Developments in Electronic Noses for Quality and Safety Control

Rayappan, John Bosco Balaguru; Kulandaisamy, Arockia Jayalatha; Ezhilan, Madeshwari; Srinivasan, P. Bala; Mani, Ganesh Kumar

doi:10.1002/9781119105916.ch3

Cited by 7 publications

(3 citation statements)

References 157 publications

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“…The major applications in food products for this type of sensors are quality control and food safety [ 22 , 23 ], authenticity control [ 24 ], and detection of contaminants [ 25 ]. This way, in the literature, there are several reports that devote their attention to the application of e-noses to fruits and vegetables in order to identify and select cultivars, to discriminate among different ripening stages, to predict the optimal harvest date, to monitor shelf life [ 26 ] or to manage the post-harvest processes and to evaluate the occurrence of defects [ 16 ].…”

Section: Related Workmentioning

confidence: 99%

Prediction of Fruity Aroma Intensity and Defect Presence in Virgin Olive Oil Using an Electronic Nose

Marchal

Sanmartin

Martínez

et al. 2021

Sensors

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The organoleptic profile of a Virgin Olive Oil is a key quality parameter that is currently obtained by human sensory panels. The development of an instrumental technique capable of providing information about this profile quickly and online is of great interest. This work employed a general purpose e-nose, in lab conditions, to predict the level of fruity aroma and the presence of defects in Virgin Olive Oils. The raw data provided by the e-nose were used to extract a set of features that fed a regressor to predict the level of fruity aroma and a classifier to detect the presence of defects. The results obtained were a mean validation error of 0.5 units for the prediction of fruity aroma using lasso regression; and 88% accuracy for the defect detection using logistic regression. Finally, the identification of two out of ten specific sensors of the e-nose that can provide successful results paves the way to the design of low-cost specific electronic noses for this application.

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Section: Related Workmentioning

confidence: 99%

Prediction of Fruity Aroma Intensity and Defect Presence in Virgin Olive Oil Using an Electronic Nose

Marchal

Sanmartin

Martínez

et al. 2021

Sensors

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“…Electronic noses are particularly useful for analyzing and detecting VOCs due to the cross-reactivity of e-nose multisensory arrays and sensitivity to a diversity of volatile compounds from a wide range of organic chemical classes [24,27]. These gas-sensing devices have a long history of effective use with many applications previously developed in numerous industries, including agriculture and forestry [27], food quality and safety [28][29][30][31], biomedical and forensic sciences [32,33], pharmaceutical and drug development [24], human health and disease diagnoses [34][35][36], and environmental protection [37]. In agriculture, electronic noses are useful in assessing quality controls for foods by virtue of electronic aroma detection (EAD) technologies that can rapidly and repeatedly detect, classify, and characterize complex VOC emissions from food products in a relatively short time.…”

Section: Introductionmentioning

confidence: 99%

Rapid Detection of Urea Fertilizer Effects on VOC Emissions from Cucumber Fruits Using a MOS E-Nose Sensor Array

et al. 2021

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The widespread use of nitrogen chemical fertilizers in modern agricultural practices has raised concerns over hazardous accumulations of nitrogen-based compounds in crop foods and in agricultural soils due to nitrogen overfertilization. Many vegetables accumulate and retain large amounts of nitrites and nitrates due to repeated nitrogen applications or excess use of nitrogen fertilizers. Consequently, the consumption of high-nitrate crop foods may cause health risks to humans. The effects of varying urea–nitrogen fertilizer application rates on VOC emissions from cucumber fruits were investigated using an experimental MOS electronic-nose (e-nose) device based on differences in sensor-array responses to volatile emissions from fruits, recorded following different urea fertilizer treatments. Urea fertilizer was applied to cucumber plants at treatment rates equivalent to 0, 100, 200, 300, and 400 kg/ha. Cucumber fruits were then harvested twice, 4 and 5 months after seed planting, and evaluated for VOC emissions using an e-nose technology to assess differences in smellprint signatures associated with different urea application rates. The electrical signals from the e-nose sensor array data outputs were subjected to four aroma classification methods, including: linear and quadratic discriminant analysis (LDA-QDA), support vector machines (SVM), and artificial neural networks (ANN). The results suggest that combining the MOS e-nose technology with QDA is a promising method for rapidly monitoring urea fertilizer application rates applied to cucumber plants based on changes in VOC emissions from cucumber fruits. This new monitoring tool could be useful in adjusting future urea fertilizer application rates to help prevent nitrogen overfertilization.

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“…It comprises of placing the microbial sample in a hermetically sealed vial after equilibrium between the matrix and the gaseous phase is established, the headspace is sampled (Peris and Escuder-Gilabert 2009). Therefore sampling techniques are designed to be stable and be able to withstand environmental effects (Rayappan et al 2017).…”

Section: Electronic Nose Sampling Systemsmentioning

confidence: 99%

Application of electronic nose as a non-invasive technique for odor fingerprinting and detection of bacterial foodborne pathogens: a review

et al. 2019

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Food safety issues across the global food supply chain have become paramount in promoting public health safety and commercial success of global food industries. As food regulations and consumer expectations continue to advance around the world, notwithstanding the latest technology, detection tools, regulations and consumer education on food safety and quality, there is still an upsurge of foodborne disease outbreaks across the globe. The development of the Electronic nose as a noninvasive technique suitable for detecting volatile compounds have been applied for food safety and quality analysis. Application of E-nose for pathogen detection has been successful and superior to conventional methods. E-nose offers a method that is noninvasive, fast and requires little or no sample preparation, thus making it ideal for use as an online monitoring tool. This manuscript presents an indepth review of the application of electronic nose (E-nose) for food safety, with emphasis on classification and detection of foodborne pathogens. We summarise recent data and publications on foodborne pathogen detection (2006)(2007)(2008)(2009)(2010)(2011)(2012)(2013)(2014)(2015)(2016)(2017)(2018) and by E-nose together with their methodologies and pattern recognition tools employed. E-nose instrumentation, sensing technologies and pattern recognition models are also summarised and future trends and challenges, as well as research perspectives, are discussed.

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Developments in Electronic Noses for Quality and Safety Control

Cited by 7 publications

References 157 publications

Prediction of Fruity Aroma Intensity and Defect Presence in Virgin Olive Oil Using an Electronic Nose

Prediction of Fruity Aroma Intensity and Defect Presence in Virgin Olive Oil Using an Electronic Nose

Rapid Detection of Urea Fertilizer Effects on VOC Emissions from Cucumber Fruits Using a MOS E-Nose Sensor Array

Application of electronic nose as a non-invasive technique for odor fingerprinting and detection of bacterial foodborne pathogens: a review

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