits. In the present work, color was determined on the CIE L*a*b* scale and the unsaturated fatty acids by Nuclear Magnetic Resonance (NMR) of ¹H and ¹³C in samples of medium roasted specialty coffee from the "Pluma" coffee-growing region, Oaxaca, Mexico. The average value of L* luminosity in ground coffee was 42.1 ± 0.1 reported for a light roast. Unsaturated fatty acids were quantified from the lipid fraction of the gr₁ ound grain by NMR ¹H and ¹³C, obtaining on average the highest abundance of linoleic (41.7 ± 0.5 by ₁ H and 41.24 ± 0.5 by ¹³C), followed by oleic (9.2 ± 0.2 by ¹H and 7.4 ± 0.2 by ¹³C) and linolenic (1.5 ± 0.1 by H and 1.1 ± 0.2 by ¹³C). This study indicates that ¹H and ¹³C NMR spectroscopy is a useful tool for the quantification of linolenic, linoleic, and oleic fatty acids by the method of key signal shifts of these acids found in lipid samples in roasted coffee grains.

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.

Detection and Quantitation of Adulterated Paprika Samples Using Second-Order HPLC-FLD Fingerprints and Chemometrics

Paprika is a widely consumed spice in the world and its authentication has gained interest considering the increase in adulteration cases in recent years. In this study, second-order fingerprints acquired by liquid chromatography with fluorescence detection (HPLC-FLD) were first used to detect and quantify adulteration levels of Chinese paprika samples. Six different adulteration cases, involving paprika production region, cultivar, or both, were investigated by pairs. Two strategies were employed to reduce the data matrices: (1) chromatographic fingerprints collected at specific wavelengths and (2) fusion of the mean data profiles in both spectral and time dimensions. Afterward, the fingerprint data with different data orders were analyzed using partial least squares (PLS) and n-way partial least squares (N-PLS) regression models, respectively. For most adulteration cases, N-PLS based on second-order fingerprints provided the overall best quantitation results with cross-validation and prediction errors lower than 2.27% and 20.28%, respectively, for external validation sets with 15-85% adulteration levels. To conclude, second-order HPLC-FLD fingerprints coupled with chemometrics can be a promising screening technique to assess paprika quality and authenticity in the control and prevention of food frauds.

Metabolomics-Based Approach for Coffee Beverage Improvement in the Context of Processing, Brewing Methods, and Quality Attributes

Coffee is a worldwide beverage of increasing consumption, owing to its unique flavor and several health benefits. Metabolites of coffee are numerous and could be classified on various bases, of which some are endogenous to coffee seeds, i.e., alkaloids, diterpenes, sugars, and amino acids, while others are generated during coffee processing, for example during roasting and brewing, such as furans, pyrazines, and melanoidins. As a beverage, it provides various distinct flavors, i.e., sourness, bitterness, and an astringent taste attributed to the presence of carboxylic acids, alkaloids, and chlorogenic acids. To resolve such a complex chemical makeup and to relate chemical composition to coffee effects, large-scale metabolomics technologies are being increasingly reported in the literature for proof of coffee quality and efficacy. This review summarizes the applications of various mass spectrometry (MS)- and nuclear magnetic resonance (NMR)-based metabolomics technologies in determining the impact of coffee breeding, origin, roasting, and brewing on coffee chemical composition, and considers this in relation to quality control (QC) determination, for example, by classifying defected and non-defected seeds or detecting the adulteration of raw materials. Resolving the coffee metabolome can aid future attempts to yield coffee seeds of desirable traits and best flavor types.

How Does LC/MS Compare to UV in Coffee Authentication and Determination of Antioxidant Effects? Brazilian and Middle Eastern Coffee as Case Studies

Coffee is a popular beverage owing to its unique flavor and diverse health benefits. The current study aimed at investigating the antioxidant activity, in relation to the phytochemical composition, of authenticated Brazilian green and roasted Coffea arabica and C. robusta, along with 15 commercial specimens collected from the Middle East. Ultra-high-performance liquid chromatography coupled to high-resolution mass spectrometry (UHPLC-ESI-HRMS) and UV spectrometry were employed for profiling and fingerprinting, respectively. With the aid of global natural product social molecular networking (GNPS), a total of 88 peaks were annotated as belonging to different chemical classes, of which 11 metabolites are reported for the first time in coffee seeds. Moreover, chemometric tools showed comparable results between both platforms, with more advantages for UV in the annotation of roasting products, suggesting that UV can serve as a discriminative tool. Additionally, antioxidant assays coupled with the UHPLC-ESI-HRMS dataset using partial least-squares discriminant analysis (PLS-DA) demonstrated that caffeoylquinic acid and caffeine were potential antioxidant markers in unroasted coffee versus dicaffeoyl quinolactone and melanoidins in roasted coffee. The study presents a multiplex metabolomics approach to the quality control of coffee, one of the most consumed beverages.

Chemical ingredients characterization basing on 1H NMR and SHS-GC/MS in twelve cultivars of Coffea arabica roasted beans

This work aimed to study the composition differences of roasted beans between 12 coffee cultivars (Catimor 7963, HIBRIDO DE TIMOR, Ruiru 11, Castillo, DTARI 296, DTARI 366, DTARI 392, DTARI 585, SL28, SL34, Catuai-Amarelo and Catuai-Vermelho) from Bourbon-Typica group and Introgressed group under subtropical humid monsoon climate. The water-soluble compounds of roasted coffee beans were characterized by proton nuclear magnetic resonance spectroscopy (¹H NMR), and the aroma components were analyzed by static headspace gas chromatography mass spectrometry (SHS-GC/MS). In total, 20 water soluble compounds and 43 volatile compounds were identified. Both water-soluble and volatile compounds are rich in acidic substances, and the content varied depending on the cultivars. Furthermore, principal component analysis (PCA) clustered 12 coffee cultivars into four groups. The four different chemically defined clusters of Arabica cultivars produced by chemical differences cannot reflect the traditional grouping based on introgressed, and it is one-sided to judge coffee quality based on lineage. These results give further insight into the quality characteristics of different coffee cultivars, which is of great significance for guiding the adjustment of cultivars' structure and the breeding of new cultivars.

Authenticity Assessment and Fraud Quantitation of Coffee Adulterated with Chicory, Barley, and Flours by Untargeted HPLC-UV-FLD Fingerprinting and Chemometrics

Coffee, one of the most popular drinks around the world, is also one of the beverages most susceptible of being adulterated. Untargeted high-performance liquid chromatography with ultraviolet and fluorescence detection (HPLC-UV-FLD) fingerprinting strategies in combination with chemometrics were employed for the authenticity assessment and fraud quantitation of adulterated coffees involving three different and common adulterants: chicory, barley, and flours. The methodologies were applied after a solid–liquid extraction procedure with a methanol:water 50:50 (v/v) solution as extracting solvent. Chromatographic fingerprints were obtained using a Kinetex^® C18 reversed-phase column under gradient elution conditions using 0.1% formic acid aqueous solution and methanol as mobile phase components. The obtained coffee and adulterants extract HPLC-UV-FLD fingerprints were evaluated by partial least squares regression-discriminants analysis (PLS-DA) resulting to be excellent chemical descriptors for sample discrimination. One hundred percent classification rates for both PLS-DA calibration and prediction models were obtained. In addition, Arabica and Robusta coffee samples were adulterated with chicory, barley, and flours, and the obtained HPLC-UV-FLD fingerprints subjected to partial least squares (PLS) regression, demonstrating the feasibility of the proposed methodologies to assess coffee authenticity and to quantify adulteration levels (down to 15%), showing both calibration and prediction errors below 1.3% and 2.4%, respectively.

Assessment of paprika geographical origin fraud by high-performance liquid chromatography with fluorescence detection (HPLC-FLD) fingerprinting

Paprika production under the protected designation of origin (PDO) standardized procedures leads to more quality products. However, it is also related to higher retail prices, making them susceptible to adulteration with low-quality paprika or its agricultural origin's mislabeling. Therefore, in this study, high-performance liquid chromatography with fluorescence detection (HPLC-FLD) fingerprints, strongly related to phenolic acid and polyphenolic compounds, were proposed as chemical markers to assess the classification of paprika from five European regions (three Spanish PDO, Hungary, and the Czech Republic), through a classification decision tree constructed by partial least squares regression-discriminant analysis (PLS-DA) models. After external validation, an excellent classification accuracy of 97.9% was achieved. Moreover, the chromatographic fingerprints were also proposed to detect and quantitate two different paprika geographical origin blend scenarios by partial least squares (PLS) regression. Low external validation and prediction errors -with values below 1.6 and 10.7%, respectively- were obtained.