Articles
Using LiDAR to detect variations in leaf area and leaf area to fruit ratio in sweet cherry trees on different rootstocks
Article number
1433_5
Pages
39 – 46
Language
English
Abstract
Rootstocks affect yield, growth and canopy characteristics of fruit trees and are therefore essential for growing fruit of the same cultivar in locations with different soil and climatic conditions.
As the profitability of an orchard depends to a large extent on the choice of rootstock, new rootstocks are constantly being evaluated in many locations around the world.
Many of the tree architectural characteristics can be measured using LiDAR scanners, saving time and allowing the recording of characteristics that are difficult to quantify manually.
The focus of this study was on detecting differences in LiDAR scanned canopy characteristics between sweet cherry trees with different rootstocks.
Sweet cherry trees of two cultivars (‘Bedel’, ‘Regina’), each grafted on eight different rootstock combinations (Gisela 3, Gisela 5, Gisela 5 high grafted at 50 cm, Gisela 12, Gisela 13, PiKU 1, Weigi 2, Weiroot 720) were scanned with a terrestrial LiDAR laser scanner in the autumn of their tenth year after planting.
The leaf area per tree (LALiDAR) was extracted from the recorded LiDAR point clouds and the leaf area to fruit ratio (LA:F) was calculated, by using yield data from the previously harvested fruit.
Both LALiDAR and LA:F showed significant differences between rootstocks, with trees grafted on Gisela 13 having the highest LALiDAR and LA:F. In contrast, trees grafted on Gisela 3 rootstocks had the lowest LALiDAR. LALiDAR showed positive linear correlation to the manual measured trunk cross sectional area.
In addition, LA:F correlated positive with average fruit mass and negative with yield efficiency.
The results show that trials to test new cultivars and roostocks in fruit trees can be supported with terrestrial LiDAR scanners by recording the LALiDAR as additional canopy property which is currently impossible to record regularly in applied trials.
As the profitability of an orchard depends to a large extent on the choice of rootstock, new rootstocks are constantly being evaluated in many locations around the world.
Many of the tree architectural characteristics can be measured using LiDAR scanners, saving time and allowing the recording of characteristics that are difficult to quantify manually.
The focus of this study was on detecting differences in LiDAR scanned canopy characteristics between sweet cherry trees with different rootstocks.
Sweet cherry trees of two cultivars (‘Bedel’, ‘Regina’), each grafted on eight different rootstock combinations (Gisela 3, Gisela 5, Gisela 5 high grafted at 50 cm, Gisela 12, Gisela 13, PiKU 1, Weigi 2, Weiroot 720) were scanned with a terrestrial LiDAR laser scanner in the autumn of their tenth year after planting.
The leaf area per tree (LALiDAR) was extracted from the recorded LiDAR point clouds and the leaf area to fruit ratio (LA:F) was calculated, by using yield data from the previously harvested fruit.
Both LALiDAR and LA:F showed significant differences between rootstocks, with trees grafted on Gisela 13 having the highest LALiDAR and LA:F. In contrast, trees grafted on Gisela 3 rootstocks had the lowest LALiDAR. LALiDAR showed positive linear correlation to the manual measured trunk cross sectional area.
In addition, LA:F correlated positive with average fruit mass and negative with yield efficiency.
The results show that trials to test new cultivars and roostocks in fruit trees can be supported with terrestrial LiDAR scanners by recording the LALiDAR as additional canopy property which is currently impossible to record regularly in applied trials.
Authors
M. Penzel, L. Zimmermann, N. Tsoulias
Keywords
fruit mass, precision horticulture, Prunus avium L., replant condition, trunk cross sectional area (TCSA), trunk diameter, yield efficiency
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