Leaf Surface Reflectance Does Not Affect Biophysical Traits Modelling from VIS-NIR Spectra in Plants with Sparsely Distributed Trichomes

Neuwirthová, Eva; Lhotáková, Zuzana; Lukeš, Petr; Albrechtová, Jana

doi:10.3390/rs13204144

Cited by 3 publications

(1 citation statement)

References 64 publications

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“…2 A -D). Our finding is consistent with previous results obtained for the glabra1 mutant showing no significant difference in specular reflectance between this hairless line and the exo70H4-1 and arpc5 mutants, both bearing trichomes (Neuwirthová et al 2021).…”

Section: The Bidirectional Reflectance Function Of Leaves Typically F...supporting

confidence: 94%

Sensitive detection of chloroplast movements through changes in leaf cross-polarized reflectance

Hermanowicz,

Giza,

Łabuz

2023

Preprint

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We present a sensitive method for non-contact detection of chloroplast movements in leaves and other photosynthetic tissues, based on changes in the magnitude of cross-polarized reflectance of the leaf. We created a custom optical set-up and dedicated software for measurements of changes in red light reflectance during irradiation with blue light, known to trigger chloroplast relocations. Experiments on Arabidopsis thaliana wild type and several mutants with disrupted chloroplast movements showed that the chloroplast avoidance response, induced by high blue light, led to a substantial increase in diffuse reflectance of unpolarized red light. The effects of the accumulation response in low blue light were the opposite. The specular reflectance of the leaf was unaffected by the chloroplast positioning. To further improve the specificity of the detection, we examined the effects of chloroplast relocations on the leaf reflectance of a linearly polarized incident beam. The greatest relative change associated with chloroplast movements was observed when the planes of polarization of the incident and detected beams were perpendicular. This suggests that the chloroplast positioning affects the magnitude of depolarization of light. We applied the developed approach to examine chloroplast relocations in four angiosperm species collected in the field. In particular, the method allowed us to detect the chloroplast avoidance response in the green stems of bilberry before bud break. Such samples are not amenable to transmittance-based detection.

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Section: The Bidirectional Reflectance Function Of Leaves Typically F...supporting

confidence: 94%

Sensitive detection of chloroplast movements through changes in leaf cross-polarized reflectance

Hermanowicz,

Giza,

Łabuz

2023

Preprint

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Asymmetry of leaf internal structure affects PLSR modelling of anatomical traits using VIS-NIR leaf level spectra

Neuwirthová,

Lhotáková,

Červená

et al. 2023

European Journal of Remote Sensing

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Making the Genotypic Variation Visible: Hyperspectral Phenotyping in Scots Pine Seedlings

Stejskal,

Čepl,

Neuwirthová

et al. 2023

Plant Phenomics

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Hyperspectral reflectance contains valuable information about leaf functional traits, which can indicate a plant’s physiological status. Therefore, using hyperspectral reflectance for high-throughput phenotyping of foliar traits could be a powerful tool for tree breeders and nursery practitioners to distinguish and select seedlings with desired adaptation potential to local environments. We evaluated the use of 2 nondestructive methods (i.e., leaf and proximal/canopy) measuring hyperspectral reflectance in the 350- to 2,500-nm range for phenotyping on 1,788 individual Scots pine seedlings belonging to lowland and upland ecotypes of 3 different local populations from the Czech Republic. Leaf-level measurements were collected using a spectroradiometer and a contact probe with an internal light source to measure the biconical reflectance factor of a sample of needles placed on a black background in the contact probe field of view. The proximal canopy measurements were collected under natural solar light, using the same spectroradiometer with fiber optical cable to collect data on individual seedlings’ hemispherical conical reflectance factor. The latter method was highly susceptible to changes in incoming radiation. Both spectral datasets showed statistically significant differences among Scots pine populations in the whole spectral range. Moreover, using random forest and support vector machine learning algorithms, the proximal data obtained from the top of the seedlings offered up to 83% accuracy in predicting 3 different Scots pine populations. We conclude that both approaches are viable for hyperspectral phenotyping to disentangle the phenotypic and the underlying genetic variation within Scots pine seedlings.

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Leaf Surface Reflectance Does Not Affect Biophysical Traits Modelling from VIS-NIR Spectra in Plants with Sparsely Distributed Trichomes

Cited by 3 publications

References 64 publications

Sensitive detection of chloroplast movements through changes in leaf cross-polarized reflectance

Sensitive detection of chloroplast movements through changes in leaf cross-polarized reflectance

Asymmetry of leaf internal structure affects PLSR modelling of anatomical traits using VIS-NIR leaf level spectra

Making the Genotypic Variation Visible: Hyperspectral Phenotyping in Scots Pine Seedlings

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