3D modeling and reconstruction of plants and trees: A cross-cutting review across computer graphics, vision, and plant phenotyping

Okura, Fumio

doi:10.1270/jsbbs.21074

Cited by 27 publications

(11 citation statements)

References 217 publications

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“…As a result, digital phenotyping has gained popularity as a means of reducing the workload for researchers. In recent years, a variety of methods for 3D model reconstruction of plants in digital phenotyping have been reported (Okura, 2022). However, there is still a paucity of studies evaluating the phenotypic traits of plants using 3D models, as the technology is still under development with a focus on methodology and software.…”

Section: Discussionmentioning

confidence: 99%

Development of a digital phenotyping system using 3D model reconstruction for zoysiagrass

Pongpiyapaiboon

Tanaka

Hashiguchi

et al. 2023

The Plant Phenome Journal

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Digital phenotyping, particularly the use of plant 3D models, is a promising method for high‐throughput plant evaluation. Although many recent studies on the topic have been published, further research is needed to apply it to breeding research and other related fields. In this study, using a 3D model phenotyping system we developed, we reconstructed and analyzed 20 accessions of zoysiagrass (Zoysia spp.), including three species and their hybrid, over a period of 1 year. Artificial neural network with three hidden layers was able to effectively remove nonplant parts while retaining plant parts that were incorrectly removed using the cropping method, offering a robust and flexible approach for post‐processing of 3D models. The system also demonstrated its ability to accurately evaluate a range of traits, including height, area, and color using red green blue (RGB)‐based vegetation indices. The results showed a high correlation between the estimated volume obtained from voxel 3D model and dry weight, enabling its use as a non‐destructive method for measuring plant volume. In addition, we found that the green red normalized difference index from RGB‐based indices was similar to the commonly used normalized difference vegetation index in controlled illumination conditions. These results demonstrate the potential for three‐dimensional model phenotyping to facilitate plant breeding, particularly in the field of turfgrass and feed crops.

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Section: Discussionmentioning

confidence: 99%

Development of a digital phenotyping system using 3D model reconstruction for zoysiagrass

Pongpiyapaiboon

Tanaka

Hashiguchi

et al. 2023

The Plant Phenome Journal

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“…The modeling of the kinematics [64,65], statics, and dynamic [66,67] of botanical systems is crucial to understanding their evolution and behavior under specific loads such as wind or fruit weight. Trunks, branches, and roots are all deformable and slender bodies characterized by one direction (the length) prevalent with respect to the other two (the crosssection), and, from a mechanical perspective, they can be described as beams.…”

Section: Kinematics Statics and Dynamicsmentioning

confidence: 99%

Soft robotics for farm to fork: applications in agriculture & farming

Armanini,

Junge,

Johnson

et al. 2024

Bioinspir. Biomim.

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Agricultural tasks and environments range from harsh field conditions with semi-structured produce or animals, through to post-processing tasks in food processing environment. From farm to fork, the development and application of soft robotics offers a plethora of potential uses. Robust yet compliant interactions between farm produce and machines and will enable new capabilities and optimize existing processes. There is also an opportunity to explore how modelling tools used in soft robotics can be applied to improve our representation and understanding of the soft and compliant structures common in agriculture. In this review we seek to highlight the potential for soft robotics technologies within the food system, and also the unique challenges that must be addressed when developing soft robotics systems for this problem domain. We conclude with an outlook on potential directions for meaningful and sustainable impact, and also how our outlook on both soft robotics and agriculture must evolve in order to achieve the required paradigm shift.

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“…Future advances that allow for higher spatialand temporal-resolution forest and canopy structure data to be collected from satellites will enable the quantification and mapping of canopy structure over wider and longer scales. Although analytical challenges remain in moving from the point-clouds produced by LiDAR systems to full and robust representations of the three-dimensional networks of branches and lianas that connect the forest canopy (Okura, 2022), it is likely that we will, in the near future, have the ability to recreate detailed maps of these environments.…”

Section: A Virtual Window Into a 25d Worldmentioning

confidence: 99%

Life in 2.5D: Animal Movement in the Trees

et al. 2022

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The complex, interconnected, and non-contiguous nature of canopy environments present unique cognitive, locomotor, and sensory challenges to their animal inhabitants. Animal movement through forest canopies is constrained; unlike most aquatic or aerial habitats, the three-dimensional space of a forest canopy is not fully realized or available to the animals within it. Determining how the unique constraints of arboreal habitats shape the ecology and evolution of canopy-dwelling animals is key to fully understanding forest ecosystems. With emerging technologies, there is now the opportunity to quantify and map tree connectivity, and to embed the fine-scale horizontal and vertical position of moving animals into these networks of branching pathways. Integrating detailed multi-dimensional habitat structure and animal movement data will enable us to see the world from the perspective of an arboreal animal. This synthesis will shed light on fundamental aspects of arboreal animals’ cognition and ecology, including how they navigate landscapes of risk and reward and weigh energetic trade-offs, as well as how their environment shapes their spatial cognition and their social dynamics.

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3D modeling and reconstruction of plants and trees: A cross-cutting review across computer graphics, vision, and plant phenotyping

Cited by 27 publications

References 217 publications

Development of a digital phenotyping system using 3D model reconstruction for zoysiagrass

Development of a digital phenotyping system using 3D model reconstruction for zoysiagrass

Soft robotics for farm to fork: applications in agriculture & farming

Life in 2.5D: Animal Movement in the Trees

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