The Effect of Leaf Stacking on Leaf Reflectance and Vegetation Indices Measured by Contact Probe during the Season

Neuwirthová, Eva; Lhotáková, Zuzana; Albrechtová, Jana

doi:10.3390/s17061202

Cited by 47 publications

(14 citation statements)

References 89 publications

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“…Changes in frond optical properties during the season depend on changes in pigment contents, anatomy, and senescence processes [ 57 ]. The reflectance curves of different specimens of the studied plants were very similar in April; however, in June, they differed significantly in some regions, which might be related to the radiation regime.…”

Section: Discussionmentioning

confidence: 99%

Frond Optical Properties of the Fern Phyllitis scolopendrium Depend on Light Conditions in the Habitat

Grašič

Sovdat

Gaberščik

2020

Plants

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Ferns display an elevated degree of phenotypic plasticity to changes in irradiance levels; however, only a few reports deal with their response to different light conditions. To get an insight into the extent of phenotypic plasticity of the fern Phyllitis scolopendrium, thriving in a forested area along a radiation gradient at the entrance of a cave, we examined selected biochemical, morphological, and physiological frond traits of the ferns from three different habitats. Sampling was performed two times during the vegetation season, in April and June. We also measured frond optical properties to point out the differences in leaf/light interactions between different plant samples. According to frond size, the middle habitat, receiving 125 µmol m−2s−1 of photosynthetically active radiation at both sampling times, appeared to be the most favourable. The production of UV-absorbing substances was highest in the habitat with the lowest radiation level. At the beginning of the season, the level of photosynthetic pigments in this habitat was the same as in the other habitats, while it was significantly lower in June when the tree canopy was closed. Frond reflectance was similar when comparing habitats and different sampling times. The most significant differences were obtained in the UV-A and near-infrared regions. The reflectance spectra depended mainly on frond biochemical properties, which altogether explained 54% (p ≤ 0.05) of the spectra variability. Frond transmittance depended on both, morphological parameters, explaining 51% (p ≤ 0.05), and frond biochemistry, explaining 73% (p ≤ 0.05) of the spectra variability. P. scolopendrium was revealed to be highly plastic regarding light conditions. The shapes of the frond reflectance and transmittance optical curves were similar to those typical of leaves of seed plants. The fronds exhibited high morphological plasticity when comparing different habitats. However, their biochemical and optical traits differed more between the two sampling times than between the habitats.

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Section: Discussionmentioning

confidence: 99%

Frond Optical Properties of the Fern Phyllitis scolopendrium Depend on Light Conditions in the Habitat

Grašič

Sovdat

Gaberščik

2020

Plants

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“…Natural orientation of leaves can result in shadowing of some leaves by others due to overlapping, which leads to lower leaf area estimates when the leaves are imaged while attached to the plant [66]. Overlapping of leaves also affects leaf spectral response, as it creates additional variability in the modes of reflectance that are usually different between fully exposed leaves, and shadowed leaves [67].…”

Section: Interaction Between Growth Traits and Spectral Reflectance Imentioning

confidence: 99%

Red-Green-Blue and Multispectral Imaging as Potential Tools for Estimating Growth and Nutritional Performance of Cassava under Deficit Irrigation and Potassium Fertigation

et al. 2021

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Cassava has high energy value and rich nutritional content, yet its productivity in the tropics is seriously constrained by abiotic stresses such as water deficit and low potassium (K) nutrition. Systems that allow evaluation of genotypes in the field and greenhouse for nondestructive estimation of plant performance would be useful means for monitoring the health of plants for crop-management decisions. We investigated whether the red–green–blue (RGB) and multispectral images could be used to detect the previsual effects of water deficit and low K in cassava, and whether the crop quality changes due to low moisture and low K could be observed from the images. Pot experiments were conducted with cassava cuttings. The experimental design was a split-plot arranged in a completely randomized design. Treatments were three irrigation doses split into various K rates. Plant images were captured beginning 30 days after planting (DAP) and ended at 90 DAP when plants were harvested. Results show that biomass, chlorophyll, and net photosynthesis were estimated with the highest accuracy (R2 = 0.90), followed by leaf area (R2 = 0.76). Starch, energy, carotenoid, and cyanide were also estimated satisfactorily (R2 > 0.80), although cyanide showed negative regression coefficients. All mineral elements showed lower estimation accuracy (R2 = 0.14–0.48) and exhibited weak associations with the spectral indices. Use of the normalized difference vegetation index (NDVI), green area (GA), and simple ratio (SR) indices allowed better estimation of growth and key nutritional traits. Irrigation dose 30% of pot capacity enriched with 0.01 mM K reduced most index values but increased the crop senescence index (CSI). Increasing K to 16 mM over the irrigation doses resulted in high index values, but low CSI. The findings indicate that RGB and multispectral imaging can provide indirect measurements of growth and key nutritional traits in cassava. Hence, they can be used as a tool in various breeding programs to facilitate cultivar evaluation and support management decisions to avert stress, such as the decision to irrigate or apply fertilizers.

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“…As mentioned above, the chlorophyll content differs across leaves; in addition, the content also varies across individual leaves. Chlorophyll is heterogeneously distributed within a leaf [48,49]. Other 2D-based imaging methods (such as hyper-spectral imaging) also estimate the chlorophyll content distribution within leaves [50,51].…”

Section: Resultsmentioning

confidence: 99%

Three-Dimensional Monitoring of Plant Structural Parameters and Chlorophyll Distribution

Itakura

Kamakura

Hosoi

2019

Sensors

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Image analysis is widely used for accurate and efficient plant monitoring. Plants have complex three-dimensional (3D) structures; hence, 3D image acquisition and analysis is useful for determining the status of plants. Here, 3D images of plants were reconstructed using a photogrammetric approach, called “structure from motion”. Chlorophyll content is an important parameter that determines the status of plants. Chlorophyll content was estimated from 3D images of plants with color information. To observe changes in the chlorophyll content and plant structure, a potted plant was kept for five days under a water stress condition and its 3D images were taken once a day. As a result, the normalized Red value and the chlorophyll content were correlated; a high R2 value (0.81) was obtained. The absolute error of the chlorophyll content estimation in cross-validation studies was 4.0 × 10−2 μg/mm2. At the same time, the structural parameters (i.e., the leaf inclination angle and the azimuthal angle) were calculated by simultaneously monitoring the changes in the plant’s status in terms of its chlorophyll content and structural parameters. By combining these parameters related to plant information in plant image analysis, early detection of plant stressors, such as water stress, becomes possible.

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The Effect of Leaf Stacking on Leaf Reflectance and Vegetation Indices Measured by Contact Probe during the Season

Cited by 47 publications

References 89 publications

Frond Optical Properties of the Fern Phyllitis scolopendrium Depend on Light Conditions in the Habitat

Frond Optical Properties of the Fern Phyllitis scolopendrium Depend on Light Conditions in the Habitat

Red-Green-Blue and Multispectral Imaging as Potential Tools for Estimating Growth and Nutritional Performance of Cassava under Deficit Irrigation and Potassium Fertigation

Three-Dimensional Monitoring of Plant Structural Parameters and Chlorophyll Distribution

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