作物农艺性状与形态结构表型智能识别技术综述OACSTPCD

[Significance]The crop phenotype is the visible result of the complex interplay between crop genes and the environment.It reflects the physiological,ecological,and dynamic aspects of crop growth and development,serving as a critical component in the realm of ad-vanced breeding techniques.By systematically analyzing crop phenotypes,researchers can gain valuable insights into gene function and identify genetic factors that influence important crop traits.This information can then be leveraged to effectively harness germ-plasm resources and develop breakthrough varieties.Utilizing data-driven,intelligent,dynamic,and non-invasive methods for measur-ing crop phenotypes allows researchers to accurately capture key growth traits and parameters,providing essential data for breeding and selecting superior crop varieties throughout the entire growth cycle.This article provides an overview of intelligent identification technologies for crop agronomic traits and morphological structural phenotypes. [Progress]Crop phenotype acquisition equipment serves as the essential foundation for acquiring,analyzing,measuring,and identify-ing crop phenotypes.This equipment enables detailed monitoring of crop growth status.The article presents an overview of the func-tions,performance,and applications of the leading high-throughput crop phenotyping platforms,as well as an analysis of the charac-teristics of various sensing and imaging devices used to obtain crop phenotypic information.The rapid advancement of high-through-put crop phenotyping platforms and sensory imaging equipment has facilitated the integration of cutting-edge imaging technology,spectroscopy technology,and deep learning algorithms.These technologies enable the automatic and high-throughput acquisition of yield,resistance,quality,and other relevant traits of large-scale crops,leading to the generation of extensive multi-dimensional,multi-scale,and multi-modal crop phenotypic data.This advancement supports the rapid progression of crop phenomics.The article also dis-cusses the research progress of intelligent recognition technologies for agronomic traits such as crop plant height acquisition,crop or-gan detection,and counting,as well as crop ideotype recognition,crop morphological information measurement,and crop three-di-mensional reconstruction for morphological structure intelligent recognition.Furthermore,this article outlines the main challenges faced in this field,including:difficulties in data collection in complex environments,high requirements for data scale,diversity,and preprocessing,the need to improve the lightweight nature and generalization ability of models,as well as the high cost of data collec-tion equipment and the need to enhance practicality. [Conclusions and Prospects]Finally,this article puts forward the development directions of crop phenotype intelligent recognition tech-nology,including:developing new and low cost intelligent field equipment for acquiring and analyzing crop phenotypes,enhancing the standardization and consistency of field crop phenotype acquisition,strengthening the generality of intelligent crop phenotype rec-ognition models,researching crop phenotype recognition methods that involve multi-perspective,multimodal,multi-point continuous analysis,and spatiotemporal feature fusion,as well as improving model interpretability.