title: [Detection of corn chlorophyll content using canopy spectral reflectance].
abstract: The canopy spectral reflectance and chlorophyll content of corn were measured and analyzed under different nitrogen treatments. The correlation between spectral reflectance and chlorophyll content was discussed based on different growth stages and different nitrogen levels. The results showed positive correlations under high and normal nitrogen treatment, while negative correlation under low nitrogen treatment. The relation between reflectance of normal fertilizer region and chlorophyll content was better than others, with r(Normal) > r(High) > r(Low). Normal fertilizer was the best condition to detect the corn chlorophyll content using spectral reflectance. Analysis of the relations at different growth stages showed that on the band of 400-1000 nm the absolute value of correlation coefficient increased and reached the maximum at shooting stage, it decreased until anthesis-silking stage, and then rebounded at milking stage. The positive correlations were found at shooting and milking stage, while negative correlations were found at seedling, trumpet and anthesis-silking stage. It was indicated that the sensitive stages to detect the chlorophyll content were shooting and trumpet stage with high absolute value of correlation coefficient above 0.6 around 550 nm. In order to detect the chlorophyll content of corn, 558, 667, 714 and 912 nm were selected to establish the MLR model and PLSR model. The results showed that PLSR was more capable of building chlorophyll content models reflecting correct relations among multi-variables compared with MLR. In the meanwhile, three wavelengths were selected (558, 667 and 714 nm) to build different vegetation indices such as GDVI, GRVI, GNDVI, DVI, RVI and NDVI. The correlation between DVI and chlorophyll con tent was better than others and DVI was used to establish binomial model and exponential model at shooting stage (R2 = 0.80) and trumpet stage (R2 = 0.66) respectively which was higher than PLSR It also provided a feasible method to detect chlorophyll content non-destructively.
authors.affiliation: Key Laboratory of Modern Precision Agriculture System Integration Research of Ministry of Education, China Agricultural University, Beijing 100083, China. honger102@163.com
authors.forename: Hong
authors.initials: H
authors.lastname: Sun
authors.forename: Min-zan
authors.initials: MZ
authors.lastname: Li
authors.forename: Yan-e
authors.initials: YE
authors.lastname: Zhang
authors.forename: Yong
authors.initials: Y
authors.lastname: Zhao
authors.forename: Hai-hua
authors.initials: HH
authors.lastname: Wang
mesh_terms: D002734:Chlorophyll / Q000032:analysis*; D005308:Fertilizers; D008962:Models, Theoretical; D009584:Nitrogen; D018515:Plant Leaves / Q000737:chemistry; D013057:Spectrum Analysis; D003313:Zea mays / Q000737:chemistry*
chemical_list: D005308:Fertilizers; D002734:Chlorophyll; D009584:Nitrogen