| 黄瓜初花期光合速率主要影响因素分析与模型构建 |
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| 引用本文： | 张海辉,张珍,张斯威,胡瑾,辛萍萍,王智永. 黄瓜初花期光合速率主要影响因素分析与模型构建[J]. 农业机械学报, 2017, 48(6): 242-248 |
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| 作者姓名： | 张海辉 张珍 张斯威 胡瑾 辛萍萍 王智永 |
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| 作者单位： | College of Mechanical and Electronic Engineering, Northwest A&F University;Key Laboratory of Agricultural Internet of Things, Ministry of Agriculture,College of Mechanical and Electronic Engineering, Northwest A&F University;Key Laboratory of Agricultural Internet of Things, Ministry of Agriculture,College of Mechanical and Electronic Engineering, Northwest A&F University;Key Laboratory of Agricultural Internet of Things, Ministry of Agriculture,College of Mechanical and Electronic Engineering, Northwest A&F University;Key Laboratory of Agricultural Internet of Things, Ministry of Agriculture,College of Mechanical and Electronic Engineering, Northwest A&F University;Key Laboratory of Agricultural Internet of Things, Ministry of Agriculture and College of Mechanical and Electronic Engineering, Northwest A&F University;Key Laboratory of Agricultural Internet of Things, Ministry of Agriculture |
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| 基金项目： | 国家自然科学基金项目(31671587、31501224）和陕西省农业科技创新与攻关项目（2016NY-125） |
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| 摘 要： | 植物光合速率受生理、生态多种因素交互影响,分析提取主要影响因素是构建高效光合速率模型的基础。选取8个典型影响因素,以初花期的黄瓜植株为实验材料,设计光合速率嵌套实验,采用相关分析法分析各因素与光合速率的相关性,证明光子通量密度、CO_2浓度、温度、气孔导度和叶绿素含量与光合速率显著相关;提出了一种融合遗传算法的径向基函数(GA-RBF)神经网络光合速率建模方法,采用RBF神经网络构建光合速率模型,利用GA算法优化RBF神经网络的扩展速度。采用异校验方法分别对融合主要影响因素和全部因素的模型性能进行分析,结果表明融合主要影响因素的模型精度显著提高,光合速率预测值与实测值决定系数为0.997 6,最大绝对误差为1.008 6μmol/(m~2·s),平均绝对误差为0.350 9μmol/(m~2·s),在降低复杂度的同时提高了预测精度。
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| 关 键 词： | 光合速率 环境影响因素 相关分析 预测模型 RBF神经网络 |
| 收稿时间： | 2016-09-28 |
Analysis of Main Influencing Factors and Modeling of Photosynthetic Rate for Cucumber at Initial Flowering Stage |
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| ZHANG Haihui,ZHANG Zhen,ZHANG Siwei,HU Jin,XIN Pingping and WANG Zhiyong. Analysis of Main Influencing Factors and Modeling of Photosynthetic Rate for Cucumber at Initial Flowering Stage[J]. Transactions of the Chinese Society for Agricultural Machinery, 2017, 48(6): 242-248 |
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| Authors: | ZHANG Haihui ZHANG Zhen ZHANG Siwei HU Jin XIN Pingping WANG Zhiyong |
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| Abstract: | |
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| Keywords: | photosynthetic rate environmental impact factors correlation analysis prediction model RBF neural network |
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