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Infrared spectroscopy enables rapid identification of Scots pine resistant to Diplodia sapinea

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Abstract

Many forest pathogens have become increasingly damaging as climate-driven stress intensifies disease outbreaks. A prominent example is Diplodia sapinea, which is causing more frequent and destructive shoot blight and dieback, particularly across northern Europe. Developing resistant planting stock is a priority, but screening currently depends on destructive inoculation assays and multi-year field trials, making the process slow and difficult to scale. This study evaluated whether a handheld Fourier-transform infrared (FT-IR) spectrometer that provides rapid and non-destructive sampling can identify constitutive chemical signatures associated with relative resistance prior to infection. FT-IR spectra were collected from needles, shoots, and stem phloem from Swedish pine families across two experimental years, followed by artificial inoculations to phenotype lesion development. A combined sparse partial least squares discriminant analysis and support vector machine workflow achieved 65-81% cross-validated accuracy in distinguishing resistant from susceptible trees, with shoot spectra consistently producing the strongest models. Principal component analysis indicated clear chemical differences between years, yet resistance-associated patterns were stable across tissues. The most frequently selected wavenumbers grouped into four biochemical domains: cell-wall polysaccharides, cellulose/hemicellulose bonding, phenolics and proteins, and aliphatic lipids/cutin, corresponding to known conifer defense pathways. These findings demonstrate that portable FT-IR spectroscopy can capture biologically meaningful variation in constitutive defense chemistry and offers a rapid, scalable approach for resistance phenotyping in Scots pine breeding programs.
Original languageEnglish
Article number1755489
Number of pages10
JournalFrontiers in Forests and Global Change
Volume9
DOIs
Publication statusPublished - 2026

Keywords

  • biochemical fingerprint
  • forest pathology
  • FT-IR
  • phenotyping
  • tree health

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