Convolutional Neural Networks for Olive Oil Classification

  • Belén Vega-MárquezEmail author
  • Andrea Carminati
  • Natividad Jurado-Campos
  • Andrés Martín-Gómez
  • Lourdes Arce-Jiménez
  • Cristina Rubio-Escudero
  • Isabel A. Nepomuceno-Chamorro
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11487)


The analysis of the quality of olive oil is a task that is having a lot of impact nowadays due to the large frauds that have been observed in the olive oil market. To solve this problem we have trained a Convolutional Neural Network (CNN) to classify 701 images obtained using GC-IMS methodology (gas chromatography coupled to ion mobility spectrometry). The aim of this study is to show that Deep Learning techniques can be a great alternative to traditional oil classification methods based on the subjectivity of the standardized sensory analysis according to the panel test method, and also to novel techniques provided by the chemical field, such as chemometric markers. This technique is quite expensive since the markers are manually extracted by an expert.

The analyzed data includes instances belonging to two different crops, the first covers the years 2014–2015 and the second 2015–2016. Both harvests have instances classified in the three categories of existing oil, extra virgin olive oil (EVOO), virgin olive oil (VOO) and lampante olive oil (LOO). The aim of this study is to demonstrate that Deep Learning techniques in combination with chemical techniques are a good alternative to the panel test method, implying even better accuracy than results obtained in previous work.


Convolutional Neural Network Olive oil classification GC-IMS method 


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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Belén Vega-Márquez
    • 1
    Email author
  • Andrea Carminati
    • 1
  • Natividad Jurado-Campos
    • 2
  • Andrés Martín-Gómez
    • 2
  • Lourdes Arce-Jiménez
    • 2
  • Cristina Rubio-Escudero
    • 1
  • Isabel A. Nepomuceno-Chamorro
    • 1
  1. 1.Department of Computer Languages and SystemsUniversity of SevillaSevillaSpain
  2. 2.Institute of Fine Chemistry and Nanochemistry, Department of Analytical ChemistryUniversity of CórdobaCórdobaSpain

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