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Record W4413251214 · doi:10.1016/j.psj.2025.105634

Meta-analysis of poultry organ weights and their relationship with meat yield

2025· article· en· W4413251214 on OpenAlexafffund
Natalee T Richardson, Ricarda E Jahnel, Bayode O. Makanjuola, Xue Bai, Shai Barbut, J.L. Ellis, Christine F. Baes, Emily M. Leishman

Bibliographic record

VenuePoultry Science · 2025
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Nutrition and Physiology
Canadian institutionsUniversity of Guelph
FundersNatural Sciences and Engineering Research Council of CanadaOntario Ministry of Agriculture, Food and Rural Affairs
KeywordsYield (engineering)Food sciencePoultry meatBiologyAnimal scienceMaterials science

Abstract

fetched live from OpenAlex

Late-stage mortality is a significant challenge for the poultry industry, leading to substantial economic losses, concerns about animal welfare, and operational sustainability. Heart-related conditions, including ascites syndrome, pulmonary hypertension syndrome, hypertrophic cardiomyopathy, and sudden death syndrome, contribute significantly to this issue. The increasing prevalence of these conditions is potentially linked to intense selection pressure aimed at maximizing meat yield, particularly breast meat. However, the precise relationship between meat yield, heart size and cardiovascular health remains unclear. To address this, a systematic literature review and meta-analysis were conducted to explore the relationship between breast meat yield and organ size (heart, lungs, liver), in which 91 publications meeting specific inclusion criteria were identified. Data extracted included variables such as live weight, portion yields (breast, leg, wing), organ weights (heart, lungs, liver), and the prevalence of heart-related conditions (pulmonary hypertension syndrome, ascites syndrome). A backward selection modeling approach was used to develop linear mixed models, treating the study as a random effect, to examine the relationship between organ weights as a percentage of body weight (% BW), meat yield and other animal attributes. The best heart weight model (% BW) included the effects of sex, species (chicken or turkey), bird purpose (meat or egg), breast meat yield (%), and live weight (g). The best liver weight model (% BW) included species, bird purpose, breast meat yield (%), and live weight (g). The best lung weight (% BW) model included heart weight (g). Model performance was evaluated using residuals analysis, root mean squared prediction error, and the concordance correlation coefficient. Findings suggest that laying hens have larger hearts relative to body weight compared to broiler chickens and turkeys. The liver and lung models revealed that broiler chickens had larger livers (% BW) compared to laying hens, and that lung weight (% BW) was negatively correlated to heart weight (g). These results highlight the potential need to consider organ health in breeding programs focused on meat yield.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.360
Threshold uncertainty score0.320

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.003
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 head0.088
GPT teacher head0.256
Teacher spread0.168 · 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

Citations4
Published2025
Admission routes2
Has abstractyes

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