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Record W3017249640 · doi:10.1007/s11947-020-02436-7

Growth Region Impacts Cell Wall Properties and Hard-to-Cook Phenotype of Canned Navy Beans (Phaseolus vulgaris)

2020· article· en· W3017249640 on OpenAlexaboutno aff
Jin Chu, Peter Ho, Caroline Orfila

Bibliographic record

VenueFood and Bioprocess Technology · 2020
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPolysaccharides and Plant Cell Walls
Canadian institutionsnot available
FundersUniversity of Leeds
KeywordsPhaseolusMiddle lamellaCell wallBlanchingCultivarFood scienceChemistryPectinGalactosePolysaccharideArabinoseBotanyHorticultureBiologyBiochemistry

Abstract

fetched live from OpenAlex

Abstract Cellular mechanisms underpinning the hard-to-cook phenomenon are poorly understood. Navy beans ( Phaseolus vulgaris ) from the same cultivar but grown in different regions of North America showed different canning characteristics. Up to 46.4% more force was required to disrupt hard beans (HB) grown in Ontario compared with soft beans (SB) grown in Manitoba. HB absorbed 12.5% and 14.7% less water during blanching and canning, respectively. Microscopic assessment revealed that canning led to swelling of middle lamella and cell walls, but preservation of cell adhesion in both types of beans. Immunofluorescence microscopy showed reduced labelling of methyl-esterified homogalacturonan (HG) and more non-methyl-esterified HG and arabinan epitopes in HB. Compositional analysis indicated that the polysaccharides from HB were less water soluble and enriched in neutral sugars, including 46.5% more arabinose and 51.8% more galactose than in SB. ELISA analysis of polymers in the canning medium supported the increased solubility of cell wall polymers in SB. In the same cultivar, growth region affects cell wall properties with consequences for processing, eating and nutritional quality.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.283

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 head0.026
GPT teacher head0.180
Teacher spread0.154 · 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

Citations22
Published2020
Admission routes1
Has abstractyes

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