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Cited article:

A Survey on Statistical and Machine Learning Algorithms Used in Electronic Noses for Food Quality Assessment

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SN Computer Science 4 (5) (2023)
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Assessment of fruity aroma intensity in olive oils from different Spanish regions using a portable electronic nose

Alessandro Bianchi, Pablo Cano Marchal, Diego M. Martínez Gila, Fabio Mencarelli and Javier Gámez García
Journal of the Science of Food and Agriculture (2023)
https://doi.org/10.1002/jsfa.13179

HS-GC-IMS and chemometric data treatment for food authenticity assessment: Olive oil mapping and classification through two different devices as an example

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Food Control 98 82 (2019)
https://doi.org/10.1016/j.foodcont.2018.11.001

On the Temporal Stability of Analyte Recognition with an E-Nose Based on a Metal Oxide Sensor Array in Practical Applications

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Sensors 18 (2) 550 (2018)
https://doi.org/10.3390/s18020550

Sensing Technology: Current Status and Future Trends II

D. Chatterjee, P. Bhattacharjee, H. Lechat, et al.
Smart Sensors, Measurement and Instrumentation, Sensing Technology: Current Status and Future Trends II 8 161 (2014)
https://doi.org/10.1007/978-3-319-02315-1_8

Food Analysis Using Artificial Senses

Magdalena Śliwińska, Paulina Wiśniewska, Tomasz Dymerski, Jacek Namieśnik and Waldemar Wardencki
Journal of Agricultural and Food Chemistry 62 (7) 1423 (2014)
https://doi.org/10.1021/jf403215y

Electronic Nose:  Current Status and Future Trends

Frank Röck, Nicolae Barsan and Udo Weimar
Chemical Reviews 108 (2) 705 (2008)
https://doi.org/10.1021/cr068121q

Simplifying chromatographic analysis of the volatile fraction of foods

Silvia López-Feria, Soledad Cárdenas and Miguel Valcárcel
TrAC Trends in Analytical Chemistry 27 (9) 794 (2008)
https://doi.org/10.1016/j.trac.2008.07.006