宁夏灌区春小麦叶面积指数的动态模拟  

Dynamic simulation of spring wheat leaf area index in Ningxia irrigable area

作　　者：张学艺[1,2] 张磊[1] 黄峰[1] 刘静[1] 马国飞[1] 

机构地区：[1]宁夏气象防灾减灾重点试验室,宁夏银川750002 [2]南京信息工程大学,江苏南京210044

出　　处：《干旱地区农业研究》2011年第1期193-196,205,共5页Agricultural Research in the Arid Areas

基　　金：中国气象局气象行业科研专项(GYHY200806022);中国气象局重点支持省所科研项目(CMATG2007S06);科技部农业科技成果转化资金项目(2006GB24160429)

摘　　要：为实现宁夏春小麦产量动态预报技术的业务化,需获得LAI（Leaf Area Index,叶面积指数）这一关键参数,依据1994-2009年宁夏永宁国家一级农业试验站大田观测数据,研究了宁夏引黄灌区春小麦的LAI变化规律。对比分析了3个指标（生理日数、有效积温和日照时数）、3个阶段（三叶-抽穗、抽穗-乳熟、三叶-乳熟）、不同函数模拟宁夏春小麦LAI的动态变化过程。结果表明,对LAI和各指标变量归一化后,三叶-乳熟期用生理日数为指标变量的y=（a＋bx）/（1＋cx＋dx^2）模拟效果最好,常用的y=a/〔1＋exp（b＋cx＋dx^2）〕及Richard方程模拟效果并不理想;分阶段后的三叶-抽穗期模拟精度比三叶-乳熟期有明显提高,决定系数R2从0.90795提高到0.95796,均方根误差从0.10359提高到0.07612,精确度从0.9156提高到0.93351,准确度从0.9717提高到0.9848,且相关性都达到极显著水平（α=0.001）,这表明该方法可以很好地获得春小麦的LAI。In order to realize the prediction of dynamic yield of spring wheat in Ningxia,it is necessary to obtain the key parameters of LAI.Based on the field observation data of 1994～2009 from the Ningxia Yongning agricultural experiment station,the LAI dynamical law of spring wheat was studied.Three indexes and three stages and different functions were contrasted and analized.The results indicated that the formula y=（a＋bx）/（1＋cx＋dx^2） was the best form to simulate the LAI in 3-leaf stage to heading stage,in which the physical day was used as the argument after LAI and these indexes were normalized.But the simulated results from the y=a/（1＋exp（b＋cx＋dx^2）） and Richard formulas were not ideal.The simulating accuracy of 3-leaf to heading was noticeably higher than that of 3-leaf to maturity after the growth processes were divided into three stages.R2 was changed from 0.90795 to 0.95796,RMSE from 0.10359 to 0.07612,the accuracy from 0.9156 to 0.93351,the degree of accuracy from 0.9717 to 0.9848,and the α0.001,which indicated that this mean could better obtain spring wheat LAI,which provided a powerful method for the prediction of spring wheat yield in Ningxia irrigable area.

关 键 词：春小麦 叶面积指数 气象要素 动态模拟 归一化处理 

分 类 号：S512.12[农业科学—作物学]