Evidence map›Paper›PMID 36230332›Full record

ArticleAnimals : an open access journal from MDPI2022

Silage Mixtures of Alfalfa with Sweet Sorghum Alter Blood and Rumen Physiological Status and Rumen Microbiota of Karakul Lambs.

Jiao Wang, Long Cheng, Abdul Shakoor Chaudhry, Hassan Khanaki, Imtiaz H R Abbasi, Yi Ma, Farzana Abbasi, Xuefeng Guo, Sujiang Zhang

Open access · goldAbstract read
In one paragraph

Article in Animals : an open access journal from MDPI, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
1.9field-weighted citation impact, top 14% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed, 8 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors at 5 institutions in 4 countries.

Jiao WangKey Laboratory of Tarim Animal Husbandry Science and Technology, College of Animal Science and Technology, Tarim University, Alar 843300, China.ORCID 0000-0002-9317-9649
Long ChengFaculty of Veterinary and Agricultural Sciences, The University of Melbourne, Dookie College 3647, Australia.ORCID 0000-0002-8483-0495
Abdul Shakoor ChaudhrySchool of Natural and Environmental Sciences, Newcastle University, Newcastle upon Tyne NE1 7RU, UK.ORCID 0000-0002-6350-0374
Hassan KhanakiFaculty of Veterinary and Agricultural Sciences, The University of Melbourne, Dookie College 3647, Australia.
Imtiaz H R AbbasiDepartment of Animal Nutrition, Faculty of Animal Production and Technology, Cholistan University of Veterinary and Animal Sciences, Bahawalpur 63100, Pakistan.
Yi MaFaculty of Veterinary and Agricultural Sciences, The University of Melbourne, Dookie College 3647, Australia.
Farzana AbbasiFaculty of Chemical and Biological Sciences, The Islamia University, Bahawalpur 63100, Pakistan.
Xuefeng GuoKey Laboratory of Tarim Animal Husbandry Science and Technology, College of Animal Science and Technology, Tarim University, Alar 843300, China.ORCID 0000-0003-3909-7869
Sujiang ZhangKey Laboratory of Tarim Animal Husbandry Science and Technology, College of Animal Science and Technology, Tarim University, Alar 843300, China.
Tarim University · CNThe University of Melbourne · AUIslamia University of Bahawalpur · PKNewcastle University · GBUniversity of Veterinary and Animal Sciences · PK

Funding

Key Laboratory of Tarim Animal Husbandry Science and Technology, Xinjiang Production & Construction Group HS202101National Natural Science Foundation of China 31760689
6 · The paper itself

Abstract

The study investigated the effects of feeding mixtures of alfalfa (AF) and sweet sorghum (SS) at different ratios of silages in terms of the physiological status of blood and rumen, and rumen microbiota in lambs. A total of 30 four-month-old male Karakul lambs with 25.5 ± 1.4 kg mean initial body weight were randomly allocated to five groups, with six lambs in each group. Five experimental diets containing 40% of one of the five AF−SS mixed silages (containing 0%, 20%, 40%, 60%, and 80% AF on a fresh weight basis, respectively) and 60% of other ingredients were formulated. Overall, the results showed that the mixed silage with more AF tended to increase serum antioxidant capacity, dry matter (DM) intake, and rumen fermentation metabolites. The AF−SS mixed silages containing AF at 60% and 80% caused a significant linear increase (p < 0.05) in the activity of total antioxidant capacity. The superoxide dismutase in the Karakul lamb responded with significant linear and quadratic increases (p < 0.01) as the ratio of AF was increased in the AF−SS mixed silages. Feeding diets with AF in silage mixtures at the ratio of 60% significantly increased (p < 0.05) the concentration of ruminal total volatile fatty acids (tVFA), acetate, and ammonia-N. However, no statistical significance (p > 0.05) was found in the alpha diversity of rumen microbes among the tested groups (p > 0.05). Principal coordinates analysis could clearly discriminate the differences between the five groups (p = 0.001). The relative abundance of Firmicutes in the rumen were significantly higher with AF at 40% in the AF−SS silage-based diet than those with AF at 0%, and 20% ratios. The abundance of Ruminococcus_albus had a significant linear increase (p < 0.05), as the ratio of AF in the AF−SS mixed silages was increased. In conclusion, the best beneficial effect on the physiological status of the blood and rumen, DM intake, and rumen microbiota in lambs came from those that consumed the diet containing the AF−SS mixed silage with 60% AF.

Indexed as

alfalfaKarakul lambsrumen fermentationrumen microbiotasilage mixturesweet sorghum

Identifiers

PMID36230332
PMCPMC9559280
OpenAlexW4297540280

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.