From Parallel Plants to Smart Plants:

Intelligent Control and Management for Plant Growth

Mengzhen Kang and Fei-Yue Wang, Fellow, IEEE

Institute of Automation, Chinese Academy of Sciences,  

Qingdao Academy of Intelligent Industries,

National University of Defense Technology, China

Abstract: 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 (the crop model), 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.

Index Terms: Artificial intelligence, cropping plan, management system, precision agriculture, plant model.

Citation: M. Z. Kang and F. Y. Wang, “From parallel plants to smart plants: intelligent control and management for plant growth,” IEEE/CAA Journal of Automatica Sinica, vol. 4, no. 2, pp. 161-166, Apr. 2017.

Full Text-PDF:

From Parallel Plants to Smart Plants- Intelligent Control and Management for Pla.pdf