文献类型： 外文期刊

作者： Xu, Bo ¹ ; Wan, Xiangyuan ¹ ; Yang, Hao ² ; Feng, Haikuan ² ; Fu, Yuanyuan ⁴ ; Cen, Haiyan ⁵ ; Wang, Binbin ² ; Zhang, Zhoufeng ⁶ ; Li, Siyuan ⁶ ; Zhao, Chunjiang ¹ ; Yang, Guijun ² ;

作者机构： 1.Univ Sci & Technol Beijing, Sch Chem & Biol Engn, Beijing 100083, Peoples R China

2.Beijing Acad Agr & Forestry Sci, Informat Technol Res Ctr, Key Lab Quantitat Remote Sensing Agr, Minist Agr & Rural Affairs, Beijing 100097, Peoples R China

3.Natl Engn Res Ctr Informat Technol Agr, Beijing 100097, Peoples R China

4.Henan Agr Univ, Zhengzhou 450002, Henan, Peoples R China

5.Zhejiang Univ, Hangzhou 310058, Zhejiang, Peoples R China

6.Chinese Acad Sci, Xian Inst OpticStudio & Precis Mech, Xian 710119, Peoples R China

关键词： Maize tassel; Organ -scale phenotypes; TreeQSM; Three-dimensional point cloud reconstruction; Digital photographs

期刊名称：COMPUTERS AND ELECTRONICS IN AGRICULTURE （ 影响因子：8.3； 五年影响因子：8.3 ）

ISSN： 0168-1699

年卷期： 2023 年 212 卷

页码：

收录情况： SCI

摘要： Maize tassel is a crucial pollen producing organ that plays an important role in maize production. It is challenging to investigate the morphological and structural traits of maize tassels for breeding programs, since traditional manual measurements of organ-scale phenotypic traits are labor-intensive and prone to human errors. It is, therefore, urgent to design and develop new phenotyping systems for maize tassels to improve throughput and measurement accuracy. This study first introduced the TreeQSM in crop phenotyping at organ scale and developed TIPS (TreeQSM based Image Phenotyping System for maize tassels). The system mainly consists of three digital cameras for acquiring multi-view images of individual maize tassel. These cameras were vertically arranged with different angles of view. The acquired images were used to reconstruct the 3D point cloud data of individual maize tassel, which were fed into the TreeQSM to extract four tassel phenotypic parameters including trunk length, branch number, branch length, and branch angle. The performance analyses of the developed system were conducted on 52 tassel samples from 37 maize materials with different canopy geometric structures. The experimental results showed that the TIPS could achieve accurate tassel parameters estimation with the R2 of 0.964, 0.973, 0.935, and 0.857, and the RMSE of 1.72, 1.28, 19.94, and 2.73 for the trunk length, branch number, total branch length, and first node branch angle, respectively. This study also investigated the advantages of the data acquisition with the TIPS and the effects of different shooting angles, number of images, lighting conditions and tassel types on the four tassel parameters estimation accuracy. The comparison results indicated that the four influencing factors reduced the estimation accuracy to varying degree. Compared with the other three parameters, the estimation accuracy of branch angles less than 20 were largely affected. The higher the degree of compactness, the worse the estimation accuracy. Compared with shooting angles, the reduction of the number of images in a certain range had less impact on the quality of 3D point cloud reconstruction. The influence of low light was obviously greater than that of strong light. This study provides a valuable guide to the collection and quantitative analysis of high-throughput phenotype information of maize tassels in breeding program.