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Record W2607637615 · doi:10.2527/asasann.2017.589

589 Heat-induced changes in protein molecular structure associated with rumen degradation of oat grains in dairy cows detecting by vibrational molecular spectroscopy

2017· article· en· W2607637615 on OpenAlexaff
Luciana L. Prates, Peiqiang Yu

Bibliographic record

VenueJournal of Animal Science · 2017
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicRuminant Nutrition and Digestive Physiology
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsRumenDegradation (telecommunications)Dairy cattleProtein degradationSpectroscopyChemistryFood scienceAnimal scienceAgronomyBiologyBiochemistryFermentation

Abstract

fetched live from OpenAlex

Heat processing may simultaneously affect protein rumen degradation and protein intestinal digestion by altering molecular protein structure in seeds. Attenuated Total Reflectance Fourier transform vibrational molecular spectroscopy (ATR-Ft/VMS) is a novel technique that reveals molecular structural features, increasing the understanding of feed structures at cellular level and new level of analytical information. The objective of this study was to reveal the change from heat-related feed processing in the molecular protein structure of oat grains: CDC Nasser and CDC Seabiscuit. Oat grains were sampled from harvested plots (n = 2) grown in 2014 and 2015. Each oat variety was equally divided into 4 portions and performed in one treatment: raw, dry-heating, autoclave heating or microwave irradiation. Samples were rolled (gap size 1.78 mm) for in situ incubation and ground through 0.5 mm screen for molecular spectral analysis. Amide I (1720 – 1577 cm-1) and amide II (1577 – 1486 cm-1) area intensities and peak heights, and secondary protein structures α-helices and β-sheets heights were measured in the region at ca. 1720 – 1486 cm-1were quantified using OMNIC 7.3 software. Rumen degradation was performed using dairy cows equipped with rumen cannulae. Spectral data were analyzed using univariate analysis of recording peak parameters. Spearman correlation was performed after normality test. Multiple regressions were performed using PROC REG of SAS 9.4. Autoclave heating increased (P < 0.001) Amide I:Amide II area ratio and heat processing methods increased (P < 0.001) Amide I:Amide II height ration comparing to raw. The α-helix and β-sheet heights were lower for autoclave heating comparing to dry heating; however these treatments were statistically similar with raw. Rate of degradation of crude protein (KdCP) was positive correlated with α-helix (r = 0.54;P= 0.028) and β-sheet (r = 0.59;P= 0.015); effective degradability (EDCP) was strongly positive correlated with Amide I (r = 0.75;P<0.001) and Amide II (r = 0.67; P < 0.001) areas, β-helix (r = 0.75; P < 0.001) and β-sheet (r = 0.86;P<0.001). Multiple regressions were obtained: KdCP = -22.66 + 205.68 × β-sheet (R2= 0.34;P= 0.015); EDCP = -52.18 + 568.89 × β-sheet (R2= 0.69;P<0.001). It can be concluded that heat-related feed processing affects molecular protein structures, the difference can be detected by ATR-Ft/VMS and protein molecular structure profile could be used as a predictor to estimate degradation kinetics of CP.

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 score0.004
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
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 head0.019
GPT teacher head0.255
Teacher spread0.237 · 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".

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Citations0
Published2017
Admission routes1
Has abstractyes

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