White Chocolate with Resistant Starch: Impact on Physical Properties, Dietary Fiber Content and Sensory Characteristics.

Resistant starch (RS) is a part of insoluble dietary fiber, and it could be recognized as a functional food ingredient in some types of confectionery products that lack dietary fiber. Unlike dark and milk chocolate, white chocolate does not contain fat-free cocoa solids rich in dietary fiber. In the present study, 5%, 10%, and 15% of white chocolate were substituted with RS in order to improve the nutritional value of enriched white chocolate. The influence of RS on rheological, textural, and thermal properties of the chocolate fat phase was firstly investigated, and then further influence on physical properties, dietary fiber content, and sensory characteristics of enriched white chocolates were investigated. The obtained results showed that enriched chocolates had increased content of total dietary fiber and reduced total fats and protein content in accordance with the added amount of RS. At the same time, RS increased viscosity and reduced the hardness and volume mean diameter in enriched chocolates in accordance with the added amount. RS improved the nutritional composition of white chocolate by increasing the content of dietary fiber. At the same time, RS did not impair the color and sensory characteristics of enriched white chocolates.

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.

Roadmap of cocoa quality and authenticity control in the industry: A review of conventional and alternative methods.

Cocoa (Theobroma cacao L.) and its derivatives are appreciated for their aroma, color, and healthy properties, and are commodities of high economic value worldwide. Wide ranges of conventional methods have been used for years to guarantee cocoa quality. Recently, however, demand for global cocoa and the requirements of sensory, functional, and safety cocoa attributes have changed. On the one hand, society and health authorities are increasingly demanding new more accurate quality control tests, including not only the analysis of physicochemical and sensory parameters, but also determinations of functional compounds and contaminants (some of which come in trace quantities). On the other hand, increased production forces industries to seek quality control techniques based on fast, nondestructive online methods. Finally, an increase in global cocoa demand and a consequent rise in prices can lead to future cases of fraud. For this reason, new analytes, technologies, and ways to analyze data are being researched, developed, and implemented into research or quality laboratories to control cocoa quality and authenticity. The main advances made in destructive techniques focus on developing new and more sensitive methods such as chromatographic analysis to detect metabolites and contaminants in trace quantities. These methods are used to assess cocoa quality; study new functional properties; control cocoa authenticity; or detect frequent emerging frauds. Regarding nondestructive methods, spectroscopy is the most explored technique, which is conducted within the near infrared range, and also within the medium infrared range to a lesser extent. It is applied mainly in the postharvest stage of cocoa beans to analyze different biochemical parameters or to assess the authenticity of cocoa and its derivatives.

Changes in Antioxidants and Sensory Properties of Italian Chocolates and Related Ingredients Under Controlled Conditions During an Eighteen-Month Storage Period.

BACKGROUND: While there has been an increasing interest in the health properties of chocolate, limited research has looked into the changes of antioxidants occurring in the time span from production to the best before date, which was a period of 18 months in this study. METHODS: Humidity, ash, pH, acidity, fiber, carotenoids, retinols, tocopherols, sugars, proteins, theobromine, caffeine, polyphenols, fats, the peroxide value, organic acids, and volatile compounds, along with the sensory profile, were monitored at 18-week intervals for 18 months under conditions simulating a factory warehouse or a point of sale. RESULTS: At the end of the storage period, more polyphenols were lost (64% and 87%) than vitamin E (5% and 14%) in cocoa mass and cocoa powder, respectively. Conversely, a greater loss in vitamin E (34% and 86%) than in polyphenols (19% and 47%) was shown in the hazelnut paste and gianduja chocolate, respectively. The sensory profiling of cocoa mass, cocoa powder, and hazelnut paste revealed increases in grittiness and astringency, as well as decreases in melting, bitterness, and toasted aroma. Moreover, in the hazelnut paste and gianduja chocolate, oiliness increased with a toasted and caramel aroma. Furthermore, dark chocolate was more gritty, acidic, and bitter. Milk chocolate lost its nutty aroma but maintained its sweetness and creaminess. CONCLUSIONS: These results should contribute an important reference for companies and consumers, in order to preserve the antioxidants and understand how antioxidants and sensory properties change from the date of production until the best before date.

Development of emotion lexicons to describe chocolate using the Check-All-That-Apply (CATA) methodology across Asian and Western groups.

Emotion-based terms selected by Asians and Westerners were analyzed to develop lexicons associated with chocolate consumption. Hence, an online-based questionnaire (Study 1: N = 206; 51% Asians, 49% Westerners) and a chocolate (milk and dark) tasting session (Study 2: N = 75; 52% Asians, 48% westerners) were conducted to assess emotion terms related to chocolate consumption using Check-All-That-Apply methodology. Emotional satisfaction was the main reason for chocolate consumption. Furthermore, selection of emotional terms was different between cultures and gender. For both studies (1 and 2), flavor of chocolate was the most important factor that determined purchase intention. For Study 2, milk and dark chocolate evoked different emotion terms for participants. The lexicon developed for milk chocolate had similar emotion terms compared to the Study 1 lexicon (online). Developing an emotion lexicon using an online survey could provide a reduced lexicon compared to lexicons generated during the tasting session and can be used as a fast-screening method to develop simplified emotion lexicons due to its similarity to the tasting lexicon. Newly developed lexicons from this study can be applied to sensory consumer tests of chocolate.

Brachial and Cerebrovascular Functions Are Enhanced in Postmenopausal Women after Ingestion of Chocolate with a High Concentration of Cocoa.

Background: Cocoa contains polyphenols that are thought to be beneficial for vascular health.Objective: We assessed the impact of chocolate containing distinct concentrations of cocoa on cerebrovascular function and cognition.Methods: Using a counterbalanced within-subject design, we compared the acute impact of consumption of energy-matched chocolate containing 80%, 35%, and 0% single-origin cacao on vascular endothelial function, cognition, and cerebrovascular function in 12 healthy postmenopausal women (mean ± SD age: 57.3 ± 5.3 y). Participants attended a familiarization session, followed by 3 experimental trials, each separated by 1 wk. Outcome measures included cerebral blood flow velocity (CBFv) responses, recorded before and during completion of a computerized cognitive assessment battery (CogState); brachial artery flow-mediated dilation (FMD); and hemodynamic responses (heart rate and blood pressure).Results: When CBFv data before and after chocolate intake were compared between conditions through the use of 2-factor ANOVA, an interaction effect (P = 0.003) and main effects for chocolate (P = 0.043) and time (P = 0.001) were evident. Post hoc analysis revealed that both milk chocolate (MC; 35% cocoa; P = 0.02) and dark chocolate (DC; 80% cocoa; P = 0.003) induced significantly lower cerebral blood flow responses during the cognitive tasks, after normalizing for changes in arterial pressure. DC consumption also increased brachial FMD compared with the baseline value before chocolate consumption (P = 0.002), whereas MC and white chocolate (0% cocoa) caused no change (P-interaction between conditions = 0.034).Conclusions: Consumption of chocolate containing high concentrations of cocoa enhanced vascular endothelial function, which was reflected by improvements in FMD. Cognitive function outcomes did not differ between conditions; however, cerebral blood flow responses during these cognitive tasks were lower in those consuming MC and DC. These findings suggest that chocolate containing high concentrations of cocoa may modify the relation between cerebral metabolism and blood flow responses in postmenopausal women. This trial was registered at www.ANZCTR.orgau as ACTRN12616000990426.

Consumption of dark chocolate attenuates subsequent food intake compared with milk and white chocolate in postmenopausal women.

BACKGROUND: Chocolate has a reputation for contributing to weight gain due to its high fat, sugar and calorie content. However, the effect of varying concentrations of cocoa in chocolate on energy intake and appetite is not clear. OBJECTIVE: To compare the acute effect of consuming an isocaloric dose of dark, milk and white chocolate on subsequent energy intake, appetite and mood in postmenopausal women. METHODS: Fourteen healthy postmenopausal women (57.6 ± 4.8yr) attended an introductory session followed by three experimental trials performed in a counterbalanced order at a standardised time of day, each separated by one week. Ad libitum energy intake, perceived appetite, mood and appetite-related peptides were assessed in response to consumption of 80% cocoa [dark chocolate], 35% cocoa [milk chocolate] and cocoa butter [white chocolate] (2099 kJ), prepared from a single-origin cacao bean. RESULTS: Ad libitum energy intake was significantly lower following dark (1355 ± 750 kJ) compared with both milk (1693 ± 969 kJ; P = 0.008) and white (1842 ± 756 kJ; P = 0.001) chocolate consumption. Blood glucose and insulin concentrations were transiently elevated in response to white and milk chocolate consumption compared with the dark chocolate (P < 0.05), while pancreatic polypeptide was elevated in response to higher cocoa content chocolate (dark and milk) compared with white chocolate (P < 0.05). No differences in active ghrelin or leptin were observed between conditions, nor was mood altered between conditions (P > 0.05). CONCLUSIONS: Dark chocolate attenuates subsequent food intake in postmenopausal women, compared to the impact of milk and white chocolate consumption.

Chocolate Classification by an Electronic Nose with Pressure Controlled Generated Stimulation.

In this work, we will analyze the response of a Metal Oxide Gas Sensor (MOGS) array to a flow controlled stimulus generated in a pressure controlled canister produced by a homemade olfactometer to build an E-nose. The built E-nose is capable of chocolate identification between the 26 analyzed chocolate bar samples and four features recognition (chocolate type, extra ingredient, sweetener and expiration date status). The data analysis tools used were Principal Components Analysis (PCA) and Artificial Neural Networks (ANNs). The chocolate identification E-nose average classification rate was of 81.3% with 0.99 accuracy (Acc), 0.86 precision (Prc), 0.84 sensitivity (Sen) and 0.99 specificity (Spe) for test. The chocolate feature recognition E-nose gives a classification rate of 85.36% with 0.96 Acc, 0.86 Prc, 0.85 Sen and 0.96 Spe. In addition, a preliminary sample aging analysis was made. The results prove the pressure controlled generated stimulus is reliable for this type of studies.