Modelling photo-modulated internode elongation in growing glasshouse cucumber canopies.
• Growing glasshouse plant canopies are exposed to natural fluctuations in light quantity, and the dynamically changing canopy architecture induces local variations in light quality. This modelling study aimed to analyse the importance of both light signals for an accurate prediction of individual internode lengths. • We conceptualized two model approaches for estimating final internode lengths (FILs). The first one is only photosynthetically active radiation (PAR)-sensitive and ignores canopy architecture, whereas the second approach uses a functional-structural growth model for considering variations in both PAR and red : far-red (R : FR) ratio (L-Cucumber). Internode lengths measured in three experiments were used for model parameterization and evaluation. • The overall trends for the simulated FILs using the exclusively PAR-sensitive model approach were already in line with the measured FILs, but they underestimated FILs at higher ranks. L-Cucumber provided considerably better FIL predictions under various light conditions and canopy architectures. • Both light signals are needed for an accurate estimation of the FILs, and only L-Cucumber is able to consider R : FR signals from the growing canopy. Yet this study highlights the significance of the PAR signal for predicting FILs as neighbour effects increase, which indicates a potential role of photosynthate signalling in internode elongation.
Institute of Biological Production Systems, Leibniz Universität Hannover, Hannover, Germany. kahlen@gem.uni-hannover.de
Katrin
K
Kahlen
Hartmut
H
Stützel
D003198:Computer Simulation; D018553:Cucumis sativus / Q000254:growth & development* / Q000528:radiation effects*; D008027:Light; D008954:Models, Biological; D010788:Photosynthesis / Q000528:radiation effects; D018515:Plant Leaves / Q000254:growth & development* / Q000528:radiation effects; D018547:Plant Stems / Q000254:growth & development* / Q000528:radiation effects*; D013997:Time Factors