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| Content Provider | Springer Nature : BioMed Central |
|---|---|
| Author | Xiang, Shuang Jin, Zhongyu Li, Jinpeng Yu, Fenghua Xu, Tongyu |
| Abstract | The radiative transfer model of vegetation leaves simulates the transmission mechanism of light inside the vegetation and simulates the reflectivity of blades according to the change law of different components in the process of plant growth. Based on the PIOSL model, this paper combines PIOSL with the structure of rice leaves to construct a radiation transfer model for rice leaves. The parameters of each layer of the RPIOSL model are determined by the Non-dominated Sorting Genetic Algorithm-III. (NSGA-III.) algorithm. The reflectance spectra of 218 rice leaf samples in different periods were simulated using the RPIOSL model. The results show that the mean (RMSE) between the simulated and measured spectra of the constructed RPIOSL model is 0.1074, which is 0.0191 lower than that of the PROSPECT model. Among them, the spectral simulation effect of RPIOSL model in yellow and red light band is the best, and the RMSE at tillering period, jointing period, heading period and grouting period are 0.0584, 0.0576, 0.0724 and 0.0820, respectively. Therefore, the establishment of the RPIOSL model can accurately describe the interaction mechanism between light, which is of great significance for the rapid acquisition of rice growth information and accurate crop management. |
| Related Links | https://plantmethods.biomedcentral.com/counter/pdf/10.1186/s13007-023-01127-6.pdf |
| Ending Page | 19 |
| Page Count | 19 |
| Starting Page | 1 |
| File Format | HTM / HTML |
| ISSN | 17464811 |
| DOI | 10.1186/s13007-023-01127-6 |
| Journal | Plant Methods |
| Issue Number | 1 |
| Volume Number | 20 |
| Language | English |
| Publisher | BioMed Central |
| Publisher Date | 2024-01-03 |
| Access Restriction | Open |
| Subject Keyword | Plant Sciences Biological Techniques Rice Radiative transfer PIOSL Hyperspectral Reflectance |
| Content Type | Text |
| Resource Type | Article |
| Subject | Plant Science Biotechnology Genetics |
| Journal Impact Factor | 4.7/2023 |
| 5-Year Journal Impact Factor | 5.6/2023 |
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