Constitutive Defense Strategy of Coffee Under Field Conditions: A Comparative Assessment of Resistant and Susceptible Cultivars to Rust.

Coffea arabica is the most economically important coffee species worldwide. However, its production is severely limited by diseases such as rust. The mechanisms underlying constitutive defense responses in coffee are still poorly understood, compared with induced defense mechanisms. We aimed to characterize constitutive defense responses of thirteen cultivars of C. arabica. Cultivars were classified under field conditions according to the level of resistance to rust: resistant (R), moderately resistant (MR), and susceptible (S). Based on this classification, the stability of eight reference genes (RGs) was evaluated. The most stable RGs were EF1α, APT1, and 24S. We also evaluated the expression of CaWRKY1, CaPAL1, CaCAD1, and CaPOX1, and activities of PAL, CAD, and POX, which are involved in lignin biosynthesis, and leaf content of total phenolic compounds and lignin. Gene expression and enzymatic activity were not correlated with defense metabolites in the R cultivar group but showed a negative correlation with phenolic compounds in MR cultivars. Cultivar S showed positive correlations of gene expression and enzyme activity with phenolic compounds. These results may assist coffee breeding programs regarding selection of genotypes and in optimization of rust resistance.

Aroma-Active Compounds in Robusta Coffee Pulp Puree-Evaluation of Physicochemical and Sensory Properties.

Wet coffee processing generates a large amount of coffee pulp waste that is mostly disposed of in the processing units. To reduce this waste and the associated environmental burden, an alternative strategy would be to exploit the coffee pulp to produce a durable and stable consumable product. Accordingly, a puree produced from Robusta coffee pulp was investigated in relation to its physicochemical and sensory properties. After thermal and chemical stabilization, the obtained puree (pH 3.6) was found to exhibit a multimodal particle size distribution, shear-thinning behavior, and lower discoloration, as well as an antioxidant capacity of 87.9 µmolTE/gDM. The flavor of the puree was examined by sensory evaluation and the corresponding analyses of aroma-active volatile compounds, as determined using aroma extract dilution analyses (AEDA) and gas chromatography-mass spectrometry/olfactometry (GC-MS/O). The puree was characterized by dominant fruity (4.4), floral (3.4), citrusy (3.3) and hay-like (3.3) odor impressions. The aroma-active compounds were predominantly aldehydes, acids, and lactones, whereby (E)-ß-damascenone, geraniol, 4-methylphenol, 3-hydroxy-4,5-dimethylfuran-2(5H)-one, and 4-hydroxy-3-methoxybenzaldehyde exhibited the highest flavor dilution (FD) factor (1024), thereby indicating their high impact on the overall aroma of the puree. This study demonstrates an approach to stabilize coffee pulp to produce a sweet, fruity puree with comparable physical properties to other fruit purees and that can be used as a new and versatile flavoring ingredient for various food applications.

Caffeine content and antioxidant activity of various brews of specialty grade coffee.

BACKGROUND: The aim of the study was to evaluate the caffeine level and antioxidant activity of brews of specialty grade coffee compared to popular coffee brands. METHODS: Ten types of coffee were used, including 7 specialty Arabica, 1 Robusta and 2 popular cheap coffee brands. For caffeine determination, HPLC analysis and the spectrophotometric method were used as reference. The total polyphenol content and antioxidant capacity (DPPH and FRAP methods) were evaluated. For two selected high-quality coffees, the influence of the brewing method on the antioxidant activity and caffeine content in the brews was assayed. RESULTS: Regarding the caffeine content, differences between specialty coffee brews and popular products were not found, and an average level amounted to 56 and 40 mg/ml, respectively. In contrast, the antioxidant capacity of specialty coffee brews was significantly higher than for popular ones, independently of the test used. The highest scavenging ability and total phenolic content was found for S3 specialty coffee (46.15% of DPPH inhibition and 58.7 mg GAE/ml, respectively), whereas the lowest was found for popular coffee (about 35% of DPPH inhibition and about 41 mg/GAE/ml). For two selected high-quality coffees, the influence of the brewing method on the antioxidant activity and caffeine content in the brews was tested. It was found that the use of a dripper (overflow brewing method) provides the brew with the best antioxidant properties but with moderate caffeine levels. CONCLUSIONS: It was found that 'specialty' quality coffees do not differ from popular brands in terms of caffeine content, but significantly outweigh them in terms of antioxidant activity. This property can be beneficial in the case of a high consumption of coffee, due to antiradical protective effects without the risk of caffeine overdose.

Prediction of specialty coffee flavors based on near-infrared spectra using machine- and deep-learning methods.

BACKGROUND: Specialty coffee fascinates people with its bountiful flavors. Currently, flavor descriptions of specialty coffee beans are only offered by certified coffee cuppers. However, such professionals are rare, and the market demand is tremendous. The hypothesis of this study was to investigate the feasibility to train machine learning (ML) and deep learning (DL) models for predicting the flavors of specialty coffee using near-infrared spectra of ground coffee as the input. Successful model development would provide a new and objective framework to predict complex flavors in food and beverage products. RESULTS: In predicting seven categories of coffee flavors, the models developed using the ML method (i.e. support vector machine) and the deep convolutional neural network (DCNN) achieved similar performance, with the recall and accuracy being 70-73% and 75-77% respectively. Through the proposed visualization method - a focusing plot - the potential correlation among the highly weighted spectral region of the DCNN model, the predicted flavor categories, and the corresponding chemical composition are presented. CONCLUSION: This study has proven the feasibility of applying ML and DL methods on the near-infrared spectra of ground coffee to predict specialty coffee flavors. The effective models provided moderate prediction for seven flavor categories based on 266 samples. The results of classification and visualization indicate that the DCNN model developed is a promising and explainable method for coffee flavor prediction. © 2021 Society of Chemical Industry.

In silico guided structural and functional analysis of genes with potential involvement in resistance to coffee leaf rust: A functional marker based approach.

Physiology-based differentiation of SH genes and Hemileia vastatrix races is the principal method employed for the characterization of coffee leaf rust resistance. Based on the gene-for-gene theory, nine major rust resistance genes (SH1-9) have been proposed. However, these genes have not been characterized at the molecular level. Consequently, the lack of molecular data regarding rust resistance genes or candidates is a major bottleneck in coffee breeding. To address this issue, we screened a BAC library with resistance gene analogs (RGAs), identified RGAs, characterized and explored for any SH related candidate genes. Herein, we report the identification and characterization of a gene (gene 11), which shares conserved sequences with other SH genes and displays a characteristic polymorphic allele conferring different resistance phenotypes. Furthermore, comparative analysis of the two RGAs belonging to CC-NBS-LRR revealed more intense diversifying selection in tomato and grape genomes than in coffee. For the first time, the present study has unveiled novel insights into the molecular nature of the SH genes, thereby opening new avenues for coffee rust resistance molecular breeding. The characterized candidate RGA is of particular importance for further biological function analysis in coffee.

Distinguishing the region-of-origin of roasted coffee beans with trace element ratios.

Determining coffee region-of-origin is most appropriately addressed through analyses of the product available to the consumer. We analyzed the concentrations of 44 trace elements in 53 samples of roasted Arabica coffee beans (Coffea arabica) from 21 different countries. Variations in absolute elemental concentrations of coffee beans arise through varying degrees of roasting (from green through dark roasts). Since trace elements are not volatilized at roasting temperatures, we conducted analyses of element ratios to evaluate concentration-related differences among beans of different origins. We used kernel density estimates to compare the distributions of 1892 element ratios for each of these countries with the combined distribution of coffee samples from the other countries. Using this quantitative approach, we demonstrated that many of the world's coffee-producing regions can be distinguished from other regions of the world on the basis of element ratios.

Characterizing product temperature-dependent sensory perception of brewed coffee beverages: Descriptive sensory analysis.

In most previous studies, brewed coffee samples were served at specific serving temperatures for sensory evaluation. While several recent studies have illustrated that serving temperature does have an impact on sensory attribute intensities of brewed coffee, more elaboration is needed. By focusing on knowledge gaps between earlier studies, this study sought to determine whether and how sensory attributes of brewed coffee can vary as a function of serving temperature and coffee variety. In this study, 6 trained panelists rated intensities of 32 sensory attributes (3 appearances, 12 aromas, 2 tastes, 13 flavors, and 2 mouthfeels) with respect to brewed coffee samples, of each of three varieties (Ethiopian, Kenyan, and Colombian) served at four different serving temperatures: 70, 55, 40, and 25 °C, respectively. The results indicated that intensities of 18 and 7 attributes, respectively, differed significantly with serving temperature and coffee variety. A principal component analysis (PCA) showed the greater amount of data variation could be attributed to serving temperature (63.28%) rather than coffee variety (21.24%), much like the result of a hierarchical clustering analysis. Regression vector (RV) coefficients, determined by a factor score matrix of brewed coffee samples served at different temperatures, revealed that brewed coffee samples served at 70 and 55 °C were perceived differently from those served at 40 and 25 °C. In conclusion, the findings emphasize that sensory attributes of brewed coffee samples should be evaluated at multiple serving temperatures, both higher (70 to 55 °C) and lower (40 to 25 °C) ones, to better capture sensory attributes of brewed coffee than those from a traditional sensory evaluation. Further study is needed to characterize different coffee samples with respect to lessening an overwhelming effect of serving temperature.

Very beyond subjectivity: The limit of accuracy of Q-Graders.

When it comes to the sensory analysis of specialty coffees, it is necessary to discuss the protocol of tests of the Specialty Coffee Association (SCA) and the formation of Q-Graders as reliable parameters in the sensory analysis. However, the training of these Q-Graders and the use of the SCA protocol has generated discussions in the scientific community and demonstrated the importance of talking about the level of professional precision as well as the use of the protocol. This study sought to understand the relation of accuracy and efficiency of the Q-Graders and protocol in the sensory analysis of coffees. Three experiments were carried out to evaluate and test the hypotheses regarding the level of precision in relation to the shift, the number of samples and the judgment abilities of Q-Graders due to the quality of the specialty coffee and nonspecialty coffee. These three experiments were performed by seven Q-Graders in an isolated environment during three consecutive days with 137 specialty coffee samples and 7 nonspecialty coffee samples as defined by the SCA. The results indicate that the Q-Graders present high precision when evaluating excellent and outstanding coffees, as defined by the SCA. In addition, the effect of the shift did not exert fatigue on the Q-Graders. However, evaluation errors were made by the Q-Graders on very good coffee (77.00-80.00 points), which are considered as nonspecialty by the SCA, thus allowing a more in-depth discussion on what would be the boundary between a specialty and nonspecialty coffee. PRACTICAL APPLICATIONS: The article deals with the sensory evaluation process of coffees, and it has great importance to teaching and research institutions in Brazil, the largest producer, largest exporter and the country with the highest concentration of coffee scholars in the world. The article focuses on a new approach and a new way of looking at the sensory evaluation process of coffees, using the methodology of the Specialty Coffee Association to analyze the accuracy and efficiency of the Q-Graders.

The typicity of coffees from different terroirs determined by groups of physico-chemical and sensory variables and multiple factor analysis.

Coffee production is the result of the relationship between local environmental conditions and coffee cultivars that grow in this place. Coffee plants develop original physico-chemical and sensory characteristics that together with the agricultural techniques practiced by growers define the terroir. The objective of this study was to describe the typicity of coffee prepared by coffee growers from seven coffee terroirs in Paraná, Brazil. The terroir categorization was based on the local latitude, longitude, altitude and annual average temperature. Coffee samples were prepared by the coffee growers according to their agricultural techniques. A multiple factor analysis (MFA) was applied to the groups of variables of the green and roasted coffee bean physico-chemical and sensory attributes. The variability in environmental conditions was sufficient to modify the green and roasted coffee bean characteristics and sensory attributes. The terroir description obtained with MFA description compared to that obtained with individual groups of variables was different among terroirs. Roasted coffee variables and sensory attributes caused the greatest differences. The individual use of these groups of variables may result in non-representative descriptions of coffee from different terroirs. Mandaguari and Ivaiporã terroirs were associated with high nitrogenous compounds content, high expansion volume and low density of roasted coffees, and the beverages showed a high turbidity and intense body. Apucarana, São Jerônimo da Serra and Ribeirão do Pinhal terroirs were associated with low lipids content, high density and low volume expansion roasted coffee, and the beverage showed intense coffee and sweet aromas and a low turbidity and body texture. In coffee from the Londrina terroir, medium nitrogenous compounds content and high sucrose and lipids contents were found. Their beverage showed a high turbidity and intense body as well as a grassy green taste and astringency. Coffee from Ribeirão Claro terroir presented high lipids and sucrose contents and low caffeine and phenolic compounds contents, and the main sensory attributes were a coffee aroma and sweet and sour tastes. In conclusion, a terroir formed by environmental conditions and agricultural techniques can produce coffee with a set of physico-chemical and sensory characteristics that define its typicity.

Identification of coffee bean varieties using hyperspectral imaging: influence of preprocessing methods and pixel-wise spectra analysis.

Hyperspectral imaging was used to identify and to visualize the coffee bean varieties. Spectral preprocessing of pixel-wise spectra was conducted by different methods, including moving average smoothing (MA), wavelet transform (WT) and empirical mode decomposition (EMD). Meanwhile, spatial preprocessing of the gray-scale image at each wavelength was conducted by median filter (MF). Support vector machine (SVM) models using full sample average spectra and pixel-wise spectra, and the selected optimal wavelengths by second derivative spectra all achieved classification accuracy over 80%. Primarily, the SVM models using pixel-wise spectra were used to predict the sample average spectra, and these models obtained over 80% of the classification accuracy. Secondly, the SVM models using sample average spectra were used to predict pixel-wise spectra, but achieved with lower than 50% of classification accuracy. The results indicated that WT and EMD were suitable for pixel-wise spectra preprocessing. The use of pixel-wise spectra could extend the calibration set, and resulted in the good prediction results for pixel-wise spectra and sample average spectra. The overall results indicated the effectiveness of using spectral preprocessing and the adoption of pixel-wise spectra. The results provided an alternative way of data processing for applications of hyperspectral imaging in food industry.

Coffee inhibition of CYP3A4 in vitro was not translated to a grapefruit-like pharmacokinetic interaction clinically.

Grapefruit can augment oral medication bioavailability through irreversible (mechanism-based) inhibition of intestinal CYP3A4. Supplementary data from our recent coffee-drug interaction clinical study showed some subjects had higher area under the plasma drug concentration - time curve (AUC) and plasma peak drug concentration (Cmax) of the CYP3A4 probe felodipine compared to aqueous control. It was hypothesized that coffee might interact like grapefruit in responsive individuals. Beans from six geographical locations were consistently brewed into coffee that was separated chromatographically to a methanolic fraction for in vitro inhibition testing of CYP3A4 metabolism of felodipine at 1% coffee strength. The effect of simultaneous incubation and 10-min preincubation with coffee fractions determined whether coffee had direct and mechanism-based inhibitory activity. A subsequent five-way randomized balanced controlled crossover clinical study evaluated the clinical pharmacokinetic interaction with single-dose felodipine. Grapefruit juice, water, or three of the in vitro tested coffees were ingested at 300 mL alone 1 h before and then with felodipine. In vitro, all six coffees decreased felodipine metabolism for both simultaneous and preincubation exposure compared to corresponding control. Five coffees demonstrated mechanism-based inhibition. Grapefruit increased felodipine AUC0-8 (25 vs. 13 ng.h/mL, P < 0.001) and Cmax (5.8 vs. 2.7 ng/mL, P < 0.001) and decreased dehydrofelodipine/felodipine AUC0-8 ratio (0.84 vs. 1.29, P < 0.001), while the three coffees caused no change in these parameters compared to water. Despite high in vitro potency of CYP3A4 inhibition, the coffees did not cause a clinical pharmacokinetic interaction possibly from insufficient amount of inhibitor(s) in coffee reaching intestinal CYP3A4 during the absorption phase of felodipine. The results of this study highlight the need for follow-up clinical testing when in vitro results indicate the possibility of an interaction.

Transferring results from NIR-hyperspectral to NIR-multispectral imaging systems: A filter-based simulation applied to the classification of Arabica and Robusta green coffee.

Due to the differences in terms of both price and quality, the availability of effective instrumentation to discriminate between Arabica and Robusta coffee is extremely important. To this aim, the use of multispectral imaging systems could provide reliable and accurate real-time monitoring at relatively low costs. However, in practice the implementation of multispectral imaging systems is not straightforward: the present work investigates this issue, starting from the outcome of variable selection performed using a hyperspectral system. Multispectral data were simulated considering four commercially available filters matching the selected spectral regions, and used to calculate multivariate classification models with Partial Least Squares-Discriminant Analysis (PLS-DA) and sparse PLS-DA. Proper strategies for the definition of the training set and the selection of the most effective combinations of spectral channels led to satisfactory classification performances (100% classification efficiency in prediction of the test set).

Low-field (1)H NMR spectroscopy for distinguishing between arabica and robusta ground roast coffees.

This work reports a new screening protocol for addressing issues of coffee authenticity using low-field (60MHz) bench-top (1)H NMR spectroscopy. Using a simple chloroform-based extraction, useful spectra were obtained from the lipophilic fraction of ground roast coffees. It was found that 16-O-methylcafestol (16-OMC, a recognized marker compound for robusta beans) gives rise to an isolated peak in the 60MHz spectrum, which can be used as an indicator of the presence of robusta beans in the sample. A total of 81 extracts from authenticated coffees and mixtures were analysed, from which the detection limit of robusta in arabica was estimated to be between 10% and 20% w/w. Using the established protocol, a surveillance exercise was conducted of 27 retail samples of ground roast coffees which were labelled as "100% arabica". None were found to contain undeclared robusta content above the estimated detection limit.

Efficacy of different caffeine concentrations on growth and ochratoxin A production by Aspergillus species.

UNLABELLED: The objective of this study was to evaluate the effect of different caffeine concentrations (0-4%) on (i) lag phase prior to growth, (ii) growth rates and (iii) ochratoxin A (OTA) production by strains from the Aspergillus section Circumdati and Aspergillus section Nigri groups, isolated from coffee, when grown on a conducive medium at 0·98 water activity and 30°C. The lag phases prior to growth increased with caffeine concentration. A strain of Aspergillus niger and Aspergillus carbonarius were the most sensitive to caffeine with growth being inhibited by <1% caffeine. For strains of Aspergillus westerdijkiae, Aspergillus ochraceus and Aspergillus steynii, although growth was inhibited significantly, some growth (10-15% of controls) occurred in 4% caffeine. OTA production was significantly inhibited by only 0·5% caffeine for strains of A. westerdijkiae, A. niger and A. carbonarius. For A. steynii at least 1·5% caffeine was required to inhibit OTA production. In contrast, for the strain of A. ochraceus there was a stimulation of OTA at 3% with a reduction at 4% caffeine. These results are discussed in the context of the different concentrations of caffeine found in Arabica and Robusta coffee and the development of minimization strategies. SIGNIFICANCE AND IMPACT OF THE STUDY: Arabic (0·6%) and Robusta coffee (4%) have significantly different amounts of endogenous caffeine. The growth of six ochratoxigenic fungi which contaminate coffee with ochratoxin A (OTA) had differential tolerance/sensitivity to concentrations of caffeine in vitro in this range. However, low concentrations of caffeine (<0·5%) was inhibitory to OTA production. These results are discussed in the context of the potential for using such information for the design of minimization strategies to control mycotoxin production in such products.

Effect of roasting degree on the antioxidant activity of different Arabica coffee quality classes.

BACKGROUND: Coffee is one of the most widely consumed beverages in the world, because of its unique sensory properties and physiological properties. Coffee beverages represent a significant source of antioxidants in the consumers' diet and contribute significantly to their daily intake. The aim of this research was to investigate the effect of different roasting degrees on the content of biologically active compounds and antioxidant activity in different quality classes of Arabica coffee. METHODS: Samples of green Arabica coffee (Rio Minas) of two quality classes from two production batches were used for the research. Roasting was carried out at temperatures of 167, 175 and 171°C. The total phenol content (TPC), total flavonoid content (TFC), flavonol content (FC) and antioxidant activity (DPPH, ABTS) in the coffee extracts was determined. RESULTS: This research shows that TPC was significantly higher (P < 0.05) in green coffee compared to TPC in roasted coffee, and TPC decreases as the roasting temperature increases. TFC and FC were significantly lower (P < 0.05) in green coffee than in roasted coffee. Differences in TPC between the 1st and 2nd classes of Arabica coffee were not significant (P > 0.05), while differences in TFC were significant (P < 0.05) only for green coffee from the second production batch and differences in FC were significant (P < 0.05) for green coffee and for coffee roasted at 175°C. Roasting temperatures have different influences the antioxidant activity (DPPH, ABTS) of coffee and the highest antioxidant activity was determined in coffee roasted at 171°C. An exception was 1st class Arabica coffee roasted at 167°C (ABTS). All samples of 1st class Arabica coffee had higher antioxidant activity (DPPH, ABTS) compared to 2nd class Arabica. CONCLUSIONS: This research shows that the bioactive compounds content and antioxidant activity of different quality classes of Arabica coffee are dependent on the degree of roasting. TPC decreases when the roasting temperature increases, while TFC and FC also increase. These results indicate that the antioxidant activity of coffee depends on a variety of bioactive components in coffee beans. Antioxidant activity largely depends on the class of coffee. The coffee samples of 1stclass quality (maximum 8 black beans/300 g from the sample and large bean size) had higher antioxidant activity compared to samples of 2nd quality class (maximum 19 black beans/300 g in the sample and medium-sized beans).

Mapping the potential beverage quality of coffee produced in the Zona da Mata, Minas Gerais, Brazil.

BACKGROUND: Detailed knowledge of coffee production systems enables optimization of crop management, harvesting and post-harvest techniques. In this study, coffee quality is mapped as a function of coffee variety, altitude and terrain aspect attributes. The work was performed in the Zona da Mata, Minas Gerais, Brazil. RESULTS: A large range of coffee quality grades was observed for the Red Catuai variety. For the Yellow Catuai variety, no quality grades lower than 70 were observed. Regarding the terrain aspect, samples from the southeast-facing slope (SEFS) and the northwest-facing slope (NWFS) exhibited distinct behaviors. The SEFS samples had a greater range of quality grades than did the NWFS samples. The highest grade was obtained from an NWFS point. The lowest quality values and the largest range of grades were observed at lower altitudes. The extracts from the highest-altitude samples did not produce any low-quality coffee. CONCLUSIONS: The production site's position and altitude are the primary variables that influenced the coffee quality. The study area has micro-regions with grades ranging from 80 to 94. These areas have the potential for producing specialty coffees. © 2015 Society of Chemical Industry.

Espresso beverages of pure origin coffee: mineral characterization, contribution for mineral intake and geographical discrimination.

Espresso coffee beverages prepared from pure origin roasted ground coffees from the major world growing regions (Brazil, Ethiopia, Colombia, India, Mexico, Honduras, Guatemala, Papua New Guinea, Kenya, Cuba, Timor, Mussulo and China) were characterized and compared in terms of their mineral content. Regular consumption of one cup of espresso contributes to a daily mineral intake varying from 0.002% (sodium; Central America) to 8.73% (potassium; Asia). The mineral profiles of the espresso beverages revealed significant inter- and intra-continental differences. South American pure origin coffees are on average richer in the analyzed elements except for calcium, while samples from Central America have generally lower mineral amounts (except for manganese). Manganese displayed significant differences (p<0.05) among the countries of each characterized continent. Intercontinental and inter-country discrimination between the major world coffee producers were achieved by applying canonical discriminant analysis. Manganese and calcium were found to be the best chemical descriptors for origin.

Discrimination between washed Arabica, natural Arabica and Robusta coffees by using near infrared spectroscopy, electronic nose and electronic tongue analysis.

BACKGROUND: The aim of this study is to investigate the feasibility of a 'holistic' approach, using near infrared (NIR) spectroscopy and electronic devices (electronic nose and electronic tongue), as instrumental tools for the classification of different coffee varieties. Analyses were performed on green coffee, on ground roasted coffee and on coffee beverage. Principal component analysis was applied on spectral and sensory data to uncover correlations between samples and variables. After variable selection, linear discriminant analysis was used to classify the samples on the basis of the three coffee classes: Robusta, natural Arabica and washed Arabica. RESULTS: Linear discriminant analysis demonstrates the practicability of this approach: the external test set validation performed with NIR data showed 100% of correctly classified samples. Moreover, a satisfying percentage of correct classification in cross-validation was obtained for the electronic devices: the average values of correctly classified samples were 81.83% and 78.76% for electronic nose and electronic tongue, respectively. CONCLUSION: NIR spectroscopy was shown to be a very reliable and useful tool to classify coffee samples in a fast, clean and inexpensive way compared to classical analysis, while the electronic devices could assume the role of investigating techniques to depict the aroma and taste of coffee samples.

Voltammetric electronic tongue and support vector machines for identification of selected features in Mexican coffee.

This paper describes a new method based on a voltammetric electronic tongue (ET) for the recognition of distinctive features in coffee samples. An ET was directly applied to different samples from the main Mexican coffee regions without any pretreatment before the analysis. The resulting electrochemical information was modeled with two different mathematical tools, namely Linear Discriminant Analysis (LDA) and Support Vector Machines (SVM). Growing conditions (i.e., organic or non-organic practices and altitude of crops) were considered for a first classification. LDA results showed an average discrimination rate of 88% ± 6.53% while SVM successfully accomplished an overall accuracy of 96.4% ± 3.50% for the same task. A second classification based on geographical origin of samples was carried out. Results showed an overall accuracy of 87.5% ± 7.79% for LDA and a superior performance of 97.5% ± 3.22% for SVM. Given the complexity of coffee samples, the high accuracy percentages achieved by ET coupled with SVM in both classification problems suggested a potential applicability of ET in the assessment of selected coffee features with a simpler and faster methodology along with a null sample pretreatment. In addition, the proposed method can be applied to authentication assessment while improving cost, time and accuracy of the general procedure.

Application of elastic net and infrared spectroscopy in the discrimination between defective and non-defective roasted coffees.

The quality of the coffee beverage is negatively affected by the presence of defective coffee beans and its evaluation still relies on highly subjective sensory panels. To tackle the problem of subjectivity, sophisticated analytical techniques have been developed and have been shown capable of discriminating defective from non-defective coffees after roasting. However, these techniques are not adequate for routine analysis, for they are laborious (sample preparation) and time consuming, and reliable, simpler and faster techniques need to be developed for such purpose. Thus, it was the aim of this study to evaluate the performance of infrared spectroscopic methods, namely FTIR and NIR, for the discrimination of roasted defective and non-defective coffees, employing a novel statistical approach. The classification models based on Elastic Net exhibited high percentage of correct classification, and the discriminant infrared spectra variables extracted provided a good interpretation of the models. The discrimination of defective and non-defective beans was associated with main chemical descriptors of coffee, such as carbohydrates, proteins/amino acids, lipids, caffeine and chlorogenic acids.