With sub-optimum conditions the current representation of potential crop development patterns needs to be reconsidered (original) (raw)

Evaluation of a Metabolic Cotton Seedling Emergence Model

A model for cotton seedling emergence (MaGi) based on malate synthase kinetics was evaluated. Cotton seeds were planted through the early spring and into typical planting times for the areas. Soil temperatures at seed depth were used as inputs into MaGi and a commonly used seedling emergence model based on heat unit accumulation (DD60). Time to 50% emergence was calculated and compared with predicted emergence using MaGi and DD60. MaGi yielded predictive capability without the need to resort to lengthy experimentation required by traditional methods. The results suggest that a physiological or semi-empirical approach incorporating both enzyme kinetics and whole plant temperature responses would be useful for rapidly constructing seedling emergence models.

Modelling cotton plant development with L-systems: A template model for incorporating physiology

2005

Cotton (Gossypium hirsutum L.) has a complex architecture resulting from an intricate pattern of development, which strongly influences its ability to capture resources. Computational modelling can play a part in increasing our understanding of the processes intrinsic to the cotton cropping system at the level of individual branches, leaves and bolls. Such studies may be made for many different purposes, and this has a significant impact on the level of abstraction in the models of underlying function. Depending on whether the model is to be used for visualisation, for understanding the effects of processes at a population level, or for detailed examination of how physiology drives plant development, an appropriate model may be constructed with no functional interaction, with interaction between component types (eg. shoots and roots), or with interactions between all component modules in a plant.