• 한국작물학회:학술대회논문집
• /
• 한국작물학회 2006년도 한국약용작물학회 공동춘계학술발표회
• /
• pp.40-54
• /
• 2006

It's not easy to detect the high quality and functional compounds for control quality of food materials. The electronic nose was an instrument, which comprised of an array of electronic chemical sensors with partial specificity and an appropriate pattern recognition system, capable of recognizing simple or complex odors. It can conduct fast analysis and provide simple and straightforward results and is best suited for quality control and process monitoring in the field of functional foods. Numbers of applications of an electronic nose in the functional food industry include discrimination of habitats for medicinal food materials, monitoring storage process, lipid oxidation, and quality control of food and/or processing with principal component analysis, neural network analysis and the electronic nose based on GC-SAW sensor. The electronic nose would be possibly useful for a wide variety of quality control in the functional food and plant cultivation when correlating traditional analytical instrumental data with sensory evaluation results or electronic nose data.

• 동아시아식생활학회지
• /
• 제18권1호
• /
• pp.14-21
• /
• 2008

Flavor is one of the most important factors for determining wine characteristics and quality. Flavor pattern of wines(brewed from America, France, Italy, Chile, and Australia) was analyzed by the electronic nose that is equipped with 12 metal oxide sensors. In the results, the flavor pattern of wines was discriminated according to their origins by the principal component analysis(PCA). Each proportion of the first principal component score in the PCA plot was 94.79%(America), 73.62%(France), 99.06%(Italy), 96.74%(Chile), and 96.53%(Australia), respectively. Consequently, the imported wines could be practically differentiated into one from the other origins by volatile properties, suggesting that electronic nose could be successfully used for easy screening and quality evaluation of wines.

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

• Preventive Nutrition and Food Science
• /
• 제11권3호
• /
• pp.237-242
• /
• 2006

The pattern of volatile emissions from white ginseng powders (WGP) that were treated with selected preservatives was investigated during 5-months of storage (at -10 and $25^{\circ}C$) by an electronic nose system equipped with 12 metal-oxide sensors. WGP were treated with gamma radiation at 5 kGy, commercial methyl bromide (MeBr), and phosphine fumigations. Electronic nose differentiated the volatile patterns of the WGP with each different preservative treatment. In addition, each volatile pattern was affected by both storage time (1, 2 and 5 months) and temperature (-10 and $25^{\circ}C$). After 5-months of storage, the least change of volatile patterns was observed from WGP fumigated with phosphine at $-10^{\circ}C$. The result also showed that volatile changes in WGP were much more affected by storage time than by storage temperature.

• 한국전기전자재료학회:학술대회논문집
• /
• 한국전기전자재료학회 1997년도 춘계학술대회 논문집
• /
• pp.99-102
• /
• 1997

An electronic nose system is an instrument designed far mimicking human olfactory system. It consists generally of gas (odor) sensor array corresponding to olfactory receptors of human nose and artificial neural network pattern recognition technique based on human biological odor sensing mechanism. Considerable attempts to develop the electronic nose system have been made far applications in the fields of floods, drinks, cosmetics, environment monitoring, etc. A portable electronic nose system has been fabricated by using oxide semiconductor gas sensor array and pattern recognition technique such as principal component analysis (PCA) and back propagation artificial neural network The sensor array consists of six thick film gas sensors whose sensing layers are Pd-doped WO$_3$ Pt-doped SnO$_2$ TiO$_2$-Sb$_2$O$_3$-Pd-doped SnO$_2$ TiO$_2$-Sb$_2$O$_{5}$-Pd-doped SnO$_2$+Pd filter layer, A1$_2$O$_3$-doped ZnO and PdCl$_2$-doped SnO$_2$. As an application the system has been used to identify CO/HC car exhausting gases and the identification has been successfully demonstrated.d.

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

• 동아시아식생활학회지
• /
• 제16권6호
• /
• pp.717-723
• /
• 2006

Chemical characteristics of soybean oil after deep-frying with potato sticks (200 g, 10% w/w of soybean oil) were studied according to the 34 deep-frying times. After consecutive 34 deep-frying, total polyunsaturated FA contents was gradually decreased while the total saturated FA and trans FA were increased. Acid value and peroxide value were increased while iodine value decreased, respectively. The Hunter $L^{\ast}$ value decreased while each $a^{\ast}\;and \;b^{\ast}b$ value were gradually increased. Electronic nose equipped with 12 metal oxide sensors was used for the discrimination of odor pattern of frying oils against the times of deep-trying. The proportions of 1st and 2nd principal component analysis showed 75.97% and 21.23%, respectively. While 6 among total 12 sensors well responded to discrimination of odor in the repented frying oils, suggesting that the odor pattern of each oil after deep-frying would be discriminated against fresh soybean oil, especially after 14 times. From the results, electronic nose could differentiate the degree of quality deterioration of the repeated deep-frying oils.

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

• 한국식품과학회지
• /
• 제33권1호
• /
• pp.24-27
• /
• 2001

Conducting polymer 센서가 부착된 전자코를 이용하여 장마, 단마, 대화마의 향기 패턴을 분석하였고, 관능평가도 병행하여 3가지 마 품종의 관능적 특성을 비교하여 보았다. 관능평가 결과, 장마는 아삭아삭한 조직감과 단맛이 강했고, 대화마는 끈적거리고 느끼하지만 고소함과 조직감이 단단하였으며, 단마는 마고유의 향이 강하고 장마와 대화마 중간 정도의 조직감을 보여주었다. 마의 향기에 대한 전자코의 감응도(intensity)는 단마에서 가장 높았고 대화마에서 가장 낮은 값의 변화를 보여주었다. 32개 센서의 표준화된 감응도에 대해서 주성분 분석을 실시했을 때 품종들 사이의 품질특성값은 모두 2미만의 값을 나타내어 각 품종들 간에 향기패턴의 차이가 없는 것으로 나타났고 제 1주성분과 제2주성분의 고유값도 각각 33%, 16%로 매우 낮았다. 그러나 감응도 변화가 $1.216{\sim}1.561$로 상대적으로 높은 8개의 민감한 센서만를 선택하여 주성분분석한 결과 단마와 대화마 사이의 품질특성값은 2.057로 향기패턴의 차이가 있는 것으로 나타났으며, 제1주성분의 고유값도 85.95%로 매우 높았다.

• 센서학회지
• /
• 제27권2호
• /
• pp.118-125
• /
• 2018

An evaluation system for an electronic-nose concept using three types of metal oxide gas sensors that react similarly to the human olfactory cells was constructed for the quantitative and qualitative evaluation of aroma fragrances. Four types of aroma fragrances (lavender, orange, jasmine, and Roman chamomile), which are commonly used in aromatherapy, were evaluated. All the gas sensors reacted remarkably to the aroma fragrances and the good correlation of r=0.58-0.88 with the aromatic odor intensities by olfaction was confirmed. From the results of the analysis of an electronic-nose concept for classifying the characteristics of aroma oil fragrances, aroma oils could be classified using the fragrance characteristics and oil extraction methods with the cumulative variability contribution rate of 95.65% (F1: 69.65%, F2: 26.03%) by principal component analysis. In the pattern recognition based on the artificial neural network, the four aroma fragrances were 100% recognized through the training data of 56 cases (70%) out of 80 cases, and the pattern recognition rate was 57.1%-71.4% through the validation and testing data of 24 cases (30%). The pattern recognition success rate through all confusion matrices was 82.1%, indicating that the classification of aroma oil fragrances using the three types of gas sensors was successful.