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Record W2594216924 · doi:10.2135/cropsci2016.10.0885

Past and Future Use of Wild Relatives in Crop Breeding

2017· article· en· W2594216924 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueCrop Science · 2017
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicGenetic and Environmental Crop Studies
Canadian institutionsUniversity of WaterlooUniversity of British Columbia
Fundersnot available
KeywordsCropAgricultureCrop diversityBiologyThreatened speciesGenetic resourcesAgroforestryResource (disambiguation)BiotechnologyPlant breedingEnvironmental resource managementAgronomyEcologyComputer science

Abstract

fetched live from OpenAlex

Wild species related to agricultural crops (crop wild relatives, or CWR) can increase the adaptive capacity of agricultural systems around the world. They represent a large pool of genetic diversity from which to draw new allelic variation required in breeding programs. Crop wild relatives have been extremely valuable in adapting crop varieties to changing disease pressures, farming practices, market demands, and climatic conditions. Unfortunately, CWR are a threatened resource and measures need to be taken to protect them, both in the wild and in genebanks. Here, we review how wild species have contributed to the development of improved crop varieties and where efforts must be concentrated to harness their value in the future. Drawing on the results of an extensive literature search, a series of 14 expert consultation meetings, and in‐depth interview with experts on 24 crops, we document the role that CWR play in modern crop breeding. We discuss (i) their past and current use, (ii) advanced breeding methods and technologies that promise to facilitate the continued use of CWR, and (iii) what constraints continue to hinder increased use of CWR in breeding.

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.

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 score0.381
Threshold uncertainty score0.556

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 studies0.0010.002
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 head0.042
GPT teacher head0.235
Teacher spread0.193 · 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