Application of Internet of Things to Agriculture—The LQ-FieldPheno Platform: A High-Throughput Platform for Obtaining Crop Phenotypes in Field

作者：Jiangchuan Fan, Yinglun Li, S.K. Yu, Wenbo Gou, Xinyu Guo, Chunjiang Zhao · 发表于：Research · 年份：2023 · DOI：10.34133/research.0059 · 被引用次数：36 · 研究领域：Smart Agriculture and AI、Remote Sensing in Agriculture、Remote Sensing and LiDAR Applications

The lack of efficient crop phenotypic measurement methods has become a bottleneck in the field of breeding and precision cultivation. However, high-throughput and accurate phenotypic measurement could accelerate the breeding and improve the existing cultivation management technology. In view of this, this paper introduces a high-throughput crop phenotype measurement platform named the LQ-FieldPheno, which was developed by China National Agricultural Information Engineering Technology Research Centre. The proposed platform represents a mobile phenotypic high-throughput automatic acquisition system based on a field track platform, which introduces the Internet of Things (IoT) into agricultural breeding. The proposed platform uses the crop phenotype multisensor central imaging unit as a core and integrates different types of equipment, including an automatic control system, upward field track, intelligent navigation vehicle, and environmental sensors. Furthermore, it combines an RGB camera, a 6-band multispectral camera, a thermal infrared camera, a 3-dimensional laser radar, and a deep camera. Special software is developed to control motions and sensors and to design run lines. Using wireless sensor networks and mobile communication wireless networks of IoT, the proposed system can obtain phenotypic information about plants in their growth period with a high-throughput, automatic, and high time sequence. Moreover, the LQ-FieldPheno has the characteristics of multiple data acqui...