How to Identify Roast Defects in Coffee Beans Based on the Volatile Compound Profile

Abstract

The aim of this study was to detect and identify the volatile compounds in coffee that was obtained in defect roast processes versus standard roasting and to determine the type and strength of the correlations between the roast defects and the volatile compound profile in roasted coffee beans. In order to achieve this goal, the process of coffee bean roasting was set to produce an underdeveloped coffee defect, an overdeveloped coffee defect, and defectless coffee. The “Typica” variety of Arabica coffee beans was used in this study. The study material originated from a plantation that is located at an altitude of 1400–2000 m a.s.l. in Huehuetenango Department, Guatemala. The analyses were carried out with the use of gas chromatography/mass spectrometry (GC–MS) and an electronic nose. This study revealed a correlation between the identified groups of volatile compounds and the following coffee roasting parameters: the time to the first crack, the drying time, and the mean temperatures of the coffee beans and the heating air. The electronic nose helped to identify the roast defects.

Nondestructive Technique for Identifying Adulteration and Additives in Lemon Juice Based on Analyzing Volatile Organic Compounds (VOCs)

“…Since the value performance in the training phase is lower than that in the experimental phase, there is no evidence of under-or overfitting. These results are consistent with the studies obtained by other researchers that have been conducted with the help of the E-nose and ANNs [69][70][71][72][73]. Khorramifar, Rasekh, Karami, Malaga-Toboła, and Gancarz [42] used an ANN and an electronic nose to classify potato varieties with a 97.8% accuracy.…”

Effect of the Consolidation Level on Organic Volatile Compound Emissions from Maize during Storage

“…Therefore, for this one compound, based on the literature data and with a low level of match of the other identified compounds for this retention time, it was considered that these are sufficient grounds to include this one compound in the presented study results, which has a lower level of match but over 60%. The obtained results were compared with the literature data for similar materials [29].…”

Application of Machine Learning to Assess the Quality of Food Products—Case Study: Coffee Bean

“…Arabica coffee is one of many group of food products that exhibit beneficial effects on the human body [3][4][5]. This is related to its content of key bioactive compounds, such as caffeine, lipids, polyphenols, vitamins, minerals and aroma compounds [3,4,6].…”

“…Arabica coffee is one of many group of food products that exhibit beneficial effects on the human body [3][4][5]. This is related to its content of key bioactive compounds, such as caffeine, lipids, polyphenols, vitamins, minerals and aroma compounds [3,4,6]. In the literature, the consumption of Arabica coffee has been shown to help neutralize free radicals in the body, reducing the risk of chronic diseases including cardiovascular disease [7,8], Alzheimer's and Parkinson's disease, and liver disease [9][10][11][12].…”

“…Therefore, the process of sourcing and selecting the right beans is important in analyzing the health properties of coffee. The interest in health properties has attracted the attention of scientists as well as healthy eaters [3,4,11,12,14,[16][17][18].…”