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Quantifying pruning impacts on olive tree architecture and annual canopy growth by using UAV-based 3D modelling

Overview of attention for article published in Plant Methods, July 2017
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  • Above-average Attention Score compared to outputs of the same age and source (52nd percentile)

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Title
Quantifying pruning impacts on olive tree architecture and annual canopy growth by using UAV-based 3D modelling
Published in
Plant Methods, July 2017
DOI 10.1186/s13007-017-0205-3
Pubmed ID
Authors

F. M. Jiménez-Brenes, F. López-Granados, A. I. de Castro, J. Torres-Sánchez, N. Serrano, J. M. Peña

Abstract

Tree pruning is a costly practice with important implications for crop harvest and nutrition, pest and disease control, soil protection and irrigation strategies. Investigations on tree pruning usually involve tedious on-ground measurements of the primary tree crown dimensions, which also might generate inconsistent results due to the irregular geometry of the trees. As an alternative to intensive field-work, this study shows a innovative procedure based on combining unmanned aerial vehicle (UAV) technology and advanced object-based image analysis (OBIA) methodology for multi-temporal three-dimensional (3D) monitoring of hundreds of olive trees that were pruned with three different strategies (traditional, adapted and mechanical pruning). The UAV images were collected before pruning, after pruning and a year after pruning, and the impacts of each pruning treatment on the projected canopy area, tree height and crown volume of every tree were quantified and analyzed over time. The full procedure described here automatically identified every olive tree on the orchard and computed their primary 3D dimensions on the three study dates with high accuracy in the most cases. Adapted pruning was generally the most aggressive treatment in terms of the area and volume (the trees decreased by 38.95 and 42.05% on average, respectively), followed by trees under traditional pruning (33.02 and 35.72% on average, respectively). Regarding the tree heights, mechanical pruning produced a greater decrease (12.15%), and these values were minimal for the other two treatments. The tree growth over one year was affected by the pruning severity and by the type of pruning treatment, i.e., the adapted-pruning trees experienced higher growth than the trees from the other two treatments when pruning intensity was low (<10%), similar to the traditionally pruned trees at moderate intensity (10-30%), and lower than the other trees when the pruning intensity was higher than 30% of the crown volume. Combining UAV-based images and an OBIA procedure allowed measuring tree dimensions and quantifying the impacts of three different pruning treatments on hundreds of trees with minimal field work. Tree foliage losses and annual canopy growth showed different trends as affected by the type and severity of the pruning treatments. Additionally, this technology offers valuable geo-spatial information for designing site-specific crop management strategies in the context of precision agriculture, with the consequent economic and environmental benefits.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 164 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 164 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 31 19%
Student > Ph. D. Student 26 16%
Student > Master 10 6%
Student > Doctoral Student 10 6%
Lecturer 8 5%
Other 35 21%
Unknown 44 27%
Readers by discipline Count As %
Agricultural and Biological Sciences 42 26%
Environmental Science 16 10%
Engineering 16 10%
Computer Science 8 5%
Medicine and Dentistry 4 2%
Other 15 9%
Unknown 63 38%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 4. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 02 October 2020.
All research outputs
#7,334,819
of 24,363,506 outputs
Outputs from Plant Methods
#451
of 1,175 outputs
Outputs of similar age
#108,720
of 317,245 outputs
Outputs of similar age from Plant Methods
#13
of 25 outputs
Altmetric has tracked 24,363,506 research outputs across all sources so far. This one has received more attention than most of these and is in the 69th percentile.
So far Altmetric has tracked 1,175 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.5. This one has gotten more attention than average, scoring higher than 61% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 317,245 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 65% of its contemporaries.
We're also able to compare this research output to 25 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 52% of its contemporaries.