黄瓜叶片分布的异质性表型特征分析与模型建立

doi:10.19788/j.issn.2096-6369.190204

农业大数据学报 ›› 2019, Vol. 1 ›› Issue (2): 41-49.doi: 10.19788/j.issn.2096-6369.190204

黄瓜叶片分布的异质性表型特征分析与模型建立

钱婷婷^1,³,陆声链²,郑秀国^1,³,赵京音^1,³,王剑⁴,杨娟^1,^3,^*()

1.上海市农业科学院农业科技信息研究所,上海 201403
2.广西师范大学,桂林 541004
3.上海数字农业工程技术研究中心,上海 201403
4.北京市农业农村局信息中心,北京 100029

收稿日期:2019-04-12 出版日期:2019-06-26 发布日期:2019-08-21
通讯作者: 杨娟 E-mail:yangjuan@saas.sh.cn
作者简介:钱婷婷,女,博士,助理研究员,研究方向:作物模型;E-mail: saasqtt@163.com
基金资助:
国家自然科学基金项目(61762013);上海市农业基础性研究项目“半封闭温室条件下黄瓜生长发育模型的建立与分析评价”[沪农科攻字(2014) 第 7-2-1 号];上海市农业基础性研究项目“基于图像分析及三维建模技术的黄瓜长势快速评价方法研究”[沪农科攻字(2015)第6-4-2 号]

Analysis and Modeling of the Heterogeneous Distribution Phenotyping Characteristics of Cucumber Leaves

Tingting Qian^1,³,Shenglian Lu²,Xiuguo Zheng^1,³,Jingyin Zhao^1,³,Jian Wang⁴,Juan Yang^1,^3,^*()

1.Shanghai Academy of Agricultural Sciences, Shanghai, 201403
2.Guangxi Normal University, Guilin, 541004
3.Research Center Of Shanghai Digital Agricultural Engineering and Technology,Shanghai 201403
4.Information Center Of Beijing Agricultural Bureau,Beijing 100029

Received:2019-04-12 Online:2019-06-26 Published:2019-08-21
Contact: Juan Yang E-mail:yangjuan@saas.sh.cn

摘要/Abstract

摘要：

【目的】黄瓜叶片方位朝向和分布特征是决定冠层光截获能力和光合能力的重要结构参数。通过对不同栽培密度的黄瓜群体中叶片方位角分布规律的分析,可以找出影响叶片分布和冠层异质性结构特征的环境因素,并为研究植物形态特征对环境的响应机制提供支持。【方法】为了研究黄瓜叶片在冠层内部光环境梯度变化的条件下叶片分布对光环境的响应,本研究通过5个密度处理下的9次测量试验数据,利用三维扫描方法对黄瓜冠层器官尺度表型参数进行数字化采集,并对不同茬口之间不同方位区域内叶片分布的异质性表型特征进行了定量化分析。【结果】本研究通过对2个栽培茬口、5个不同密度群体中方位角分布规律与太阳高度角、叶面积指数相关性分析,建立了方位角分布频率与太阳高度角、叶面积指数的相关关系模型,并提取了模型参数。进一步利用cosine函数对畦内和畦间方位角分布频率进行了修正,实现了方位角分布频率对人为栽培管理措施的响应。通过实测数据对模型准确性进行验证,准确率达到0.89。【结论】本研究实现了方位角分布频率模拟模型对冠层生长发育、外界环境以及人为管理措施的响应。为黄瓜冠层尺度表型参数获取提供了重要参考,也为更加精确的黄瓜功能结构模型构建奠定了基础。

关键词: 表型, 结构, 异质性, 冠层, 方位角, 黄瓜, 植物表型组学

Abstract:

[Objective] The orientation and distribution characteristics of the cucumber leaf blade are important structural parameters that determine the light interception and photosynthesis capacity of the canopy. Detailed analysis of leaf azimuth distribution with different cultivation densities will determine the environmental factors that affect leaf distribution and canopy heterogeneity structural characteristics, and support the study of the response mechanism of plant morphology to the environment. [Methods] To study the response of leaf distribution to the light environment under light gradient changes inside the canopy, nine sets of measurement test data under five density treatments were used. A three-dimensional scanning method was used to digitally collect the phenotypic parameters of cucumber canopy organs, and the heterogeneous characteristics of leaf distribution were quantitatively analyzed in different azimuth regions. [Results] Based on the detailed analysis of the relationship between leaf azimuth distribution and solar elevation angle and leaf area index, correlation models were established. The difference in azimuth distribution frequency between the inside and outside of double rows was amended using the cosine function to simulate the response of azimuth distribution frequency to man-made cultivation management. The accuracy of the model was verified by the measured data, and the accuracy rate reached 0.89. [Conclusion] In this study, the response of the azimuthal distribution frequency to canopy growth, light environment and planting management was implemented. It provides an important reference for the acquisition of cucumber canopy phenotypic parameters, and lays the foundation for more accurate cucumber functional and structural plant model construction.

Key words: phenotyping, structure, heterogeneity, canopy, azimuth, cucumber, plant phenomics

中图分类号:

钱婷婷,陆声链,郑秀国,赵京音,王剑,杨娟. 黄瓜叶片分布的异质性表型特征分析与模型建立[J]. 农业大数据学报, 2019, 1(2): 41-49.

Tingting Qian,Shenglian Lu,Xiuguo Zheng,Jingyin Zhao,Jian Wang,Juan Yang. Analysis and Modeling of the Heterogeneous Distribution Phenotyping Characteristics of Cucumber Leaves[J]. Journal of Agricultural Big Data, 2019, 1(2): 41-49.

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黄瓜叶片分布的异质性表型特征分析与模型建立

Analysis and Modeling of the Heterogeneous Distribution Phenotyping Characteristics of Cucumber Leaves

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