Model Based on Clusters of Similar Color and NIR to Estimate Oil Content of Single Olives

Fredes Monsalves, Claudio and Valero Ubierna, Constantino and Diezma Iglesias, Belen and Mora, Marco and Naranjo-Torres, José and Wilson, Manuel and Delgadillo, Gabriel (2021). Model Based on Clusters of Similar Color and NIR to Estimate Oil Content of Single Olives. "Foods", v. 10 (n. 3); pp. 1-11. ISSN 2304-8158. https://doi.org/10.3390/foods10030609.

Description

Title: Model Based on Clusters of Similar Color and NIR to Estimate Oil Content of Single Olives
Author/s:
  • Fredes Monsalves, Claudio
  • Valero Ubierna, Constantino
  • Diezma Iglesias, Belen
  • Mora, Marco
  • Naranjo-Torres, José
  • Wilson, Manuel
  • Delgadillo, Gabriel
Item Type: Article
Título de Revista/Publicación: Foods
Date: 13 March 2021
ISSN: 2304-8158
Volume: 10
Subjects:
Freetext Keywords: infrared spectroscopy; visible image; support vector machine; olive quality
Faculty: E.T.S. de Ingeniería Agronómica, Alimentaria y de Biosistemas (UPM)
Department: Ingeniería Agroforestal
UPM's Research Group: Técnicas Avanzadas en Agroalimentación LPF-TAGRALIA
Creative Commons Licenses: None

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Abstract

Lipid extraction using the traditional, destructive Soxhlet method is not able to measure oil content (OC) on a single olive. As the color and near infrared spectrum are key parameters to build an oil estimation model (EM), this study grouped olives with similar color and NIR for building EM of oil content obtained by Soxhlet from a cluster of similar olives. The objective was to estimate OC of individual olives, based on clusters of similar color and NIR in two seasons. This study was performed with Arbequina olives in 2016 and 2017. The descriptor of the cluster consisted of the three color channels of c1c2c3 color model plus 11 reflectance points between 1710 and 1735 nm of each olive, normalized with the Z-score index. Clusters of similar color and NIR spectrum were formed with the k-means++ algorithm, leaving a sufficient number of olives to perform the Soxhlet analysis of OC, as reference value of EM. The training of EM was based on Support Vector Machine. The test was performed with Leave One-Out Cross Validation in different training-testing combinations. The best EM predicted the OC with 6 and 13% deviation with respect to the real value when one season was tested with itself and with another season, respectively. The use of clustering in EM is discussed.

Funding Projects

TypeCodeAcronymLeaderTitle
Universidad Politécnica de MadridAL14-PID-11UnspecifiedConstantino Valero UbiernaP1720280091 Estimación de calidad y contenido en aceite de aceitunas mediante procedimientos ópticos VIS y NIR (FONDEF ID15101142 Chile)

More information

Item ID: 66395
DC Identifier: http://oa.upm.es/66395/
OAI Identifier: oai:oa.upm.es:66395
DOI: 10.3390/foods10030609
Official URL: https://www.mdpi.com/2304-8158/10/3/609
Deposited by: Profesor Constantino Valero Ubierna
Deposited on: 13 Mar 2021 17:49
Last Modified: 13 Mar 2021 17:49
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