Assessment of Laser Scanner Use under Different Settings in Two Differently Managed Vineyards for Estimating Pruning Wood Parameters

Anastasiou, Evangelos; Balafoutis, Athanasios T.; Theocharis, Serafeim; Theodorou, Nikolaos; Koundouras, Stéfanos; Fountas, Spyros

doi:10.3390/agriengineering4030047

Cited by 4 publications

(1 citation statement)

References 27 publications

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“…The feasibility of the model was verified through virtual experiments on environmental conditions (the amount of light and temperature) and the species characteristics of simulated trees (the number of buds and branching angle) [9]. Anastasiou et al [10] assessed a laser scanner sensor for accurate estimation of pruning wood parameters in vineyards and found that the laser scanner emerged as a valuable tool for vineyard applications. It also shows that the point cloud data acquired by LiDAR are crucial for tree pruning.…”

Section: Introductionmentioning

confidence: 99%

A Multiple Criteria Decision-Making Method Generated by the Space Colonization Algorithm for Automated Pruning Strategies of Trees

Zhao,

Wang

2024

AgriEngineering

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The rise of mechanical automation in orchards has sparked research interest in developing robots capable of autonomous tree pruning operations. To achieve accurate pruning outcomes, these robots require robust perception systems that can reconstruct three-dimensional tree characteristics and execute appropriate pruning strategies. Three-dimensional modeling plays a crucial role in enabling accurate pruning outcomes. This paper introduces a specialized tree modeling approach using the space colonization algorithm (SCA) tailored for pruning. The proposed method extends SCA to operate in three-dimensional space, generating comprehensive cherry tree models. The resulting models are exported as normalized point cloud data, serving as the input dataset. Multiple criteria decision analysis is utilized to guide pruning decisions, incorporating various factors such as tree species, tree life cycle stages, and pruning strategies during real-world implementation. The pruning task is transformed into a point cloud neural network segmentation task, identifying the trunks and branches to be pruned. This approach reduces the data acquisition time and labor costs during development. Meanwhile, pruning training in a virtual environment is an application of digital twin technology, which makes it possible to combine the meta-universe with the automated pruning of fruit trees. Experimental results demonstrate superior performance compared to other pruning systems. The overall accuracy is 85%, with mean accuracy and mean Intersection over Union (IoU) values of 0.83 and 0.75. Trunks and branches are successfully segmented with class accuracies of 0.89 and 0.81, respectively, and Intersection over Union (IoU) metrics of 0.79 and 0.72. Compared to using the open-source synthetic tree dataset, this dataset yields 80% of the overall accuracy under the same conditions, which is an improvement of 6%.

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Section: Introductionmentioning

confidence: 99%

A Multiple Criteria Decision-Making Method Generated by the Space Colonization Algorithm for Automated Pruning Strategies of Trees

Zhao,

Wang

2024

AgriEngineering

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Precision farming technologies for crop protection: A meta-analysis

Anastasiou,

Fountas,

Voulgaraki

et al. 2023

Smart Agricultural Technology

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Delineating Natural Terroir Units in Wine Regions Using Geoinformatics

et al. 2023

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The terroir effect refers to the interactions between the grapes and their natural surroundings and has been recognized as an important factor in wine quality. The identification and mapping of viticultural terroir have long been relying on expert opinion coupled with land classification and soil/climate mapping. In this study, the data-driven approach has been implemented for mapping natural terroir units based on spatial modeling of public-access geospatial information regarding the three most important environmental factors that make up the terroir effect on different scales, climate, soil, and topography. K-means cluster analysis was applied to the comprehensive databases of relevant spatial information, and the optimum number of clusters was identified by the Dunn and CCC indices. The results have revealed ten clusters that cover the agricultural area of Drama (Greece), where it was applied, and displayed variable conditions on the climate, soil, and topographic factors. The implications of the resulting natural terroir units on the vini-viticultural management of the most common vine varieties are discussed. As more accurate and detailed input spatial data become available, the potential of such an approach is highlighted and paving the way toward a true understanding of the drivers of terroir.

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Assessment of Laser Scanner Use under Different Settings in Two Differently Managed Vineyards for Estimating Pruning Wood Parameters

Cited by 4 publications

References 27 publications

A Multiple Criteria Decision-Making Method Generated by the Space Colonization Algorithm for Automated Pruning Strategies of Trees

A Multiple Criteria Decision-Making Method Generated by the Space Colonization Algorithm for Automated Pruning Strategies of Trees

Precision farming technologies for crop protection: A meta-analysis

Delineating Natural Terroir Units in Wine Regions Using Geoinformatics

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