分枝是植物适应环境的主要形态发生过程。在草丛中,分耕种分为三个阶段:分耕种出苗,停止分till和till退耕。了解和预测分till过程是更好地控制谷物产量的主要挑战。在本文中,我们介绍并评估沃尔特,基于简单的自适应规则的基于个体的小麦模型,用于预测播种密度不同的分till动态。
WALTer模拟了冬小麦空中结构的三维(3-D)发育。分耕是使用两个主要假设进行建模的:(H1)当达到临界绿色面积指数(GAIc)时,植物会停止启动新的分till,和(H2),如果分till的光拦截低于阈值(PARt),则会发生分till的回归。营养器官的发育遵循从文献改编的描述性规则。进行了敏感性分析,以评估每个参数对分ill和GAI动力学的影响。WALTer使用初始数据集进行参数化和评估,该数据集提供了对GAI动力学的广泛描述,和另一个数据集描述了在宽范围的播种密度下的分till动态。
敏感性分析表明GAIc和PARt的主要重要性。WALTer很好地拟合了expt1的分级和GAI动力学。一旦根据expt2的农艺密度进行了校准,分till参数就可以在不同的播种密度下充分预测分till动力学。
使用简单的规则和少量的参数,WALTer有效地模拟了在实验数据中以对比密度观察到的小麦分till动力学。这些结果表明,临界GAI和PAR阈值的定义是一种相关的表示方法,分别,在争光的情况下停止分till和分till退耕。
Branching is a main morphogenetic process involved in the adaptation of plants to the environment. In grasses, tillering is divided into three phases: tiller emergence, cessation of tillering and tiller regression. Understanding and prediction of the tillering process is a major challenge to better control cereal yields. In this paper, we present and evaluate WALTer, an individual-based model of wheat built on simple self-adaptive rules for predicting the tillering dynamics at contrasting sowing densities.
WALTer simulates the three-dimensional (3-D) development of the aerial architecture of winter wheat. Tillering was modelled using two main hypotheses: (H1) a plant ceases to initiate new tillers when a critical Green Area Index (GAIc) is reached, and (H2) the regression of a tiller occurs if its interception of light is below a threshold (PARt). The development of vegetative organs follows descriptive rules adapted from the literature. A sensitivity analysis was performed to evaluate the impact of each parameter on tillering and GAI dynamics. WALTer was parameterized and evaluated using an initial dataset providing an extensive description of GAI dynamics, and another dataset describing tillering dynamics under a wide range of sowing densities.
Sensitivity analysis indicated the predominant importance of GAIc and PARt. Tillering and GAI dynamics of expt 1 were well fit by WALTer. Once calibrated based on the agronomic density of expt 2, tillering parameters allowed an adequate prediction of tillering dynamics at contrasting sowing densities.
Using simple rules and a small number of parameters, WALTer efficiently simulated the wheat tillering dynamics observed at contrasting densities in experimental data. These results show that the definition of a critical GAI and a threshold of PAR is a relevant way to represent, respectively, cessation of tillering and tiller regression under competition for light.