植株表型性状是遗传育种和农业生产中普遍关心的数据,传统表型观测已成为限制育种效率和管理生长的主要因素。基于可见光图像的植株表型检测具有成本低、效率高、易推广等优点,不但可以原位、实时和连续获取植物生长图像,而且能够解析出植物结构、形态、颜色和纹理等多种表型参数。从玉米群体、单株和器官尺度上论述了基于可见光图像的玉米植物表型检测方法和技术,重点介绍了玉米根、叶、穗部等主要器官的高通量表型检测进展,并分析了基于可见光图像进行植物表型检测存在的问题和发展趋势,以期为制定作物表型检测技术方案和实施规程,及系统开展植物表型组学研究提供参考。 Plant phenotypic traits are generally concerned with genetic breeding and agricultural production, and traditional phenotyping has become a major factor limiting the efficiency of breeding and management of growth. Plant phenotype detection based on visible light image has the advantages of low cost, high efficiency and easy popularization. It not only can obtain plant growth images in situ, real-time and continuously, but also can analyze many phenotypes such as plant structure, morphology, color and texture parameter. The methods and techniques of phenotypic detection of corn plants based on visible light images were discussed from the corn population, plant and organ scales. The progress of high-throughput phenotypic detection of corn, root, leaf and panicle were emphatically introduced. Based on the visible light image, the existing problems and development trend of plant phenotype detection are analyzed in order to provide references for the formulation of technical scheme and implementation regulation of crop phenotype detection and systematic study on plant phenomics.