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The tensor-based model for growth and cell divisions of the root apex. I. The significance of principal directions

Overview of attention for article published in Planta, March 2008
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Title
The tensor-based model for growth and cell divisions of the root apex. I. The significance of principal directions
Published in
Planta, March 2008
DOI 10.1007/s00425-008-0728-y
Pubmed ID
Authors

Jerzy Nakielski

Abstract

Plant organs grow symplastically, i.e. in a continuous and coordinated way. Such growth is of a tensor nature, which is manifested in the property that at every point of the organ three mutually orthogonal principal growth directions (PDG) can be recognized. The PDGs are postulated to affect orientation of cell divisions. This paper shows for the first time the 2D simulation model for growth in which cells divide taking into account the PDGs. The model, conceptually based on the growth tensor (GT), is applied to the root apex of radish, having a quiescent centre (QC). It shows the simulation of how exemplary cell pattern of the real root apex develops in time. The results provide satisfactory description of the root growth. The computer-generated cell pattern is realistic and more or less steady indicating that PDGs are important for growth. Presumably cells detect PDGs and obey them in the course of cell divisions. Computer generated division walls, perpendicular to PDGs, form periclinal and anticlinal zigzags as regular as those observed in microscopic sections. Growth tensor defines a field of growth rates at the organ level. QC, fundamental in this field, determines the group of quiescent initial cells which is, in turn, surrounded by active functional initials, from which all tissues of the root apex originate. The present simulations have shown that stability of generated cell pattern depends on whether the group of the functional initials is permanent; if this is not the case, the cell wall pattern changes in accordance with PDGs.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 45 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Netherlands 1 2%
United Kingdom 1 2%
Mexico 1 2%
Belgium 1 2%
Poland 1 2%
Unknown 40 89%

Demographic breakdown

Readers by professional status Count As %
Researcher 14 31%
Student > Ph. D. Student 11 24%
Professor 4 9%
Professor > Associate Professor 4 9%
Student > Bachelor 2 4%
Other 5 11%
Unknown 5 11%
Readers by discipline Count As %
Agricultural and Biological Sciences 27 60%
Computer Science 4 9%
Biochemistry, Genetics and Molecular Biology 3 7%
Physics and Astronomy 3 7%
Engineering 2 4%
Other 1 2%
Unknown 5 11%
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 03 December 2010.
All research outputs
#20,187,333
of 22,703,044 outputs
Outputs from Planta
#2,370
of 2,713 outputs
Outputs of similar age
#78,007
of 81,168 outputs
Outputs of similar age from Planta
#12
of 13 outputs
Altmetric has tracked 22,703,044 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 2,713 research outputs from this source. They receive a mean Attention Score of 3.3. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
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We're also able to compare this research output to 13 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.