Identification and Quantification of Olive Oil Quality Parameters Using an Electronic Nose

An electronic nose (EN), which is a kind of chemical sensors, was employed to check olive oil quality parameters. Fifty samples of olive oil, covering the four quality categories extra virgin, virgin, ordinary virgin and lampante, were gathered from different Palestinian cities. The samples were ana...

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Main Author: Nawaf Abu-Khalaf
Format: Article
Language:English
Published: MDPI AG 2021-07-01
Series:Agriculture
Subjects:
Online Access:https://www.mdpi.com/2077-0472/11/7/674
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author Nawaf Abu-Khalaf
author_facet Nawaf Abu-Khalaf
author_sort Nawaf Abu-Khalaf
collection DOAJ
description An electronic nose (EN), which is a kind of chemical sensors, was employed to check olive oil quality parameters. Fifty samples of olive oil, covering the four quality categories extra virgin, virgin, ordinary virgin and lampante, were gathered from different Palestinian cities. The samples were analysed chemically using routine tests and signals for each chemical were obtained using EN. Each signal acquisition represents the concentration of certain chemical constituents. Partial least squares (PLS) models were used to analyse both chemical and EN data. The results demonstrate that the EN was capable of modelling the acidity parameter with a good performance. The correlation coefficients of the PLS-1 model for acidity were 0.87 and 0.88 for calibration and validation sets, respectively. Furthermore, the values of the standard error of performance to standard deviation (RPD) for acidity were 2.61 and 2.68 for the calibration and the validation sets, respectively. It was found that two principal components (PCs) in the PLS-1 scores plot model explained 86% and 5% of EN and acidity variance, respectively. PLS-1 scores plot showed a high performance in classifying olive oil samples according to quality categories. The results demonstrated that EN can predict/model acidity with good precision. Additionally, EN was able to discriminate between diverse olive oil quality categories.
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spelling doaj.art-40f9800a3f614d5ead8b88e0edf657f52023-11-22T02:57:31ZengMDPI AGAgriculture2077-04722021-07-0111767410.3390/agriculture11070674Identification and Quantification of Olive Oil Quality Parameters Using an Electronic NoseNawaf Abu-Khalaf0Department of Agricultural Biotechnology, Faculty of Agricultural Sciences and Technology, Palestine Technical University-Kadoorie (PTUK), Tulkarm P.O. Box 7, PalestineAn electronic nose (EN), which is a kind of chemical sensors, was employed to check olive oil quality parameters. Fifty samples of olive oil, covering the four quality categories extra virgin, virgin, ordinary virgin and lampante, were gathered from different Palestinian cities. The samples were analysed chemically using routine tests and signals for each chemical were obtained using EN. Each signal acquisition represents the concentration of certain chemical constituents. Partial least squares (PLS) models were used to analyse both chemical and EN data. The results demonstrate that the EN was capable of modelling the acidity parameter with a good performance. The correlation coefficients of the PLS-1 model for acidity were 0.87 and 0.88 for calibration and validation sets, respectively. Furthermore, the values of the standard error of performance to standard deviation (RPD) for acidity were 2.61 and 2.68 for the calibration and the validation sets, respectively. It was found that two principal components (PCs) in the PLS-1 scores plot model explained 86% and 5% of EN and acidity variance, respectively. PLS-1 scores plot showed a high performance in classifying olive oil samples according to quality categories. The results demonstrated that EN can predict/model acidity with good precision. Additionally, EN was able to discriminate between diverse olive oil quality categories.https://www.mdpi.com/2077-0472/11/7/674electronic nosechemical sensorolive oil qualitymultivariate data analysispartial least squares (PLS)
spellingShingle Nawaf Abu-Khalaf
Identification and Quantification of Olive Oil Quality Parameters Using an Electronic Nose
Agriculture
electronic nose
chemical sensor
olive oil quality
multivariate data analysis
partial least squares (PLS)
title Identification and Quantification of Olive Oil Quality Parameters Using an Electronic Nose
title_full Identification and Quantification of Olive Oil Quality Parameters Using an Electronic Nose
title_fullStr Identification and Quantification of Olive Oil Quality Parameters Using an Electronic Nose
title_full_unstemmed Identification and Quantification of Olive Oil Quality Parameters Using an Electronic Nose
title_short Identification and Quantification of Olive Oil Quality Parameters Using an Electronic Nose
title_sort identification and quantification of olive oil quality parameters using an electronic nose
topic electronic nose
chemical sensor
olive oil quality
multivariate data analysis
partial least squares (PLS)
url https://www.mdpi.com/2077-0472/11/7/674
work_keys_str_mv AT nawafabukhalaf identificationandquantificationofoliveoilqualityparametersusinganelectronicnose