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Record W2168967887 · doi:10.3168/jds.2009-2220

Technical note: The use of a telemetric system to continuously monitor ruminal temperature and to predict ruminal pH in cattle

2009· article· en· W2168967887 on OpenAlexafffund
Ousama AlZahal, M.A. Steele, Eduardo V. Valdes, B.W. McBride

Bibliographic record

VenueJournal of Dairy Science · 2009
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicEffects of Environmental Stressors on Livestock
Canadian institutionsUniversity of Guelph
FundersNatural Sciences and Engineering Research Council of CanadaDairy Farmers of Canada
KeywordsNeutral Detergent FiberAnimal scienceDry matterHayBolus (digestion)RumenChemistryAlfalfa hayCarbohydrateDairy cattleBiologyBiochemistryFermentationAnatomy

Abstract

fetched live from OpenAlex

The objective of this study was to compare a telemetric monitoring system to an existing in situ methodology (conventional system) of monitoring ruminal temperature and to validate its use to detect changes in ruminal pH (RpH). Four nonlactating, ruminally cannulated Holstein dairy cows (760 +/- 30 kg of body weight, mean +/- standard deviation) housed in a tie-stall facility were used in the study. The experiment was conducted during the month of May and the recorded ambient temperature was 8.0 +/- 2.0 degrees C (mean +/- SD). The cows were fed a diet consisting of chopped mixed hay (MH; 11.3% crude protein, 59.7% neutral detergent fiber, 17.3% nonfiber carbohydrate, 3.1% ether extract, and 11.3% ash; dry matter basis) during wk 1 and were gradually switched to a high-grain (HG) diet (11.6% crude protein, 30.2% neutral detergent fiber, 50.7% nonfiber carbohydrate, 3.0% ether extract, and 6.0% ash; dry matter basis) during wk 2. A conventional system that utilized an indwelling electrode was used to monitor RpH and ruminal temperature (RT(C)) during d 6 and 7 of each week. The indwelling electrode was attached to a telemetric bolus and ruminal temperature (RT(T)) was logged into a personal computer. The daily mean, minimum, and maximum RpH and duration (min/d) RpH <6.2 were 6.39 +/- 0.04, 6.10 +/- 0.05, 6.66 +/- 0.03, and 107 +/- 50 during MH feeding (wk 1) and 5.84 +/- 0.03, 5.35 +/- 0.05, 6.35 +/- 0.03, and 1,257 +/- 40 during HG feeding (wk 2), respectively, and were different across diets (week effect). Ruminal pH did not decrease below 5.6, 5.8, and 6.0 during MH feeding; mean duration of RpH <5.6, <5.8, and <6.0 during HG feeding was 279 +/- 149, 611 +/- 139, and 894 +/- 101, respectively. Mean daily RT(C) increased from 37.5 degrees C +/- 0.1 in wk 1 to 38.6 degrees C +/- 0.1 in wk 2; there was also an increase from wk 1 to wk 2 in minimum and maximum daily RT(C) and durations (min/d) of RT(C) >38.0, >38.2, >38.4, and >38.6 degrees C. These increases were not detectable with the telemetric system. Ruminal temperature obtained by the conventional system was 0.68 degrees C +/- 0.005 lower than RT(T) during MH feeding (wk 1), whereas RT(C) was 0.04 degrees C +/- 0.004 higher than RT(T) during HG feeding (wk 2). Daily minimum RpH was associated with maximum daily RT(C) and RT(T) during MH and HG feeding (R(2) = 0.88 and 0.43, respectively). There was a high association between low RpH and high ruminal temperature, with the highest associations being between duration (min/d) of RpH <6.0 and duration of RT(C) >39.0 degrees C (R(2) = 0.68) and RT(T) >39.2 degrees C (R(2) = 0.72). Unlike the telemetric system, the conventional system requires cow cannulation; therefore, the current study provided a noninvasive alternative for measuring ruminal temperature and the prediction of RpH. Additional studies are needed to develop an algorithm that accounts for diet type, seasonal variation in temperature, and core body temperature to predict subacute ruminal acidosis effectively on farm.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.951
Threshold uncertainty score0.162

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.012
GPT teacher head0.234
Teacher spread0.222 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations42
Published2009
Admission routes2
Has abstractyes

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