Assessing T-LiDAR technology for high throughput phenotyping apple tree topological and architectural traits
| Autor: | Frédéric Boudon, Sébastien Martinez, Olivier Simler, Evelyne Costes, Benoît Pallas, Emma Carrie |
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| Přispěvatelé: | Amélioration génétique et adaptation des plantes méditerranéennes et tropicales (UMR AGAP), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro) |
| Jazyk: | angličtina |
| Rok vydání: | 2018 |
| Předmět: |
0106 biological sciences
Population pommier Apple tree Geometry 02 engineering and technology Horticulture Topology digitalisation 3 d surface foliaire 01 natural sciences Branching (linguistics) Leaf area High throughput phenotypic phénotypage 0202 electrical engineering electronic engineering information engineering [SDV.BV]Life Sciences [q-bio]/Vegetal Biology education Throughput (business) Mathematics topologie education.field_of_study Vegetal Biology Structure reconstruction architecture de l'arbre 020207 software engineering Branching points Tree (data structure) Lidar Allometry Biologie végétale 010606 plant biology & botany |
| Zdroj: | 30. International Horticultural Congress IHC2018 30. International Horticultural Congress IHC2018, Aug 2018, Istanbul, Turkey Proceedings International on Symposium Understanding Fruit Tree Behaviour in Dynamic Environments 2018; 30. International Horticultural Congress IHC2018, Istanbul, TUR, 2018-08-12-2018-08-16 |
| Popis: | We aim at extending methodologies based on T-Lidar scans for providing a description of individual apple tree topology and architecture. Experiments were performed on 2- and 3-year-old trees belonging to a core collection of French apple cultivars. In 2016, ten trees were precisely scanned in winter to assess our ability to extract topological traits. In 2017, the whole core-collection was scanned to estimate tree leaf areas at the end of the summer period. Topological reconstructions on 2016 data were performed with Plantscan3D software using existing algorithms whereas an allometric relationship depending on tree alpha hull volumes was used for estimating tree leaf areas on 2017 data. Topological traits extracted from T-LiDAR data were compared to digitizing data of the same trees and the estimated total leaf areas were compared to manual measurements on a sample of twenty trees displaying large variability in vegetative development. In 2016, topological reconstructions gave promising results with R² values higher than 0.90 for the total number of axes and growth units pet tree and for their mean length when T-Lidar were compared to digitizing data. However, a significant number of short axes or growth units were not detected by the T-Lidar. Comparisons between T-LiDAR and digitizing data showed g ood adequacy if axes were classified depending on their branching order suggesting that our method was relevant for evaluating the number of branching points in the structure. Regarding data collected on leafy trees in 2017, the total leaf area estimated from T-LiDAR was also highly correlated (R²= 0.83) with manual measurements. Forthcoming works are undergoing for improving topological reconstruction algorithms in order to extract topological traits and new variables related to vegetative development on the whole population. Nevertheless this first study suggests that this method could be adapted for phenotypic architectural traits on large tree population on which genetic analyses could be performed. |
| Databáze: | OpenAIRE |
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