Impact of Coffee Bean Roasting on the Content of Pyridines Determined by Analysis of Volatile Organic Compounds

Detection of several volatile organic compounds through Ar+ induced chemical ionisation using inductively coupled plasma-tandem mass spectrometry (ICP-MS/MS)

A new analytical technique for detection of organic compounds using inductively coupled plasma-tandem mass spectrometry (ICP-MS/MS) is described. Volatile organic compounds (VOCs) were introduced into the collision/reaction cell (CRC), instead of through the ICP ion source, and the molecules were ionised through an ion reaction, induced by collision with the primary ions (Ar+) produced in the ICP. The ionisation characteristics of this new approach were investigated by mass spectrometric analysis of eight VOCs (i.e., benzene, toluene, ethyl acetate, methyl butyrate, ethyl butyrate, pentyl acetate, pyridine, and 2-methylfuran). These molecules were detected as molecular ions (M+), protonated ions ([M + H]+), or deprotonated ions ([M - H]+), demonstrating that soft ionisation was achieved by the present ionisation protocol using ICP-MS/MS. In addition, a volatile selenium-containing organic compound, dimethyl diselenide (Se2(CH3)2), was also analysed to investigate the feasibility of this ionisation protocol to achieve soft and hard ionisation simultaneously. Several Se-related ions such as Se+, SeH+, Se2+, [SeCH3]+, and [Se2CH3]+, together with [Se2(CH3)2]+, were observed, suggesting that while soft ionisation was possible, ion reaction-induced-fragmentation and hard ionisation also occurred. To demonstrate the analytical capability of the present technique, volatile components released from coffee beans were subjected to the present mass spectrometric analysis. Many ion peaks originating from VOCs were detected from the coffee beans. The data obtained here demonstrated that ICP-MS equipped with a CRC can become an effective tool for analyzing both elements and molecules.

A Recyclable Polypropylene Multilayer Film Maintaining the Quality and the Aroma of Coffee Pods during Their Shelf Life

Films for coffee-pod packaging usually contain aluminium as an impermeable foil that is not recyclable and has to be discharged as waste. In this study, a recyclable polypropylene multilayer film is proposed as an alternative. The performance on the chemical composition of coffee was evaluated and compared to that of film containing aluminium (standard). The oxygen in the headspace, moisture, lipidic oxidation, and volatile organic compounds were studied in coffee pods during storage for 12 months at 25 and 40 °C. In addition, the acidity and acceptability of extracted coffee were evaluated. In the polypropylene-packaged pods, the percentage of oxygen during storage at 25 °C was lower than that in the standard. Moisture was not affected by the type of packaging materials. No differences were found between the peroxide values, except in pods stored for 3, 10, and 11 months at 25 °C, where they were even lower than the standard. Furans and pyrazines were the main volatile organic compounds detected. No differences were found in the pH and titratable acidity of the coffee brew either. All samples were well accepted by consumers without any perceived difference related to the packaging film. The polypropylene multilayer film is a sustainable recyclable material with high performance, in particular, against oxygen permeation.

Coffee brewing sonoreactor for reducing the time of cold brew from several hours to minutes while maintaining sensory attributes

This research designed and developed an ultrasonic reactor for a fast and on demand production of cold brew coffee, remarkably reducing the brewing time from 24 h to less than 3 min. The technology was engineered by utilizing resonance to induce ultrasonic waves around the walls of the brewing basket of an espresso machine. The sound transmission system comprised a transducer, a horn and a brewing basket. This arrangement transformed the coffee basket into an effective sonoreactor that injected sound waves at multiple points through its walls, thereby generating multiple regions for acoustic cavitation within the reactor. Furthermore, acoustic streaming induced greater mixing and enhanced mass transfer during brewing. The design was accomplished by modeling the transmission of sound, and acoustic cavitation. Brew characterization and chemical composition analysis was performed, considering factors such as pH, acidity, color, and the composition of caffeine, fatty acids, and volatiles. The efficiency of the extraction increased by decreasing the basket loading percentage (BLP). For instance, sonicating at 100 W doubled the extraction yield and caffeine concentration, from 15.05 % to 33.44 % at BLP = 33 %, and from 0.91 mg/mL to 1.84 mg/mL at BLP = 67 %, respectively. The total fatty acids increased from 1.16 mg/mL to 9.20 mg/mL, representing an eightfold increase, at BLP = 33 %. Finally, a sensory analysis was conducted to evaluate appearance, aroma, texture, flavor, and aftertaste, which demonstrated that coffee brewed for 1 and 3 min in the sonoreactor exhibited almost undistinguishable properties compared to a standard 24 h brewing without ultrasound.

Can a cup a day keep cancer away? A systematic review exploring the potential of coffee constituents in preventing oral squamous cell carcinoma

BACKGROUND

Coffee is one of the most consumed beverages in the world. Containing an abundance of bioactive molecules including polyphenols and flavonoids, the constituents of this beverage may exert antiproliferative, antioxidant and anti-inflammatory effects.

METHODS

We conducted a systematic review to summarise the available evidence on the anticancer effects of coffee constituents and their potential therapeutic use for oral squamous cell carcinoma (OSCC). Studies were identified through a comprehensive search of OVID MEDLINE, OVID EMBASE and Web of Science, including articles from any year up to 15 May 2023.

RESULTS

Of the 60 reviewed papers, 45 were in vitro, 1 was in silico and 8 were in vivo exclusively. The remaining studies combined elements of more than one study type. A total of 55 studies demonstrated anti-proliferative effects, whilst 12 studies also investigated migration and invasion of neoplastic cells. The constituents studied most frequently were quercetin and epigallocatechin gallate (EGCG), demonstrating various cytotoxic effects whilst also influencing apoptotic mechanisms in cancer cell lines. Dose-dependent responses were consistently found amongst the studied constituents.

CONCLUSION

Whilst there was heterogeneity of study models and methods, consistent use of specific models such as SCC25 for in vitro studies and golden hamsters for in vivo studies enabled relative comparability. The constituents of coffee have gained significant interest over the last 30 years, particularly in the last decade, and present an area of interest with significant public health implications. Currently, there is a paucity of literature on utilization of active coffee constituents for the therapeutic treatment of oral cancers.

Effect of Extraction Methods on Aroma Profile, Antioxidant Activity and Sensory Acceptability of Specialty Coffee Brews

Specialty coffees from various geographical origins were processed using different extraction methods. Four extraction techniques were employed: cold brew (CB), espresso (ES), French press (FR), and aeropress (AE). The potential health benefits of coffee brews were linked to their antioxidant activity, as determined by the DPPH assay, and total polyphenol content (TPC) measured through the Folin-Ciocalteu reducing-capacity assay. The Columbia (C) espresso coffee type (omni-roasting) exhibited the highest antioxidant activity (86.31 ± 0.70) μmol/100 mL, with a TPC value of (44.41 ± 0.35) mg GAE/g. Quantitative analyses of caffeine and chlorogenic acid were conducted using high-performance liquid chromatography (HPLC). The evaluation of coffee aroma profiles involved the application of headspace solid-phase microextraction/gas chromatography-mass spectrometry (HS-SPME/GC-MS) and was complemented by sensory analysis following the Specialty Coffee Association (SCA) standard protocol. The predominant volatile compounds found in all samples included furans, phenols, pyrazines, and terpenes. The EY espresso type (medium dark roasting) had the highest levels of most coffee volatiles. The C cold brew type (omni-roasting) was rated as the preferred coffee in terms of its sensory characteristics and flavour. In summary, ES and CB were found to be more effective extraction methods for the parameters assessed.

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.

Influence of Coffee Variety and Processing on the Properties of Parchments as Functional Bioadditives for Biobased Poly(butylene succinate) Composites

Fermented polymers like biobased poly(butylene succinate) (BioPBS) have become more relevant as technical substitutes for ductile petrochemical-based polymers but require biogenic functional additives to deaccelerate undesired thermo-oxidative degradation and keep a fully biobased character. In this paper, the influence of coffee parchment (PMT) from two different varieties and processings on the thermo-oxidative stabilization and mechanical properties of poly(butylene succinate) composites up to 20 wt.-% PMT were investigated. Micronized with a TurboRotor mill, both PMT powders differ in particle size and shape, moisture ab- and adsorption behavior and antioxidative properties. It could be shown that pulped-natural PMT consists partially of coffee cherry residues, which leads to a higher total polyphenol content and water activity. The homogeneous PMT from fully washed processing has a higher thermal degradation resistance but consists of fibers with larger diameters. Compounded with the BioPBS and subsequent injection molded, the fully washed PMT leads to higher stiffness and equal tensile strength but lower toughness compared to the pulped-natural PMT, especially at lower deformation speed. Surprisingly, the fully washed PMT showed a higher stability against thermo-oxidative decomposition despite the lower values in the total phenol content and antioxidative activity. The required antioxidative stabilizers might be extracted at higher temperatures from the PMT fibers, making it a suitable biogenic stabilizer for extrusion processes.

Environmental Engineering Applications of Electronic Nose Systems Based on MOX Gas Sensors

Nowadays, the electronic nose (e-nose) has gained a huge amount of attention due to its ability to detect and differentiate mixtures of various gases and odors using a limited number of sensors. Its applications in the environmental fields include analysis of the parameters for environmental control, process control, and confirming the efficiency of the odor-control systems. The e-nose has been developed by mimicking the olfactory system of mammals. This paper investigates e-noses and their sensors for the detection of environmental contaminants. Among different types of gas chemical sensors, metal oxide semiconductor sensors (MOXs) can be used for the detection of volatile compounds in air at ppm and sub-ppm levels. In this regard, the advantages and disadvantages of MOX sensors and the solutions to solve the problems arising upon these sensors' applications are addressed, and the research works in the field of environmental contamination monitoring are overviewed. These studies have revealed the suitability of e-noses for most of the reported applications, especially when the tools were specifically developed for that application, e.g., in the facilities of water and wastewater management systems. As a general rule, the literature review discusses the aspects related to various applications as well as the development of effective solutions. However, the main limitation in the expansion of the use of e-noses as an environmental monitoring tool is their complexity and lack of specific standards, which can be corrected through appropriate data processing methods applications.

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

The aim of this study was to determine the emission of organic volatile compounds from maize grain as a function of granularity and packing density of bulk material in conditions imitating processes occurring in silos. The study was carried out with the use of a gas chromatograph and an electronic nose, which was designed and constructed at the Institute of Agrophysics of PAS and has a matrix of eight MOS (metal oxide semiconductor) sensors. A 20-L volume of maize grain was consolidated in the INSTRON testing machine with pressures of 40 and 80 kPa. The control samples were not compacted, and the maize bed had bulk density. The analyses were carried out at a moisture content of 14% and 17% (w.b.-wet basis). The measurement system facilitated quantitative and qualitative analyses of volatile organic compounds and the intensity of their emission during 30-day storage. The study determined the profile of volatile compounds as a function of storage time and the grain bed consolidation level. The research results indicated the degree of grain degradation induced by the storage time. The highest emission of volatile compounds was recorded on the first four days, which indicated a dynamic nature of maize quality degradation. This was confirmed by the measurements performed with electrochemical sensors. In turn, the intensity of the volatile compound emission decreased in the next stage of the experiments, which showed a decline in the quality degradation dynamics. The sensor responses to the emission intensity decreased significantly at this stage. The electronic nose data on the emission of VOCs (volatile organic compounds) as well as grain moisture and bulk volume can be helpful for the determination of the quality of stored material and its suitability for consumption.

Coffee bean particle motion in a rotating drum measured using Positron Emission Particle Tracking (PEPT)

Physicochemical transformation of coffee during roasting depends on the applied time-temperature profile (i.e., rate of heat transfer), with heat transfer phenomena governed by particle dynamics. Positron Emission Particle Tracking (PEPT), a non-invasive imaging technique, was used here to characterise the granular flow of coffee in a real, pilot-scale rotating drum roaster. The experimental study established the impact of drum speed, batch size and bean density (i.e., roast degree) on the system's particle dynamics. Particle motion data revealed two distinct regions: (i) a disperse (low occupancy, high velocity) region of in-flight particles and (ii) a dense (high occupancy, low velocity) bean bed. Implications of these results for heat transfer suggest that controlling drum speed for different density coffees will provide roaster operators with a tool to modulate conductive heat transfer from the heated drum to the bean bed. These comprehensive data thus inform roasting best practices and support the development of physics-driven models coupling heat and mass transfer to particle dynamics.

Determining the shelf life and quality changes of potatoes (Solanum tuberosum) during storage using electronic nose and machine learning

The activities of alpha-amylase, beta-amylase, sucrose synthase, and invertase enzymes are under the influence of storage conditions and can affect the structure of starch, as well as the sugar content of potatoes, hence altering their quality. Storage in a warehouse is one of the most common and effective methods of storage to maintain the quality of potatoes after their harvest, while preserving their freshness and sweetness. Smart monitoring and evaluation of the quality of potatoes during the storage period could be an effective approach to improve their freshness. This study is aimed at assessing the changes in the potato quality by an electronic nose (e-nose) in terms of the sugar and carbohydrate contents. Three potato cultivars (Agria, Santé, and Sprite) were analyzed and their quality variations were separately assessed. Quality parameters (i.e. sugar and carbohydrate contents) were evaluated in six 15-day periods. The e-nose data were analyzed by means of chemometric methods, including principal component analysis (PCA), linear data analysis (LDA), support vector machine (SVM), and artificial neural network (ANN). Quadratic discriminant analysis (QDA) and multivariate discrimination analysis (MDA) offer the highest accuracy and sensitivity in the classification of data. The accuracy of all methods was higher than 90%. These results could be applied to present a new approach for the assessment of the quality of stored potatoes.

Investigating Changes in pH and Soluble Solids Content of Potato during the Storage by Electronic Nose and Vis/NIR Spectroscopy

Potato is an important agricultural product, ranked as the fourth most common product in the human diet. Potato can be consumed in various forms. As customers expect safe and high-quality products, precise and rapid determination of the quality and composition of potatoes is of crucial significance. The quality of potatoes may alter during the storage period due to various phenomena. Soluble solids content (SSC) and pH are among the quality parameters experiencing alteration during the storage process. This study is thus aimed to assess the variations in SSC and pH during the storage of potatoes using an electronic nose and Vis/NIR spectroscopic techniques with the help of prediction models including partial least squares (PLS), multiple linear regression (MLR), principal component regression (PCR), support vector regression (SVR) and an artificial neural network (ANN). The variations in the SSC and pH are ascending and significant. The results also indicate that the SVR model in the electronic nose has the highest prediction accuracy for the SSC and pH (81, and 92%, respectively). The artificial neural network also managed to predict the SSC and pH at accuracies of 83 and 94%, respectively. SVR method shows the lowest accuracy in Vis/NIR spectroscopy while the PLS model exhibits the best performance in the prediction of the SSC and pH with respective precision of 89 and 93% through the median filter method. The accuracy of the ANN was 85 and 90% in the prediction of the SSC and pH, respectively.

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

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.

Study on the Suitability of Tea Cultivars for Processing Oolong Tea from the Perspective of Aroma Based on Olfactory Sensory, Electronic Nose, and GC-MS Data Correlation Analysis

The oolong tea aroma is shown to consist of cultivar aroma and technical aroma in this study based on the aroma differences between oolong tea products of cultivars of different suitability, as determined by correlation analysis of olfactory, sensory, electronic nose, and GC-MS data. Human senses were significantly affected by the aroma components, which included eight terpene metabolites (β-Ocimene, (Z)-Furan linalool oxide, linalool, (3E)-4,8-Dimethyl-1,3,7-nonatriene, (E)-Pyranoid linalool oxide, γ-Elemene, Humulene, (Z,E)-α-Farnesene), three carotenoid metabolites (β-Ionone, (Z)-Geranylacetone and 6-methyl-5-Hepten -2-one), three lipid metabolites ((Z)-3-Hexenyl (Z)-3-hexenoate, Butanoic acid hexyl ester, and (Z)-Jasmone), four amino acid metabolites (Methyl salicylate, Geranyl isovalerate, indole, and Phenylethyl alcohol), and six thermal reaction products (2-Pentylfuran, Octanal, Decanal, (E,E)-2,4-Nonadienal, (Z)-2-Decenal, and (E)-2-Undecenal). Meanwhile, several aroma compounds (such as (E)-Nerolidol and α-Farnesene), mainly comprising the “technical aroma” formed in the processing mode, were noted to be less closely related to cultivar suitability. This study sheds light on the aroma characteristics of different tea cultivars for oolong tea processing.

Recent advances in analytical strategies for coffee volatile studies: Opportunities and challenges

Coffee has attracted significant research interest owing to its complex volatile composition and aroma, which imparts a pleasant sensorial experience that remains challenging to analyse and interpret. This review summarises analytical challenges associated with coffee's volatile and matrix complexity, and recent developments in instrumental techniques to resolve them. The benefits of state-of-the-art analytical techniques applied to coffee volatile analysis from experimental design to sample preparation, separation, detection, and data analysis are evaluated. Complementary method selection coupled with progressive experimental design and data analysis are vital to unravel the increasing comprehensiveness of coffee volatile datasets. Considering this, analytical workflows for conventional, targeted, and untargeted coffee volatile analyses are thus proposed considering the trends towards sorptive extraction, multidimensional gas chromatography, and high-resolution mass spectrometry. In conclusion, no single analytical method addresses coffee's complexity in its entirely, and volatile analysis must be tailored to the key objectives and concerns of the analyst.

Application of MOS Gas Sensors Coupled with Chemometrics Methods to Predict the Amount of Sugar and Carbohydrates in Potatoes

Five potato varieties were studied using an electronic nose with nine MOS sensors. Parameters measured included carbohydrate content, sugar level, and the toughness of the potatoes. Routine tests were carried out while the signals for each potato were measured, simultaneously, using an electronic nose. The signals obtained indicated the concentration of various chemical components. In addition to support vector machines (SVMs that were used for the classification of the samples, chemometric methods, such as the partial least squares regression (PLSR) method, the principal component regression (PCR) method, and the multiple linear regression (MLR) method, were used to create separate regression models for sugar and carbohydrates. The predictive power of the regression models was characterized by a coefficient of determination (R²), a root-mean-square error of prediction (RMSEP), and offsets. PLSR was able to accurately model the relationship between the smells of different types of potatoes, sugar, and carbohydrates. The highest and lowest accuracy of models for predicting sugar and carbohydrates was related to Marfona potatoes and Sprite cultivar potatoes. In general, in all cultivars, the accuracy in predicting the amount of carbohydrates was somewhat better than the accuracy in predicting the amount of sugar. Moreover, the linear function had 100% accuracy for training and validation in the C-SVM method for classification of five potato groups. The electronic nose could be used as a fast and non-destructive method for detecting different potato varieties. Researchers in the food industry will find this method extremely useful in selecting the desired product and samples.