From Parallel Plants to Smart Plants:Intelligent Control and Management for Plant Growth

作     者：Mengzhen Kang Fei-Yue Wang 

作者机构：State Key Laboratory of Management and Control for Complex SystemsInstitute of AutomationChinese Academy of Sciences (SKL-MCCSCASIA) Qingdao Academy of Intelligent Industries Beijing Engineering Research Center of Intelligent Systems and Technology IEEE State Key Laboratory of Management and Control for Complex Systems (SKL-MCCS)Institute of AutomationChinese Academy of Sciences (CASIA) School of Computer and Control EngineeringUniversity of Chinese Academy of Sciences Research Center for Military Computational Experiments and Parallel Systems TechnologyNational University of Defense Technology 

出 版 物：《IEEE/CAA Journal of Automatica Sinica》 (自动化学报（英文版）)

年 卷 期：2017年第4卷第2期

页      面：161-166页

核心收录：

学科分类：0810[工学-信息与通信工程] 1205[管理学-图书情报与档案管理] 12[管理学] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 082804[工学-农业电气化与自动化] 08[工学] 0828[工学-农业工程] 081104[工学-模式识别与智能系统] 0802[工学-机械工程] 0835[工学-软件工程] 0811[工学-控制科学与工程] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：supported by the National High Technology Research and Development Program(863 program)of China(2012AA101906-2) the National Natural Science Foundation of China(3140030594) 

主　　题：Agriculture Artificial intelligence Decision support systems Expert systems Sustainable development 

摘      要：Precision management of agricultural systems, aiming at optimizing profitability, productivity and sustainability, comprises a set of technologies including sensors, information systems, and informed management, etc. Expert systems are expected to aid farmers in plant management or environment control, but they are mostly based on the offline and static information, deviated from the actual situation. Parallel management, achieved by virtual/artificial agricultural system, computational experiment and parallel execution, provides a generic framework of solution for online decision support. In this paper, we present the three steps toward the parallel management of plant: growth description U+0028 the crop model U+0029, prediction, and prescription. This approach can update the expert system by adding learning ability and the adaption of knowledge database according to the descriptive and predictive model. The possibilities of passing the knowledge of experienced farmers to younger generation, as well as the application to the parallel breeding of plant through such system, are discussed. © 2017 Chinese Association of Automation.