BreedVision--a multi-sensor platform for non-destructive field-based phenotyping in plant breeding.
BreedVision--a multi-sensor platform for non-destructive field-based phenotyping in plant breeding.
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DOI：
10.3390/s130302830
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发表时间：
2013-02-27
期刊：
影响因子：
--
通讯作者：
Ruckelshausen A
中科院分区：
文献类型：
--
作者：
Busemeyer L;Mentrup D;Möller K;Wunder E;Alheit K;Hahn V;Maurer HP;Reif JC;Würschum T;Müller J;Rahe F;Ruckelshausen A
到2050年，世界人口可能超过90亿，要实现不断增长的世界人口的粮食和能源安全，对植物育种来说是一项重大挑战。在过去的几十年里，我们在田间条件下测量性状的能力几乎没有提高，目前构成了作物改良的主要瓶颈。这项工作描述了一个拖拉机牵引的多传感器表型平台的小粒谷物的发展，重点是该系统的技术发展。系统集成了光幕成像、3D飞行时间相机、激光距离传感器、高光谱成像以及彩色成像等各种光学传感器，收集植物的光谱和形态信息。该研究详细说明了：机械设计、用于数据收集和数据处理的系统架构、综合系统的表型程序、用于数据质量评估的田间试验结果，以及用于确定植物高度的校准结果，作为平台应用的量化示例。在2011年和2012年，以小黑麦（×Triticosecale Wittmack L.）为模式种，在植物的三个发育阶段进行了重复测量。对于几乎所有不同类型的传感器，测量结果的技术重复性都很高，这证实了该平台在现场条件下的高适用性。开发的平台为进一步的传感器和多传感器融合模型的开发和校准奠定了坚实的基础，以测量各种农艺性状，如植物水分含量、倒伏、分蘖密度或生物量产量，因此，代表着扩大作物改良和植物遗传研究的非破坏性表型瓶颈的重要一步。
To achieve the food and energy security of an increasing World population likely to exceed nine billion by 2050 represents a major challenge for plant breeding. Our ability to measure traits under field conditions has improved little over the last decades and currently constitutes a major bottleneck in crop improvement. This work describes the development of a tractor-pulled multi-sensor phenotyping platform for small grain cereals with a focus on the technological development of the system. Various optical sensors like light curtain imaging, 3D Time-of-Flight cameras, laser distance sensors, hyperspectral imaging as well as color imaging are integrated into the system to collect spectral and morphological information of the plants. The study specifies: the mechanical design, the system architecture for data collection and data processing, the phenotyping procedure of the integrated system, results from field trials for data quality evaluation, as well as calibration results for plant height determination as a quantified example for a platform application. Repeated measurements were taken at three developmental stages of the plants in the years 2011 and 2012 employing triticale (×Triticosecale Wittmack L.) as a model species. The technical repeatability of measurement results was high for nearly all different types of sensors which confirmed the high suitability of the platform under field conditions. The developed platform constitutes a robust basis for the development and calibration of further sensor and multi-sensor fusion models to measure various agronomic traits like plant moisture content, lodging, tiller density or biomass yield, and thus, represents a major step towards widening the bottleneck of non-destructive phenotyping for crop improvement and plant genetic studies.
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影响因子：
8.3
作者：
Ehlert, Deflef;Horn, Hans-Juergen;Adamek, Rolf
通讯作者：
Adamek, Rolf
影响因子：
5.1
作者：
Saeys, W.;Lenaerts, B.;De Baerdemaeker, J.
通讯作者：
De Baerdemaeker, J.
影响因子：
5.8
作者：
Erdle, Klaus;Mistele, Bodo;Schmidhalter, Urs
通讯作者：
Schmidhalter, Urs
影响因子：
5.8
作者：
Ferrio, JP;Villegas, D;Royo, C
通讯作者：
Royo, C
影响因子：
5.8
作者：
Montes, J. M.;Technow, F.;Melchinger, A. E.
通讯作者：
Melchinger, A. E.