Electronic Noses as a Powerful Tool for Assessing Meat Quality: a Mini Review

Jia, Wei; Liang, Gang; Wang, Yalei; Wang, Jihua

doi:10.1007/s12161-018-1283-1

Cited by 43 publications

(36 citation statements)

References 36 publications

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“…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 ]. This technology has also been employed to evaluate the quality of fish [ 27 , 28 ], meat [ 29 ] and processed vegetables [ 25 , 30 , 31 , 32 ].…”

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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“…The electronic nose technology, which imitates the functions of the human olfactory system, has been rapidly developed. Electronic noses can recognize the characteristic information of complex flavors [6,7] and provide superior performance in terms of response time, detection speed, evaluation range, and repeatability [8]. An electronic nose consists of two parts: a gas sensor array and a pattern recognition system [9,10].…”

Section: Introductionmentioning

confidence: 99%

Electronic Nose-Based Technique for Rapid Detection and Recognition of Moldy Apples

Jia

Liang

Tian

et al. 2019

Sensors

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In this study, the PEN3 electronic nose was used to detect and recognize fresh and moldy apples inoculated with Penicillium expansum and Aspergillus niger, taking Golden Delicious apples as the model subject. Firstly, the apples were divided into two groups: individual apple inoculated only with/without different molds (Group A) and mixed apples of inoculated apples with fresh apples (Group B). Then, the characteristic gas sensors of the PEN3 electronic nose that were most closely correlated with the flavor information of the moldy apples were optimized and determined to simplify the analysis process and improve the accuracy of the results. Four pattern recognition methods, including linear discriminant analysis (LDA), backpropagation neural network (BPNN), support vector machines (SVM), and radial basis function neural network (RBFNN), were applied to analyze the data obtained from the characteristic sensors, aiming at establishing the prediction model of the flavor information and fresh/moldy apples. The results showed that only the gas sensors of W1S, W2S, W5S, W1W, and W2W in the PEN3 electronic nose exhibited a strong signal response to the flavor information, indicating most were closely correlated with the characteristic flavor of apples and thus the data obtained from these characteristic sensors were used for modeling. The results of the four pattern recognition methods showed that BPNN had the best prediction performance for the training and testing sets for both Groups A and B, with prediction accuracies of 96.3% and 90.0% (Group A), 77.7% and 72.0% (Group B), respectively. Therefore, we demonstrate that the PEN3 electronic nose not only effectively detects and recognizes fresh and moldy apples, but also can distinguish apples inoculated with different molds.

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“…[140] ults. With additional studies [141][142][143][144] , EN systems offer benefits such as pace, portability, low cost and nondestructive measurements with high relative accuracy, hence these systems can be used as an alternative for the analysis of bacterial population on meat and meat products.…”

Section: % 917%mentioning

confidence: 99%

Electronic Nose and Its Applications: A Survey

Karakaya

Ulucan

Türkan

2019

Int. J. Autom. Comput.

257

152

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In the last two decades, improvements in materials, sensors and machine learning technologies have led to a rapid extension of electronic nose (EN) related research topics with diverse applications. The food and beverage industry, agriculture and forestry, medicine and health-care, indoor and outdoor monitoring, military and civilian security systems are the leading fields which take great advantage from the rapidity, stability, portability and compactness of ENs. Although the EN technology provides numerous benefits, further enhancements in both hardware and software components are necessary for utilizing ENs in practice. This paper provides an extensive survey of the EN technology and its wide range of application fields, through a comprehensive analysis of algorithms proposed in the literature, while exploiting related domains with possible future suggestions for this research topic.

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Electronic Noses as a Powerful Tool for Assessing Meat Quality: a Mini Review

Cited by 43 publications

References 36 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

Electronic Nose-Based Technique for Rapid Detection and Recognition of Moldy Apples

Electronic Nose and Its Applications: A Survey

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