Evidence map›Paper›PMID 35803981›Full record

ArticleScientific reports2022

Adaptability and stability of Coffea canephora to dynamic environments using the Bayesian approach.

Fabio Luiz Partelli, Flavia Alves da Silva, André Monzoli Covre, Gleison Oliosi, Caio Cezar Guedes Correa, Alexandre Pio Viana

Abstract read
In one paragraph

Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Nutritional Efficiency ofPlants (Basel, Switzerland) · 2025
    Article
  5. Coffee Breeding and Stress Biology.Plants (Basel, Switzerland) · 2024
    Article
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

6 authors.

Fabio Luiz PartelliCentro Universitário Norte do Espírito Santo, Universidade Federal do Espírito Santo, 29932-540, São Mateus, Espírito Santo, Brasil.
Flavia Alves da SilvaLaboratório de Melhoramento Genético Vegetal, Universidade Estadual do Norte Fluminense Darcy Ribeiro, 28013-602, Campos dos Goytacazes, Rio de Janeiro, Brasil. flavia_uems@hotmail.com.
André Monzoli CovreCentro Universitário Norte do Espírito Santo, Universidade Federal do Espírito Santo, 29932-540, São Mateus, Espírito Santo, Brasil.
Gleison OliosiCentro Universitário Norte do Espírito Santo, Universidade Federal do Espírito Santo, 29932-540, São Mateus, Espírito Santo, Brasil.
Caio Cezar Guedes CorreaCentro de Ciências Agrárias Engenharias, Universidade Federal do Espíerito Santo, 29500-000, Alegre, Espírito Santo, Brasil.
Alexandre Pio VianaLaboratório de Melhoramento Genético Vegetal, Universidade Estadual do Norte Fluminense Darcy Ribeiro, 28013-602, Campos dos Goytacazes, Rio de Janeiro, Brasil.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The objective of this work was to use the Bayesian approach, modeling the interaction of coffee genotypes with the environment, using a bisegmented regression to identify stable and adapted genotypes. A group of 43 promising genotypes of Coffea canephora was chosen. The genotypes were arranged in a randomized block design with three replications of seven plants each. The experimental plot was harvested four years in the study period, according to the maturation cycle of each genotype. The proposed Bayesian methodology was implemented in the free program R using rstanarm and coda packages. It was possible to use previous information on coffee genotypes as prior information on parameter distributions of an Adaptability and Stability model, which allowed obtaining shorter credibility intervals and good evidence of low bias in the model by the determination coefficient. After fine adjustments in the approach, it was possible to make inferences about the significant GxE interaction and to discriminate the coffee genotypes regarding production, adaptability, and stability. This is still a new approach for perennials, and since it allows more accurate estimates it can be advantageous when planning breeding programs. The Z21 genotype is recommended to compose part of selected genetic material for highly technical farmers, as it responds very well to the favorable environment, being one of the most productive and with excellent stability.

Indexed as

CoffeaBayes TheoremCoffeeGenotypePlant BreedingCoffee

Identifiers

PMID35803981
PMCPMC9270379

What OpenQuestion holds

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Registered trials

None linked

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.