摘要
现代的温室是一个复杂的环境系统,其中土壤、作物和微气候三个子系统间各种生物和非生物现象时常发生。农业数学模型可以用来模拟和预测温室内微气候和植物生长的变化,从而推荐最优化的生产管理策略。本文对国内外温室气候模型和温室作物生长模型进行了综述,温室气候动态模型可以预测关键气候因子,分为机械模型和黑箱模型。机械模型基于物理方程构建,它描述了基于过程的知识模拟的系统;黑箱模型属于经验模型,更多地用于温室系统控制、优化和设计的应用。作物生长模型是基于科学原理和数学关系的一种定量化工具,可以评估温室内土壤、微气候、水分和管理因素对作物生长发育的影响程度,预测作物生长状况。作物生长模型主要包括两类:描述性模型和解释性模型。温室作物模型是基于露地作物建立的最早的作物生长模型,并在几十年发展过程中对原来各功能模块进行修正、扩展和升级而来。功能-结构植物模型(functional–structural plant modeling,FSPM)是基于植物建筑学并结合气候和作物模块而形成,可以模拟单个植物的生长、形态以及它们与其生长环境的相互作用。最后指出未来趋势是利用数字技术、人工智能结合FSP模型,利用云数据储存计算分析。
The modern greenhouse is a complex environmental system where various biological and abiotic phenomena occur fre⁃quently among the three subsystems of soil,crop,and microclimate.Agricultural mathematical models can be used to simulate and predict changes in greenhouse microclimate and plant growth,thereby recommending optimized production management strategies.This paper reviewed the domestic and foreign greenhouse climate models and greenhouse crop growth models.The greenhouse climate dynamic models can predict key climate factors and are classified as mechanistic models and black-box mod⁃els.The mechanistical models are based on physical equations describes a system that simulates process-based knowledge.The black-box models belong to an empirical model and are more commonly used for greenhouse system control,optimization,and design application.The crop growth model is a quantitative tool based on scientific principles and mathematical relation⁃ships.It can evaluate the impacts of soil,microclimate,water,and management factors on crop growth and development in the greenhouse and predict crop growth status.The crop growth models mainly include two types:descriptive models and explana⁃tory models.The greenhouse crop model is the original crop growth model established based on field crops,and it has been re⁃vised,expanded,and upgraded over several decades of development.The functional⁃structural plant modeling is based on plant architecture and combined with climate and crop modules,which can with simulate the growth,morphology,and interac⁃tions of individual plants with their growing environment.Finally,it is pointed out that the future trend is to use digital technol⁃ogy and artificial intelligence combined with the FSP model,and to use cloud data storage and analysis for computation.
作者
金梁
魏丹
殷大伟
邹国元
张亦涛
丁建莉
王磊
李艳
左强
申慧波
王宇先
王俊强
孙磊
王伟
梁丽娜
孙鑫
王文
Jin Liang;Wei Dan;Yin Dawei;Zou Guoyuan;Zhang Yitao;Ding Jianli;Wang Lei;Li Yan;Zuo Qiang;Shen Huibo;Wang Yuxian;Wang Junqiang;Sun Lei;Wang Wei;Liang Lina;Sun Xin;Wang Wen(The Institute of Plant Nutrition,Resources and Environment,Beijing Academy of agricultural and Forestry Sciences,Bei-jing 100097,China;Heilongjiang Bayi Agricultural University,Daqing 163319,China;Institute of Geographic Sciences and Natural Resources Research,Beijing 100101,China;Qiqihar Branch of Heilongjiang Academy of Agricultural Scienc-es,Qiqihar 161006,China;Heilongjiang Agricultural Sciences Academy,Haerbin 150086,China;Black soil protection and Utilization Research Institute of Heilongjiang Agricultural Sciences Academy,Haerbin 150086,China;Beijing Univer-sity of Agriculture,Beijing 100096,China)
出处
《山西农业大学学报（自然科学版）》
CAS
北大核心
2023年第1期55-64,共10页
Journal of Shanxi Agricultural University(Natural Science Edition)
基金
国家自然科学基金(41977095)
植物营养与资源环境研究所团队促进项目(ZHS202304)
黑土地保护与利用科技创新工程专项资助(XDA28130200)
国家重点研发计划资助(2022YFD1500204
2019YFD1100304-3)
北京学者计划(市财政资助)
北京市农林科学院科技创新能力建设专项(KJCX20200801
KJCX20190408)
国家大豆产业技术体系(CARS-04)
黑龙江省科技计划(2021ZXJ05B011)
UNDP(cpr/19/401)。
关键词
微气候模型
温室作物模型
预测
植物生长
管理
Micro-climate model
Greenhouse crop model
Prediction
Plant growth
Management
