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Record W2062163591 · doi:10.1021/jf400028n

Chemical Profile, Energy Values, and Protein Molecular Structure Characteristics of Biofuel/Bio-oil Co-products (Carinata Meal) in Comparison with Canola Meal

2013· article· en· W2062163591 on OpenAlexaff
Hangshu Xin, Peiqiang Yu

Bibliographic record

VenueJournal of Agricultural and Food Chemistry · 2013
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicProtein Hydrolysis and Bioactive Peptides
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsCanolaMealFood scienceChemistryCarbohydrateBiochemistry

Abstract

fetched live from OpenAlex

To our knowledge, little information exists on nutritive values and molecular structural characteristics associated with protein biopolymers of carinata meal from biofuel and bio-oil processing. The objectives of this study were to investigate (1) chemical compositions; (2) protein and carbohydrate subfractions partitioned by the Cornell Net Carbohydrate and Protein System (CNCPS); (3) truly digestible nutrients and energy values; (4) protein conformation spectral characteristics using the ATR-FT/IR technique; and (5) the correlation between protein intrinsic structural features and nutrient profiles of carinata meal in comparison with conventional canola meal as references. The results showed that carinata meal was higher (p < 0.05) in soluble crude protein (SCP, 55.6% CP) and nonprotein nitrogen (NPN, 38.5% CP) and lower in acid detergent insoluble crude protein (ADICP, 1.3% CP) compared to canola meal. Although no differences were found in CP and carbohydrate (CHO) contents, CNCPS protein and carbohydrate subfractions were different (p < 0.05) between carinata meal and canola meal. Carinata meal has similar contents of total digestible nutrient (TDN) and predicted energy values to canoal meal (p > 0.05). As for protein spectral features, much greater IR absorbance in amide I height and area as well as α-helix and β-sheet height for carinata meal by 20-31% (p < 0.05) was found compared with canola meal; however, results from agglomerative hierarchical cluster analysis (CLA) and principal component analysis (PCA) indicated these two meals could not be distinguished completely within the protein spectrum (ca. 1728-1478 cm(-1)). Additionally, close correlations were observed between protein structural parameters and protein nutrient profiles and subfractions. All the comparisons between carinata meal and canola meal in our study indicated that carinata meal could be used as a potential high-protein supplement source for ruminants. Further study is needed on more information associated with nutrient degradability, utilization, and availability of carinata meal to ruminants for its better and effective application in animal industry.

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 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 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 score0.017
Threshold uncertainty score0.584

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.005
GPT teacher head0.192
Teacher spread0.187 · 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.

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

Citations49
Published2013
Admission routes1
Has abstractyes

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