Claim · model-written summary
The three models had similar goodness of fit and prediction accuracy for wheat leaf area index and biomass.
- Taxon
- wheat
Triticum aestivumt0 - Outcome
- goodness of fit or prediction accuracye0
- Direction
- similare0
- Comparator
- modeling approachese0
Verbatim
e0“none of the modeling approaches clearly outperformed any other in terms of goodness of fit or prediction accuracy as indicated by similar posterior median values for root mean squared error (RMSE), Willmott’s agreement index (d), and Nash-Sutcliffe efficiency (NSE)”
t0“wheat growth”
Title
Pratishtha Poudel; Nora M. Bello; Romulo P. Lollato; et al. Field Crops Research 2022. doi:10.1016/j.fcr.2022.108549
Other claims from this paper (7)
- Method / resource ODE, linear, and nonlinear models had LAI RMSEp values of 1.38, 1.14, and 1.19, respectively.
- Method / resource ODE, linear, and nonlinear models had LAI dp values of 0.91, 0.93, and 0.93, respectively.
- Method / resource ODE, linear, and nonlinear models had LAI NSEp values of 0.69, 0.78, and 0.76, respectively.
- Method / resource ODE, linear, and nonlinear models had biomass RMSEp values of 274.08, 253.04, and 207.63, respectively.
- Method / resource ODE, linear, and nonlinear models had biomass dp values of 0.95, 0.95, and 0.97, respectively.
- Method / resource ODE, linear, and nonlinear models had biomass NSEp values of 0.82, 0.84, and 0.89, respectively.
- Method / resource The ODE model enabled biologically meaningful system-level inferences unavailable from the linear and nonlinear models.