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Record W4378905738 · doi:10.1111/pbr.13117

Evidence of scientific research on organic plant breeding: A bibliometric study

2023· article· en· W4378905738 on OpenAlexaboutno aff
Bojan Mitrović, Miroslav Zorić, S. Terzić, Dalibor Živanov, Petar Čanak, Branko Milošević, Đura Karagić

Bibliographic record

VenuePlant Breeding · 2023
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Pathogens and Resistance
Canadian institutionsnot available
Fundersnot available
KeywordsOrganic farmingAgriculturePlant breedingWeb of scienceAgricultural scienceBiologyLibrary scienceBiotechnologyAgronomyEcologyComputer scienceMEDLINE

Abstract

fetched live from OpenAlex

Abstract Use of varieties bred under organic conditions is essential in order to minimize the yield gap between organic and conventional agriculture. The aim of this study was to analyse research publications related to the topic ‘organic plant breeding’ from the Web of Science database using bibliometric science mapping and visualization tools. The number of analysed documents in the bibliographic dataset was 204 from the 53 sources. The overall trend in the organic plant breeding literature showed that the number of publications increased during the observed time‐span. We found that in total, 65 countries and 337 institutions are active in the field of organic plant breeding with a high degree of international collaboration. The top five countries according to the number of publications were the United States, Italy, Germany, France, and Canada, while the most active institutions were Wageningen University, Iowa State University, University of Alberta, University of Copenhagen, and University of Hohenheim. All keywords from the organic plant breeding research in the agronomy category were separated into seven clusters for different research topics. Although there is evident progress viewed through the increased trend in the number of publications, organic plant breeding needs further expansion and development. This is especially through the implementation of novel plant breeding techniques and methods aiming to improve traits that are highly specific to organic conditions.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesBibliometrics
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.933
Threshold uncertainty score0.954

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0040.066
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.330
GPT teacher head0.345
Teacher spread0.015 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations2
Published2023
Admission routes1
Has abstractyes

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