Needle‐ and Canopy‐Level Genetic Variation in Scots Pine ( <i>Pinus sylvestris</i> L.) Revealed by Hyperspectral Phenotyping Across Sites and Seasons

As an essential species across European forests, Scots pine (<i>Pinus sylvestris</i> L.) plays a vital ecological and economic role, yet its physiological variability underlying its adaptive potential remains underexplored. Understanding this intraspecific variability is crucial for uncovering the genetic basis of adaptation. Traditional genetic evaluations require large sample sizes and are time-consuming, whereas hyperspectral sensing/imaging enables rapid, nondestructive assessment of physiological traits across many individuals, facilitating more efficient exploration of adaptive variation. We assessed needle functional traits (NFTs) linked to foliar structure, water content, and pigment composition in clonal seed orchards over two seasons, integrating hyperspectral measurements at needle and canopy levels with genotyping using a new 50 K single-nucleotide polymorphism (SNP) array. Linear mixed models revealed substantial genetic variation, with the carotenoid-to-total-chlorophyll ratio showing the highest heritability (0.29) among pigment traits, and structural/water-related traits reaching heritability values up to 0.38. Significant genetic correlations were observed between stress-related traits (pigment content, equivalent water thickness) and reflectance, suggesting that spectral traits could serve as proxies for indirect selection of adaptive traits or in breeding programs. Low genotype-by-environment interaction and stable clonal performance across years further underscore the reliability of these traits for identifying resilient genotypes. Overall, our findings highlight hyperspectral phenotyping and NFTs as promising tools for accelerating climate-adaptive breeding in Scots pine.

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Publication Details

Journal
Evolutionary Applications
Published
2025-11-01
DOI
https://doi.org/10.1111/eva.70176
Citations
2
Primary Topic
Remote Sensing in Agriculture
Type
article
Field-Weighted Citation Impact
3.43
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article

Needle‐ and Canopy‐Level Genetic Variation in Scots Pine ( Pinus sylvestris L.) Revealed by Hyperspectral Phenotyping Across Sites and Seasons

Zuzana Lhotáková, Milan Lstibůrek, Lucie Kupková, Adenan Yandra Nofrizal et al.
2 citations
Evolutionary Applications
Remote Sensing in Agriculture
3.43
article

Needle‐ and Canopy‐Level Genetic Variation in Scots Pine ( Pinus sylvestris L.) Revealed by Hyperspectral Phenotyping Across Sites and Seasons

Zuzana Lhotáková, Milan Lstibůrek, Lucie Kupková, Adenan Yandra Nofrizal, Petya Campbell, Salvador Alejandro Gezan, Jaroslav Klápště, Eva Neuwirthová, Jaroslav J Čepl, Jan Stejskal, Lucie Červená, Jiří Korecký, Jon Kehlet Hansen, Jana Albrechtová, Daniel Provazník
article en
2 citations

Abstract

As an essential species across European forests, Scots pine (<i>Pinus sylvestris</i> L.) plays a vital ecological and economic role, yet its physiological variability underlying its adaptive potential remains underexplored. Understanding this intraspecific variability is crucial for uncovering the genetic basis of adaptation. Traditional genetic evaluations require large sample sizes and are time-consuming, whereas hyperspectral sensing/imaging enables rapid, nondestructive assessment of physiological traits across many individuals, facilitating more efficient exploration of adaptive variation. We assessed needle functional traits (NFTs) linked to foliar structure, water content, and pigment composition in clonal seed orchards over two seasons, integrating hyperspectral measurements at needle and canopy levels with genotyping using a new 50 K single-nucleotide polymorphism (SNP) array. Linear mixed models revealed substantial genetic variation, with the carotenoid-to-total-chlorophyll ratio showing the highest heritability (0.29) among pigment traits, and structural/water-related traits reaching heritability values up to 0.38. Significant genetic correlations were observed between stress-related traits (pigment content, equivalent water thickness) and reflectance, suggesting that spectral traits could serve as proxies for indirect selection of adaptive traits or in breeding programs. Low genotype-by-environment interaction and stable clonal performance across years further underscore the reliability of these traits for identifying resilient genotypes. Overall, our findings highlight hyperspectral phenotyping and NFTs as promising tools for accelerating climate-adaptive breeding in Scots pine.

Evolutionary ApplicationsVol. 18(11)
University of Copenhagen (DK), Goddard Space Flight Center (US), Czech University of Life Sciences Prague (CZ), Charles University (CZ), VSN International (United Kingdom) (GB), Mount Medical Centre (AU), University of Maryland, Baltimore County (US)
Openalex Percentile: Top 7%
Remote Sensing in Agriculture
3.43
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