Unravelling pine response to Fusarium circinatum through Raman spectroscopy

Abstract

Pine Pitch Canker (PPC), caused by the fungus Fusarium circinatum, is associated to significant economic and ecological losses worldwide. The effectiveness of PPC monitoring, early detection in nurseries and plantations, and the identification of resistant plant material relies on the development of objective, non‐destructive, and cost‐effective tools. This study analyzed the potential of employing Raman Spectroscopy (RS) for the early detection of biochemical changes associated with PPC in Pinus spp. with different susceptibilities to F. circinatum (highly susceptible Pinus radiata vs relatively resistant Pinus pinea), while unveiling possible mechanisms of action on these pathosystems. Our results indicate lignin as a key constitutive component of pine resistance against PPC and thus the potential of using this technology for the selection of PPC resistant trees. Moreover, we demonstrate the power of RS‐based approaches for the rapid detection of the disease in susceptible species. Early spectral variations were found in P. radiata upon inoculation with F. circinatum from 3 days post‐inoculation (dpi) onwards, whereas changes in histological analysis, relative internal stem necrosis measurements, and visual disease symptoms were only visible at 6, 8, and 9 dpi, respectively. These spectral changes have been associated to cell wall degradation and induction of phenolic compounds synthesis upon infection in P. radiata. Altogether, we believe that RS is an innovative promising tool able to reduce disease detection time in pine species and providing an appealing alternative for the development of new and eco‐friendly disease control measures.

Reduced Recalcitrance and Improved Pulp Properties in Eucalypt Woods Pretreated with White-Rot Fungi and Mild Alkali

“…The spectral data were imported into MatLab (v. R2021b, MathWorks, MA) and all computations�vector normalization to unit length (2-Norm), and baseline correction according to the automatic weighted least-squares algorithm (polynomial order = 2)�were carried out using the PLS_Toolbox (v. 9.0, Eigenvector Research, WA) and in-house developed routines, as previously described. 35,36 Finally, the spectra were restricted to the fingerprint region (1800−800 cm −1 ), averaged (per replicate), and plotted.…”

“…The Bruker Opus 8.1 software was applied to: (i) remove eventual H 2 O and CO 2 contributions and (ii) correct for the frequency dependence of the electric field penetration depth in ATR (considering a mean refractive index of 1.25). The spectral data were imported into MatLab (v. R2021b, MathWorks, MA) and all computationsvector normalization to unit length (2-Norm), and baseline correction according to the automatic weighted least-squares algorithm (polynomial order = 2)were carried out using the PLS_Toolbox (v. 9.0, Eigenvector Research, WA) and in-house developed routines, as previously described. , Finally, the spectra were restricted to the fingerprint region (1800–800 cm –1 ), averaged (per replicate), and plotted.…”