Plasma Metabolites, Productive Performance and Rumen Volatile Fatty Acid Profiles of Northern Australian Bos indicus Steers Supplemented with Desmanthus and Lucerne
Abstract
:1. Introduction
2. Results
2.1. Chemical Composition
2.2. Animal Performance
2.3. Effect of Lucerne and Desmanthus on Rumen and Plasma Metabolites
2.4. Nitrogen Metabolism
2.5. Effect of Polyethylene Glycol on Animal Performance, Rumen VFA, Plasma Metabolites, and Nitrogen Retention
3. Discussion
3.1. Chemical Composition
3.2. Animal Performance
3.3. Effect of Lucerne and Desmanthus on Rumen Volatile Fatty Acids and Plasma Metabolites
3.4. Nitrogen Concentration in Animals Fed Lucerne and Desmanthus
3.5. Effect of Polyethylene Glycol on Animal Performance, Rumen VFA, Plasma Metabolites, and Nitrogen Concentrations
4. Materials and Methods
4.1. Animals and Treatment
4.2. Feed Chemical Composition and Analysis
4.3. Dry Matter Intake and Liveweight Gain
4.4. F.NIRS Estimates of Diet Quality and Estimation of Urinary N
4.5. Rumen Collection and Volatile Fatty Acids Analysis
4.6. Blood Sample Collection and Plasma Metabolite Analysis
4.7. Statistical Analyses
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
- Connolly, S.; Dona, A.; Hamblin, D.; D’Occhio, M.J.; Gonzalez, L.A. Changes in the blood metabolome of Wagyu crossbred steers with time in the feedlot and relationships with marbling. Sci. Rep. 2020, 10, 11. [Google Scholar] [CrossRef]
- Goldansaz, S.A.; Guo, A.C.; Sajed, T.; Steele, M.A.; Plastow, G.S.; Wishart, D.S. Livestock metabolomics and the livestock metabolome: A systematic review. PLoS ONE 2017, 12, e0177675. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Yang, J.S.; Zheng, J.; Fang, X.P.; Jiang, X.; Sun, Y.K.; Zhang, Y.G. Effects of dietary N-carbamylglutamate on growth performance, apparent digestibility, nitrogen metabolism and plasma metabolites of fattening Holstein bulls. Animals 2021, 11, 126. [Google Scholar] [CrossRef] [PubMed]
- Connolly, S.; Dona, A.; Wilkinson-White, L.; Hamblin, D.; D’Occhio, M.; Gonzalez, L.A. Relationship of the blood metabolome to subsequent carcass traits at slaughter in feedlot Wagyu crossbred steers. Sci. Rep. 2019, 9, 11. [Google Scholar] [CrossRef] [Green Version]
- Martinez-Fernandez, G.; Jiao, J.Z.; Padmanabha, J.; Denman, S.E.; McSweeney, C.S. Seasonal and nutrient supplement responses in rumen microbiota structure and metabolites of tropical rangeland cattle. Microorganisms 2020, 8, 1550. [Google Scholar] [CrossRef] [PubMed]
- Zhao, Y.C.; Xie, B.; Gao, J.; Zhao, G.Y. Dietary supplementation with sodium sulfate improves rumen fermentation, fiber digestibility, and the plasma metabolome through modulation of rumen bacterial communities in steers. Appl. Environ. Microbiol. 2020, 86, 18. [Google Scholar] [CrossRef] [PubMed]
- Kim, Y.; Kim, S.H.; Oh, S.J.; Lee, H.S.; Ji, M.; Choi, S.; Lee, S.S.; Paik, M.J. Metabolomic analysis of organic acids, amino acids, and fatty acids in plasma of Hanwoo beef on a high-protein diet. Metabolomics 2020, 16, 10. [Google Scholar] [CrossRef] [PubMed]
- Foroutan, A.; Fitzsimmons, C.; Mandal, R.; Berjanskii, M.V.; Wishart, D.S. Serum metabolite biomarkers for predicting residual feed intake (RFI) of young Angus bulls. Metabolites 2020, 10, 491. [Google Scholar] [CrossRef]
- Fitzsimons, C.; Kenny, D.A.; Deighton, M.H.; Fahey, A.G.; McGee, M. Methane emissions, body composition, and rumen fermentation traits of beef heifers differing in residual feed intake. J. Anim. Sci. 2013, 91, 5789–5800. [Google Scholar] [CrossRef] [Green Version]
- Annicchiarico, P.; Barrett, B.; Brummer, E.C.; Julier, B.; Marshall, A.H. Achievements and challenges in improving temperate perennial forage legumes. Crit. Rev. Plant. Sci. 2015, 34, 327–380. [Google Scholar] [CrossRef]
- McDonald, W.J.; Nikandrow, A.; Bishop, A.; Lattimore, M.; Gardner, P.; Williams, R.; Hyson, L. Lucerne for Pasture and Fodder. Available online: https://www.dpi.nsw.gov.au/__data/assets/pdf_file/0010/164737/p2225pt1.pdf (accessed on 8 December 2020).
- Kanani, J.; Lukefahr, S.; Stanko, R. Evaluation of tropical forage legumes (Medicago sativa, Dolichos lablab, Leucaena leucocephala and Desmanthus bicornutus) for growing goats. Small Rumin. Res. 2006, 65, 1–7. [Google Scholar] [CrossRef]
- Le, H.V.; Nguyen, D.V.; Nguyen, Q.V.; Malau-Aduli, B.S.; Nichols, P.D.; Malau-Aduli, A.E.O. Fatty acid profiles of muscle, liver, heart and kidney of Australian prime lambs fed different polyunsaturated fatty acids enriched pellets in a feedlot system. Sci. Rep. 2019, 9, 11. [Google Scholar] [CrossRef]
- McDonnell, R.P.; Staines, M.V.; Douglas, M.L.; Auldist, M.J.; Jacobs, J.L.; Wales, W.J. Rumen degradability characteristics of five starch-based concentrate supplements used on Australian dairy farms. Anim. Prod. Sci. 2017, 57, 1512–1519. [Google Scholar] [CrossRef]
- Pengelly, B.C.; Conway, M.J. Pastures on cropping soils: Which tropical pasture legume to use? Trop. Grassl. 2000, 34, 162–168. [Google Scholar]
- Suybeng, B.; Charmley, E.; Gardiner, C.P.; Malau-Aduli, B.S.; Malau-Aduli, A.E. Supplementing northern Australian beef cattle with Desmanthus tropical legume reduces in-vivo methane emissions. Animals 2020, 10, 2097. [Google Scholar] [CrossRef]
- Makkar, H.P.S. Effects and fate of tannins in ruminant animals, adaptation to tannins, and strategies to overcome detrimental effects of feeding tannin-rich feeds. Small Rumin. Res. 2003, 49, 241–256. [Google Scholar] [CrossRef]
- Grainger, C.; Clarke, T.; Auldist, M.; Beauchemin, K.; McGinn, S.; Waghorn, G.; Eckard, R.J. Potential use of Acacia mearnsii condensed tannins to reduce methane emissions and nitrogen excretion from grazing dairy cows. Can. J. Anim. Sci. 2009, 89, 241–251. [Google Scholar] [CrossRef] [Green Version]
- Lagrange, S.; Beauchemin, K.A.; MacAdam, J.; Villalba, J.J. Grazing diverse combinations of tanniferous and non-tanniferous legumes: Implications for beef cattle performance and environmental impact. Sci. Total Environ. 2020, 746, 13. [Google Scholar] [CrossRef]
- Tseu, R.J.; Junior, F.P.; Carvalho, R.F.; Sene, G.A.; Tropaldi, C.B.; Peres, A.H.; Rodrigues, P.H.M. Effect of tannins and monensin on feeding behaviour, feed intake, digestive parameters and microbial efficiency of nellore cows. Ital. J. Anim. Sci. 2020, 19, 262–273. [Google Scholar] [CrossRef] [Green Version]
- Sordi, A.; Dieckow, J.; Bayer, C.; Alburquerque, M.A.; Piva, J.T.; Zanatta, J.A.; Tomazi, M.; da Rosa, C.M.; de Moraes, A. Nitrous oxide emission factors for urine and dung patches in a subtropical Brazilian pastureland. Agric. Ecosyst. Environ. 2014, 190, 94–103. [Google Scholar] [CrossRef]
- Mueller-Harvey, I. Unravelling the conundrum of tannins in animal nutrition and health. J. Sci. Food Agric. 2006, 86, 2010–2037. [Google Scholar] [CrossRef]
- Mekuriaw, S.; Tsunekawa, A.; Ichinohe, T.; Tegegne, F.; Haregeweyn, N.; Nobuyuki, K.; Tassew, A.; Mekuriaw, Y.; Walie, M.; Tsubo, M.; et al. Mitigating the anti-nutritional effect of polyphenols on in vitro digestibility and fermentation characteristics of browse species in north western Ethiopia. Trop. Anim. Health Prod. 2020, 52, 1287–1298. [Google Scholar] [CrossRef] [PubMed]
- CSIRO. Nutrient Requirements of Domesticated Ruminants; CSIRO Publishing: Collingwood, VIC, Australia, 2007.
- Kohn, R.A.; Dinneen, M.M.; Russek-Cohen, E. Using blood urea nitrogen to predict nitrogen excretion and efficiency of nitrogen utilization in cattle, sheep, goats, horses, pigs, and rats. J. Anim. Sci. 2005, 83, 879–889. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Norman, H.C.; Hulm, E.; Humphries, A.W.; Hughes, S.J.; Vercoe, P.E. Broad near-infrared spectroscopy calibrations can predict the nutritional value of >100 forage species within the Australian feedbase. Anim. Prod. Sci. 2020, 60, 1111–1122. [Google Scholar] [CrossRef]
- Sonawane, A.S.; Deshpande, K.Y.; Rathod, S.B.; Shelke, P.R.; Nikam, M.G.; Gholve, A.U. Effect of feeding Hedge lucerne (Desmanthus virgatus) on intake, growth performance and body condition score in growing Osmanabadi goats. Indian J. Anim. Sci. 2019, 89, 881–884. [Google Scholar]
- Bergman, E. Energy contributions of volatile fatty acids from the gastrointestinal tract in various species. Physiol. Rev. 1990, 70, 567–590. [Google Scholar] [CrossRef] [Green Version]
- Brandao, V.L.N.; Faciola, A.P. Unveiling the relationships between diet composition and fermentation parameters response in dual-flow continuous culture system: A meta-analytical approach. Transl. Anim. Sci. 2019, 3, 1064–1075. [Google Scholar] [CrossRef] [Green Version]
- Vandermeulen, S.; Singh, S.; Ramírez-Restrepo, C.A.; Kinley, R.D.; Gardiner, C.P.; Holtum, J.A.; Hannah, I.; Bindelle, J. In vitro assessment of ruminal fermentation, digestibility and methane production of three species of Desmanthus for application in northern Australian grazing systems. Crop Pasture Sci. 2018, 69, 797–807. [Google Scholar] [CrossRef]
- Jayanegara, A.; Goel, G.; Makkar, H.P.; Becker, K. Divergence between purified hydrolysable and condensed tannin effects on methane emission, rumen fermentation and microbial population in vitro. Anim. Feed Sci. Technol. 2015, 209, 60–68. [Google Scholar] [CrossRef]
- Hristov, A.N.; Etter, R.P.; Ropp, J.K.; Grandeen, K.L. Effect of dietary crude protein level and degradability on ruminal fermentation and nitrogen utilization in lactating dairy cows. J. Anim. Sci. 2004, 82, 3219–3229. [Google Scholar] [CrossRef] [Green Version]
- Aboagye, I.A.; Oba, M.; Castillo, A.R.; Koenig, K.M.; Iwaasa, A.D.; Beauchemin, K.A. Effects of hydrolyzable tannin with or without condensed tannin on methane emissions, nitrogen use, and performance of beef cattle fed a high-forage diet. J. Anim. Sci. 2018, 96, 5276–5286. [Google Scholar] [CrossRef]
- Aguerre, M.J.; Capozzolo, M.C.; Lencioni, P.; Cabral, C.; Wattiaux, M.A. Effect of quebracho-chestnut tannin extracts at 2 dietary crude protein levels on performance, rumen fermentation, and nitrogen partitioning in dairy cows. J. Dairy Sci. 2016, 99, 4476–4486. [Google Scholar] [CrossRef] [Green Version]
- Beauchemin, K.A.; McGinn, S.M.; Martinez, T.F.; McAllister, T.A. Use of condensed tannin extract from quebracho trees to reduce methane emissions from cattle. J. Anim. Sci. 2007, 85, 1990–1996. [Google Scholar] [CrossRef] [Green Version]
- Kiro, R. Assessment of the rumen fluid of a bovine patient. Dairy Vet. Sci. J. 2017, 2, 555588. [Google Scholar] [CrossRef]
- Grünwaldt, E.G.; Guevara, J.C.; Estévez, O.R.; Vicente, A.; Rousselle, H.; Alcuten, N.; Aguerregaray, D.; Stasi, C.R. Biochemical and haematological measurements in beef cattle in Mendoza plain rangelands (Argentina). Trop. Anim. Health Prod. 2005, 37, 527–540. [Google Scholar] [CrossRef]
- Polkinghorne, R.; Philpott, J.; Thompson, J.M. Do extended transport times and rest periods impact on eating quality of beef carcasses? Meat Sci. 2018, 140, 101–111. [Google Scholar] [CrossRef]
- Rubio Lozano, M.S.; Méndez Medina, R.D.; Reyes Mayorga, K.; Rubio García, M.E.; Ovando, M.A.; Ngapo, T.M.; Galindo Maldonado, F.A. Effect of an allostatic modulator on stress blood indicators and meat quality of commercial young bulls in Mexico. Meat Sci. 2015, 105, 63–67. [Google Scholar] [CrossRef]
- Singh, A.K.; Kumar, M.; Kumar, V.; Roy, D.; Kushwaha, R.; Vaswani, S.; Kumar, A. Feed utilization, blood metabolites and ingestive behavior in Sahiwal calves divergently selected for low and high residual feed intake. Vet. Arh. 2019, 89, 481–503. [Google Scholar] [CrossRef]
- Hammond, A.C. The use of blood urea nitrogen concentration as an indicator of protein status in cattle. Bov. Pract. 1983, 1983, 114–118. [Google Scholar]
- Foroutan, A.; Fitzsimmons, C.; Mandal, R.; Piri-Moghadam, H.; Zheng, J.M.; Guo, A.C.; Li, C.; Guan, L.L.; Wishart, D.S. The bovine metabolome. Metabolites 2020, 10, 233. [Google Scholar] [CrossRef]
- Russel, A.J.F.; Wright, I.A. The use of blood metabolites in the determination of energy status in beef cows. Anim. Sci. 1983, 37, 335–343. [Google Scholar] [CrossRef]
- Lindsay, D. The effect of feeding pattern and sampling procedure on blood parameters. BSAP Occas. Publ. 1978, 1, 99–120. [Google Scholar] [CrossRef]
- Clemmons, B.A.; Mihelic, R.I.; Beckford, R.C.; Powers, J.B.; Melchior, E.A.; McFarlane, Z.D.; Cope, E.R.; Embree, M.M.; Mulliniks, J.T.; Campagna, S.R.; et al. Serum metabolites associated with feed efficiency in black angus steers. Metabolomics 2017, 13, 8. [Google Scholar] [CrossRef]
- Llonch, P.; Troy, S.M.; Duthie, C.-A.; Somarriba, M.; Rooke, J.; Haskell, M.J.; Roehe, R.; Turner, S.P. Changes in feed intake during isolation stress in respiration chambers may impact methane emissions assessment. Anim. Prod. Sci. 2018, 58, 1011–1016. [Google Scholar] [CrossRef] [Green Version]
- Dijkstra, J.; Oenema, O.; van Groenigen, J.W.; Spek, J.W.; van Vuuren, A.M.; Bannink, A. Diet effects on urine composition of cattle and N2O emissions. Animal 2013, 7, 292–302. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Aboagye, I.A.; Beauchemin, K.A. Potential of molecular weight and structure of tannins to reduce methane emissions from ruminants: A review. Animals 2019, 9, 856. [Google Scholar] [CrossRef] [Green Version]
- Calsamiglia, S.; Ferret, A.; Reynolds, C.K.; Kristensen, N.B.; van Vuuren, A.M. Strategies for optimizing nitrogen use by ruminants. Animal 2010, 4, 1184–1196. [Google Scholar] [CrossRef]
- Hristov, A.N.; Bannink, A.; Crompton, L.A.; Huhtanen, P.; Kreuzer, M.; McGee, M.; Noziere, P.; Reynolds, C.K.; Bayat, A.R.; Yanez-Ruiz, D.R.; et al. Invited review: Nitrogen in ruminant nutrition: A review of measurement techniques. J. Dairy Sci. 2019, 102, 5811–5852. [Google Scholar] [CrossRef] [Green Version]
- Lapierre, H.; Berthiaume, R.; Raggio, G.; Thivierge, M.C.; Doepel, L.; Pacheco, D.; Dubreuil, P.; Lobley, G.E. The route of absorbed nitrogen into milk protein. Anim.Sci. 2005, 80, 11–22. [Google Scholar] [CrossRef]
- Hammond, A.C.; Bowers, E.J.; Kunkle, W.E.; Genho, P.C.; Moore, S.A.; Crosby, C.E.; Ramsay, K.H.; Harris, J.H.; Essig, H.W. Use of blood urea nitrogen concentration to determine time and level of protein supplementation in wintering COWS1, 2. Prof. Anim. Sci. 1994, 10, 24–31. [Google Scholar] [CrossRef]
- Dixon, R.; Coates, D. Near infrared spectroscopy of faeces to evaluate the nutrition and physiology of herbivores. J. Near Infrared Spectrosc. 2009, 17, 1–31. [Google Scholar] [CrossRef]
- Waghorn, G. Beneficial and detrimental effects of dietary condensed tannins for sustainable sheep and goat production-Progress and challenges. Anim. Feed Sci. Technol. 2008, 147, 116–139. [Google Scholar] [CrossRef]
- Landau, S.; Silanikove, N.; Nitsan, Z.; Barkai, D.; Baram, H.; Provenza, F.D.; Perevolotsky, A. Short-term changes in eating patterns explain the effects of condensed tannins on feed intake in heifers. Appl. Anim. Behav. Sci. 2000, 69, 199–213. [Google Scholar] [CrossRef]
- Kumar, R.; Singh, M. Tannins: Their adverse role in ruminant nutrition. J. Agric. Food Chem. 1984, 32, 447–453. [Google Scholar] [CrossRef]
- Yisehak, K.; De Boever, J.L.; Janssens, G.P.J. The effect of supplementing leaves of four tannin-rich plant species with polyethylene glycol on digestibility and zootechnical performance of zebu bulls ( Bosindicus). J. Anim. Physiol. Anim. Nutr. 2014, 98, 417–423. [Google Scholar] [CrossRef] [PubMed]
- Bhatta, R.; Uyeno, Y.; Tajima, K.; Takenaka, A.; Yabumoto, Y.; Nonaka, I.; Enishi, O.; Kurihara, M. Difference in the nature of tannins on in vitro ruminal methane and volatile fatty acid production and on methanogenic archaea and protozoal populations. J. Dairy Sci. 2009, 92, 5512–5522. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Fagundes, G.M.; Benetel, G.; Carriero, M.M.; Sousa, R.L.M.; Muir, J.P.; Macedo, R.O.; Bueno, I.C.S. Tannin-rich forage as a methane mitigation strategy for cattle and the implications for rumen microbiota. Anim. Prod. Sci. 2020, 12. [Google Scholar] [CrossRef]
- Mkhize, N.R.; Heitkonig, I.M.A.; Scogings, P.F.; Dziba, L.E.; Prins, H.H.T.; de Boer, W.F. Effects of condensed tannins on live weight, faecal nitrogen and blood metabolites of free-ranging female goats in a semi-arid African savanna. Small Rumin. Res. 2018, 166, 28–34. [Google Scholar] [CrossRef]
- Yan, T.; Frost, J.P.; Keady, T.W.J.; Agnew, R.E.; Mayne, C.S. Prediction of nitrogen excretion in feces and urine of beef cattle offered diets containing grass silage. J. Anim. Sci. 2007, 85, 1982–1989. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Cochran, R.C.; Galyean, M.L. Measurement of in vivo forage digestion by ruminants. In Forage Quality, Evaluation, and Utilization; Wiley: Hoboken, NJ, USA, 1994. [Google Scholar] [CrossRef]
- Coates, D.B.; Dixon, R.M. Developing robust faecal near infrared spectroscopy calibrations to predict diet dry matter digestibility in cattle consuming tropical forages. J. Near Infrared Spectrosc. 2011, 19, 507–519. [Google Scholar] [CrossRef]
- Durmic, Z.; Ramírez-Restrepo, C.A.; Gardiner, C.; O’Neill, C.J.; Hussein, E.; Vercoe, P.E. Differences in the nutrient concentrations, in vitro methanogenic potential and other fermentative traits of tropical grasses and legumes for beef production systems in northern Australia. J. Sci. Food Agric. 2017, 97, 4075–4086. [Google Scholar] [CrossRef]
- AOAC. Official Methods of Analysis, 17th ed.; Association of Official Analytical Chemist: Arlington, VA, USA, 2000. [Google Scholar]
- Van Soest, P.J. Nutritional Ecology of the Ruminant; Cornell University Press: Ithaca, NY, USA, 1994. [Google Scholar]
- Clarke, T.; Flinn, P.C.; McGowan, A.A. Low-cost pepsin-cellulase assays for prediction of digestibility of herbage. Grass Forage Sci. 1982, 37, 147–150. [Google Scholar] [CrossRef]
- Coates, D. Improving Reliability of Faecal NIRS Calibration Equations; Meat & Livestock Australia Limited: Sydney, Australia, 2004; Volume 121. [Google Scholar]
- Coates, D.B.; Dixon, R.M. Development of near infrared analysis of faeces to estimate non-grass proportions in diets selected by cattle grazing tropical pastures. J. Near Infrared Spectrosc. 2007, 16, 471–480. [Google Scholar] [CrossRef]
- Gagen, E.J.; Wang, J.; Padmanabha, J.; Liu, J.; de Carvalho, I.P.C.; Liu, J.; Webb, R.I.; Al Jassim, R.; Morrison, M.; Denman, S.E.; et al. Investigation of a new acetogen isolated from an enrichment of the tammar wallaby forestomach. BMC Microbiol. 2014, 14, 314. [Google Scholar] [CrossRef] [Green Version]
- Chaney, A.L.; Marbach, E.P. Modified reagents for determination of urea and ammonia. Clin. Chem. 1962, 8, 130–132. [Google Scholar] [CrossRef]
- Wickham, H.; Francois, R.; Henry, L.; Muller, K.; RStudio. Dplyr: A Grammar of Data Manipulation. Available online: https://CRAN.R-project.org/package=dplyr (accessed on 7 May 2021).
- Pinheiro, J.; Bates, D.; DebRoy, S.; Sarkar, D.; R Core Team. nlme: Linear and Nonlinear Mixed Effects Models. Available online: https://CRAN.R-project.org/package=nlme (accessed on 7 May 2021).
- Bates, D.; Machler, M.; Bolker, B.M.; Walker, S.C. Fitting linear mixed-effects models using lme4. J. Stat. Softw. 2015, 67, 1–48. [Google Scholar] [CrossRef]
- Fox, J.; Weisberg, S.A. R Companion to Applied Regression, 3rd ed.; Sage Publications Inc.: Thousand Oaks, CA, USA, 2019. [Google Scholar]
- Hothorn, T.; Bretz, F.; Westfall, P. Simultaneous inference in general parametric models. Biom. J. 2008, 50, 346–363. [Google Scholar] [CrossRef] [Green Version]
Variable | Rhodes Grass | Lucerne | JCU2 (D. virgatus) | JCU4 (D. bicornutus) | JCU7 (D. leptophyllus) | Desmanthus spp. 2 |
---|---|---|---|---|---|---|
DM (%) | 84.0 ± 0.94 | 84.0 ± 1.16 | 32.3 ± 1.61 | 30.7 ± 1.26 | 34.2 ± 0.93 | 32.3 ± 0.78 |
CP (% DM) | 8.8 ± 0.19 | 15.1 ± 0.61 | 10.3 ± 0.99 | 13.0 ± 0.85 | 10.6 ± 0.80 | 11.3 ± 3.65 |
ADF (% DM) | 42.8 ± 0.43 | 37.5 ± 0.73 | 44.5 ± 1.33 | 40.4 ± 1.10 | 43.4 ± 1.00 | 42.8 ± 0.70 |
NDF (% DM) | 73.8 ± 0.41 | 49.6 ± 0.79 | 57.5 ± 1.38 | 53.1 ± 1.34 | 58.5 ± 1.20 | 56.4 ± 0.81 |
DMD (%) | 50.6 ± 0.56 | 65.2 ± 1.08 | 47.8 ± 2.57 | 51.7 ± 1.55 | 49.4 ± 1.41 | 49.6 ± 0.011 |
ME (MJ/kg DM) 1 | 7.0 ± 0.10 | 9.5 ± 0.19 | 6.5 ± 0.44 | 7.2 ± 0.27 | 6.8 ± 0.24 | 7.4 ± 0.19 |
Variable | Rhodes Grass | Lucerne | JCU2 (D. virgatus) | JCU4 (D. bicornutus) | JCU7 (D. leptophyllus) | Desmanthus spp. 2 | p-Value | ||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Wet Chemistry | NIRS | Wet Chemistry | NIRS | Wet Chemistry | NIRS | Wet Chemistry | NIRS | Wet Chemistry | NIRS | r between NIR and Wet Chemistry Values | |||
CP (% DM) | 9.8 | 9.0 | 17.0 | 16.6 | 19.6 | 13.8 | 17.4 | 16.7 | 14.3 | 7.5 | 17.1 | 0.71 | 0.18 |
ADF (% DM) | 40.0 | 44.0 | 35.3 | 36.3 | 21.9 | 39.7 | 30.9 | 35.9 | 30.5 | 46.7 | 27.8 | 0.14 | 0.82 |
NDF (% DM) | 72.7 | 74.7 | 47.4 | 48.5 | 33.0 | 47.3 | 43.5 | 49.8 | 45.8 | 61.8 | 40.8 | 0.89 | 0.04 |
DMD (%) | 45.3 | 48.4 | 58.8 | 70.0 | 50.1 | 60.6 | 41.8 | 59.0 | 43.2 | 48.3 | 45.1 | 0.79 | 0.11 |
ME (MJ/kg DM) 1 | 6.1 | 6.6 | 8.4 | 10.3 | 6.9 | 8.7 | 5.5 | 8.4 | 5.8 | 6.6 | 7.9 | 0.79 | 0.11 |
Variable | Lucerne | JCU2 | JCU4 | JCU7 | Desmanthus spp. 2 | SEM | p-Value |
---|---|---|---|---|---|---|---|
CP (% DM) | 10.2 | 9.2 | 10.1 | 9.4 | 9.6 | 0.17 | 0.08 |
ADF (% DM) | 41.3 a | 41.9 b | 41.9 b | 42.8 b | 42.6 | 0.62 | 0.01 |
NDF (% DM) | 68.4 | 68.7 | 67.2 | 68.8 | 68.3 | 0.74 | 0.13 |
ME (MJ/kg DM) 1 | 7.6 a | 7.1 b | 7.1 b | 7.0 b | 7.0 | 0.06 | 0.01 |
Variable | Lucerne | Desmanthus spp. | SEM | p-Value |
---|---|---|---|---|
Initial DMI (kg/day) | 5.5 | 5.4 | 0.12 | 0.67 |
Final DMI (kg/day) | 6.5 | 6.1 | 0.14 | 0.03 |
Initial LW (kg) | 270.7 | 275.0 | 0.04 | 0.95 |
Final LW (kg) | 320.0 | 303.4 | 0.03 | 0.04 |
Daily LW gain (kg/day) | 0.6 | 0.34 | 0.04 | 0.01 |
DMI/kg LW (%) | 2.0 | 2.0 | 0.03 | 0.98 |
Feed conversion ratio | 10.6 | 22.9 | 4.70 | 0.19 |
Variable | Lucerne | JCU2 | JCU4 | JCU7 | Desmanthus spp. | SEM | p-Value |
---|---|---|---|---|---|---|---|
Rumen volatile fatty acids | |||||||
Total VFA (mg/100 dL) | 65.2 a | 60.2 ab | 57.0 ab | 51.5 b | 56.4 | 1.64 | 0.01 |
Acetate (molar %) | 75.4 | 76.5 | 75.9 | 76.8 | 76.4 | 0.27 | 0.17 |
Propionate (molar %) | 14.5 | 13.9 | 14.5 | 14.0 | 14.2 | 0.15 | 0.34 |
Acetate/propionate ratio | 5.2 | 5.5 | 5.3 | 5.5 | 5.4 | 0.08 | 0.34 |
Iso-Butyrate (molar %) | 0.97 a | 0.81 ab | 0.76 b | 0.80 b | 0.79 | 0.02 | 0.01 |
n-Butyrate (molar %) | 7.0 | 6.8 | 6.9 | 6.6 | 6.8 | 0.13 | 0.63 |
Iso-Valerate (molar %) | 1.0 a | 0.87 ab | 0.83 b | 0.86 ab | 0.85 | 0.02 | 0.02 |
n-Valerate (molar %) | 0.95 | 0.89 | 0.93 | 0.81 | 0.88 | 0.04 | 0.65 |
n-Caproate (molar %) | 0.15 | 0.16 | 0.17 | 0.17 | 0.17 | 0.01 | 0.87 |
pH | 7.0 | 7.0 | 7.1 | 7.2 | 7.1 | 0.03 | 0.10 |
Plasma metabolites | |||||||
Glucose (mmol/L) | 4.2 | 4.1 | 4.2 | 4.1 | 4.1 | 0.05 | 0.08 |
NEFA (mmol/L) | 0.053 a | 0.074 ab | 0.11 b | 0.081 ab | 0.088 | 0.01 | 0.01 |
Cortisol (nmol/L) | 28.0 | 30.3 | 23.7 | 27.6 | 24.3 | 3.39 | 0.97 |
Variable | Lucerne | JCU2 | JCU4 | JCU7 | Desmanthus spp. 2 | SEM | p-Value |
---|---|---|---|---|---|---|---|
Diet N (% DM) | 1.6 | 1.5 | 1.6 | 1.5 | 1.5 | 0.03 | 0.30 |
Diet N by F.NIRS (% DM) | 2.4 a | 2.2 b | 2.2 b | 2.2 b | 2.2 | 0.04 | 0.01 |
N intake (g/day) | 111.8 a | 92.8 b | 101.7 ab | 92.0 b | 95.8 | 2.77 | 0.01 |
Rumen NH3-N (mg/dL) | 17.6 | 15.5 | 16.4 | 15.6 | 15.8 | 0.46 | 0.32 |
Plasma urea (mmol/L) | 5.3 | 5.4 | 5.6 | 5.5 | 5.5 | 0.16 | 0.96 |
Fecal N (% DM) | 1.8 a | 1.9 b | 2.0 b | 2.1 c | 2.0 | 0.03 | 0.01 |
Urinary N (g/day) 1 | 59.3 | 58.5 | 59.3 | 60.0 | 59.3 | 1.92 | 0.64 |
Variable | Desmanthus spp. | SEM | p-Value | |
---|---|---|---|---|
No PEG | PEG | |||
Animal performance | ||||
DMI (kg/day) | 5.6 | 6.2 | 0.21 | 0.20 |
Rumen volatile fatty acids | ||||
Total VFA (mg/100 dL) | 37.7 | 40.9 | 3.60 | 0.69 |
Acetate (molar %) | 80.1 | 77.9 | 0.50 | 0.06 |
Propionate (molar %) | 12.2 | 13.0 | 0.28 | 0.23 |
Acetate/propionate ratio | 6.6 | 6.0 | 0.18 | 0.17 |
Iso-Butyrate (molar %) | 0.63 | 0.92 | 0.05 | 0.01 |
n-Butyrate (molar %) | 5.4 | 6.0 | 0.16 | 0.18 |
Iso-Valerate (molar %) | 0.7 | 1.0 | 0.06 | 0.01 |
n-Valerate (molar %) | 0.84 | 0.98 | 0.04 | 0.04 |
n-Caproate (molar %) | 0.14 | 0.16 | 0.01 | 0.54 |
pH | 7.0 | 7.3 | 0.08 | 0.11 |
Plasma metabolites | ||||
Glucose (mmol/L) | 4.2 | 4.4 | 0.11 | 0.43 |
NEFA (mmol/L) | 0.12 | 0.12 | 0.02 | 0.99 |
Cortisol (nmol/L) | 25.9 | 22.2 | 5.12 | 0.73 |
Nitrogen concentrations | ||||
Diet N (% DM) | 1.5 | 1.6 | 0.05 | 0.36 |
Diet N by F.NIRS (% DM) | 2.1 | 2.2 | 0.05 | 0.98 |
N intake (g/day) | 99.3 | 108.0 | 6.48 | 0.51 |
Rumen NH3-N (mg/dL) | 15.6 | 15.5 | 1.27 | 0.95 |
Plasma urea (mmol/L) | 5.6 | 6.1 | 0.28 | 0.43 |
Fecal N (% DM) | 2.1 | 2.2 | 0.05 | 0.05 |
Urinary N (g/day) 1 | 62.6 | 73.4 | 4.36 | 0.35 |
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Suybeng, B.; Charmley, E.; Gardiner, C.P.; Malau-Aduli, B.S.; Malau-Aduli, A.E.O. Plasma Metabolites, Productive Performance and Rumen Volatile Fatty Acid Profiles of Northern Australian Bos indicus Steers Supplemented with Desmanthus and Lucerne. Metabolites 2021, 11, 356. https://doi.org/10.3390/metabo11060356
Suybeng B, Charmley E, Gardiner CP, Malau-Aduli BS, Malau-Aduli AEO. Plasma Metabolites, Productive Performance and Rumen Volatile Fatty Acid Profiles of Northern Australian Bos indicus Steers Supplemented with Desmanthus and Lucerne. Metabolites. 2021; 11(6):356. https://doi.org/10.3390/metabo11060356
Chicago/Turabian StyleSuybeng, Bénédicte, Edward Charmley, Christopher P. Gardiner, Bunmi S. Malau-Aduli, and Aduli E. O. Malau-Aduli. 2021. "Plasma Metabolites, Productive Performance and Rumen Volatile Fatty Acid Profiles of Northern Australian Bos indicus Steers Supplemented with Desmanthus and Lucerne" Metabolites 11, no. 6: 356. https://doi.org/10.3390/metabo11060356
APA StyleSuybeng, B., Charmley, E., Gardiner, C. P., Malau-Aduli, B. S., & Malau-Aduli, A. E. O. (2021). Plasma Metabolites, Productive Performance and Rumen Volatile Fatty Acid Profiles of Northern Australian Bos indicus Steers Supplemented with Desmanthus and Lucerne. Metabolites, 11(6), 356. https://doi.org/10.3390/metabo11060356