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Record W4394826684 · doi:10.5376/tgg.2024.15.0002

Genetic Diversity and Molecular Marker Discovery of Adaptive Traits in Triticeae Crops

2024· article· en· W4394826684 on OpenAlexvenueno aff
Weichang Wu

Bibliographic record

VenueTriticeae Genomics and Genetics · 2024
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicWheat and Barley Genetics and Pathology
Canadian institutionsnot available
Fundersnot available
KeywordsTriticeaeBiologyGenetic diversityMolecular markerBiotechnologyGeneticsGenePopulationMedicine

Abstract

fetched live from OpenAlex

Triticeae crops, including wheat, barley and rye, are of concern because of their important role in the global food supply, and their adaptive traits, such as drought, salt and alkali tolerance and disease resistance, are key determinants of their productivity and stability. The formation of adaptive traits is affected by many environmental and genetic factors, and its genetic diversity is of great significance to the adaptive ability and genetic improvement of Triticeae crops. This study summarized the genetic diversity of adaptive traits in Triticeae crops and its evaluation methods. In particular, the use of molecular marker technologies such as single nucleotide polymorphism (SNP) and simple sequence repeat (SSR) in the assessment and utilization of these traits, Molecular markers not only reveal the complexity of genetic diversity, but also accelerate the study of genes associated with adaptive traits, providing a powerful tool for molecular assisted breeding. Bioinformatics methods combined with molecular markers will further promote the study of adaptive traits of Triticeae crops, and provide a scientific basis for coping with climate change and improving food security.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.962
Threshold uncertainty score0.341

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 head0.017
GPT teacher head0.208
Teacher spread0.190 · 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

Citations1
Published2024
Admission routes1
Has abstractyes

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