Animal Bioscience

  • 제34권10호
  • /
  • Pages.1623-1631
  • /
  • 2021
  • /
  • 2765-0189(pISSN)
  • /
  • 2765-0235(eISSN)
아세아태평양축산학회 (Asian Australasian Association of Animal Production Societies)
권호 표지
DOI QR코드

DOI QR Code

Evaluation of the equation for predicting dry matter intake of lactating dairy cows in the Korean feeding standards for dairy cattle

  • Lee, Mingyung (Division of Animal and Dairy Sciences, Chungnam National University) ;
  • Lee, Junsung (Division of Animal and Dairy Sciences, Chungnam National University) ;
  • Jeon, Seoyoung (Division of Animal and Dairy Sciences, Chungnam National University) ;
  • Park, Seong-Min (National Institute of Animal Science, Rural Development Administration) ;
  • Ki, Kwang-Seok (National Institute of Animal Science, Rural Development Administration) ;
  • Seo, Seongwon (Division of Animal and Dairy Sciences, Chungnam National University)
  • 투고 : 2020.09.28
  • 심사 : 2020.11.09
  • 발행 : 2021.10.01
PDF 다운로드
⟨ 이전 논문 다음 논문 ⟩

초록

Objective: This study aimed to validate and evaluate the dry matter (DM) intake prediction model of the Korean feeding standards for dairy cattle (KFSD). Methods: The KFSD DM intake (DMI) model was developed using a database containing the data from the Journal of Dairy Science from 2006 to 2011 (1,065 observations 287 studies). The development (458 observations from 103 studies) and evaluation databases (168 observations from 74 studies) were constructed from the database. The body weight (kg; BW), metabolic BW (BW0.75, MBW), 4% fat-corrected milk (FCM), forage as a percentage of dietary DM, and the dietary content of nutrients (% DM) were chosen as possible explanatory variables. A random coefficient model with the study as a random variable and a linear model without the random effect was used to select model variables and estimate parameters, respectively, during the model development. The best-fit equation was compared to published equations, and sensitivity analysis of the prediction equation was conducted. The KFSD model was also evaluated using in vivo feeding trial data. Results: The KFSD DMI equation is 4.103 (±2.994)+0.112 (±0.022)×MBW+0.284 (±0.020)×FCM-0.119 (±0.028)×neutral detergent fiber (NDF), explaining 47% of the variation in the evaluation dataset with no mean nor slope bias (p>0.05). The root mean square prediction error was 2.70 kg/d, best among the tested equations. The sensitivity analysis showed that the model is the most sensitive to FCM, followed by MBW and NDF. With the in vivo data, the KFSD equation showed slightly higher precision (R2 = 0.39) than the NRC equation (R2 = 0.37), with a mean bias of 1.19 kg and no slope bias (p>0.05). Conclusion: The KFSD DMI model is suitable for predicting the DMI of lactating dairy cows in practical situations in Korea.

키워드

과제정보

This research was supported by the Rural Development Administration, Republic of Korea (Project No. PJ0150482021).

참고문헌

  1. National Research Council. Nutrient requirements of dairy cattle. 8th rev. ed. Washington, DC, USA: National Academies Press; 2001.
  2. Roseler DK, Fox DG, Chase LE, Pell AN, Stone WC. Development and evaluation of equations for prediction of feed intake for lactating Holstein dairy cows. J Dairy Sci 1997;80:878-93. https://doi.org/10.3168/jds.S0022-0302(97)76010-7
  3. Rural Development Administration. Korean feeding standards for dairy cattle. 1st ed. Suwon, Korea: National Institute of Animal Science; 2002.
  4. Rural Development Administration. Korean feeding standards for dairy cattle. 1st rev. ed. Suwon, Korea: National Institute of Animal Science; 2007.
  5. Lee JS, Lee SY, Ki KS, Kim HS, Seo S. Changes in the parameter estimates for the linear relationships of milk and milk component yields with dry matter intake of dairy cows during the last decade. In: 2010 ADSA-ASAS Joint Meetings; 2010 July 11-15; Denver, CO, USA. p. 720.
  6. Rural Development Administration. Korean feeding standards for dairy cattle. 2nd rev. ed. Suwon, Korea: National Institute of Animal Science; 2012.
  7. Seo S, Tedeschi LO, Lanzas C, Schwab CG, Fox DG. Development and evaluation of empirical equations to predict feed passage rate in cattle. Anim Feed Sci Technol 2006;128:6783. https://doi.org/10.1016/j.anifeedsci.2005.09.014
  8. Allen MS. Effects of diet on short-term regulation of feed intake by lactating dairy cattle. J Dairy Sci 2000;83:1598624. https://doi.org/10.3168/jds.S0022-0302(00)75030-2
  9. Ministry of Agriculture, Food and Rural Affairs. 2011 DHI annual report in Korea. Goyang, Korea: Dairy Cattle Improvement Center; 2012.
  10. Fox DG, Tedeschi LO, Tylutki TP, et al. The Cornell Net Carbohydrate and Protein System model for evaluating herd nutrition and nutrient excretion. Anim Feed Sci Technol 2004;112:29-78. https://doi.org/10.1016/j.anifeedsci.2003.10.006
  11. National Agriculture and Food Research Organization. Japanese feeding standard for dairy cattle. Japan Livestock Industry Association, Tokyo, Japan: National Agriculture and Food Research Organization; 2006.
  12. Brown CA, Chandler PT, Holter JB. Development of predictive equations for milk yield and dry matter intake in lactating cows. J Dairy Sci 1977;60:1739-54. https://doi.org/10.3168/jds.S0022-0302(77)84098-8
  13. Fuentes-Pila J, Ibanez M, De Miguel JM, Beede DK. Predicting average feed intake of lactating Holstein cows fed totally mixed rations. J Dairy Sci 2003;86:309-23. https://doi.org/10.3168/jds.S0022-0302(03)73608-X
  14. Rayburn EB, Fox DG. Variation in neutral detergent fiber intake of Holstein cows. J Dairy Sci 1993;76:544-54. https://doi.org/10.3168/jds.S0022-0302(93)77374-9
  15. Cunniff P; AOAC International. Official methods of analysis. 16th ed. Arlington, VA, USA: AOAC International; 1995.
  16. 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;74:3583-97. https://doi.org/https://doi.org/10.3168/jds.S0022-0302(91)78551-2
  17. Plegge SD, Goodrich RD, Hanson SA, Kirick MA. Predicting dry matter intake of feedlot cattle. In: 45th Minnesota Nutrition Conference; 1984; St. Paul, MN, USA. p. 56-70.
  18. Carter RR, Grovum WL. Factors affecting the voluntary intake of food by sheep: 5. The inhibitory effect of hypertonicity in the rumen. Br J Nutr 1990;64:285-99. https://doi.org/10.1079/BJN19900029
  19. Mertens DR. Factors influencing feed intake in lactating cows: from theory to application using neutral detergent fiber. In: 46th Georgia Nutrition Conference; 1985; Athens, GA, USA: University of Georgia. pp. 1-18.
  20. Azevedo JAG, Valadares Filho SdC, Pina DdS, Chizzotti ML, Valadares RFD. A meta-analysis of dry matter intake in Nellore and Zebu-crosses cattle. Rev Bras Zootec 2010;39:1801-9. https://doi.org/10.1590/S1516-35982010000800024
  21. Van Soest PJ. Nutritional ecology of the ruminant. 2nd ed. Ithaca, NY, USA: Cornell University Press; 1994.
  22. Ferrell CL, Jenkins TG. Cow type and the nutritional environment: nutritional aspects. J Anim Sci 1985;61:725-41. https://doi.org/10.2527/jas1985.613725x
  23. Veerkamp RF. Selection for economic efficiency of dairy cattle using information on live weight and feed intake: a review. J Dairy Sci 1998;81:1109-19. https://doi.org/10.3168/jds.S0022-0302(98)75673-5
  24. Manzanilla-Pech CIV, Veerkamp RF, Tempelman RJ, et al. Genetic parameters between feed-intake-related traits and conformation in 2 separate dairy populations-the Netherlands and United States. J Dairy Sci 2016;99:443-57. https://doi.org/10.3168/jds.2015-9727
  25. Gaines WL. The energy basis of measuring milk yield in dairy cows. Urbana, IL, USA: University of Illinois Agricultural Experiment Station Bulletin; 1928. No. 308.
  26. Minson DJ. Forage in ruminant nutrition. San Diego, CA, USA: Academic Press, Inc.; 1990.
  27. Beauchemin KA, McAllister TA, Dong Y, Farr BI, Cheng KJ. Effects of mastication on digestion of whole cereal grains by cattle. J Anim Sci 1994;72:236-46. https://doi.org/10.2527/1994.721236x
  28. Mertens DR. Predicting intake and digestibility using mathematical models of ruminal function. J Anim Sci 1987;64:1548-58. https://doi.org/10.2527/jas1987.6451548x
  29. St-Pierre NR. Reassessment of biases in predicted nitrogen flows to the duodenum by NRC 2001. J Dairy Sci 2003;86:344-50. https://doi.org/10.3168/jds.S0022-0302(03)73612-1
  30. National Research Council. Effect of environment on nutrient requirements of domestic animals. Washington, DC, USA: National Academies Press; 1981.