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Record W1964177570 · doi:10.3390/plants4010001

Accumulation of Phosphorus-Containing Compounds in Developing Seeds of Low-Phytate Pea (Pisum sativum L.) Mutants

2014· article· en· W1964177570 on OpenAlexaff
Arun S. K. Shunmugam, Cheryl B. Bock, Gene Arganosa, Fawzy Georges, Gordon R. Gray, Thomas D. Warkentin

Bibliographic record

VenuePlants · 2014
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPhytase and its Applications
Canadian institutionsNational Research Council CanadaSaskatchewan Research Council (Canada)University of Saskatchewan
Fundersnot available
KeywordsPhytic acidPisumMutantField peaSativumBiologyGenotypePhosphorusOpen reading frameGeneticsChemistryBiochemistryBotanyGenePeptide sequence

Abstract

fetched live from OpenAlex

Low phytic acid (lpa) crops are low in phytic acid and high in inorganic phosphorus (Pi). In this study, two lpa pea genotypes, 1-150-81, 1-2347-144, and their progenitor CDC Bronco were grown in field trials for two years. The lpa genotypes were lower in IP₆ and higher in Pi when compared to CDC Bronco. The total P concentration was similar in lpa genotypes and CDC Bronco throughout the seed development. The action of myo-inositol phosphate synthase (MIPS) (EC 5.5.1.4) is the first and rate-limiting step in the phytic acid biosynthesis pathway. Aiming at understanding the genetic basis of the lpa mutation in the pea, a 1530 bp open reading frame of MIPS was amplified from CDC Bronco and the lpa genotypes. Sequencing results showed no difference in coding sequence in MIPS between CDC Bronco and lpa genotypes. Transcription levels of MIPS were relatively lower at 49 days after flowering (DAF) than at 14 DAF for CDC Bronco and lpa lines. This study elucidated the rate and accumulation of phosphorus compounds in lpa genotypes. The data also demonstrated that mutation in MIPS was not responsible for the lpa trait in these pea lines.

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 score0.649
Threshold uncertainty score0.137

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 head0.056
GPT teacher head0.282
Teacher spread0.225 · 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

Citations26
Published2014
Admission routes1
Has abstractyes

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