Leaf development stages and ontogenetic changes in passionfruit (Passiflora edulis Sims.) are detected by narrowband spectral signal

Fernandes, Amanda Mendes; Fortini, Evandro Alexandre; Müller, Larissa Areal de Carvalho; Batista, Diego Silva; Vieira, Luciana Marques; Silva, Priscila Oliveira; Amaral, Cibele Hummel do; Poethig, R. Scott; Otoni, Wagner Campos

doi:10.1016/j.jphotobiol.2020.111931

Cited by 22 publications

(26 citation statements)

References 63 publications

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“…On the other hand, by reducing the energy distribution to the ground diameter accordingly, the seedlings used as much photosynthetic product as possible for vertical growth to obtain more lights from their crown width; this could be interpreted as a growth strategy for rapid resource acquisition and consumption. However, longterm exposure to insufficient light directly inhibits the seedling growth rate and carbon accumulation; hence, seedlings tend to adopt conservative growth strategies for slow resource acquisition and consumption [77]. Our results demonstrate that moderate light intensity was beneficial to the production of secondary needles (mature foliage), which were conducive to seedling growth.…”

Section: Discussionmentioning

confidence: 71%

Morphological and Physiological Responses of Pinus massoniana Seedlings to Different Light Gradients

Wang

et al. 2021

Forests

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Light intensity is a critical factor regulating photosynthetic capacity in plants. However, the effects of varying light intensity on morphological and photoprotective mechanisms in Pinus massoniana seedlings have not been explored in depth, especially those in the first seedling growing season. We measured the growth, photosynthetic physiology, biochemistry, and chlorophyll fluorescence of P. massoniana seedlings at four light gradients: 100% relative irradiance (RI, full sunlight), 70% RI, 50% RI, and 20% RI. The seedling height at 70% RI was 9.27% higher than that at 100% RI. However, seedling height was inhibited under low light intensity; at 20% RI, all seedlings died. The decreasing light intensity inhibited ground diameter growth but increased the height-diameter ratio. The secondary needle emergence rate was 53.4% higher at 70% RI than at 100% RI but was only 2% at 50% RI. The chlorophyll and carotenoid contents increased significantly with decreasing light intensity. The increased Chl b and Car contents promoted the photoreceptor potential of the violet (400~420 nm), blue (440~480 nm), and yellow-orange (597~655 nm) regions in leaves. Among the chlorophyll fluorescence parameters, Fv/Fm, Fv′/Fm′, Y(II), qp, and ETR all reached maximum values at 70% RI but were significantly lower at 50% RI than at 100% RI. However, decreasing the light intensity caused a reduction in NPQ. The 70% RI level increased POD and SOD activity and the contents of osmotic regulation substances and slowed MDA accumulation. Seedlings at 70% RI had a higher growth rate, higher photosynthetic activity and potential, and significantly greater stress resistance than the other seedlings. Therefore, appropriate shading measures were beneficial to the cultivation of vigorous seedlings. Furthermore, spectral reflectance indexes were found to be a suitable tool for monitoring the photosynthetic physiological characteristics, stress resistance characteristics, and growth status of P. massoniana seedlings in real time.

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Section: Discussionmentioning

confidence: 71%

Morphological and Physiological Responses of Pinus massoniana Seedlings to Different Light Gradients

Wang

et al. 2021

Forests

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“…The precision of reflectance spectroscopy is further refined by selecting the most responsive wavelengths for analysis, given that different plant traits are more discernible at specific wavelengths [ 15 , 16 , 17 ]. This selection process is key to generating reliable and actionable data.…”

Section: Introductionmentioning

confidence: 99%

Reflectance Spectroscopy for the Classification and Prediction of Pigments in Agronomic Crops

Falcioni

Antunes

Demattê

et al. 2023

Plants

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Reflectance spectroscopy, in combination with machine learning and artificial intelligence algorithms, is an effective method for classifying and predicting pigments and phenotyping in agronomic crops. This study aims to use hyperspectral data to develop a robust and precise method for the simultaneous evaluation of pigments, such as chlorophylls, carotenoids, anthocyanins, and flavonoids, in six agronomic crops: corn, sugarcane, coffee, canola, wheat, and tobacco. Our results demonstrate high classification accuracy and precision, with principal component analyses (PCAs)-linked clustering and a kappa coefficient analysis yielding results ranging from 92 to 100% in the ultraviolet–visible (UV–VIS) to near-infrared (NIR) to shortwave infrared (SWIR) bands. Predictive models based on partial least squares regression (PLSR) achieved R2 values ranging from 0.77 to 0.89 and ratio of performance to deviation (RPD) values over 2.1 for each pigment in C3 and C4 plants. The integration of pigment phenotyping methods with fifteen vegetation indices further improved accuracy, achieving values ranging from 60 to 100% across different full or range wavelength bands. The most responsive wavelengths were selected based on a cluster heatmap, β-loadings, weighted coefficients, and hyperspectral vegetation index (HVI) algorithms, thereby reinforcing the effectiveness of the generated models. Consequently, hyperspectral reflectance can serve as a rapid, precise, and accurate tool for evaluating agronomic crops, offering a promising alternative for monitoring and classification in integrated farming systems and traditional field production. It provides a non-destructive technique for the simultaneous evaluation of pigments in the most important agronomic plants.

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“…These sensors facilitate rapid data acquisition without the need for spatial context, making them highly efficient for large-scale or remote assessments. The flexibility and precision of non-imaging hyperspectral sensors enable the detection of subtle physiological changes, enhancing the capacity to monitor plant stress responses with exceptional accuracy [11,[18][19][20][21]. Consequently, these tools are invaluable for advancing our understanding of plant dynamics and improving agricultural practices.…”

Section: Introductionmentioning

confidence: 99%

Estimation of Biochemical Compounds in Tradescantia Leaves Using VIS-NIR-SWIR Hyperspectral and Chlorophyll a Fluorescence Sensors

Falcioni,

Oliveira,

Chicati

et al. 2024

Remote Sensing

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An integrated approach that utilises hyperspectral and chlorophyll a fluorescence sensors to predict biochemical and biophysical parameters represents a new generation of remote-sensing research. The main objective of this study was to obtain a detailed spectral profile that correlates with plant physiology, thereby enhancing our understanding and management of plant health, pigment profiles, and compound fingerprints. Leveraging datasets using non-imaging or passive hyperspectral and chlorophyll fluorescence sensors to collect data in Tradescantia species demonstrated significant differences in leaf characteristics with pigment concentrations and structural components. The main goal was to use principal component analysis (PCA) and partial least squares regression (PLS) methods to analyse the variations in their spectra. Our findings demonstrate a strong correlation between hyperspectral data and chlorophyll fluorescence, which is further supported by the development of hyperspectral vegetation indices (HVIs) that can accurately evaluate fingerprints and predict many compounds in variegated leaves. The higher the integrated analytical approach and its potential application in HVIs and fingerprints, the better the selection of wavelengths and sensor positions for rapid and accurate analysis of many different compounds in leaves. Nonetheless, limitations arose from the specificity of the data for the Tradescantia species, warranting further research across diverse plant types and compounds in the leaves. Overall, this study paves the way for more sustainable and informed agricultural practices through breakthroughs in the application of sensors to remote-sensing technologies.

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Leaf development stages and ontogenetic changes in passionfruit (Passiflora edulis Sims.) are detected by narrowband spectral signal

Cited by 22 publications

References 63 publications

Morphological and Physiological Responses of Pinus massoniana Seedlings to Different Light Gradients

Morphological and Physiological Responses of Pinus massoniana Seedlings to Different Light Gradients

Reflectance Spectroscopy for the Classification and Prediction of Pigments in Agronomic Crops

Estimation of Biochemical Compounds in Tradescantia Leaves Using VIS-NIR-SWIR Hyperspectral and Chlorophyll a Fluorescence Sensors

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