FREE SHIPPING over $40
OVER 9000 FIVE-STAR REVIEWS
5% OFF ALL SUBSCRIPTIONS
100% HAPPINESS GUARANTEE
Analyze Diet
0
Home / Equine Research Bank / BMC Vet Res / Effects of steam-flaked grains on foals’ growth and fa...
BMC veterinary research2021; 17(1); 293; doi: 10.1186/s12917-021-02994-8

Effects of steam-flaked grains on foals’ growth and faecal microbiota.

Abstract: There is little objective information concerning the effect of steam-flaked grains on foal's growth performance and faecal microbiota. To determine the effects of steam-flaked grains on foal's growth performance and faecal microbiota, faecal samples were collection from 18 foals which had been fed either corn, oat or barley diets over the 60 days of the experiment. Body weight and conformation measurements were collected. Next-generation sequencing of the V3 + V4 region of the 16 S rRNA gene was used to assess the microbial composition of faeces. Alpha diversity, Venn graph, Relative abundance and beta diversity are presented. Results: There was a significantly higher larger increase in the body weight of those foals fed barley compared to either corn or oats. There were also significant changes in the Alpha diversity of the gut microbiota. The Shannon and Simpson indices were significantly higher in the barley fed group than those fed corn or oats. The Chao1 index was significantly higher in the oat fed group than the corn or barley fed groups. There were significant changes in the relative abundance of bacteria in the microbiota in terms of phylum, family and genus. The histogram of LDA value distribution showed that the 12 statistically different biomarkers of the bacteria were present. Tax4Fun function annotation clustering heat map showed that functional information was detected from 26 species of bacteria in faecal samples from the foals. Conclusions: Differences by starch sources were found in overall growth of the foals and in the faecal microbiota if either supplementary corn, oat or barley was fed. Further studies are required to determine the potential impact of the changes in the microbiota on the health and development of foals fed cereal starch of different sources.
© 2021. The Author(s).
Get Full Text
Publication Date: 2021-09-04 PubMed ID: 34481494PubMed Central: PMC8418754DOI: 10.1186/s12917-021-02994-8Google Scholar: Lookup
The Equine Research Bank provides access to a large database of publicly available scientific literature. Inclusion in the Research Bank does not imply endorsement of study methods or findings by Mad Barn.
LinkedInCopy
  • Journal Article

Summary

This research summary has been generated with artificial intelligence and may contain errors and omissions. Refer to the original study to confirm details provided. Submit correction.

This research investigated the impact of feeding steam-flaked grains (corn, oat, or barley) on the growth and gut microbiome of foals. Results indicated that diet alterations significantly influenced both the foals’ growth, with barley-fed foals gaining more weight, and the diversity and composition of the gut microbiota.

Research Methodology

  • The study was conducted on 18 foals, partitioned into three groups, each receiving a diet of steam-flaked corn, oats, or barley over a 60 day period.
  • Body weight and conformation measurements were taken to assess growth performance.
  • Faecal samples were collected to determine the effect on the faecal microbiota.
  • Next-generation sequencing of the 16S rRNA gene markers in the collected samples was performed for microbial identification and diversity analysis. This method allows for accurate profiling of gut microbiota.

Research Findings

  • Foals fed on barley had a significantly higher increase in body weight compared to those fed corn or oats.
  • There were noticeable differences in the diversity and composition of gut microbiota based on the type of grain consumed.
  • Several diversity indices (including Shannon and Simpson) were significantly higher in the barley-fed group, indicating more diverse microbiota.
  • The Chao1 index, another measure of diversity, was significantly higher in oat-fed foals than those fed with corn or barley.
  • There were variations in the relative abundance of bacteria on the phylum, family and genus levels, depending on the type of grain fed.
  • The distribution of Linear discriminant analysis (LDA) values indicated the presence of 12 statistically different bacterial biomarkers among the groups.
  • Functional annotation, using Tax4Fun function, detected information from 26 bacterial species in the foals’ faecal samples. This function helps understand the potential roles of these bacteria within the gut.

Conclusion

  • The study found differences in the overall growth of the foals and the diversity and composition of the faecal microbiota, based on the source of starch in their diet (corn, oat or barley).
  • This preliminary study points out that diet modifications can influence the development and health of foals through changes in body growth and gut microbial diversity.
  • However, further studies are needed to better interpret the potential impact of microbiota changes on the health and development of foals due to varying cereal starch sources.

Cite This Article

APA
Li XB, Huang XX, Zang CJ, Ma C, Chen KX, Zhao GD, Li Q, Li XY, Zhang WJ, Yang KL. (2021). Effects of steam-flaked grains on foals’ growth and faecal microbiota. BMC Vet Res, 17(1), 293. https://doi.org/10.1186/s12917-021-02994-8

Publication

BMC veterinary research
ISSN: 1746-6148
NlmUniqueID: 101249759
Country: England
Language: English
Volume: 17
Issue: 1
Pages: 293
PII: 293

Researcher Affiliations

Li, Xiao Bin
  • College of Animal Science, Xinjiang Key Laboratory of Herbivore Nutrition for Meat & Milk Production, Xinjiang Agricultural University, Xinjiang, 830052, Urumqi, China.
Huang, Xin Xin
  • College of Animal Science, Xinjiang Key Laboratory of Herbivore Nutrition for Meat & Milk Production, Xinjiang Agricultural University, Xinjiang, 830052, Urumqi, China.
Zang, Chang Jiang
  • College of Animal Science, Xinjiang Key Laboratory of Herbivore Nutrition for Meat & Milk Production, Xinjiang Agricultural University, Xinjiang, 830052, Urumqi, China.
Ma, Chen
  • College of Animal Science, Xinjiang Key Laboratory of Herbivore Nutrition for Meat & Milk Production, Xinjiang Agricultural University, Xinjiang, 830052, Urumqi, China.
Chen, Kai Xu
  • College of Animal Science, Xinjiang Key Laboratory of Herbivore Nutrition for Meat & Milk Production, Xinjiang Agricultural University, Xinjiang, 830052, Urumqi, China.
Zhao, Guo Dong
  • College of Animal Science, Xinjiang Key Laboratory of Herbivore Nutrition for Meat & Milk Production, Xinjiang Agricultural University, Xinjiang, 830052, Urumqi, China.
Li, Qian
  • College of Animal Science, Xinjiang Key Laboratory of Herbivore Nutrition for Meat & Milk Production, Xinjiang Agricultural University, Xinjiang, 830052, Urumqi, China.
Li, Xuan Yue
  • College of Animal Science, Xinjiang Key Laboratory of Herbivore Nutrition for Meat & Milk Production, Xinjiang Agricultural University, Xinjiang, 830052, Urumqi, China.
Zhang, Wen Jie
  • College of Animal Science, Xinjiang Key Laboratory of Herbivore Nutrition for Meat & Milk Production, Xinjiang Agricultural University, Xinjiang, 830052, Urumqi, China.
Yang, Kai Lun
  • College of Animal Science, Xinjiang Key Laboratory of Herbivore Nutrition for Meat & Milk Production, Xinjiang Agricultural University, Xinjiang, 830052, Urumqi, China. 1196129362@qq.com.

MeSH Terms

  • Animal Feed / analysis
  • Animals
  • Avena
  • Bacteria / classification
  • Diet / veterinary
  • Dietary Carbohydrates
  • Gastrointestinal Microbiome
  • Hordeum
  • Horses / growth & development
  • Horses / microbiology
  • RNA, Ribosomal, 16S / analysis
  • Zea mays

Grant Funding

  • 31860649 / Foundation for Innovative Research Groups of the National Natural Science Foundation of China

Conflict of Interest Statement

The authors declare that they have no competing interests.

References

This article includes 38 references
  1. Costa MC, Stämpfli HR, Arroyo LG, Allen-Vercoe E, Gomes RG, Weese JS. Changes in the equine fecal microbiota associated with the use of systemic antimicrobial drugs.. BMC Vet Res 2015 Feb 3;11:19.
    doi: 10.1186/s12917-015-0335-7pmc: PMC4323147pubmed: 25644524google scholar: lookup
  2. Glinsky MJ, Smith RM, Spires HR, Davis CL. Measurement of volatile fatty acid production rates in the cecum of the pony.. J Anim Sci 1976 Jun;42(6):1465-70.
    doi: 10.2527/jas1976.4261465xpubmed: 931822google scholar: lookup
  3. Dicks LMT, Botha M Dicks E, Botes M. The equine gastro-intestinal tract: an overview of the microbiota, disease and treatment.. Livestock Sci 2014;160:69–81.
  4. Daly K, Proudman CJ, Duncan SH, Flint HJ, Dyer J, Shirazi-Beechey SP. Alterations in microbiota and fermentation products in equine large intestine in response to dietary variation and intestinal disease.. Br J Nutr 2012 Apr;107(7):989-95.
    doi: 10.1017/S0007114511003825pubmed: 21816118google scholar: lookup
  5. Costa MC, Arroyo LG, Allen-Vercoe E, Stämpfli HR, Kim PT, Sturgeon A, Weese JS. Comparison of the fecal microbiota of healthy horses and horses with colitis by high throughput sequencing of the V3-V5 region of the 16S rRNA gene.. PLoS One 2012;7(7):e41484.
    doi: 10.1371/journal.pone.0041484pmc: PMC3409227pubmed: 22859989google scholar: lookup
  6. Harlow BE, Lawrence LM, Hayes SH, Crum A, Flythe MD. Effect of Dietary Starch Source and Concentration on Equine Fecal Microbiota.. PLoS One 2016;11(4):e0154037.
    pmc: PMC4851386pubmed: 27128793doi: 10.1371/journal.pone.0154037google scholar: lookup
  7. Svihus B, Uhlen AK, Harstad OM. Effect of starch granule structure,associated components and processing on nutritive value of cereal starch: a review.. Anim Feed Sci Technol 2005;122(3):303–320.
    doi: 10.1016/j.anifeedsci.2005.02.025google scholar: lookup
  8. Kienzle E, Pohlenz J, Radicke S. Morphology of starch digestion in the horse.. Zentralbl Veterinarmed A 1997 Jun;44(4):207-21.
    pubmed: 9270343doi: 10.1111/j.1439-0442.1997.tb01103.xgoogle scholar: lookup
  9. Kienzle E, Pohlenz J, Radicke S. Microscopy of starch digestion in the horse.. J Anim Physiol Anim Nutr 1998;80(1–5):213–216.
    doi: 10.1111/j.1439-0396.1998.tb00529.xgoogle scholar: lookup
  10. Defombelle A, Julliand V Drogoul C, Jacotot E. Feeding and microbial disorders in horses:1-Effects of an abrupt incorporation of two levels of barley in a hay diet on microbial profile and activities.. J EquineVet Sci 2001;21(9):439–45.
  11. Medina B, Girard ID, Jacotot E, Julliand V. Effect of a preparation of Saccharomyces cerevisiae on microbial profiles and fermentation patterns in the large intestine of horses fed a high fiber or a high starch diet.. J Anim Sci 2002 Oct;80(10):2600-9.
    pubmed: 12413082doi: 10.2527/2002.80102600xgoogle scholar: lookup
  12. Willing B, Vörös A, Roos S, Jones C, Jansson A, Lindberg JE. Changes in faecal bacteria associated with concentrate and forage-only diets fed to horses in training.. Equine Vet J 2009 Dec;41(9):908-14.
    pubmed: 20383990doi: 10.2746/042516409x447806google scholar: lookup
  13. Julliand V, Defombelle A, Varloud M. Starch digestion in horses: the impact of feed processing.. Livestock Sci 2005;100(1):44–52.
    doi: 10.1016/j.livprodsci.2005.11.001google scholar: lookup
  14. Rowe JB, Choct M, Pethick DW. Processing cereal grains for animal feeding.. Aust J Agric Res 1999;50:721–736.
    doi: 10.1071/AR98163google scholar: lookup
  15. Yao QF, Zhao YP, Mang L, Wu NEF. Study progress on diversity of germplasm resources of Chinese local horses.. Anim Husbandry Feed Sci 2009;30(10):126–30.
  16. Magoč T, Salzberg SL. FLASH: fast length adjustment of short reads to improve genome assemblies.. Bioinformatics 2011 Nov 1;27(21):2957-63.
    doi: 10.1093/bioinformatics/btr507pmc: PMC3198573pubmed: 21903629google scholar: lookup
  17. Caporaso JG, Kuczynski J, Stombaugh J, Bittinger K, Bushman FD, Costello EK, Fierer N, Peña AG, Goodrich JK, Gordon JI, Huttley GA, Kelley ST, Knights D, Koenig JE, Ley RE, Lozupone CA, McDonald D, Muegge BD, Pirrung M, Reeder J, Sevinsky JR, Turnbaugh PJ, Walters WA, Widmann J, Yatsunenko T, Zaneveld J, Knight R. QIIME allows analysis of high-throughput community sequencing data.. Nat Methods 2010 May;7(5):335-6.
    doi: 10.1038/nmeth.f.303pmc: PMC3156573pubmed: 20383131google scholar: lookup
  18. Wang Q, Garrity GM, Tiedje JM, Cole JR. Naive Bayesian classifier for rapid assignment of rRNA sequences into the new bacterial taxonomy.. Appl Environ Microbiol 2007 Aug;73(16):5261-7.
    doi: 10.1128/AEM.00062-07pmc: PMC1950982pubmed: 17586664google scholar: lookup
  19. McDonald D, Price MN, Goodrich J, Nawrocki EP, DeSantis TZ, Probst A, Andersen GL, Knight R, Hugenholtz P. An improved Greengenes taxonomy with explicit ranks for ecological and evolutionary analyses of bacteria and archaea.. ISME J 2012 Mar;6(3):610-8.
    doi: 10.1038/ismej.2011.139pmc: PMC3280142pubmed: 22134646google scholar: lookup
  20. Rideout JR, He Y, Navas-Molina JA, Walters WA, Ursell LK, Gibbons SM, Chase J, McDonald D, Gonzalez A, Robbins-Pianka A, Clemente JC, Gilbert JA, Huse SM, Zhou HW, Knight R, Caporaso JG. Subsampled open-reference clustering creates consistent, comprehensive OTU definitions and scales to billions of sequences.. PeerJ 2014;2:e545.
    doi: 10.7717/peerj.545pmc: PMC4145071pubmed: 25177538google scholar: lookup
  21. Cole JR, Wang Q, Cardenas E, Fish J, Chai B, Farris RJ, Kulam-Syed-Mohideen AS, McGarrell DM, Marsh T, Garrity GM, Tiedje JM. The Ribosomal Database Project: improved alignments and new tools for rRNA analysis.. Nucleic Acids Res 2009 Jan;37(Database issue):D141-5.
    pmc: PMC2686447pubmed: 19004872doi: 10.1093/nar/gkn879google scholar: lookup
  22. Segata N, Izard J, Waldron L, Gevers D, Miropolsky L, Garrett WS, Huttenhower C. Metagenomic biomarker discovery and explanation.. Genome Biol 2011 Jun 24;12(6):R60.
    pmc: PMC3218848pubmed: 21702898doi: 10.1186/gb-2011-12-6-r60google scholar: lookup
  23. Langille MG, Zaneveld J, Caporaso JG, McDonald D, Knights D, Reyes JA, Clemente JC, Burkepile DE, Vega Thurber RL, Knight R, Beiko RG, Huttenhower C. Predictive functional profiling of microbial communities using 16S rRNA marker gene sequences.. Nat Biotechnol 2013 Sep;31(9):814-21.
    doi: 10.1038/nbt.2676pmc: PMC3819121pubmed: 23975157google scholar: lookup
  24. Li B, Zhang X, Guo F, Wu W, Zhang T. Characterization of tetracycline resistant bacterial community in saline activated sludge using batch stress incubation with high-throughput sequencing analysis.. Water Res 2013 Sep 1;47(13):4207-16.
    doi: 10.1016/j.watres.2013.04.021pubmed: 23764571google scholar: lookup
  25. Aßhauer KP, Wemheuer B, Daniel R, Meinicke P. Tax4Fun: predicting functional profiles from metagenomic 16S rRNA data.. Bioinformatics 2015 Sep 1;31(17):2882-4.
    doi: 10.1093/bioinformatics/btv287pmc: PMC4547618pubmed: 25957349google scholar: lookup
  26. Gómez LM, Posada Ángel SL, O M. Starch in ruminant diets:a review.. Rev Colombiana Ciencias Pecuarias 2016;29(2):77–90.
  27. Pérez S, Bertoft E. The molecular structures of starch components and their contribution to the architecture of starch granules: a comprehensive review.. Starch-Stärke 2010;62(8):389–420.
    doi: 10.1002/star.201000013google scholar: lookup
  28. Meyer H, Radicke S, Kienzle E, Wilke S, Kleffken D. Investigations on preileal digestion of oats, corn and barley starch in relation to grain processing.. in ENPS (ed): 13th Equine Nutrition and Physiology Symposium Gainesville; 1993. p. 92–7.
  29. Mohsen R Mehdi K&B, Mehdi HY, Mehdi M. Effects of corn grain processing method (ground versus steam-flaked) with rumen undegradable to degradable protein ratio on growth performance, ruminal fermentation, and microbial protein yield in Holstein dairy calves.. Anim Feed Sci Technol 2020;269:114646.
  30. Potter GD, Arnold FF, Householder DD, Hansen Brown DHKM. Digestion of starch in the small or large intestine of the equine.. Pferdeheilkunde 1992;1(4):107–111.
  31. Meyer H, Radicke S, Kienzle E, Wilke S, Kleffken D, Illenseer M. Investigations on preileal digestion of starch from grain, potato and manioc in horses.. Zentralbl Veterinarmed A 1995 Aug;42(6):371-81.
    pubmed: 7495169doi: 10.1111/j.1439-0442.1995.tb00389.xgoogle scholar: lookup
  32. Kienzle E, Radicke S, Wilke S, Landes E, Meyer H. Preileal starch digestion in relation to source and preparation of starch. Pferdeheilkunde (1st European Conference on Horse Nutrition) 1992; p. 103.
  33. Kong BW, Kim JI, Kim MJ, Kim JC. Porcine pancreatic alpha-amylase hydrolysis of native starch granules as a function of granule surface area.. Biotechnol Prog 2003 Jul-Aug;19(4):1162-6.
    doi: 10.1021/bp034005mpubmed: 12892477google scholar: lookup
  34. Radicke S, Kienzle E, Meyer H. Preileal apparent digestibility of oats and corn starch and consequences for cecal metabolism. Proceedings of the 12th Equine Nutrition and Physiology Symposium, Calgary, Canada 1991:43–8.
  35. de Fombelle A, Veiga L, Drogoul C, Julliand V. Effect of diet composition and feeding pattern on the prececal digestibility of starches from diverse botanical origins measured with the mobile nylon bag technique in horses.. J Anim Sci 2004 Dec;82(12):3625-34.
    doi: 10.2527/2004.82123625xpubmed: 15537784google scholar: lookup
  36. Rosenfeld I, Austbø D. Digestion of cereals in the equine gastrointestinal tract measured by the mobile bag technique on caecally cannulated horses.. Anim Feed Sci Technol 2008;150(3):249–258.
  37. Garner HE, Moore JN, Johnson JH, Clark L, Amend JF, Tritschler LG, Coffmann JR, Sprouse RF, Hutcheson DP, Salem CA. Changes in the caecal flora associated with the onset of laminitis.. Equine Vet J 1978 Oct;10(4):249-52.
    pubmed: 738266doi: 10.1111/j.2042-3306.1978.tb02273.xgoogle scholar: lookup
  38. Bulmer LS, Murray JA, Burns NM, Garber A, Wemelsfelder F, McEwan NR, Hastie PM. High-starch diets alter equine faecal microbiota and increase behavioural reactivity.. Sci Rep 2019 Dec 9;9(1):18621.
    doi: 10.1038/s41598-019-54039-8pmc: PMC6901590pubmed: 31819069google scholar: lookup

Citations

This article has been cited 1 times.
  1. Li XB, Huang XX, Li Q, Li XY, Li JH, Li C, He LJ, Jing HX, Yang KL. Effects of different grains on bacterial diversity and enzyme activity associated with digestion of starch in the foal stomach.. BMC Vet Res 2022 Nov 17;18(1):407.
    doi: 10.1186/s12917-022-03510-2pubmed: 36397114google scholar: lookup
Subscribe to our newsletter
Join 99,344 horse owners like you who receive our email updates on horse health and nutrition.