Abstract
Cereals and grasses adapt their structural development to environmental conditions and the resources available. The primary adaptive response is a variable degree of branching, called tillering in cereals. Especially for heterogeneous plant configurations the degree of tillering varies per plant. Functional–structural plant modeling (FSPM) is a modeling approach allowing simulation of the architectural development of individual plants, culminating in the emergent behavior at the canopy level. This paper introduces the principles of modeling tillering in FSPM, using (I) a probability approach, forcing the dynamics of tillering to correspond to measured probabilities. Such models are particularly suitable to evaluate the effect structural variables on system performance. (II) Dose–response curves, representing a measured or assumed response of tillering to an environmental cue. (III) Mechanistic approaches to tillering including control by carbohydrates, hormones, and nutrients. Tiller senescence is equally important for the structural development of cereals as tiller appearance. Little study has been made of tiller senescence, though similar concepts seem to apply as for tiller appearance.
Highlights
Production of branches is an important trait of many cereal plants such as wheat (Triticum aestivum) and rice (Oryza species)
This paper introduces the principles of modeling tillering in Functional–structural plant modeling (FSPM), using (I) a probability approach, forcing the dynamics of tillering to correspond to measured probabilities
We show how tiller appearance and senescence can be represented in FSPM and how internal and environmental regulation of tillering can be implemented
Summary
Cereals and grasses adapt their structural development to environmental conditions and the resources available. The primary adaptive response is a variable degree of branching, called tillering in cereals. Functional–structural plant modeling (FSPM) is a modeling approach allowing simulation of the architectural development of individual plants, culminating in the emergent behavior at the canopy level. This paper introduces the principles of modeling tillering in FSPM, using (I) a probability approach, forcing the dynamics of tillering to correspond to measured probabilities. Such models are suitable to evaluate the effect structural variables on system performance. (III) Mechanistic approaches to tillering including control by carbohydrates, hormones, and nutrients.Tiller senescence is important for the structural development of cereals as tiller appearance.
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