MétaCan
Menu
Back to cohort
Record W3039714957 · doi:10.1021/acs.jafc.9b07866

Do Faba Bean Genotypes Carrying Different Zero-Tannin Genes (<i>zt1</i> and <i>zt2</i>) Differ in Phenolic Profiles?

2020· article· en· W3039714957 on OpenAlexafffund
Stefano Zanotto, Hamid Khazaeı, Fatma M. Elessawy, Albert Vandenberg, Randy W. Purves

Bibliographic record

VenueJournal of Agricultural and Food Chemistry · 2020
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant pathogens and resistance mechanisms
Canadian institutionsCanadian Food Inspection AgencyUniversity of Saskatchewan
FundersInnovationsfondenWestern Grains Research FoundationMinistry of Agriculture - Saskatchewan
KeywordsTanninCoatCondensed tanninProanthocyanidinLegumeBiologyGenotypeGenePhenolsPhenotypeFood scienceBotanyPolyphenolBiochemistry

Abstract

fetched live from OpenAlex

Faba bean is a cool season grain legume that produces seeds with a high protein content. Seed coat tannins limit its use in food and feed. A low-tannin phenotype is controlled by either of two unlinked recessive genes zt1 and zt2. Liquid chromatography–mass spectrometry was used to characterize phenolic profiles of seed coat and flower tissue of three faba bean genotypes: CDC Snowdrop (zt1 gene), Disco/2 (zt2 gene), and ILB 938/2 (tannin-containing). For both tissues, clear differences in phenolic profiles of ILB 938/2 were observed in comparison to both low-tannin lines. Although seed coat phenolic profiles of zt1 and zt2 genotypes were similar, distinct differences were evident in flower tissue, suggesting that the gene action results in some different end products of the phenolic biosynthetic pathway. These distinctive compounds could be used as biochemical markers to distinguish between low-tannin phenotypes.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.552
Threshold uncertainty score0.285

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 head0.015
GPT teacher head0.179
Teacher spread0.164 · 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 designBench or experimental
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

Citations19
Published2020
Admission routes2
Has abstractyes

Explore more

Same venueJournal of Agricultural and Food ChemistrySame topicPlant pathogens and resistance mechanismsFrench-language works237,207