数字农科院2.0

New insights on canopy heterogeneous analysis and light micro-climate simulation in Chinese solar greenhouse

文献类型： 外文期刊

作者： Demin Xu;Haochong Chen;Fang Ji;Jinyu Zhu;Zhi Wang;Ruihang Zhang;Maolin Hou;Xin Huang;Dongyu Wang;Tiangang Lu;Jian Zhang;Feng Yu;Yuntao Ma

作者机构：

关键词： 3D light interception;Cucumber;LiDAR;Modelling;Plant phenotype;Solar greenhouse

期刊名称： Computers and Electronics in Agriculture

ISSN： 0168-1699

年卷期： 2025 年 233 卷

页码：

收录情况： SCIE（2025版） ; ; EI（2025版）

摘要： Accurate acquisition of the canopy structure is critical for calculating phenotypic traits and light interception, which contributes to a deeper understanding of the interaction mechanism between plants and the environment. The objective of the present study was to accurately obtain the phenotypic characteristics of greenhouse crop populations and to quantify canopy light interception. The terrestrial LiDAR scanning was used to capture the canopy structure of cucumber populations under two common planting strategies inside Chinese solar greenhouse. Furthermore, an integrated 3D model combining the greenhouse structure, canopy structure, and solar radiation was developed to compare the light environment difference between the LiDAR-derived canopy and the virtual canopy. The results indicated that terrestrial LiDAR scanning was an effective technique for obtaining accurate canopy structures, enabling the extraction of detailed phenotypic traits from plant canopies. Significant heterogeneity was observed both vertically and horizontally within cucumber canopy, cultivated in a north–south row orientation inside greenhouse. Using the virtual canopy constructed from measured organ geometry and angle, the maximum amount of light interception was underestimated by 21.4 %, and the photosynthetic rate by 14.8 %, compared to calculations using the LiDAR-derived canopy. In summary, using the 3D structure of virtual canopies cannot accurately quantify the actual light environment in Chinese solar greenhouse. The proposed methodology provides new insights on canopy heterogeneous analysis and light micro-climate simulation in Chinese solar greenhouse, offering a foundation for precise greenhouse management.

分类号：

  • 相关文献

[1]Changes of organic soil substrate with continuous vegetable cultivation in solar greenhouse. Han Ling,Song Weijiao,Li Yan Su,Yan Yan,Yu Xianchang,He Chaoxing.

[2]基于GIS数据的城市路网快速三维建模. 梁其洋,潘瑜春,吴保国,郝星耀. 2018

[3]Improved 3D point cloud segmentation for accurate phenotypic analysis of cabbage plants using deep learning and clustering algorithms. Ruichao Guo,Jilong Xie,Jiaxi Zhu,Ruifeng Cheng,Yi Zhang,Xihai Zhang,Xinjing Gong,Ruwen Zhang,Hao Wang,Fanfeng Meng. 2023

[4]Applications of 3D Reconstruction Techniques in Crop Canopy Phenotyping: A Review. Yanzhou Li,Zhuo Liang,Bo Liu,Lijuan Yin,Fanghao Wan,Wanqiang Qian,Xi Qiao. 2025

[5]Estimating LAI for Cotton Using Multisource UAV Data and a Modified Universal Model. Yan, Puchen,Han, Qisheng,Feng, Yangming,Kang, Shaozhong. 2022

[6]A review of three-dimensional computer vision used in precision livestock farming for cattle growth management. Yaowu Wang,Sander Mücher,Wensheng Wang,Leifeng Guo,Lammert Kooistra. 2023

[7]Coupled estimation of global 500m daily aerodynamic roughness length, zero-plane displacement height and canopy height. Zhong Peng,Ronglin Tang,Meng Liu,Yazhen Jiang,Zhao Liang Li. 2023

[8]Mangrove tree height growth monitoring from multi-temporal UAV-LiDAR. Yin D.,Wang L.,Lu Y.,Shi C.. 2024

[9]Maize height estimation using combined unmanned aerial vehicle oblique photography and LIDAR canopy dynamic characteristics. Tao Liu,Shaolong Zhu,Tianle Yang,Weijun Zhang,Yang Xu,Kai Zhou,Wei Wu,Yuanyuan Zhao,Zhaosheng Yao,Guanshuo Yang,Ying Wang,Chengming Sun,Jianjun Sun. 2024

[10]Combining UAV multisensor field phenotyping and genome-wide association studies to reveal the genetic basis of plant height in cotton (Gossypium hirsutum). Liqiang Fan,Jiajie Yang,Xuwen Wang,Zhao Liu,Bowei Xu,Li Liu,Chenxu Gao,Xiantao Ai,Fuguang Li,Lei Gao,Yu Yu,Zuoren Yang. 2025

[11]Using UAVs in Potato Growing: Diseases Diagnostics, Liquid Spraying. Elena Shkodina,Andrey Ronzhin,Hongbiao Ding. 2026

[12]Microbial growth kinetics models of raw milk in storage and transportation. Hou, Liwei,Xing, Shaohua,Wang, Yong. 2013

[13]Soil organic carbon sequestration under different fertilizer regimes in north and northeast China: RothC simulation. Wang, J.,Lu, C.,Xu, M.,Zhang, W.,Zhu, P.,Peng, C.,Huang, S.,Chen, X.,Wu, L.. 2013

[14]Simulation of water and nitrogen dynamics as affected by drip fertigation strategies. Zhang Jian-jun,Zhao Bing-qiang,Li Yan-ting,Li Jiu-sheng. 2015

[15]Crop productivity and nutrient use efficiency as affected by long-term fertilisation in North China Plain. Wang, Yingchun,Wang, Enli,Smith, Chris J.,Wang, Yingchun,Huang, Shaomin,Wang, Daolong,Ma, Yibing,Wang, Ligang.

[16]Modelling of seed yield and its components in tall fescue (Festuca arundinacea) based on a large sample. Wang, Quanzhen,Hu, Tianming,Cui, Jian,Wang, Xianguo,Zhou, He,Han, Jianguo,Zhang, Tiejun. 2011

[17]Modelling the abundance of three key plant species in New Zealand hill-pasture using a decision tree approach. Wan, Liqiang,Li, Xianglin,Zhang, Baisen,Kemp, Peter. 2009

[18]Modelling impact of agro-drought on grain production in China. Qin, Zhihao,Tang, Huajun,Li, Wenjuan,Qin, Zhihao,Zhao, Shuhe,Zhang, Hao,Wang, Qiang. 2014

[19]A model for photothermal responses of flowering in rice .1. Model description and parameterization. Xinyou Yin , Martin J. Kropff *, Takeshi Horie , Hiroshi Nakagawa , Helen G.S. Centeno , Defeng Zhu , Jan Goudriaan. 1997

[20]A model to identify entry points to curb emissions from complex manure management chains. Qingbo Qu,Keqiang Zhang,Jeroen C.J. Groot. 2023

作者其他论文 更多>>