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Record W2104317753 · doi:10.5713/ajas.2013.13161

Production, Nutritional Quality and <italic>In vitro</italic> Methane Production from <italic>Andropogon gayanus</italic> Grass Harvested at Different Maturities and Preserved as Hay or Silage

2014· article· en· W2104317753 on OpenAlexaff
Gabriel O Ribeiro, A.M. Teixeira, Frederico Osório Velasco, Wilson Gonçalves Faria Júnior, Luiz Gustavo Ribeiro Pereira, Alex V. Chaves, L.C. Gonçalves, Tim A. McAllister

Bibliographic record

VenueAsian-Australasian Journal of Animal Sciences · 2014
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicRuminant Nutrition and Digestive Physiology
Canadian institutionsAgriculture and Agri-Food Canada
FundersFundação de Amparo à Pesquisa do Estado de Minas GeraisConselho Nacional de Desenvolvimento Científico e Tecnológico
KeywordsHayDry matterSilageForageAnimal scienceRumenBiologyChemistryAgronomyFermentationBiochemistry

Abstract

fetched live from OpenAlex

Andropogon gayanus is an important grass due to its high biomass production, drought tolerance and favorable growth on low fertility acidic soils. Currently, there is little research on the impact of growth stage on the nutritional quality or the degree of CH4 production that may arise from this forage during ruminal fermentation. The objectives of this study were to determine the effects of regrowth stage of A. gayanus on its chemical composition, in vitro production of gas and CH4, as well as in vitro dry matter (DM) digestibility when grown under tropical Brazilian conditions and conserved as hay or as silage. The nutritional value of A. gayanus grass declined with increasing maturity; however digestible DM yield linearly increased. After 112 d of regrowth, A. gayanus produced higher quality silage (higher lactate and lower pH and butyrate content) and higher DM yield. However, the low levels of crude protein at this time would make protein supplementation a necessity for proper rumen fermentation. No differences in CH4 kinetic parameters were found with advancing maturity or preservation method (hay or silage).

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)0.003
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Science and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.936
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.002
Science and technology studies0.0020.004
Scholarly communication0.0010.003
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.069
GPT teacher head0.302
Teacher spread0.233 · 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; both teacher heads agree on what is shown here.

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

Citations33
Published2014
Admission routes1
Has abstractyes

Explore more

Same venueAsian-Australasian Journal of Animal SciencesSame topicRuminant Nutrition and Digestive PhysiologyFrench-language works237,207