Electronic Nose for Detection of Food Flavor and Volatile Components

2011 ◽  
pp. 267-288
Keyword(s):  
Electronic Nose ◽  
Volatile Components

scholarly journals Electronic nose based on nanoweights, expectation and reality

2017 ◽  
Vol 89 (10) ◽  
pp. 1587-1601 ◽  
Author(s):  
Tatyana Anatolievna Kuchmenko
Keyword(s):  
Electronic Nose ◽  
Raw Materials ◽  
Visual Image ◽  
Quantitative Information ◽  
Volatile Components ◽  
Integral Image ◽  
Standard Samples ◽  
Wine Quality ◽  
Electronic Noses ◽  
Complicated Task

AbstractOne of the topical approaches in analysis – outside the framework of traditional ones – is the formation of an integral “image” of the object. There are several approaches to solving the issue of obtaining as much information about the sample by a certain portion of its properties or its composition as possible. The first approach is forming a visual image (diagram) of several different properties of the analyzed sample, for example, the content of certain metals, acids, volatile components and some other indicators of wine quality. The consolidated image of a sample enables us to distinguish samples identical or similar in the selected properties from crucially different ones, even in case of an acceptable change of each indicator. Or else, using the consolidated image one can evaluate the direction of an image shift of a certain sample compared to the set of standard samples. The analysis of the geometry of the sample image by diverse indicators affords ground for assumption of the reasons for this deviation, as well as identification of falsification, or even solution of a more complicated task: detecting the area of growth of raw materials. The second approach is close to the first one in terms of methodology, but it digitizes properties using detectors and presents this as an image (“visual print” of response) of signals of these detectors on some components of the sample (presence, content). The feature of this approach is the use of a detector system that is non-selective and cross-sensitive to certain sample components. These sample images are produced using a system of “electronic nose”. “Visual prints” of array signals of different character sensors contain qualitative and quantitative information about the part of the analyzed sample which is sorbed by sensors. Despite the uncertainty of this information, “electronic noses” of piezoelectric type are widely used in the analysis of samples with complex varying composition.

scholarly journals Analysis of Volatile Components of Auricularia auricula from Different Origins by GC-MS Combined with Electronic Nose

2020 ◽  
Vol 2020 ◽  
pp. 1-9
Author(s):  
Lijun Fu ◽  
Gen Yang ◽  
Li Liu ◽  
Yongzheng Ma ◽  
Xiumin Zhang ◽  
...  
Keyword(s):  
Acetic Acid ◽  
Electronic Nose ◽  
Relative Content ◽  
Volatile Components ◽  
Auricularia Auricula ◽  
Edible Fungus ◽  
Odor Activity Value ◽  
Diethyl Azodicarboxylate ◽  
Different Origins ◽  
High Degree

Auricularia auricula is a kind of nutrient-rich edible fungus, which has the reputation of “king of vegetarians.” In this paper, the electronic nose combined with GC-MS technology was used to analyze the volatile components of A. auricula in Heilongjiang, Jilin, Shanghai, and Sichuan provinces to investigate the differences and characteristics of A. auricula in different origins. The results showed that the electronic nose could obviously distinguish the samples from Jilin and Shanghai with a high degree of discrimination, while it was inappropriate to distinguish the samples from Heilongjiang and Sichuan Province. GC-MS was used to further analyze the volatile compounds in A. auricula qualitatively and quantitatively. The results showed that 98 volatile components were detected and 23 of them were common components, including alcohols, aldehydes, acids, esters, hydrocarbons, and other volatile components. The relative content of acetic acid and diethyl azodicarboxylate in A. auricula from the four origins was relatively high. According to the relative odor activity value (ROAV), it was found that the key compounds that caused the aroma difference between different origins were 1-octene-3-ol, cis-3-nonene-1-ol, (E)-2-octenal, (E)-2-nonenal, (E,E)-2,4-nonadienal, and 3-methyl butanal.

scholarly journals Discrimination of Two Cultivars of Alpinia Officinarum Hance Using an Electronic Nose and Gas Chromatography-Mass Spectrometry Coupled with Chemometrics

Sensors ◽  
2019 ◽  
Vol 19 (3) ◽  
pp. 572 ◽  
Author(s):  
Qin Long ◽  
Zhong Li ◽  
Bin Han ◽  
Hamid Gholam Hosseini ◽  
Huaying Zhou ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Gas Chromatography ◽  
Electronic Nose ◽  
Principal Component ◽  
Gas Chromatography Mass Spectrometry ◽  
Volatile Components ◽  
Alpinia Officinarum ◽  
Chromatography Mass Spectrometry ◽  
Detection Technology ◽  
Highly Correlated

Background: Alpinia officinarum Hance is both an herbal medicine and a condiment, and generally has different cultivars such as Zhutou galangal and Fengwo galangal. The appearance of these A. officinarum cultivars is similar, but their chemical composition and quality are different. It is therefore important to discriminate between different A. officinarum plants to ensure the consistency of the efficacy of the medicine. Therefore, we used an electronic nose (E-nose) to explore the differences in odor information between the two cultivars for fast and robust discrimination. Methods: Odor and volatile components of all A. officinarum samples were detected by the E-nose and gas chromatography-mass spectrometry (GC-MS), respectively. The E-nose sensors and GC-MS data were analyzed respectively by principal component analysis (PCA), the correlation between E-nose sensors and GC-MS data were analyzed by partial least squares (PLS). Results: It was found that Zhutou galangal and Fengwo galangal can be discriminated by combining the E-nose with PCA, and the E-nose sensors S2, S6, S7, S9 were important sensors for distinguishing different cultivars of A. officinarum. A total of 56 volatile components of A. officinarum were identified by the GC-MS analysis, and the composition and content of the volatile components from the two different A. officinarum cultivars were different, in particular the relative contents of 1,8-cineole and α-farnesene. The classification result by PCA analysis based on GC-MS data was consistent with the E-nose results. The PLS analysis demonstrated that the volatile terpene, alcohol and ester components primarily interacted with the sensors S2 and S7, indicating that particular E-nose sensors were highly correlated with some aroma constituents. Conclusions: Combined with advanced chemometrics, the E-nose detection technology can discriminate two cultivars of A. officinarum, with GC-MS providing support to determine the material basis of the E-nose sensors’ response.

Comparative flavor analysis of four kinds of sweet fermented grains by sensory analysis combined with GC-MS

2022 ◽  
Vol 0 (0) ◽  
Author(s):  
Lei Wang ◽  
Ke Yang ◽  
Liu Liu
Keyword(s):  
Physicochemical Properties ◽  
Volatile Compounds ◽  
Electronic Nose ◽  
Sensory Analysis ◽  
Raw Materials ◽  
Electronic Tongue ◽  
Volatile Components ◽  
Red Rice ◽  
Different Types ◽  
Fermented Grains

Abstract Four types of cereals (glutinous rice, purple rice, red rice, yellow millet) were selected to produce sweet fermented grains. Flavor profiles of sweet fermented grains are comparatively studied to distinguish various flavor types by using GC-MS, electronic nose (E-nose), and sensory analysis, and the amino acid composition and physicochemical properties of sweet fermented grains were analyzed. The results showed that the volatile compounds of sweet fermented grains were significantly different. Esters and alcohols were the major volatile compounds in sweet fermented grains. The electronic nose, electronic tongue and sensory analysis jointly verified that the volatile components of sweet fermented grains had differences between them. The sweet fermented grains could be classified based on differences in volatile compounds. In the amino acids analysis, Glu, Pro, Asp and Leu were the most abundant. The difference in physicochemical properties is more helpful to distinguish different types of sweet fermented grains. Correlation analysis between antioxidant active substances and color value showed a positive correlation between with a* value, and a negative correlation with L*, b* value. Our results suggested that there were differences in the flavor characteristics of sweet fermented grains fermented from different types of cereals. The results of the study will provide valuable information for the selection of raw materials for sweet fermented grains.

scholarly journals Volatile components of white Hypsizygus marmoreus detected by electronic nose and HS-SPME-GC-MS: Influence of four drying methods

2017 ◽  
Vol 20 (12) ◽  
pp. 2901-2910 ◽  
Author(s):  
Guitang Chen ◽  
Fangning Wu ◽  
Fei Pei ◽  
Shujie Cheng ◽  
Benard Muinde ◽  
...  
Keyword(s):  
Electronic Nose ◽  
Volatile Components ◽  
Drying Methods ◽  
Hypsizygus Marmoreus

Development of a Portable Electronic Nose System to Analyze Flavour Signal Patterns of Kochujang

2006 ◽  
Vol 321-323 ◽  
pp. 1217-1220
Author(s):  
Jeong Woo Lee ◽  
Dong Wha Shin ◽  
Seong Min Kim
Keyword(s):  
Electronic Nose ◽  
Gas Sensors ◽  
Signal Analysis ◽  
Operating Conditions ◽  
Transient Signal ◽  
Optimum Operating ◽  
Volatile Components ◽  
Metal Oxide Gas Sensors ◽  
Electronic Nose System ◽  
Transient And Steady State

The purpose of this study is to develop a portable electronic nose system to measure volatile components of agricultural and food products. Also, operating software to control the electronic nose system through the Internet was developed. Various experiments to find optimum operating conditions of the system were performed. An array of commercial metal oxide gas sensors was used to detect various gas components. For kochujang experiment, flavour signal patterns were different to the type of kochujang. Transient and steady state signals were analyzed. Transient signal analysis was more useful in PCA. Cluster analysis showed the possibility of reduction of the number of sensors. It is feasible to optimise the kochujang making process.

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