Evidence map›Paper›PMID 37287031›Full record

ArticlePlant methods2023

A successive time-to-event model of phyllochron dynamics for hypothesis testing: application to the analysis of genetic and environmental effects in maize.

Sandra Plancade, Elodie Marchadier, Sylvie Huet, Adrienne Ressayre, Camille Noûs, Christine Dillmann

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Article in Plant methods, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
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2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

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4 · The record

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PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Sandra PlancadeUR MIAT, University of Toulouse, INRAE, 31320, Castanet-Tolosan, France. sandra.plancade@inrae.fr.
Elodie MarchadierGQE - Le Moulon, Université Paris-Saclay, INRAE, CNRS, AgroParisTech, IDEEV, 12 route 128, 91190, Gif-sur-Yvette, France.
Sylvie HuetMaIAGE, Université Paris-Saclay, INRAE, 78350, Jouy-en-Josas, France.
Adrienne RessayreGQE - Le Moulon, Université Paris-Saclay, INRAE, CNRS, AgroParisTech, IDEEV, 12 route 128, 91190, Gif-sur-Yvette, France.
Camille NoûsCogitamus Laboratory, 31320, Castanet-Tolosan, France.
Christine DillmannGQE - Le Moulon, Université Paris-Saclay, INRAE, CNRS, AgroParisTech, IDEEV, 12 route 128, 91190, Gif-sur-Yvette, France.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe time between the appearance of successive leaves, or phyllochron, characterizes the vegetative development of annual plants. Hypothesis testing models, which allow the comparison of phyllochrons between genetic groups and/or environmental conditions, are usually based on regression of thermal time on the number of leaves; most of the time a constant leaf appearance rate is assumed. However regression models ignore auto-correlation of the leaf number process and may lead to biased testing procedures. Moreover, the hypothesis of constant leaf appearance rate may be too restrictive.

methodsWe propose a stochastic process model in which emergence of new leaves is considered to result from successive time-to-events. This model provides a flexible and more accurate modeling as well as unbiased testing procedures. It was applied to an original maize dataset collected in the field over three years on plants originating from two divergent selection experiments for flowering time in two maize inbred lines. RESULTS AND

conclusionWe showed that the main differences in phyllochron were not observed between selection populations but rather between ancestral lines, years of experimentation and leaf ranks. Our results highlight a strong departure from the assumption of a constant leaf appearance rate over a season which could be related to climate variations, even if the impact of individual climate variables could not be clearly determined.

Indexed as

Climate variablesDivergent selectionGenotypic effectsHypothesis testing modelMaizePhenology and plant developmentPhyllochronStochastic processTime to event

Identifiers

PMID37287031
PMCPMC10245529

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.