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Record W6982018707

Genetic Study and QTL Analysis on Soybean Seed Protein Quality and Quantity

2022· dissertation· en· W6982018707 on OpenAlexaboutno aff

Bibliographic record

VenueThe Atrium (University of Guelph) · 2022
Typedissertation
Languageen
FieldChemical Engineering
TopicChemical Safety and Risk Management
Canadian institutionsnot available
Fundersnot available
KeywordsMethionineQuantitative trait locusProtein qualityAmino acidLysineGenotypeTraitCysteine
DOInot available

Abstract

fetched live from OpenAlex

Soybean (Glycine max (L.) Merrill) protein quality is limited by deficiencies in the concentrations of amino acids cysteine (Cys), methionine (Met), threonine (Thr), and lysine (Lys). This study aimed to: (1) assess the effects of genotype, environment, and genotype-by-environment interactions (GEI) on seed protein quantity and quality in two recombinant inbred line (RIL) populations derived from amino acid manipulated fast neutron mutants, in multi-environment trials (MET) conducted in four environments in southern Ontario; and (2) to identify and validate quantitative trait loci (QTL) associated with seed protein quantity and quality in the two populations. Genotype and environment effects were significant for all target traits. Significant GEI effects on protein, Thr, and Lys were observed in at least one population. A modified QTL-seq analysis discovered genomic regions associated with target traits in three of the 20 soybean chromosomes. These results may be useful for breeding efforts on improving soybean protein nutrition.

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 score0.919
Threshold uncertainty score0.740

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 head0.247
Teacher spread0.231 · 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

Citations0
Published2022
Admission routes1
Has abstractyes

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