Plant Architecture Modelling: Virtual Plants and Complex Systems

Godin, Christophe; Costes, Evelyne; Sinoquet, Hervé

doi:10.1002/9781119312994.apr0171

Cited by 9 publications

(5 citation statements)

References 124 publications

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“…The geometric mean of the maximum and minimum diameters determined the mean diameter of the oval-shaped roots 24 . The output data file was analysed using AMAPmod software 25 , which handles topological structure and provides 3D graphical reconstruction for data validation (Fig. 1).…”

Section: Methodsmentioning

confidence: 99%

“…Using Fastrak technology, it is possible to estimate several root biometric and geometric parameters at different soil depths and radial distributions, such as biomass, length, diameter, and angle. However, some limitations have been noted for these root techniques, such as high sensitivity to wind fluctuations in the field for the sonic digitizer 25 and the interference with the Fastrak magnetic field by surrounding iron frames 26 . Above all, root excavation methods are extremely time consuming and labour intensive, and they are not always an option, especially in urban environments, because of the presence of pavement as well as underground service lines, pipes, rocks, and other buried materials.…”

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confidence: 99%

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A sonic root detector for revealing tree coarse root distribution

Proto

Iorio

Abenavoli

et al. 2020

Sci Rep

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this study assesses the reliability of a non-destructive method for determining the in situ distribution of tree coarse roots within a scaled distance 6-fold the DBH by comparing the results with the actual 3D root architecture revealed by invasive methods. The root architecture of 22-year-old olive trees was determined non-destructively with a Root Detector device (Fakopp Enterprise Bt) using sonic speed and directly by a 3D digitizer (Fastrak, Polhemus) after soil removal. The radial and vertical distributions of the coarse root biomass and diameter in the soil as determined by the 3D digitizer were correlated with the root map detected by sonic speed. A highly significant correlation was observed between the coarse root biomass distribution and the sonic speed within 30 cm of soil depth, but this correlation decreased with increasing distance from the trunk, up to 120 cm. No correlations were observed between sonic speed and root diameter. The Root Detector was able to map the coarse roots of the olive tree in the soil environment, but only under certain conditions. First, root detection was more efficient within 30 cm of soil depth, provided that more than 35% of the total biomass of lateral roots occurs within this depth range. Second, the distance of 120 cm from the trunk, scaled as 6-fold the DBH, may be considered the threshold over which the sonic speed and the detection of roots markedly decreased. Third, Root Detector technology is unable to detect root size in terms of geometric parameters such as root diameter.

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Section: Methodsmentioning

confidence: 99%

mentioning

confidence: 99%

A sonic root detector for revealing tree coarse root distribution

Proto

Iorio

Abenavoli

et al. 2020

Sci Rep

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“…To generate the complexity index, we use the fractal dimension, which is a ratio that measures how the detail of geometry changes at different scales (Godin et al, 2005). We used box-counting in three-dimensional arrays (Chatzigeorgiou Group, 2019) as the method for our measurement, which is a standard procedure for calculating the fractal dimension of 3D objects.…”

Section: Measurement and Comparisonmentioning

confidence: 99%

An Artificial Intelligence Agent That Synthesises Visual Abstractions of Natural Forms to Support the Design of Human-Made Habitat Structures

et al. 2022

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Biodiversity is in a state of global collapse. Among the main drivers of this crisis is habitat degradation that destroys living spaces for animals, birds, and other species. Design and provision of human-made replacements for natural habitat structures can alleviate this situation. Can emerging knowledge in ecology, design, and artificial intelligence (AI) help? Current strategies to resolve this issue include designing objects that reproduce known features of natural forms. For instance, conservation practitioners seek to mimic the function of rapidly disappearing large old trees by augmenting utility poles with perch structures. Other approaches to restoring degraded ecosystems employ computational tools to capture information about natural forms and use such data to monitor remediation activities. At present, human-made replacements of habitat structures cannot reproduce significant features of complex natural forms while supporting efficient construction at large scales. We propose an AI agent that can synthesise simplified but ecologically meaningful representations of 3D forms that we define as visual abstractions. Previous research used AI to synthesise visual abstractions of 2D images. However, current applications of such techniques neither extend to 3D data nor engage with biological conservation or ecocentric design. This article investigates the potential of AI to support the design of artificial habitat structures and expand the scope of computation in this domain from data analysis to design synthesis. Our case study considers possible replacements of natural trees. The application implements a novel AI agent that designs by placing three-dimensional cubes – or voxels – in the digital space. The AI agent autonomously assesses the quality of the resulting visual abstractions by comparing them with three-dimensional representations of natural trees. We evaluate the forms produced by the AI agent by measuring relative complexity and features that are meaningful for arboreal wildlife. In conclusion, our study demonstrates that AI can generate design suggestions that are aligned with the preferences of arboreal wildlife and can support the development of artificial habitat structures. The bio-informed approach presented in this article can be useful in many situations where incomplete knowledge about complex natural forms can constrain the design and performance of human-made artefacts.

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“…Such discrete and explicit models consider root architecture through its complete discrete topology and geometry and can be based on several distinct mathematical formalisms (Godin, 2000 ; Balduzzi et al, 2017 ). Two of the most popular formalisms used to represent discrete plant architecture in general are multi-scale tree graphs (MTGs) (Godin and Caraglio, 1998 ; Godin et al, 1999 , 2005 ) and L-systems (Prusinkiewicz and Lindenmayer, 1990 ).…”

Section: Root System Architectural Modelingmentioning

confidence: 99%

Virtual Plants Need Water Too: Functional-Structural Root System Models in the Context of Drought Tolerance Breeding

et al. 2017

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Developing a sustainable agricultural model is one of the great challenges of the coming years. The agricultural practices inherited from the Green Revolution of the 1960s show their limits today, and new paradigms need to be explored to counter rising issues such as the multiplication of climate-change related drought episodes. Two such new paradigms are the use of functional-structural plant models to complement and rationalize breeding approaches and a renewed focus on root systems as untapped sources of plant amelioration. Since the late 1980s, numerous functional and structural models of root systems were developed and used to investigate the properties of root systems in soil or lab-conditions. In this review, we focus on the conception and use of such root models in the broader context of research on root-driven drought tolerance, on the basis of root system architecture (RSA) phenotyping. Such models result from the integration of architectural, physiological and environmental data. Here, we consider the different phenotyping techniques allowing for root architectural and physiological study and their limits. We discuss how QTL and breeding studies support the manipulation of RSA as a way to improve drought resistance. We then go over the integration of the generated data within architectural models, how those architectural models can be coupled with functional hydraulic models, and how functional parameters can be measured to feed those models. We then consider the assessment and validation of those hydraulic models through confrontation of simulations to experimentations. Finally, we discuss the up and coming challenges facing root systems functional-structural modeling approaches in the context of breeding.

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Plant Architecture Modelling: Virtual Plants and Complex Systems

Abstract: The sections in this article areIntroductionNature of Plant Architecture: Basic ConceptsRepresenting and Analysing Plant ArchitectureModelling Functions on Static StructuresModels of Plant DevelopmentConclusion and PerspectivesAcknowledgements

Cited by 9 publications

References 124 publications

A sonic root detector for revealing tree coarse root distribution

A sonic root detector for revealing tree coarse root distribution

An Artificial Intelligence Agent That Synthesises Visual Abstractions of Natural Forms to Support the Design of Human-Made Habitat Structures

Virtual Plants Need Water Too: Functional-Structural Root System Models in the Context of Drought Tolerance Breeding

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