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Record W2594343316 · doi:10.1071/cp16252

Association analysis of molecular markers with traits under drought stress in safflower

2017· article· en· W2594343316 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 and Pasture Science · 2017
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicSunflower and Safflower Cultivation
Canadian institutionsCanadian Council on International Law
Fundersnot available
KeywordsBiologyCarthamusAmplified fragment length polymorphismQuantitative trait locusDrought stressAgronomyBotanyHorticulturePopulationGenetic diversityGeneticsGene

Abstract

fetched live from OpenAlex

This study was performed to identify marker loci associated with important agronomic traits and oil content under two moisture conditions and find stable associations in test environments in a worldwide collection of safflower (Carthamus tinctorius L.). Association analysis was conducted between eight important traits and 341 polymorphic AFLP markers produced by 10 primer combinations (EcoRI/MseI) in 100 safflower genotypes. The results of population structure analysis identified three main subpopulations possessing significant genetic differences revealed by analysis of molecular variance. Association analysis explained the highest percentage of trait variation for seed yield (38%) under drought-stress conditions and number of seeds per capitulum (27.75%) under normal conditions. Four markers (M51/E41-6, M51/E41-4, M61/E40-6 and M62/E40-17) in drought-stress conditions and two markers (M62/E40-35 and M47/E37-13) in normal conditions were simultaneously associated with seed and oil yield. The markers stably associated with traits in all test environments included M62/E40-35 with seed yield in normal conditions, M62/E40-17 with seed yield in drought stress conditions, and M62/E41-11 with oil yield in drought-stress conditions. Significant relationships were identified between oil content and three markers (M61/E40-6, M47/E37-8 and M51/E32-9) under drought-stress conditions, and three markers (M61/E2-2, M61/E40-6 and M51/E41-12) under normal conditions. Among them, M51/E32-9 and M61/E2-2 markers showed stable association with oil content under drought-stress and normal conditions, respectively. Detected markers would be useful in marker-assisted breeding programs for safflower improvement in arid and semi-arid area.

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 score0.245
Threshold uncertainty score0.235

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.009
GPT teacher head0.229
Teacher spread0.220 · 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