Accurate assessment of canopy carotenoid content(CC_(x+c)C)in crops is central to monitor physiological conditions in plants and vegetation stress,and consequently supporting agronomic decisions.However,due to the ove...Accurate assessment of canopy carotenoid content(CC_(x+c)C)in crops is central to monitor physiological conditions in plants and vegetation stress,and consequently supporting agronomic decisions.However,due to the overlap of absorption peaks of carotenoid(C_(x+c))and chlorophyll(C_(a+b)),accurate estimation of carotenoid using reflectance where carotenoid absorb is challenging.The objective of present study was to assess CC_(x+c)C in winter wheat(Triticum aestivum L.)with ground-and aircraft-based hyperspectral measurements in the visible and near-infrared spectrum.In-situ hyperspectral reflectance were measured and airborne hyperspectral data were acquired during major growth stages of winter wheat in five consecutive field experiments.At the canopy level,a remarkable linear relationship(R^(2)=0.95,p<0.001)existed between C_(x+c) and Ca+b,and correlation between CC_(x+c)C and wavelengths within 400 to 1000 nm range indicated that CC_(x+c)C could be estimated using reflectance ranging from visible to near-infrared wavebands.Results of Cx+c assessment based on chlorophyll and carotenoid indices showed that red edge chlorophyll index(CI red edge)performed with the highest accuracy(R^(2)=0.77,RMSE=22.27μg/cm^(2),MAE=4.97μg/cm^(2)).Applying partial least square regression(PLSR)in CC_(x+c)C retrieval emphasized the significance of reflectance within 700 to 750 nm range in CC_(x+c)C assessment.Based on CI red edge index,use of airborne hyperspectral imagery achieved satisfactory results in mapping the spatial distribution of CC_(x+c)C.This study demonstrates that it is feasible to accurately assess CC_(x+c)C in winter wheat with red edge chlorophyll index provided that C_(x+c) correlated well with C_(a+b) at the canopy scale.it is therefore a promising method for CC_(x+c)C retrieval at regional scale from aerial hyperspectral imagery.展开更多
基金supported by the Fundamental Research Funds for the Provincial Universities of Zhejiang(Project No.GK229909299001-302)the National Natural Science Foundation of China(Project No.41901268)+1 种基金the Natural Science Foundation of Zhejiang Province(Project No.LQ19D010009)the Provincial Education Department General Scientific Research Items(Project No.Y202249845).
文摘Accurate assessment of canopy carotenoid content(CC_(x+c)C)in crops is central to monitor physiological conditions in plants and vegetation stress,and consequently supporting agronomic decisions.However,due to the overlap of absorption peaks of carotenoid(C_(x+c))and chlorophyll(C_(a+b)),accurate estimation of carotenoid using reflectance where carotenoid absorb is challenging.The objective of present study was to assess CC_(x+c)C in winter wheat(Triticum aestivum L.)with ground-and aircraft-based hyperspectral measurements in the visible and near-infrared spectrum.In-situ hyperspectral reflectance were measured and airborne hyperspectral data were acquired during major growth stages of winter wheat in five consecutive field experiments.At the canopy level,a remarkable linear relationship(R^(2)=0.95,p<0.001)existed between C_(x+c) and Ca+b,and correlation between CC_(x+c)C and wavelengths within 400 to 1000 nm range indicated that CC_(x+c)C could be estimated using reflectance ranging from visible to near-infrared wavebands.Results of Cx+c assessment based on chlorophyll and carotenoid indices showed that red edge chlorophyll index(CI red edge)performed with the highest accuracy(R^(2)=0.77,RMSE=22.27μg/cm^(2),MAE=4.97μg/cm^(2)).Applying partial least square regression(PLSR)in CC_(x+c)C retrieval emphasized the significance of reflectance within 700 to 750 nm range in CC_(x+c)C assessment.Based on CI red edge index,use of airborne hyperspectral imagery achieved satisfactory results in mapping the spatial distribution of CC_(x+c)C.This study demonstrates that it is feasible to accurately assess CC_(x+c)C in winter wheat with red edge chlorophyll index provided that C_(x+c) correlated well with C_(a+b) at the canopy scale.it is therefore a promising method for CC_(x+c)C retrieval at regional scale from aerial hyperspectral imagery.
