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Oil Quality Prediction in Olive Oil by Near-Infrared Spectroscopy: Applications in Olive Breeding

Author

Listed:
  • Hande Yılmaz-Düzyaman

    (IFAPA Centro Alameda del Obispo, Avda. Menéndez Pidal s/n, 14004 Córdoba, Spain)

  • Raúl de la Rosa

    (Instituto de Agricultura Sostenible (CSIC), Avda. Menéndez Pidal s/n, 14004 Córdoba, Spain)

  • Leonardo Velasco

    (Instituto de Agricultura Sostenible (CSIC), Avda. Menéndez Pidal s/n, 14004 Córdoba, Spain)

  • Nieves Núñez-Sánchez

    (Departamento de Producción Animal, Universidad de Córdoba, Campus de Rabanales, 14071 Córdoba, Spain)

  • Lorenzo León

    (IFAPA Centro Alameda del Obispo, Avda. Menéndez Pidal s/n, 14004 Córdoba, Spain)

Abstract

The oxidative stability index (OSI) and fatty acid (FA) composition of extra virgin olive oils (EVOOs) are key parameters in the characterization of new varieties in breeding programs. Their determination through traditional methods (Rancimat and gas chromatography, respectively) is expensive and time-consuming. Therefore, there is a need to develop rapid and cost-effective analytical procedures. This study aimed to evaluate the potential use of near-infrared spectroscopy (NIRS) for analyzing OSI and FA composition in EVOOs. A total of 318 samples sourced from different origins were evaluated using both FT-NIR MPA and MicroNIR instruments in transmittance mode, with wavelengths ranging from 1100 to 2500 nm and 908 to 1676 nm, respectively. Different accuracies were obtained in the models developed for the different evaluated traits, with simpler models (using a lower number of latent variables) for the MPA analyzer in all cases. Additionally, consistent results between instruments for the partitioning of the variance and heritability estimation, and the reliable ranking of genotypes were obtained from one of the sample sets tested. In summary, models derived from PLS regression using spectroscopic data of both instruments demonstrated promising results in determining these EVOO traits, facilitating their evaluation and selection of genotypes, particularly in breeding programs.

Suggested Citation

  • Hande Yılmaz-Düzyaman & Raúl de la Rosa & Leonardo Velasco & Nieves Núñez-Sánchez & Lorenzo León, 2024. "Oil Quality Prediction in Olive Oil by Near-Infrared Spectroscopy: Applications in Olive Breeding," Agriculture, MDPI, vol. 14(5), pages 1-13, May.
  • Handle: RePEc:gam:jagris:v:14:y:2024:i:5:p:721-:d:1387878
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