Chemometric Modeling of Coffee Sensory Notes through Their Chemical Signatures: Potential and Limits in Defining an Analytical Tool for Quality Control

Bressanello, Davide; Liberto, Erica; Cordero, Chiara; Sgorbini, Barbara; Pellegrino, Gloria; Ruosi, Manuela Rosanna; Bicchi, Carlo

doi:10.1021/acs.jafc.8b01340

Cited by 44 publications

(38 citation statements)

References 37 publications

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“…Thus, the aroma complexity of blueberries has been profiled recently through SPME‐GC‐MS analysis of five cultivars at four ripening stages . Coffee sensory notes have been recently modelled through their chemical signatures obtained using HS‐SPME‐GC‐MS and a chemometric‐driven approach . Taking advantage of the last developments in gas chromatography, comprehensive two‐dimensional GC (GCxGC) coupled to MS has been recently used for instance to fingerprint high‐quality cocoa at early stages of processing .…”

Section: Introductionmentioning

confidence: 99%

“…2 Coffee sensory notes have been recently modelled through their chemical signatures obtained using HS-SPME-GC-MS and a chemometric-driven approach. 3 Taking advantage of the last developments in gas chromatography, comprehensive two-dimensional GC (GCxGC) coupled to MS has been recently used for instance to fingerprint high-quality cocoa at early stages of processing. 4 Liquid chromatography alone (LC), or coupled to MS (LC-MS), was also used for fingerprinting with some success.…”

Section: Introductionmentioning

confidence: 99%

“…with the measured product ions [MH + ] and measured primary ions [H3 O + ], and where t R is the average resident time of the ions in the drift-tube that can be measured or calculated from mobility values reported in the literature 71. The high density of primary ions H 3 O + provided by pure and intense ion sources, and not diluting the sample gas in an additional buffer gas, contribute to enhance significantly the…”

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confidence: 99%

“…The scan speed was 499.5 ms for a mass range of m/z 0 to 250. The mass resolution varied from 3500 to 4500 along the scanned mass range.The raw data were subsequently corrected for transmission and peak areas converted into concentration (part per billion by volume) using the primary ions H3 O + and (H 2 O) 2 H + measured by their respective 18 O isotopologues and using a common coefficient rate (k = 2.10 −9 cm 3 /s) in the formula determined by Lindinger et al, 71 resulting in absolute HS VOC concentration. The use of the same reaction rate coefficient for all the VOCs produces a systematic error that is typically negligible even if the estimation accuracy can be improved if the actual reaction rate coefficient is known.…”

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confidence: 99%

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Volatile compounds profiling by using proton transfer reaction‐time of flight‐mass spectrometry (PTR‐ToF‐MS). The case study of dark chocolates organoleptic differences

et al. 2019

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Direct‐injection mass spectrometry (DIMS) techniques have evolved into powerful methods to analyse volatile organic compounds (VOCs) without the need of chromatographic separation. Combined to chemometrics, they have been used in many domains to solve sample categorization issues based on volatilome determination. In this paper, different DIMS methods that have largely outperformed conventional electronic noses (e‐noses) in classification tasks are briefly reviewed, with an emphasis on food‐related applications. A particular attention is paid to proton transfer reaction mass spectrometry (PTR‐MS), and many results obtained using the powerful PTR‐time of flight‐MS (PTR‐ToF‐MS) instrument are reviewed. Data analysis and feature selection issues are also summarized and discussed. As a case study, a challenging problem of classification of dark chocolates that has been previously assessed by sensory evaluation in four distinct categories is presented. The VOC profiles of a set of 206 chocolate samples classified in the four sensory categories were analysed by PTR‐ToF‐MS. A supervised multivariate data analysis based on partial least squares regression‐discriminant analysis allowed the construction of a classification model that showed excellent prediction capability: 97% of a test set of 62 samples were correctly predicted in the sensory categories. Tentative identification of ions aided characterisation of chocolate classes. Variable selection using dedicated methods pinpointed some volatile compounds important for the discrimination of the chocolates. Among them, the CovSel method was used for the first time on PTR‐MS data resulting in a selection of 10 features that allowed a good prediction to be achieved. Finally, challenges and future needs in the field are discussed.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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confidence: 99%

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confidence: 99%

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Volatile compounds profiling by using proton transfer reaction‐time of flight‐mass spectrometry (PTR‐ToF‐MS). The case study of dark chocolates organoleptic differences

et al. 2019

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“…Flavour can be considered the signature of a product [5][6][7][8], and defining a relationship between chemical profile and aroma sensory impact is an important challenge for both the analytical and industrial fields, as they aim to achieve an objective and fast routine evaluation of a product with an automatic analytical procedure [9][10][11][12][13][14].…”

Section: Introductionmentioning

confidence: 99%

HS-SPME-MS-Enose Coupled with Chemometrics as an Analytical Decision Maker to Predict In-Cup Coffee Sensory Quality in Routine Controls: Possibilities and Limits

et al. 2019

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The quality assessment of the green coffee that you will go to buy cannot be disregarded from a sensory evaluation, although this practice is time consuming and requires a trained professional panel. This study aims to investigate both the potential and the limits of the direct headspace solid phase microextraction, mass spectrometry electronic nose technique (HS-SPME-MS or MS-EN) combined with chemometrics for use as an objective, diagnostic and high-throughput technique to be used as an analytical decision maker to predict the in-cup coffee sensory quality of incoming raw beans. The challenge of this study lies in the ability of the analytical approach to predict the sensory qualities of very different coffee types, as is usual in industry for the qualification and selection of incoming coffees. Coffees have been analysed using HS-SPME-MS and sensory analyses. The mass spectral fingerprints (MS-EN data) obtained were elaborated using: (i) unsupervised principal component analysis (PCA); (ii) supervised partial least square discriminant analysis (PLS-DA) to select the ions that are most related to the sensory notes investigated; and (iii) cross-validated partial least square regression (PLS), to predict the sensory attribute in new samples. The regression models were built with a training set of 150 coffee samples and an external test set of 34. The most reliable results were obtained with acid, bitter, spicy and aromatic intensity attributes. The mean error in the sensory-score predictions on the test set with the available data always fell within a limit of ±2. The results show that the combination of HS-SPME-MS fingerprints and chemometrics is an effective approach that can be used as a Total Analysis System (TAS) for the high-throughput definition of in-cup coffee sensory quality. Limitations in the method are found in the compromises that are accepted when applying a screening method, as opposed to human evaluation, in the sensory assessment of incoming raw material. The cost-benefit relationship of this and other screening instrumental approaches must be considered and weighed against the advantages of the potency of human response which could thus be better exploited in modulating blends for sensory experiences outside routine.

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Application of SPME‐GC‐TOFMS, E‐nose, and sensory evaluation to investigate the flavor characteristics of Chinese Yunnan coffee at three different conditions (beans, ground powder, and brewed coffee)

Cui

Liu

Chen

et al. 2020

Flavour & Fragrance J

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SPME‐GC‐TOFMS, E‐nose, and sensory evaluation were used to explore the volatile organic compounds (VOCs) in four Chinese Yunnan coffee at three conditions (beans, ground powder, and brewed coffee). VOCs were detected by GC‐TOFMS and compared the difference between all samples, depending on the VOCs in the coffee sample. The E‐nose was used for rapid detection to differentiate the sample. The two results are analyzed by principal component analysis (PCA). Quantitative description analysis (QDA) was used to evaluate the flavor profiles of coffee samples. The results shown that GC‐TOFMS detected 412, 498, and 294 VOCs in roasted, ground powder, and brewed coffee, respectively. The PCA of SPME‐GC‐TOFMS results shown that Nankang coffee was mainly related to ketone compounds; the aroma of Hongguang coffee was determined by dimethyl disulfide and acetic acid; pyrazine and ketone compounds were important to Hainan coffee; ketone and ester compounds were dominated in Xinghuan coffee. The results of E‐nose shown that the first two principal components (PCs) accounted for 97.3%, 92.5%, and 93.8% of variances in roasted, ground powder, and brewed coffee, respectively. The different brands of coffee samples at the same condition shown separated locations on the PCA results of E‐nose. Sensory evaluation shown the special flavor of coffee samples, Nankang coffee with a bake flavor, Hongguang coffee had chocolate and nutty flavors, Hainan coffee had the caramel‐like aroma, and the aroma Xinghuan coffee was sweet. This study could provide a better understanding of Chinese coffee produced in Yunnan province.

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Chemometric Modeling of Coffee Sensory Notes through Their Chemical Signatures: Potential and Limits in Defining an Analytical Tool for Quality Control

Cited by 44 publications

References 37 publications

Volatile compounds profiling by using proton transfer reaction‐time of flight‐mass spectrometry (PTR‐ToF‐MS). The case study of dark chocolates organoleptic differences

Volatile compounds profiling by using proton transfer reaction‐time of flight‐mass spectrometry (PTR‐ToF‐MS). The case study of dark chocolates organoleptic differences

HS-SPME-MS-Enose Coupled with Chemometrics as an Analytical Decision Maker to Predict In-Cup Coffee Sensory Quality in Routine Controls: Possibilities and Limits

Application of SPME‐GC‐TOFMS, E‐nose, and sensory evaluation to investigate the flavor characteristics of Chinese Yunnan coffee at three different conditions (beans, ground powder, and brewed coffee)

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