TR32-Database: Database of Transregio 32

[1684] - 3D Integrative Modelling and Upscaling of Root Water Uptake

All available metadata of the dataset are listed below. Some features are available, e.g. download of dataset or additional description file.

Features
Citation
Morandage, S., Schnepf, A., Vanderborght, J., 2016. 3D Integrative Modelling and Upscaling of Root Water Uptake. PhD Report, IBG-3, Forschungszentrum Jülich, Jülich,Germany. Accessed from http://www.tr32db.uni-koeln.de/data.php?dataID=1684 at 2017-12-15.
Identification
Title(s):Main Title: 3D Integrative Modelling and Upscaling of Root Water Uptake
Subtitle: Virtual experiments on root sampling methods to infer the specific root traits by inverse modelling
Alternative Title: PhD Report 1
Description(s):Abstract: The agricultural industry has been developed rapidly over past few decades to overcome the challenges in increasing global food demand and consumption. In order to maintain the increasing food demand, it is required to increase the crop yield under limited resources such as water, nutrient and land allocation. Understanding the interaction between plant and its surrounding environment is important to improve the plant productivity by enhancing ecological factors. Root water uptake, shoot growth and root growth rates are highly influenced by environmental conditions. Therefore, it is necessary to measure and monitor both aboveground and belowground variables over several growing seasons under different field conditions to obtain a wide range of experimental data for modelling and simulations of root water uptake processes. Ph.D. project on “3D Integrative Modelling and Upscaling of Root Water Uptake” aims to derive root water uptake functions in large-scale terrestrial models based on experimental data and modelling results. This research is conducted by the sub-project “B4” of Transregional Collaborative Research Centre 32 (TR32), which is funded by The Deutsche Forschungsgemeinschaft (DFG). Apart from the field experiments and modelling, the project on “Virtual experiments on root sampling methods to infer specific root traits” focuses on plant growth and sampling in a virtual environment. We will investigate classical sampling schemes to study the possibilities to determine specific sampling methods or combinations of methods to get information about specific traits, which will later be adapted in classical field sampling methods to infer phenotypic root traits. The innovative method can be used in field sampling schemes with specific interests in root system architecture (RSA), or to get information about the specific traits of different genotypes for plant breeding programs to develop new crop varieties to adapt different environments and field conditions.
Responsible Party
Creator(s):Author: Shehan Morandage
Principal Investigator: Andrea Schnepf
Principal Investigator: Jan Vanderborght
Publisher:CRC/TR32 Database (TR32DB)
Topic
TR32 Topic:Soil
Related Sub-project(s):B4
Subject(s):CRC/TR32 Keywords: Field Scale, Plant Function, Root, Root Growth, Root Length Density
Topic Category:Enviroment
File Details
File Name:1_PhD_Report_Shehan_Morandage.pdf
Data Type:Text
File Size:1333 kB (1.302 MB)
Date(s):Created: 2016-09-30
Mime Type:application/pdf
Data Format:PDF
Language:English
Status:Completed
Constraints
Download Permission:OnlyOwnSubproject
General Access and Use Conditions:According to the TR32DB data policy agreement.
Access Limitations:According to the TR32DB data policy agreement.
Geographic
North:50.86888
East:6.45034
South:50.86888
West:6.45034
Measurement Region:Ellebach
Measurement Location:Selhausen
Specific Informations - Report
Report Date:1st of March, 2016
Report Type:PhD Report
Report City:Jülich,Germany
Report Institution:IBG-3, Forschungszentrum Jülich
Number Of Pages:25
Period of Pages:1 - 25
Metadata Details
Metadata Creator:Shehan Morandage
Metadata Created:2017-07-25
Metadata Last Updated:2017-08-24
Subproject:B4
Funding Phase:3
Metadata Language:English
Metadata Version:V42
Dataset Metrics
Page Visits:78
Metadata Downloads:0
Dataset Downloads:0
Dataset Activity
Features