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<p>Three almond cultivars (Lauranne, Marinada, and Vairo) were studied, considering morphological parameters that showed statistical cultivar-dependence but not enabled accurate cultivar recognition. Alternatively, attenuated total reflectance Fourier transform infrared spectroscopy (ATR-FTIR) was applied to whole endocarp, kernel, and ground almonds. Both transmittance spectra and respective derivatives (3400–2800 and 1900–600&#xa0;cm<sup>−1</sup>) of the three matrices were used to establish multivariate linear discriminant models, based on subsets of selected wavenumbers (6–33), allowing 90.5–99.7% of correct cultivar classification for repeated K-fold cross-validation. Ground almonds yielded the best results regardless of spectrum pre-treatment. While epicarp analysis offers less invasiveness, the use of raw transmittance spectra of ground almonds resulted into the most practical approach due to the need of fewer independent variables (less complex models), proving effective for cultivar identification via ATR-FTIR -chemometric tools. Overall, the findings point out that ATR-FTIR is a reliable tool for almond cultivar traceability.</p>

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Potential use of the ATR-FTIR spectroscopy as an almond cultivar recognition tool: impact of sample and spectral pre-treatments

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年2月28日

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  • Sandra Lamas,
  • Nuno Rodrigues,
  • Arantzazu Santamaria-Echart,
  • Igor Palu,
  • Jocyla R. Manhique,
  • Baudilio Herrero,
  • Isabel López-Cortés,
  • José Alberto Pereira,
  • António M. Peres

摘要

Three almond cultivars (Lauranne, Marinada, and Vairo) were studied, considering morphological parameters that showed statistical cultivar-dependence but not enabled accurate cultivar recognition. Alternatively, attenuated total reflectance Fourier transform infrared spectroscopy (ATR-FTIR) was applied to whole endocarp, kernel, and ground almonds. Both transmittance spectra and respective derivatives (3400–2800 and 1900–600 cm−1) of the three matrices were used to establish multivariate linear discriminant models, based on subsets of selected wavenumbers (6–33), allowing 90.5–99.7% of correct cultivar classification for repeated K-fold cross-validation. Ground almonds yielded the best results regardless of spectrum pre-treatment. While epicarp analysis offers less invasiveness, the use of raw transmittance spectra of ground almonds resulted into the most practical approach due to the need of fewer independent variables (less complex models), proving effective for cultivar identification via ATR-FTIR -chemometric tools. Overall, the findings point out that ATR-FTIR is a reliable tool for almond cultivar traceability.