Comparison of two hyperspectral imaging and two laser-induced fluorescence instruments for the detection of zinc stress and chlorophyll concentration in bahia grass (Paspalum notatum Flugge.)

Schuerger, Andrew C.; Capelle, Gene A.; Benedetto, John A. Di; Mao, Chengye; Thai, Chi N.; Evans, Mark D; Richards, Jeffrey T.; Blank, Tim A; Stryjewski, Elizabeth C

doi:10.1016/s0034-4257(02)00181-5

Cited by 107 publications

(59 citation statements)

References 33 publications

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“…Schuerger et al [30] modeled zinc stress in bahia grass in controlled conditions and showed that NDVI and several other vegetation indices could be used to model zinc stress at certain levels. Sridhar et al [31] exposed Pteris vittata ferns to arsenic and chromium soil contamination in a controlled environment and found that a unique ratio of R 1110 /R 810 monitors structural changes in the fern due to Cr accumulation was not as successful in the As treated ferns.…”

Section: The Red Edgementioning

confidence: 99%

Spectroscopic Analysis of Arsenic Uptake in Pteris Ferns

2009

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Two arsenic-accumulating Pteris ferns (Pteris cretica mayii and Pteris multifida), along with a non-accumulating control fern (Nephrolepis exaltata) were grown in greenhouse conditions in clean sand spiked with 0, 20, 50, 100 and 200 ppm sodium arsenate. Spectral data were collected for each of five replicates prior to harvest at 4-week intervals. Fern samples were analyzed for total metals content and Partial Least Squares and Stepwise Linear Regression techniques were used to develop models from the spectral data. Results showed that Pteris cretica mayii and Pteris multifida are confirmed hyperaccumulators of inorganic arsenic and that reasonably accurate predictive models of arsenic concentration can be developed from the first derivative of spectral reflectance of the hyperaccumulating Pteris ferns. Both the arsenic uptake and spectral results indicate that there is some species-specific variability but the results compare favorably with previously published data and additional research is recommended.

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Section: The Red Edgementioning

confidence: 99%

Spectroscopic Analysis of Arsenic Uptake in Pteris Ferns

2009

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“…The spectral reflectance (in SWIR regions at ∼1400 and ∼1900 nm) also influences by plant water content. Researchers have studied these spectral changes to relate them with phytoaccumulation of metals [Horler et al, 1980;Clevers and Kooistra, 2003;Schuerger et al, 2003;Clevers et al, 2004;Kooistra et al, 2004;Dunagan et al, 2007;Sridhar et al, 2007a,b;Su et al, 2007]. Most studies used various vegetation indices (ratios or linear combinations of two or more spectral wavelengths [Bannari et al, 1995]) and rededge position (a sharp transition between red and NIR wavelengths; positively related to chlorophyll concentration; [Horler et al, 1983;Dawson and Curran, 1998]) as an indication of plant stress.…”

Section: Introductionmentioning

confidence: 99%

Spectral changes in the leaves of barley plant due to phytoremediation of metals—results from a pot study

Rathod

Brackhage

Meer

et al. 2015

European Journal of Remote Sensing

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This research studied the changes in leaf reflectance spectra (350-2500 nm) due to metal phytoextraction into barley plants grown in metal-spiked soils (3 levels of Cd, Pb, As and their metal-mixture treatments). Growth of barley was adversely affected due to 100 mg As kg −1 and metal-mixture (10 Cd+150 Pb+100 As; mg kg) treatments. Metal phytoextraction were in order of: root >straw ≥leaves >grains. Results of reflectance spectra of leaves show the influence of As-treatment only, causing spectral changes in visible and infrared domains mostly, as apparent from the significant correlation between leaf-As and leaf-spectra. Chlorophyll and water stress indices and band depths analyses showed significant correlations to leaf-As, and can be used to distinguish metal-stressed plants.Finally, regression models demonstrate the potential use of hyperspectral reflectance data to monitor plant health during phytoremediation process and to estimate leaf-As in barley, particularly in this study.

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“…2017, 9,424 3 of 15 comprehensively analyze spatial-temporal variation in FAPAR based on the coupled model under different heavy metal conditions.…”

Section: Study Areamentioning

confidence: 99%

“…Some studies show that the heavy metal ions can influence the cell structure of plants and cause changes in physiological function, affecting the normal growth of crops [6,7]. Significantly, these changes can impair crop photosynthesis by affecting activity of photosynthetic enzymes and pigment content (chlorophyll) [8][9][10][11]. The fraction of absorbed photosynthetically active radiation (FAPAR), defined as the fraction of photosynthetically active radiation (PAR) absorbed by a green canopy in the 0.4-0.7 µm spectral range, has been proven to be effective for quantitative estimation of canopy analyze spatial-temporal variation in FAPAR based on the coupled model under different heavy metal conditions.…”

Section: Introductionmentioning

confidence: 99%

Estimating FAPAR of Rice Growth Period Using Radiation Transfer Model Coupled with the WOFOST Model for Analyzing Heavy Metal Stress

Zhou¹,

Liu²,

Zhao³

et al. 2017

Remote Sensing

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Timely assessment of crop growth conditions under heavy metal pollution is of great significance for agricultural decision-making and estimation of crop productivity. The object of this study is to assess the effects of heavy metal stress on physiological functions of rice through the spatial-temporal analysis of the fraction of absorbed photosynthetically active radiation (FAPAR). The calculation of daily FAPAR is conducted based on a coupled model consisting of the leaf-canopy radiative transfer model and World Food Study Model (WOFOST). These two models are connected by leaf area index (LAI) and a fraction of diffused incoming solar radiation (SKYL) in the rice growth period. The input parameters of the coupled model are obtained from measured data and GF-1 images. Meanwhile, in order to improve accuracy of FAPAR, the crop growth model is optimized by data assimilation. The validation result shows that the correlation between the simulated FAPAR and the measured data is strong in the rice growth period, with the correlation coefficients being above 7.5 for two areas. The discrepancy of FAPAR between two areas of different stress levels is visualized by spatial-temporal analysis. FAPAR discrepancy starts to appear in the jointing-booting period and experiences a gradual rise, reaching its maximum in the heading-flowering stage. This study suggests that the coupled model, consisting of the leaf-canopy radiative transfer model and the WOFOST model, is able to accurately simulate daily FAPAR during crop growth period and FAPAR can be used as a potential indicator to reflect the impact of heavy metal stress on crop growth.

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Comparison of two hyperspectral imaging and two laser-induced fluorescence instruments for the detection of zinc stress and chlorophyll concentration in bahia grass (Paspalum notatum Flugge.)

Cited by 107 publications

References 33 publications

Spectroscopic Analysis of Arsenic Uptake in Pteris Ferns

Spectroscopic Analysis of Arsenic Uptake in Pteris Ferns

Spectral changes in the leaves of barley plant due to phytoremediation of metals—results from a pot study

Estimating FAPAR of Rice Growth Period Using Radiation Transfer Model Coupled with the WOFOST Model for Analyzing Heavy Metal Stress

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