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Record W4402541696 · doi:10.1093/jas/skae234.670

PSVIII-21 Meta-analysis of nutritive factors influencing mean retention time of digesta in the gastrointestinal tract of broiler chickens

2024· article· en· W4402541696 on OpenAlexaff
Grace Hong, Emily M. Leishman, Elijah G. Kiarie, J.L. Ellis

Bibliographic record

VenueJournal of Animal Science · 2024
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Nutrition and Physiology
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsBroilerGastrointestinal tractAnimal scienceRetention timeMeta-analysisBiologyFood scienceChemistryInternal medicineMedicineBiochemistryChromatography

Abstract

fetched live from OpenAlex

Abstract Broiler chicken meat is an important source of food protein for human consumption globally. Over the last several decades, dramatic changes have been made to broiler genetics, management, and nutrition to increase production efficiency. Different feeds with varying nutrient composition have been researched to target goals such as improving growth and feed conversion ratio. Part of understanding and further improving these feeding programs involves understanding the effects of the feed on nutrient digestibility and animal performance. As such, models are a key tool in the wholistic evaluation of diet, genetics, and management interactions. Towards developing a mechanistic digestion model for broilers, knowledge of mean retention time (MRT, min) of digesta in the gastrointestinal tract (GIT) across a variety of diets is required. To understand the relationship between MRT in broilers and their diet, a systematic literature search and meta-analysis was conducted where 34 articles were found to meet the inclusion criteria. MRT in these studies was measured in various parts of the GIT where 7 studies reported MRT in just one segment (e.g. jejunum), 12 studies reported MRT in multiple combined segments (e.g. jejunum + ileum) and 21 studies reported MRT of the entire GIT. Birds used in these studies included those in the starter, grower, and finisher phases as well as breeders. Nutritional composition of the diets was represented by data on metabolizable energy (ME, kcal/kg), crude fiber (% DM), crude fat (% DM), crude protein (% DM) and calcium (% DM) that was consistently reported across studies. A mixed model (PROC MIXED, in SAS), treating study as a random effect, and using a subset of the data collected where MRT was reported for the entire GIT, and limited to grower and finisher phases, was used to examine the relationship between the diet composition and MRT. Only ME (F1,28.1 = 4.25; P = 0.0486) was found to be significantly related to MRT, where an increase in one kcal/kg of ME resulted in a decrease of MRT by 0.091 minutes (within the range of 2,749 to 3,507 kcal/kg ME). Other nutritional components of the diet were found to have no significant relation to MRT (all P > 0.05), though next steps will examine how the source of ME (fat vs starch vs fiber) impacts this relationship. Although other factors (such as age and feed intake) are still to be considered, the initial results from this study provide valuable insights into how nutritional composition of poultry feeds relates to MRT. Further investigation will also quantify this relationship within segment of the GIT. This work not only provides valuable information to nutritionists, but also lays the groundwork for empirical model development to predict MRT of poultry feed, essential to poultry nutritional models.

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)0.008
metaresearch head score (Gemma)0.018
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.992
Threshold uncertainty score0.044

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.018
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0130.049
Bibliometrics0.0050.005
Science and technology studies0.0010.001
Scholarly communication0.0040.001
Open science0.0020.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0050.001

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 head0.070
GPT teacher head0.286
Teacher spread0.216 · 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.

Study designMeta-analysis
DomainMethods
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

Citations1
Published2024
Admission routes1
Has abstractyes

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