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Record W2011025254 · doi:10.4141/cjas07075

Chemical composition and ruminal degradability of grain pearl millet grown in southwestern Quebec

2008· article· en· W2011025254 on OpenAlexaffvenueabout
A. F. Mustafa, Philippe Séguin, Guy Bélair, Anand Kumar

Bibliographic record

VenueCanadian Journal of Animal Science · 2008
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicRuminant Nutrition and Digestive Physiology
Canadian institutionsAgriculture Environmental Renewal Canada (Canada)Agriculture and Agri-Food CanadaMcGill University
Fundersnot available
KeywordsHybridStarchNeutral Detergent FiberAgronomyDry matterBiologyChemical compositionLigninFatty acidAnimal scienceChemistryFood scienceBotanyBiochemistry

Abstract

fetched live from OpenAlex

The objectives of this study were to determine the chemical composition and ruminal nutrient degradabilities of grain of five hybrids of pearl millet grown in southwestern Quebec. Hybrids were selected because they were poor hosts of the widely prevalent root lesion nematode (Pratylenchus penetrans). Neutral detergent fiber and acid detergent lignin were similar for all hybrids. However, acid detergent fiber (ADF) was higher for CGPMH-1 than CGPMH-7 and CGPMH-38 and was higher for CGPMH-11 and CGPMH-20 than CGPMH-7. Starch content was higher for CGPMH-7 (668 g kg -1 DM) than the other hybrids (average 635 g kg -1 DM). Crude protein (CP) was lower for CGPMH-7 (141 g kg -1 DM) than the other hybrids (average 181 g kg -1 DM). Fatty acid content was higher for CGPMH -11 and CGPMH-20 than CGPMH-38. Linoleic acid was the most abundant fatty acid in all hybrids and was lower for CGPMH-38 than the other hybrids. Ruminal dry matter degradability was similar for all hybrids (average 69.5%). However, ruminal CP and starch degradabilities were higher for CGPMH-1 and CGPMH-20 than CGPMH-11 and CGPMH-38. It was concluded that grain concentrations of CP, ADF, and starch, and ruminal CP and starch degradabilities of pearl millet varied among hybrid. Key words: Chemical composition, Pearl millet, Ruminal degradability

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.907
Threshold uncertainty score0.975

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 studies0.0000.001
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 head0.023
GPT teacher head0.219
Teacher spread0.196 · 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 designObservational
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

Citations15
Published2008
Admission routes3
Has abstractyes

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