Evidence map›Paper›PMID 36662255›Full record

ArticleTAG. Theoretical and applied genetics. Theoretische und angewandte Genetik2023

Simulations of rate of genetic gain in dry bean breeding programs.

Jennifer Lin, Vivi Arief, Zulfi Jahufer, Juan Osorno, Phil McClean, Diego Jarquin, Valerio Hoyos-Villegas

Erratum issuedAbstract read
In one paragraph

Article in TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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

6 citing papers in PubMed.

  1. Article
  2. Article
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  4. Review
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

7 authors.

Jennifer LinDepartment of Plant Science, McGill University, Montreal, Canada.
Vivi AriefUniversity of Queensland, Brisbane, Australia.
Zulfi JahuferUniversity of Queensland, Brisbane, Australia.
Juan OsornoNorth Dakota State University, Fargo, ND, USA.
Phil McCleanNorth Dakota State University, Fargo, ND, USA.
Diego JarquinUniversity of Florida, Gainesville, FL, USA.
Valerio Hoyos-VillegasDepartment of Plant Science, McGill University, Montreal, Canada. Valerio.hoyos-villegas@mcgill.ca.ORCID http://orcid.org/0000-0003-1080-9148

Funding

Natural Sciences and Engineering Research Council of Canada (NSERC) RGPIN-2020-07002
6 · The paper itself

Abstract

key messageA reference study for breeders aiming at maximizing genetic gain in common bean. Depending on trait heritability and genetic architecture, conventional approaches may provide an advantage over other frameworks. Dry beans (Phaseolus vulgaris L.) are a nutrient dense legume that is consumed by developed and developing nations around the world. The progress to improve this crop has been quite steady. However, with the continued rise in global populations, there are demands to expedite genetic gains. Plant breeders have been at the forefront at increasing yields in the common bean. As breeding programs are both time-consuming and resource intensive, resource allocation must be carefully considered. To assist plant breeders, computer simulations can provide useful information that may then be applied to the real world. This study evaluated multiple breeding scenarios in the common bean and involved five selection strategies, three breeding frameworks, and four different parental population sizes. In addition, the breeding scenarios were implemented in three different traits: days to flowering, white mold tolerance, and seed yield. Results from the study reflect the complexity of breeding programs, with the optimal breeding scenario varying based on trait being selected. Relative genetic gains per cycle of up to 8.69% for seed yield could be obtained under the use of the optimal breeding scenario. Principal component analyses revealed similarity between strategies, where single seed descent and the modified pedigree method would often aggregate. As well, clusters in the direction of the Hamming distance eigenvector are a good indicator of poor performance in a strategy.

Indexed as

PhaseolusPlant BreedingPhenotypeSeeds

Identifiers

PMID36662255
PMCPMC9859924

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.