中国农机化学报 ›› 2023, Vol. 44 ›› Issue (2): 112-118.DOI: 10.13733/j.jcam.issn.2095-5553.2023.02.016
吴俊鹏1,黄光文1,李君1, 2
出版日期:
2023-02-15
发布日期:
2023-02-28
基金资助:
Wu Junpeng, Huang Guangwen, Li Jun.
Online:
2023-02-15
Published:
2023-02-28
摘要: 水果病害是影响果树健康生长、果实品质和产量的重要因素之一,及时、精准地掌握果树的病害信息并进行精准施药管控,对防范果园重大病害的发生和流行,保障水果的稳产优产具有重要意义。随着现代农业朝规模化、智能化和高效率的发展需求,视觉和光谱检测技术因具有无损检测、可规模化和高效率等优点,逐渐发展为检测水果病害的重要技术之一。梳理国内外机器视觉和光谱技术在水果病害检测应用领域的研究进展,介绍图像处理技术有较好的解释性,有利于与植保农艺研究相结合;深度学习技术有较好的精度和泛化性;透射光谱技术可用于检测果实内部病害;反射光谱技术可用于检测果实、叶片表面病害,并实现分级。最后,总结未来机器视觉与光谱检测技术优化和应用的方向,并展望水果病害检测的实际生产应用前景,以期为水果病害检测研究提供参考与借鉴。
中图分类号:
吴俊鹏, 黄光文, 李君, . 水果病害视觉与光谱检测技术研究现状及展望[J]. 中国农机化学报, 2023, 44(2): 112-118.
Wu Junpeng, Huang Guangwen, Li Jun.. Research status and prospect of visual and spectral detection of fruit diseases[J]. Journal of Chinese Agricultural Mechanization, 2023, 44(2): 112-118.
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