Comparison of different types of electronic nose instruments for evaluation of odour nuisance from landfill

2014 ◽  
Author(s):  
Jacek Gębicki ◽  
Tomasz Dymerski ◽  
Jacek Namieśnik
Keyword(s):  
Electronic Nose ◽  
Different Types

In Vitro Discrimination of Tumor Cell Lines with an Electronic Nose

2007 ◽  
Vol 137 (2) ◽  
pp. 269-273 ◽  
Author(s):  
Kristin B. Gendron ◽  
Neil G. Hockstein ◽  
Erica R. Thaler ◽  
Anil Vachani ◽  
C. William Hanson
Keyword(s):  
Tumor Cell ◽  
Cell Lines ◽  
Electronic Nose ◽  
Normal Fibroblast ◽  
Tumor Cell Lines ◽  
Upper Aerodigestive Tract ◽  
Mahalanobis Distances ◽  
Different Types ◽  
Components Analysis

OBJECTIVE: The electronic nose is a sensor of volatile molecules that is useful in the analysis of expired gases. Our hypothesis is that the electronic nose can distinguish between different types of upper aerodigestive tract tumor cells in vitro. STUDY DESIGN: Cells from both tumor and normal cell lines were suspended in saline, and a polymer composite electronic nose was used to evaluate the headspace gases. The data were subjected to principal components analysis, and Mahalanobis distances were calculated to demonstrate the ability of the electronic nose to distinguish among samples. RESULTS: The tumor cell lines, including adenocarcinoma, squamous cell carcinoma, and mesothelioma, were distinct from each other, and from the normal fibroblast and smooth muscle cells as seen on canonical discrimination plots. CONCLUSION: The electronic nose can distinguish between tumor cell lines in vitro and has the potential to be a useful screening test for cancer.

scholarly journals Discrimination of Different Types Damage of Tomato Seedling by Electronic Nose

2017 ◽  
Vol 11 ◽  
pp. 01019 ◽  
Author(s):  
Shao-Ming Cheng ◽  
Jun Wang ◽  
Yong-Wei Wang ◽  
Zhen-Bo Wei
Keyword(s):  
Electronic Nose ◽  
Tomato Seedling ◽  
Different Types

scholarly journals Electronic Nose, Tongue and Eye: Their Usefulness for the Food Industry

Revista Vitae ◽  
2020 ◽  
Vol 27 (3) ◽  
Author(s):  
Roberto Ordoñez-Araque ◽  
Johnny Rodríguez-Villacres ◽  
Julio Urresto-Villegas
Keyword(s):  
Mechanism Of Action ◽  
Electronic Nose ◽  
Sensory Analysis ◽  
Food Industry ◽  
Sensory Characteristics ◽  
Inclusion Criteria ◽  
Food Industries ◽  
Different Types ◽  
The Future ◽  
Main Components

Background: The electronic nose, tongue, and eye are futuristic technologies that have been used for many years; they have been gaining market in different types of industries and can increasingly be found in the food area; their function is to determine sensory characteristics (smell, aroma, and flavor) and objective visuals, without the subjectivity that can be represented by sensory analysis by people (the study that can complement the analysis of machines, without being exclusive). Objectives: Find the main generalities of these mechanisms, their sensors, software, mechanism of action, and applications within the food industry. Methods: A search was carried out in the main databases of indexed articles, with terms that allowed collecting the necessary information, and 89 articles were used that met different inclusion criteria. Results: The main outcomes were to understand the operation of each of these technologies, what their main components are, and how they can be linked in the beer, wine, oil, fruit, vegetable, dairy, etc. industry to determine their quality, safety, and fraud. Conclusions: The use of electronic nose, tongue, and eye is found in more food industries every day. Its technology continues to evolve; the future of sensory analysis will undoubtedly apply these mechanisms due to the reliability, speed, and reproducibility of the results.

scholarly journals Identification of the raw and processed Crataegi Fructus based on the electronic nose coupled with chemometric methods

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Chenghao Fei ◽  
Chenchen Ren ◽  
Yulin Wang ◽  
Lin Li ◽  
Weidong Li ◽  
...  
Keyword(s):  
Electronic Nose ◽  
Sensor Array ◽  
Prediction Models ◽  
Back Propagation ◽  
Back Propagation Neural Network ◽  
Stepwise Discriminant Analysis ◽  
Accuracy Rate ◽  
Different Types ◽  
Chemical Content ◽  
Electronic Nose System

AbstractCrataegi Fructus (CF) is widely used as a medicinal and edible material around the world. Currently, different types of processed CF products are commonly found in the market. Quality evaluation of them mainly relies on chemical content determination, which is time and money consuming. To rapidly and nondestructively discriminate different types of processed CF products, an electronic nose coupled with chemometrics was developed. The odour detection method of CF was first established by single-factor investigation. Then, the sensor array was optimised by a stepwise discriminant analysis (SDA) and analysis of variance (ANOVA). Based on the best-optimised sensor array, the digital and mode standard were established, realizing the odour quality control of samples. Meanwhile, mathematical prediction models including the discriminant formula and back-propagation neural network (BPNN) model exhibited good evaluation with a high accuracy rate. These results suggest that the developed electronic nose system could be an alternative way for evaluating the odour of different types of processed CF products.

Comparative flavor analysis of four kinds of sweet fermented grains by sensory analysis combined with GC-MS

2022 ◽  
Vol 0 (0) ◽  
Author(s):  
Lei Wang ◽  
Ke Yang ◽  
Liu Liu
Keyword(s):  
Physicochemical Properties ◽  
Volatile Compounds ◽  
Electronic Nose ◽  
Sensory Analysis ◽  
Raw Materials ◽  
Electronic Tongue ◽  
Volatile Components ◽  
Red Rice ◽  
Different Types ◽  
Fermented Grains

Abstract Four types of cereals (glutinous rice, purple rice, red rice, yellow millet) were selected to produce sweet fermented grains. Flavor profiles of sweet fermented grains are comparatively studied to distinguish various flavor types by using GC-MS, electronic nose (E-nose), and sensory analysis, and the amino acid composition and physicochemical properties of sweet fermented grains were analyzed. The results showed that the volatile compounds of sweet fermented grains were significantly different. Esters and alcohols were the major volatile compounds in sweet fermented grains. The electronic nose, electronic tongue and sensory analysis jointly verified that the volatile components of sweet fermented grains had differences between them. The sweet fermented grains could be classified based on differences in volatile compounds. In the amino acids analysis, Glu, Pro, Asp and Leu were the most abundant. The difference in physicochemical properties is more helpful to distinguish different types of sweet fermented grains. Correlation analysis between antioxidant active substances and color value showed a positive correlation between with a* value, and a negative correlation with L*, b* value. Our results suggested that there were differences in the flavor characteristics of sweet fermented grains fermented from different types of cereals. The results of the study will provide valuable information for the selection of raw materials for sweet fermented grains.

scholarly journals Classification of Agarwood Oil Using an Electronic Nose

Sensors ◽  
2010 ◽  
Vol 10 (5) ◽  
pp. 4675-4685 ◽  
Author(s):  
Wahyu Hidayat ◽  
Ali Yeon Md. Shakaff ◽  
Mohd Noor Ahmad ◽  
Abdul Hamid Adom
Keyword(s):  
Neural Network ◽  
Electronic Nose ◽  
Principal Component ◽  
Hierarchical Cluster ◽  
Scatter Plot ◽  
Different Types ◽  
Artificial Neural Network Ann ◽  
Distinct Separation ◽  
Agarwood Oil

Presently, the quality assurance of agarwood oil is performed by sensory panels which has significant drawbacks in terms of objectivity and repeatability. In this paper, it is shown how an electronic nose (e-nose) may be successfully utilised for the classification of agarwood oil. Hierarchical Cluster Analysis (HCA) and Principal Component Analysis (PCA), were used to classify different types of oil. The HCA produced a dendrogram showing the separation of e-nose data into three different groups of oils. The PCA scatter plot revealed a distinct separation between the three groups. An Artificial Neural Network (ANN) was used for a better prediction of unknown samples.

scholarly journals Electronic-Nose System for Classification of Fruits and Freshness Measurement using K-NN Algorithm

2019 ◽  
Vol 8 (6S4) ◽  
pp. 641-644 ◽  
Keyword(s):  
Electronic Nose ◽  
Sensor Array ◽  
Fruit Juice ◽  
Ph Value ◽  
Manufacturing Industries ◽  
Sensor Data ◽  
Food Manufacturing ◽  
Different Types ◽  
Electronic Nose System

The main objective of this work is to design electronic nose system (E-Nose) which detects the odour and freshness of different fruits such as mango, pineapple, orange which are mainly used in food manufacturing industries. E-Nose system consists of sensor array of two with each sensor respond to different types of odours. These sensor data is analyzed with the K-nearest neighbour algorithm (K-NN Algorithm) using MATLAB for identification of different fruits. Freshness of fruit juice is determined by the measurement of pH value of juice by using pH electrode

scholarly journals Electronic nose to differentiate between several drying techniques for Origanum syriacum leaves

Food Research ◽  
2021 ◽  
Vol 5 (6) ◽  
pp. 260-265
Author(s):  
S. Mudalal ◽  
N. Abu-Khalaf
Keyword(s):  
Electronic Nose ◽  
Sensory Analysis ◽  
Multivariate Data Analysis ◽  
Principal Component ◽  
Colour Index ◽  
Functional Ingredients ◽  
Freeze Dried ◽  
Drying Techniques ◽  
Different Types ◽  
Drying Technology

Dried oregano (Origanum syriacum L.) is a common product in the Mediterranean diet and it has wide culinary applications. The quality and functional ingredients profile of oregano is highly affected by drying technology. This study was aimed to discriminate different quality traits of air, solar, and freeze-dried oregano by employing electronic nose (e-nose), chromameter, and sensory analysis. E-nose signals were analysed by using multivariate data analysis (MVDA). Our findings showed that the e-nose signal exhibited different clusters for all groups by using principal component analysis (PCA). Moreover, there were clear differences in the colour index (L*a*b*) between groups. Freeze-dried oregano exhibited significantly lower L*-values than air and solar-dried oregano. Sensory analysis showed that there were clear differences between solar and freeze-dried oregano. In this context, f-dried thyme had significantly lower values of colour acceptance (4.80 vs. 7.57, p<0.05), degree of freshness (5.57 vs. 7.14, p<0.05), taste acceptance (5.46 vs. 6.75, p<0.05), and overall acceptance (5.75 vs. 7.19, p<0.05) than solar-dried thyme, respectively. In conclusion, e-nose and chromameter were effective tools to discriminate between different types of dried oregano

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