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Record W2614233653

THE LENTIL-MEAT SYSTEM: INVESTIGATING THE ANTIOXIDANT EFFECT OF LENTIL ON COLOUR AND LIPID OXIDATION OF RAW BEEF BURGERS

2017· dissertation· en· W2614233653 on OpenAlexfundno aff
He Li

Bibliographic record

VenueUniversity Library - University of Saskatchewan (University of Saskatchewan) · 2017
Typedissertation
Languageen
FieldNursing
TopicNuts composition and effects
Canadian institutionsnot available
FundersChina Scholarship CouncilAgriculture and Agri-Food CanadaNatural Sciences and Engineering Research Council of CanadaSaskatchewan Pulse Growers
KeywordsFood scienceLipid oxidationAntioxidantChemistryHorticultureMathematicsBiologyBiotechnologyBiochemistry
DOInot available

Abstract

fetched live from OpenAlex

Discoloration and lipid oxidation are the main deteriorative causes of raw meat products.The flour of lentil, when heat treated, was found to protect fresh meat colour and inhibit lipid oxidation when incorporated into raw meat products.In order to postulate a possible mechanism of this useful functionality of lentil flour, three studies were conducted.In the first study, the impact of infrared heating to 115 and 150 o C and water bath heating of 90 o C (30 min) of different seed components of two Canadian lentil cultivars were evaluated.Enzyme activities, soluble proteins and phenolics that promote and negate oxidation reactions were assayed.The second study was designed to investigate the effects of seed coat and cotyledon with or without heat treatment in relation to enzyme and antioxidant activities in the ground meat system.It was investigated the effects on colour parameters (L*, a* and b*) and myoglobin redox states (met-, oxy-and deoxy-) of the product surface and lipid oxidation (thiobarbituric acid reactive substances: TBARS) during the refrigerated storage of lentil-ground meat product for 7 days.In the third study, the usability of lentil as a binder was evaluated when ground beef burgers containing the same levels of lentil components were stored for 12 weeks under frozen (-20 o C) condition, in terms of the effect on colour, myoglobin redox states and lipid oxidation.In the first study, it was found that the lipoxygenase, peroxidase and glutathione reductase activities were mostly found in cotyledon rather than in seed coat.The seed coat exhibited higher superoxide dismutase activity than cotyledon.The heat treatments tested were able to deactivate lipoxygenase, peroxidase and glutathione reductase significantly (P<0.05),but not the superoxide dismutase (P>0.05).Heat treatments significantly (P<0.05)increased Fe 2+ chelating activity for all samples.Soluble proteins in the seed coat (hull) showed higher antiradical (1,1-diphenyl-2picryl-hydrazyl: DDPH and 2,2'-azinobis-(3-ethylbenzothiazoline-6-sulfonic acid): ABTS) and antioxidant (ferric reducing antioxidant potential: FRAP, Fe 2+ chelating) activities than those obtained from the cotyledon, and this corresponded with the higher amount of protein-bound phenolic compounds.The extracts (water and 70% (v/v) ethanol) of the seed coat contained a values than those containing seed coat one (P<0.05).Significant negative correlations were found between a* value and metmyoglobin and between a* and TBARS values.Overall, it was found that the antioxidant activity of the water soluble components of the lentil seed is the main factor that protects colour and retards lipid oxidation in raw meat products, via metmyoglobin reduction, Fe 2+ chelating, free radicals scavenging and inhibition of unsaturated lipid oxidation catalyzed by metmyoglobin.The pro-oxidative activities of lentil components are mainly due to the oxidative enzymes and these enzymes are more sensitive to heat.The performance of lentil flour differs in meat products under refrigerated and frozen conditions.But heat-treated lentil flour can be considered more stable in providing colour protection and inhibiting lipid oxidation during storage.v Wanasundara for their instructions on my research and on my thinking of how to establish research work in the future.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.011
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.006
GPT teacher head0.187
Teacher spread0.181 · 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 source (direct Gemma or distilled Codex), 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

Citations3
Published2017
Admission routes1
Has abstractno

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