Unique metabolite profiles of Indonesian cocoa beans from different origins and their correlation with temperature

Revealing metabolite profiles in soy sauce and exploring their correlation with umami taste using UPLC-Orbitrap-MS/MS and GC-Tof-MS derivatization

Soy sauce has a rich base of non-volatile substances, but existing studies are insufficient. This study analyzed the metabolites of 19 Chinese commercial soy sauces by UPLC-Orbitrap-MS/MS and GC-Tof-MS derivatization, and detected 674 and 230 kinds of substances, respectively, that could be grouped into 12 different classes of compounds, such as peptides, amino acid derivatives, organic acids, sugars, sugar alcohols, amino acids and so on. For the first time, 215 dipeptides and 91 amino acid derivatives in soy sauce were analyzed in detail and systematically from the perspective of composition and amino acid structure. The flavor profile of soy sauce was obtained by electronic tongue analysis, and orthogonal projections to latent structures (OPLS), random forest (RF), correlation were used to screen potential compounds associated with umami. The intersection of the three methods yielded 9 substances, including 4 reported umami-taste compounds, i.e., Glu, Fru-Glu, Inosine 5'prime-monophosphate (IMP) and Arg-Ser, as well as 5 others that may potentially contribute to umami or be associated with umami-taste producing microorganisms, including His-Asn and Homoserine lactone. This study will advance the understanding of soy sauce metabolites, and provide an in-depth reference for dipeptides and amino acid derivatives in soy sauce.

Characterization of fine-flavor cocoa in parent-hybrid combinations using metabolomics approach

Fine-flavored cocoa is generally characterized by fresh bean color and sensory characteristics. However, these methods cannot be applied to progenies/hybrids because their colors may vary depending on their parents. Additionally, sensory evaluation lacks universal quality standards, necessitating robust complementary characterization methods. This study aimed to characterize the fine-flavor cacao in parent-hybrid combinations using widely targeted Gas Chromatography-Mass Spectrometry (GC-MS) and bean phenotype analysis. Fine-flavored cacao exhibits white-bean characteristics and a lighter color than forastero. Conversely, the hybrids displayed varying percentages of fresh bean color. Caffeine and organic acids (malic acid, fumaric acid, citric acid, lactic acid, and tartaric acid) were found to correspond to the characteristics of fine-flavored cacao. Each parent-hybrid combination demonstrated distinct flavor characteristics, with the ICCRI03-hybrid emerging as a promising clone, exhibiting flavor characteristics similar to those of its female parent (fine-flavor cacao). This information on flavor characteristics will be beneficial for further fine-flavored cacao selection.

Exploring volatile compounds and microbial dynamics: Kluyveromyces marxianus and Hanseniaspora opuntiae reduce Forastero cocoa fermentation time

Traditional cocoa bean fermentation is a spontaneous process and can result in heterogeneous sensory quality. For this reason, yeast-integrated starter cultures may be an option for creating consistent organoleptic profiles. This study proposes the mixture of Hanseniaspora opuntiae and Kluyveromyces marxianus (from non-cocoa fermentation) as starter culture candidates. The microorganisms and volatile compounds were analyzed during the cocoa fermentation process, and the most abundant were correlated with predominant microorganisms. Results showed that Kluyveromyces marxianus, isolated from mezcal fermentation, was identified as the dominant yeast by high-throughput DNA sequencing. A total of 63 volatile compounds identified by HS-SPME-GC-MS were correlated with the more abundant bacteria and yeast using Principal Component Analysis and Agglomerative Hierarchical Clustering. This study demonstrates that yeasts from other fermentative processes can be used as starter cultures in cocoa fermentation and lead to the formation of more aromatic esters, decrease the acetic acid content.

Simultaneous discovery of compounds dominated by either molding kinetics or geographical region of origin for moisture damaged cacao beans using orthogonally applied tile-based fisher ratio analysis of GC×GC-TOFMS data

Herein, two "orthogonal" characteristics of moisture damaged cacao beans (temporally dependent molding kinetics versus the time-independent geographical region of origin) are simultaneously analyzed in a comprehensive two-dimensional (2D) gas chromatography time-of-flight mass spectrometry (GC×GC-TOFMS) dataset using tile-based Fisher ratio (F-ratio) analysis. Cacao beans from six geographical regions were analyzed once a day for six days following the initiation of moisture damage to trigger the molding process. Thus, there are two "extremes" to the experimental sample class design: six time points for the molding kinetics versus the six geographical regions of origin, resulting in a 6 × 6 element signal array referred to as a composite chemical fingerprint (CCF) for each analyte. Usually, this study would involve initial generation of two separate hit lists using F-ratio analysis, one hit list from inputting the data with the six time point classes, then another hit list from inputting the dataset from the perspective of geographic region of origin. However, analysis of two separate hit lists with the intent to distill them down to one hit list is extremely time-consuming and fraught with shortcomings due to the challenges associated with attempting to match analytes across two hit lists. To address this challenge, tile-based F-ratio analysis is "orthogonally applied" to each analyte CCF to simultaneously determine two F-ratios at the chromatographic 2D location (F-ratiokinetic and F-ratioregion) for each hit, by ranking a single hit list using the higher of the two F-ratios resulting in the discovery of 591 analytes. Further, using a pseudo-null distribution approach, at the 99.9% threshold over 400 analytes were deemed suitable for PCA classification. Using a more stringent 99.999% threshold, over 100 analytes were explored more deeply using PARAFAC to provide a purified mass spectrum.

Multidisciplinary approach combining food metabolomics and epidemiology identifies meglutol as an important bioactive metabolite in tempe, an Indonesian fermented food

This study introduces a multidisciplinary approach to investigate bioactive food metabolites often overlooked due to their low concentrations. We integrated an in-house food metabolite library (n = 494), a human metabolite library (n = 891) from epidemiological studies, and metabolite pharmacological databases to screen for food metabolites with potential bioactivity. We identified six potential metabolites, including meglutol (3-hydroxy-3-methylglutarate), an understudied low-density lipoprotein (LDL)-lowering compound. We further focused on meglutol as a case study to showcase the range of characterizations achievable with this approach. Green pea tempe was identified to contain the highest meglutol concentration (21.8 ± 4.6 mg/100 g). Furthermore, we identified a significant cross-sectional association between plasma meglutol (per 1-standard deviation) and lower LDL cholesterol in two Hispanic adult cohorts (n = 1,628) (β [standard error]: -5.5 (1.6) mg/dl, P = 0.0005). These findings highlight how multidisciplinary metabolomics can serve as a systematic tool for discovering and enhancing bioactive metabolites in food, such as meglutol, with potential applications in personalized dietary approaches for disease prevention.

Integrating shotgun metagenomics and metabolomics to elucidate the dynamics of microbial communities and metabolites in fine flavor cocoa fermentation in Hainan

The aim of this study was to investigate the dynamic profile of microorganisms and metabolites in Hainan Trinitario cocoa during a six-day spontaneous box fermentation process. Shotgun metagenomic and metabolomic approaches were employed for this investigation. The potential metabolic functions of microorganisms in cocoa fermentation were revealed through a joint analysis of microbes, functional genes, and metabolites. During the anaerobic fermentation phase, Hanseniaspora emerged as the most prevalent yeast genus, implicated in pectin decomposition and potentially involved in glycolysis and starch and sucrose metabolism. Tatumella, possessing potential for pyruvate kinase, and Fructobacillus with a preference for fructose, constituted the primary bacteria during the pre-turning fermentation stage. Upon the introduction of oxygen into the fermentation mass, acetic acid bacteria ascended to dominant within the microflora. The exponential proliferation of Acetobacter resulted in a decline in taxonomic richness and abundance. Moreover, the identification of novel species within the Komagataeibacter genus suggests that Hainan cocoa may serve as a valuable reservoir for the discovery of unique cocoa fermentation bacteria. The KEGG annotation of metabolites and enzymes also highlighted the significant involvement of phenylalanine metabolism in cocoa fermentation. This research will offer a new perspective for the selection of starter strains and the formulation of mixed starter cultures.

Cocoa polyphenols and milk proteins: covalent and non-covalent interactions, chocolate process and effects on potential polyphenol bioaccesibility

In this study, we discussed covalent and non-covalent reactions between cocoa polyphenols and proteins (milk and cocoa) and the possible effects of these reactions on their bioaccessibility, considering environmental and processing conditions. Better insight into these interactions is crucial for understanding the biological effects of polyphenols, developing nutritional strategies, and improving food processing and storage. Protein-polyphenol reactions affect the properties of the final product and can lead to the formation of various precursors at various stages in the manufacturing process, such as fermentation, roasting, alkalization, and conching. Due to the complex composition of the chocolate and the various technological processes, comprehensive food profiling strategies should be applied to analyze protein-polyphenol covalent reactions covering a wide range of potential reaction products. This will help to identify potential effects on the bioaccessibility of bioactive compounds such as low-molecular-weight peptides and polyphenols. To achieve this, databases of potential reaction products and their binding sites can be generated, and the effects of various process conditions on related parameters can be investigated. This would then allow to a deeper insight into mechanisms behind protein-polyphenol interactions in chocolate, and develop strategies to optimize chocolate production for improved nutritional and sensory properties.

Omics approaches to understand cocoa processing and chocolate flavor development: A review

The global market of chocolate has increased worldwide during the last decade and is expected to reach a value of USD 200 billion by 2028. Chocolate is obtained from different varieties of Theobroma cacao L, a plant domesticated more than 4000 years ago in the Amazon rainforest. However, chocolate production is a complex process requiring extensive post-harvesting, mainly involving cocoa bean fermentation, drying, and roasting. These steps have a critical impact on chocolate quality. Standardizing and better understanding cocoa processing is, therefore, a current challenge to boost the global production of high-quality cocoa worldwide. This knowledge can also help cocoa producers improve cocoa processing management and obtain a better chocolate. Several recent studies have been conducted to dissect cocoa processing via omics analysis. A vast amount of data has been produced regarding omics studies of cocoa processing performed worldwide. This review systematically analyzes the current data on cocoa omics using data mining techniques and discusses opportunities and gaps for cocoa processing standardization from this data. First, we observed a recurrent report in metagenomics studies of species of the fungi genus Candida and Pichia as well as bacteria from the genus Lactobacillus, Acetobacter, and Bacillus. Second, our analyzes of the available metabolomics data showed clear differences in the identified metabolites in cocoa and chocolate from different geographical origin, cocoa type, and processing stage. Finally, our analysis of peptidomics data revealed characteristic patterns in the gathered data including higher diversity and lower size distribution of peptides in fine-flavor cocoa. In addition, we discuss the current challenges in cocoa omics research. More research is still required to fill gaps in central matter in chocolate production as starter cultures for cocoa fermentation, flavor evolution of cocoa, and the role of peptides in the development of specific flavor notes. We also offer the most comprehensive collection of multi-omics data in cocoa processing gathered from different research articles.

Investigation of the effect of processing on the component changes of single-origin chocolate during the bean-to-bar process

Chocolate is one of the most popular sweets in the world. In recent years, the bean-to-bar process for chocolate production has attracted global attention. Bean-to-bar is a method of managing the whole production process from cocoa beans to chocolate bars, including single-origin chocolate (SOC). Many manufacturers aim to produce high-quality chocolate to maximize the flavor of cocoa beans. However, chocolate compounds are very complex due to many processes, and there are a limited number of studies on the SOC produced from the bean-to-bar process. Therefore, understanding the effects of processing is important for the growth of the chocolate industry. The objective of this study was to investigate the processing effect on the component changes of SOC during the bean-to-bar process. In this study, the component changes during the bean-to-bar process were monitored using gas chromatography/mass spectrometry (GC/MS). Then, the characteristics of SOC from five regions in Indonesia were further investigated. Lastly, the component profiles were combined with the data obtained from sensory evaluation. Our results showed that the influence of the manufacturing process was greater than that of the difference in the cocoa production area. Moreover, 1-pentanol, raffinose, and heptanoic acid were correlated with sweetness and dairy flavor, whereas glutamic acid, tartaric acid, 3-methyl-2-butanone, mannitol, and ethyl cinnamate were correlated with bitterness, astringency, and cocoa flavor, which were shown to be affected by fermentation, roasting, and sugar addition. This information might provide a basis for improving the chocolate production process and its quality related to the component profiles.