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Record W4232679753 · doi:10.22175/rmc2017.097

The Effects of Ractopamine and Hormonal Growth Promotants on Growth and Meat Quality of Crossbred Angus Steers

2017· article· en· W4232679753 on OpenAlexaff
Patience Coleman, Bimol C. Roy, Heather L. Bruce

Bibliographic record

VenueMeat and Muscle Biology · 2017
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPharmacological Effects and Assays
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsRactopamineTendernessCrossbreedAnimal scienceSplit plotMeat tendernessImplantEstradiol benzoateHormoneBiologyMedicineEndocrinologySurgeryOvariectomized ratRandomized block design

Abstract

fetched live from OpenAlex

ObjectivesMeat tenderness is an important quality parameter that influences consumer preference. The cattle industry has over the years seen the emergence of feed additives and hormonal growth promotants in the form of β-adrenergic agonists (β-AA) and steroids, respectively. The objective of this study was to analyze the effect of hormonal growth implants and ractopamine on slaughter weight and meat quality parameters of steers selected for high (inefficient) and low (efficient) residual feed intake (RFI) performance.Materials and MethodsForty-eight crossbred Angus steers identified from individual GrowSafe data as high (n = 21) or low (n = 27) RFI cattle were randomly assigned to pens according to treatment (n = 12). Treatments included control (no ractopamine hydrochloride (RAC)/no steroids), RAC and steroids, steroids only, and RAC only in a 2x2x2 factorial design. Steers on steroid treatment received a first implant (200mg progesterone, 20mg estradiol benzoate and 29mg tylosin tartrate) at about 350 d of age and 450kg live weight and a terminal implant (120 mg trenbolone acetate and 24mg estradiol) at about 100 d before slaughter. RAC was fed to the appropriate group 28 d before slaughter at a rate of 200mg head–1d–1. Cattle were slaughtered at about 16 mo of age over 6 consecutive weeks by weight and back fat, with 1 animal per treatment represented in each kill for a total of 8 animals slaughtered per week. Hot carcass weights (HCW) were recorded. Gluteus medius (GM) muscles were obtained from the carcasses 3 d post mortem and halved for ageing, with one half aged a further 12 d under vacuum. After ageing at 4°C, muscle halves were assessed for pH, color, drip loss and Warner-Bratzler shear force (WBSF). For all data the experimental unit was the steer as the effect of ageing was not considered. Data was analyzed using the General Linear Model procedure in SAS (SAS Inst. Inc., Cary, NC) with RFI, steroids, RAC and their interactions as fixed factors with slaughter day used as a covariate. Mean differences were determined using Least Square Means and Tukey’s multiple comparisons.ResultsResults revealed no effect (P > 0.05) of RFI and RAC on slaughter weight (SW) but steroids increased (P < 0.0001) SW of steers. An interaction effect (P = 0.0381) was seen between RFI, steroids and RAC on HCW, where high RFI steers that were implanted with steroids and fed RAC had a higher HCW at 389.64 ± 8.70 kg than low RFI steers that were neither implanted nor fed RAC (325.68 ± 7.05kg). An interaction between RFI, steroids and RAC (P = 0.045) for drip loss was observed on muscles aged for 12 d, where high RFI steers that were implanted but not fed RAC had a higher drip loss (1.93 ± 0.23 g) than low RFI steers that were not implanted but feed RAC (0.63 ± 0.19g). Muscles from implanted steers had a higher mean WBSF value than muscles from non-implanted steers on d 12 post-mortem (P = 0.039), while high RFI steers that received RAC had the lowest mean WBSF (P = 0.015).ConclusionResults indicated that steroids compromised the development of tenderness during post mortem ageing in the GM. This suggests that the benefit of steroid use on slaughter and hot carcass weights will compromise tenderness of this muscle. Additional post mortem ageing beyond 12 d may be required. Conversely, the use of the β-AA RAC showed potential for decreasing cooked GM toughness in high RFI steers regardless of the ageing period.

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)0.000
metaresearch head score (Gemma)0.001
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 score0.872
Threshold uncertainty score0.299

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.288
Teacher spread0.263 · 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".

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Citations0
Published2017
Admission routes1
Has abstractyes

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