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OliveCan: A Process-Based Model of Development, Growth and Yield of Olive Orchards

Overview of attention for article published in Frontiers in Plant Science, May 2018
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  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (95th percentile)
  • High Attention Score compared to outputs of the same age and source (99th percentile)

Mentioned by

news
9 news outlets
policy
1 policy source

Readers on

mendeley
75 Mendeley
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Title
OliveCan: A Process-Based Model of Development, Growth and Yield of Olive Orchards
Published in
Frontiers in Plant Science, May 2018
DOI 10.3389/fpls.2018.00632
Pubmed ID
Authors

Álvaro López-Bernal, Alejandro Morales, Omar García-Tejera, Luca Testi, Francisco Orgaz, J. P. De Melo-Abreu, Francisco J. Villalobos

Abstract

Several simulation models of the olive crop have been formulated so far, but none of them is capable of analyzing the impact of environmental conditions and management practices on water relations, growth and productivity under both well-irrigated and water-limiting irrigation strategies. This paper presents and tests OliveCan, a process-oriented model conceived for those purposes. In short, OliveCan is composed of three main model components simulating the principal elements of the water and carbon balances of olive orchards and the impacts of some management operations. To assess its predictive power, OliveCan was tested against independent data collected in two 3-year field experiments conducted in Córdoba, Spain, each of them applying different irrigation treatments. An acceptable level of agreement was found between measured and simulated values of seasonal evapotranspiration (ET, range 393 to 1016 mm year-1; RMSE of 89 mm year-1), daily transpiration (Ep, range 0.14-3.63 mm d-1; RMSE of 0.32 mm d-1) and oil yield (Yoil, range 13-357 g m-2; RMSE of 63 g m-2). Finally, knowledge gaps identified during the formulation of the model and further testing needs are discussed, highlighting that there is additional room for improving its robustness. It is concluded that OliveCan has a strong potential as a simulation platform for a variety of research applications.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 75 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 75 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 17 23%
Student > Ph. D. Student 9 12%
Student > Master 8 11%
Other 7 9%
Student > Doctoral Student 5 7%
Other 11 15%
Unknown 18 24%
Readers by discipline Count As %
Agricultural and Biological Sciences 37 49%
Environmental Science 6 8%
Unspecified 2 3%
Earth and Planetary Sciences 2 3%
Engineering 2 3%
Other 4 5%
Unknown 22 29%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 67. 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 24 August 2022.
All research outputs
#593,579
of 24,323,943 outputs
Outputs from Frontiers in Plant Science
#124
of 22,870 outputs
Outputs of similar age
#13,867
of 331,469 outputs
Outputs of similar age from Frontiers in Plant Science
#3
of 435 outputs
Altmetric has tracked 24,323,943 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 97th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 22,870 research outputs from this source. They receive a mean Attention Score of 3.9. This one has done particularly well, scoring higher than 99% 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 331,469 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 95% of its contemporaries.
We're also able to compare this research output to 435 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 99% of its contemporaries.