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作物杂志,2026, 第4期: 8–16 doi: 10.16035/j.issn.1001-7283.2026.04.002

• 专题综述 • 上一篇    下一篇

机器视觉光谱成像技术在玉米种子质量检测中的应用

展慧1(), 吴擎2, 李丽君3   

  1. 1 武昌工学院信息工程学院， 430065， 湖北武汉
    2 华中农业大学工学院， 430070， 湖北武汉
    3 华中农业大学植物科学技术学院， 430070， 湖北武汉
  • 收稿日期:2025-02-09 修回日期:2025-05-02 出版日期:2026-08-15 发布日期:2026-08-11
  • 作者简介:展慧，主要从事智能化检测与控制及图像处理研究，E-mail：979220853@qq.com
  • 基金资助:
    湖北省支持种业高质量发展资金项目(HBZY2023B002)

Application of Spectral Imaging Technology Based on Machine Vision in Maize Seed Quality Detection

Zhan Hui1(), Wu Qing2, Li Lijun3   

  1. 1 Department of Information Engineering, Wuchang Institute of Technology, Wuhan 430065, Hubei, China
    2 College of Engineering, Huazhong Agricultural University, Wuhan 430070, Hubei, China
    3 College of Plant Science and Technology, Huazhong Agricultural University, Wuhan 430070, Hubei, China
  • Received:2025-02-09 Revised:2025-05-02 Online:2026-08-15 Published:2026-08-11

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摘要：

随着玉米密植与单粒精量播种技术的发展，传统种子质量检测方法无法满足高效性与准确性的要求，而机器视觉光谱成像技术提供了一种快速、无损且高效的检测手段。本文介绍了机器视觉光谱成像技术的原理及其发展，归纳了基于该技术的种子质量检测流程，分析了其在玉米品种鉴定、纯度分析、不完善粒辨识、霉变粒检测、含水率检测及种子活力检测等方面的研究进展，剖析了机器视觉光谱成像技术研究与应用中存在的问题，从多技术集成与多模态数据融合、标准数据库构建、新算法模型和智能化在线检测系统研发等方面展望了该技术在玉米种子质量检测应用中的发展趋势，以期为推动该技术在玉米种子检测中的应用提供参考。

关键词: 玉米, 机器视觉光谱成像技术, 种子质量检测, 发展趋势

Abstract:

With the development of maize dense planting and single-seed precision sowing technologies, traditional seed quality detection methods cannot meet the requirements for high efficiency and accuracy, while machine vision spectral imaging technology provides a rapid, non-destructive, and efficient means of detection. This paper introduces the principles and development of machine vision spectral imaging technology, summarizes the seed quality detection workflow based on this technology, and analyzes the research progress in maize variety identification, purity analysis, imperfect grain identification, moldy grain detection, moisture content detection, and seed vigor detection. The existing problems in the research and application of machine vision spectral imaging technology are analyzed. The development trends of this technology in maize seed quality detection are prospected from the aspects of multi-technology integration and multimodal data fusion, construction of standard databases, new algorithm models, and research and development of intelligent online detection systems, aiming to provide a reference for promoting the application of this technology in maize seed detection.

Key words: Maize, Machine vision-based spectral imaging technology, Seed quality detection, Development trends

图1

机器视觉光谱成像种子质量检测系统组成及一般流程

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