Challenges and Recommendations for 3d Plant Phenotyping in Agriculture Using Terrestrial Lasers Scanners

Medic, T.; Bömer, J.; Paulus, S.

doi:10.5194/isprs-annals-x-1-w1-2023-1007-2023

Cited by 3 publications

(1 citation statement)

References 28 publications

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“…The reference model was positioned at different angles and locations relative to the sensor to maximize the variability of structural influences like distance or angle of incidence as described by Medic et al. [ 57 ]. After generating a 3D point cloud from the individual scans of the LiDAR sensor, the reference plant was extracted manually.…”

Section: Methodsmentioning

confidence: 99%

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

Bömer,

Esser,

Marks

et al. 2024

GigaScience

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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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Section: Methodsmentioning

confidence: 99%

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

Bömer,

Esser,

Marks

et al. 2024

GigaScience

View full text Add to dashboard Cite

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Investigation of the rock mass state in the near-wall part of the quarry and its stability management

Saik,

Rysbekov,

Kassymkanova

et al. 2024

Front. Earth Sci.

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Introduction: The research is aimed to identify the vulnerable areas of quarry slopes through the creation of a stress-strain state model for the rock mass at the Vostochny quarry, East Saryoba field of the Zhi-landy Group of cupriferous sandstones, as well as their subsequent strengthening.Methods: The research is based on the development of a database containing information on mining-geological, geophysical, geodetic and aerospace surveys. The authors of the research use modern geodetic, aerospace and geophysical technologies for scientifically based predicting of technogenic disasters and the rock mass stress-strain state modeling to ensure safe and optimal mining of fields in difficult mining-geological conditions.Results: The results obtained show that the strengthening of weakened quarry slopes based on the rock mass stress-strain state modeling contributes to the scientific-practical profitability of field mining and provides safe mining in difficult mining-geological conditions.Discussion: Novelty is in the scientific substantiation of the method for strengthening quarry slopes, which is based on the rock mass stress-strain state modeling. The research is of great practical importance, as the rock mass stress-strain state modeling increases the reliability of predicting the rock mass state during its mining. Strengthening of quarry slopes using the proposed method reduces risks and increases safety and economic efficiency of mining the solid mineral deposits in difficult mining-geological conditions.

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Cotton morphological traits tracking through spatiotemporal registration of terrestrial laser scanning time-series data

Rodriguez-Sanchez,

Snider,

Johnsen

et al. 2024

Front. Plant Sci.

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Understanding the complex interactions between genotype-environment dynamics is fundamental for optimizing crop improvement. However, traditional phenotyping methods limit assessments to the end of the growing season, restricting continuous crop monitoring. To address this limitation, we developed a methodology for spatiotemporal registration of time-series 3D point cloud data, enabling field phenotyping over time for accurate crop growth tracking. Leveraging multi-scan terrestrial laser scanning (TLS), we captured high-resolution 3D LiDAR data in a cotton breeding field across various stages of the growing season to generate four-dimensional (4D) crop models, seamlessly integrating spatial and temporal dimensions. Our registration procedure involved an initial pairwise terrain-based matching for rough alignment, followed by a bird’s-eye view adjustment for fine registration. Point clouds collected throughout nine sessions across the growing season were successfully registered both spatially and temporally, with average registration errors of approximately 3 cm. We used the generated 4D models to monitor canopy height (CH) and volume (CV) for eleven cotton genotypes over two months. The consistent height reference established via our spatiotemporal registration process enabled precise estimations of CH (R2 = 0.95, RMSE = 7.6 cm). Additionally, we analyzed the relationship between CV and the interception of photosynthetically active radiation (IPARf), finding that it followed a curve with exponential saturation, consistent with theoretical models, with a standard error of regression (SER) of 11%. In addition, we compared mathematical models from the Richards family of sigmoid curves for crop growth modeling, finding that the logistic model effectively captured CH and CV evolution, aiding in identifying significant genotype differences. Our novel TLS-based digital phenotyping methodology enhances precision and efficiency in field phenotyping over time, advancing plant phenomics and empowering efficient decision-making for crop improvement efforts.

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Challenges and Recommendations for 3d Plant Phenotyping in Agriculture Using Terrestrial Lasers Scanners

Cited by 3 publications

References 28 publications

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

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

Investigation of the rock mass state in the near-wall part of the quarry and its stability management

Cotton morphological traits tracking through spatiotemporal registration of terrestrial laser scanning time-series data

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