Evidence map›Paper›PMID 28343247›Full record

ArticleTAG. Theoretical and applied genetics. Theoretische und angewandte Genetik2017

Development of a QTL-environment-based predictive model for node addition rate in common bean.

Li Zhang, Salvador A Gezan, C Eduardo Vallejos, James W Jones, Kenneth J Boote, Jose A Clavijo-Michelangeli, Mehul Bhakta, Juan M Osorno, Idupulapati Rao, Stephen Beebe and 6 more

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Article in TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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

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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

3 citing papers in PubMed.

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4 · The record

Corrections and comments

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

16 authors.

Li ZhangAgricultural and Biological Engineering Department, University of Florida, Gainesville, FL, 32611, USA.
Salvador A GezanSchool of Forest Resources and Conservation, University of Florida, Gainesville, FL, 32611, USA.
C Eduardo VallejosHorticultural Sciences Department, University of Florida, Gainesville, FL, 32611, USA.
James W JonesAgricultural and Biological Engineering Department, University of Florida, Gainesville, FL, 32611, USA.
Kenneth J BooteAgronomy Department, University of Florida, Gainesville, FL, 32611, USA.
Jose A Clavijo-MichelangeliAgronomy Department, University of Florida, Gainesville, FL, 32611, USA.
Mehul BhaktaHorticultural Sciences Department, University of Florida, Gainesville, FL, 32611, USA.
Juan M OsornoDepartment of Plant Sciences, North Dakota State University, Fargo, ND, 58108, USA.
Idupulapati RaoCIAT, Cali, Colombia.
Stephen BeebeCIAT, Cali, Colombia.
Elvin Roman-PaoliUniversity of Puerto Rico, Mayagüez, 00682, Puerto Rico.
Abiezer GonzalezUniversity of Puerto Rico, Mayagüez, 00682, Puerto Rico.
James BeaverUniversity of Puerto Rico, Mayagüez, 00682, Puerto Rico.
Jaumer RicaurteCIAT, Cali, Colombia.
Raphael ColbertDepartment of Plant Sciences, North Dakota State University, Fargo, ND, 58108, USA.
Melanie J CorrellAgricultural and Biological Engineering Department, University of Florida, Gainesville, FL, 32611, USA. correllm@ufl.edu.ORCID http://orcid.org/0000-0002-2432-6107

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

key messageThis work reports the effects of the genetic makeup, the environment and the genotype by environment interactions for node addition rate in an RIL population of common bean. This information was used to build a predictive model for node addition rate. To select a plant genotype that will thrive in targeted environments it is critical to understand the genotype by environment interaction (GEI). In this study, multi-environment QTL analysis was used to characterize node addition rate (NAR, node day

Indexed as

Gene-Environment InteractionQuantitative Trait LociEnvironmentGenotypeModels, GeneticPhaseolusSunlightTemperature

Identifiers

PMID28343247

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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.