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Record W3031287138 · doi:10.3168/jds.2019-17705

Effect of diet-induced negative energy balance on the feeding behavior of dairy cows

2020· article· en· W3031287138 on OpenAlexaff
Siobhan Moore, T.J. DeVries

Bibliographic record

VenueJournal of Dairy Science · 2020
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicRuminant Nutrition and Digestive Physiology
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsNEFADry matterStrawAnimal scienceLactationChemistryForageEnergy balanceBiologyFatty acidAgronomyBiochemistry

Abstract

fetched live from OpenAlex

The objective of this study was to determine how feeding behavior of dairy cows is altered in response to diet-induced negative energy balance, and if this response varies depending on dietary particle size distribution. Multiparous Holstein cows (n = 30; days in milk=59 ± 5; parity=2.8 ± 0.19), producing 44.6 ± 1.2 kg/d of milk, were fed (on a dry matter basis) a lactating diet [net energy of lactation (NE L ) = 1.66 Mcal/kg; 68% forage, including 1.8% wheat straw] during a 2-wk baseline period. To induce negative energy balance, cows were then exposed for 3 wk to 1 of 2 diets formulated for a 20% reduction in energy available for milk (NE L = 1.58 Mcal/kg; 73% forage, including 17.2% wheat straw). These diets were identical, only varying in straw chop length: (1) long straw diet (LS): straw chopped with a 10.2-cm screen, or (2) short straw diet (SS): straw chopped with a 2.54-cm screen. Cows consumed 25.6 ± 0.26 kg/d during the baseline period. Dry matter intake decreased on the experimental diets; dry matter intake was greater for the SS diet as compared with the LS diet (23.1 vs. 22.5 kg/d; standard error=0.47). During the baseline period, cow serum nonesterified fatty acids (NEFA) and blood β-hydroxybutyrate averaged 0.27 ± 0.02 and 0.71 ± 0.05 mmol/L, respectively. During the experimental period, NEFA and β-hydroxybutyrate averaged 0.34 and 1.04 mmol/L, respectively, with a peak of NEFA (0.63 ± 0.06 mmol/L) occurring 4 d after dietary change. During baseline, cows produced 42.3 ± 0.33 kg/d of milk; milk yield was decreased for both SS cows and LS cows during the experimental period (SS = 39.0, LS=37.8 kg/d; standard error=0.67). On the experimental diets, cows spent more time eating (266.8 vs. 221.8 min/d), had longer meal lengths (46.9 vs. 37.5 min/meal), and consumed fewer meals (7.1 vs. 7.7 meals/d) compared with the baseline period. Within the experimental period, LS cows spent more time eating per day than SS cows (LS = 281.3, SS=252.2 min/d). During the baseline period cows sorted against long particles (>19 mm), did not sort medium particles (8 to 19 mm), and sorted for short (4 to 8 mm) and fine (<4 mm) particles. Cows did not change sorting of long particles on the SS diet, but increased sorting against these on the LS diet. On the SS diet cows did not change their sorting of short and fine particles. On the LS diet cows increased sorting for short and fine particles. In the baseline period, no association was detected between feed sorting and serum NEFA concentration. During the experimental period, greater NEFA concentration was associated with greater sorting in favor of short particles for both the LS and SS diets. Furthermore, greater NEFA concentration was associated with greater sorting against the longest particles for both the LS and SS diets. No associations of blood and meal variables were detected during the experimental period. Overall, cows altered their feed sorting behavior in response to experiencing a diet-induced period of negative energy balance and the severity of negative energy balance was associated with the extent of that change in feed sorting.

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 score0.004

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 integrity0.0000.001
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 head0.033
GPT teacher head0.266
Teacher spread0.234 · 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

Citations26
Published2020
Admission routes1
Has abstractyes

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