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  • 崔丹丹,杨瑞芳,佘玮,等.基于可见光遥感的苎麻种质资源冠层性状研究[J].植物遗传资源学报,2020,21(2):483-490.    [点击复制]
  • CUI Dan-dan,YANG Rui-fang,SHE Wei,et al.Studies on Canopy Characters of Ramie Germplasm Resources Based on Visible Light Remote Sensing[J].植物遗传资源学报,2020,21(2):483-490.   [点击复制]
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基于可见光遥感的苎麻种质资源冠层性状研究
崔丹丹1, 杨瑞芳1, 佘玮1, 刘曜端2, 李林林1, 苏小惠1, 王继龙1, 刘皖慧1, 王昕慧1, 刘婕仪1, 付虹雨1, 崔国贤1
0
(1.湖南农业大学农学院;2.湖南环境生物职业技术学院)
摘要:
无人机近空遥感技术可快速实时掌握农田信息,在农作物田间监测中发挥日益重要的作用。本研究使用无人机可见光遥感平台,获取苎麻冠层航拍图像,通过图像处理获得苎麻种质资源冠层图像特征值,结合各苎麻种质资源生长性状,研究26份苎麻种质资源冠层图像性状差异。结果表明,使用HSV色彩空阈值分割可有效将苎麻与土壤杂草分割;26份苎麻资源6个表型性状变异系数分布在11.00%~52.39%之间,多样性指数分布在0.62~1.58之间;26份苎麻资源15个冠层颜色、纹理性状变异系数分布在0.28%~48.09%之间,多样性指数分布在1.25~1.54之间,表明试验苎麻种质资源具有丰富变异和广泛多样性。15个冠层颜色纹理性状主成分分析得到2个主成分,累计贡献率达到95.10%,可有效反映各性状的主要信息。
关键词:  苎麻  种质资源  无人机  冠层性状
DOI:10.13430/j.cnki.jpgr.20190505002
投稿时间:2019-05-05修订日期:2020-01-13
基金项目:国家重点研发计划课题(2018YFD0201106);国家麻类产业技术体系(CARS-16-E11);国家自然科学基金(31471543); 国家自然科学基金(31871673)
Studies on Canopy Characters of Ramie Germplasm Resources Based on Visible Light Remote Sensing
CUI Dan-dan1, YANG Rui-fang1, SHE Wei1, LIU Yao-duan2, LI Lin-lin1, SU Xiao-hui1, WANG Ji-long1, LIU Wan-hui1, WANG Xin-hui1, LIU Jie-yi1, FU Hong-yu1, CUI Guo-xian1
(1.Agricultural College of Hunan Agricultural University;2.Hunan Polytechnic of Environmental and Biotechnology)
Abstract:
Unmanned aerial vehicle (UAV) near-air remote sensing technology provides the accessibility to monitor the farmland in a rapid and real-time manner. By taking use of the UAV visible light remote sensing platform, here the aerial images of canopy using 26 ramie germplasms were generated and analyzed for the characteristic values using the image processing pipeline. The results showed that HSV color image segmentation can effectively recognize ramie from soil weeds. The variation coefficient at 6 phenotypic traits of 26 ramie resources was 11.00%-52.39%, and the diversity index was 0.62-1.58. The variation coefficients of 15 canopy color and texture traits of 26 ramie resources were distributed between 0.28% and 48.09%, and the diversity index was ranged from 1.25 to 1.54. That indicated a broad phenotypic variation in the tested ramie germplasm resources. Two principal components were identified by principal component analysis of 15 canopy color and texture traits, and the cumulative contribution rate reached 95.10%, which can effectively reflect the main information of each trait.
Key words:  ramie  germplasm resources  UAV  canopy traits

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