中文摘要：

叶水势是作物水分状况的最佳度量,是灌溉决策的重要依据。依据Penman-Monteith蒸腾算式计算或依据遥感数据反演的方法因机理算式复杂、待定参数多、可移植性差、测量成本高等原因,难以推广应用。因此,选取易于获取的作物微环境因子作为辅助变量,建立了基于RBF网络的夏玉米叶水势软测量模型,并进行了仿真研究。仿真结果表明,该方法简单实用,估算精度较高,是一种在线估算田间作物水分状况的有效措施。

英文摘要：

Leaf water potential is the best parameter of estimating plant water status and is the important basis for irrigating decision.Evaluation from Penman-Monteith transpiration formula or retrieval from remote sensing data has complex calculations,too many parameters,poor transplantations,high costs and too many difficulties to widen it.This paper selects accessible micro-environment factors of plant as auxiliary variables,and establishes a leaf water potential soft-sensing model with RBF neural network.Simulation result shows that this model is simple and practical,and has higher accuracy.It is one of effective methods estimating field plant water status on line.