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Record W2890656750

Development and characterization of peptide antioxidants from sorghum proteins

2018· dissertation· en· W2890656750 on OpenAlexfundno aff
Sihua Xu

Bibliographic record

VenueK-State Research Exchange (Kansas State University) · 2018
Typedissertation
Languageen
FieldArts and Humanities
TopicHermeneutics and Narrative Identity
Canadian institutionsnot available
FundersGlaucoma Research Society of Canada
KeywordsSorghumCharacterization (materials science)PeptideBiochemistryChemistryComputational biologyBiologyNanotechnologyAgronomyMaterials science
DOInot available

Abstract

fetched live from OpenAlex

Antioxidants are widely used in food industries to delay lipid oxidation and prevent oxidative deterioration. In recent years, growing interests in developing safe and efficient antioxidants from natural sources due to the health-related risks associated with synthetic antioxidants. Recently, peptide antioxidants have drawn growing interests as since proteins are a macronutrient with various functionalities and high consumer acceptability. A lot of dietary proteins have been validated for their antioxidant potentials especially those obtained from animal proteins, nuts and pulses. Relatively less information is available on characterizing the antioxidant profile of cereal protein, and even less for sorghum protein. Sorghum is the fifth largest crop worldwide and is the third in United States. U.S. is leading in global sorghum production and distribution, and the state of Kansas is producing nearly half of U.S. sorghum. Currently, about one third of the U.S. sorghum is being used for ethanol production, resulting in more than 450 kilotons of by-products (e.g., DDGS) annually, which were often discarded or underutilized. DDGS is a premium protein source (~ 30% protein) that could be potentially modified into value-added products such as peptide antioxidants. In this study, relevant literatures detailing the extraction of cereal proteins, enzymatic hydrolysis of proteins, purification and characterization of hydrolysates, and evaluation of antioxidant profiles were extensively reviewed in Chapter 1. As preliminary experiments, sorghum kafirin protein was extracted from defatted sorghum white flour and hydrolyzed by 10 different types of enzymes from microbial, plant and animal sources. Hydrolysates prepared with Neutrase, Alcalase, and Papain displayed the most promising antioxidant activities as well as total protein recovery were primarily selected and investigated in depth described in Chapter 2, Chapter 3, and Chapter 4. The reaction conditions including substrate content, enzyme-to-substrate ratio, and hydrolysis time are critical parameters in producing peptides with desired activity and consistency, were therefore examined and optimized for each case of kafirin hydrolysates. The antioxidant capacity of the resulting hydrolysates was measured for antioxidant capacity through in vitro assays (DPPH, ABTS, ORAC, reducing power, and metal chelating) and then demonstrated in model systems (oil-in-water emulsion and ground meat). The fractions of hydrolysates possessing strongest activities were further fractionated by gel filtration and HPLC. Peaks representing the largest areas from HPLC were identified for major sequences by MALDI-TOF-MS. The experiment results indicated that all the three selected fractions of kafirin hydrolysates revealed excellent inhibition effects against oil and fat oxidations, which could be employed as tools to predict their performances in real food products. In addition, the structure studies showed that medium-sized hydrolysates of Neutrase (3 – 10 kDa) and Alcalase (5 – 10 kDa), and small-sized hydrolysates of Papain (1 – 3 kDa) exhibited relatively stronger activities. This study provided a workable processing method and critical reaction parameters for the production of peptide antioxidants from sorghum protein. The experiment results revealed that the sorghum peptide antioxidant could act through multiple mechanisms including free radical scavenging, metal ion chelation, hydrogen donating, and forming physical barriers to minimize the contact of oxidative agents to targets. These antioxidative peptides are a promising ingredient that can be potentially incorporated to food and feed products as alternatives to synthetic antioxidants or synergetic elements to nonpeptic antioxidants for protection of susceptible food ingredients. This study also made a positive impact to sorghum ethanol industry by guiding the conversion of sorghum protein-rich by-products into value-added antioxidant products as an additional revenue stream.

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 score0.001
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 integrity0.0000.001
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 head0.068
GPT teacher head0.277
Teacher spread0.209 · 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
Published2018
Admission routes1
Has abstractno

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