scholarly journals Detection of Volatile Organic Compounds (VOCs) in Livestock Houses Based on Electronic Nose

2021 ◽  
Vol 11 (5) ◽  
pp. 2337
Author(s):  
Xiaohui Weng ◽  
Cheng Kong ◽  
Hongyang Jin ◽  
Dongxue Chen ◽  
Chunguang Li ◽  
...  
Keyword(s):  
Volatile Organic Compounds ◽  
Organic Compounds ◽  
Electronic Nose ◽  
Large Scale ◽  
Gas Chromatography Mass Spectrometry ◽  
Support Vector ◽  
Classification Rate ◽  
Linear Discriminant ◽  
Volatile Organic ◽  
Livestock Farms

The composition of volatile organic compounds (VOCs) in large-scale livestock farms is complex, which seriously affects the health of livestock and is difficult to evaluate. In order to quickly analyze the pollution degree of VOCs in livestock farms, electronic nose technology was used in this study to detect and analyze the gases in pig and chicken houses, respectively. Firstly, the gas chromatography–mass spectrometry (GC–MS) and electronic nose were used to analyze the VOCs in the pig and chicken houses at different time and locations. The types and relative contents of VOCs were obtained from different livestock farms by GC–MS analysis. The sensor array response of the electronic nose showed similar results. In addition, linear discriminant analysis (LDA), K nearest neighbor (KNN) and support vector machine (SVM) analyses were performed on the electrical signal that was generated by the sensors of electronic nose, respectively. Finally, the classification rate of different odor sources in livestock farms was the highest (>85%), which indicates that SVM is a more effective method suitable for volatile gases recognition in livestock farms. The results have shown that the developed electronic nose sensor is a promising and feasible instrument for characterizing volatile odors in livestock farms.

Evaluation of Semanotus bifasciatus (Motschulsky) Infestation in Platycladus orientalis Plants Using E-Nose and GC-MS

2020 ◽  
Vol 63 (6) ◽  
pp. 1629-1637
Author(s):  
Zhenhe Wang ◽  
Yubing Sun ◽  
Jun Wang ◽  
Yongwei Wang
Keyword(s):  
Neural Network ◽  
Feature Extraction ◽  
Volatile Organic Compounds ◽  
Organic Compounds ◽  
Electronic Nose ◽  
Support Vector ◽  
List Type ◽  
Linear Discriminant ◽  
Platycladus Orientalis ◽  
Volatile Organic

HighlightsE-nose was employed for evaluation of Semanotus bifasciatus infestation based on four time-domain features.Plant VOCs were analyzed by GC-MS, and the results proved the feasibility of E-nose detection.PNN, BPNN, SVM, and PLSR were introduced to classify and predict Semanotus bifasciatus infestation numbers.Abstract. Trunk-boring insects such as Semanotus bifasciatus (Motschulsky) are difficult to detect because the larvae are hidden inside the trunks. In this study, the variation of volatile organic compounds (VOCs) in Platycladus orientalis after S. bifasciatus infestation was evaluated using an electronic nose (E-nose). VOCs from sample plants were observed with gas chromatography - mass spectrometry (GC-MS), and the results indicated that uninfected and infected groups differed both qualitatively and quantitatively, which proves the feasibility of E-nose evaluation. To extract features of the E-nose response signals, four feature extraction methods were applied, and their performances were compared based on linear discriminant analysis (LDA). Three classification models, including back-propagation neural network (BPNN), support vector machine (SVM), and probabilistic neural network (PNN), were established to identify the severity of infestation based on the optimal feature extraction method (75th second value). The classification results of BPNN, PNN, and SVM based on the calibration set were 96.43%, 91.07%, and 100%, respectively, and the results based on the validation set were 91.67%, 91.67%, and 100%, respectively. In addition, partial least squares regression (PLSR) and BPNN were used to predict the larvae density and achieved highly reliable results. It can be concluded that combining E-nose with GC-MS is a potential technique for evaluating trunk-borer infestation and can be used for pest management. Keywords: Electronic nose, Feature extraction, Pest evaluation, Semanotus bifasciatus, Volatile organic compounds.

scholarly journals Flexible Impedimetric Electronic Nose for High-Accurate Determination of Individual Volatile Organic Compounds by Tuning the Graphene Sensitive Properties

Chemosensors ◽  
2021 ◽  
Vol 9 (12) ◽  
pp. 360
Author(s):  
Tianqi Lu ◽  
Ammar Al-Hamry ◽  
José Mauricio Rosolen ◽  
Zheng Hu ◽  
Junfeng Hao ◽  
...  
Keyword(s):  
Volatile Organic Compounds ◽  
Organic Compounds ◽  
Electronic Nose ◽  
Accurate Determination ◽  
Identification Accuracy ◽  
Structural Defects ◽  
Support Vector ◽  
Volatile Organic ◽  
Variable Sensitivity ◽  
Relative Change

We investigated functionalized graphene materials to create highly sensitive sensors for volatile organic compounds (VOCs) such as formaldehyde, methanol, ethanol, acetone, and isopropanol. First, we prepared VOC-sensitive films consisting of mechanically exfoliated graphene (eG) and chemical graphene oxide (GO), which have different concentrations of structural defects. We deposited the films on silver interdigitated electrodes on Kapton substrate and submitted them to thermal treatment. Next, we measured the sensitive properties of the resulting sensors towards specific VOCs by impedance spectroscopy. We obtained the eG- and GO-based electronic nose composed of two eG films- and four GO film-based sensors with variable sensitivity to individual VOCs. The smallest relative change in impedance was 5% for the sensor based on eG film annealed at 180 °C toward 10 ppm formaldehyde, whereas the highest relative change was 257% for the sensor based on two-layers deposited GO film annealed at 200 °C toward 80 ppm ethanol. At 10 ppm VOC, the GO film-based sensors were sensitive enough to distinguish between individual VOCs, which implied excellent selectivity, as confirmed by Principle Component Analysis (PCA). According to a PCA-Support Vector Machine-based signal processing method, the electronic nose provided identification accuracy of 100% for individual VOCs. The proposed electronic nose can be used to detect multiple VOCs selectively because each sensor is sensitive to VOCs and has significant cross-selectivity to others.

scholarly journals Determination of volatile organic compounds in Slovak bryndza cheese by the electronic nose and the headspace solid-phase microextraction gas chromatography-mass spectrometry

10.5219/1300 ◽  
2020 ◽  
Vol 14 ◽  
pp. 767-773
Author(s):  
Jana Štefániková ◽  
Július Árvay ◽  
Michal Miškeje ◽  
Miroslava Kačániová
Keyword(s):  
Mass Spectrometry ◽  
Gas Chromatography ◽  
Volatile Organic Compounds ◽  
Organic Compounds ◽  
Electronic Nose ◽  
Solid Phase Microextraction ◽  
Solid Phase ◽  
Gas Chromatography Mass Spectrometry ◽  
Chromatography Mass Spectrometry ◽  
Volatile Organic

The aim of the present study was to describe volatile organic compounds of the traditional Slovak bryndza cheese determined by using an electronic nose (e-nose) and a gas chromatography mass spectrometry (GCMS) with head-space solid phase microextraction (HS-SPME). For the first time, e-nose based on the gas chromatography principle with a flame ionization detector was described to identify and quantify aroma active compounds of bryndza cheese from Slovakia. The e-nose detects aroma compounds of very small concentrations in real-time of a few minutes and identifies them by comparing Kovats´ retention indices with the NIST library. Bryndza cheese produced from unpasteurized ewe´s milk and from a mixture of raw ewe´s and pasteurized cow´s types of milk were collected from 2 different Slovak farms beginning in May through to September 2019. The flavour and aroma of bryndza cheese are apparently composed of compounds contained in milk and the products of fermentation of the substrate by bacteria and fungi. Regarding volatile organic compounds, 25 compounds were detected and identified by an electronic nose with a discriminant >0.900 with ethyl acetate, isopentyl acetate, 2-butanone, acetic acid, butanoic acid, and butane-2,3-dione confirmed by gas chromatography. We confirm the suitability of the electronic nose to be used for monitoring of bryndza cheese quality.

scholarly journals Non-Invasive Diagnosis of Diabetes by Volatile Organic Compounds in Urine Using FAIMS and Fox4000 Electronic Nose

Biosensors ◽  
2018 ◽  
Vol 8 (4) ◽  
pp. 121 ◽  
Author(s):  
Siavash Esfahani ◽  
Alfian Wicaksono ◽  
Ella Mozdiak ◽  
Ramesh Arasaradnam ◽  
James Covington
Keyword(s):  
Volatile Organic Compounds ◽  
Organic Compounds ◽  
Electronic Nose ◽  
Area Under The Curve ◽  
Urine Samples ◽  
Support Vector ◽  
Sparse Logistic Regression ◽  
Non Invasive ◽  
Volatile Organic ◽  
Sample Age

The electronic nose (eNose) is an instrument designed to mimic the human olfactory system. Usage of eNose in medical applications is more popular than ever, due to its low costs and non-invasive nature. The eNose sniffs the gases and vapours that emanate from human waste (urine, breath, and stool) for the diagnosis of variety of diseases. Diabetes mellitus type 2 (DM2) affects 8.3% of adults in the world, with 43% being underdiagnosed, resulting in 4.9 million deaths per year. In this study, we investigated the potential of urinary volatile organic compounds (VOCs) as novel non-invasive diagnostic biomarker for diabetes. In addition, we investigated the influence of sample age on the diagnostic accuracy of urinary VOCs. We analysed 140 urine samples (73 DM2, 67 healthy) with Field-Asymmetric Ion Mobility Spectrometry (FAIMS); a type of eNose; and FOX 4000 (AlphaM.O.S, Toulouse, France). Urine samples were collected at UHCW NHS Trust clinics over 4 years and stored at −80 °C within two hours of collection. Four different classifiers were used for classification, specifically Sparse Logistic Regression, Random Forest, Gaussian Process, and Support Vector on both FAIMS and FOX4000. Both eNoses showed their capability of diagnosing DM2 from controls and the effect of sample age on the discrimination. FAIMS samples were analysed for all samples aged 0–4 years (AUC: 88%, sensitivity: 87%, specificity: 82%) and then sub group samples aged less than a year (AUC (Area Under the Curve): 94%, Sensitivity: 92%, specificity: 100%). FOX4000 samples were analysed for all samples aged 0–4 years (AUC: 85%, sensitivity: 77%, specificity: 85%) and a sub group samples aged less than 18 months: (AUC: 94%, sensitivity: 90%, specificity: 89%). We demonstrated that FAIMS and FOX 4000 eNoses can discriminate DM2 from controls using urinary VOCs. In addition, we showed that urine sample age affects discriminative accuracy.

Discriminative detection of volatile organic compounds using an electronic nose based on TiO2 hybrid nanostructures

2021 ◽  
pp. 130124
Author(s):  
Patrick P. Conti ◽  
Rafaela S. Andre ◽  
Luiza A. Mercante ◽  
Lucas Fugikawa-Santos ◽  
Daniel S. Correa
Keyword(s):  
Volatile Organic Compounds ◽  
Organic Compounds ◽  
Electronic Nose ◽  
Hybrid Nanostructures ◽  
Volatile Organic

scholarly journals Species and characteristics of volatile organic compounds emitted from an auto-repair painting workshop

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
M. Y. Song ◽  
H. Chun
Keyword(s):  
Volatile Organic Compounds ◽  
Organic Compounds ◽  
Large Scale ◽  
Butyl Acetate ◽  
Small Scale ◽  
Indoor Environments ◽  
Voc Emissions ◽  
Volatile Organic ◽  
Before And After ◽  
Adsorption Systems

AbstractVolatile organic compounds (VOCs) are secondary pollutant precursors having adverse impacts on the environment and human health. Although VOC emissions, their sources, and impacts have been investigated, the focus has been on large-scale industrial sources or indoor environments; studies on relatively small-scale enterprises (e.g., auto-repair workshops) are lacking. Here, we performed field VOC measurements for an auto-repair painting facility in Korea and analyzed the characteristics of VOCs emitted from the main painting workshop (top coat). The total VOC concentration was 5069–8058 ppb, and 24–35 species were detected. The VOCs were mainly identified as butyl acetate, toluene, ethylbenzene, and xylene compounds. VOC characteristics differed depending on the paint type. Butyl acetate had the highest concentration in both water- and oil-based paints; however, its concentration and proportion were higher in the former (3256 ppb, 65.5%) than in the latter (2449 ppb, 31.1%). Comparing VOC concentration before and after passing through adsorption systems, concentrations of most VOCs were lower at the outlets than the inlets of the adsorption systems, but were found to be high at the outlets in some workshops. These results provide a theoretical basis for developing effective VOC control systems and managing VOC emissions from auto-repair painting workshops.

scholarly journals Volatile metabolites of willows determining host discrimination by adult Plagiodera versicolora

2021 ◽  
Author(s):  
Jiahao Ling ◽  
Xiaoping Li ◽  
Guo Yang ◽  
Tongming Yin
Keyword(s):  
Volatile Organic Compounds ◽  
Organic Compounds ◽  
Insect Pests ◽  
Leaf Beetle ◽  
Gas Chromatography Mass Spectrometry ◽  
Host Discrimination ◽  
Plagiodera Versicolora ◽  
Volatile Metabolites ◽  
Hexenyl Acetate ◽  
Volatile Organic

AbstractPlagiodera versicolora Laicharting is a highly damaging leaf beetle foraging on willow leaves. In willow germplasm collections, observation has shown that Salix suchowensis Cheng was severely foraged by this leaf beetle while Salix triandra L. was damage free or only slightly damaged. Results of olfactometer bioassays show that the headspace volatiles from leaves of S. triandra significantly repelled adult beetles, suggesting that this species produces volatile repellents against P. versicolora. S. suchowensis had no effect on the beetles. Gas chromatography-mass spectrometry was carried out to profile the headspace volatile organic compounds and 23 compounds from leaves of the alternate species in significantly different concentrations were detected. The effects of 20 chemical analogs on host discrimination were examined. Olfactory response to these chemicals showed that o-cymene, a S. suchowensis specific constituent, significantly attracted adult P. versicolora. In contrast, cis-3-hexenyl acetate, a constituent concentrated more in S. triandra than in S. suchowensis, significantly repelled beetles. Mixing o-cymene and cis-3-hexenyl acetate in comparable concentrations as in the volatiles of S. suchowensis demonstrated that the latter could mask the attracting effect of the former, causing a neutral response by adult beetles to leaves of S. suchowensis against clean air. In addition, chemical analogs have the same effect as plants when resembling volatile organic compounds in real samples. Two volatile metabolites were detected triggering host discrimination by one of the most damaging insect pests to host and non-host willows. The two metabolites are of considerable potential for use as olfactory signs in managing the beetles.

scholarly journals Non-Invasive Method to Detect Infection with Mycobacterium tuberculosis Complex in Wild Boar by Measurement of Volatile Organic Compounds Obtained from Feces with an Electronic Nose System

Sensors ◽  
2021 ◽  
Vol 21 (2) ◽  
pp. 584
Author(s):  
Kelvin de Jesús Beleño-Sáenz ◽  
Juan Martín Cáceres-Tarazona ◽  
Pauline Nol ◽  
Aylen Lisset Jaimes-Mogollón ◽  
Oscar Eduardo Gualdrón-Guerrero ◽  
...  
Keyword(s):  
Volatile Organic Compounds ◽  
Wild Boar ◽  
Organic Compounds ◽  
Electronic Nose ◽  
Bovine Tuberculosis ◽  
Human Beings ◽  
Non Invasive ◽  
Testing Phase ◽  
Volatile Organic ◽  
Electronic Nose System

More effective methods to detect bovine tuberculosis, caused by Mycobacterium bovis, in wildlife, is of paramount importance for preventing disease spread to other wild animals, livestock, and human beings. In this study, we analyzed the volatile organic compounds emitted by fecal samples collected from free-ranging wild boar captured in Doñana National Park, Spain, with an electronic nose system based on organically-functionalized gold nanoparticles. The animals were separated by the age group for performing the analysis. Adult (>24 months) and sub-adult (12–24 months) animals were anesthetized before sample collection, whereas the juvenile (<12 months) animals were manually restrained while collecting the sample. Good accuracy was obtained for the adult and sub-adult classification models: 100% during the training phase and 88.9% during the testing phase for the adult animals, and 100% during both the training and testing phase for the sub-adult animals, respectively. The results obtained could be important for the further development of a non-invasive and less expensive detection method of bovine tuberculosis in wildlife populations.

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