|本期目录/Table of Contents|

[1]李修华,项志伟,郭新宇,等.基于图像的生菜表型高通量获取方法[J].江苏农业科学,2022,50(20):1-9.
 Li Xiuhua,et al.High-throughput acquisition of lettuce phenotype based on image[J].Jiangsu Agricultural Sciences,2022,50(20):1-9.
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基于图像的生菜表型高通量获取方法(PDF)
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《江苏农业科学》[ISSN:1002-1302/CN:32-1214/S]

卷:
第50卷
期数:
2022年第20期
页码:
1-9
栏目:
“表型组学”专栏
出版日期:
2022-10-20

文章信息/Info

Title:
High-throughput acquisition of lettuce phenotype based on image
作者:
李修华1项志伟13郭新宇23王传宇23
1.广西大学电气工程学院,广西南宁 530004; 2.北京市农林科学院信息技术研究中心,北京 100097;3.数字植物北京市重点实验室,北京 100097
Author(s):
Li Xiuhuaet al
关键词:
生菜表型鉴定高通量图像处理图像分割
Keywords:
-
分类号:
TP391.41
DOI:
-
文献标志码:
A
摘要:
为了解决生菜表型指标人工获取效率低、大型表型设备成本高等问题,提出一种基于图像的无损、快速获取生菜表型的高通量方法。首先获取温室内正常生长的生菜图像,通过标定物检出、背景分割算法得到目标前景图像,识别叶片轮廓并剔除噪点部分,得到感兴趣的区域,然后计算颜色、形状、纹理三大类共计39个表型指标,应用该方法获取59种生菜材料成熟期的图像并分析表型指标。结果表明,生菜叶片面积指标与鲜质量人工测量值回归分析的决定系数为0.91,验证了系统的精度和准确性。采用非监督聚类方法对59个材料表型指标进行分类,共获得三种表型类型,通过树状图、主成分分析图和剖面图分析各表型指标在分类中的作用及不同分类生菜的主要表型差异。结果显示,该方法能够快速获取多个生菜的表型指标,能够满足大规模种质资源鉴定和商业化育种对表型数据的需求。
Abstract:
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备注/Memo

备注/Memo:
收稿日期:2021-11-19
基金项目:北京市农林科学院院表型协同创新中心项目(编号:KJCX201917);北京市农林科学院科研创新平台建设项目;北京市农林科学院改革与发展项目。
作者简介:李修华(1983—),女,重庆人,博士,副教授,主要从事作物检测和农业物联网研究。E-mail:lixh@gxu.edu.cn。
通信作者:王传宇,博士,副研究员,主要从事基于图像的作物长相长势监测研究。E-mail:wangcy@nercita.org.cn。
更新日期/Last Update: 2022-10-20