Josu Amorebieta

Josu Amorebieta Herrero

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Additional information

Josu Amorebieta obtained his M.Sc. and Ph.D degrees in Telecommunications Engineering from the University of the Basque Country (UPV/EHU), Bilbao, Spain, in 2016 and 2021, respectively. Afterwards, he continued his research career in the Applied Photonics Group from the University of the Basque Country (UPV/EHU). His research fields involve the mathematical modelling, design, fabrication and validation of photonic sensors for several industrial applications such as the aeronautical industry. Nowadays, he is a lecturer at the Department of Applied Mathematics in the Bilbao School of Engineering of University of the Basque Country (UPV/EHU).

Current Research Activities

Fabrication and design of multicore optical fibres; design and validation of Structural Health Monitoring optical fiber-based sensors

Google Scholar

https://scholar.google.es/citations?user=DpM-dekAAAAJ&hl=es

ORCiD

https://orcid.org/0000-0002-0349-3037

ResearchGate

https://www.researchgate.net/profile/Josu-Amorebieta-2

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ESPECTROLIVE 

Research on the use of spectroscopy and complementary technologies in detecting phytosanitary products in situ in whole olives.

Main objective

Investigate the application of spectroscopy and electronic nose technologies for the detection of phytosanitary products in whole olives in situ in order to ensure compliance with regulatory limits for these compounds in olive oils and perform real-time monitoring of the production process that allows rapid identification of problems and immediate action related to the presence of contaminants, helping to reduce waste and improving the efficiency and quality control of olive oils, as well as performing an appropriate classification of the fruit, before milling, to achieve "zero residue" oils, which are highly valued by today's consumers.

Specific objectives

The specific technical objectives carried out in the Applied Photonics Group are: 

  • Raman
  1. Optimize Raman spectra acquisition parameters to improve the resolution and accuracy of the results (maximize the signal-to-noise ratio). 
  2. Identify and quantify the concentration of specific phytosanitary products in the samples.
  3. Develop multivariate models for classifying different varieties of phytosanitary products and examining their evolution over time.
  4. To evaluate the sensitivity and selectivity of the technique in comparison with other existing analytical techniques.
  5. Validate the results obtained by means of cross-validation techniques and comparison with reference values.

Expected outcomes

  1. A real-time olive classification system is based on the presence of contaminants.
  2. Promotion of the health properties of olive oil as a sales argument for these products. 
  3. Improvement of olive oil export channels through better compliance with restrictive regulations on the presence of phytosanitary residues in olive oil. 
  4. Improvement of the competitiveness of the olive oil sector and the associated auxiliary industry. 
  5. Promotion in the agro-industrial sector of sensor technologies aligned with Industry 4.0.

Partners

  • INOLEO (Coordinator)
  • SECPHO (SOUTHERN EUROPEAN CLUSTER IN PHOTONICS AND)
  • AOTECH (ADVANCED OPTICAL TECHNOLOGIES S.L.
  • ISR (INTEGRACIÓN SENSORIAL Y ROBOTICA SL)
  • UNIVERSIDAD DE JAÉN (UJA)
  • UNIVERSITY OF THE BASQUE COUNTRY (UPV/EHU)

Duration

From 05/2023 to 04/2024

Budget

308,010 €

Grant program

Support grants for Innovative Business Groups to improve the competitiveness of small and medium-sized companies and the call for applications for 2023, within the framework of the Recovery, Transformation and Resilience Plan.

Funder

Spanish Ministry of Industry, Commerce and Tourism (MINCOTUR).

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