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Record W7056575272

Evaluation of the chemical composition and energy values of expeller/ cold-pressed canola fed to growing pigs

2023· dissertation· en· W7056575272 on OpenAlexfundno aff

Bibliographic record

VenueMspace (University of Manitoba) · 2023
Typedissertation
Languageen
FieldPhysics and Astronomy
TopicMagnetic confinement fusion research
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsCanolaChemical compositionComposition (language)NutrientDry matterNitrogenResidual oil
DOInot available

Abstract

fetched live from OpenAlex

There is rising importance in the use of expeller/ cold-pressing method to produce canola oil from its seed. This method leads to the presence of residual oil in the expeller/ cold-pressed canola (ECPC) making it a potential source of protein and energy for pigs. Although in this method canola seed is not heat and moisture treated as it is in the conventional pre-press solvent extraction, the differences in processing steps contribute to the variation in chemical composition and energy value of ECPC. Thus, determination of energy content of ECPC for swine and establishing correlation with its chemical components was the goal of this research. A detailed chemical composition of ECPC samples from five different processing plants was conducted. Results confirmed a variation in nutrient composition of ECPC among processing plants. The crude protein (CP), ether extract (EE), neutral detergent fibre (NDF) and glucosinolates (GLS) content of expeller/ cold-pressed canola ranged between 351.4 – 419.4g/kg, 84.9 – 177.2g/kg, 230.7 – 300.1g/kg and 5.0 – 9.7 μmol of total GLS/g, respectively (DM basis). Two metabolic studies with growing pigs were conducted to determine the energy values of ECPC and to explore how they are correlated with the nutrient composition. The first study was conducted to determine digestible energy (DE) and metabolizable energy (ME) of ECPC for growing pigs. Result showed the presence of greater residual oil in ECPC and its influence on DE and ME content. The goal of the second experiment was to determine the net energy (NE) content of different ECPC samples for growing pigs and compare the determined NE values using indirect calorimetry (IC) with predicted NE using published prediction equations. The NE of ECPC A, B, C, D and E determined using IC were 2,478, 3,058, 2,586, 2789, 3218 kcal/kg (DM basis), respectively, and these values were 2.3, 15.3, 10.2, 9.5 and 16.8% higher, respectively, compared with those estimated using prediction equations. However, significant differences were observed between determined and predicted values for only ECPC B, C, D and E. In general, ECPC contained an average of 3,531, 3,172, 2,826 and 2,507 kcal/kg, DE, ME, NE and predicted NE, respectively on DM basis. In conclusion, ECPC is a valuable source of energy in pig diets. The difference in processing technology within cold pressing method is a major source of variation in the chemical composition and energy values of ECPC. The residual oil in ECPC is an important contributor to its energy concentration.

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 score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.019
GPT teacher head0.244
Teacher spread0.225 · 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

Citations0
Published2023
Admission routes1
Has abstractyes

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