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
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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
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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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