Development of Electronic Nose with Low-Cost Dynamic Headspace for Classifying Vegetable Oils and Animal Fats

A portable electronic nose (e-nose) using low-cost dynamic headspace and commercially metal oxide gas sensors has been developed. This paper reports evaluation on the performance of the e-nose to classify vegetable oils (sunflower and grape seed oils) and animal fats (mutton, chicken and pig fats). The e-nose consists of a dynamic headspace sampling, a gas sensor array and a real-time data acquisition system based on ATMega-16 microcontroller. The dynamic headspace can divided into two chambers, i.e. sample and gas sensor array room. It is also equipped with three small fans for adjusting sensing and purging processes. Principal component analysis (PCA) was used for measurement data analysis after all features being extracted. The first two principal components were kept because they accounted for 91.1% of the variance in the data set (first and second principals accounted for 72.9, 18.2% of the variance, respectively). This results show that the e-nose can distinguish vegetable oils and animal fats. This work demonstrates for the future that the e-nose with low-cost dynamic headspace technique may be applied to the identification of oils and fats in halal authentication.

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B5.4 - Gas Sensor Array for Low-cost Gas Chromatography in Food Industry Processes

10.5162/sensor09/v1/b5.4 ◽

2009 ◽

Author(s):

Marie-Luise Bauersfeld ◽

Carolin Peter ◽

Juergen Woellenstein ◽

Mark Buecking ◽

Joerg Bruckert ◽

...

Keyword(s):

Gas Chromatography ◽

Gas Sensor ◽

Food Industry ◽

Sensor Array ◽

Low Cost ◽

Gas Sensor Array

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The Effectiveness of Varroa destructor Infestation Classification Using an E-Nose Depending on the Time of Day

Sensors ◽

10.3390/s20092532 ◽

2020 ◽

Vol 20 (9) ◽

pp. 2532

Author(s):

Andrzej Szczurek ◽

Monika Maciejewska ◽

Żaneta Zajiczek ◽

Beata Bąk ◽

Jakub Wilk ◽

...

Keyword(s):

Gas Sensor ◽

Varroa Destructor ◽

Sensor Array ◽

Measurement Data ◽

Time Of Day ◽

Semiconductor Gas Sensor ◽

Bee Colony ◽

Gas Sensor Array ◽

Array Measurement ◽

Method Of Assessment

Honey bees are subject to a number of stressors. In recent years, there has been a worldwide decline in the population of these insects. Losses raise a serious concern, because bees have an indispensable role in the food supply of humankind. This work is focused on the method of assessment of honey bee colony infestation by Varroa destructor. The approach allows to detect several categories of infestation: “Low”, “Medium” and “High”. The method of detection consists of two components: (1) the measurements of beehive air using a gas sensor array and (2) classification, which is based on the measurement data. In this work, we indicate the sensitivity of the bee colony infestation assessment to the timing of measurement data collection. It was observed that the semiconductor gas sensor responses to the atmosphere of a defined beehive, collected during 24 h, displayed temporal variation. We demonstrated that the success rate of the bee colony infestation assessment also altered depending on the time of day when the gas sensor array measurement was done. Moreover, it was found that different times of day were the most favorable to detect the particular infestation category. This result could indicate that the representation of the disease in the beehive air may be confounded during the day, due to some interferences. More studies are needed to explain this fact and determine the best measurement periods. The problem addressed in this work is very important for scheduling the beekeeping practices aimed at Varroa destructor infestation assessment, using the proposed method.

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Application of Electronic Nose for Evaluation of Wastewater Treatment Process Effects at Full-Scale WWTP

Processes ◽

10.3390/pr7050251 ◽

2019 ◽

Vol 7 (5) ◽

pp. 251 ◽

Cited By ~ 8

Author(s):

Grzegorz Łagód ◽

Sylwia M. Duda ◽

Dariusz Majerek ◽

Adriana Szutt ◽

Agnieszka Dołhańczuk-Śródka

Keyword(s):

Wastewater Treatment ◽

Gas Sensor ◽

Electronic Nose ◽

Sensor Array ◽

Treatment Plant ◽

Full Scale ◽

Oxide Semiconductor ◽

Pollution Level ◽

Gas Sensor Array

This paper presents the results of studies aiming at the assessment and classification of wastewater using an electronic nose. During the experiment, an attempt was made to classify the medium based on an analysis of signals from a gas sensor array, the intensity of which depended on the levels of volatile compounds in the headspace gas mixture above the wastewater table. The research involved samples collected from the mechanical and biological treatment devices of a full-scale wastewater treatment plant (WWTP), as well as wastewater analysis. The measurements were carried out with a metal-oxide-semiconductor (MOS) gas sensor array, when coupled with a computing unit (e.g., a computer with suitable software for the analysis of signals and their interpretation), it formed an e-nose—that is, an imitation of the mammalian olfactory sense. While conducting the research it was observed that the intensity of signals sent by sensors changed with drops in the level of wastewater pollution; thus, the samples could be classified in terms of their similarity and the analyzed gas-fingerprint could be related to the pollution level expressed by physical and biochemical indicators. Principal component analysis was employed for dimensionality reduction, and cluster analysis for grouping observation purposes. Supervised learning techniques confirmed that the obtained data were applicable for the classification of wastewater at different stages of the purification process.

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