• 센서학회지
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• 제13권6호
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• pp.454-461
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• 2004

We have designed a portable electronic nose (e-nose) system using an array of commercial gas sensors and personal digital assistants (PDA) for the recognition and analysis of volatile organic compounds (VOC) in the field. Field screening of pollutants has been a target of instrumental development during the past years. A portable e-nose system was advantageous to localize the special extent of a pollution or to find pollutants source. The employment of PDA improved the user-interface and data transfer by Internet from on-site to remote computer. We adapted the Lavenberg-Marquardt algorithm based on the back-propagation and proposed the method that could predict the concentration levels of VOC gases after classification by separating neural network into two parts.

• 한국식품과학회지
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• 제37권6호
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• pp.1048-1064
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• 2005

Detection of specific compounds influencing food flavor quality is not easy. Electronic nose, comprised of electronic chemical sensors with partial specificity and appropriate pattern recognition system, is capable of recognizing simple and complex volatiles. It provides fast analysis with simple and straightforward results and is best suited for quality control and process monitoring of flavor in food industry. This review examines application of electronic nose in food analysis with brief explanation of its principle. Characteristics of different sensors and sensor drift. and solutions to related problems are reviewed. Applications of electronic nose in food industry include monitoring of fermentation process and lipid oxidation, prediction of shelf life, identification of irradiated volatile compounds, discrimination of food material origin, and quality control of food and processing by principal component analysis and neural network analysis. Electronic nose could be useful for quality control in food industry when correlating analytical instrumental data with sensory evaluation results.

• E2M - 전기 전자와 첨단 소재
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• 제8권4호
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• pp.509-517
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• 1995

• 농업과학연구
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• 제38권4호
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• pp.761-767
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• 2011

The objective of this study was to predict total bacteria count of pork meats by using the portable electronic nose systems developed throughout two stages of the prototypes. Total bacteria counts were measured for pork meats stored at $4^{\circ}C$ for 21days and compared with the signals of the electronic nose systems. PLS(Partial least square), PCR (Principal component regression), MLR (Multiple linear regression) models were developed for the prediction of total bacteria count of pork meats. The coefficient of determination ($R_p{^2}$) and root mean square error of prediction (RMSEP) for the models were 0.789 and 0.784 log CFU/g with the 1st system for the pork loin, 0.796 and 0.597 log CFU/g with the 2nd system for the pork belly, and 0.661 and 0.576 log CFU/g with the 2nd system for the pork loin respectively. The results show that the developed electronic system has potential to predict total bacteria count of pork meats.

• KSBB Journal
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• 제22권6호
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• pp.401-408
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• 2007

전자코는 비특정센서를 이용하여 향기성분을 검출하는 분석 장치로 칼럼의 교체나 별도의 전처리과정 없이 사람의 코와 마찬가지로 패턴을 인식하여 신속하게 향기를 분석하거나 이취여부를 판별해 준다. 다변량 통계에 의한 차별성을 토대로 향기성분의 특성간의 차이를 주로 판별할 수도 있고 인공신경망을 통하여 반복된 학습 과정을 통해 미지의 시료의 향기성분과 비교하여 판별할 수도 있다. 전자코는 된장, 치즈, 포도주 등의 발효공정 과정에서 발효 정도를 예측할 수 있으며 또 다른 미생물의 오염 여부를 판단할 수가 있다. 식품산업에서 많이 활용되어 왔던 전자코 시스템의 응용은 바이오테크놀로지의 다양한 분야에도 보다 폭넓게 활용되어지기를 기대하여 본다.

• 센서학회지
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• 제24권6호
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• pp.368-372
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• 2015

In this paper, we proposed a post-processing technique for improving classification performance of electronic nose (E-Nose) system which may be occurred drift signals from sensor array. An adaptive radial basis function network using stochastic gradient (SG) and singular value decomposition (SVD) is applied to process signals from sensor array. Due to drift from sensor's aging and poisoning problems, the final classification results may be showed bias and fluctuations. The predicted classification results with drift are quantized to determine which identification level each class is on. To mitigate sharp fluctuations moving-averaging (MA) technique is applied to quantized identification results. Finally, quantization and some edge correction process are used to decide levels of the fluctuation-smoothed identification results. The proposed technique has been indicated that E-Nose system was shown correct odor identification results even if drift occurred in sensor array. It has been confirmed throughout the experimental works. The enhancements have produced a very robust odor identification capability which can compensate for decision errors induced from drift effects with sensor array in electronic nose system.

• 한국식품과학회지
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• 제37권5호
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• pp.856-860
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• 2005

Electronic-nose system was used to discriminate commercial sesame oils (A-F) extracted from imported seeds. Response (delta $R_{gas}/R_{air}$) of sensors gained from electronic nose was analyzed by principal component analysis (PCA). Flavor pattern of sesame oil A was similar to those of sesame oils B, C, and D. Sesame oils blended with corn oil at the ratio of 95:5, 90:10 and 80:20% (sesame oil/corn oil, w/w) could be discriminated from ouch genuine sesame oil.

• 한국연초학회지
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• 제22권2호
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• pp.170-175
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• 2000

This study was carried out to compare the quality of licorices from various cultivating areas. licorice samples used in this study were collected from North-east and Sinkiang area in China, Mongolia, Uzvekistan and Kazahstan. The chemical components of licorice samples were analyzed and the signal patterns of the electracts were detected by the electronic nose. Contents of glycyrrhizin and glicyrrhizic acid, the key components of licorice were distributed in the region of 16.7～25.2% and 5.8～10.2%, respectively and were various according to the samples of the collected areas. In glycyrrhizin contents, root of Sinkiang showed the lowest value of 16.7%, and that of North-east the highest of 25.2%. In glycyrrhizic acid contents, root of Sinkiang showed the lowest of 5.8 %, and Kazahstan showed the highest of 10.2 %. Composition ratio of glycyrrhizin to glycyrrhizic acid was not always limear. As other components is other components affecting quality, contents of ash, starch and gums were 2.4～3.7%, 0.2～3.9%, respectively. When the headspace volatiles of licorices were analyzed using Electronic Nose System and the obtained data were interpreted using statistical method of MANOVA, characteristic patterns of licorices were different from each other according to collected area and its p value showed 0.0001. These results suggest that licorices may be discriminated from the collected areas by using Electronic Nose System.

• 한국축산식품학회지
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• 제30권2호
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• pp.185-189
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• 2010

An electronic nose was used to identify Salmonella contamination on beef based on odors. To detect pathogen contamination of beef, $100{\mu}L$ of $10^5CFU/g$ Salmonella Enteritidis or Salmonella Typhimurium cell suspensions were spiked onto 5 g beef sirloin samples in individual vials. Odor changes over time were then measured and analyzed using an electronic nose system to identify pathogen contamination. In principle, the electronic nose system based on a surface acoustic wave (SAW) detector produced different frequency responses depending on the time and amount of each chemical. Multivariate analysis of the odor data was conducted to detect Salmonella contamination of beef. Salmonella odors were successfully distinguished from uncontaminated beef odors by principal component analysis (PCA). The PCA results showed that Salmonella contamination of beef could be detected after 4 h of incubation. The numbers of cells enumerated by standard plate count after 4 h of inoculation were $2{\times}10^6CFU/g$ for both Salmonella Enteritidis and Salmonella Typhimurium.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2004년도 학술대회 논문집 정보 및 제어부문
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• pp.39-42
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• 2004

We have designed a portable electronic nose(e-nose) system using an array of commercial gas sensors for recognition and analyzing the various odours. In this paper, we have implemented a portable e-nose system using an array gas sensors and personal digital assistants(PDA) for recognizing and analyzing volatile organic compounds(VOCs) in the field. Field screening for pollutants has been a target of instrumental development for number of year. A portable e-nose system can be substantial benefit to rapidly localize the spacial extent of a pollution or to find pollutants source. And, by using PDA, E-nose have a better function such as the easy user-interface and data transfer by internet from on- site to remote computer. We adapted the Levenberg-Marquardt algorithm based on the back-propagation and proposed the method that could be predicted concentration levels of VOCs gases after classification by separating neural network into two parts.