Towards smart dairy nutrition: Improving sustainability and economics of dairy production

https://doi.org/10.17221/16/2020-CJASCitation:Schönleben M., Mentschel J., Střelec L. (2020): Towards smart dairy nutrition: Improving sustainability and economics of dairy production. Czech J. Anim. Sci., 65: 153-161.
download PDF

Tosatisfy increasing food and nutrient supply requirements forour growing future human population, farmers and staple food producers carry vital responsibilities. Especially farmers with ruminant livestock like dairy cows transform otherwise forhuman consumption unsuitable fibre into highly nutritious milk and meat. Nevertheless, dairy farmers are challenged increasingly bythe consequences of global warming. Economic risks like feed supply and volatile commodity prices need tobe balanced, also taking into account theincreasing environmental awareness of end-customers. Focusing just onemissions, dairy production is contributing anessential part of thetotal carbon footprint emitted bythe agricultural sector. Since rumen degradability of feed was identified bythe Food and Agriculture Organization of theUnited Nations as one of themost influential parameters inreducing thecarbon footprint of dairy farming, thedesire toexploit leverage potential forefficiency increases can be considered exceptionally high. Although thepositive effects of improved feed, inother words, neutral detergent fibre rumen degradability fordairy farming are well understood, detailed information onthe correct management toobtain well digestible feed sources is still missing. Using thesmart dairy nutrition ration formulation concept, applying readily on-farm available digitized data and management information theobjectives of this study were: 1) toassess theinfluential parameters which govern neutral detergent fibre rumen degradability of corn silage, using aset of 584 corn silages from multiple years, and 2) toevaluate within anintegrated dairy production set up theeconomic and ecological improvement potential byfeeding asubset of 28 different corn silages, including detailed variety information. Results show that theneutral detergent fibre rumen degradability is primarily governed byvariety choice and can be four times more important than thecorrect harvest stage decision. Byfeeding corn silage varieties with high neutral detergent fibre rumen degradability, monetary income could be increased by~10% while simultaneously reducing manure accumulation.

References:
Allen MR, Shine KP, Fuglestvedt JS, Millar RJ, Cain M, Frame DJ, Macey AH. A solution to the misrepresentations of CO2-equivalent emissions of short-lived climate pollutants under ambitious mitigation. Clim Atmos Sci 2018 Jun 4;1(16):1-8. https://doi.org/10.1038/s41612-018-0026-8
 
Britt JH, Cushman RA, Dechow CD, Dobson H, Humblot H, Hutjens MF, Jones GA, Ruegg PS, Sheldon IM, Stevenson JS. Invited review: Learning from the future – A vision for dairy farms and cows in 2067. J Dairy Sci. 2018 May;101(5):3722-41. https://doi.org/10.3168/jds.2017-14025
 
FAO – Food and Agriculture Organization of the United Nations. Greenhouse gas emissions from the dairy sector: A life cycle assessment. Rome, Italy: FAO Animal Production and Health Division; 2010. 98 p.
 
Fox DG, Tedeschi L, Tylutki TP, Van Amburgh M. The net carbohydrate and protein system for evaluating herd nutrition and nutrient excretion: Model documentation. Anim Feed Sci Technol. 2004 Feb;112(1-4):29-78. https://doi.org/10.1016/j.anifeedsci.2003.10.006
 
Gerber P, Vellinga T, Opio C, Steinfeld H. Productivity gains and greenhouse gas emissions intensity in dairy systems. Livest Sci. 2011 Jul;139(1):100-8. https://doi.org/10.1016/j.livsci.2011.03.012
 
Hutjens MF. Feeding guide. Hoard´s dairyman. Fort Atkinson, WI: W.D. Hoard & Sons; 2018. 103 p.
 
Jung HJ, Samac DA, Sarath G. Modifying crops to increase cell wall digestibility. Plant Sci. 2012 Apr 1;185:65-77. https://doi.org/10.1016/j.plantsci.2011.10.014
 
Kaloxylos A, Eigenmann R, Teye F, Politopoulou Z, Wolfert S, Shrank C, Dillinger M, Lampropoulou I, Antoniou E, Pesonen L, Huether N, Floerchinger T, Alonistioti N, Kormentzas G. Farm management systems and the future internet era. Comput Electron Agric. 2012 Nov;89:130-44. https://doi.org/10.1016/j.compag.2012.09.002
 
Marton CL, Kalman L, Arendas T, Bonis P, Szieberth D. Comparison of some methods for estimating vegetation periods in maize. Acta Agron Hung. 2007 Mar 1;55(1):1-5. https://doi.org/10.1556/AAgr.55.2007.1.1
 
Masoero G, Sala G, Peiretti G. Development of near infrared (NIR) spectroscopy and electronic nose (EN) techniques to analyse the conservation quality of farm silages. J Food Agric Environ. 2007 Jan 5(1):172-7.
 
NRC – National Research Council. Nutrient requirements of dairy cattle. 7th ed. Washington, DC, USA: National Academies Press; 2001. 408 p.
 
Oba M, Allen MS. Evaluation of the importance of the digestibility of neutral detergent fiber from forage: Effects on dry matter intake and milk yield of dairy cows. J Dairy Sci. 1999 Mar;82(3):589-96. https://doi.org/10.3168/jds.S0022-0302(99)75271-9
 
Overton TR, Van Amburgh ME, Chase LE. Understanding CNCPS and CPM: Biology, modeling, and “best cost” applications for balancing the nutrient requirements in dairy diets. Penn State Dairy Nutrition Workshop. Cornell University; 2010. 44 p.
 
R Core Team. R: A language and environment for statistical computing [Internet]. Vienna, Austria: R Foundation for Statistical Computing. 2018 [cited 2020 Jan 18]. Available from http://www.R-project.org/.
 
Raffrenato E, Ross DA, Van Amburgh ME. Development of an in vitro method to determine rumen undigested aNDFom for use in feed evaluation. J Dairy Sci. 2018 Nov;110(11):9888-900. https://doi.org/10.3168/jds.2018-15101
 
Roach B, Harris JM, Codur AM. Microeconomics and the environment [Internet]. Global Development and Environment Institute, Tufts University. 2015 [cited 2019 Dec 20]. Available from http://ase.tufts.edu/gdae.
 
Russell J. Rumen microbiology and its role in ruminant nutrition. New York: Cornell University; 2002. 121 p.
 
Smedman A, Lindmark-Mansson H, Drewnowski A, Modin Edman AK. Nutrient density of beverages in relation to climate impact. Food Nutr Res. 2010 Aug 23;(54):5170-8. https://doi.org/10.3402/fnr.v54i0.5170
 
United Nations. World population prospects: The 2017 revision, key findings and advance. New York: United Nations; 2017. 24 p.
 
Van Amburgh ME, Collao-Saenz EA, Higgs RJ, Ross DA, Recktenwald EB, Raffrenato E, Chase LE, Overton TR, Mills JK, Foskolos A. The Cornell net carbohydrate and protein system: Updates to the model and evaluation of version 6.5. J Dairy Sci. 2015 Sep;98(9):6361-80. https://doi.org/10.3168/jds.2015-9378
 
Van Soest PJ, Robertson JB, Lewis BA. Methods for dietary fiber, neutral detergent fiber, and nonstarch polysaccharides in relation to animal nutrition. J Dairy Sci. 1991 Oct;74(10):3583-97. https://doi.org/10.3168/jds.S0022-0302(91)78551-2
 
VandeHaar MJ, St-Pierre N. Major advances in nutrition: Relevance to the sustainability of the dairy industry. J Dairy Sci. 2006 Apr;89(4):1280-91. https://doi.org/10.3168/jds.S0022-0302(06)72196-8
 
Wiersma EW, Carter PR, Albrecht KA, Coors JG. Kernel milkline stage and corn forage yield, quality, and dry matter content. J Prod Agric. 1993 Jan 1;6(1):94-9. https://doi.org/10.2134/jpa1993.0094
 
Wilson JR, Mertens DR. Cell wall accessibility and cell structure limitations to microbial digestion of forage. Crop Sci. 1995 Jan 1;35(1):251-9. https://doi.org/10.2135/cropsci1995.0011183X003500010046x
 
download PDF

© 2020 Czech Academy of Agricultural Sciences | Prohlášení o přístupnosti