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Record W2007201560 · doi:10.1071/an14059

Effect of sex and slaughter weight on meat and fat quality of the Krškopolje pig reared in an enriched environment

2014· article· en· W2007201560 on OpenAlexaff
Marjeta ŽEMVA, T.M. Ngapo, Špela Pezdevšek Malovrh, Alenka Levart, Milena Kovač

Bibliographic record

VenueAnimal Production Science · 2014
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicMeat and Animal Product Quality
Canadian institutionsAgriculture and Agri-Food Canada
Fundersnot available
KeywordsIntramuscular fatLoinBreedAnimal scienceBiologyComposition (language)Carcass weightFatty acidEnvironmental management systemFood scienceBody weightAgronomyIrrigation

Abstract

fetched live from OpenAlex

Improvements in meat quality are sought through sources of variation along the meat chain, including breed and production system. Hence, the aim of this study was to determine slaughter weight and sex effects on the meat quality of the indigenous Krškopolje pig breed reared in a feed-enriched indoor environment for the growing-finishing periods. Raised in this enriched environment, the intramuscular fat (IMF) content of the loin was 1.5–2.5% higher than previously reported for other production systems. Slaughter weight (119–132 kg or >135–170 kg) influences on meat colour and IMF composition were observed. Animals from the light group had lighter coloured meat with lower Japanese colour scores as well as higher saturated fatty acid (SFA) and lower monounsaturated fatty acid (MUFA) proportions in the IMF. A lower proportion of MUFA was also observed in the IMF from gilts than barrows. Furthermore, a higher proportion of SFA was found in the IMF from the gilts. However, the lower IMF content in the gilts negates any apparent compositional advantages between the sexes. The IMF content and composition of the Krškopolje pig reared in an enriched environment suggests good commercial potential of this breed.

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)0.003
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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.515
Threshold uncertainty score0.253

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
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 head0.034
GPT teacher head0.281
Teacher spread0.247 · 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 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

Citations8
Published2014
Admission routes1
Has abstractyes

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