Fingerprint and authenticity roasted coffees by 1H-NMR: the Brazilian coffee case

Comprehensive analysis of alcohol compounds in commercial instant coffee: A validated 1H NMR spectroscopy study within the Islamic paradigm

Coffee, a globally consumed beverage, has raised concerns in Islamic jurisprudence due to the possible presence of alcohol compounds. This research aims to utilise the sensitivity and reliability of 1H NMR spectroscopy in the quantification of alcohol compounds such as ethanol, furfuryl alcohol, and 5-(hydroxymethyl) furfural (HMF) in commercial instant coffee. Analysis of seven products was performed using advanced 1H Nuclear Magnetic Resonance (NMR) spectroscopy together with Statistical Total Correlation Spectroscopy (STOCSY) and Resolution-Enhanced (RED)-STORM. The analysis of the 100 mg sample revealed the absence of ethanol. The amount of furfuryl alcohol and HMF in the selected commercial instant coffee samples was 0.817 μg and 0.0553 μg, respectively. This study demonstrates the utility of 1H NMR spectroscopy in accurate quantification of trace components for various applications.

1H NMR-based approach to determine the geographical origin and cultivation method of roasted coffee

A comprehensive study of 603 roasted arabica coffee samples using NMR fingerprinting and multivariate data analysis was performed to differentiate coffee samples according to their geographical origin and cultivation method. Both lipophilic and hydrophilic coffee metabolites were recorded using 1H NMR spectroscopy, and principal component analysis followed by linear discriminant analysis (PCA-LDA) was applied. Coffee samples were fist differentiated according to their continents of origin followed by discrimination of coffee samples from Brazil, Ethiopia, and Colombia from coffee samples originating from another continent. Discrimination of coffee samples according to their continent of origin and additional assignment to the countries Brazil and Ethiopia were successful. However, an unambiguous separation of Colombian coffee samples from coffee samples of another continent (other than South America) was not possible. Also, differentiation of organically and conventionally produced coffee samples by using 1H NMR and PCA-LDA was not achieved.

Rapid analysis technologies with chemometrics for food authenticity field: A review

In recent years, the problem of food adulteration has become increasingly rampant, seriously hindering the development of food production, consumption, and management. The common analytical methods used to determine food authenticity present challenges, such as complicated analysis processes and time-consuming procedures, necessitating the development of rapid, efficient analysis technology for food authentication. Spectroscopic techniques, ambient ionization mass spectrometry (AIMS), electronic sensors, and DNA-based technology have gradually been applied for food authentication due to advantages such as rapid analysis and simple operation. This paper summarizes the current research on rapid food authenticity analysis technology from three perspectives, including breeds or species determination, quality fraud detection, and geographical origin identification, and introduces chemometrics method adapted to rapid analysis techniques. It aims to promote the development of rapid analysis technology in the food authenticity field.

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.

Current State-of-the-Art Spectroscopic and Chromatographic Techniques Utilized in Food Authenticity and Food Traceability

Food products are heterogeneous and complex matrices characterized by various compounds and in variable proportions [...].

Anaerobic germination of green coffee beans: A novel strategy to improve the quality of commercial Arabica coffee

This study aimed to improve the brewing quality of commercial Arabica coffee through anaerobic germination. Changes in important compounds and cupping scores of germination roasting coffee with different germination degrees were investigated by 1H NMR, HS-SPME-GC-MS and sensory analysis. Statistical analysis of multivariate analysis results indicated that 6 water-soluble chemical components and 8 volatile chemical components have the potential to be markers of germinated roasting coffee. In addition, germination significantly reduced caffeine content and acrylamide formation in roasted coffee. Sensory analysis according to the Specialty Coffee Association (SCA) cupping protocol demonstrated that anaerobic germination modified flavor attributes, improved the quality, and increased sensory scores. Furthermore, anaerobic sprouting increased fruity descriptors, but over-sprouting did not improve overall attributes while producing both fermentative and vegetable descriptors. Therefore, suitable anaerobic germination of green coffee beans can be used as a new strategy to improve the flavor of commercial Arabica coffee.

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.

Detection of Markers in Green Beans and Roasted Beans of Kalosi-Enrekang Arabica Coffee with Different Postharvest Processing Using LC-MS/MS

Our study is aimed at evaluating the effect of postharvest processing (natural, honey, and fully washed) on the compounds profile in green beans and roasted beans of Kalosi-Enrekang Arabica coffee and determining the marker compounds for each process. These beans were extracted using boiling water, and the extract was analyzed using LC-MS/MS. The results of this work confirmed the significant impact of postharvest processing on compounds in the coffee beans, and each process has a marker compound. Green beans by natural processing have 3 marker compounds, honey processing has 6 marker compounds, and fully washed processing has 2 marker compounds. Meanwhile, roasted beans by natural processing have 4 marker compounds, honey processing has 5 marker compounds, and fully washed processing has 7 marker compounds. In addition, our research identified caffeoyl tyrosine in green beans from natural and honey processing, which was previously only identified in Robusta coffee. These marker compounds can differentiate postharvest processing (natural, honey, and fully washed). These results can also help understand the effect of postharvest processing on the chemical composition of green and roasted beans.

NMR-Based Approaches in the Study of Foods

In this review, the three different NMR-based approaches usually used to study foodstuffs are described, reporting specific examples. The first approach starts with the food of interest that can be investigated using different complementary NMR methodologies to obtain a comprehensive picture of food composition and structure; another approach starts with the specific problem related to a given food (frauds, safety, traceability, geographical and botanical origin, farming methods, food processing, maturation and ageing, etc.) that can be addressed by choosing the most suitable NMR methodology; finally, it is possible to start from a single NMR methodology, developing a broad range of applications to tackle common food-related challenges and different aspects related to foods.

Decaffeination and improvement of taste, flavor and health safety of coffee and tea using mid-infrared wavelength rays

Background

Coffee (Coffea arabica) and tea (Camellia sinensis) are beverages consumed widely across the globe. Flavor enhancement of beverages is the prime interest for consumers and industry, but it is still a major challenge for researchers.

Objectives

In this work, we aimed to enhance the sensory characteristics and lower the caffeine content of tea and coffee by applying 2-6 μm mid-infrared wavelengths emitted through our recently invented Mid-Infrared Generating Atomizer (MIRGA) without creating any adverse effects.

Methodology

Two methods were followed: Direct MIRGA spraying over the packaged coffee or tea powder packets, and direct MIRGA spraying over the liquid coffee or tea. Controls were maintained in both methods. The treated samples were subjected to organoleptic tests by an expert panel and consumers.

Results

This study is supported by comprehensive field trials, including sensory attributes evaluation and laboratory analyses. In coffee, spraying resulted in 8% decaffeination and increase in theobromine and theophylline by 40% and 10-20%, respectively. In tea, caffeine and theobromine increased by 20-25% and 30%, respectively in addition to a 0.6-1.2% increase in thearubigins. A 20-30% lower amount of sprayed coffee or tea powder was required to prepare beverages with regular sensory characteristics. We have proven that the MIRGA technology applied to the products reduced the caffeine content in coffee, rendered them safe to consume, improved the taste and flavor, and induced health benefits. In addition, as the MIRGA platform contributed toward improving the product characteristics, it can also positively impact their price and affordability.

Conclusion

Applications of MIRGA technique and its benefits can be potentially scaled up and utilized for a variety of products used in daily life.

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.

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.

Metabolite Profiles of the Green Beans of Indonesian Arabica Coffee Varieties

The green beans of 3 Indonesian arabica coffee varieties, namely, ateng, buhun, and sigararutang, were analyzed with ¹H NMR-based metabolomics coupled with alpha-glucosidase inhibitory activity assay. These coffees were cultivated in the same geographical conditions. The PLSDA model successfully classified the green coffee beans based on their varieties. To reveal the characteristic metabolites for each coffee variety, S-plot of two-class OPLSDA models was generated and analyzed. Ateng coffee was characterized with trigonelline, sucrose, 5-CQA, and acetic acid. The characteristic metabolites of buhun coffee were citric acid and malic acid. Meanwhile, the most discriminant compound of sigararutang coffee was quinic acid. HCA analysis revealed the lineage relationship of the 3 coffee varieties. Ateng coffee had closer lineage relationship to sigararutang compared to the buhun coffee. Alpha-glucosidase inhibitory activity of the coffee samples did not differ widely. IC₅₀ values of alpha-glucosidase inhibitory activity of ateng, sigararutang, and buhun coffees were 3.01 ± 0.16, 3.14 ± 0.20, and 5.05 ± 0.28 mg/mL, respectively. Although grown in the same geographical conditions, our results revealed that each coffee variety possessed a unique metabolome clarifying the diversity of Indonesian arabica coffees. This study verified that ¹H NMR-based metabolomics is an excellence method for discovering the lineage relationship in the samples with different varieties or cultivars.

Dissecting coffee seeds metabolome in context of genotype, roasting degree, and blending in the Middle East using NMR and GC/MS techniques

With a favored taste and various bioactivities, coffee has been consumed as a daily beverage worldwide. The current study presented a multi-faceted comparative metabolomics approach dissecting commercially available coffee products in the Middle East region for quality assessment and functional food purposes using NMR and GC/MS platforms. NMR metabolites fingerprinting led to identification of 18 metabolites and quantification (qNMR) of six prominent markers for standardization purposes. An increase of β-ethanolamine (MEA) reported for the first time, 5-(hydroxymethyl) furfural (5-HMF), concurrent with a reduction in chlorogenic acid, kahweol, and sucrose levels post roasting as revealed using multivariate data analyses (MVA). The diterpenes kahweol and cafestol were identified in green and roasted Coffea arabica, while 16-O-methyl cafestol in roasted C. robusta. Moreover, GC/MS identified a total of 143 metabolites belonging to 15 different chemical classes, with fructose found enriched in green C. robusta versus fatty acids abundance, i.e., palmitic and stearic acids in C. arabica confirming NMR results. These potential results aided to identify novel quality control attributes, i.e., ethanolamine, for coffee in the Middle East region and have yet to be confirmed in other coffee specimens.

Bioactive Compounds, Sugars, and Sensory Attributes of Organic and Conventionally Produced Courgette (Cucurbita pepo)

Organic agriculture is considered one of the elements of sustainable food production and consumption, mainly due to its limited impact on the natural environment. At the same time, the quality features of organically produced foods, especially sensory attributes and health promoting values, are important factors determining consumers’ interest, and therefore play a key role in the organic sector’s development. The aim of this study was to investigate the sensory characteristics and concentrations of sugars and selected health-promoting bioactive compounds of organic courgette compared to conventionally grown courgette. In addition, untargeted metabolomic analysis of the courgette fruits was performed. The results of this study did not show a significant effect of the horticultural system (organic vs. conventional) on the concentrations of vitamin C, carotenoids, and chlorophylls in the courgette fruits. However, the fruits from the organic systems were significantly richer in sugars when compared to the conventionally cultivated ones (p = 0.038). Moreover, the organic fruits fertilized with manure contained significantly higher amounts of polyphenols, including gallic acid (p = 0.016), chlorogenic acid (p = 0.012), ferulic acid (p = 0.019), and quercetin-3-O-rutinoside (p = 0.020) compared to the conventional fruits. The untargeted analysis detected features significantly differentiating courgette fruits depending on the cultivar and horticultural system. Some significant differences in sensory values were also identified between fruits representing the two cultivars and coming from the horticultural systems compared in the study. Conventional courgettes were characterized by the most intensive peel color and aquosity, but at the same time were the least hard and firm compared to the fruits from the two organic systems. There was also a trend towards higher overall quality of the organically grown fruits. The presented study shows that the organic and conventional courgette fruits differ in a number of quality features which can influence consumers’ health and purchasing choices.

1H HR-MAS NMR-Based Metabolomic Fingerprinting to Distinguish Morphological Similarities and Metabolic Profiles of Maytenus ilicifolia, a Brazilian Medicinal Plant

Maytenus ilicifolia or "Espinheira-Santa" is a renowned Brazilian medicinal plant usually used against intestinal and stomach ulcers. Other species with similar thorny leaves have raised great confusion in order to discern the authentic M. ilicifolia. Misidentifications can lead to product adulteration of authentic M. ilicifolia with other species, which can be found on the Brazilian market. The intake of misclassified herbal products potentially could be fatal, demanding faster reliable fingerprinting-based classification methods. In this study, the use of ¹H HR-MAS NMR metabolomics fingerprinting and principal component analysis (PCA) allowed an evaluation of the authenticity for both collected and commercial M. ilicifolia samples, from the content of the flavanol, (-)-epicatechin (2), by observing variations in metabolic patterns. Plant specimen types from cultivated and natural habitats were analyzed by considering seasonal and topological differences. The interand intraplant topological metabolic profiles were found to be affected by seasonal and/or ecological trends such as sunlight, shade, rain, and the presence of pathogens. Moreover, several commercial samples, labeled as M. ilicifolia, were evaluated, but most of these products were of an inadequate quality.

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.

Integrated 1H NMR fingerprint with NIR spectroscopy, sensory properties, and quality parameters in a multi-block data analysis using ComDim to evaluate coffee blends

Coffee quality is determined by several factors and, in the chemometric domain, the multi-block data analysis methods are valuable to study multiple information describing the same samples. In this industrial study, the Common Dimension (ComDim) multi-block method was applied to evaluate metabolite fingerprints, near-infrared spectra, sensory properties, and quality parameters of coffee blends of different cup and roasting profiles and to search relationships between these multiple data blocks. Data fusion-based Principal Component Analysis was not effective in exploiting multiple data blocks like ComDim. However, when a multi-block was applied to explore the data sets, it was possible to demonstrate relationships between the methods and techniques investigated and the importance of each block or criterion involved in the industrial quality control of coffee. Coffee blends were distinguished based on their qualities and metabolite composition. Blends with high cup quality and lower roasting degrees were generally differentiated from those with opposite characteristics.

The main effects of elevated CO2 and soil-water deficiency on 1H NMR-based metabolic fingerprints of Coffea arabica beans by factorial and mixture design

The metabolic response of Coffea arabica trees in the face of the rising atmospheric concentration of carbon dioxide (CO₂) combined with the reduction in soil-water availability is complex due to the various (bio)chemical feedbacks. Modern analytical tools and the experimental advance of agronomic science tend to advance in the understanding of the metabolic complexity of plants. In this work, Coffea arabica trees were grown in a Free-Air Carbon Dioxide Enrichment dispositive under factorial design (2²) conditions considering two CO₂ levels and two soil-water availabilities. The ¹H NMR mixture design-fingerprinting effects of CO₂ and soil-water levels on beans were strategically investigated using the principal component analysis (PCA), analysis of variance (ANOVA) - simultaneous component analysis (ASCA) and partial least squares-discriminant analysis (PLS-DA). From the ASCA, the CO₂ factor had a significant effect on changing the ¹H NMR profile of fingerprints. The soil-water factor and interaction (CO₂ × soil-water) were not significant. ¹H NMR fingerprints with PCA, ASCA and PLS-DA analysis determined spectral profiles for fatty acids, caffeine, trigonelline and glucose increases in beans from current CO₂, while quinic acid/chlorogenic acids, malic acid and kahweol/cafestol increased in coffee beans from elevated CO₂. PLS-DA results revealed a good classification performance between the significant effect of the atmospheric CO₂ levels on the fingerprints, regardless of the soil-water availabilities. Finally, the PLS-DA model showed good prediction ability, successfully classifying validation data-set of coffee beans collected over the vertical profile of the plants and included several fingerprints of different extracting solvents. The results of this investigation suggest that the association of experimental design, mixture design, PCA, ASCA and PLS-DA can provide accurate information on a series of metabolic changes provoked by climate changes in products of commercial importance, in addition to minimizing the extra work necessary in classic analytical approaches, encouraging the development of similar strategies.

Food authentication in real life: How to link nontargeted approaches with routine analytics?

In times of increasing globalization and the resulting complexity of trade flows, securing food quality is an increasing challenge. The development of analytical methods for checking the integrity and, thus, the safety of food is one of the central questions for actors from science, politics, and industry. Targeted methods, for the detection of a few selected analytes, still play the most important role in routine analysis. In the past 5 years, nontargeted methods that do not aim at individual analytes but on analyte profiles that are as comprehensive as possible have increasingly come into focus. Instead of investigating individual chemical structures, data patterns are collected, evaluated and, depending on the problem, fed into databases that can be used for further nontargeted approaches. Alternatively, individual markers can be extracted and transferred to targeted methods. Such an approach requires (i) the availability of authentic reference material, (ii) the corresponding high-resolution laboratory infrastructure, and (iii) extensive expertise in processing and storing very large amounts of data. Probably due to the requirements mentioned above, only a few methods have really established themselves in routine analysis. This review article focuses on the establishment of nontargeted methods in routine laboratories. Challenges are summarized and possible solutions are presented.

Fully Automated Identification of Coffee Species and Simultaneous Quantification of Furfuryl Alcohol Using NMR Spectroscopy

BACKGROUND

Coffee is a popular beverage with two species, Coffea canephora and C. arabica, being commercially exploited. The quality and commercial value of coffee is dependent on species and processing. C. arabica typically obtains a higher price on the market compared to C. canephora. Coffee beans undergo roasting during processing, resulting in the formation of flavor compounds including furfuryl alcohol which has been classified by the International Agency for Research on Cancer as possibly carcinogenic to humans (Group 2B).

OBJECTIVE

The aim of this study was to identify coffee species and other properties using nuclear magnetic resonance (NMR) spectroscopy, specifically to conduct quantification of the roasting process contaminant furfuryl alcohol.

METHOD

The quantification of furfuryl alcohol was performed from the NMR spectra using the pulse length-based concentration (PULCON) methodology. Prior to NMR analysis, samples were extracted using deuterated chloroform.

RESULTS

Roasting experiments identified the maximum roasting temperature to be the most significant factor in the formation of furfuryl alcohol. Among the coffee species, C. canephora was found to contain a relatively lower amount of furfuryl alcohol compared to C. arabica. The roasting of wet processed coffee resulted in higher contents of furfuryl alcohol. Geographical origin and variety within species had no influence on the furfuryl alcohol content.

CONCLUSION

Validation results show that NMR spectroscopy is fit-for-purpose to obtain targeted information of coffee samples.

HIGHLIGHTS

The PULCON NMR methodology allows a simple, rapid and accurate determination of constituents of coffee.

Identification of markers of thermal processing ("roasting") in aqueous extracts of Coffea arabica L. seeds through NMR fingerprinting and chemometrics

Roasting of Coffea arabica L. seeds gives rise to chemical reactions that produce more than 800 compounds, some being responsible for the desired organoleptic properties for which the beverage called "coffee" is known. In the industry, the "roasting profile," that is, the times and temperatures applied, is key to influence the composition of roasted coffee beans and the flavour of the beverage made from them. The impact of roasting on the chemical composition of coffee has been the subject of numerous studies, including by nuclear magnetic resonance (NMR) spectroscopy. However, the roasting equipment and profiles applied in these studies are often far from real industrial conditions. In this work, the effects of two critical technological parameters of the roasting process, namely, the "development time" (the period of time after the "first crack," a characteristic noise due to seed disruption) and the final roasting temperature on coffee extracts, were investigated. Seeds were roasted at pilot scale according to 13 industrial roasting profiles and extracted in D₂ O. The extracts were analysed by ¹ H NMR experiments. The NMR spectra were compared using (a) quantitative analysis of main signals by successive orders of magnitude and (b) chemometric tools (principal component analysis, partial least squares and sparse-orthogonal partial least squares analysis). This allowed to identify compounds, which may serve as markers of roasting and showed that changes in chemical composition can be detected even for slight change in final temperature (~1°C) or in total roasting time (~25 s).

The potentiality of NMR-based metabolomics in food science and food authentication assessment

In the last years, there was an increasing interest on nuclear magnetic resonance (NMR) spectroscopy, whose applications experienced an exponential growth in several research fields, particularly in food science. NMR was initially developed as the elective technique for structure elucidation of single molecules and nowadays is playing a dominant role in complex mixtures investigations. In the era of the "omics" techniques, NMR was rapidly enrolled as one of the most powerful methods to approach metabolomics studies. Its use in analytical routines, characterized by rapid and reproducible measurements, would provide the identification of a wide range of chemical compounds simultaneously, disclosing sophisticated frauds or addressing the geographical origin, as well as revealing potential markers for other authentication purposes. The great economic value of high-quality or guaranteed foods demands highly detailed characterization to protect both consumers and producers from frauds. The present scenario suggests metabolomics as the privileged approach of modern analytical studies for the next decades. The large potentiality of high-resolution NMR techniques is here presented through specific applications and using different approaches focused on the authentication process of some foods, like tomato paste, saffron, honey, roasted coffee, and balsamic and traditional balsamic vinegar of Modena, with a particular focus on geographical origin characterization, ageing determination, and fraud detection.

Coffee variety, origin and extraction procedure: Implications for coffee beneficial effects on human health

We set up an efficient protocol for the rapid analysis of NMR spectra of green and roasted coffee extracts, enabling the automatic identification and quantification of metabolites in approximately two minutes per spectrum. This method allowed for the metabolic profiling and the subsequent evaluation of the content of bioactive compounds and antioxidant activity of coffee samples, depending on their species (Arabica and Robusta), geographical origin and extraction procedure (hydroalcoholic, espresso and moka). The hydroalcoholic extraction is the most efficient method in terms of yields of low molecular weight compounds (in particular chlorogenic acids), while moka extraction provides the highest amounts of melanoidins. Moreover, that the ratio between health-giving compounds (chlorogenic acids, trigonelline and choline) and caffeine is higher in Arabica coffees. The data collected provide useful insights for the selection of coffee raw material to be used in the preparation of coffee-based dietary supplements, nutraceuticals and functional beverages.

Estimated daily per capita intakes of phenolics and antioxidants from coffee in the Korean diet

This study evaluated the daily per drinker intakes of total phenolics, total flavonoids, and antioxidants from coffee in the Korean diet. Four types of coffee (instant coffee, decaffeinated instant coffee, roasted coffee, and coffee mix) were selected and analyzed. Based on the Korea National Health and Nutrition Examination Survey in 2012, the daily intakes per coffee drinker were estimated to be 348.6 mg gallic acid equivalents for phenolics, 222.5 mg catechin equivalents for flavonoids, and 370.8 mg vitamin C equivalents (DPPH assay) or 546.7 mg vitamin C equivalents (ABTS assay) for antioxidants. Men had higher intakes of instant coffee and coffee mix, while women had a higher intake of roasted coffee. Regarding age categories, over 58% of the coffee consumers were 30-59 years old. This study revealed that, in Korea, approximately half of the people drank about 1.4 cups of roasted coffee or 2.0 cups of instant coffee every day.