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Record W7006588376

Use of exogenous fibrolytic enzymes to improve the nutritive value of preserved forage for ruminants

2015· article· en· W7006588376 on OpenAlexfundaboutno aff

Bibliographic record

VenueArca (British Columbia Electronic Library Network) · 2015
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicRuminant Nutrition and Digestive Physiology
Canadian institutionsnot available
FundersAlberta Livestock and Meat Agency
KeywordsForageHayFodderAnimal productionCarbonatation
DOInot available

Abstract

fetched live from OpenAlex

This study was conducted to determine the effects of fibrolytic enzymes applied at baling, with or without ferulic acid esterase (FAE) producing bacterial inoculant, or to hay at feeding on digestibility and growth performance of lambs. Prior to starting the animal studies, two runs of replicated 24- and 48-h batch culture in vitro incubations were conducted using control alfalfa hay to select a suitable enzyme and dose. Eleven replicate bales of alfalfa-grass (93.8:6.2) hay (~500 kg) were produced with the application of one of three treatments: control (water), enzyme applied at baling (Eb; Econase RDE-L, AB Vista, Wiltshire, UK) and enzyme plus ferulic acid esterase producing bacterial additive applied at baling (EIb; 11 GFT, Pioneer HI-Bred Ltd., Chathan, ON, Canada). The mean internal bale temperature after 50 days of storage was greater (P<0.001) for Eb than control and EIb, as was the post-storage hemicellulose (P<0.05) concentration [mean bale temperature (°C), Eb = 26.8, EIb = 22.8, control = 17.8; hemicellulose concentration (g/kg dry matter), Eb = 127, control = 115, EIb = 114]. Two animal experiments using lambs were conducted after bales were stored for at least 90 days. The digestibility study was a replicated 4 × 4 Latin square design with 16 lambs and the animal performance study consisted of 32 lambs (8 per treatment) in a randomized complete block design. In both studies lambs received one of four treatments: control, Eb, EIb and enzymes added to control hay at feeding (Ef). In the digestibility study, total tract apparent organic matter (OM) (P=0.07) digestibility tended to be affected by treatment, with OM digestibilities greater for lambs fed Ef compared with lambs fed the other treatments, although differences were small (Ef vs. others; OM, 0.658 vs. 0.646). However, neutral detergent fiber (aNDF) and hemicellulose digestibilities were greatest (P<0.05) for lambs fed Eb, with no differences among the other treatments (aNDF, Eb = 0.480, control = 0.437, Ef = 0.430, EIb = 0.430; hemicellulose, Eb = 0.524, control = 0.460, Ef = 0.458, EIb = 0.446). In both studies there was no effect (P>0.05) of treatment on OM intakes. Average daily gain (ADG, g/d) of lambs in the performance study was greater (P=0.048) for EIb (233) than control (192) and Ef (202), and intermediate for Eb (206). Feed efficiency tended to be affected (P=0.07) by treatment; gain:feed for EIb was 18% greater than control and Eb and Ef were similar to the control. This study showed that applying enzymes to alfalfa hay at baling decreased aerobic stability, and increased fiber content and its digestibility, but ADG and gain:feed of lambs were not improved. Adding FAE producing bacterial inoculant with enzymes at baling improved aerobic stability of hay and ADG and gain:feed of lambs were increased relative to lambs fed control and enzymes applied at feeding. Applying enzymes at feeding increased apparent OM digestibilities but not fiber digestibilities, and had no effect on animal performance. We conclude that fibrolytic enzyme application with FAE producing bacterial inoculant at baling was the most promising method for enhancing performance of lambs fed baled alfalfa hay

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 score0.002

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 head0.025
GPT teacher head0.207
Teacher spread0.182 · 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

Citations0
Published2015
Admission routes2
Has abstractyes

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