Merging genomic control networks and soil-plant-atmosphere-continuum models

Advances in genomic science make it desirable to include genomic controls in soil-plant-atmosphere-continuum (SPAC) models by methods proposed in this paper. Molecular genetic concepts suggest that a differential equation similar to ones used in neural networks can be used to model single-gene elements of larger systems. Natural modifications to the equation incorporate temperature dependency. Multi-gene components based on this element function as Boolean logic gates, linear arithmetic units, delays, differentiators, integrators, oscillators, coincidence detectors, and bi-stable devices. Related genetic circuitry from real organisms is shown. Genomic integration with SPAC models entails whole-plant modeling with realistic morphology. Plants are networks of parts, iterated in time and space under genetic control, that induce and modulate conservative SPAC mass/energy flows. Network developmental rules can be stated as Lindenmayer grammars whose symbols represent plant parts programmed as software objects. A structure is presented for simulators based on these concepts. The discussion argues that prior object-oriented plant modeling approaches (i) do not reflect how plants actually develop morphologically and (ii) may represent processes in tactically unwise ways at a time when genomics is advancing knowledge of process interactions. Finally, genomics and expanding computing power redefine concepts of model “simplicity” and “complexity” to favor increased realism.