Meta-analysis of the effects of prepartum dietary protein on performance of dairy cows.

Clicks: 265
ID: 42160
2019
Article Quality & Performance Metrics
Overall Quality
Not rated
Combines reader engagement with the AI quality analysis. This article has not been analysed, so there is no overall score — reader engagement is measured and shown alongside.
AI Quality Assessment
Not analyzed
Readership in this journal
Steady

Ranked #56 of 140 articles by views in Journal of dairy science

Most read Least read

Bar heights use a square-root scale. Only the 120 most-read articles are drawn; the journal has 140 in total.

Mint this article as an NFT
Not yet minted

Create a permanent, verifiable on-chain record of this article on the Scimatic Network. The NFT is held in your Journament account, and you can withdraw it to your own wallet at any time.

5 SUSD one-off · no wallet required
Abstract
The objectives were to review the published literature and use meta-analytic methods to determine the effects of dietary protein fed prepartum on productive performance of dairy cows. The hypothesis was that responses to dietary protein prepartum would differ between nulliparous and parous cows, and performance would be maximized at a greater protein supply in nulliparous than in parous cows. The literature was systematically reviewed, searching randomized experiments in which the prepartum dietary content or degradability of protein was manipulated. Twenty-seven experiments including 125 treatment means and 1,801 cows were included in the meta-analysis. Of those, 8 experiments with 27 treatment means reported responses for 510 nulliparous cows. Data collected included the ingredient composition and chemical analyses of prepartum diets, parity group, and means and respective measures of variance for productive responses. Mixed model meta-analysis was conducted and statistical models investigated the effects of dietary crude protein (CP) or supply of metabolizable protein (MP) prepartum on performance. Supply of MP was predicted using the National Research Council Nutrient Requirements of Dairy Cattle (2001) model. The mean ± standard deviation and median (range) concentrations of dietary CP fed to cows prepartum were 14.4 ± 2.2 and 14.4% (8.9 to 20.9%), resulting in mean and median (range) intakes of CP prepartum of 1,720 ± 432 and 1,734 g/d (745 to 2,482 g/d). Predicted prepartum supply of MP averaged 822 ± 157 in nulliparous cows, ranging from 517 to 1,094 g/d, and 1,146 ± 316 in parous cows, ranging from 463 to 1,733 g/d. Increasing prepartum CP content or predicted supply of MP improved postpartum dry matter intake in nulliparous cows, but increasing prepartum CP content reduced prepartum dry matter intake in parous cows. Yields of milk and fat-corrected milk increased with increasing prepartum supply of MP in nulliparous but not in parous cows. Yields of fat and protein increased in nulliparous cows with increased CP content or supply of MP. Alternatively, in parous cows, yield of milk fat was not influenced by supply of MP but responded quadratically to dietary CP content and was maximized at approximately 14% CP. Dietary CP had no effect on protein yield in parous cows, but increasing the supply of MP improved protein yield only in cows from experiments with >36 kg/d of milk production, whereas MP supply had no effect on protein yield of parous cows from experiments with <28 kg/d of milk production. Performance of dairy cows was responsive to prepartum supply of MP and nulliparous benefited from diets with increased MP intake. Based on current results, production responses for nulliparous cows increased linearly up to the maximum MP intake of 1,100 g/d observed in the study, whereas for parous cows, only yield of milk protein in cows producing more than 36 kg of milk/d was influenced by supplying more than 800 g/d of MP.
Reference Key
husnain2019metaanalysisjournal Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Husnain, A;Santos, J E P;
Journal Journal of dairy science
Year 2019
DOI
S0022-0302(19)30764-7
URL
Keywords Keywords not found

Citations

No citations found. To add a citation, contact the admin at info@scimatic.org

No comments yet. Be the first to comment on this article.