[show abstract][hide abstract] ABSTRACT: Plant population density (PPD) influences plant growth greatly. Functional-structural plant models such as GREENLAB can be used to simulate plant development and growth and PPD effects on plant functioning and architectural behaviour can be investigated. This study aims to evaluate the ability of GREENLAB to predict maize growth and development at different PPDs.
Two field experiments were conducted on irrigated fields in the North China Plain with a block design of four replications. Each experiment included three PPDs: 2.8, 5.6 and 11.1 plants m(-2). Detailed observations were made on the dimensions and fresh biomass of above-ground plant organs for each phytomer throughout the seasons. Growth stage-specific target files (a description of plant organ weight and dimension according to plant topological structure) were established from the measured data required for GREENLAB parameterization. Parameter optimization was conducted using a generalized least square method for the entire growth cycles for all PPDs and years. Data from in situ plant digitization were used to establish geometrical symbol files for organs that were then applied to translate model output directly into 3-D representation for each time step of the model execution.
The analysis indicated that the parameter values of organ sink variation function, and the values of most of the relative sink strength parameters varied little among years and PPDs, but the biomass production parameter, computed plant projection surface and internode relative sink strength varied with PPD. Simulations of maize plant growth based on the fitted parameters were reasonably good as indicated by the linearity and slopes similar to unity for the comparison of simulated and observed values. Based on the parameter values fitted from different PPDs, shoot (including vegetative and reproductive parts of the plant) and cob fresh biomass for other PPDs were simulated. Three-dimensional representation of individual plant and plant stand from the model output with two contrasting PPDs were presented with which the PPD effect on plant growth can be easily recognized.
This study showed that GREENLAB model has the ability to capture plant plasticity induced by PPD. The relatively stable parameter values strengthened the hypothesis that one set of equations can govern dynamic organ growth. With further validation, this model can be used for agronomic applications such as yield optimization.
Annals of Botany 06/2008; 101(8):1185-94. · 3.45 Impact Factor
[show abstract][hide abstract] ABSTRACT: Simplification of field measurement to reduce the time-consuming data collection for calibration is important to facilitate the application of the GREENLAB model. The effect of such simplifications on the accuracy of parameter values should be quantified in order to define to what extent simplifications are valid. This study introduced a new method for model parameter optimization with sparse data of maize using a multi-fitting technique, evaluated the effect of such simplifications on the parameter values, and validated the calibrated model with four independent field data sets. The results showed that coefficients of variance (CV) among different simplifications were below 15% for most parameter values. The parameter values of the beta function varied more compared with those of relative sink strength for different simplifications. Organ biomass under four different climate regimes was simulated based on parameter values optimized with a sparse dataset. Significant (P<0.05) deviations of simulation vs. observation correlations from the 1:1 relationship were only observed for internodes of second experiment in 2003. Thus, multi-fitting with sparse data can provide reasonable accuracy of parameter values.
Plant Growth Modeling and Applications, 2006. PMA '06. Second International Symposium on; 12/2006