Parameter sensitivity analysis of a root system architecture model based on virtual field sampling
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| Title: | Main Title: Parameter sensitivity analysis of a root system architecture model based on virtual field sampling |
| Description: | Abstract: Aims: Traits of the plant root system architecture (RSA) play a key role in crop performance. Therefore, architectural root traits are becoming increasingly important in plant phenotyping. In this study, we use a mathematical model to investigate the sensitivity of characteristic root system measures, obtained from different classical field root sampling schemes, to RSA parameters. Methods: Root systems of wheat and maize were simulated and sampled virtually to mimic real field experiments using the root system architecture (RSA) model CRootBox. By means of a sensitivity analysis, we found RSA parameters that significantly influenced the virtual field sampling results. To identify correlations between sensitivities, we carried out a principal component analysis. Results: We found that the parameters of zero order roots are the most sensitive, and parameters of higher order roots are less sensitive. Moreover, different characteristic root system measures showed different sensitivity to RSA parameters. RSA parameters that could be derived independently from different types of field observations were identified. Conclusions: Selection of characteristic root system measures and parameters is essential to reduce the problem of parameter equifinality in inverse modeling with multi-parameter models and is an important step in the characterization of root traits from field observations. |
| Citation Advice: | Morandage S, Schnepf A, Leitner D, Javaux M, Vereecken H, Vanderborght J (2019) Parameter sensitivity analysis of a root system architecture model based on virtual field sampling. Plant and Soil 438: 101-126. doi: 10.1007/s11104-019-03993-3. |
Responsible Party
| Creators: | Shehan Morandage (Author), Andrea Schnepf (Principal Investigator), Jan Vanderborght (Principal Investigator), Harry Vereecken (Author), Mathieu Javaux (Author) |
| Publisher: | SpringerLink |
| Publication Year: | 2019 |
Topic
| TR32 Topic: | Vegetation |
| Related Subproject: | B4 |
| Subjects: | Keywords: Root System, Root Length Density |
| Geogr. Information Topic: | Farming |
File Details
| Filename: | Morandage2019_Article_ParameterSensitivityAnalysisOf.pdf |
| Data Type: | Text - Article |
| File Size: | 4.7 MB |
| Date: | Available: 12.06.2019 |
| Mime Type: | application/pdf |
| Language: | English |
| Status: | Completed |
Constraints
| Download Permission: | Free |
| General Access and Use Conditions: | According to the TR32DB data policy agreement. |
| Access Limitations: | According to the TR32DB data policy agreement. |
| Licence: | None |
Geographic
Specific Information - Publication
| Publication Status: | Published |
| Review Status: | Peer reviewed |
| Publication Type: | Article |
| Article Type: | Journal |
| Source: | Plant and Soil |
| Source Website: | https://link.springer.com/journal/11104 |
| Issue: | 1-2 |
| Volume: | 438 |
| Number of Pages: | 26 (101 - 126) |
Metadata Details
| Metadata Creator: | Shehan Morandage |
| Metadata Created: | 12.06.2019 |
| Metadata Last Updated: | 12.06.2019 |
| Subproject: | B4 |
| Funding Phase: | 3 |
| Metadata Language: | English |
| Metadata Version: | V50 |
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| Page Visits: | 650 |
| Metadata Downloads: | 0 |
| Dataset Downloads: | 2 |
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