Simulating the physiological dynamics of winter wheat after grazing

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Harrison, M. T.
Evans, J. R.
Moore, A. D.

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Winter wheat can be grown for the dual purposes of livestock grazing and grain production. The development of cultivars capable of producing large quantities of both herbage and grain has recently increased the adoption of this farming practice in Australia. The objectives of this study were to (1) develop a model capable of accurately simulating the regrowth and grain production of winter wheat after grazing, and (2) apply the model to determine the primary mechanisms controlling crop growth rates after grazing. An existing crop model, SUCROS2 was extended with a defoliation subroutine. Dry matter accumulation was modified from leaf photosynthesis to a canopy radiation-use efficiency approach. Grazing was simulated as a reduction in shoot biomass and leaf area index. The proportion of shoot removed was weighted towards leaf biomass. Carbon allocation patterns following defoliation were shifted in favour of shoots and leaves, thus tending to restore genetically-determined 'target' root-shoot and leaf-shoot ratios. The model was calibrated using soil water, leaf, stem and kernel biomass measurements taken during an experiment conducted near Canberra, Australia. Simulations produced reliable estimates of leaf and stem biomass, however kernel biomass was underestimated when the crop was grazed. Simulated cumulative water use was greater than that observed for a period after grazing. This study revealed two main insights. First, compared to ungrazed wheat, grazed crops remained greener for longer, allowing them to continue growing much later in the season. Second, grazing delayed soil water use, allowing growth rates of grazed crops to exceed those of ungrazed crops. This occurred in late spring during a period of water stress, even though the leaf area and light interception of the grazed wheat was less than that of the ungrazed.

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Precision Agriculture 2009 - Papers Presented at the 7th European Conference on Precision Agriculture, ECPA 2009

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