Link between Flavor Perception and Volatile Compound Composition of Dark Chocolates Derived from Trinitario Cocoa Beans from Dominican Republic.

The chemical composition of dark chocolate has a significant impact on its complex flavor profile. This study aims to investigate the relationship between the volatile chemical composition and perceived flavor of 54 dark chocolate samples made from Trinitario cocoa beans from the Dominican Republic. The samples were evaluated by a trained panel and analyzed using gas chromatography-mass spectrometry (GC-MS) to identify and quantify the volatile compounds. Predictive models based on a partial least squares regression (PLS) allowed the identification of key compounds for predicting individual sensory attributes. The models were most successful in classifying samples based on the intensity of bitterness and astringency, even though these attributes are mostly linked to non-volatile compounds. Acetaldehyde, dimethyl sulfide, and 2,3-butanediol were found to be key predictors for various sensory attributes, while propylene glycol diacetate was identified as a possible marker for red fruit aroma. The study highlights the potential of using volatile compounds to accurately predict chocolate flavor potential.

Cocoa bean fingerprinting via correlation networks.

Cocoa products have a remarkable chemical and sensory complexity. However, in contrast to other fermentation processes in the food industry, cocoa bean fermentation is left essentially uncontrolled and is devoid of standardization. Questions of food authenticity and food quality are hence particularly challenging for cocoa. Here we provide an illustration how network science can support food fingerprinting and food authenticity research. Using a large dataset of 140 cocoa samples comprising three cocoa fermentation/processing stages and eight countries, we obtain correlation networks between the cocoa samples by computing measures of pairwise correlation from their liquid chromatography-mass spectrometry (LC-MS) profiles. We find that the topology of correlation networks derived from untargeted LC-MS profiles is indicative of the fermentation and processing stage as well as the origin country of cocoa samples. Progressively increasing the correlation threshold firstly reveals network clusters based on processing stage and later country-based clusters. We present both, qualitative and quantitative evidence through network visualization, network statistics and concepts from machine learning. In our view, this network-based approach for classifying mass spectrometry data has broad applicability beyond cocoa.

HPLC-MS-based design of experiments approach on cocoa roasting.

Modern statistical methods, such as the design of experiments and response surface methodology, are widely used to describe changes in multiparameter processes during the processing of food in both science and technology contexts. However, these approaches are described to a lesser degree in the case of cocoa roasting than other foods and processes. Our study aimed to use the design of experiments to establish a model of cocoa roasting for relevant flavor-related constituents. We have used HPLC-MS techniques to link standard process parameters with chemical compounds changing in concentration during cocoa roasting. Influence of time, temperature, the addition of water, acid, and base, on relative concentrations of procyanidin monomers, dimers, and trimers, an Amadori compound, and a peptide, was shown. High-quality models for each compound were established and validated, displaying good prediction accuracy. Such an approach could be used to optimize processing conditions for cocoa roasting in order to influence the concentration of certain chemical compounds, and in turn, improving the flavor of chocolate products.

Cocoa origin classifiability through LC-MS data: A statistical approach for large and long-term datasets.

Classification of food samples based upon their countries of origin is an important task in food industry for quality assurance and development of fine flavor products. Liquid chromatography -mass spectrometry (LC-MS) provides a fast technique for obtaining in-depth information about chemical composition of foods. However, in a large dataset that is gathered over a period of few years, multiple, incoherent and hard to avoid sources of variations e.g., experimental conditions, transportation, batch and instrumental effects, etc. pose technical challenges that make the study of origin classification a difficult problem. Here, we use a large dataset gathered over a period of four years containing 297 LC-MS profiles of cocoa sourced from 10 countries to demonstrate these challenges by using two popular multivariate analysis methods: principal component analysis (PCA) and linear discriminant analysis (LDA). We show that PCA provides a limited separation in bean origin, while LDA suffers from a strong non-linear dependence on the set of compounds. Further, we show for LDA that a compound selection criterion based on Gaussian distribution of intensities across samples dramatically enhances origin clustering of samples thereby suggesting possibilities for studying marker compounds in such a disparate dataset through this approach. In essence, we show and develop a new approach that maximizes, avoiding overfitting, the utility of multivariate analysis in a highly complex dataset.

Novel Amadori and Heyns compounds derived from short peptides found in dried cocoa beans.

Chemical transformations of Amadori compounds are responsible for the formation of aroma volatiles at the end of the Maillard reaction cascade, which in turn contributes to unique organoleptic characteristics of chocolate. A large amount of short peptides reported in fermented cocoa suggests the existence of a much larger variety of these flavor precursors than previously suspected. An HPLC-MS-MS study was performed on dried Malaysian cocoa beans to identify novel Amadori and Heyns compounds. In total, 34 species were found, including 26 previously unknown derived from di- and tripeptides. We illustrate how the structures were elucidated via tandem MS experiments, as well as present a comparative study on their relative quantities in samples coming from 11 countries of origin. There were significant differences between them, and discrimination was possible by principal component analysis based on Amadori content alone. However, the PCA separation could be a result of various post-harvest practices exerted among said countries.

Monitoring the changes in low molecular weight carbohydrates in cocoa beans during spontaneous fermentation: A chemometric and kinetic approach.

The low molecular weight carbohydrate (LMWC) profile has recently been investigated, showing considerable changes between fermented and unfermented cocoa beans. These differences are a consequence of the fermentation process, which is considered a crucial step in chocolate production. During fermentation, LMWC are involved in Maillard reaction, a crucial reaction for the development of aroma and taste precursors. However, there is a lack of information related to LMWC changes and of contextualization with changes in other physicochemical parameters (pH and dry matter) during spontaneous fermentation. The different approaches employed in this manuscript have allowed the identification of a sequential degradation of tetra-, tri- and disaccharides, as well as an increase in the monosaccharide content during fermentation. Moreover, a correlation was determined between some LMWC and physicochemical parameters. Besides that, the chemometric approach identified the fermentation period ranging between 48 and 96 h as determinant to produce noticeable changes in unfermented beans based on the indicators evaluated. Furthermore, different kinetic parameteres (reaction order, observed reaction rates (kobs) and half-life values (t1/2)) of different LMWC were determined, showing differences between them. The results showed in this manuscript provide unprecedented mechanistic details of spontaneous cocoa fermentation.

Experimentally modelling cocoa bean fermentation reveals key factors and their influences.

Cocoa bean fermentation still remains a rather empirical process. The research presented here employed an artificial system of fermentation, using controlled incubations, in order to achieve greater control over the external influences that cocoa beans are exposed to, with the aim of experimentally modelling changes to bean components (responses). Experimental design was used, in a first-ever attempt, to study the effects of five factors and their interactions on the profiles of pH, peptides, and flavanols in the bean during the incubations. Temperature, incubation time and the concentration of acetic acid were the main factors influencing the three responses. Moreover, there was a significant amount of factor interaction, revealing the process to be more complex than initially thought, especially with respect to the role of ethanol. Using the model, one was also able to accurately predict the response of the bean to the exposure to specific factors.

Thermally-induced formation of taste-active 2,5-diketopiperazines from short-chain peptide precursors in cocoa.

2,5-diketopiperazines (DKPs) are cyclic dipeptides responsible for the specific bitter taste of cocoa formed during roasting. The 2,5-diketopiperazine and peptide composition of four different cocoa bean samples from different origins were studied using LC-MS techniques. 34 diketopiperazines were identified, of which 10 are newly reported in cocoa. Their formation was followed during two different roasting time-series using a zero-order and an alternative Prout-Tompkins solid-state kinetic models. The activation energies of diketopiperazine formation showed a distribution close to normal with individual values depending on the nature of the substituents. The relative concentrations of the DKPs were correlated with their putative peptide precursors in unroasted cocoa bean samples. The results showed a significant positive correlation, indicating that oligopeptides formed in cocoa bean fermentation are taste-precursors for bitter tasting diketopiperazines. Unexpectedly, for most diketopiperazines, a single major peptide precursor could be suggested.

Analysis of minor low molecular weight carbohydrates in cocoa beans by chromatographic techniques coupled to mass spectrometry.

The low molecular weight carbohydrate (LMWC) profile of cocoa beans has recently been studied using hydrophilic interaction liquid chromatography coupled to electrospray ionization-time of flight mass spectrometry (HILIC-ESI-TOF MS) and HILIC-ESI-tandem mass spectrometry (HILIC-ESI-MSn). However, different LMWC could not be unambiguously identified. Thus, as a first approach in this paper, gas chromatography coupled to mass spectrometry (GC-MS) was used as a complementary analytical technique to characterize LMWC of cocoa beans. Different mono-, di-, tri- and tetrasaccharides, as well as myo-inositol, galactinol and a diglycosil glycerol were detected. scyllo-Inositol, 1-kestose and 6-kestose were identified in unfermented cocoa beans for the first time. Moreover, other minor LMWC were tentatively assigned as fructosyl-fructose, fructosyl-glucose and glucosyl-sucrose. As a second step, in order to evaluate new possible indicators of cocoa bean origin or fermentation status, scyllo-inositol, 1-kestose and galactinol were selected as target compounds and a HILIC-ESI-TOF MS method was optimized for their analysis. The optimized conditions, using an acetonitrile:water gradient with 0.05% ammonium hydroxide at 40 °C showed narrow peaks (wh: 0.3-0.5 min) with good resolution values (Rs: 0.83-2.83). The validated HILIC-ESI-TOF MS method was applied to the analysis of 35 cocoa bean samples from different origins and fermentation status. The content of scyllo-inositol, 1-kestose and galactinol in unfermented beans (n = 21) was in the range of traces-504.9, 36.1-133.5 and traces-1970.4 µg g-1 cocoa DM respectively. In fermented beans (n = 14), the content of scyllo-inositol and 1-kestose was in the range of 15.5-491.9 and traces-115.5 µg g-1 cocoa DM respectively. Galactinol was absent in fermented beans, indicating that it could be a potential indicator of fermentation status. The methodology proposed could be used for quality control of natural products and other food ingredients containing inositols and oligosaccharides.

Origin and varietal based proteomic and peptidomic fingerprinting of Theobroma cacao in non-fermented and fermented cocoa beans.

It is well known that the development of chocolate flavor is initiated during cocoa bean fermentation. Storage proteins undergo the most intensive breakdown yielding peptides and free amino acids, which both serve as flavor precursors. A comprehensive analysis of cocoa proteins and oligopeptides of non-fermented and fermented beans from various geographic origins allows the assessment of systematic differences with respect to their origin as well as fermentation status. Protein quantities as well as their profiles derived from two-dimensional gel electrophoresis, showed striking differences for non-fermented beans depending on their geographical origin. From fermented beans, oligopeptides were relatively quantified by utilizing UHPLC-ESI-Q-q-TOF and annotated based on their characteristic fragmentation pattern in the positive-ion mode. With >800 unique oligopeptides, excluding di- and tri-peptides, across 25 different samples, we are herein reporting on the largest collection of cocoa oligopeptides ever observed and identified. The detected diversity of peptides could not be correlated to the geographical origin but rather to the degree of fermentation. Our findings suggest that the variability in peptide patterns depends on the fermentation method applied in the country of origin ultimately indicating diversified proteolytic activities. Furthermore, our results showed that well-fermented and fair-fermented beans can be differentiated from partially fermented and under-fermented ones by higher numbers and total amounts of oligopeptides.

Variation of triacylglycerol profiles in unfermented and dried fermented cocoa beans of different origins.

Fermentation and drying are the two crucial processing steps required to produce cocoa beans with desired properties, especially taste and flavor. To understand their impact on the lipid profile of cocoa, the lipid composition of unfermented raw and fermented dried beans from six different origins was investigated using high-performance liquid chromatography-mass spectrometry methods. While the comparison of triacylglycerol profiles across the different origins showed only small variations in individual compound concentrations, the comparison along the fermentation status showed major differences regarding the occurrence of polar lipids. These compounds may serve as biomarkers for the fermentation status of the beans and a simple analytical method suitable for field trials is proposed. Finally, a hypothesis identifying key unsaturated triacylglycerols contributing to the hardness and softness of cocoa butter is presented.

Degradation of cocoa proteins into oligopeptides during spontaneous fermentation of cocoa beans.

Degradation products of proteins produced during fermentation are believed to be the key precursors of a range of Maillard reactions that deliver the characteristic flavor and aroma of cocoa and chocolate. We have utilized UPLC-ESI-Q-q-TOF to identify and relatively quantify the largest collection of cocoa oligopeptides during a spontaneous fermentation time series using Ivory Coast cocoa beans. Peptides were identified, sequenced by tandem mass spectrometry and annotated based on their characteristic fragmentation pattern in the positive-ion mode. This enabled us to quantitatively trace the sequential degradation of the two main cocoa storage proteins, namely, albumin and vicilin. We observed sequential proteolytic degradation forming longer peptides in the early stages of fermentation and an increasing number of shorter peptides at the latter stages of fermentation. Protein degradation is mediated by both endo- and exopeptidases degrading at either peptide termini. In excess of 800 fermentation peptides could be unambiguously identified, providing unprecedented mechanistic details of cocoa fermentation.

Characterization of triacylglycerols in unfermented cocoa beans by HPLC-ESI mass spectrometry.

The nutritional value of cocoa butter is mainly determined by the composition of triacylglycerols (TAGs). In this paper we have developed a non-aqueous reversed-phase liquid chromatographic method, using ethanol as the mobile phase, coupled to electrospray ionization (ESI) tandem mass spectrometry to identify TAGs in raw cocoa beans from six different origins. Tandem mass spectrometry was adopted to facilitate the identification of TAGs using unique diacylglycerol product ions and neutral losses. Additionally, two-dimensional m/z retention time maps aided the identification of entire homologous series of TAGs. A total of 83 different TAGs were identified in unfermented cocoa beans, 58 of which were not previously reported in cocoa. Thirty-one of these compounds represent a new class of TAGs characterized by the presence of one to three hydroxyl groups on the unsaturated fatty acid chain. To date, this represents the largest number of TAGs identified in cocoa.