A cooperative regulation method for greenhouse soil moisture and light using Gaussian curvature and machine learning algorithms
文献类型: 外文期刊
第一作者: Hou, Junying
作者: Hou, Junying;Li, Yuanfang;Sun, Zhangtong;Wang, Haoyu;Lu, Miao;Hu, Jin;Hou, Junying;Hu, Jin;Wu, Huarui;Hu, Jin
作者机构:
关键词: Environmental regulation; Photosynthetic rate prediction model; Generalized additive model; Gaussian curvature; Regulation strategies
期刊名称:COMPUTERS AND ELECTRONICS IN AGRICULTURE ( 影响因子:7.7; 五年影响因子:8.4 )
ISSN: 0168-1699
年卷期: 2023 年 215 卷
页码:
收录情况: SCI
摘要: Soil moisture (SM) exerts a significant impact on crop growth, interacting with environmental factors such as temperature, photosynthetic photon flux density (PPFD), and CO2, ultimately affecting crop photosynthesis (Pn). This study employs a nested experimental design to investigate the photosynthetic activity of cucumber seedlings under diverse environmental conditions and establishes a support vector regression (SVR) model for Pn prediction. The SVR model takes temperature, PPFD, SM, and CO2 concentration as inputs and demonstrates a high level of accuracy (The model's coefficient of determination = 0.9830, root mean square error = 0.9138). Subsequently, through a generalized additive model, the study unveils the significant impact of interactions between SM and PPFD on Pn. Accordingly, this research constructs a Pn response surface based on these two factors and identifies the maximum point of Gaussian curvature on this surface. Polynomial regression is applied to these points, yielding a comprehensive regulation strategy for SM and PPFD. In comparison to traditional methods based on maximizing Pn, this innovative approach reduces Pn by 12.9 % while significantly conserving light (35.59 %) and water (32.80 %) consumption. Although no significant changes are observed in crop physiological traits (plant height, stem diameter, dry weight, fresh weight), substantial variations are noted in irrigation volume and PPFD consumption. Thus, the regulation strategy proposed in this study embodies efficiency and energy conservation in greenhouse crop cultivation.
分类号:
- 相关文献
作者其他论文 更多>>
-
A New Large-Scale Monitoring Index of Desertification Based on Kernel Normalized Difference Vegetation Index and Feature Space Model
作者:Guo, Bing;Xu, Mei;Liu, Panpan;Wang, Longhao;Zhang, Rui;Lu, Miao
关键词:KNDVI; feature space; spatiotemporal evolution; desertification
-
Eliminating Primacy Bias in Online Reinforcement Learning by Self-Distillation
作者:Li, Jingchen;Wu, Huarui;Zhao, Chunjiang;Shi, Haobin;Hwang, Kao-Shing
关键词:Online reinforcement learning; overfitting; reinforcement learning
-
A WebGIS-Based System for Supporting Saline-Alkali Soil Ecological Monitoring: A Case Study in Yellow River Delta, China
作者:Song, Yingqiang;Pan, Yinxue;Xiang, Meiyan;Yang, Weihao;Zhan, Dexi;Wang, Xingrui;Lu, Miao;Lu, Miao
关键词:WebGIS; ecological monitoring; machine learning; Yellow River Delta
-
Recognition Method of Cabbage Heads at Harvest Stage under Complex Background Based on Improved YOLOv8n
作者:Tian, Yongqiang;Zhang, Taihong;Zhao, Yunjie;Zhao, Chunjiang;Wu, Huarui;Zhang, Taihong;Zhao, Yunjie;Zhang, Taihong;Zhao, Yunjie;Wu, Huarui
关键词:cabbage; recognition and localization; object detection; deep learning; automatic harvesting
-
A Vis/NIR device for detecting moldy apple cores using spectral shape features
作者:Liu, Haoling;Wei, Ziyuan;Lu, Miao;Zhao, Juan;Gao, Pan;Hu, Jin;Liu, Haoling;Wei, Ziyuan;Lu, Miao;Gao, Pan;Zhao, Juan;Hu, Jin;Li, Jiangkuo;Gao, Pan;Hu, Jin
关键词:Apple; Moldy core; Portable device; Vis/NIR; Spectral shape features
-
Functional characterization of sex pheromone receptors PflaOR29 and PflaOR44 involved in the chemoreception of a diurnal moth, Phauda flammans (Walker) (Lepidoptera: Phaudidae)
作者:Hu, Jin;Tan, Liusu;Wang, Xiaoyun;Zheng, Xialin;Zhang, Yan;Liu, Wei;Wang, Guirong;Zhang, Yan
关键词:Diurnal moth; Pheromone receptors; Drosophila empty neuron system; Sexual communication
-
Cabbage Transplantation State Recognition Model Based on Modified YOLOv5-GFD
作者:Sun, Xiang;Miao, Yisheng;Wang, Yuansheng;Li, Qingxue;Zhu, Huaji;Wu, Huarui;Sun, Xiang;Miao, Yisheng;Wu, Xiaoyan;Wang, Yuansheng;Li, Qingxue;Zhu, Huaji;Wu, Huarui;Sun, Xiang;Miao, Yisheng;Wang, Yuansheng;Li, Qingxue;Zhu, Huaji;Wu, Huarui;Wu, Xiaoyan
关键词:the state of cabbage transplantation; target detection; deep separable convolution; YOLOv5s