To quantify the relationships between rice plant architecture parameters and the corresponding organ biomass, and to research on functional structural plant models of rice plant, this paper presented a biomass-based model of aboveground architectural parameters of rice (Oryza sativa L.) in the young seedling stage, designed to explain effects of cultivars and environmental conditions on rice aboveground morphogenesis at the individual leaf level. Various model variables, including biomass of blade and blade length, were parameterized for rice based on data derived from an outdoor experiment with rice cv. Liangyou 108, 86You 8, Nanjing 43, and Yangdao 6. The organ dimensions of rice aboveground were modelled taking corresponding organ biomass as an independent variable. Various variables in rice showed marked consistency in observation and simulation, suggesting possibilities for a general rice architectural model in the young seedling stage. Our descriptive model was suitable for our objective. However, they can set the stage for connection to physiological model via biomass and development of functional structural rice models (FSRM), and start with the localized production and partitioning of assimilates as affected by abiotic growth factors. The finding of biomass-based rice architectural parameter models also can be used in morphological models of blade, sheath, and tiller of the other stages in rice life.
CAO Hong-xinLIU YanLIU Yong-xiaJim Scott HananYUE Yan-binZHU Da-weiLU Jian-feiSUN Jin-yingSHI Chun-linGE Dao-kuoWEI Xiu-fangYAO An-qingTIAN Ping-pingBAO Tai-lin
In this paper, the many indices used in validation of crop models, such as RMSE (root mean square errors), Sd (standard error of absolute difference), da (mean absolute difference), dap (ratio of da to the mean observation), r (correlation), and R2 (determination coefficient), are compared for the same rice architectural parameter model, and their advantages and disadvantages are analyzed. A new index for validation of crop models, dap between the observed and the simulated values, is proposed, with dap<5% as the suggested standard for precision of crop models. The different kinds of validation methods in crop models should be combined in the following aspects:(1) calculating da and dap; (2) calculating the RMSE or Sd; (3) calculating r and R2, at the same time, plotting 1:1 diagram.
CAO Hong-xinJim Scott HananLIU YanLIU Yong-xiaYUE Yan-binZHU Da-weiLU Jian- feiSUNJin-yingSHI Chun-linGE Dao-kuoWEI Xiu-fangYAO An-qingTIAN Ping-pingBAO Tai-lin
