Discriminating trees species from the relationship between spectral reflectance and chlorophyll contents of mangrove forest in Malaysia

Zulfa, A.W.; Norizah, K.; Hamdan, O.; Zulkifly, Shahrizim; Faridah-Hanum, I.; Rhyma, P.P.

doi:10.1016/j.ecolind.2019.106024

Cited by 21 publications

(9 citation statements)

References 25 publications

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“…This indicated that the performance of discrimination of tree species from the second location was better than that of trees from the first location for these algorithms. Compared with other studies (Korpela et al 2011, Lang et al 2017, Zulfa et al 2020, although an accuracy rate of 100 percent was achieved for the classification of tree species (The second location), there existed a large number of misjudgments for A, B, and C species from the first location. This may be due to the single level of tree species spectra or the spectral noise.…”

Section: Tree Species Discrimination Modelscontrasting

confidence: 64%

Determination of Geographical Origin and Tree Species Using Vis-NIR and Chemometric Methods

Liu¹,

Via²,

Li³

et al. 2022

Forest Products Journal

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The variation of wood properties between different geographical origin and tree species has an important influence on end use applications. This study aimed to investigate the feasibility of wood origin and species classification based on visible and near infrared spectroscopy and chemometric methods. The influence of geographical origin on tree species identification also was analyzed. A total of 530 samples with 2 origins and 5 tree species were collected for analysis. The raw reflectance spectra were preprocessed by spectral transformation technique, and nonlinear discrimination models were built by support vector machine (SVM) using various spectral forms. Three algorithms—grid search (GS), genetic algorithm (GA), and particle swarm optimization (PSO)—were applied to optimize the parameters of SVM models, respectively. Regardless of spectral forms and optimization techniques, the prediction accuracy was lower than that of the calibration set for wood origin and tree species identification. Except for reflectance spectra, prediction accuracy of 100 percent was obtained based on SVM in combination with three algorithms for origin discrimination. However, SVM in combination with reflectance spectra and GS technique achieved the best prediction accuracy (93.18%) for tree species identification. These results demonstrated that visible and near infrared spectroscopy combined with chemometric techniques can be used for geographical origin and tree species determination.

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Section: Tree Species Discrimination Modelscontrasting

confidence: 64%

Determination of Geographical Origin and Tree Species Using Vis-NIR and Chemometric Methods

Liu¹,

Via²,

Li³

et al. 2022

Forest Products Journal

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“…It made the research more achievable and accurate. Previous studies [20,21,35] can also estimate chlorophyll concentration, but research objects were mostly single crops or densely covered areas with single vegetation type. Therefore, this study is meaningful to the analysis of urban vegetation growth environment and the estimation of important component parameters.…”

Section: Discussionmentioning

confidence: 99%

“…Reflectance spectroscopy technology can better combine pigment concentration and reflectance spectra of vegetation for cross-spatial-scale research. For example, Zulfa et al [20] and Zhao et al [21] identified the relationship between hyperspectral data and chlorophyll of mangrove species. Jesús et al [22] quantified the chlorophyll content of vegetation based on the hyperspectral index.…”

Section: Introductionmentioning

confidence: 99%

Effect of Dust Deposition on Chlorophyll Concentration Estimation in Urban Plants from Reflectance and Vegetation Indexes

Lin

Xü

et al. 2021

Remote Sensing

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Using reflectance spectroscopy to monitor vegetation pigments is a crucial method to know the nutritional status, environmental stress, and phenological phase of vegetation. Defining cities as targeted areas and common greening plants as research objects, the pigment concentrations and dust deposition amounts of the urban plants were classified to explore the spectral difference, respectively. Furthermore, according to different dust deposition levels, this study compared and discussed the prediction models of chlorophyll concentration by correlation analysis and linear regression analysis. The results showed: (1) Dust deposition had interference effects on pigment concentration, leaf reflectance, and their correlations. Dust was an essential factor that must be considered. (2) The influence of dust deposition on chlorophyll—a concentration estimation was related to the selected vegetation indexes. Different modeling indicators had different sensitivity to dust. The SR705 and CIrededge vegetation indexes based on the red edge band were more suitable for establishing chlorophyll-a prediction models. (3) The leaf chlorophyll concentration prediction can be achieved by using reflectance spectroscopy data. The effect of the chlorophyll estimation model under the levels of “Medium dust” and “Heavy dust” was worse than that of “Less dust”, which meant the accumulation of dust had interference to the estimation of chlorophyll concentration. The quantitative analysis of vegetation spectrum by reflectance spectroscopy shows excellent advantages in the research and application of vegetation remote sensing, which provides an important theoretical basis and technical support for the practical application of plant chlorophyll content prediction.

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“…The chlorophyll contents of plants were determined by UV spectrophotometry (UV-2600, Shimadzu Instruments Co., Ltd., Suzhou, China). The mixed solution of acetoneabsolute ethanol =1:1 was taken as the blank control, and the absorbance measured at the wavelengths of 645 nm and 663 nm, respectively [20,21]. The concentration of C a , C b , and C T (i.e., chlorophyll a, b, and total chlorophyll, mg•L −1 ) was calculated by the following formula.…”

Section: Determination Of Chlorophyll Contentsmentioning

confidence: 99%

Effects of Ficus carica L. Water Extract on Taxus cuspidata Sieb. et Zucc. Growth

Li,

Huang,

Yang

et al. 2023

Forests

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Our research group successfully designed the F. carica and Taxus cuspidata Sieb. et Zucc mixed forest, and confirmed that their interspecific relationship was stable and F. carica has a promoting effect on neighboring T. cuspidata growth. However, the promoting mechanism has not been elucidated. In this study, F. carica was used as the donor plant and T. cuspidata was used as the recipient plant. T. cuspidata seedlings were irrigated with F. carica root extracts of different concentrations (10.0, 20.0, 40.0 g·L−1), and the plant height, base diameter, photosynthetic parameters, photosynthetic pigments, MDA contents, and antioxidant enzyme activities were measured. Soil physical and chemical properties, enzyme activities, and microbial diversity were measured. The results showed that the abundance of growth-promoting bacteria increased and the number of pathogenic bacteria decreased in the rhizosphere of T. cuspidata soil. It was speculated that the chemicals secreted by F. carica roots interacted with soil microorganisms of T. cuspidata soil after enrichment, changed soil microbial diversity, and indirectly promoted the growth of T. cuspidata. UPLC-QTOF-MS/MS was used to analyze F. carica root water extract and F. carica root exudates, respectively, and it was found that the main components were similar. Therefore, the promoting effect of F. carica on T. cuspidata is mainly caused by the accumulation of potential chemicals in F. carica root exudates in the soil through interaction with soil microorganisms. Furthermore, the allelopathic-promoting mechanism of F. carica on T. cuspidata was discussed from various aspects, to provide a theoretical basis for the protection, breeding, and sustainable management of T. cuspidata resources.

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Discriminating trees species from the relationship between spectral reflectance and chlorophyll contents of mangrove forest in Malaysia

Cited by 21 publications

References 25 publications

Determination of Geographical Origin and Tree Species Using Vis-NIR and Chemometric Methods

Determination of Geographical Origin and Tree Species Using Vis-NIR and Chemometric Methods

Effect of Dust Deposition on Chlorophyll Concentration Estimation in Urban Plants from Reflectance and Vegetation Indexes

Effects of Ficus carica L. Water Extract on Taxus cuspidata Sieb. et Zucc. Growth

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