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Summary: Roasting processing was commonly applied to enhance flavour characteristics, and thus this study was to investigate the taste and aroma compounds between broccoli floret and stem during oven‐roasting processes. In electronic tongue analysis, sourness, saltiness, umami, and sweetness in florets showed an increasing tendency during the roasting, however, decreasing bitterness. Besides, In electronic nose analysis, methanethiol was reduced after the roasting processes and other sulfur compounds were generated in oven‐roasted florets and stems. Furthermore, furans were generated after the roasting. Pyridine and pyrazines were only identified in oven‐roasted florets, however, pyrrole was only identified in oven‐roasted stems. Principal component analysis and cluster analysis were conducted based on combined taste and aroma profiles. Broccoli floret roasted at 15 min was affected by numerous variables compared with the others, and broccoli stems roasted at 15 and 20 min were affected by numerous variables. Additionally, the floret roasted at 15 min was the highest dissimilarity amongst all florets, and the stems roasted at 15 and 20 min were the highest dissimilarity amongst all stems. Accordingly, oven‐roasting induced higher changes in taste and aroma characteristics with increasing times. In addition, this research may provide a basis for enhancing the flavour characteristics of broccoli. [ABSTRACT FROM AUTHOR]

BACKGROUND: Waxy maize (Zea mays L. sinensis Kulesh) is a good material for brewing. Waxy maize wine, a kind of Chinese rice wine, is strongly affected by a fermentation starter named Qu. In this study, an innovative mixed Qu, consisting of two yeasts and three molds, was produced and the raw‐starch brewing method was applied in winemaking. Three other waxy maize wines fermented by three kinds of commercial Qu were also analyzed for comparison. RESULTS: Due to superb growth and fermentation characteristics, Saccharomyces cerevisiae CICC1009 and Pichia anomala CICC1851 were chosen to produce yeast Qu. The addition amount of yeast Qu was determined to be 30 g kg−1. In terms of chemical properties, mixed Qu was more suitable for making maize wine by the raw‐starch brewing method than the three kinds of commercial Qu with which it was compared. The most influential components for the overall aroma profile in maize wines fermented by mixed Qu and Mifeng Qu were ethyl butyrate and β‐damascenone, respectively, while in maize wines fermented by Angel Qu and Like Qu the most influential component was ethyl octanoate. Obvious differences were found among four maize wines regarding bitterness, umami, richness, saltiness, and sourness by the electronic tongue. The olfactory characteristics of maize wine fermented by Mifeng Qu were quite different from the other three according to the electronic nose. CONCLUSION: The innovative mixed Qu can be considered as an excellent starter for raw‐starch brewing of waxy maize. The chemical indices and volatile flavor compounds of waxy maize wines were greatly affected by different kinds of Qu. © 2020 Society of Chemical Industry [ABSTRACT FROM AUTHOR]

Pufferfish (Takifugu spp.) are rapidly becoming a valuable food commodity across Asia, making the flavour characterization of the different species economically significant. In this study, the flavour characteristics of four cultured pufferfish varieties (T obscurus, T flavidus, T bimaculatus and T rubripes) were evaluated using headspace‐gas chromatography‐ion mobility spectrometry (HS‐GC‐IMS) coupled with an electronic nose and electronic tongue. A total of 37 volatile compounds, primarily aldehydes and alcohols, were identified by HS‐GC‐IMS and used to distinguish the four pufferfish species. Principal component analysis (PCA) of the volatile compound profiles indicated that the four cultivated varieties had unique chemical compositions. PCA of the electronic nose and tongue response data was consistent with HS‐GC‐IMS evaluation and revealed that the aroma and taste of T rubripes were distinct from the other varieties. The collaborative analysis method combining HS‐GC‐IMS and intelligent sensory systems could significantly advance the evaluation of flavour differences. [ABSTRACT FROM AUTHOR]

The purpose of this present study was to develop a rapid and effective approach for identification of red wines that differ in geographical origins, brands, and grape varieties, a multi‐sensor fusion technology based on a novel cost‐effective electronic nose (E‐nose) and a voltammetric electronic tongue (E‐tongue) was proposed. The E‐nose sensors was created using porphyrins or metalloporphyrins, pH indicators and Nile red printed on a C2 reverse phase silica gel plate. The voltammetric E‐Tongue with six metallic working electrodes, namely platinum, gold, palladium, tungsten, titanium, and silver was employed to sense the taste of red wines. Principal component analysis (PCA) was utilized for dimensionality reduction and decorrelation of the raw sensors datasets. The fusion models derived from extreme learning machine (ELM) were built with PCA scores of E‐nose and tongue as the inputs. Results showed superior performance (100% recognition rate) using combination of odor and taste sensors than individual artificial systems. The results suggested that fusion of the novel cost‐effective E‐nose created and voltammetric E‐tongue coupled with ELM has a powerful potential in rapid quality evaluation of red wine. [ABSTRACT FROM AUTHOR]

BACKGROUND The aim of this study is to investigate the feasibility of a 'holistic' approach, using near infrared ( NIR) spectroscopy and electronic devices (electronic nose and electronic tongue), as instrumental tools for the classification of different coffee varieties. Analyses were performed on green coffee, on ground roasted coffee and on coffee beverage. Principal component analysis was applied on spectral and sensory data to uncover correlations between samples and variables. After variable selection, linear discriminant analysis was used to classify the samples on the basis of the three coffee classes: Robusta, natural Arabica and washed Arabica. RESULTS Linear discriminant analysis demonstrates the practicability of this approach: the external test set validation performed with NIR data showed 100% of correctly classified samples. Moreover, a satisfying percentage of correct classification in cross-validation was obtained for the electronic devices: the average values of correctly classified samples were 81.83% and 78.76% for electronic nose and electronic tongue, respectively. CONCLUSION NIR spectroscopy was shown to be a very reliable and useful tool to classify coffee samples in a fast, clean and inexpensive way compared to classical analysis, while the electronic devices could assume the role of investigating techniques to depict the aroma and taste of coffee samples. © 2014 Society of Chemical Industry [ABSTRACT FROM AUTHOR]