Coffee growing altitude influences the microbiota, chemical compounds and the quality of fermented coffees.

The objective of this work was to evaluate the influence of different altitudes on the epiphytic microbiota of coffee beans and on sensorial and chemical quality of coffees grown at 800, 1000, 1200, and 1400 m in Serra do Caparaó, Espírito Santo, Brazil. For microbiological analysis, the population counts of mesophilic bacteria, lactic acid bacteria (LAB), and yeasts were performed from the surface plating. The isolates were grouped and identified from the Matrix Assisted Laser Desorption Ionization Time-of-Flight Mass Spectrometry (MALDI-TOF MS) and sequencing of the ribosomal region was used. The chemical composition of the green grains was evaluated by Raman spectroscopy, and the sensory analysis of the roasted grains was performed using temporal dominance of sensations (TDS). During fermentation, there was a decrease in the LAB in pulped coffee from 800 and 1000 m altitude, while an increase was observed at 1200 and 1400 m. In natural coffee, there was an increase of LAB population at all altitudes. The highest diversity of mesophilic bacteria and yeast were identified in natural 1400 m and 1000 m, respectively. However pulped coffee treatments it was at 1200 m and 800 m. The chlorogenic acid and fatty acids in the green bean changed with altitude variation and processing. The floral attribute was detected only at altitude 1400 m. Caramel, chocolate and almond attributes were most frequently detected in coffees at different altitudes and processing. Therefore, pulped coffee processing was most suitable at low altitude while at high altitudes, both processes can be conducted to obtain a beverage with unusual sensory profile.

Steam pressure treatment of defective Coffea canephora beans improves the volatile profile and sensory acceptance of roasted coffee blends.

Between 15 and 20% of Brazilian coffee production corresponds to defective beans (PVA), which decreases the quality of the coffee brew. Steam treatment has been reported as an alternative to improve the volatile profile and cup quality of coffee. The aim of this study was to propose a steam treatment of defective Coffea canephora beans to improve the volatile profile of the roasted coffee. The sensory impacts of adding steamed coffee (SC) in Coffea arabica blends were evaluated. The steam treatments studied modified the volatile profile of roasted SCs, increasing the contents of acetoin, benzyl alcohol, maltol, 2,6-dimethylpyrazine, 2-furfurylthiol, and 5-methylfurfural and decreasing the contents of 4-ethylguaiacol, isovaleric acid, methional, 2,3-diethyl-5-methylpyrazine, and 3-methoxy-3-methylpyrazine. Among the evaluated parameters, the best condition to maximized the content of the volatiles with a potential positive impact and minimize those with a potential negative impact was 5bar/16min (SC 5). The thresholds of consumer rejection and of detection indicate that up to 30% SC 5 can be added to a high cup quality Coffea arabica coffee without perception or rejection of the coffee brew. A blend of 30% of SC 5 and 70% of Coffea arabica was well accepted.

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.

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.

Prediction models for Arabica coffee beverage quality based on aroma analyses and chemometrics.

In this work, soft modeling based on chemometric analyses of coffee beverage sensory data and the chromatographic profiles of volatile roasted coffee compounds is proposed to predict the scores of acidity, bitterness, flavor, cleanliness, body, and overall quality of the coffee beverage. A partial least squares (PLS) regression method was used to construct the models. The ordered predictor selection (OPS) algorithm was applied to select the compounds for the regression model of each sensory attribute in order to take only significant chromatographic peaks into account. The prediction errors of these models, using 4 or 5 latent variables, were equal to 0.28, 0.33, 0.35, 0.33, 0.34 and 0.41, for each of the attributes and compatible with the errors of the mean scores of the experts. Thus, the results proved the feasibility of using a similar methodology in on-line or routine applications to predict the sensory quality of Brazilian Arabica coffee.

Chemometric models for the quantitative descriptive sensory analysis of Arabica coffee beverages using near infrared spectroscopy.

Mathematical models based on chemometric analyses of the coffee beverage sensory data and NIR spectra of 51 Arabica roasted coffee samples were generated aiming to predict the scores of acidity, bitterness, flavour, cleanliness, body and overall quality of coffee beverage. Partial least squares (PLS) were used to construct the models. The ordered predictor selection (OPS) algorithm was applied to select the wavelengths for the regression model of each sensory attribute in order to take only significant regions into account. The regions of the spectrum defined as important for sensory quality were closely related to the NIR spectra of pure caffeine, trigonelline, 5-caffeoylquinic acid, cellulose, coffee lipids, sucrose and casein. The NIR analyses sustained that the relationship between the sensory characteristics of the beverage and the chemical composition of the roasted grain were as listed below: 1 - the lipids and proteins were closely related to the attribute body; 2 - the caffeine and chlorogenic acids were related to bitterness; 3 - the chlorogenic acids were related to acidity and flavour; 4 - the cleanliness and overall quality were related to caffeine, trigonelline, chlorogenic acid, polysaccharides, sucrose and protein.

Comparison of bean biochemical composition and beverage quality of Arabica hybrids involving Sudanese-Ethiopian origins with traditional varieties at various elevations in Central America.

For buyers of Arabica coffee (Coffea arabica L.) in Central America, elevation and variety are important indicators of quality. We compared coffee produced by three types of varieties established in various trials at elevations ranging from 700-1600 m in three countries (El Salvador, Costa Rica and Honduras). Arabica hybrids resulting from crosses of Sudanese-Ethiopian origins with either traditional varieties or with introgressed lines derived from the hybrid of Timor (C. arabica x Coffea canephora Pierre ex Froehn) were compared with traditional cultivars (TC). Effects of elevation and variety on bean biochemical composition (caffeine, chlorogenic acid, trigonelline, fat and sucrose) were evaluated by predictive models based on calibration of near-infrared (NIR) spectra and by chemometric analysis of the global NIR spectrum. Beverage quality tests were performed by a panel of ten professional cup-tasters. Experiment 1 was carried out on the slopes of the Poas volcano (Costa Rica) with the traditional cultivar 'Caturra'. Experiment 2 compared the three varieties in a network of trials established in three countries of Central America. Significant linear regressions with elevation were observed in Experiment 1 with Caturra and in Experiment 2 for the traditional cultivars, and trends were established relating variation in biochemical compounds and cup quality to elevation. Convergence or divergence of the new hybrids in relation to these trends was observed. For the traditional cultivars, elevation had a significant effect on bean biochemical composition, with chlorogenic acid and fat concentrations increasing with increasing elevation. For the Arabica hybrids, elevation explained little of the variation in chlorogenic acid concentration and none of the variation in fat concentration. Nevertheless, Arabica hybrids had 10-20% higher fat concentrations than the traditional varieties at low elevations and similar fat concentrations at high elevations. The samples could be discriminated according to elevation based on NIR spectra; however, the spectra of the TC varieties were more strongly modified by elevation than the spectra of the hybrids. Nonetheless, this analysis confirmed homeostasis of the hybrids for which bean biochemical composition was less affected by elevation than that of the traditional varieties. The organoleptic evaluation, performed on samples originating from high elevations, showed no significant differences between Arabica hybrids and traditional cultivars. The new hybrid varieties with high beverage quality and productivity potential should act as a catalyst in increasing the economic viability of coffee agroforestry systems being developed in Central America.

Discrimination of Brazilian arabica green coffee samples by chlorogenic acid composition.

Coffee is basically consumed for the pleasure given by its taste and aroma, that is, the quality and acceptance of the coffee beverage are directly related to its sensorial characteristics. Thus, nowadays coffee quality is basically evaluated by sensorial analysis. However, together with this kind of analysis, it should be important to have available more objective chemical methods to assess coffee quality. One possible approach could be based on the analysis of chlorogenic acids (CGA), since they are considered precursors of coffee flavour and pigments during roasting. In the present work, high performance liquid chromatography (HPLC) analysis of chlorogenic acids was applied to six different Brazilian arabica green coffee samples which were previously characterised by sensorial analysis. The results showed the potential to correlate the chemical data, evaluated by the Principal Components Analysis (PCA) statistical method, with sensorial analysis in order to discriminate the quality of the samples. It was observed that the 3,4-dicaffeoylquinic (3,4-diCQA) and 3,5-dicaffeoylquinic (3,5-diCQA) isomers are very important for grouping the coffees into good and bad samples.