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Chacón I, Roales J, Lopes-Costa T, Pedrosa JM. Analyzing the Organoleptic Quality of Commercial Extra Virgin Olive Oils: IOC Recognized Panel Tests vs. Electronic Nose. Foods 2022; 11:1477. [PMID: 35627047 PMCID: PMC9141220 DOI: 10.3390/foods11101477] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2022] [Revised: 05/03/2022] [Accepted: 05/16/2022] [Indexed: 02/05/2023] Open
Abstract
Virgin olive oil (VOO) classification into quality categories determines its labeling and market price. This procedure involves performing a series of chemical-physical analyses and, ultimately, a sensory analysis through the panel test. This work explores the analysis of VOOs quality with an electronic olfactory system (EOS) and examines its abilities using the panel test as a reference. To do this, six commercial olive oils labelled as extra virgin were analyzed with an EOS and classified by three panels recognized by the International Olive Council. The organoleptic analysis of the oils by the panels indicated that most of the oils in the study were in fact not extra virgin. Besides this, the classifications showed inconsistencies between panels, needing statistical treatment to be used as a reference for the EOS training. The analysis of the same oils by the EOS and their subsequent statistical analysis by PCA revealed a good correlation between the first principal component and the olive oil quality from the panels using average scores. It also showed a more consistent classification than the panels. Overall, the EOS proved to be a cheaper, faster, and highly reliable method as a complement to the panel test for the olive oil classification.
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Affiliation(s)
| | | | | | - José M. Pedrosa
- Departmento de Sistemas Físicos, Químicos y Naturales, Universidad Pablo de Olavide, 41013 Sevilla, Spain; (I.C.); (J.R.); (T.L.-C.)
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Abstract
The adulteration of olive oils can be detected with chemical test. This is very expensive and takes very long time. Thus, this study is focused on reducing both time and cost. For this purpose, the raw data has been collected from olive oils by using an e-nose from different regions in Balikesir in Turkey. This study presents two methods to analyze quality control of olive oils. In the first method, 32 inputs are applied to the classifiers directly. In the second, 32-input collected data are reduced to 8 inputs by Principal Component Analysis. These reduced data as 8 inputs are applied to the classifiers. Different machine learning classifiers such as Naïve Bayesian, K-Nearest Neighbors (k-NN), Linear Discriminate Analysis (LDA), Decision Tree, Artificial Neural Networks (ANN), and Support Vector Machine (SVM) were used. Then performances of these classifiers were compared according to their accuracies.
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Borràs E, Ferré J, Boqué R, Mestres M, Aceña L, Calvo A, Busto O. Prediction of olive oil sensory descriptors using instrumental data fusion and partial least squares (PLS) regression. Talanta 2016; 155:116-23. [DOI: 10.1016/j.talanta.2016.04.040] [Citation(s) in RCA: 35] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2016] [Revised: 04/14/2016] [Accepted: 04/19/2016] [Indexed: 12/18/2022]
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Olive oil sensory defects classification with data fusion of instrumental techniques and multivariate analysis (PLS-DA). Food Chem 2016; 203:314-322. [DOI: 10.1016/j.foodchem.2016.02.038] [Citation(s) in RCA: 70] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2015] [Revised: 01/11/2016] [Accepted: 02/04/2016] [Indexed: 11/23/2022]
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Sghaier L, Vial J, Sassiat P, Thiebaut D, Watiez M, Breton S, Rutledge DN, Cordella CB. An overview of recent developments in volatile compounds analysis from edible oils: Technique-oriented perspectives. EUR J LIPID SCI TECH 2016. [DOI: 10.1002/ejlt.201500508] [Citation(s) in RCA: 30] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/13/2023]
Affiliation(s)
- Lilia Sghaier
- R&D Center; Lesieur; Coudekerque-Branche France
- Department of Analytical, Bioanalytical Sciences and Miniaturization (LSABM), Institute of Chemistry, Biology and Innovation (CBI) - ESPCI ParisTech, CNRS UMR 8231; PSL Research University; Paris Cedex 05 France
- UMR1145 GENIAL; AgroParisTech; Paris France
| | - Jérôme Vial
- Department of Analytical, Bioanalytical Sciences and Miniaturization (LSABM), Institute of Chemistry, Biology and Innovation (CBI) - ESPCI ParisTech, CNRS UMR 8231; PSL Research University; Paris Cedex 05 France
| | - Patrick Sassiat
- Department of Analytical, Bioanalytical Sciences and Miniaturization (LSABM), Institute of Chemistry, Biology and Innovation (CBI) - ESPCI ParisTech, CNRS UMR 8231; PSL Research University; Paris Cedex 05 France
| | - Didier Thiebaut
- Department of Analytical, Bioanalytical Sciences and Miniaturization (LSABM), Institute of Chemistry, Biology and Innovation (CBI) - ESPCI ParisTech, CNRS UMR 8231; PSL Research University; Paris Cedex 05 France
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Borràs E, Mestres M, Aceña L, Busto O, Ferré J, Boqué R, Calvo A. Identification of olive oil sensory defects by multivariate analysis of mid infrared spectra. Food Chem 2015; 187:197-203. [DOI: 10.1016/j.foodchem.2015.04.030] [Citation(s) in RCA: 25] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2014] [Revised: 04/09/2015] [Accepted: 04/12/2015] [Indexed: 02/01/2023]
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Del Carlo M, Fusella G, Pepe A, Sergi M, Di Martino M, Mascini M, Martino G, Cichelli A, Di Natale C, Compagnone D. Novel oligopeptides based e-nose for food quality control: application to extra-virgin olive samples. QUALITY ASSURANCE AND SAFETY OF CROPS & FOODS 2014. [DOI: 10.3920/qas2013.0377] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/19/2022]
Affiliation(s)
- M. Del Carlo
- Faculty of Bioscience and Technology for Food, Agriculture and Environment, University of Teramo, Via Lerici 1, 64023 Mosciano Sant'Angelo, Teramo, Italy
| | - G.C. Fusella
- Faculty of Bioscience and Technology for Food, Agriculture and Environment, University of Teramo, Via Lerici 1, 64023 Mosciano Sant'Angelo, Teramo, Italy
| | - A. Pepe
- Faculty of Bioscience and Technology for Food, Agriculture and Environment, University of Teramo, Via Lerici 1, 64023 Mosciano Sant'Angelo, Teramo, Italy
| | - M. Sergi
- Faculty of Bioscience and Technology for Food, Agriculture and Environment, University of Teramo, Via Lerici 1, 64023 Mosciano Sant'Angelo, Teramo, Italy
| | - M. Di Martino
- Department of Economy, Food Commodities Laboratory, University d'Annunzio Chieti-Pescara, Viale Pindaro12, 65127 Pescara, Italy
| | - M. Mascini
- Faculty of Bioscience and Technology for Food, Agriculture and Environment, University of Teramo, Via Lerici 1, 64023 Mosciano Sant'Angelo, Teramo, Italy
| | - G. Martino
- Faculty of Bioscience and Technology for Food, Agriculture and Environment, University of Teramo, Via Lerici 1, 64023 Mosciano Sant'Angelo, Teramo, Italy
| | - A Cichelli
- Department of Economy, Food Commodities Laboratory, University d'Annunzio Chieti-Pescara, Viale Pindaro12, 65127 Pescara, Italy
| | - C. Di Natale
- Department of Electronic Engineering, University of Tor Vergata, Via del Politecnico, 00133 Rome, Italy
| | - D. Compagnone
- Faculty of Bioscience and Technology for Food, Agriculture and Environment, University of Teramo, Via Lerici 1, 64023 Mosciano Sant'Angelo, Teramo, Italy
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Śliwińska M, Wiśniewska P, Dymerski T, Namieśnik J, Wardencki W. Food analysis using artificial senses. JOURNAL OF AGRICULTURAL AND FOOD CHEMISTRY 2014; 62:1423-48. [PMID: 24506450 DOI: 10.1021/jf403215y] [Citation(s) in RCA: 140] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/18/2023]
Abstract
Nowadays, consumers are paying great attention to the characteristics of food such as smell, taste, and appearance. This motivates scientists to imitate human senses using devices known as electronic senses. These include electronic noses, electronic tongues, and computer vision. Thanks to the utilization of various sensors and methods of signal analysis, artificial senses are widely applied in food analysis for process monitoring and determining the quality and authenticity of foods. This paper summarizes achievements in the field of artificial senses. It includes a brief history of these systems, descriptions of most commonly used sensors (conductometric, potentiometric, amperometic/voltammetric, impedimetric, colorimetric, piezoelectric), data analysis methods (for example, artificial neural network (ANN), principal component analysis (PCA), model CIE L*a*b*), and application of artificial senses to food analysis, in particular quality control, authenticity and falsification assessment, and monitoring of production processes.
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Affiliation(s)
- Magdalena Śliwińska
- Department of Analytical Chemistry, Gdansk University of Technology , 11/12 Narutowicza Street, 80-233 Gdańsk, Poland
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Carrasco JA, Duque JP. Classification of Iberian pigs according to intensive feeding by chemsensor. GRASAS Y ACEITES 2013. [DOI: 10.3989/gya.130512] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
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Su R, Feng X, Yu A, Zhang H, Wang X. Application of real-time refrigeration turbidimetry for rapid discrimination and purity assessment of refined peanut oils adulterated with other seed oils. Eur Food Res Technol 2011. [DOI: 10.1007/s00217-011-1623-5] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/15/2022]
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Dymerski TM, Chmiel TM, Wardencki W. Invited review article: an odor-sensing system--powerful technique for foodstuff studies. THE REVIEW OF SCIENTIFIC INSTRUMENTS 2011; 82:111101. [PMID: 22128959 DOI: 10.1063/1.3660805] [Citation(s) in RCA: 31] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/10/2011] [Accepted: 08/20/2011] [Indexed: 05/31/2023]
Abstract
This work examines gas sensor array technology combined with multivariate data processing methods and demonstrates a promising potential for rapid, non-destructive analysis of food. Main attention is focused on detailed description of sensor used in e-nose instruments, construction, and principle of operation of these systems. Moreover, this paper briefly reviews the progress in the field of artificial olfaction and future trends in electronic nose technology, namely, e-nose based on mass spectrometry. Further discussion concerns a comparison of artificial nose with gas chromatography-olfactometry and the application of e-nose instruments in different areas of food industry.
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Affiliation(s)
- T M Dymerski
- Department of Analytical Chemistry, Gdansk University of Technology, 11/12 G. Narutowicza Str., 80-233 Gdańsk, Pomerania, Poland
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Escuderos ME. Olive Oil Aroma Evaluation By Gas Chromatographic Method: A Critical Review. Crit Rev Anal Chem 2011. [DOI: 10.1080/10408347.2011.533939] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
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Nightingale LM, Lee SY, Engeseth NJ. Impact of Storage on Dark Chocolate: Texture and Polymorphic Changes. J Food Sci 2011; 76:C142-53. [DOI: 10.1111/j.1750-3841.2010.01970.x] [Citation(s) in RCA: 23] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
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Peris M, Escuder-Gilabert L. A 21st century technique for food control: Electronic noses. Anal Chim Acta 2009; 638:1-15. [DOI: 10.1016/j.aca.2009.02.009] [Citation(s) in RCA: 334] [Impact Index Per Article: 22.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2008] [Revised: 02/03/2009] [Accepted: 02/03/2009] [Indexed: 10/21/2022]
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Fatty acid methyl and ethyl esters as well as wax esters for evaluating the quality of olive oils. Eur Food Res Technol 2008. [DOI: 10.1007/s00217-008-0907-x] [Citation(s) in RCA: 36] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/21/2022]
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