A 3D printed plant model for accurate and reliable 3D plant phenotyping.

IF 11.8 2区 生物学 Q1 MULTIDISCIPLINARY SCIENCES GigaScience Pub Date : 2024-01-02 DOI:10.1093/gigascience/giae035
Jonas Bömer, Felix Esser, Elias Marks, Radu Alexandru Rosu, Sven Behnke, Lasse Klingbeil, Heiner Kuhlmann, Cyrill Stachniss, Anne-Katrin Mahlein, Stefan Paulus
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Abstract

Background: This study addresses the importance of precise referencing in 3-dimensional (3D) plant phenotyping, which is crucial for advancing plant breeding and improving crop production. Traditionally, reference data in plant phenotyping rely on invasive methods. Recent advancements in 3D sensing technologies offer the possibility to collect parameters that cannot be referenced by manual measurements. This work focuses on evaluating a 3D printed sugar beet plant model as a referencing tool.

Results: Fused deposition modeling has turned out to be a suitable 3D printing technique for creating reference objects in 3D plant phenotyping. Production deviations of the created reference model were in a low and acceptable range. We were able to achieve deviations ranging from -10 mm to +5 mm. In parallel, we demonstrated a high-dimensional stability of the reference model, reaching only ±4 mm deformation over the course of 1 year. Detailed print files, assembly descriptions, and benchmark parameters are provided, facilitating replication and benefiting the research community.

Conclusion: Consumer-grade 3D printing was utilized to create a stable and reproducible 3D reference model of a sugar beet plant, addressing challenges in referencing morphological parameters in 3D plant phenotyping. The reference model is applicable in 3 demonstrated use cases: evaluating and comparing 3D sensor systems, investigating the potential accuracy of parameter extraction algorithms, and continuously monitoring these algorithms in practical experiments in greenhouse and field experiments. Using this approach, it is possible to monitor the extraction of a nonverifiable parameter and create reference data. The process serves as a model for developing reference models for other agricultural crops.

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用于准确可靠的三维植物表型的三维打印植物模型。
背景:本研究探讨了三维(3D)植物表型分析中精确参照的重要性,这对推进植物育种和提高作物产量至关重要。传统上,植物表型分析中的参考数据依赖于侵入式方法。三维传感技术的最新进展为收集人工测量无法参考的参数提供了可能。这项工作的重点是评估作为参照工具的三维打印甜菜植物模型:结果:熔融沉积建模已被证明是一种适用于创建三维植物表型参考对象的三维打印技术。所创建参考模型的生产偏差较低,在可接受范围内。我们能够实现 -10 毫米到 +5 毫米的偏差范围。与此同时,我们还证明了参考模型的高维稳定性,在一年的时间里变形量仅为±4毫米。我们提供了详细的打印文件、装配说明和基准参数,为复制提供了便利,并使研究界受益匪浅:结论:利用消费级三维打印技术创建了稳定且可重复的甜菜植物三维参考模型,解决了三维植物表型中形态参数参考的难题。该参考模型适用于 3 个示范用例:评估和比较三维传感器系统、研究参数提取算法的潜在准确性,以及在温室和田间试验的实际实验中持续监控这些算法。使用这种方法,可以监测不可验证参数的提取,并创建参考数据。这一过程可作为开发其他农作物参考模型的范例。
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来源期刊
GigaScience
GigaScience MULTIDISCIPLINARY SCIENCES-
CiteScore
15.50
自引率
1.10%
发文量
119
审稿时长
1 weeks
期刊介绍: GigaScience seeks to transform data dissemination and utilization in the life and biomedical sciences. As an online open-access open-data journal, it specializes in publishing "big-data" studies encompassing various fields. Its scope includes not only "omic" type data and the fields of high-throughput biology currently serviced by large public repositories, but also the growing range of more difficult-to-access data, such as imaging, neuroscience, ecology, cohort data, systems biology and other new types of large-scale shareable data.
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