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Record W3121193229 · doi:10.4236/ojas.2021.111008

Effects of Guar (<i>Cyamopsis tetragonoloba</i>) Residues on the Performance and Nutrients Digestibility in Finishing Awassi Lambs

2021· article· en· W3121193229 on OpenAlexfundno aff
Jamal Abo Omar, Ahmed Zaazaa, Maen Sheqwarah, Bassam Abu Shanab, Wael Qaisi, Jehad Abdallah

Bibliographic record

VenueOpen Journal of Animal Sciences · 2021
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPolysaccharides Composition and Applications
Canadian institutionsnot available
FundersGovernment of CanadaAn-Najah National University
KeywordsCyamopsisStrawGuarAnimal scienceDry matterAwassiNutrientChemistryNeutral Detergent FiberDigestion (alchemy)BiologyAgronomyFood science

Abstract

fetched live from OpenAlex

The nutritive quality of guar (Cyamopsis tetragonoloba) residues (GR) was investigated and the effects of partial replacement of wheat straw by GR on nutrients intake, digestibility, and growth performance. Twenty four male lambs, with average body weight (BW) of 40.3 ± 2.5 kg were divided into three groups. Lambs were fed individually for 104 days with concentrate mixture (18% crude protein) and wheat straw as a total mixed ration. Wheat straw was replaced with 0, 100 and 145 g/kg dry matter guar residues. All rations were isonitrogenous and isocaloric. The fattening trial lasted 104 days. At the end of week 10 of the trail, a digestion trial was performed using six lambs from each group. The composition of nutrients in the GR was 87%, 8.5%, 56.4% and 40.1% for DM, CP, NDF and ADF, respectively. DM and crude protein (CP) intake were not affected by the inclusion of GR. However, neutral detergent fibre (NDF) and acid detergent fibre (ADF) intake were lower in lambs fed GR compared to control lambs. At the end of the experiment, lambs fed 100 and 145 g GR/kg DM diets gained more weight (P version (CR). Results from this work suggested that GR had advantages compared to regular roughage (wheat straw) in regard to parameters investigated as well as the significant reduction in fattening diets cost.

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)0.002
metaresearch head score (Gemma)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.866
Threshold uncertainty score0.528

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.052
GPT teacher head0.291
Teacher spread0.239 · 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

Citations4
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueOpen Journal of Animal SciencesSame topicPolysaccharides Composition and ApplicationsFrench-language works237,207