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

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Author
Yılmaz-Düzyaman, Hande
Rosa Navarro, Raúl de la
Velasco Varo, Leonardo
Núñez-Sánchez, Nieves
León, Lorenzo
Publisher
MDPI
Date
2024
Subject
Olive breeding
EVOO
Fatty acid composition
Oxidative stability
Comparative trials
Near infrared
Olea europaea
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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.
URI
http://hdl.handle.net/10396/33821
Fuente
Yılmaz-Düzyaman, H.; de la Rosa, R.; Velasco, L.; Núñez-Sánchez, N.; León, L. Oil Quality Prediction in Olive Oil by Near-Infrared Spectroscopy: Applications in Olive Breeding. Agriculture 2024, 14, 721.
Versión del Editor
https://doi.org/10.3390/agriculture14050721
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