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Record W7018892837

Enzymatic Hydrolysis of Flaxseed Oil to Produce Free Fatty Acids

2021· dissertation· en· W7018892837 on OpenAlexaboutno aff

Bibliographic record

VenueUniversity Library (University of Saskatchewan) · 2021
Typedissertation
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEnzyme Catalysis and Immobilization
Canadian institutionsnot available
Fundersnot available
KeywordsCandida rugosaAspergillus nigerLipaseHydrolysisTriacylglycerol lipaseLinoleic acidFatty acidEnzyme
DOInot available

Abstract

fetched live from OpenAlex

Microorganisms with the potential to secrete extracellular enzymes such as Candia rugosa and Aspergillus niger have the potential for industrial applications. The primary application of interest in this study includes the development of biocatalysts for the bioprocessing industry. Both microbial species secrete enzymes including lipase which has been used to catalyse the hydrolysis of glycerols. Saskatchewan is the largest producer of flaxseed worldwide accounting for 40% of worldwide flaxseed production. Flaxseed can be further processed to acquire nutrient-rich flaxseed oil. Linolenic and linoleic acids account for 58 wt. % and 15 wt. % of the total free fatty acids content of flaxseed oil. The free fatty acid concentrations can be increased via the process of enzymatic hydrolysis. α- linoleic and linolenic acids are high-value nutritional supplements in great demand in the pharmaceutical and health industries. In this study, the potential of lipase from Candida rugosa and Aspergillus niger to catalyse the hydrolysis of naturally occurring glycerols in flaxseed oil into free fatty acids was investigated. \nThe research work was divided into 2 phases. The first, optimization of reaction conditions. In this phase, the optimal reaction conditions for the hydrolysis of flaxseed oil catalyzed by lipase were determined. The reaction conditions pH, temperature and flaxseed oil concentration were set as the reaction parameters for optimization. A central composite design with three center points was used as the experimental design for optimization. The optimal reaction conditions for lipase from Aspergillus niger and Candida rugosa were determined independently. The second phase studied the enzyme kinetics of the hydrolysis of flaxseed oil using lipase. Kinetic analyses were performed using Michaelis-Menten modelling for enzyme kinetics. \nThe reaction conditions such as pH, reaction temperature, and oil to buffer ratio in a homogenous mixture (mL flaxseed oil to mL TRIS-HCl buffer) were investigated to optimize free fatty acid production. Optimum reaction conditions for Aspergillus niger lipase, ANL, were found to occur at a pH of 5 and a temperature of 35 C with a 15% flaxseed oil concentration. These conditions yielded an average of 78% increase in the free fatty acid concentration when compared to the FFA concentration of pure flaxseed oil. Optimum reaction conditions for Candida rugosa lipase, CRL occurred at a pH of 6.5 and a temperature of 30 C with a 10% flaxseed oil concentration. These conditions yielded a 95% increase on average in the free fatty acid concentration compared to pure flaxseed oil. Brunaurer-Emmett-Teller, BET, analysis of the surface characteristics of lipase showed CRL to have the greatest surface area of 11.7±0.1 (m2/g) and a pore diameter of 7.6 nm. The surface area and pore diameter for ANL were undetectable by BET characterization. Analyses of the kinetic parameters were conducted to determine the Michaelis-Menten constant, Km, maximum reaction velocity, Vm, and, the turnover number, kcat, respectively. The results are as follows; 4.25x10-5g/mL-sec, 1.06g/mL, 6.61x10-2/sec using CRL, 6.46x10-7, 1.62, 3.45x10-2/sec using ANL. The biomedical imaging and therapy facility beamline, BMIT, beamline imaging taken at the Canadian light source confirmed that the hydrolysis reaction takes place at the flaxseed oil-water interface as lipase becomes active and migrates to the interface. The results of this study showed CRL is the superior source of lipase compared to ANL based on the experimental findings, kinetic analyses, and enzyme characterizations. \n

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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 categoriesMeta-epidemiology (narrow)
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 score0.187
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.004
GPT teacher head0.170
Teacher spread0.166 · 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.

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

Citations0
Published2021
Admission routes1
Has abstractyes

Explore more

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