Journal
PLANT SOIL AND ENVIRONMENT
Volume 62, Issue 4, Pages 178-183Publisher
CZECH ACADEMY AGRICULTURAL SCIENCES
DOI: 10.17221/802/2015-PSE
Keywords
remote sensing; Oryza sativa; macroelement; environmental pollution; leaf nitrogen content
Categories
Funding
- National Natural Science Foundation of China [41127901]
- Program for Innovative Research Team in University of Ministry of Education of China [IRT1278]
Ask authors/readers for more resources
Paddy rice is one of the most important cereal crops in China. Nitrogen (N) is closely related to crops production by influencing the photosynthetic efficiency of paddy rice. In this study, laser-induced fluorescence (LIF) technology with the help of principal component analysis (PCA) and back-propagation neural network (BPNN) is proposed to monitor leaf N content (LNC) of paddy rice. The PCA is utilized to extract the characteristic variables of LIF spectra by analysing the major attributes. The results showed that the first three principal components (PCs) can explain 95.76% and 93.53% of the total variance contained in the fluorescence spectra for tillering stage and shooting stage, respectively. Then, BPNN was utilized to inverse the LNC on the basis of the first three PCs as input variables and can obtain the satisfactory inversion results (R-2 of tillering stage and shooting stage are 0.952 and 0.931, respectively; residual main range from -0.2 to 0.2 mg/g). The experimental results demonstrated that LIF technique combined with multivariate analysis will be a useful method for monitoring the LNC of paddy rice, which can provide consultations for the decision-making of peasants in their N fertilization strategies.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available