MétaCan
Menu
Back to cohort
Record W4402541217 · doi:10.1093/jas/skae234.878

PSXII-28 Physiochemical and nutritional characteristics of the newly developed value-added blended fat stimulated feed product in comparison with commercial protein and energy feeds

2024· article· en· W4402541217 on OpenAlexaffabout
Umair Ihsan, Luciana L. Prates, H.A. Lardner, Rex N Newkirk, María E. Rodríguez Espinosa, Peiqiang Yu

Bibliographic record

VenueJournal of Animal Science · 2024
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicFood and Agricultural Sciences
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsFood scienceProduct (mathematics)ChemistryValue (mathematics)Pulp and paper industryMathematicsEngineering

Abstract

fetched live from OpenAlex

Abstract The objectives of this study were to determine physiochemical and nutritional characteristics of the newly developed value-added blended fat stimulated feed product (BFSFP) in comparison with commercial protein and energy feeds. The new value-added BFSFB with three-batch samples (BFSFP1, BFSFP2, BFSFP3) were developed. Barley grain (n = 3) and canola meal samples (n = 3) were obtained from Canadian Feed Research Center. Chemical composition and nutrient profiles were determined using standard feed analysis methods (e.g., AOAC, NRC-energy). The treatment design was a one-way structure. The experimental design was a CRD with feed treatments as a fixed effect. The data were analyzed using the Mixed model procedure of SAS. Tukey’s method was used for multi-treatment comparison. The results showed that compared with commercially available energy-rich and protein-rich feeds, the BFSFP had greater (P < 0.05) ether extract (EE) than both canola meal and barley grain [4.8 vs. 1.0, 1.6 % dry matter (DM), respectively]. It had decreased ash content than canola meal but greater than barley grain (P < 0.05). For protein chemical profiles, the BFSFP had less (P < 0.05) CP (31.0 vs. 41.6, 12.5%DM), SCP (4.9 vs. 9.1, 3.4% DM), and NPN (11.0 vs. 18.2, 9.2% CP) than canola meal but greater than barley grain. The BFSFP had greatest NDICP (2.6 vs. 0.9, 0.4%CP) and ADICP (0.14 vs. 0.30, 0.06%DM) than both canola meal and barley grain. For carbohydrate chemical profiles, the BFSFP had greater (P < 0.05) carbohydrate (58.1 vs. 50.4, 83.7%DM) and starch (4.5 vs. 1.3, 55.9%DM) than canola meal but less than barley grain. The BFSFP had greater (P < 0.05) NDF (42.9 vs. 28.6, 18.9%DM) and hemicellulose (27.7 vs. 10.5, 12.9%DM) than both canola meal and barley grain. The BFSFP had had less (P < 0.05) ADF (12.7 vs. 17.5, 5.7%DM) and ADL (3.0 vs. 8.0, 0.8%DM) than canola meal but greater barley grain. As to energy profle, the BFSFP had no significant difference in NE for lactation when compared with barley grain and canola meal (1.80 vs 1.93 vs. 1.69 Mcal/kg DM, P > 0.05). The BFSFP had similar in NE for growth (1.29 Mcal/kg DM) when compared with canola meal (1.29 vs. 1.20 Mcal/kg DM, P > 0.05) but less than barley (1.29 vs 1.42 Mcal/kg DM, P < 0.05). In conclusion, the newly developed blended fat stimulated feed product differed in physiochemical and nutritional characteristics in comparison with commercially available energy-rich and protein-rich feeds.

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 score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.020
GPT teacher head0.238
Teacher spread0.219 · 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
Published2024
Admission routes2
Has abstractyes

Explore more

Same venueJournal of Animal ScienceSame topicFood and Agricultural SciencesFrench-language works237,207