High-Precision Phenotyping of Grape Bunch Architecture Using Fast 3D Sensor and Automation.
High-Precision Phenotyping of Grape Bunch Architecture Using Fast 3D Sensor and Automation.
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DOI：
10.3390/s18030763
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发表时间：
2018-03-02
期刊：
影响因子：
--
通讯作者：
Töpfer R
中科院分区：
文献类型：
--
作者：
Rist F;Herzog K;Mack J;Richter R;Steinhage V;Töpfer R
葡萄种植者更喜欢具有较松散的果串结构的品种，因为这样可以降低果串腐烂的风险。因此，葡萄育种者必须根据适当的葡萄串性状来选择幼苗和新品种。束结构是不同单一性状的镶嵌体，这使得表型分析既费力又耗时。在本研究中，开发了一种快速、高精度的表型分析流程。光学传感器Artec Spider 3D扫描仪（Artec 3D，L-1466，卢森堡）用于在实验室条件下生成葡萄串的密集3D点云，并开发了名为3D-Bunch-Tool的自动分析软件来提取不同的单3D串特征，即浆果数量、浆果直径、单浆果体积、浆果总体积、葡萄凸壳体积、串宽度和串长度。该方法在不同葡萄品种和表型可变育种材料的整串上进行了验证。获得了可靠的表型数据，与地面真实数据相比，这些数据显示出高度显着的相关性（浆果数量高达 r2 = 0.95）。此外，事实证明Artec Spider可以直接在现场使用，所获得的数据显示与实验室应用相当的精度。这种非侵入性和非接触式现场应用促进了第一个基于大型植物组中 3D 簇性状的高精度表型分析流程。
Wine growers prefer cultivars with looser bunch architecture because of the decreased risk for bunch rot. As a consequence, grapevine breeders have to select seedlings and new cultivars with regard to appropriate bunch traits. Bunch architecture is a mosaic of different single traits which makes phenotyping labor-intensive and time-consuming. In the present study, a fast and high-precision phenotyping pipeline was developed. The optical sensor Artec Spider 3D scanner (Artec 3D, L-1466, Luxembourg) was used to generate dense 3D point clouds of grapevine bunches under lab conditions and an automated analysis software called 3D-Bunch-Tool was developed to extract different single 3D bunch traits, i.e., the number of berries, berry diameter, single berry volume, total volume of berries, convex hull volume of grapes, bunch width and bunch length. The method was validated on whole bunches of different grapevine cultivars and phenotypic variable breeding material. Reliable phenotypic data were obtained which show high significant correlations (up to r2 = 0.95 for berry number) compared to ground truth data. Moreover, it was shown that the Artec Spider can be used directly in the field where achieved data show comparable precision with regard to the lab application. This non-invasive and non-contact field application facilitates the first high-precision phenotyping pipeline based on 3D bunch traits in large plant sets.
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影响因子：
5.1
作者：
Cubero, Sergio;Diago, Maria Paz;Aleixos, Nuria
通讯作者：
Aleixos, Nuria
影响因子：
5.1
作者：
Aquino, Arturo;Diago, Maria P.;Tardaguila, Javier
通讯作者：
Tardaguila, Javier
影响因子：
4.1
作者：
Tello, Javier;Cubero, Sergio;Ibanez, Javier
通讯作者：
Ibanez, Javier
影响因子：
4.5
作者：
Vail, ME;Wolpert, JA;Rademacher, MR
通讯作者：
Rademacher, MR
影响因子：
3
作者：
Wahabzada M;Paulus S;Kersting K;Mahlein AK
通讯作者：
Mahlein AK