Electronic Prediction of Chemical Contaminants in Aroma of Brewed Roasted Coffee and Quantification of Acrylamide Levels.

The aim of this research was to apply an electronic device as indirect predictive technology to evaluate toxic chemical compounds in roasted espresso coffee. Fresh coffee beans were subjected to different thermal treatments and analyzed to determine volatile organic compounds, content of acrylamide and 5-hydroxymethylfurfural, sensory characteristics and electronic nose data. In total, 70 different volatile compounds were detected and grouped into 15 chemical families. The greatest percentage of these compounds were furans, pyrazines, pyridines and aldehydes. The positive aroma detected had the intensity of coffee odor and a roasted aroma, whereas the negative aroma was related to a burnt smell. A linear relationship between the toxic substances and the sensory defect was established. A high sensory defect implied a lower content of acrylamide and a higher content of 5-hydroxymethylfurfural. Finally, electronic signals were also correlated with the sensory defect. This relationship allowed us to predict the presence of these contaminants in the roasted coffee beverage with an indirect method by using this electronic device. Thus, this device may be useful to indirectly evaluate the chemical contaminants in coffee beverages according to their sensory characteristics.

Development of Gluten-Free Bread Using Teosinte (Dioon mejiae) Flour in Combination with High-Protein Brown Rice Flour and High-Protein White Rice Flour.

Gluten-free bread is an important product that is under development using different sources, such as rice and starchy plants. Teosinte seeds are utilized by ethnic groups in Honduras to produce gluten-free flour to prepare traditional baked goods and beverages. The quality of gluten-free products could vary depending on flour properties, such as amylose content, particle size, and water absorption capacity. A good strategy for developing baked goods is to mix different cereal grain sources to optimize their physicochemical properties. As a result, the current study aimed to develop bread from novel flours including teosinte (TF), high-protein brown rice (BRF), and high-protein white rice (WRF). Breads were analyzed for hardness, specific volume, and color utilizing a Simplex-Centroid mixture design coupled with the desirability function. Pasting, and rheological characteristics of the flours, were also analyzed. For flour characteristics, TF addition to BRF or WRF decreased the peak, trough, breakdown, setback, and final viscosities, which would result in a more stable bread and decrease the flow index of rice flour dispersions. BRF and WRF had similar pasting properties, except that BRF had a lower breakdown viscosity. For bread characteristics, TF addition to BRF or WRF increased the specific volume and hardness of the bread compared to rice flour alone. L* of the crust and crumb a* values were increased with greater TF in the mixture, whereas TF decreased the crust a*and b* values and crumb L* values when mixed with BRF or WRF compared to rice flours alone. WRF and BRF were similar in crumb color (L* and a*), except that BRF had greater crumb yellowness (b*). Teosinte flour can be used in combination with rice flour to produce bread with good quality.

Sous-vide processing of silver carp: Effect of processing temperature and cold storage duration on the microbial quality of the product as well as modeling by artificial neural networks.

Silver carp (Hypophthalmichthys molitrixi) was processed by sous-vide method at different temperatures (60, 65, 70, and 75°C). Then, the microbiological quality of the processed samples was monitored during cold storage (4°C) for 21 days. The target microorganisms were Enterobacteriaceae, Lactic Acid bacteria (LAB), Pseudomonas, Psychrotrophs, and total viable count (TVC). In samples processed at 75°C, the presence of Enterobacteriaceae, Pseudomonas and Psychrotrophs were not detectable up to 15 days of storage and lactic acid bacteria were not detectable even at the end of the storage period. A radial basis function neural network (RBFNN) model was established to predict the changes in the microbial content of silver carp. In this step, the relationship between processing temperature and storage duration on microbial growth was modeled by ANNs (artificial neural networks). The optimal ANN topology for modeling Enterobacteriaceae, Pseudomonas, and Psychrotroph contained 9 neurons in the hidden layer, but it contained 15 and 14 neurons for TVC and LAB, respectively. By experimenting with the temperature of -80°C, it was revealed that the obtained ANN model has a high potential for prediction.

Electronic Nose and Gas Chromatograph Devices for the Evaluation of the Sensory Quality of Green Coffee Beans.

The aim of this work is to discriminate between the volatile org9anic compound (VOC) characteristics of different qualities of green coffee beans (Coffea arabica) using two analysis approaches to classify the fresh product. High-quality coffee presented the highest values for positive attributes, the highest of which being fruity, herbal, and sweet. Low-quality samples showed negative attributes related to roasted, smoky, and abnormal fermentation. Alcohols and aromatic compounds were most abundant in the high-quality samples, while carboxylic acids, pyrazines, and pyridines were most abundant in the samples of low quality. The VOCs with positive attributes were phenylethyl alcohol, nonanal and 2-methyl-propanoic acid, and octyl ester, while those with negative attributes were pyridine, octanoic acid, and dimethyl sulfide. The aroma quality of fresh coffee beans was also discriminated using E-nose instruments. The PLS-DA model obtained from the E-nose data was able to classify the different qualities of green coffee beans and explained 96.9% of the total variance. A PLS chemometric approach was evaluated for quantifying the fruity aroma of the green coffee beans, obtaining an RP2 of 0.88. Thus, it can be concluded that the E-nose represents an accurate, inexpensive, and non-destructive device for discriminating between different coffee qualities during processing.

Masking Effect of Cassia grandis Sensory Defect with Flavoured Stuffed Olives.

Carao (Cassia grandis) is an America native plant characterized by its high iron content. This particular property allows its use as a natural additive to fix the black colour in California-style black olives, while masking its unpleasant aroma by stuffing olives with flavoured hydrocolloid. The tasting panel evaluated olives filled with unflavoured hydrocolloid with a fruity aroma, classified them as an extra category. Olives with the Carao addition presented a positive aroma, but also showed negative sensory attributes such as cheese, fermented and metallic flavours/aromas. The aroma of lyophilized Carao was better than the fresh one. The 'Mojo picón' aroma masked defective olives, allowing their classification from the second to the first commercial category. The volatile compounds belonged to the following families: terpenes, hydrocarbons, and oxygenated compounds, while the minor ones were alcohols and acid derivatives. The main volatile compounds identified were dialyl disulphide and 3-methyl-butanoic acid; among the minor ones were 2,4-dimethyl-hexane and dimethyl-silanediol and nonanal. Addition of fresh Carao increased the unpleasant aroma provoked by 3-methyl-butanoic acid, 2-methyl-butanoic acid and (E)-2-Decenal. Finally, an electronic device was able to discriminate these aromas and the results obtained agreed with those of the tasting panel and the volatile compounds.