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Record W2087992693 · doi:10.3168/jds.2006-818

Altering Physically Effective Fiber Intake Through Forage Proportion and Particle Length: Digestion and Milk Production

2007· article· en· W2087992693 on OpenAlexafffund
Wenzhu Yang, K. A. Beauchemin

Bibliographic record

VenueJournal of Dairy Science · 2007
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicRuminant Nutrition and Digestive Physiology
Canadian institutionsAgriculture and Agri-Food Canada
FundersAgriculture and Agri-Food CanadaDairy Farmers of Canada
KeywordsDry matterLatin squareNeutral Detergent FiberDigestion (alchemy)ForageAnimal scienceChemistrySilageTotal mixed rationNutrientFood scienceFiberBiologyAgronomyRumenLactationFermentationChromatographyIce calving

Abstract

fetched live from OpenAlex

Intake of physically effective neutral detergent fiber (peNDF) of dairy cows was altered by adjusting the proportion of forage in the diet and forage particle length, and effects on nutrient intake, site and extent of digestion, microbial N synthesis, and milk production were measured. The experiment was designed as a triplicated 4 x 4 Latin square using 12 lactating dairy cows, with 4 that were ruminally and duodenally cannulated, 4 that were ruminally cannulated, and 4 that were intact. Thus, the site and extent of digestion, and microbial N synthesis were measured in a single 4 x 4 Latin square. Treatments were arranged in a 2 x 2 factorial design; 2 forage particle lengths (FPL) of alfalfa silage (short and long) were combined with low (35:65) and high (60:40) forage:concentrate (F:C) ratios (dry matter basis). Dietary peNDF content was determined from the sum of the proportion (dry matter basis) of dietary dry matter retained either on the 2 screens (8- and 19-mm) or on the 3 screens (1.18-, 8-, and 19-mm) of the Penn State Particle Separator multiplied by the neutral detergent fiber content of the diet. An increased F:C ratio reduced intakes of dry matter and starch by 9 and 46%, respectively, but increased intake of fiber from forage sources by 53%. Digestibility of dry matter in the total tract was not affected, whereas total digestion of fiber and N was improved by increasing the F:C ratio. Improved total fiber digestion resulted from higher ruminal digestion, which was partially due to a shift in starch digestion from the rumen to the intestine with the increased F:C ratio. Actual milk yield was decreased but production of 4% fat-corrected milk was similar between the low and high F:C diets because of increased milk fat content. Increased FPL increased intake of peNDF, especially when the high F:C diet was fed. However, nutrient intakes, N metabolism in the digestive tract, and milk production were not affected. Digestibility of neutral detergent fiber in the total tract was increased because of improved fiber digestion in the rumen with increased FPL. These results indicate that feeding dairy cows a low F:C diet is beneficial in terms of increasing feed intake, microbial N synthesis, and milk production. However, low F:C diets do not maximize feed digestion and production efficiency because of the effects of subacute ruminal acidosis. Increased FPL improves fiber utilization with minimal effects on the digestion of other nutrients and milk production. Increasing dietary peNDF, through an increased proportion of forage or increased FPL, improves fiber digestion because of improved rumen function.

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)0.001
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 score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
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 head0.019
GPT teacher head0.261
Teacher spread0.242 · 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

Citations60
Published2007
Admission routes2
Has abstractyes

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