Evidence map›Paper›PMID 34264990›Full record

ArticlePloS one2021

Genetic divergence for adaptability and stability in sugarcane: Proposal for a more accurate evaluation.

João de Andrade Dutra Filho, Tercilio Calsa Júnior, Djalma Euzébio Simões Neto, Lauter Silva Souto, Anielson Dos Santos Souza, Rômulo Gil de Luna, Frank Gomes-Silva, Guilherme Rocha Moreira, Moacyr Cunha-Filho, André Luiz Pinto Dos Santos and 4 more

Erratum issuedAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in PloS one, 2021. 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 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Evaluation of a Sugarcane (Plants (Basel, Switzerland) · 2023
    Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

14 authors.

João de Andrade Dutra FilhoBiological Sciences Nucleus, Federal University of Pernambuco, Vitória de Santo Antão, Pernambuco, Brazil.ORCID 0000-0002-9515-7267
Tercilio Calsa JúniorGenetics Department, Federal University of Pernambuco, Recife, Pernambuco, Brazil.
Djalma Euzébio Simões NetoCarpina Sugarcane Experimental Station, Federal Rural University of Pernambuco, Carpina, Pernambuco, Brazil.
Lauter Silva SoutoAgrarian Sciences Academic Unit, Federal University of Campina Grande, Pombal, Paraíba, Brazil.
Anielson Dos Santos SouzaAgrarian Sciences Academic Unit, Federal University of Campina Grande, Pombal, Paraíba, Brazil.
Rômulo Gil de LunaEnvironmental Technology Sciences Academic Unit, Federal University of Campina Grande, Pombal, Paraíba, Brazil.
Frank Gomes-SilvaStatistics and Informatics Department, Federal Rural University of Pernambuco, Recife, Pernambuco, Brazil.
Guilherme Rocha MoreiraStatistics and Informatics Department, Federal Rural University of Pernambuco, Recife, Pernambuco, Brazil.
Moacyr Cunha-FilhoStatistics and Informatics Department, Federal Rural University of Pernambuco, Recife, Pernambuco, Brazil.
André Luiz Pinto Dos SantosStatistics and Informatics Department, Federal Rural University of Pernambuco, Recife, Pernambuco, Brazil.
Cícero Carlos Ramos de BritoFederal Institute of Pernambuco, Recife, Pernambuco, Brazil.
Fabiana Aparecida Cavalcante SilvaPhytosanitary Diagnosis Laboratory, Northeast Strategic Technologies Center, Recife, Pernambuco, Brazil.ORCID 0000-0002-4674-895X
Andréa Chaves Fiuza PortoAgricultural College Dom Agostinho Ikas, Federal Rural University of Pernambuco, Carpina, Pernambuco, Brazil.
Maria Lindomárcia Leonardo da CostaAnimal Science Department, Federal University of Paraíba, Areia, Paraíba, Brazil.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The best agro-industrial performance presented by a crop genotype in one environment may not be reproduced in another owing to complex edaphoclimatic variations. Therefore, breeding programs are constantly attempting to obtain, through artificial hybridization, novel genotypes with high adaptability and stability potential. The objective of this study was to analyze genetic divergence in sugarcane based on the genotypic values of adaptability and stability. A total of 11 sugarcane genotypes were analyzed for eight agro-industrial traits. The genotypic values of the traits were determined using mixed model methodology, and the genetic divergence based on phenotypic and genotypic values was measured using the Mahalanobis distance. The distance matrices were correlated using the Mantel test, and the genotypes were grouped using the Tocher method. Genetic divergence is more accurate when based on genotypic values free of genotype-environment interactions and will differ from genetic divergence based on phenotypic data, changing the genotype allocations in the groups. The above methodology can be applied to assess genetic divergence to obtain novel sugarcane genotypes with higher productivity that are adapted to intensive agricultural systems using diverse technologies. This methodology can also be tested in other crops to increase accuracy in selecting the parents to be crossed.

Indexed as

GenotypePhenotypeSaccharumAdaptation, PhysiologicalCrops, AgriculturalGenetic VariationPlant Breeding

Identifiers

PMID34264990
PMCPMC8282048

What OpenQuestion holds

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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.