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Liquid Chromatography-Mass Spectrometry (LC-MS) provides an unprecedented wealth of metabolomics information for food products, including insights into compositional changes during food processing. Here, we employed the largest available LC-MS dataset of around 300 cocoa bean samples to assess the capability of two popular multivariate classification methods, principal component analysis (PCA) and linear decomposition analysis (LDA), for studying bean geographic origin and responsible characteristic compounds.The unsupervised method, PCA, only provides a limited separation in bean origin. Expectedly, the supervised method, LDA, provides a better origin clustering. However, it suffers from a strong, nonlinear dependence on the set of compounds used in the analysis. We show that for LDA a compound filtering criterion based on Gaussian intensity distributions dramatically enhances origin clustering of samples, thus increasing its predictive efficiency. In this form, the supervised method of LDA holds the possibility to identify potential markers of a specific origin.

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.

Polyphenols, a group of secondary metabolites, have well-known relevant effects on human health. During traditional alkalization, this content dramatically lowers. We aimed to evaluate an alternative alkalization method based on extrusion on cocoa functional characteristics. The results showed that the antioxidant capacity and total phenolic values increased as alkali concentration and temperature did, and these values doubled under less extreme conditions. Comparing the functional properties between extruded and traditionally produced powders revealed that catechin, epicatechin and dimers B1 and B2 contents were 43%, 33%, 54% and 34% lower in the extruded samples, respectively. However, this reduction was partially balanced by increased clovamide content up to 50%. Thus the total phenol content and antioxidant capacity of the extruded samples were statistically above those of the commercial one. Hence extrusion alkalization should be considered a new processing alternative to avoid markedly reducing functional properties.

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.

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.

A cocoa bean fermentation series, comprising bean samples taken every 24 h of a seven-day cocoa fermentation was analyzed by ultra-high-resolution mass spectrometry using the ESI-FT-ICR technique. Data were acquired in both positive and negative ion mode. At early fermentation times around 2000 signals could be resolved raising to a maximum of 8000 signals in each ion mode towards the end of the fermentation. Molecular formulae were assigned to a large number of observed peaks leading to ion statistics classifying cocoa constituents according elemental composition. Time dependent van Krevelen diagrams were constructed allowing the tracking of chemical changes in bean composition. In particular, the number of CHON compounds assigned to short peptides and their derivatives were shown to undergo significant chemical transformations. Theoretical MS data bases were constructed containing all possible peptides up to a length of ten amino acids and putative derivatives expected to be formed during microbial fermentation. Experimental m/z values were compared to these databases and conclusions drawn with respect to the composition of fermenting beans with tentative fermentation products suggested.

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.

Kale (Brassica oleracea) is a cool-season vegetable widely employed in the elaboration of diverse products such as tea and smoothies in USA or in the Northern German cuisine in wintertime. Besides, kale is gaining attention due to the diverse health benefits reported in the literature for its consumption, e.g. antigenotoxic and anticarcinogenic effect, protection of cardiovascular system and gastrointestinal tract. Low molecular weight carbohydrates (LMWC) are compounds directly related with kale flavour and nutritional quality. Despite different studies focusing on the chemical composition of kale, few information on LMWC is available. Thus, in this work a multianalytical approach was conducted in order to perform a comprehensive study of kale LMWC; their evolution during plant development and acclimation to cool temperatures was also evaluated. Gas chromatography coupled to mass spectrometry allowed the identification of 13 LMWC, being myo-inositol, galactinol, maltose and melibiose described for the first time in kale. Eight major LMWC were quantified in three different commercial kale cultivars using hydrophilic interaction liquid chromatography coupled to mass spectrometry to monitor possible differences in their content during plant development and as consequence of plant acclimation to cold temperatures. Overall, for all types of kales under study, the content of maltose and sucrose decreased during the plant development while the concentration of fructose, melibiose, maltose, raffinose and galactinol was increased in all kale types exposed to low temperatures. These results underline the importance of controlling the temperature during kale cultivation in order to obtain products with a high nutritional value., Authors would like to mention their gratitude to Dr Gorka Ruiz de Garibay for the valuable discussions on the statistical analysis. Also, the authors would like to acknowledge to Anja Müller for her encouragement to develop this project and assistance during the measurements. The identification performed by GC-MS was supported by Ministerio de Economía, Industria y Competitividad of Spain (project AGL2016- 80475-R, AEI/FEDER, UE), by the Comunidad of Madrid and European funding from FSE and FEDER programs (project S2018/BAA-4393, AVANSECAL-II-CM).

A comprehensive analysis of cocoa polyphenols from unfermented and fermented cocoa beans from a wide range of geographic origins was carried out to catalogue systematic differences based on their origin as well as fermentation status. This study identifies previously unknown compounds with the goal to ascertain, which of these are responsible for the largest differences between bean types. UHPLC coupled with ultra-high resolution time-of-flight mass spectrometry was employed to identify and relatively quantify various oligomeric proanthocyanidins and their glycosides amongst several other unreported compounds. A series of biomarkers allowing a clear distinction between unfermented and fermented cocoa beans and for beans of different origins were identified. The large sample set employed allowed comparison of statistically significant variations of key cocoa constituents.

We report two 71-year-old female monozygotic twins presenting with advanced hyperostosis frontalis interna, obesity, shortness and cognitive impairment. They both have suffered from generalized seizures since their early adulthood. Moreover, the patients showed some additional conditions only occurring in one individual or the other such as migraine, marked recurrent depressive disorder or polyarthrosis. The symptoms common to both twins appear to correspond to the Morgagni-Stewart-Morel syndrome and indicate a genetic basis of this disorder as these features occur in genetically identical patients.

We report two 71-year-old female monozygotic twins presenting with advanced hyperostosis frontalis interna, obesity, shortness and cognitive impairment. They both have suffered from generalized seizures since their early adulthood. Moreover, the patients showed some additional conditions only occurring in one individual or the other such as migraine, marked recurrent depressive disorder or polyarthrosis. The symptoms common to both twins appear to correspond to the Morgagni-Stewart-Morel syndrome and indicate a genetic basis of this disorder as these features occur in genetically identical patients.