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Record W2084890835 · doi:10.3168/jds.2007-0810

Evaluation of the Response of Ruminal Fermentation and Activities of Nonstarch Polysaccharide-Degrading Enzymes to Particle Length of Corn Silage in Dairy Cows

2008· article· en· W2084890835 on OpenAlexaff
Qendrim Zebeli, M. Tafaj, B. Junck, V. Ölschläger, Burim N. Ametaj, W. Drochner

Bibliographic record

VenueJournal of Dairy Science · 2008
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicRuminant Nutrition and Digestive Physiology
Canadian institutionsUniversity of Alberta
FundersFreie Universität BerlinUniversität Hohenheim
KeywordsSilageRumenDry matterNeutral Detergent FiberTotal mixed rationFood scienceChemistryFermentationDairy cattleLactoseHayAnimal scienceLactationBiologyIce calving

Abstract

fetched live from OpenAlex

The main objective of this study was to evaluate effects of particle length (PL) of corn silage (CS) on distribution of dietary particle fractions, contents of physically effective neutral detergent fiber (peNDF), cows' intake patterns and sorting activity, fermentation pro-file, and activities of nonstarch polysaccharide-degrading enzymes as well as degradation in the rumen and total tract in lactating dairy cows. Four ruminally cannulated Holstein cows, weighing 624 +/- 50 kg and 60 +/- 8 d in milk, were fed ad libitum 3 total mixed rations [about 16% crude protein, 34% neutral detergent fiber (NDF), and 7 MJ of net energy of lactation/kg of dry matter (DM)] containing on DM basis 50% concentrate, 10% grass hay, and 40% CS with 3 different theoretical PL at harvesting (14, 8.1, and 5.5 mm for long, medium, and short, respectively). Results showed that the amount of DM retained on sieves with 19- and 8-mm screens of Penn State Particle Separator decreased linearly with decreasing PL of CS. The latter was reflected in a significant decrease in the content of dietary peNDF including both the DM (peNDF(>8)) and the NDF (peNDF(>8-NDF)) retained on 19- and 8-mm screens. In contrast, the fraction of particles retained between the 1.18- and 8-mm screens was increased, such that no differences among the diets were observed regarding the content of peNDF that includes DM of particles >1.18 mm (peNDF(>1.18)). The intake of particles retained between the 1.18- and 8-mm screens increased linearly, whereas the intake of peNDF(>1.18) increased quadratically with decreasing PL of CS. Sorting consumption was reduced by feeding the short CS, which was reflected in a reduced proportion of propionate and increased acetate-to-propionate ratio and butyrate pro-portion in the rumen. In contrast, no effects of PL of CS were observed on the concentration of total volatile fatty acids and pH in the rumen. In general, decreasing the PL of CS significantly increased the activities of nonstarch polysaccharide-degrading enzymes. However, greater ruminal and total tract degradation of fiber and nonfiber carbohydrates were observed only by medium CS. Results of the present study suggest that in addition to fractions of long particles (i.e., >8 mm), the particle fraction retained between 1.18- and 8-mm should also be considered to better predict rumen conditions and digestion. In conclusion, a moderate reduction of PL of CS has beneficial effects on nutrient digestion, and may maximize feed efficiency and energy supply in high-yielding dairy cows.

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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.061
GPT teacher head0.301
Teacher spread0.240 · 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

Citations44
Published2008
Admission routes1
Has abstractyes

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