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Record W2966730320

Inheritance and quantitative trait loci analysis of folate content in dry beans.

2012· dissertation· en· W2966730320 on OpenAlexfundno aff
Sameer Khanal, Shi C, Wanzhuo Xie, Istvan Rajcan, Yu Kang, Pauls Kp, Alireza Navabi

Bibliographic record

VenueThe Atrium (University of Guelph) · 2012
Typedissertation
Languageen
FieldAgricultural and Biological Sciences
TopicPhytase and its Applications
Canadian institutionsnot available
FundersAgriculture and Agri-Food CanadaUniversity of Guelph
KeywordsQuantitative trait locusTraitBiologyInheritance (genetic algorithm)GeneticsComputer scienceGene
DOInot available

Abstract

fetched live from OpenAlex

Dry beans (Phaseolus vulgaris L.) contain high levels of folates. These compounds are essential vitamins and folate deficiencies may lead to a number of health problems. The objectives of this study were to examine the mode of inheritance of folate content and identify quantitative trait loci (QTL) associated with folate content in dry beans. Inheritance of folate content was studied in the F1 hybrids of one-way diallel crosses among Othello, AC Elk, Redhawk and Taylor, and an F2 population of the cross between Redhawk and Othello. Total folate content and 5 methyltetrahydrofolate (5MTHF) were measured twice within a one hour interval. Significant variation in folate content was observed among the parental genotypes, their F1 hybrids, and the F2 individuals of a cross between Redhawk and Othello, ranging from 147 to 345 µg/100g. Reductions in the 5MTHF content and total folate content values in the second measurement from samples were highly variable for all four parental lines ranging from 5 to 30% and 7 to 33%, respectively. A single marker QTL analysis identified at least three QTL for folate content in the F2 population. For the majority of identified QTL, dominance effects appeared to be the major genetic effect.

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 score0.969
Threshold uncertainty score0.989

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 head0.040
GPT teacher head0.237
Teacher spread0.197 · 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

Citations2
Published2012
Admission routes1
Has abstractyes

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