Common roasting defects in coffee: Aroma composition, sensory characterization and consumer perception

Abstract The demand for high quality and specialty coffee is increasing worldwide. In order to meet these demands, a more uniform and standardized quality assessment of coffee is essential. The aim of this study was to make a sensory scientific and chemical characterization of common roasting defects in coffee, and to investigate their potential relevance for consumers’ acceptance of coffee. To this end, six time-temperature roasting profiles based on a single origin Arabica bean were developed: one ‘normal’, representing a reference coffee free of defects, and five common roast defects (‘dark’, ‘light’, ‘scorched’, ‘baked’ and ‘underdeveloped’. The coffee samples obtained from these beans were evaluated by means of (1) aroma analysis by Gas Chromatography-Mass Spectrometry (GC–MS), (2) sensory descriptive analysis (DA) by trained assessors, and (3) hedonic and sensory evaluation by consumers using a Check-All-That-Apply (CATA) questionnaire. Multivariate analyses of aroma, DA, and CATA data produced similar sample spaces, showing a clear opposition of the light roast to the dark and scorched roasts), with the normal roast having average values of key aroma compounds. The DA data confirmed this indications and showed the normal roast to have a balanced sensory profile compared to the other defects. Importantly, the normal roast was also significantly preferred in the consumer test ( N = 83 ), and significantly associated to positive CATA attributes ‘Harmonic’, ‘Pleasant’, and ‘Balanced’. Taken overall, the results provide a solid basis for understanding chemical and sensory markers associated with common roasting defects, which coffee professionals may use internally in both quality control and product development applications.

[1]  Michael O'Mahony,et al.  At What Temperatures Do Consumers Like to Drink Coffee?: Mixing Methods , 2002 .

[2]  J. Hayes,et al.  Allelic variation in TAS2R bitter receptor genes associates with variation in sensations from and ingestive behaviors toward common bitter beverages in adults. , 2011, Chemical senses.

[3]  D. Giacalone,et al.  Quality does not sell itself: divergence between ‘objective’ product quality and preference for coffee in naïve consumers , 2016 .

[4]  J. S. Ribeiro,et al.  Prediction models for Arabica coffee beverage quality based on aroma analyses and chemometrics. , 2012, Talanta.

[5]  A. S. Franca,et al.  Discrimination between defective and non-defective Brazilian coffee beans by their volatile profile , 2008 .

[6]  Edgar Chambers,et al.  Evolution of sensory aroma attributes from coffee beans to brewed coffee. , 2011 .

[7]  Sébastien Lê,et al.  FactoMineR: An R Package for Multivariate Analysis , 2008 .

[8]  Ian D Fisk,et al.  Discrimination of roast and ground coffee aroma , 2012, Flavour.

[9]  Harry T. Lawless,et al.  Sensory Evaluation of Food: Principles and Practices , 1998 .

[10]  Alistair Paterson,et al.  Gender preference in hedonic ratings for espresso and espresso-milk coffees. , 2000 .

[11]  M. Petersen,et al.  Influence of serving temperature on flavour perception and release of Bourbon Caturra coffee. , 2017, Food chemistry.

[12]  John C. Castura,et al.  Existing and new approaches for the analysis of CATA data , 2013 .

[13]  John Prescott,et al.  The impact of individual variations in taste sensitivity on coffee perceptions and preferences , 2015, Physiology & Behavior.

[14]  Jérôme Pagès,et al.  Multiple factor analysis with confidence ellipses: a methodology to study the relationships between sensory and instrumental data , 2005 .

[15]  Felix Escher,et al.  Coffee roasting and aroma formation: application of different time-temperature conditions. , 2008, Journal of agricultural and food chemistry.

[16]  Unikl Micet,et al.  SENSORY EVALUATION OF FOOD , 2015 .

[17]  S. Jaeger,et al.  Check-all-that-apply questions: Influence of attribute order on sensory product characterization , 2013 .

[18]  Carl P. Borchgrevink,et al.  Consumer preferred hot beverage temperatures , 1999 .

[19]  J. S. Ribeiro,et al.  Prediction of sensory properties of Brazilian Arabica roasted coffees by headspace solid phase microextraction-gas chromatography and partial least squares. , 2009, Analytica chimica acta.

[20]  J. S. Ribeiro,et al.  Chemometric models for the quantitative descriptive sensory analysis of Arabica coffee beverages using near infrared spectroscopy. , 2011, Talanta.

[21]  Ian D Fisk,et al.  Determination of volatile marker compounds of common coffee roast defects , 2016, Food chemistry.

[22]  Paula Varela,et al.  An alternative way to uncover drivers of coffee liking: Preference mapping based on consumers’ preference ranking and open comments , 2014 .

[23]  W. Bredie,et al.  Stimulus collative properties and consumers’ flavor preferences ☆ , 2014, Appetite.

[24]  K. P. P. Nair,et al.  The Agronomy and Economy of Important Tree Crops of the Developing World , 2010 .

[25]  N. Guzman,et al.  Comparison of Results from Cupping and Descriptive Sensory Analysis of Colombian Brewed Coffee: Coffee: Comparing Cupping and Descriptive Analysis , 2014 .

[26]  Alejandro M. Feria-Morales,et al.  Examining the case of green coffee to illustrate the limitations of grading systems/expert tasters in sensory evaluation for quality control , 2002 .

[27]  J. N. Wintgens Green Coffee Defects , 2008 .

[28]  J. Prescott,et al.  Caffeine metabolism rate influences coffee perception, preferences and intake , 2016 .

[29]  Felix Escher,et al.  Pore Structure of Coffee Beans Affected by Roasting Conditions , 2000 .

[30]  S. Ponte The 'Latte Revolution'? Regulation, Markets and Consumption in the Global Coffee Chain , 2002 .

[31]  Fredericka Brown,et al.  Calculating the optimum temperature for serving hot beverages. , 2008, Burns : journal of the International Society for Burn Injuries.