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Record W7018565390

Development of edible films from gelatin extracted from Argentine shortfin squid «Illex Argentinus» with the use of an enzyme (pepsin) aided process

2017· dissertation· en· W7018565390 on OpenAlexafffund

Bibliographic record

VenueeScholarship@McGill (McGill) · 2017
Typedissertation
Languageen
FieldMaterials Science
TopicNanocomposite Films for Food Packaging
Canadian institutionsMcGill University
FundersMcGill University
KeywordsGelatinExtraction (chemistry)Yield (engineering)SquidElongationEnzymeUltimate tensile strength
DOInot available

Abstract

fetched live from OpenAlex

Gelatin, a protein biopolymer, can be easily derived from marine biomass.Studies have been carried out on different marine gelatin sources.However, there is still limited research on films formed using squid gelatin.For this study, gelatin was extracted from shortfin squid (Illex argentinus) using an enzyme-aided method, specifically pepsin, under different reaction conditions; enzyme concentrations of 25, 15 and 5U of pepsin/g of dehydrated squid, heat extraction temperatures of 45 °C, 55 °C and 65 °C and extraction durations of 12, 18 and 24 hours.These parameters were observed to have a direct effect on not only the quality and yield of gelatin but as well as the edible films formed and their respective properties.Optimal conditions for each parameter were determined and used to extract subsequent gelatin for the formation of edible films.Results indicated that the optimal enzyme concentration, 25 U/g, produced the highest yield of gelatin at 6.59% ± 0.7221.Through the BCA assay, the highest protein concentration was determined to be of 671.5 µg/ml ± 0.0045.The lowest extraction temperature, 45 °C in conjunction with the lowest extraction duration, 12 hours, was determined to be the shrinkage temperature at which the triple helix arrangement of the polypeptide subunits in the collagen molecule will collapse due to the non-covalent and covalent inter-and intra-molecular bonds breaking, converting into gelatin.However, the lack of fragments of beta and alpha chains indicated the extraction of low-quality gelatin.Film forming solutions of 4% and 8% gelatin-glycerol films were characterized to have a tensile strength of 0.229 ± 0.0037 N/mm 2 and 0.939N/mm 2 ± 0.0104 respectively.The elongation at break remained relatively stable at 27.2% ± 0.1979 and 22.3% ± 0.0824 respectively.The water solubility of both films was calculated to be 100%.The opacity of the films indicated that both films were effective in blocking both UV and visible light at opacities higher than 90% showing effectiveness in blocking lipid oxidation.The present study indicated that it is possible to extract gelatin and despite it being low quality, edible films with adequate properties were formed.Further studies are required in order to explore optimization for gelatin extraction as well as film properties.Department of Food Science for this incredible learning opportunity for the fulfillment of this degree.I have walked away from this experience with immense appreciation in this field of research.I would not have been able to successfully complete the research without the guidance and support received from the members of the department.A special thanks to Dr. Ngadi and the students in his lab for allowing me access to their facilities and freeze dryer.This aided in my lab work immensely and helped me obtain the best possible results.I would also like to thank the students in Dr. Karboune's lab for sharing their expertise with me and helping me learn outside of my scope.I am appreciative for all of their encouragements.There is a special place in my heart for all of my lab colleagues for their endless guidance and emotional support over this past year and a half.I would like to thank you all for your kind words and friendship that made this experience so much more enjoyable.From the bottom of my heart, I would like to thank my parents, brothers, and sister for their continual support and endless love.Thank you for the encouragement and for always pushing me to do and be the best that I can.Without your sacrifices and heartfelt prayers, I know that none of this would have been possible.Thank you for believing in me especially when I did not.I would also like to

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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 score0.001
Threshold uncertainty score0.002

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 head0.038
GPT teacher head0.264
Teacher spread0.226 · 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

Citations1
Published2017
Admission routes2
Has abstractyes

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