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Record W7077042165 · doi:10.5376/tgg.2024.15.0017

Spread and Adaptation of <i>Triticeae</i> Crops: From Ancient Origins to Global Distribution

2024· article· en· W7077042165 on OpenAlexvenueno aff

Bibliographic record

VenueTriticeae Genomics and Genetics · 2024
Typearticle
Languageen
FieldComputer Science
TopicGeochemistry and Geologic Mapping
Canadian institutionsnot available
Fundersnot available
KeywordsTriticeaeDomesticationAdaptation (eye)AgricultureAgricultural productivityClimate change

Abstract

fetched live from OpenAlex

Triticeae  crops, such as wheat, barley, and rye,are globally important food crops critical for human and animal nutrition and ecosystem sustainability. Understanding the origins, domestication, and global dissemination mechanisms of these crops is essential for improving their production efficiency and adaptability. This study reviews the early evolution of Triticeae  crops and their wild relatives, the genetic changes during domestication, and the impact of early agricultural practices, trade, and migration routes on their spread. It explores the adaptation mechanisms of Triticeae  crops to climate, soil, and pests, and summarizes the application of modern breeding technologies in enhancing yield and disease resistance. The research indicates that Triticeae  crops underwent significant genetic changes during domestication, which have been elucidated through modern genetic techniques. Early agricultural practices and ancient civilizations played a crucial role in the dissemination of these crops. Modern genetic improvement technologies, such as genome editing and marker-assisted selection, have significantly enhanced crop yield and disease resistance. By comprehensively reviewing the domestication and dissemination history of Triticeae  crops, this study provides valuable genetic resources and strategies for modern breeding programs. Understanding the adaptation mechanisms of these crops in different environments will aid in developing more resilient and high-yielding varieties to meet the growing global food demand.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.652
Threshold uncertainty score0.777

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 head0.016
GPT teacher head0.236
Teacher spread0.219 · 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 designNot applicable
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

Citations0
Published2024
Admission routes1
Has abstractyes

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