Discrimination of Cocoa Liquors Based on Their Odor Fingerprint: a Fast GC Electronic Nose Suitability Study

FlavorMiner: a machine learning platform for extracting molecular flavor profiles from structural data

Flavor is the main factor driving consumers acceptance of food products. However, tracking the biochemistry of flavor is a formidable challenge due to the complexity of food composition. Current methodologies for linking individual molecules to flavor in foods and beverages are expensive and time-consuming. Predictive models based on machine learning (ML) are emerging as an alternative to speed up this process. Nonetheless, the optimal approach to predict flavor features of molecules remains elusive. In this work we present FlavorMiner, an ML-based multilabel flavor predictor. FlavorMiner seamlessly integrates different combinations of algorithms and mathematical representations, augmented with class balance strategies to address the inherent class of the input dataset. Notably, Random Forest and K-Nearest Neighbors combined with Extended Connectivity Fingerprint and RDKit molecular descriptors consistently outperform other combinations in most cases. Resampling strategies surpass weight balance methods in mitigating bias associated with class imbalance. FlavorMiner exhibits remarkable accuracy, with an average ROC AUC score of 0.88. This algorithm was used to analyze cocoa metabolomics data, unveiling its profound potential to help extract valuable insights from intricate food metabolomics data. FlavorMiner can be used for flavor mining in any food product, drawing from a diverse training dataset that spans over 934 distinct food products.Scientific Contribution FlavorMiner is an advanced machine learning (ML)-based tool designed to predict molecular flavor features with high accuracy and efficiency, addressing the complexity of food metabolomics. By leveraging robust algorithmic combinations paired with mathematical representations FlavorMiner achieves high predictive performance. Applied to cocoa metabolomics, FlavorMiner demonstrated its capacity to extract meaningful insights, showcasing its versatility for flavor analysis across diverse food products. This study underscores the transformative potential of ML in accelerating flavor biochemistry research, offering a scalable solution for the food and beverage industry.

Characterization of Pulse-Containing Cakes Using Sensory Evaluation and Instrumental Analysis

Despite the nutritional and environmental benefits of pulses, their incorporation into bakery products has been impeded by their characteristic off-flavour. This study characterizes five pulses (faba bean, chickpea, whole lentil, split pea and pinto bean) in a cake application with a 40% wheat flour substitution, alongside a control cake. Physicochemical analysis and sensory analysis using a consumer panel (n = 124) and instrumental analysis (GC E-nose) were conducted. The liking scores for the pulse-containing cakes were significantly lower compared to the control cake, but half of the participants preferred a pulse-containing cake, indicating their market potential. Both instrumental analysis and sensory evaluation identified the chickpea and faba bean cakes as most similar to the control, while the pea cake was the most divergent. This cake was described as beany and grassy by consumers, negatively affecting the overall acceptance. Consumers in the sensory study had difficulties in distinguishing between the chickpea and faba bean cakes. Similarly, based on the volatile profiles, the chickpea and faba bean cakes demonstrated the closest relationship. The alignment between sensory data and E-nose results supports the added value of instrumental techniques such as the GC E-nose in sensory research.

Kimchi Lactic Acid Bacteria Starter Culture: Impact on Fermented Malt Beverage Volatile Profile, Sensory Analysis, and Physicochemical Traits

Starter cultures used during the fermentation of malt wort can increase the sensory characteristics of the resulting beverages. This study aimed to explore the aroma composition and flavor recognition of malt wort beverages fermented with lactic acid bacteria (Levilactobacillus brevis WiKim0194) isolated from kimchi, using metabolomic profiling and electronic tongue and nose technologies. Four sugars and five organic acids were detected using high-performance liquid chromatography, with maltose and lactic acid present in the highest amounts. Additionally, e-tongue measurements showed a significant increase in the sourness (AHS), sweetness (ANS), and umami (NMS) sensors, whereas bitterness (SCS) significantly decreased. Furthermore, 20 key aroma compounds were identified using gas chromatography-mass spectrometry and 15 key aroma flavors were detected using an electronic nose. Vanillin, citronellol, and β-damascenone exhibited significant differences in the flavor profile of the beverage fermented by WiKim0194, which correlated with floral, fruity, and sweet notes. Therefore, we suggest that an appropriate starter culture can improve sensory characteristics and predict flavor development in malt wort beverages.

Effect of Light Conditions, Trichoderma Fungi and Food Polymers on Growth and Profile of Biologically Active Compounds in Thymus vulgaris and Thymus serpyllum

The research investigates the influence of different lighting conditions and soil treatments, in particular the application of food polymers separately and in combination with spores of Trichoderma consortium, on the growth and development of herbs-Thymus vulgaris and Thymus serpyllum. The metabolic analysis focuses on detecting changes in the levels of biologically active compounds such as chlorophyll a and b, anthocyanins, carotenoids, phenolic compounds (including flavonoids), terpenoids, and volatile organic compounds with potential health-promoting properties. By investigating these factors, the study aims to provide insights into how environmental conditions affect the growth and chemical composition of selected plants and to shed light on potential strategies for optimising the cultivation of these herbs for the improved quality and production of bioactive compounds. Under the influence of additional lighting, the growth of T. vulgaris and T. serpyllum seedlings was greatly accelerated, resulting in an increase in shoot biomass and length, and in the case of T. vulgaris, an increase in carotenoid and anthocyanin contents. Regarding secondary metabolites, the most pronounced changes were observed in total antioxidant capacity and flavonoid content, which increased significantly under the influence of additional lighting. The simultaneous or separate application of Trichoderma and food polymers resulted in an increase in flavonoid content in the leaves of both Thymus species. The increase in terpenoid content under supplemental light appears to be related to the presence of Trichoderma spores as well as food polymers added to the soil. However, the nature of these changes depends on the thyme species. Volatile compounds were analysed using an electronic nose (E-nose). Eight volatile compounds (VOCs) were tentatively identified in the vapours of T. vulgaris and T. serpyllum: α-pinene, myrcene, α-terpinene, γ-terpinene; 1,8-cineole (eucalyptol), thymol, carvacrol, and eugenol. Tendencies to increase the percentage of thymol and γ-terpinene under supplemental lighting were observed. The results also demonstrate a positive effect of food polymers and, to a lesser extent, Trichoderma fungi on the synthesis of VOCs with health-promoting properties. The effect of Trichoderma and food polymers on individual VOCs was positive in some cases for thymol and γ-terpinene.

Rapid analysis technologies with chemometrics for food authenticity field: A review

In recent years, the problem of food adulteration has become increasingly rampant, seriously hindering the development of food production, consumption, and management. The common analytical methods used to determine food authenticity present challenges, such as complicated analysis processes and time-consuming procedures, necessitating the development of rapid, efficient analysis technology for food authentication. Spectroscopic techniques, ambient ionization mass spectrometry (AIMS), electronic sensors, and DNA-based technology have gradually been applied for food authentication due to advantages such as rapid analysis and simple operation. This paper summarizes the current research on rapid food authenticity analysis technology from three perspectives, including breeds or species determination, quality fraud detection, and geographical origin identification, and introduces chemometrics method adapted to rapid analysis techniques. It aims to promote the development of rapid analysis technology in the food authenticity field.

Recent developments of e-sensing devices coupled to data processing techniques in food quality evaluation: a critical review

A greater demand for high-quality food is being driven by the growth of economic and technological advancements. In this context, consumers are currently paying special attention to organoleptic characteristics such as smell, taste, and appearance. Motivated to mimic human senses, scientists developed electronic devices such as e-noses, e-tongues, and e-eyes, to spot signals relative to different chemical substances prevalent in food systems. To interpret the information provided by the sensors' responses, multiple chemometric approaches are used depending on the aim of the study. This review based on the Web of Science database, endeavored to scrutinize three e-sensing systems coupled to chemometric approaches for food quality evaluation. A total of 122 eligible articles pertaining to the e-nose, e-tongue and e-eye devices were selected to conduct this review. Most of the performed studies used exploratory analysis based on linear factorial methods, while classification and regression techniques came in the second position. Although their applications have been less common in food science, it is to be noted that nonlinear approaches based on artificial intelligence and machine learning deployed in a big-data context have generally yielded better results for classification and regression purposes, providing new perspectives for future studies.

Authentication of Cocoa Products Based on Profiling and Fingerprinting Approaches: Assessment of Geographical, Varietal, Agricultural and Processing Features

Cocoa and its derivative products, especially chocolate, are highly appreciated by consumers for their exceptional organoleptic qualities, thus being often considered delicacies. They are also regarded as superfoods due to their nutritional and health properties. Cocoa is susceptible to adulteration to obtain illicit economic benefits, so strategies capable of authenticating its attributes are needed. Features such as cocoa variety, origin, fair trade, and organic production are increasingly important in our society, so they need to be guaranteed. Most of the methods dealing with food authentication rely on profiling and fingerprinting approaches. The compositional profiles of natural components -such as polyphenols, biogenic amines, amino acids, volatile organic compounds, and fatty acids- are the source of information to address these issues. As for fingerprinting, analytical techniques, such as chromatography, infrared, Raman, and mass spectrometry, generate rich fingerprints containing dozens of features to be used for discrimination purposes. In the two cases, the data generated are complex, so chemometric methods are usually applied to extract the underlying information. In this review, we present the state of the art of cocoa and chocolate authentication, highlighting the pros and cons of the different approaches. Besides, the relevance of the proposed methods in quality control and the novel trends for sample analysis are also discussed.

Characterization of the key odorants in floral aroma green tea based on GC-E-Nose, GC-IMS, GC-MS and aroma recombination and investigation of the dynamic changes and aroma formation during processing

To characterize the key odorants of floral aroma green tea (FAGT) and reveal its dynamic evolution during processing, the volatile metabolites in FAGT during the whole processing were analyzed by integrated volatolomics techniques, relative odor activity value (rOAV), aroma recombination, and multivariate statistical analysis. The volatile profiles undergone significant changes during processing, especially in the withering and fixation stages. A total of 184 volatile compounds were identified (∼53.26% by GC-MS). Among them, 7 volatiles with rOAV > 1 were identified as characteristic odorants of FAGT, and most of these compounds reached the highest in withering stage. According to the formation pathways, these key odorants could be divided into four categories: fatty acid-derived volatiles, glycoside-derived volatiles, amino acid-derived volatiles, and carotenoid-derived volatiles. Our study provides a comprehensive strategy to elucidate changes in volatile profiles during processing and lays a theoretical foundation for the targeted processing of high-quality green tea.

Key Aromatic Volatile Compounds from Roasted Cocoa Beans, Cocoa Liquor, and Chocolate

The characteristic aromas at each stage of chocolate processing change in quantity and quality depending on the cocoa variety, the chemical composition of the beans, the specific protein storage content, and the polysaccharides and polyphenols determining the type and quantity of the precursors formed during the fermentation and drying process, leading to the formation of specific chocolate aromas in the subsequent roasting and conching processes. Bean aroma is frequently profiled, identified, and semiquantified by headspace solid-phase microextraction combined with gas chromatography-mass spectrometry (HS-SPMEGC-MS) and by gas chromatography olfactometry (GC-O). In general, the flavors generated in chocolate processing include fruity, floral, chocolate, woody, caramel, earthy, and undesirable notes. Each processing stage contributes to or depletes the aroma compounds that may be desirable or undesirable, as discussed in this report.

Data fusion of electronic noses and electronic tongues aids in botanical origin identification on imbalanced Codonopsis Radix samples

Codonopsis Radix (CR) is an edible food and traditional Chinese herb medicine in China. Various varieties of Codonopsis Radix have different tastes. To make the flavor of processed food stable, two kinds of electronic sensory devices, electronic nose and electronic tongue, were used to establish a discrimination model to identify the botanical origin of each sample. The optimal model built on the 88 batches of samples was selected from the models trained with all combination of two pretreatment methods and three classification methods. A comparison were performed on the models trained on the data collected by electronic nose and electronic tongue. The results showed that the model trained on the fused dataset outperformed the models trained separately on the electronic nose data and electronic tongue data. The two preprocessing approaches could improve the prediction performance of all classification methods. Classification and Regression Tree approach performed better than Partial Least Square Discriminant Analysis and Linear Discriminant Analysis in terms of accuracy. But Classification and Regression Tree tends to assign the samples of minority class to the majority class. Meanwhile, Partial Least Square Discriminant Analysis keeps a good balance between the identification requirements of all the two groups of samples. Taking all the results above, the model built using the Partial Least Square Discriminant Analysis method on the fused data after z-score was used to identify the botanical origin of Codonopsis Radix.

A comprehensive insight on modern green analyses for quality control determination and processing monitoring in coffee and cocoa seeds

Green analysis is defined as the analysis of chemicals in a manner where sample extraction and analysis are performed with least amounts of steps, low hazardous materials, while maintaining efficiency in terms of analytes detection. Coffee and cocoa represent two of the most popular and valued beverages worldwide in addition to their several products i.e., cocoa butter, chocolates. This study presents a comprehensive overview of green methods used to evaluate cocoa and coffee seeds quality compared to other conventional techniques highlighting advantages and or limitations of each. Green techniques discussed in this review include solid phase microextraction, spectroscopic techniques i.e., infra-red (IR) spectroscopy and nuclear magnetic resonance (NMR) besides, e-tongue and e-nose for detection of flavor. The employment of multivariate data analysis in data interpretation is also highlighted in the context of identifying key components pertinent to specific variety, processing method, and or geographical origin.

Characterization and Discrimination of Apples by Flash GC E-Nose: Geographical Regions and Botanical Origins Studies in China

Forty-one apple samples from 7 geographical regions and 3 botanical origins in China were investigated. A total of 29 volatile compounds have been identified by flash GC E-nose. They are 17 esters, 5 alcohols, 3 aldehydes, 1 ketone, and 3 others. A principal component analysis was employed to study the relationship between varieties and volatiles. A partial least squares discriminant analysis (PLS-DA), stepwise linear discriminant analysis (SLDA), and decision tree (DT) are used to discriminate apples from 4 geographical regions (34 apple samples) and 3 botanical origins (36 apple samples). The most influential markers identified by PLS-DA are 2-hexadecanone, methyl decanoate, tetradecanal, 1,8-cineole, hexyl 2-butenoate, (Z)-2-octenal, methyl 2-methylbutanoate, ethyl butyrate, dimethyl trisulfide, methyl formate, ethanol, S(-)2-methyl-1-butanol, ethyl acetate, pentyl acetate, butyl butanoate, butyl acetate, and ethyl octanoate. From the present work, SLDA reveals the best discrimination results in geographical regions and botanical origins, which are 88.2% and 88.9%, respectively. Although machine learning DT is attempted to classify apple samples, the results are not satisfactory.

Identification of Key Aroma Compounds Responsible for the Floral Ascents of Green and Black Teas from Different Tea Cultivars

Chemicals underlying the floral aroma of dry teas needs multi-dimensional investigations. Green, black, and freeze-dried tea samples were produced from five tea cultivars, and only ‘Chunyu2’ and ‘Jinguanyin’ dry teas had floral scents. ‘Chunyu2’ green tea contained the highest content of total volatiles (134.75 μg/g) among green tea samples, while ‘Jinguanyin’ black tea contained the highest content of total volatiles (1908.05 μg/g) among black tea samples. The principal component analysis study showed that ‘Chunyu2’ and ‘Jinguanyin’ green teas and ‘Chunyu2’ black tea were characterized by the abundant presence of certain alcohols with floral aroma, while ‘Jinguanyin’ black tea was discriminated due to the high levels of certain alcohols, esters, and aldehydes. A total of 27 shared volatiles were present in different tea samples, and the contents of 7 floral odorants in dry teas had correlations with those in fresh tea leaves (p < 0.05). Thus, the tea cultivar is crucial to the floral scent of dry tea, and these seven volatiles could be promising breeding indices.

Electronic Noses and Their Applications for Sensory and Analytical Measurements in the Waste Management Plants-A Review

Waste management plants are one of the most important sources of odorants that may cause odor nuisance. The monitoring of processes involved in the waste treatment and disposal as well as the assessment of odor impact in the vicinity of this type of facilities require two different but complementary approaches: analytical and sensory. The purpose of this work is to present these two approaches. Among sensory techniques dynamic and field olfactometry are considered, whereas analytical methodologies are represented by gas chromatography–mass spectrometry (GC-MS), single gas sensors and electronic noses (EN). The latter are the core of this paper and are discussed in details. Since the design of multi-sensor arrays and the development of machine learning algorithms are the most challenging parts of the EN construction a special attention is given to the recent advancements in the sensitive layers development and current challenges in data processing. The review takes also into account relatively new EN systems based on mass spectrometry and flash gas chromatography technologies. Numerous examples of applications of the EN devices to the sensory and analytical measurements in the waste management plants are given in order to summarize efforts of scientists on development of these instruments for constant monitoring of chosen waste treatment processes (composting, anaerobic digestion, biofiltration) and assessment of odor nuisance associated with these facilities.

Influence of Freeze-Dried Phenolic-Rich Plant Powders on the Bioactive Compounds Profile, Antioxidant Activity and Aroma of Different Types of Chocolates

In this study, the blueberries (BLUB), raspberries (RASB), blackberries (BLCB), pomegranates pomace (POME) and beetroots (BEET) freeze-dried powders were used as the sources of phenolic compounds to enrich different types of chocolates, substituting a part of the sweetener. It was found that 1% addition of fruit or vegetable powders to chocolates increased the content of total phenolic compounds (flavan-3-ols, phenolic acids and anthocyanins) of enriched dark and milk chocolates compared to the control ones dependent on the powder used. Among the enriched chocolates, the chocolates with the addition of BLUB powder were characterized by the highest total polyphenol content. The highest percentage increase (approximately 80%) in the total polyphenol content was observed in MCH chocolate enriched with BLUB powder. Chocolates incorporated with BLUB, RASB, BLCB and POME powders presented a richer phenolic compound profile than control counterparts. The highest DPPH radical-scavenging capacity was exhibited by the DCH98S chocolate enriched with BEET powder. However, the DCH98ESt chocolates enriched with POME and BEET powders demonstrated the highest FRAP values. An electronic nose analysis confirmed the existence of differences between the profiles of volatile compounds of various types of chocolates enriched with fruit or vegetable powders. Thus, the enrichment of dark and milk chocolates with BLUB, RASB, BLCB, POME and BEET powders seemed to be an interesting approach to enhance bioactivity and to enrich the sensory features of various chocolate types.

Quality differentiation of cocoa beans: implications for geographical indications

Geographical indications may stimulate collective actions of governance for quality control, trade and marketing as well as innovation based on the use of local resources and regional biodiversity. Cocoa production, however, dominated by small family agriculture in tropical regions, has rarely made use of such strategies. This review is aimed at understanding major research interests and emerging technologies helpful for the origin differentiation of cocoa quality. Results from literature search and cited references of publications on cocoa research were imported into VOSviewer for data analysis, which aided in visualizing major research hotpots. Co-occurrence analysis yielded major research clusters which guided the discussion of this review. Observed was a consensus recognizing cocoa quality resulting from the interaction of genotype, fermentation variables and geographical origin. A classic view of cocoa genetics based on the dichotomy of 'fine versus bulk' has been reexamined by a broader perspective of human selection and cocoa genotype evolution. This new approach to cocoa genetic diversity, together with the understanding of complex microbiome interactions through fermentation, as well as quality reproducibility challenged by geographical conditions, have demonstrated the importance of terroir in the production of special attributes. Cocoa growing communities around the tropics have been clearly enabled by new omics and chemometrics to systematize producing conditions and practices in the designation of specifications for the differentiation of origin quality. © 2021 Society of Chemical Industry.

Application of gas chromatography-ion mobility spectrometry (GC-IMS) and ultrafast gas chromatography electronic-nose (uf-GC E-nose) to distinguish four Chinese freshwater fishes at both raw and cooked status

The volatile organic compounds (VOCs) in four Chinese freshwater fishes (i.e., Hypophthalmichthys molitrix (H), Aristichthys nobilis (A), Lateolabrax japonicus (L), Parabramis pekinensis (P)) were separated using gas chromatography-ion mobility spectrometry (GC-IMS) and ultrafast gas chromatography electronic-nose (uf-GC E-nose). Principal component analysis (PCA) was applied to distinguish the VOCs identified from the four freshwater fishes in both raw and cooked states. Twenty compounds were identified from the spectral database of GC-IMS, including five aldehydes, eight alcohols, six ketones, and three esters. In addition, using GC E-nose, 32 compounds were isolated by the first column MTX-5, and 24 compounds were isolated by the second column MXT-1701. PCA results showed that the four fishes could be well discriminated against. The odor profiles of raw and cooked fishes were clearly different. This study demonstrated that specific signals provided from GC-IMS could differentiate freshwater fishes. GC-IMS and uf-GC E-nose could be developed further to distinguish aquatic products based on VOCs. PRACTICAL APPLICATIONS: Two new methods, gas chromatography-ion mobility spectrometry (GC-IMS) and ultrafast gas chromatography electronic-nose (uf-GC E-nose), were used to analyze the volatile organic compounds (VOCs) in four Chinese freshwater fishes at raw and cooked status. GC-IMS has the characteristics of fast detection speed and high sensitivity. The accuracy of the qualitative analysis of the compounds is better with GC-IMS (larger data volume, leading to a better in-depth statistical analysis). Uf-GC E-nose could provide a nondestructive, fast, relatively low cost, and trustworthy way for flavor analysis. According to the techniques, the established fingerprints of VOCs provided an additional tool for food analysis.

Rapid characterization of the volatile profiles in Pu-erh tea by gas phase electronic nose and microchamber/thermal extractor combined with TD-GC-MS

Aroma plays an important role in the quality of Pu-erh tea. However, the quality evaluation of Pu-erh tea aroma is heavily relied on the experience of sensory evaluation, and the theoretical research is relatively scarce. In the present work, the volatile compounds in Pu-erh tea were characterized by using gas phase electronic nose (e-nose) and microchamber/thermal extractor (µ-CTE) combined with thermal desorption coupled to gas chromatography-mass spectrometry (TD-GC-MS). A satisfactory discrimination model (R² Y = 0.95, Q²  = 0.807) was obtained by using orthogonal partial least squares discriminant analysis (OPLS-DA) based on the odor fingerprint of different brands of Pu-erh tea. In addition, based on the double criterion of multivariate analysis with VIP >1.0 and univariate analysis with p ≤ 0.001, 39 volatile components were identified to contribute greatly to the discrimination of five brands of Pu-erh tea. The results suggested that gas phase e-nose and µ-CTE combined with TD-GC/MS were simple, rapid techniques to characterize the volatile compounds in Pu-erh tea and were allowed to effectively distinguish different brands of Pu-erh tea, which would provide an important reference on the quality assessment of Pu-erh tea. PRACTICAL APPLICATION: This work demonstrates that the volatile compounds in Pu-erh tea are simply and rapidly characterized by using µ-CTE/TD-GC/MS and gas phase e-nose, allowing to effectively distinguish different brands of Pu-erh tea, which can provide an important reference for the quality assessment and authentication of Pu-erh tea.

Assessing the flavor of cocoa liquor and chocolate through instrumental and sensory analysis: a critical review

The performance of appropriate instrumental and/or sensory analyses is essential to gain insights into the flavor profile of cocoa products. This three-part review is compiled of an overview of the most commonly used instrumental techniques to study cocoa liquor and chocolate flavor, their perception by a trained panel and the potential relationship between them. Each part is the result of a thorough literature study, principally focusing on the assumptions, features and limitations of these techniques. Reviewing of the literature revealed that cocoa matrix effects and methodology restraints were not always considered when instrumentally analyzing cocoa flavor. With respect to sensory analyses, various studies lacked reporting of accomplished trainings and performance of panelists. Moreover, a discrepancy was noticed in the descriptive flavor lexicon employed. Finally, when linking instrumental and sensory data, linear modeling is regularly applied, which might not always be appropriate. This review paper addresses the challenges associated with flavor assessment, intending to incite researchers to critically study cocoa flavor and apply standardized protocols and procedures.

The type of microorganism and substrate determines the odor fingerprint of dried bacteria targeting microbial protein production

The rapidly increasing demand for protein has led to the pursuit of new protein sources, among which microbial protein (MP) is one of the most promising. Although the nutritional properties of MP are important and often well-studied, the sensory properties of the microbial cells will in part determine the commercial success of the product and are much less investigated. Here we assessed the odor fingerprint of dried bacteria originating from pure cultures and enriched mixed microbial communities using an electronic nose (e-nose). The e-nose discriminated between the different MP sources, while the choice of culture and substrate substantially affected their volatile organic compound (VOC) profile. The most dominant odor descriptors (>20% of VOC peak area) were sweet, fruity and fishy, while the mixed cultures presented higher peak areas indicating potentially more intense aromas than the pure cultures. The e-nose can detect the suitability of new MP sources and determine their best end-use.

Multi-block classification of chocolate and cocoa samples into sensory poles

The present study aims at developing an analytical methodology which allows correlating sensory poles of chocolate to their chemical characteristics and, eventually, to those of the cocoa beans used for its preparation. Trained panelists investigated several samples of chocolate, and they divided them into four sensorial poles (characterized by 36 different descriptors) attributable to chocolate flavor. The same samples were analyzed by six different techniques: Proton Transfer Reaction-Time of Flight-Mass Spectrometry (PTR-ToF-MS), Solid Phase Micro Extraction-Gas Chromatography-Mass Spectroscopy (SPME-GC-MS), High-Performance Liquid Chromatography (HPLC) (for the quantification of eight organic acids), Ultra High Performance Liquid Chromatography coupled to triple-quadrupole Mass Spectrometry (UHPLC-QqQ-MS) for polyphenol quantification, 3D front face fluorescence Spectroscopy and Near Infrared Spectroscopy (NIRS). A multi-block classification approach (Sequential and Orthogonalized-Partial Least Squares - SO-PLS) has been used, in order to exploit the chemical information to predict the sensorial poles of samples. Among thirty-one test samples, only two were misclassified.

Roasting-induced changes in cocoa beans with respect to the mood pyramid

The mood pyramid of cocoa, which was previously proposed as a new concept, consists of four levels (flavan-3-ols, methylxanthines, minor compounds and orosensory properties). Roasting is a crucial process for flavor development in cocoa but is likely to have a negative impact on the phytochemicals. We investigated the effect of roasting time (10-50 min) and temperature (110-160 °C) on the potential mood-enhancing compounds corresponding to the distinct mood pyramid levels. Phytochemicals were analyzed using UPLC-HRMS, while the flavor was mapped via aroma (HS-SPME-GC-MS) and generic descriptive analysis (trained panel). Results revealed that roasting at 130 °C for 30 min did not significantly affect the levels of epicatechin, procyanidin B2 and theobromine, while salsolinol significantly increased. Moreover, bitterness and astringency were reduced and the desired cocoa flavor was developed. Thus, through selection of appropriate roasting time and temperature conditions phytochemicals of interest could be retained without comprising the flavor.

Characterization of the flavor compounds in wheat bran and biochemical conversion for application in food

Wheat bran, an abundant and low-cost by-product from agricultural processing, can be used as an alternative food resource. Biochemical conversion of wheat bran to food ingredient involves pretreatments of bran to enhance its acceptability. In this work, the effects of the Maillard reaction and enzymolysis on flavor properties of wheat bran and sensory evaluation of steamed buns fortified with wheat bran were analyzed using GC-MS combined with sensory evaluation. The results showed that the Maillard reaction and enzymatic hydrolysis, as well as flavoring process, could effectively improve the flavor profiles of wheat bran. The flavor compounds in modified wheat bran products as well as its fuzzy sensory score increased significantly (P < 0.05) compared with those in commercially available dry malt extract. Additionally, steamed buns fortified with wheat bran had enhanced flavor and overall acceptability. The study can be useful in valorization a plethora of grain bran (waste) into valuable resources.

Non-volatile and volatile composition of West African bulk and Ecuadorian fine-flavor cocoa liquor and chocolate

Cocoa products are obtained from the seeds of Theobroma cacao L. In this research, cocoa liquor and chocolate produced from cocoa beans from West Africa (Forastero, "bulk" cacao) and Ecuador (Nacional variety, "fine-flavor" cacao), were investigated, using a novel approach in which various analytical techniques are combined in order to obtain in-depth knowledge of the studied cocoa samples. The levels of various classes of primary metabolites were determined and a wide range of secondary metabolites, including volatile organic acids, aldehydes, esters, pyrazines, polyphenols, methylxanthines and biogenic amines, were identified and/or quantified by HS-SPME GC-MS (headspace-solid phase microextraction gas chromatography - mass spectrometry). and UPLC-HRMS (ultra-performance liquid chromatography - high resolution mass spectrometry). Odor Activity Values (OAV) were calculated to assess the contribution of individual volatiles on the final aroma. Various volatile aroma compounds were more abundant in the West African cocoa liquor and chocolate, while the Ecuadorian samples were richer in most quantified non-volatile metabolites. Principal component analysis (PCA) confirmed that the four samples can be clearly distinguished. Alcohols, pyrazines, amino acids and biogenic amines were found to be highly influential in causing this differentiation. The proposed approach can be useful in future studies on more extensive cocoa sample collections, in order to highlight similarities and pinpoint typical differences in chemical composition among these samples.

Ion Mobility Spectrometry as a Potential Tool for Flavor Control in Chocolate Manufacture

Chocolate has a complex flavor profile composed of more than 600 volatile compounds that mainly arise from the thermo-mechanical treatment during roasting and conching. The aim of this study was to evaluate the applicability of ion mobility spectrometry (IMS), as a real-time method for process monitoring in chocolate manufacture. It is evident from the ion mobility (IM) fingerprint spectra that individual processing steps affect the signal intensities at particular drift time regions. The analysis of individual IM spectra by principal component analysis (PCA) revealed that it is possible to distinguish with respect to conching temperature and time. PCA also allowed identifying those parts of the IM spectra that were predominantly affected by the respective treatment. It was, on the basis of the IM flavor fingerprints and subsequent PCA, possible to distinguish between the different states of processing of bulk cocoa. The results of the study imply that, using appropriate post-data treatment, IMS could be used for process control in cocoa processing.

Identification of Dialkylpyrazines Off-Flavors in Oak Wood

Volatile extractive compounds from high-quality oak wood (Quercus sp.) are responsible for important pleasant olfactory notes, such as coconut, wood, vanilla, caramel, and spice. Recently, a new off-flavor reminiscent of rancid butter has been detected in oak wood. Using gas chromatography-olfactometry (GC-O) coupled to several detection modes, such as nitrogen-phosphorus detection (GC-O-NPD) or mass spectrometry (GC-O-MS) and multidimensional GC-O coupled to time-of-flight mass spectrometry, six compounds containing nitrogen atoms were identified. The volatiles were suggested to belong to 2,5-disubstituted pyrazines family, which was confirmed by comparison with synthetic reference compounds. For this purpose, symmetric and dissymmetric 2,5-dialkylpyrazines were prepared from methyl esters of corresponding aliphatic amino acids (Val, Leu, and Ile) by a three-step, one-pot reaction under mild reducing conditions. Organoleptic descriptors and odor detection thresholds were also determined, whereas a bacterial origin explaining these off-flavors was hypothesized.