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作 者:杨再强[1,2] 黄川容[2] 费玉娟[2] 彭晓丹[2] 朱凯[2] 扎西才让
机构地区:[1]中国气象局兰州干旱气象研究所,兰州730020 [2]南京信息工程大学应用气象学院,南京210044 [3]青海省海东地区气象局,青海平安810600
出 处:《东北农业大学学报》2011年第11期70-77,共8页Journal of Northeast Agricultural University
基 金:干旱气象科学研究基金(IAM200901);江苏省科技支撑项目(BE2010734);公益性行业(气象)科研专项GYHY(QX)200906023;公益性行业(气象)科研专项GYHY(QX)201006028;南京信息工程大学科研基金(80127)
摘 要:试验于2009年5月~2010年3月间,在我国青海海东地区和江苏南京温室内分别设计番茄栽培试验,测定和分析作物气孔导度数据和环境数据,研究发现温室番茄气孔导度与叶片温度成正相关,与饱和水气压差和CO2浓度呈负相关,气孔导度与光合有效辐射相关不显著。在此基础上,构建基于Bp神经网络的温室番茄叶片气孔导度模拟模型。结果表明,模型对"苏粉8号"和"大红"品种的气孔导度日变化的模拟值与实测值间基于1 1线的决定系数(R2)分别为0.760和0.674,其回归估计标准误差(RMSE)分别为0.054和0.061 mol.m-2.s-1。研究建立的Bp神经网络模型模拟叶片气孔导度的精度明显高于Ball-berry模型。Experiments were carried out in greenhouse from May 2009 to March 2010 in Haidong region of Qinghai Province and Nanjing of Jiansu Province,wherein environmental and plant stomatal conductance data were collected and analyzed.Results indicated that there was a positive relationship between leaf stomatal conductance and the leaf temperature of tomato in greenhouse,and the stomatal conductance was negative relevant to CO2 concentration and vapor press deficit(VPD).There was no significant effect of photosynthetic active radiation(PAR) on the stomatal conductance.Then the model was established to simulate the stomatal conductance of based on bp artificial neural net(ANN).The determination coefficients(R2) between the simulations and measurements for the stomatal conductance daily change of cv."sufen 8" and cv.R2 were 0.760,and 0.674,respectively,and RMSE were 0.054 and 0.061 mol·m-2·s-1.The prediction accuracy of the Bp ANN based model is significantly higher than that of Ball-berry model.
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