Diagnoses of rice nitrogen status based on spectral characteristics of leaf and canopy
The scanner and unmanned aerial vehicle (UAV) were adopted to take the leaf and canopy images, respectively. The images were corrected and applied to assess the rice nitrogen status on leaf level to canopy level by image analysis. The main results were as follows: 1) According to the analysis of rel...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Zhejiang University Press
2010-01-01
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| Series: | 浙江大学学报. 农业与生命科学版 |
| Subjects: | |
| Online Access: | https://www.academax.com/doi/10.3785/j.issn.1008-9209.2010.01.013 |
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| Summary: | The scanner and unmanned aerial vehicle (UAV) were adopted to take the leaf and canopy images, respectively. The images were corrected and applied to assess the rice nitrogen status on leaf level to canopy level by image analysis. The main results were as follows: 1) According to the analysis of relationship between the content of chlorophyll a and the color parameters, the effective color parameters were discovered as B, b, b/r+g), b/r, b/g. The regression was carried out on leaf level based on the distinctive characteristics in terms of color and shape. It was arranged in a particular form with C<sub>B</sub> calculated at YIQ color system. The accuracy of the model under different nitrogen rates was as follows: N0(0 kg N·hm<sup>-2</sup>)74.9%, N1(60 kg N·hm<sup>-2</sup>) 52%, N2(90 kg N·hm<sup>-2</sup>) 84.7%, N3(120 kg N·hm<sup>-2</sup>) 75%. 2) As far as the canopy level concerned, the synthesis characteristics were abstracted as G, B, b, g, b/(r+g), b/r, b/g, H, S, DGCI by calculating the relationship between the color parameters and nitrogen concentrations. The accuracy was as follows: N 0(0 kg N·hm<sup>-2</sup>)91.6%, N1(60 kg N·hm<sup>-2</sup>) 70.83%, N2(90 kg N·hm<sup>-2</sup>) 86.7%, N3(120 kg N·hm<sup>-2</sup>) 95%. The primary study indicated that the digital images taken from scanner and UAV could be applied to provide a cost-effective and accurate way to estimate rice nitrogen status. |
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| ISSN: | 1008-9209 2097-5155 |