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Record W3092897185 · doi:10.3168/jds.2020-18580

Effect of dietary lipids and other nutrients on milk odd- and branched-chain fatty acid composition in dairy ewes

2020· article· en· W3092897185 on OpenAlexafffund
Pablo G. Toral, Gonzalo Hervás, Antonella Della Badia, R. Gervais, Pilar Frutos

Bibliographic record

VenueJournal of Dairy Science · 2020
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicRuminant Nutrition and Digestive Physiology
Canadian institutionsUniversité Laval
FundersAgencia Estatal de InvestigaciónEuropean Social FundEuropean Regional Development FundMinisterio de Ciencia e InnovaciónUniversité Laval
KeywordsRumenFood sciencePolyunsaturated fatty acidComposition (language)NutrientFatty acidBiologyMilk fatAnimal scienceChemistryBiochemistry

Abstract

fetched live from OpenAlex

Milk odd- and branched-chain fatty acids (OBCFA) are largely derived from bacteria leaving the rumen, which has encouraged research on their use as biomarkers of rumen function. Targeted research has examined relationships between these fatty acids (FA) and dietary components, but interactions between the effects of lipids and other nutrients on milk OBCFA are not well characterized yet. Furthermore, factors controlling milk OBCFA in sheep are largely unknown. Thus, the present meta-analysis examined relationships between diet composition and milk OBCFA using a database compiled with lot observations from 14 trials in dairy ewes fed lipid supplements. A total of 47 lots received lipid supplements, whereas their respective controls (27 lots) were fed the same basal diets without lipid supplementation. Relationships between milk OBCFA and dietary components were first assessed through a principal component analysis (PCA) and a correlation analysis. Then, responses of milk OBCFA to variations in specific dietary components (selected on the basis of the PCA) were examined in more detail by regression analysis. According to the loading plot, dietary unsaturated C18 FA loaded opposite to major milk OBCFA (e.g., 15:0, 15:0 anteiso, and 17:0) and were strongly correlated with principal component 1, which described 46% of variability. Overall, regression equations supported this negative, and generally linear, relationship between unsaturated C18 FA levels and milk OBCFA. However, the influence of C20-22 n-3 polyunsaturated FA and saturated FA was more limited. The PCA also suggested that dietary crude protein is not a determinant of milk OBCFA profile in dairy ewes, but significant relationships were observed between some OBCFA and dietary fiber or starch, consistent with a potential role of these FA as biomarkers of rumen cellulolytic and amylolytic bacteria. In this regard, regression equations indicated that iso FA would show opposite responses to increasing levels of acid detergent fiber (positive linear coefficients) and starch (negative linear coefficients). Lipid supplementation would not largely affect these associations, supporting the potential of OBCFA as noninvasive markers of rumen function under different feeding conditions (i.e., with or without lipid supplementation). Because consumption of these FA may have nutritional benefits for humans, the use of high-fiber/low-starch rations might be recommended to maintain the highest possible content of milk OBCFA in dairy sheep.

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)0.005
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.005
Threshold uncertainty score0.029

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.003
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.021
GPT teacher head0.256
Teacher spread0.235 · 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.

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

Citations19
Published2020
Admission routes2
Has abstractyes

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