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Root models are therefore an essential tool to identify key root traits for water efficient crops in a certain target cropping environment.
The statistical analysis showed that the behaviours of the generated data on density, water absorption and compressive strength can be adequately represented by linear, natural log and square root models, respectively.
Several structural functional root models have been published (e.g. SimRoot, Lynch et al. [1997] and R-SWMS, Dunbabin et al. [2013]) as well as other soil models (Reviewed in Hill et al. [2013]).
Our empirical analysis centers around the implementation of a series of simulation and prediction experiments, as well as a discussion of the stochastic properties of seasonal unit root models.
Based on the exact analytical solution of the singular stresses and electrical displacements near the crack front, the numerical method of the hypersingular integral equation is proposed by the finite-part integral method and boundary element method, which the square root models of the displacement and electric potential discontinuities in elements near the crack front are applied.
As shown in Table 2, the linear and square root models for the two summary scales yielded non-significant χ2 values and CFIs well above the acceptable level of.900, indicating very good model fit.
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The conceptual device of translocal is subsequently formulated as one conveying the traveling of ideas locally, which can enrich and root models-in-circulation.
cylinder diameter for the root model [m].
Various models have been proposed such as the logarithmic model, and cube root model.
(a) First, the root model is trained taking into account all training instances.
In the paper, the dynamic root model is simulated based on L-systems.
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