Modeling Allometric Relationships in Leaves of Young Rapeseed (Brassica napus L.) Grown at Different Temperature Treatments.

2017 | journal article. A publication with affiliation to the University of Göttingen.

Jump to:Cite & Linked | Documents & Media | Details | Version history

Cite this publication

​Modeling Allometric Relationships in Leaves of Young Rapeseed (Brassica napus L.) Grown at Different Temperature Treatments.​
Tian, T.; Wu, L.; Henke, M.; Ali, B.; Zhou, W. & Buck-Sorlin, G.​ (2017) 
Frontiers in plant science8 art. 313​.​ DOI: https://doi.org/10.3389/fpls.2017.00313 

Documents & Media

License

Details

Authors
Tian, Tian; Wu, Lingtong; Henke, Michael; Ali, Basharat; Zhou, Weijun; Buck-Sorlin, Gerhard
Abstract
Functional-structural plant modeling (FSPM) is a fast and dynamic method to predict plant growth under varying environmental conditions. Temperature is a primary factor affecting the rate of plant development. In the present study, we used three different temperature treatments (10/14°C, 18/22°C, and 26/30°C) to test the effect of temperature on growth and development of rapeseed (Brassica napus L.) seedlings. Plants were sampled at regular intervals (every 3 days) to obtain growth data during the length of the experiment (1 month in total). Total leaf dry mass, leaf area, leaf mass per area (LMA), width-length ratio, and the ratio of petiole length to leaf blade length (PBR), were determined and statistically analyzed, and contributed to a morphometric database. LMA under high temperature was significantly smaller than LMA under medium and low temperature, while leaves at high temperature were significantly broader. An FSPM of rapeseed seedlings featuring a growth function used for leaf extension and biomass accumulation was implemented by combining measurement with literature data. The model delivered new insights into growth and development dynamics of winter oilseed rape seedlings. The present version of the model mainly focuses on the growth of plant leaves. However, future extensions of the model could be used in practice to better predict plant growth in spring and potential cold damage of the crop.
Issue Date
2017
Publisher
Frontiers Media S.A.
Journal
Frontiers in plant science 
ISSN
1664-462X
eISSN
1664-462X
Language
English

Reference

Citations


Social Media