Analysis of Electronic Nose and Electronic Tongue and Sensory Characteristics of Commercial Seasonings

Jeon, Seo-Young; Kim, Jinsook; Kim, Gi-Chang; Choi, Song-Yi; Kim, Sang-Bum; Kim, Kyungmi

doi:10.9724/kfcs.2017.33.5.538

Cited by 9 publications

(4 citation statements)

References 14 publications

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“…Recently, e-tongues have widely utilized to objectively measure tastes in many studies, such as investigation of the taste properties of fermented soybeans with mycelia of Tricholoma matsutake and Bacillus sp. [28], analysis of chemical compounds that may affect sensory properties of different parts of Wasabi koreana Nakai [30], discrimination of geographical origins of red ginseng [31], and investigation of the sensory properties of commercial seasonings [32].…”

Section: Resultsmentioning

confidence: 99%

Perilla frutescens Britton: A Comprehensive Study on Flavor/Taste and Chemical Properties During the Roasting Process

et al. 2019

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This study investigated changes of volatile compounds, sniffing test-assisted sensory properties, taste associated-constituent and free amino acid compositions, taste description by electronic-tongue, and chemical characteristics in Perilla frutescens Britton var. acuta Kudo after roasting at 150 °C for 0–8 min. A total of 142 volatile compounds were identified, among which methyl benzoate and limonene were predominant, regardless of roasting time, and these were also detected as the major compounds in the sniffing test by GC-olfactometry. For constituent amino acids analyzed by the acid hydrolysis method using hydrochloric acid (HCl), the concentration of glutamic acid, aspartic acid, and leucine showed an increase pattern with increased roasting time, which results in umami taste, sour taste, and bitter taste, respectively. For free amino acids, valine and hydroxylysine eliciting bitter and bitter and sweet tastes, respectively, also tend to increase by roasting. The pattern of amino acid concentration by roasting was readily matched to the taste description by electronic-tongue but that of sweetness and sourness by electronic-tongue did not coincide with the amino acid composition. For the chemical properties, total phenolic content, antioxidative capacity, and browning intensity tend to increase with roasting but decreased by 8 min. The results of this study provide fundamental information on perilla in both the food industry and cooking environment for the sake of increasing the utilization of perilla as a food source and ingredient.

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Section: Resultsmentioning

confidence: 99%

Perilla frutescens Britton: A Comprehensive Study on Flavor/Taste and Chemical Properties During the Roasting Process

et al. 2019

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“…In regard to amino acids associated with sweetness, Lee et al [ 19 ] reported that sweetness increased with an increased level of glycine in electronic tongue analysis of roasted Platycodon sample. The taste result by electronic tongue not only comes from major taste components of peanut but is an expression of a complex interaction of tastes from coffee and peanuts [ 43 ]. Electronic tongue analysis can exclude the subjectivity of panelists and offers analysis results within a short time and has therefore been widely utilized in recent years [ 43 ].…”

Section: Resultsmentioning

confidence: 99%

“…The taste result by electronic tongue not only comes from major taste components of peanut but is an expression of a complex interaction of tastes from coffee and peanuts [ 43 ]. Electronic tongue analysis can exclude the subjectivity of panelists and offers analysis results within a short time and has therefore been widely utilized in recent years [ 43 ]. However, electronic tongues lack the capacity to reflect all the complexity of biological aspects associated with the human oral environment.…”

Section: Resultsmentioning

confidence: 99%

Peanut Coffee: Enhancement of Nutritional, Physicochemical, and Sensory Characteristics in Coffee Brewed with Conventional and High-Oleic Peanut Extracts

Lee

Hong

jin-ju

et al. 2020

Foods

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This study investigated nutritional, physicochemical, and sensory characteristics of coffee brewed with conventional and high-oleic peanut extracts. Compared to normal coffee, peanut coffee exhibited more diverse amino acids compositions. In constituent amino acids composition, peanut coffee exhibited increased proportions of glutamic and aspartic acids but decreased phenylalanine. Peanut coffee had higher thiamin, niacin, and sugar contents, improved antioxidant capacity, and lower caffeine contents. In electronic tongue analysis, peanut coffee showed an increased intensity of sweetness and umami taste but decreased bitterness, corresponding to the result of amino acids compositions and caffeine and sugar contents. In volatile compounds analysis using gas chromatography-mass spectrometry (GC/MS) with the sniffing test, peanut coffee had high concentrations of 2-ethyl-3,6-dimethylpyrazine, 2,2′-methylenebis-furan, and furfuryl propionate, which were perceived as peanut and roasted odors in the sniffing test. This study will provide informative data in extending the application of peanut to coffee and developing novel coffee, with added peanut, that is nutritionally beneficial.

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“…Based on the taste difference between grafted and non-grafted watermelon fruits, the relationship between sensory evaluation and electronic tongue was studied, suggesting that these two measurement methods can complement each other [25]. Some researchers obtained the descriptive characteristics of commercial seasonings through artificial sensory evaluation, and conducted flavoring taste perception experiments with electronic tongues, which proved that there's a certain correlation between human senses and electronic tongue sensors [26]. Some researchers have scored rice wine through artificial sensory evaluation.…”

Section: Introductionmentioning

confidence: 99%

Fuzzy Evaluation Output of Taste Information for Liquor Using Electronic Tongue Based on Cloud Model

Liu

Zuo

Low

et al. 2020

Sensors

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As a taste bionic system, electronic tongues can be used to derive taste information for different types of food. On this basis, we have carried forward the work by making it, in addition to the ability of accurately distinguish samples, be more expressive by speaking evaluative language like human beings. Thus, this paper demonstrates the correlation between the qualitative digital output of the taste bionic system and the fuzzy evaluation language that conform to the human perception mode. First, through principal component analysis (PCA), backward cloud generator and forward cloud generator, two-dimensional cloud droplet groups of different flavor information were established by using liquor taste data collected by electronic tongue. Second, the frequency and order of the evaluation words for different flavor of liquor were obtained by counting and analyzing the data appeared in the artificial sensory evaluation experiment. According to the frequency and order of words, the cloud droplet range corresponding to each word was calculated in the cloud drop group. Finally, the fuzzy evaluations that originated from the eight groups of liquor data with different flavor were compared with the artificial sense, and the results indicated that the model developed in this work is capable of outputting fuzzy evaluation that is consistent with human perception rather than digital output. To sum up, this method enabled the electronic tongue system to generate an output, which conforms to human’s descriptive language, making food detection technology a step closer to human perception.

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Analysis of Electronic Nose and Electronic Tongue and Sensory Characteristics of Commercial Seasonings

Cited by 9 publications

References 14 publications

Perilla frutescens Britton: A Comprehensive Study on Flavor/Taste and Chemical Properties During the Roasting Process

Perilla frutescens Britton: A Comprehensive Study on Flavor/Taste and Chemical Properties During the Roasting Process

Peanut Coffee: Enhancement of Nutritional, Physicochemical, and Sensory Characteristics in Coffee Brewed with Conventional and High-Oleic Peanut Extracts

Fuzzy Evaluation Output of Taste Information for Liquor Using Electronic Tongue Based on Cloud Model

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