Next Article in Journal
Ultra-Long-Distance Hybrid BOTDA/Ф-OTDR
Next Article in Special Issue
Laser Spectroscopic Sensors for the Development of Anthropomorphic Robot Sensitivity
Previous Article in Journal
An Indoor Positioning-Based Mobile Payment System Using Bluetooth Low Energy Technology
Previous Article in Special Issue
Determination of Food Oxalates Using Silica–Titania Xerogel Modified with Eriochrome Cyanine R
Article Menu
Issue 4 (April) cover image

Export Article

Open AccessArticle
Sensors 2018, 18(4), 975; https://doi.org/10.3390/s18040975

Non-Invasive Methodology to Estimate Polyphenol Content in Extra Virgin Olive Oil Based on Stepwise Multilinear Regression

Robotics, Automation and Computer Vision Group, University of Jaen, Campus Las Lagunillas s/n, ES-23071 Jaen, Spain
*
Author to whom correspondence should be addressed.
Received: 30 January 2018 / Revised: 20 March 2018 / Accepted: 20 March 2018 / Published: 25 March 2018
(This article belongs to the Special Issue Spectroscopy Based Sensors)
Full-Text   |   PDF [10656 KB, uploaded 3 May 2018]   |  

Abstract

Normally the olive oil quality is assessed by chemical analysis according to international standards. These norms define chemical and organoleptic markers, and depending on the markers, the olive oil can be labelled as lampante, virgin, or extra virgin olive oil (EVOO), the last being an indicator of top quality. The polyphenol content is related to EVOO organoleptic features, and different scientific works have studied the positive influence that these compounds have on human health. The works carried out in this paper are focused on studying relations between the polyphenol content in olive oil samples and its spectral response in the near infrared spectra. In this context, several acquisition parameters have been assessed to optimize the measurement process within the virgin olive oil production process. The best regression model reached a mean error value of 156.14 mg/kg in leave one out cross validation, and the higher regression coefficient was 0.81 through holdout validation. View Full-Text
Keywords: olive oil production process; near infrared spectrum; polyphenol content; feature extraction olive oil production process; near infrared spectrum; polyphenol content; feature extraction
Figures

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
SciFeed

Share & Cite This Article

MDPI and ACS Style

Martínez Gila, D.M.; Cano Marchal, P.; Gómez Ortega, J.; Gámez García, J. Non-Invasive Methodology to Estimate Polyphenol Content in Extra Virgin Olive Oil Based on Stepwise Multilinear Regression. Sensors 2018, 18, 975.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Sensors EISSN 1424-8220 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top