PSVIII-21 Meta-analysis of nutritive factors influencing mean retention time of digesta in the gastrointestinal tract of broiler chickens
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.018 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.013 | 0.049 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".