scholarly journals Simulation and Non-Invasive Testing of Vinegar Storage Time by Olfaction Visualization System and Volatile Organic Compounds Analysis

Foods ◽  
2021 ◽  
Vol 10 (3) ◽  
pp. 532
Author(s):  
Hao Lin ◽  
Jinjin Lin ◽  
Benteng Song ◽  
Quansheng Chen
Keyword(s):  
Volatile Organic Compounds ◽  
Organic Compounds ◽  
Storage Time ◽  
Recognition Rate ◽  
Principal Component ◽  
Reaction Chamber ◽  
Visualization System ◽  
Linear Discriminant ◽  
Air Inlet ◽  
Volatile Organic

An olfactory visualization system conducts a qualitative or quantitative analysis of volatile organic compounds (VOCs) by utilizing the sensor array made of color sensitive dyes. The reaction chamber is important to the sensor array’s sufficient and even exposure to VOCs. In the current work, a reaction chamber with an arc baffle embedded in the front of the air inlet for drainage effect was designed. The velocity of field and particle distribution of flow field in the reaction chamber was simulated by COMSOL Multiphysics. Through repeated simulation, the chamber achieved optimal result when the baffle curvature was 3.1 and the vertical distance between the baffle front end and the air inlet was 1.6 cm. Under the new reaction chamber, principal component analysis (PCA) and linear discriminant analysis (LDA) were employed to identify vinegar samples with different storage time through analyzing their VOCs. The LDA model achieved optimal performance when 8 principal components (PCs) were used, and the recognition rate was 95% in both training and prediction sets. The new reaction chamber could improve the stability and precision of an olfactory visualization system for VOCs analysis, and achieve the accurate differentiation and rapid discrimination of Zhenjiang vinegar with different storage time.

scholarly journals Tracking the Progression of Triple Negative Mammary Tumors over Time by Chemometric Analysis of Urinary Volatile Organic Compounds

Cancers ◽  
2021 ◽  
Vol 13 (6) ◽  
pp. 1462
Author(s):  
Mark Woollam ◽  
Luqi Wang ◽  
Paul Grocki ◽  
Shengzhi Liu ◽  
Amanda P. Siegel ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Volatile Organic Compounds ◽  
Organic Compounds ◽  
Triple Negative ◽  
Solid Phase ◽  
Univariate Analysis ◽  
Principal Component ◽  
Linear Discriminant ◽  
Volatile Organic ◽  
Over Time

Previous studies have shown that volatile organic compounds (VOCs) are potential biomarkers of breast cancer. An unanswered question is how urinary VOCs change over time as tumors progress. To explore this, BALB/c mice were injected with 4T1.2 triple negative murine tumor cells in the tibia. This typically causes tumor progression and osteolysis in 1–2 weeks. Samples were collected prior to tumor injection and from days 2–19. Samples were analyzed by headspace solid phase microextraction coupled to gas chromatography–mass spectrometry. Univariate analysis identified VOCs that were biomarkers for breast cancer; some of these varied significantly over time and others did not. Principal component analysis was used to distinguish Cancer (all Weeks) from Control and Cancer Week 1 from Cancer Week 3 with over 90% accuracy. Forward feature selection and linear discriminant analysis identified a unique panel that could identify tumor presence with 94% accuracy and distinguish progression (Cancer Week 1 from Cancer Week 3) with 97% accuracy. Principal component regression analysis also demonstrated that a VOC panel could predict number of days since tumor injection (R2 = 0.71 and adjusted R2 = 0.63). VOC biomarkers identified by these analyses were associated with metabolic pathways relevant to breast cancer.

scholarly journals Influence of age and gender on the profile of exhaled volatile organic compounds analyzed by an electronic nose

2016 ◽  
Vol 42 (2) ◽  
pp. 143-145 ◽  
Author(s):  
Silvano Dragonieri ◽  
Vitaliano Nicola Quaranta ◽  
Pierluigi Carratu ◽  
Teresa Ranieri ◽  
Onofrio Resta
Keyword(s):  
Volatile Organic Compounds ◽  
Organic Compounds ◽  
Electronic Nose ◽  
Principal Component ◽  
Exhaled Breath ◽  
Age And Gender ◽  
Volatile Organic ◽  
Older Subjects ◽  
Never Smokers ◽  
And Gender

We aimed to investigate the effects of age and gender on the profile of exhaled volatile organic compounds. We evaluated 68 healthy adult never-smokers, comparing them by age and by gender. Exhaled breath samples were analyzed by an electronic nose (e-nose), resulting in "breathprints". Principal component analysis and canonical discriminant analysis showed that older subjects (≥ 50 years of age) could not be distinguished from younger subjects on the basis of their breathprints, as well as that the breathprints of males could not distinguished from those of females (cross-validated accuracy, 60.3% and 57.4%, respectively).Therefore, age and gender do not seem to affect the overall profile of exhaled volatile organic compounds measured by an e-nose.

scholarly journals Effect of Spices on the Formation of VOCs in Roasted Mutton Based on GC-MS and Principal Component Analysis

2019 ◽  
Vol 2019 ◽  
pp. 1-11
Author(s):  
Jiapei Xi ◽  
Ping Zhan ◽  
Honglei Tian ◽  
Peng Wang
Keyword(s):  
Principal Component Analysis ◽  
Volatile Organic Compounds ◽  
Organic Compounds ◽  
Principal Component ◽  
Component Analysis ◽  
Volatile Components ◽  
Volatile Profile ◽  
Asian Countries ◽  
Volatile Organic ◽  
Chinese Prickly Ash

Peppertree prickly ash, Amomum tsao-ko, cumin, and ginger have long been used in Asian countries to modify the flavor and to partially neutralize any unpleasant odors present in roast lamb. The purpose of this study was to evaluate the change in the amount of volatile components present in roast lamb compared to meat added with peppertree prickly ash, Amomum tsao-ko, cumin, and ginger. Principal component analysis was carried out on the 27 initially selected from 88 volatile substances, and 15 substances with a projection of more than 0.25 in the load matrix were used as indicators to study the different contents in roasted mutton and lamb prepared by adding peppertree prickly ash, Amomum tsao-ko, cumin, and ginger. The types of VOCs (volatile organic compounds) detected in roast meat without adding spices were the least. Roast meat with the addition of cumin leads to the strongest content of aldehydes, followed by the addition of Amomum tsao-ko. Additionally, roast meat with the addition of Chinese prickly ash leads to the strongest content of terpenes, followed by the addition of ginger. Moreover, with the addition of spices, the content of volatiles responsible for the presence of a mutton odor (such as hexanal, heptanal, pentanal, (z)-4-decenal, benzaldehyde, p-propyl-anisole, and dimethyl ether) was not significantly decreased, and in fact some volatiles increased in amount such as pentanal, hexanal, octanal, and (z)-4-decenal. In conclusion, the effect of addition of spices on the volatile profile of roasted mutton and lamb can be attributed to the generation of flavor volatiles mainly derived from raw spices’ hot action, with few additional volatiles formed during boiling.

scholarly journals Stability and Selective Vapor Sensing of Structurally Colored Lepidopteran Wings Under Humid Conditions

Sensors ◽  
2020 ◽  
Vol 20 (11) ◽  
pp. 3258
Author(s):  
Gábor Piszter ◽  
Krisztián Kertész ◽  
Zsolt Bálint ◽  
László Péter Biró
Keyword(s):  
Water Vapor ◽  
Volatile Organic Compounds ◽  
Organic Compounds ◽  
Color Change ◽  
Response Times ◽  
Principal Component ◽  
Time Dependent ◽  
Dependent Manner ◽  
Vapor Sensing ◽  
Volatile Organic

Biological photonic nanoarchitectures are capable of rapidly and chemically selectively sensing volatile organic compounds due to changing color when exposed to such vapors. Here, stability and the vapor sensing properties of butterfly and moth wings were investigated by optical spectroscopy in the presence of water vapor. It was shown that repeated 30 s vapor exposures over 50 min did not change the resulting optical response signal in a time-dependent manner, and after 5-min exposures the sensor preserved its initial properties. Time-dependent response signals were shown to be species-specific, and by using five test substances they were also shown to be substance-specific. The latter was also evaluated using principal component analysis, which showed that the time-dependent optical responses can be used for real-time analysis of the vapors. It was demonstrated that the capability to detect volatile organic compounds was preserved in the presence of water vapor: high-intensity color change signals with short response times were measured in 25% relative humidity, similar to the one-component case; therefore, our results can contribute to the development of biological photonic nanoarchitecture-based vapor detectors for real-world applications, like living and working environments.

scholarly journals Selective Detection of Target Volatile Organic Compounds in Contaminated Air Using Sensor Array with Machine Learning: Aging Notes and Mold Smells in Simulated Automobile Interior Contaminant Gases

Sensors ◽  
2020 ◽  
Vol 20 (9) ◽  
pp. 2687
Author(s):  
Toshio Itoh ◽  
Yutaro Koyama ◽  
Woosuck Shin ◽  
Takafumi Akamatsu ◽  
Akihiro Tsuruta ◽  
...  
Keyword(s):  
Machine Learning ◽  
Random Forest ◽  
Volatile Organic Compounds ◽  
Organic Compounds ◽  
Sensor Array ◽  
Selective Detection ◽  
K Nearest Neighbor ◽  
Linear Discriminant ◽  
Age Related ◽  
Volatile Organic

We investigated the selective detection of target volatile organic compounds (VOCs) which are age-related body odors (namely, 2-nonenal, pelargonic acid, and diacetyl) and a fungal odor (namely, acetic acid) in the presence of interference VOCs from car interiors (namely, n-decane, and butyl acetate). We used eight semiconductive gas sensors as a sensor array; analyzing their signals using machine learning; principal-component analysis (PCA), and linear-discriminant analysis (LDA) as dimensionality-reduction methods; k-nearest-neighbor (kNN) classification to evaluate the accuracy of target-gas determination; and random forest and ReliefF feature selections to choose appropriate sensors from our sensor array. PCA and LDA scores from the sensor responses to each target gas with contaminant gases were generally within the area of each target gas; hence; discrimination between each target gas was nearly achieved. Random forest and ReliefF efficiently reduced the required number of sensors, and kNN verified the quality of target-gas discrimination by each sensor set.

scholarly journals Determination of Volatile Organic Compounds in Selected Strains of Cyanobacteria

2015 ◽  
Vol 2015 ◽  
pp. 1-6 ◽  
Author(s):  
Ivan Milovanović ◽  
Aleksandra Mišan ◽  
Jelica Simeunović ◽  
Dajana Kovač ◽  
Dubravka Jambrec ◽  
...  
Keyword(s):  
Volatile Organic Compounds ◽  
Volatile Compounds ◽  
Organic Compounds ◽  
Principal Component ◽  
Hierarchical Cluster ◽  
Growth Conditions ◽  
Multivariate Techniques ◽  
Microalgal Biomass ◽  
Medium Chain Length ◽  
Volatile Organic

Microalgal biomass can be used in creating various functional food and feed products, but certain species of microalgae and cyanobacteria are known to produce various compounds causing off-flavour. In this work, we investigated selected cyanobacterial strains ofSpirulina,Anabaena, andNostocgenera originating from Serbia, with the aim of determining the chemical profile of volatile organic compounds produced by these organisms. Additionally, the influence of nitrogen level during growth on the production of volatile compounds was investigated forNostocandAnabaenastrains. In addition, multivariate techniques, namely, principal component analysis (PCA) and hierarchical cluster analysis (HCA), were used for making distinction among different microalgal strains. The results show that the main volatile compounds in these species are medium chain length alkanes, but other odorous compounds such as 2-methylisoborneol (0.51–4.48%), 2-pentylfuran (0.72–8.98%),β-cyclocitral (0.00–1.17%), andβ-ionone (1.15–2.72%) were also detected in the samples. Addition of nitrogen to growth medium was shown to negatively affect the production of 2-methylisoborneol, while geosmin was not detected in any of the analyzed samples, which indicates that the manipulation of growth conditions may be useful in reducing levels of some unwanted odor-causing components.

Sign in / Sign up

Export Citation Format

Share Document