Hyperspectral estimation of photosynthetic pigment contents of summer maize leaves
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DOI:10.7606/j.issn.1000-7601.2019.04.24
Key Words: summer maize  photosynthetic pigments  hyperspectral estimation  random forests  Guanzhong district
Author NameAffiliation
LUO Li-li College of Nature Resources and Environment, Northwest A&F University,Yangling, Shaanxi 712100, China 
CHANG Qing-rui College of Nature Resources and Environment, Northwest A&F University,Yangling, Shaanxi 712100, China 
WU Xu-mei College of Nature Resources and Environment, Northwest A&F University,Yangling, Shaanxi 712100, China 
YANG Jing College of Nature Resources and Environment, Northwest A&F University,Yangling, Shaanxi 712100, China 
LI Fen-ling College of Nature Resources and Environment, Northwest A&F University,Yangling, Shaanxi 712100, China 
WANG Qi College of Nature Resources and Environment, Northwest A&F University,Yangling, Shaanxi 712100, China 
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Abstract:
      To realizing the rapid and non-destructive detection of photosynthetic pigment content of summer maize, the spectral reflectance characteristics of maize leaf with different total pigment contents were studied by taking “Dafeng 26” of summer maize in Guanzhong district of Shaanxi Province as the research object. First, 15 spectral parameters with good correlation of chlorophyll a, chlorophyll b, carotenoids and total pigments are extracted. Then, the estimation models of photosynthetic pigments were established by single variable regression, multiple stepwise regression and random forest regression analysis, respectively. The results showed that the estimation model of photosynthetic pigments based on random forest had the highest accuracy. Specifically, the R2 of fitting model of chlorophyll a, chlorophyll b and carotenoids was 0.93, the R2 of fitting model of total pigments was 0.92, the R2 of validation model of chlorophyll a and carotenoids was 0.74, and the R2 of validation model of chlorophyll b and total pigments was 0.71. The RMSE and RE of each model are similar. The fitting accuracy from high to low was the RF model of chlorophyll a, carotenoids, total pigments and chlorophyll b, respectively. The study constructed a high-precision RF estimation model of photosynthetic pigments, which has application and population value.
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