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基于气体传感器阵列的物种鉴别。

Species Discrimination Using a Gas Sensor Array.

机构信息

Department of Electronic Engineering, University of Rome Tor Vergata, Via del Politecnico 1, 00133 Rome, Italy.

Department of Occupational and Environmental Medicine, Epidemiology and Hygiene, National Institute for Insurance against Accidents at Work (INAIL) Via Fontana Candida 1, 00078 Monte Porzio Catone, Rome, Italy.

出版信息

Sensors (Basel). 2020 Jul 18;20(14):4004. doi: 10.3390/s20144004.

DOI:10.3390/s20144004
PMID:32708481
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7412133/
Abstract

The efficiency of electronic noses in detecting and identifying microorganisms has been proven by several studies. Since volatile compounds change with the growth of colonies, the identification of strains is highly dependent on the growing conditions. In this paper, the effects of growth were investigated with different species of , which is one of the most studied microorganisms because of its implications in environmental and food safety. For this purpose, we used an electronic nose previously utilized for volatilome detection applications and based on eight porphyrins-functionalized quartz microbalances. The volatile organic compounds (VOCs) released by cultured fungi were measured at 3, 5, and 10 days after the incubation. The signals from the sensors showed that the pattern of VOCs evolve with time. In particular, the separation between the three studied strains progressively decreases with time. The three strains could still be identified despite the influence of culture time. Linear Discriminant Analysis (LDA) showed an overall accuracy of 88% and 71% in the training and test sets, respectively. These results indicate that the presence of microorganisms is detectable with respect to background, however, the difference between the strains changes with the incubation time.

摘要

电子鼻在检测和识别微生物方面的效率已被多项研究证明。由于挥发性化合物随着菌落的生长而变化,因此菌株的鉴定高度依赖于生长条件。在本文中,我们研究了不同种类的生长效应,因为其在环境和食品安全方面的重要性, 是研究最多的微生物之一。为此,我们使用了一种先前用于挥发组检测应用的电子鼻,该电子鼻基于 8 个卟啉功能化的石英微天平。在培养真菌后 3、5 和 10 天测量培养真菌释放的挥发性有机化合物 (VOC)。传感器的信号表明,VOC 随时间的变化而演变。特别是,三种研究菌株之间的分离度随时间逐渐降低。尽管受到培养时间的影响,三种菌株仍可以被识别。线性判别分析 (LDA) 分别在训练集和测试集中显示出 88%和 71%的总体准确性。这些结果表明,与背景相比,可以检测到微生物的存在,但是菌株之间的差异会随着培养时间而变化。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/da67/7412133/8d83237149d6/sensors-20-04004-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/da67/7412133/50e64ad233ed/sensors-20-04004-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/da67/7412133/638185442abd/sensors-20-04004-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/da67/7412133/0d0d91d91f22/sensors-20-04004-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/da67/7412133/638194f12ec2/sensors-20-04004-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/da67/7412133/23326a549183/sensors-20-04004-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/da67/7412133/c87ad487a624/sensors-20-04004-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/da67/7412133/2fbb4b39c1f4/sensors-20-04004-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/da67/7412133/3eacf5426a5c/sensors-20-04004-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/da67/7412133/8d83237149d6/sensors-20-04004-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/da67/7412133/50e64ad233ed/sensors-20-04004-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/da67/7412133/638185442abd/sensors-20-04004-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/da67/7412133/0d0d91d91f22/sensors-20-04004-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/da67/7412133/638194f12ec2/sensors-20-04004-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/da67/7412133/23326a549183/sensors-20-04004-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/da67/7412133/c87ad487a624/sensors-20-04004-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/da67/7412133/2fbb4b39c1f4/sensors-20-04004-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/da67/7412133/3eacf5426a5c/sensors-20-04004-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/da67/7412133/8d83237149d6/sensors-20-04004-g009.jpg

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