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Record W4378902638 · doi:10.3390/agronomy13061518

DNA-Based Molecular Markers and Antioxidant Properties to Study Genetic Diversity and Relationship Assessment in Blueberries

2023· article· en· W4378902638 on OpenAlexafffund
Samir C. Debnath, Dhrumit S. Bhatt, Juran C. Goyali

Bibliographic record

VenueAgronomy · 2023
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicBerry genetics and cultivation research
Canadian institutionsMemorial University of NewfoundlandAgriculture and Agri-Food Canada
FundersAgriculture and Agri-Food Canada
KeywordsGenetic diversityVacciniumAntioxidantBiologyCultivarBiotechnologyBerryHealth benefitsFood scienceBotanyComputational biologyTraditional medicineBiochemistryMedicine

Abstract

fetched live from OpenAlex

Blueberries (Vaccinium L. spp.) are an economically and medicinally important plant. Their antioxidant properties are well-known for their medicinal value in negating the harmful effects of free radicals. It is very important to develop genotypes that are high in health-promoting factors and economic value to meet present world needs. Estimation of genetic diversity using molecular markers, antioxidant properties, and their association can reveal genotypes with important characteristics and help in berry improvement programs. Wild blueberries are a better source of antioxidant metabolites compared to cultivated ones. Extensive variations are present in molecular and biochemical contents among wild clones and cultivars. The current review provides detailed and updated information on the economic and medicinal importance of blueberries, the application of molecular markers, and biochemical estimation in berry improvement and conservation, filling the gap in the literature.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.246

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.055
GPT teacher head0.262
Teacher spread0.207 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations11
Published2023
Admission routes2
Has abstractyes

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