研究目的
Advancing the PROSPECT-5 model to simulate the spectral reflectance of copper-stressed leaves by adding copper content as an input variable and estimating the specific absorption coefficient related to copper.
研究成果
The modified PROSPECT-5 model, which includes copper content and a specific absorption coefficient for copper, provides more accurate simulations of spectral reflectance for copper-stressed leaves compared to the original PROSPECT-5 model. This advancement supports remote sensing applications for monitoring copper stress in vegetation, with potential uses in mineral prospecting and environmental pollution monitoring. However, further validation with larger datasets and integration with canopy models are needed.
研究不足
The study is limited by the small sample size (33 groups), which may affect the robustness of the estimated Kcu. The model is empirical and not fully physical, as Kcu reflects overall effects of copper stress rather than just copper ion absorption. Future work should include more samples and investigate the mechanisms behind the absorption features. The model is at the leaf scale and does not account for canopy-level factors like LAI or view geometry.
1:Experimental Design and Method Selection:
The study modified the PROSPECT-5 model by incorporating copper content and estimating the specific absorption coefficient (Kcu) for copper. The methodology involved estimating leaf structure parameters (N) using reflectance in 400-510 nm to avoid copper absorption influence, and fitting Kcu using a merit function minimization approach.
2:Sample Selection and Data Sources:
Used 33 groups of datasets from copper-stressed wheat and pak choi leaves grown in controlled experiments with varying copper levels (25 to 4800 mg/kg in soil). Samples were divided into 22 for calibration and 11 for validation. A public dataset LOPEX93 was also used for comparison.
3:List of Experimental Equipment and Materials:
ASD FieldSpec FR spectroradiometer with Li-1800 integrating sphere, halogen lamp, spectrophotometer for pigment measurement, atomic absorption spectrophotometer for copper content, scanning electron microscope (KYKY-EM 3200), plastic pots, copper sulfate solutions, and various chemicals for biochemical analysis.
4:Experimental Procedures and Operational Workflow:
Plants were grown in copper-treated soil, spectral reflectance was measured using the spectroradiometer and integrating sphere, biochemical contents were measured post-reflectance using chemical methods, and SEM images were acquired for structural analysis. Data processing involved estimating N and Kcu, and validating the model with RMSE calculations.
5:Data Analysis Methods:
Statistical analysis including mean, standard deviation, coefficient of variation, and root mean square error (RMSE) for comparing simulated and measured spectra. Specific absorption coefficients were estimated using minimization of merit functions.
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