Amino acid profile behavior during the fermentation of Criollo cocoa beans.

The study investigated the behavior of seventeen amino acids during spontaneous (SF) and starter culture (SC) fermentation of Criollo cocoa beans from Copallín, Guadalupe and Tolopampa, Amazonas-Peru. For this purpose, liquid chromatography (UHPLC) was used to quantify amino acids. Multivariate analysis was used to differentiate the phases of the fermentation process. The percentage of essential amino acids during SC fermentation (63.4%) was higher than SF (61.8%); it was observed that the starter culture accelerated their presence and increased their concentration during the fermentation process. The multivariate analysis identified a first stage (day 0 to day 2), characterized by a low content of amino acids that increased due to protein hydrolysis. The study showed that adding the starter culture (Saccharomyces cerevisiae) to the fermentation mass increased the concentration of essential amino acids (63.0%) compared to the spontaneous process (61.8%). Moreover, this addition reduced the fermentation time (3-4 days less), demonstrating that the fermentation process with a starter culture allows obtaining a better profile of amino acids precursors of flavor and aroma.

Reduction in the Cocoa Spontaneous and Starter Culture Fermentation Time Based on the Antioxidant Profile Characterization.

In current systems, the fermentation spontaneous process produces fermented beans of heterogeneous quality due to the fermentation time. This study demonstrated that the fermentation time should be reduced. For this purpose, the physicochemical parameters, antioxidant profile, and volatile compounds were characterized in two types of fermentation (spontaneous and starter culture) for 168 h in cocoa from three altitude levels. Multivariate analysis (cluster and PCA) was used to discriminate the fermentation stages. We found three stages in all fermentations, where the first two stages (0 h to 96 h) were characterized by a higher antioxidant potential of the cocoa bean and the presence of desirable volatile compounds such as acids, alcohols, aldehydes, ketones, and esters, which are precursors of cocoa aroma; however, prolonged fermentation times affected the antioxidant profile of the bean. In addition, the use of a starter culture facilitates the release of compounds in a shorter time (especially alcohols and esters). It is concluded that it is necessary to reduce the fermentation time under these conditions in the region of Amazonas.

Changes in bioactive compounds during fermentation of cocoa (Theobroma cacao) harvested in Amazonas-Peru.

Cocoa (Theobroma cacao) is the main raw material for the production of chocolate; it is considered the food of the gods, as it possesses a diversity of bioactive compounds beneficial to human health. The abundance of bioactive compounds, among others, is conditioned by the post-harvest processing of cocoa beans, and fermentation is a major step in this regard. Consequently, this research evaluated the changes in phenolic compounds and methylxanthines occurred in the fermentation of Criollo and CCN-51 cocoa beans, varieties of great commercial interest for the cocoa-growing areas of Peru. For this purpose, samples were taken every 12 h of cocoa beans under fermentation for 204 h in which phenols (gallic acid, caffeic acid, catechin, and epicatechin) and methylxanthines (theobromine, caffeine and theophylline) were quantified by ultra-high performance liquid chromatography (UHPLC); total polyphenols by Folin Ciocalteu; antioxidant capacity by DPPH free radical capture method; total anthocyanins; pH; titratable acidity; and fermentation rate of beans. We found that during fermentation, phenolic content, antioxidant activity, and methylxanthines of cocoa beans decreased; on the other hand, the anthocyanin content increased slightly. Indeed, at distinctly degree, fermentation influences bioactive compounds in cocoa beans, depending on the variety cultivated.

Characterization and antimicrobial activity of microencapsulated citral with dextrin by spray drying.

Aim of this work was to evaluate the antimicrobial activity and physical characteristics of citral microencapsulated with dextrin (Dx) by spray drying. The encapsulation was optimized using response surface methodology (RSM), maximizing yield and efficiency, considering as independent variables the citral:Dx ratio (1:5 and 1:20) and the inlet air temperature (120 and 200 °C). Yield and efficiency under optimal conditions were 71.9% and 99.9%, respectively. Antimicrobial activity against Escherichia coli, Salmonella enterica, Staphylococcus aureus and Bacillus cereus of the citral microparticles obtained under optimal conditions and of free citral was evaluated using the disk diffusion methodology. Both compounds showed a broad spectrum inhibitory effect, being Escherichia coli and Bacillus cereus the most sensitive microorganisms. The inhibition ratio varied between 55 and 75%, and the antibacterial activity was maintained after microencapsulation. The minimum inhibitory concentrations of free citral were above 0.8 mg/mL. The optimal citral microparticles showed acceptable physicochemical characteristics and broad-spectrum antimicrobial activity. Polymer and emulsifier used in microencapsulation protected the functional activity of citral, thus suggesting that these microparticles could be used in the design of antimicrobial food systems to extend the shelf life of perishable foods.

Determination of the superficial citral content on microparticles: An application of NIR spectroscopy coupled with chemometric tools.

This work evaluates near-infrared (NIR) spectroscopy coupled with chemometric tools for determining the superficial content of citral ( S C C t ) on microparticles. To perform this evaluation, using spray drying, citral was encapsulated in a matrix of dextrin using twelve combinations of citral:dextrin ratios (CDR) and inlet air temperatures (IAT). From each treatment, six samples were extracted, and their S C C t and NIR absorption spectral profiles were measured. Then, the spectral profiles, pretreated and randomly divided into modeling and validation datasets, were used to build the following prediction models: principal component analysis-multilinear regression (PCA-MLR), principal component analysis-artificial neural network (PCA-ANN), partial least squares regression (PLSR) and an artificial neural network (ANN). During the validation stage, the models showed R 2 values from 0.73 to 0.96 and a root mean squared error (RMSE) range of [0.061-0.140]. Moreover, when the models were compared, the full and optimized ANN models showed the best fits. According to this study, NIR coupled with chemometric tools has the potential for application in determining S C C t on microparticles, particularly when using ANN models.