Evidence map›Paper›PMID 38190444›Full record

ArticleJournal of animal science2024

Effects of bacterial direct-fed microbial combinations on beef cattle growth performance, feeding behavior, nutrient digestibility, ruminal morphology, and carcass characteristics.

Alejandra M Lopez, Jhones O Sarturi, Bradley J Johnson, Dale R Woerner, Darren D Henry, Francine M Ciriaco, Kaliu G S Silva, Camron J Rush

Open access · greenAbstract readRandomized Controlled Trial, Veterinary
In one paragraph

Article in Journal of animal science, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
5.7field-weighted citation impact, top 5% 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

6 citing papers in PubMed, 10 citations in OpenAlex.

  1. Article
  2. Article
  3. The effect of aVeterinary and animal science · 2025
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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

8 authors at 2 institutions in 1 country.

Alejandra M LopezDepartment of Animal and Food Sciences, Texas Tech University, Lubbock, TX 79409, USA.
Jhones O SarturiDepartment of Animal and Food Sciences, Texas Tech University, Lubbock, TX 79409, USA.
Bradley J JohnsonDepartment of Animal and Food Sciences, Texas Tech University, Lubbock, TX 79409, USA.
Dale R WoernerDepartment of Animal and Food Sciences, Texas Tech University, Lubbock, TX 79409, USA.
Darren D HenryDepartment of Animal and Dairy Science, University of Georgia, Tifton, GA 31793, USA.
Francine M CiriacoDepartment of Animal and Dairy Science, University of Georgia, Tifton, GA 31793, USA.
Kaliu G S SilvaDepartment of Animal and Food Sciences, Texas Tech University, Lubbock, TX 79409, USA.
Camron J RushDepartment of Animal and Food Sciences, Texas Tech University, Lubbock, TX 79409, USA.
Texas Tech University · USUniversity of Georgia · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The effects of the dietary inclusion of a mixture of bacterial direct-fed microbial (DFM) on feedlot beef cattle growth performance, carcass characteristics, nutrient digestibility, feeding behavior, and ruminal papillae morphology were evaluated. Crossbred-Angus steers (n = 192; initial body weight (BW) = 409 kg ± 8 kg) were blocked by BW and randomly assigned into 48 pens (4 steers/pen and 16 pens/treatment) following a randomized complete block design. A steam-flaked corn-based fishing diet was offered to ad libitum intake once daily for 153 d containing the following treatments: (1) Control (no DFM, lactose carrier only); (2) treat-A (Lactobacillus animalis, Propionibacterium freudenreichii, Bacillus subtilis, and Bacillus licheniformis), at 1:1:1:3 ratio, respectively; totaling 6 × 109 CFU (50 mg)/animal-daily minimum; and (3) treat-B, the same DFM combination, but with doses at 1:1:3:1 ratio. Bacterial counts were ~30% greater than the minimum expected. Data were analyzed using the GLIMMIX procedure of SAS, with pen as the experimental unit, the fixed effect of treatment, and the random effect of BW-block, while preplanned contrasts comparing Control × treat-A or treat-B were used. Steers offered treat-A had increased carcass-adjusted average daily gain (P = 0.03) by 6.7%, gain efficiency (P < 0.01) by 6%, tended (P = 0.07) to have increased carcass-adjusted final BW by 15 kg, and hot carcass weight (P = 0.07) by 10 kg, while treat-B did not differ (P ≥ 0.17) from control. Overall dry matter (DM) intake (P = 0.36) and other carcass traits (P ≥ 0.13) were not affected by treatments. Steers offered treat-A tended to have increased digestibility of DM (P = 0.07) by 3%, neutral detergent fiber (P = 0.10), and hemicellulose (P = 0.08) by 9% compared with control, while treat-B did not differ (P ≥ 0.10) from control. No treatment × period interactions (P ≥ 0.21) or main effects of treatment (P ≥ 0.12) were observed during 24-h feeding behavior. Steers ruminated, ate, chewed, and were more active (P ≤ 0.01) during the second behavioral assessment (day 113), while drinking behavior was not affected (P ≥ 0.88). Ruminal papillae morphology and ruminal ammonia concentration (ruminal fluid collected at slaughter facility) were not affected by treatment (P ≥ 0.39). Steers offered the DFM treat-A had improved growth performance and it positively affected carcass weight and nutrient digestion. The DFM combinations did not seem to affect feedlot cattle feeding behavior or ruminal papillae morphology.

Indexed as

DietNutrientsAnimal FeedAnimalsCattleDigestionFeeding BehaviorLactobacillusRumenNutrientsBacillus licheniformisBacillus subtilisLactobacillus animalispapillae morphologyPropionibacterium freudenreichii

Identifiers

PMID38190444
PMCPMC10836501
OpenAlexW4390659603

What OpenQuestion holds

Textmetadata
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.