摘要
利用LI-6400便携式光合测定仪,在山东农业大学试验基地对冬小麦品种鲁麦23生理生态多项指标进行系统测定,在此基础上,从Jarvis和Ball-Berry模型中分别选取两种模型,利用最小二乘法对气孔导度参数进行拟合检验,并对模型预测效果进行统计分析和对比。结果表明,Ball-Berry模型2预测精度最高,其预测值与实测值的相关系数和均方根误差分别为0.625(P<0.01)和0.158mol.m-2.s-1,Jarvis模型1优于Jarvis模型2,Ball-Berry模型1预测效果最差,其预测值与实测值的相关系数和均方根误差分别为0.369(P<0.01)和0.235mol.m-2.s-1。4种模型在华北地区的适应性与长江中下游地区相比存在一定差异,因此需要在更多地区对气孔导度模型进行更深入研究,以期为土壤-植被-大气系统研究提供更为可靠的参考依据。
The eco-physiological indexes of winter wheat Lu 23 were systematically measured by using the LI - 6400 portable photosynthesis analyzer in Shandong Agricultural University. The parameters of several stomatal conductance models, which were selected from the Jarvis and Ball - Berry models, were fitted by using the least square method. Then the models were validated and compared. The results indicated that Ball - Berry model 2 performed the best with the highest correlation coefficient value of 0. 625 （P 〈 0. 01 ） and the lowest root mean squared error （RMSE） value of 0. 158 mol · m 2 . s 1. Meanwhile, Jarvis model 1 performed better than Jarvis model 2 and Ball - Berry model 1 performed the worst, with the lowest correlation coefficient value of 0. 369 （ P 〈 0.01 ） and the highest root mean squared error （RMSE） value of 0. 235 mol · m-2·s-1. The applicability of the four models was quite different from that in the Yangtze River delta, which meant further research on the applicability of stomatal conductance models in different regions was necessary to provide more reliable references for the future study on the SPAC.
出处
《中国农业气象》
CSCD
北大核心
2012年第3期412-416,共5页
Chinese Journal of Agrometeorology
基金
中国气象科学研究院基本科研业务费重点项目(2009Z002)
国家科技部科技支撑计划项目(2011BAD32B02)
关键词
华北地区
冬小麦
气孔导度模型
适应性
North China plain
Winter wheat
Stomatal conductance model
Applicability
