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Record W4402541674 · doi:10.1093/jas/skae234.190

491 Processing and stomach pH influenced in vitro gastric protein solubilization kinetics in sunflower meal

2024· article· en· W4402541674 on OpenAlexaff
Felix M Njeri, Mai Anh Ton Nu, Hagen Schulze, Elijah G. Kiarie

Bibliographic record

VenueJournal of Animal Science · 2024
Typearticle
Languageen
FieldNursing
TopicFood composition and properties
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsSunflowerMealFood scienceStomachSolubilizationChemistryIn vitroKineticsBiochemistryAgronomyBiology

Abstract

fetched live from OpenAlex

Abstract The study aimed to evaluate the effect of processing and pH on gastric protein solubilization kinetics in sunflower meal (SFM) products using porcine digestion simulation model. The SFM samples were derived from diverse processing approaches: 1) dehulled-cold pressed (SFM_CP), 2) dehulled-solvent-extracted (SFM_SE), and 3) application of electrostatic separation technology on SFM_SE to generate high crude protein (CP) version (SFM_SEP). Soybean meal (SBM) was included for reference comparison (Table 1). Considering the complex factors influencing retention time, gastric pH, and pepsin secretion, the study employed multiple sampling times, and pH levels. A total of 500 mg CP equivalent of each sample (in triplicates) was mixed with 25 mL of 0.1 M phosphate buffer (pH 6.0) and 2 mL of pepsin (27 mg/mL). The pH was adjusted to either 1.5, 2.5, 3.5 or 4.5 using 1 M HCl and placed in incubator shaker (200 rpm) at 39°C. Samples were taken at 0, 30, 60, and 90 min, snap-frozen in liquid nitrogen, stored frozen, later thawed at 4°C, centrifuged (15,000 × g for 10 min) and supernatants analyzed for CP. The data were analyzed using Proc GLIMIXX in SAS while Gompertz equation was used to describe the gastric protein solubilization kinetics. The model included the fixed effects of protein source or processing, stomach pH and their interaction on the gastric CP solubility at 90 min and gastric protein solubility kinetics (A-maximum solubilized CP, Wo- initial CP solubility, Ku- solubilization rate, Ti- time to inflection). The analyzed CP SBM, SFM_CP, SFM_SE, and SFM_SEP, were 514.4, 524.4, 393.5, and 484.2 g/kg DM, respectively. Gastric CP solubility increased with lower pH and longer incubation time (P < 0.05), which corresponded well with the optimum pH of pepsin activity around 2. Compared with SFM, SBM had the least (P < 0.05) gastric CP solubility at pH 4.5 and 3.5, and the least predicted maximum gastric CP solubility (A) at pH 4.5, 3.5 and 2.5 (P < 0.05; Table 2). SFM_CP showed the greatest predicted initial gastric CP solubility at 0 h (Wo) and A (P < 0.05). Electrostatic fractionation of SFM_SE (SFM_SEP) enhanced gastric CP solubility at pH 3.5 and 2.5 and reduced the solubility time to inflection point (Ti; P < 0.05). In conclusion, data indicated that cold pressing SFM increased gastric CP solubility relative to solvent extraction. However, electrostatic fractionation of SFM_SE improved protein gastric solubility. While SBM remains a standard, incorporating the studied sunflower meals with their fast CP digestion kinetics in feed formulation could improve protein utilization in young animals with high stomach pH. In vivo studies, particularly on ileal amino acid digestibility, are crucial to validate these findings. Sunflower meal tables_FMN.pdf

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 score0.003
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
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 head0.018
GPT teacher head0.285
Teacher spread0.267 · 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

Citations2
Published2024
Admission routes1
Has abstractyes

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