Scholarlink

<p>The oxidative stability index (OSI) and sensory properties are key parameters in the characterization of the commercial quality of extra virgin olive oil (EVOO). The determination of these parameters by reference methodologies is expensive and time-consuming, so fast and inexpensive analytical procedures are needed. Near-infrared spectroscopy (NIRS) has been proven to provide rapid and accurate measurements with minimum sample preparation for many parameters in a wide range of foodstuffs. In this work, 414 EVOO samples obtained from two different origins (laboratory mill Abencor system and commercial samples) were subjected to NIRS evaluation in the 1100–2500&#xa0;nm wavelength range in transmittance mode. Partial least squares (PLS) regression models developed from the whole sample’s spectral dataset for OSI prediction yielded a correlation coefficient of approximately 0.9, a range error ratio (RER) of approximately 10, and comparable results regardless of the origin of the samples (Abencor or commercial). In contrast, neither the prediction of sensory scoring nor the grouping of top-scored samples was possible from the NIRS models. These results suggest that the NIRS prediction of OSI could be used for the routine determination of EVOO with sufficient accuracy, which could be particularly useful for large screening experiments such as selection in olive breeding programs.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Evaluation of Oxidative Stability and Sensory Scoring of Extra Virgin Olive Oil by Near-Infrared Spectroscopy

  • 期刊论文

  • 发表日期：

    2025年5月9日

查看全文
  • Songul Acar,
  • Raúl de la Rosa,
  • Nieves Núñez-Sánchez,
  • José M. Penco,
  • Lorenzo León

摘要

The oxidative stability index (OSI) and sensory properties are key parameters in the characterization of the commercial quality of extra virgin olive oil (EVOO). The determination of these parameters by reference methodologies is expensive and time-consuming, so fast and inexpensive analytical procedures are needed. Near-infrared spectroscopy (NIRS) has been proven to provide rapid and accurate measurements with minimum sample preparation for many parameters in a wide range of foodstuffs. In this work, 414 EVOO samples obtained from two different origins (laboratory mill Abencor system and commercial samples) were subjected to NIRS evaluation in the 1100–2500 nm wavelength range in transmittance mode. Partial least squares (PLS) regression models developed from the whole sample’s spectral dataset for OSI prediction yielded a correlation coefficient of approximately 0.9, a range error ratio (RER) of approximately 10, and comparable results regardless of the origin of the samples (Abencor or commercial). In contrast, neither the prediction of sensory scoring nor the grouping of top-scored samples was possible from the NIRS models. These results suggest that the NIRS prediction of OSI could be used for the routine determination of EVOO with sufficient accuracy, which could be particularly useful for large screening experiments such as selection in olive breeding programs.