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•Microbial richness increases depending on the condition of the fermentation.•Microorganisms actions could be correlated with sensory attributes.•Fermentation conditions promote ...sensory and chemical changes in coffee.
In view of the possibility of diversifying metabolic routes promoted by fermentation, this study proposed a new processing method for coffee, which consists of adapting a technique already consolidated in winemaking, carbonic maceration. The assay occurred under anaerobic conditions with different time and temperature fermentation. The aim of this study was to determine the differences in coffee characteristics (sensorial, chemical, and microbial) after carbonic maceration and fermentation. Specialty Coffee Association protocol, nuclear magnetic resonance, and denaturing gradient gel electrophoresis were used in these analyzes. A significant functional relationship between global score and temperature (38 °C), for the fermentation time of 96 h was observed. Bacterial diversity and sensory characteristics had a positive correlation. Furthermore, trigonelline, formic acid, hydroxymethylfurfural, lipids, and γ-butyrolactone also contributed to score and sensory quality of coffee beverage. Thus, our data show consistent factors to infer on the microbiological action on the sensory quality of coffee beverage.
VOLATILE PROFILE OF Coffea arabica AND Coffea canephora var. conilon BY SHS-GC-MS AND CHEMOMETRICS. The volatile composition of coffee exerts a substantial influence on its quality, as it defines the ...characteristics of the beverage. However, these compounds are influenced by factors within the coffee production chain, such as botanical origin, geography, processing methods, and roasting. Consequently, the identification of such compounds becomes a vital tool for characterizing coffees to these factors. In this context, gas chromatography with headspace extraction is widely used for aroma analysis, providing a composition closer to consumer perception. Headspace extraction offers speed, simplicity, minimal sample preparation, and no need for solvents. In this study, static headspace extraction (SHS) coupled with gas chromatography-mass spectrometry (SHS-GC-MS) was employed to establish the chemical profile of volatile compounds in Coffea arabica and Coffea canephora var. conilon and determine discriminants between the species. A total of 97 compounds, belonging to 17 chemical classes, were identified. The chemometric analysis highlighted furans, phenols, and carboxylic acids as key differentiating classes. Notably, furfuryl alcohol, acetic acid, 4-vinylguaiacol, N-acetyl-4(H)-pyridine, and N-furfurylpyrrole emerged as crucial volatile compounds. The variable selection using Fisher weight applied directly in the chromatograms, produced models consistent with relative area data, with furfuryl alcohol and 4-vinylguaiacol regions being particularly influential in differentiation.
The quality of the coffee beverage is related to the chemical, physical, and sensory attributes of the coffee beans that vary with the geographic location of the crop, genetic factors, and ...post‐harvest processing. So, the objective of this study was to evaluate the genetic divergence of 27 genotypes of Coffea canephora using the volatile compounds and sensory attributes profile to select genotypes that produce a coffee beverage with high sensory quality. This genetic diversity was estimated from the Euclidean distance matrix using non‐standard data and the Unweighted Pair‐Group Method Using Arithmetic Averages (UPGMA). The 2‐furyl‐methanol, 4‐ethenyl‐2‐methoxyphenol, furfural, 5‐methylfurfural, methylpyrazine, and 2,6‐dimethylpyrazine were predominating volatile compounds in the genotypes. The sensory attributes had a positive Pearson's correlation with the total score. The volatile compounds had a different relative contribution to the genetic divergence between the genotypes of C. canephora. The 4‐ethenyl‐2‐methoxyphenol, 2‐furyl‐methanol, and furfural were volatile compounds that most contributed to the formation of the groups in the UPGMA dendrogram. The relative contribution of sensory attributes to dissimilarity among genotypes was 6.42% to 20.20%. Therefore, this study verified the relative contribution of volatile compounds, in specially 4‐ethenyl‐2‐methoxyphenol, 2‐furyl‐methanol, and furfural, and sensory attributes (flavor, mouthfeel, and bitterness/sweetness) to the genetic divergence between the genotypes of the three clonal varieties. Thus, this work points out compounds that positively contribute to the sensory quality of the Conilon coffee beverage.
Considering the great economic significance of
(arabica) associated with the lower production cost of
(conilon), blends of these coffees are commercially available to reduce costs and combine sensory ...attributes. Thus, analytical tools are required to ensure consistency between real and labeled compositions. In this sense, chromatographic methods based on volatile analysis using static headspace-gas chromatography-mass spectrometry (SHS-GC-MS) and Fourier transform infrared (FTIR) spectroscopy associated with chemometric tools were proposed for the identification and quantification of arabica and conilon blends. The peak integration from the total ion chromatogram (TIC) and extracted ion chromatogram (EIC) was compared in multivariate and univariate scenarios. The optimized partial least squares (PLS) models with uninformative variable elimination (UVE) and chromatographic data (TIC and EIC) have similar accuracy according to a randomized test, with prediction errors between 3.3% and 4.7% and
> 0.98. There was no difference between the univariate models for the TIC and EIC, but the FTIR model presented a lower performance than GC-MS. The multivariate and univariate models based on chromatographic data had similar accuracy. For the classification models, the FTIR, TIC, and EIC data presented accuracies from 96% to 100% and error rates from 0% to 5%. Multivariate and univariate analyses combined with chromatographic and spectroscopic data allow the investigation of coffee blends.
•Coffee filtration methods were more preferred than pressure methods.•Appearance and aroma were the most relevant attributes for untrained consumers.•Mid-infrared has proven to be useful in ...separating brewing methods.
Coffee beverage presents unique organoleptic characteristics of aroma and taste. These sensory attributes depend on the chemical composition of the brewed coffee. Our objectives were to determine the sensory quality of the coffee beverage obtained by different brewing methods as assessed by untrained tasters and to characterize the solid residues of this extraction using the medium infrared spectrum. Four brewing methods were evaluated by 124 untrained consumers. The infusion method presented better global impression and preference of these consumers than the other brewing methods. Significant changes in the chemical composition of the coffee residues were observed. These changes influenced the acceptance of the consumers and can be due to the potential of retention or filtering of organic compounds by the brewing method. Thus, there was a sensory quality difference among the brewing methods and the infrared spectrum indicated the need to distinguish the classes of organic compounds for a better understanding of how coffee brewing interacts with the chemical composition.
Roasting has been used by the coffee industry to promote changes in the physical and chemical structure of coffee beans that influence the sensory quality of coffee beverages. However, there are no ...standardization rules for the temperature and roasting time. Thus, this study evaluated the influence of four roasting profiles obtained by two different roasters on the chemical and sensory quality of the coffee bean. Baked, light, medium, and dark roasting were evaluated using medium infrared spectroscopy and cupping test. Individual and joint effects of temperature and time for each roasting profile were observed on the loss of grain mass. There are specific regions in the infrared spectrum that can be used as markers to discriminate the roasting profiles and the type of roaster used. Despite the difference observed in the ranges of the infrared spectra, the roasters did not present significant differences in the average of the final sensory notes. This result shows the need to use analytical chemical techniques together with sensory analysis in order to better determine differences between coffee samples. Therefore, differences observed in the chemical analyzes and in the sensory attributes of roasted coffee are related to the roasting profile and type of roaster.
The physical or morphological integrity of the coffee bean during post-harvest processing directly influences the economic value and sensory quality of the coffee beverage. Breakdowns in the outer ...layers of the beans are characteristics observed for the morphological and economic classification of coffee beans during the commercialization of this product. However, physical changes in the inner layers of the beans that are not seen with the naked eye can also influence the sensory quality of the coffee. Therefore, the objective of this study was to relate changes in the physical structure of coffee beans roasted by four different processes (light, medium, dark, and baked) with the sensory attributes of the beverage. The analyses of the physical characteristics of the coffee beans were carried out by X-ray microtomography and the sensory profile was determined using the Specialty Coffee Association of America protocol. The roasting profile with the highest sensory scores showed higher values for total pore space volume and a negative Euler number. However, the roasting profiles that fluctuated between the highest and lowest of scores of the sensory attributes did not present standardized behavior for the connectivity, Euler number, and total pore space volume. Hence, morphological or physical changes in the coffee beans caused by the different types of roasting correlate with changes in the sensorial profile. Furthermore, the sensory discrimination of these coffee beans among the different roast profiles may be observed by the joint analysis of the flavor and fragrance scores.
SHS-GC-MS applied in and blend assessment Vieira Lyrio, Marcos Valério; Pereira da Cunha, Pedro Henrique; Debona, Danieli Grancieri ...
Analytical methods,
07/2023, Letnik:
15, Številka:
29
Journal Article
Recenzirano
Considering the great economic significance of
Coffea arabica
(arabica) associated with the lower production cost of
C. canephora
(conilon), blends of these coffees are commercially available to ...reduce costs and combine sensory attributes. Thus, analytical tools are required to ensure consistency between real and labeled compositions. In this sense, chromatographic methods based on volatile analysis using static headspace-gas chromatography-mass spectrometry (SHS-GC-MS) and Fourier transform infrared (FTIR) spectroscopy associated with chemometric tools were proposed for the identification and quantification of arabica and conilon blends. The peak integration from the total ion chromatogram (TIC) and extracted ion chromatogram (EIC) was compared in multivariate and univariate scenarios. The optimized partial least squares (PLS) models with uninformative variable elimination (UVE) and chromatographic data (TIC and EIC) have similar accuracy according to a randomized test, with prediction errors between 3.3% and 4.7% and
R
p
2
> 0.98. There was no difference between the univariate models for the TIC and EIC, but the FTIR model presented a lower performance than GC-MS. The multivariate and univariate models based on chromatographic data had similar accuracy. For the classification models, the FTIR, TIC, and EIC data presented accuracies from 96% to 100% and error rates from 0% to 5%. Multivariate and univariate analyses combined with chromatographic and spectroscopic data allow the investigation of coffee blends.
The present study proposes a new approach for blend assessment based on the volatile composition extracted and analyzed by SHS-GC-MS associated with multivariate and univariate methods for a qualitative (identification) and quantitative evaluation.
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