Retrieving chlorophyll content and equivalent water thickness of Moso bamboo(Phyllostachys pubescens) forests under Pantana phyllostachysae Chao-induced stress from Sentinel-2A/B images in a multiple LUTs-based PROSAIL framework

Biochemical components of Moso bamboo(Phyllostachys pubescens)are critical to physiological and ecological processes and play an important role in the material and energy cycles of the ecosystem.The coupled PROSPECT with SAIL(PROSAIL)radiative transfer model is widely used for vegetation biochemical component content inversion.However,the presence of leaf-eating pests,such as Pantana phyllostachysae Chao(PPC),weakens the performance of the model for estimating biochemical components of Moso bamboo and thus must be considered.Therefore,this study considered pest-induced stress signals associated with Sentinel-2A/B images and field data and established multiple sets of biochemical canopy reflectance look-up tables(LUTs)based on the PROSAIL framework by setting different parameter ranges according to infestation levels.Quantitative inversions of leaf area index(LAI),leaf chlorophyll content(LCC),and leaf equivalent water thickness(LEWT)were derived.The scale conversions from LCC to canopy chlorophyll content(CCC)and LEWT to canopy equivalent water thickness(CEWT)were calculated.The results showed that LAI,CCC,and CEWT were inversely related with PPC-induced stress.When applying multiple LUTs,the p-values were<0.01;the R2 values for LAI,CCC,and CEWT were 0.71,0.68,and 0.65 with root mean square error(RMSE)(normalized RMSE,NRMSE)values of 0.38(0.16),17.56μg cm-2(0.20),and 0.02 cm(0.51),respectively.Compared to the values obtained for the traditional PROSAIL model,for October,R2 values increased by 0.05 and 0.10 and NRMSE decreased by 0.09 and 0.02 for CCC and CEWT,respectively and RMSE decreased by 0.35μg cm-2 for CCC.The feasibility of the inverse strategy for integrating pest-induced stress factors into the PROSAIL model,while establishing multiple LUTs under different pest-induced damage levels,was successfully demonstrated and can potentially enhance future vegetation parameter inversion and monitoring of bamboo forest health and ecosystems.

RhizoVision Crown:An Integrated Hardware and Software Platform for Root Crown Phenotyping

Root crown phenotyping measures the top portion of crop root systems and can be used for marker-assisted breeding,genetic mapping,and understanding how roots influence soil resource acquisition.Several imaging protocols and image analysis programs exist,but they are not optimized for high-throughput,repeatable,and robust root crown phenotyping.The RhizoVision Crown platform integrates an imaging unit,image capture software,and image analysis software that are optimized for reliable extraction of measurements from large numbers of root crowns.The hardware platform utilizes a backlight and a monochrome machine vision camera to capture root crown silhouettes.The RhizoVision Imager and RhizoVision Analyzer are free,open-source software that streamline image capture and image analysis with intuitive graphical user interfaces.The RhizoVision Analyzer was physically validated using copper wire,and features were extensively validated using 10,464 groundtruth simulated images of dicot and monocot root systems.This platform was then used to phenotype soybean and wheat root crowns.A total of 2,799 soybean(Glycine max)root crowns of 187 lines and 1,753 wheat(Triticum aestivum)root crowns of 186 lines were phenotyped.Principal component analysis indicated similar correlations among features in both species.The maximum heritability was 0.74 in soybean and 0.22 in wheat,indicating that differences in species and populations need to be considered.The integrated RhizoVision Crown platform facilitates high-throughput phenotyping of crop root crowns and sets a standard by which open plant phenotyping platforms can be benchmarked.