Abstract:In recent years, the rapid development of plant genomes, but the lack of sufficient phenotypic data limits the ability of humans to analyze the genetics of quantitative traits. This problem can be effectively solved by developing a plant phenotypic monitoring platform. High-throughput, automated and high-resolution phenotyping platform is critical for accelerating crop improvement and breeding strategies for higher yield and disease tolerance. Plant phenotyping has been advancing at an accelerated rate as a response to the need to fill the gap between genomic information and the plasticity of the plant phenome. Domestic and international efforts have been made to develop phenotyping facilities, and these devices are actively contributing to the generation of high-dimensional, richly informative datasets about the phenotype of model and crop plants. The plant phenotypic monitoring platform integrates multiple sensors for quantitative research on complex traits related to growth, yield, and adaptation to biotic or abiotic stresses such as plant height, leaf number and area, root morphology, biomass, and fruit characteristics. The research progress of plant phenotypic monitoring technology and research status of platform at home and abroad was mainly introduced. The research progress of plant phenotypic information collection platform and technology was introduced, and the functions and characteristics of each were summarized and analyzed. Thus, various phenotypic platform based on indoor and field environments were presented together with applications of these platforms with different mounting modes. An overview of the most commonly used sensors that empower digital phenotyping and the information they provide were presented. Function and feature of each phenotype platform was also analyzed. Meanwhile, an in-depth analysis of image processing with its major issues was given, and the algorithms that were used or emerged as useful to obtain data out of images in an automatic fashion. In this review, the current and emerging methods of image acquisition and processing that allow image-based phenomics were covered. The main bottlenecks that still remained in the field was concluded and the application prospect of plant phenotypic monitoring technology and platform were expected, which pointed out the following challenges: developing plant phenotyping platform of multi-sensor integrated system, introducing plant growth environment monitoring module into plant phenotypic information collection platform, designing forest phenotypic information collection platform, conducting integration and mining phenotype data captured by sensors, collecting the phenotypic data of underground part by nondestructive in situ plant root measurement technology, building unified open standards for phenotypic data and prompting interdisciplinary cooperation.
