Infrared spectroscopy coupled with chemometrics in coffee post-harvest processes as complement to the sensory analysis

Integration of widely targeted metabolomics and the e-tongue reveals the chemical variation and taste quality of Yunnan Arabica coffee prepared using different primary processing methods

UPLC-Q-TOF-MS and electronic tongue analysis were applied to analyse the metabolic profile and taste quality of Yunnan Arabica coffee under seven primary processing methods. The total phenolic content ranged from 34.44 to 44.42 mg/g DW, the e-tongue results revealed the strongest umami sensor response value in the sample prepared with traditional dry processing, while the samples prepared via honey processing II had the strongest astringency sensor response value. Metabolomics analysis identified 221 differential metabolites, with higher contents of amino acids and derivatives within dry processing II sample, and increased contents of lipids and phenolic acids in the honey processing III sample. The astringency and aftertaste-astringency of the coffee samples positively correlated with the trigonelline, 3,5-di-caffeoylquinic acid and 4-caffeoylquinic acid content. The results contributed to a better understanding of how the primary processing process affects coffee quality, and supply useful information for the enrichment of coffee biochemistry theory.

Discrimination of Filter Coffee Extraction Methods of a Medium Roasted Specialty Coffee Based on Volatile Profiles and Sensorial Traits

An untargeted gas chromatography-mass spectrometry (GC-MS) approach combined with sensory analysis was used to present the effects of different extraction methods (i.e., Pure Brew, V60, AeroPress, and French Press) on specialty graded Coffea arabica from Kenya. Partial Least Square Discriminant analysis and hierarchical clustering were applied as multivariate statistical tools in data analysis. The results showed good discrimination and a clear clustering of the groups of samples based on their volatile profiles. Similarities were found related to the filter material and shape used for the extraction. Samples extracted with paper filters (V60 and AeroPress) resulted in higher percentages of caramel-, and flowery-related compounds, while from metal filter samples (Pure Brew and French Press), more fruity and roasted coffees were obtained. Discriminant analysis allowed the identification of eight compounds with a high VIP (variable important in projection) discriminant value (i.e., >1), with 2-furanmethanol being the main feature in discrimination. Sensorial analyses were carried out through an expert panel test. The main evaluations revealed the French Press system as the lowest-scored sample in all the evaluated parameters, except for acidity, where its score was similar to V60. In conclusion, the data obtained from GC-MS analyses were in line with the sensorial results, confirming that the extraction process plays a fundamental role in the flavor profile of filter coffee beverages.

Exploring the effect of utilising organic acid solutions in ultrasound-assisted extraction of pectin from apple pomace, and its potential for biomedical purposes

Biomass resulting from food production represents valuable material to recover different biomolecules. In our study, we used apple pomace to obtain pectin, which is traditionally extracted using mineral acids. Our hypothesis consisted of carrying out extractions with organic acids, assisted by ultrasound, by varying processing parameters including time, temperature, and type of acid. The analytical determinations of galacturonic acid content, methoxylation and esterification degree, ζ-potential and extraction yield were used as pectin quality indicators. Pectins extracted using treatment conditions with better performance were assessed biologically in vitro for their potential to be used in biomedical applications. Overall, the extracted pectin presented a galacturonic acid content, methoxylation and esterification degree ranged from 19.7 to 67%, 26.8-41.4% and 58-65.2% respectively, and were negatively charged (-24.1 to -13.2 mV). It was found that factors of time and temperature greatly influenced the response variables excepting the esterification degree, while the acid type influenced the ζ-potential, methoxylation and esterification degrees. Additionally, it was seen that the longer extraction time (50 min) and higher temperature (50 °C) exhibited the better extraction yield (∼10.9%). Finally, the selected pectin showed high cytocompatibility up to 500 μg/mL of concentration when seeded with Neonatal Normal Human Dermal Fibroblasts.

Comparative studies of fermented coffee fruits post-treatments on chemical and sensory properties of roasted beans in Yunnan, China

In this study, medium roasted coffee with four different fermented coffee fruits post-treatments (dry, wet, semi-dry and hot air dry) was used as the material. Chemical profile and sensorial analysis were used to comprehensively analyze the effects of post-treatments on coffee flavor characteristics from multiple dimensions. A total of 31 water-soluble chemical components and 39 volatile compounds were identified in roasted coffee, and distinct post-treatments based on chemical orientation make coffee highly differentiated. In addition, the principal component analysis (PCA) of the chemical composition integrated data set showed that the first two principal components could explain 54.9% of the sample variability. All four post-treatments can be classified as "specialty coffees" according to the Specialty Coffee Association (SCA) protocol, with various organoleptic characteristics and flavor attributes. As a result, the fermented coffee fruits post-treatment method further determines the quality characteristics of coffee, thus meeting the needs of different niche markets.

Quantification of Corn Adulteration in Wet and Dry-Processed Peaberry Ground Roasted Coffees by UV-Vis Spectroscopy and Chemometrics

In this present research, a spectroscopic method based on UV–Vis spectroscopy is utilized to quantify the level of corn adulteration in peaberry ground roasted coffee by chemometrics. Peaberry coffee with two types of bean processing of wet and dry-processed methods was used and intentionally adulterated by corn with a 10–50% level of adulteration. UV–Vis spectral data are obtained for aqueous samples in the range between 250 and 400 nm with a 1 nm interval. Three multivariate regression methods, including partial least squares regression (PLSR), multiple linear regression (MLR), and principal component regression (PCR), are used to predict the level of corn adulteration. The result shows that all individual regression models using individual wet and dry samples are better than that of global regression models using combined wet and dry samples. The best calibration model for individual wet and dry and combined samples is obtained for the PLSR model with a coefficient of determination in the range of 0.83–0.93 and RMSE below 6% (w/w) for calibration and validation. However, the error prediction in terms of RMSEP and bias were highly increased when the individual regression model was used to predict the level of corn adulteration with differences in the bean processing method. The obtained results demonstrate that the use of the global PLSR model is better in predicting the level of corn adulteration. The error prediction for this global model is acceptable with low RMSEP and bias for both individual and combined prediction samples. The obtained RPD_p and RER_p in prediction for the global PLSR model are more than two and five for individual and combined samples, respectively. The proposed method using UV–Vis spectroscopy with a global PLSR model can be applied to quantify the level of corn adulteration in peaberry ground roasted coffee with different bean processing methods.