基于微环境因子的夏玉米叶水势软测量  

Soft-sensing for Leaf Water Potential of Summer Corn Based on Micro-environment Factors

作　　者：代方远[1] 卢胜利[1] 潘艳梅[1] 

机构地区：[1]天津职业技术师范大学自动化与电气工程学院,天津300222

出　　处：《节水灌溉》2010年第9期19-23,共5页Water Saving Irrigation

基　　金：国家自然科学基金资助项目(60772167)

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。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.

关 键 词：SPAC 叶水势 环境因子 精准灌溉 软测量 RBF网络 

分 类 号：S513[农业科学—作物学] TP273.24[自动化与计算机技术—检测技术与自动化装置]