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4D phenotyping of germinating seeds and seedlings as a tool to objectively measure seed quality and improve field establishment and yield of sugar beets

机译:发芽种子和幼苗的4D表型分析作为客观测量种子质量并改善甜菜田间建立和产量的工具

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The plant breeding company Strube, in cooperation with the German Fraunhofer Institute for non-destructive testing, has developed an automated high-throughput germination test for sugar beet seeds. The phenoTest permits objective measurement and classification of germinating seeds and resulting seedlings. It is therefore more accurate and provides more information than the conventional ISTA (International Seed Testing Association)-germination test, which relies purely on visual assessment and classification into the categories "normal" or "abnormal". This differentiation is difficult to standardise, and is, to a significant degree, subjective. The phenoTest is based on three-dimensional (3D) X-ray images. Repeated tests of the same plants enable an objective assessment of seedling development over the course of time (4D phenotyping). The individual organs of each plant (radicle, hypocotyl and cotyledons) are automatically identified and measured. The method provides detailed information on germinating capacity and vigour, as well as the homogeneity of a seed lot. Results are documented as measurement values and 3D-images of each individual plant at different time points. The data is used to compare seed lots concerning their natural germination capacity and especially vigour, the processing or priming technologies they experienced, the pelleting and seed treatment applied etc. in order to predict their field emergence potential even under difficult growing conditions. These analyses also helps to optimise all these processes in commercial seed production to obtain a quick, homogeneous and complete field emergence, making full use of the genetic yield potential of sugar beet.
机译:植物育种公司Strube与德国Fraunhofer研究所合作进行无损检测,开发了甜菜种子的自动化高通量发芽测试。 phenoTest可以对发芽的种子和所得的幼苗进行客观的测量和分类。因此,它比常规的ISTA(国际种子测试协会)发芽测试更为准确,并提供更多信息,后者仅依赖于视觉评估并将其分类为“正常”或“异常”类别。这种区分很难标准化,并且在很大程度上是主观的。 phenoTest基于三维(3D)X射线图像。重复测试相同的植物可以客观评估一段时间内的幼苗发育(4D表型)。自动识别和测量每种植物的单个器官(胚根,下胚轴和子叶)。该方法提供了有关发芽能力和活力以及种子批次同质性的详细信息。结果记录为不同时间点每个植物的测量值和3D图像。数据用于比较种子批次的自然发芽能力,特别是活力,种子经历的加工或引发技术,制粒和种子处理等,以便即使在艰难的生长条件下也能预测其出苗潜力。这些分析还有助于优化商业种子生产中的所有这些过程,以获得快速,均匀和完整的田间出苗,充分利用甜菜的遗传产量潜力。

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