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Kinetic Modeling of Sunflower Grain Filling and Fatty Acid Biosynthesis

Overview of attention for article published in Frontiers in Plant Science, May 2016
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Title
Kinetic Modeling of Sunflower Grain Filling and Fatty Acid Biosynthesis
Published in
Frontiers in Plant Science, May 2016
DOI 10.3389/fpls.2016.00586
Pubmed ID
Authors

Ignacio Durruty, Luis A. N. Aguirrezábal, María M. Echarte

Abstract

Grain growth and oil biosynthesis are complex processes that involve various enzymes placed in different sub-cellular compartments of the grain. In order to understand the mechanisms controlling grain weight and composition, we need mathematical models capable of simulating the dynamic behavior of the main components of the grain during the grain filling stage. In this paper, we present a non-structured mechanistic kinetic model developed for sunflower grains. The model was first calibrated for sunflower hybrid ACA855. The calibrated model was able to predict the theoretical amount of carbohydrate equivalents allocated to the grain, grain growth and the dynamics of the oil and non-oil fraction, while considering maintenance requirements and leaf senescence. Incorporating into the model the serial-parallel nature of fatty acid biosynthesis permitted a good representation of the kinetics of palmitic, stearic, oleic, and linoleic acids production. A sensitivity analysis showed that the relative influence of input parameters changed along grain development. Grain growth was mostly affected by the specific growth parameter (μ') while fatty acid composition strongly depended on their own maximum specific rate parameters. The model was successfully applied to two additional hybrids (MG2 and DK3820). The proposed model can be the first building block toward the development of a more sophisticated model, capable of predicting the effects of environmental conditions on grain weight and composition, in a comprehensive and quantitative way.

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Mendeley readers

The data shown below were compiled from readership statistics for 21 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Chile 1 5%
Singapore 1 5%
Unknown 19 90%

Demographic breakdown

Readers by professional status Count As %
Researcher 6 29%
Student > Ph. D. Student 5 24%
Student > Master 2 10%
Student > Postgraduate 2 10%
Professor > Associate Professor 2 10%
Other 1 5%
Unknown 3 14%
Readers by discipline Count As %
Agricultural and Biological Sciences 15 71%
Engineering 2 10%
Unknown 4 19%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 06 May 2016.
All research outputs
#20,323,943
of 22,867,327 outputs
Outputs from Frontiers in Plant Science
#16,138
of 20,246 outputs
Outputs of similar age
#253,072
of 298,725 outputs
Outputs of similar age from Frontiers in Plant Science
#387
of 512 outputs
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