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Current IssueEditorial BoardOnline First ArticlesArchive

Research Article

volume 53 issue 2 (february 2019) : 227-231,   Doi: 10.18805/ijar.B-868

Effects of CPM model software on diet energy and nitrogen diagnosis, and lactating performance of dairy cows

Y
Y. Chen
Y
Y. L. Qu
J
J. Bao
L
L. C. Liu
L
L. Zhen
1College of Animal Science and Veterinary Medicine, Heilongjiang Bayi Agricultural University, Daqing, China.
Cite article:- Chen Y., Qu L. Y., Bao J., Liu C. L., Zhen L. (2018). Effects of CPM model software on diet energy and nitrogen diagnosis, and lactating performance of dairy cows. Indian Journal of Animal Research. 53(2): 227-231. doi: 10.18805/ijar.B-868.

ABSTRACT

ne hundred twelve China Holstein cows with similar body weight and lactation stage were selected. The average daily milk yield of one half was 20.34±1.61kg and the other was 25.41±2.97kg. In each herd, the cows were randomly assigned to two groups. The control diets (I and II) were the original dairy farm diets, and the test diets (I and II) were the corresponding control diets adjusted by CPM-Dairy (Cornell-Penn-Miner Dairy System). The diagnosis for the two original diets showed the ME and MP balance were greater than the cow requirement. The rumen peptide balance also showed the same tendency. Both test diets had lower CP (%/DM) than the corresponding Control diet by 1.60% and 2.5%, respectively. However, both the RUPs (%/CP) were increased a little in the two test diets. The MP allowed daily milk yield of Control diet I was greater than the actual daily milk yield and ME allowed daily milk yield (P < 0.05), but they didn’t present significant difference in Test diet I (P > 0.05).

REFERENCES

  1. Allen, M. S., Bradford, B. J. and Harvatine. K. J. (2005). The cow as a model to study food intake regulation. Annual Review of Nutrition, 25:523-547.
  2. AOAC. (1980). Official Methods of Analysis. 13th Ed Washington, D C: association of Official Analytical Chemists.
  3. Cannas, A., Tedeschi, L. O., Fox, D. G., Pell, A. N. and Van Soest. P. J. (2004). A mechanistic model for predicting the nutrient requirements and feed biological values for sheep. Journal of Animal Science, 82:149-169.
  4. Fernando, S. C., Purvis II, H. T., Najar, F. Z., Sukharnikov, L. O., Krehbiel, C. R., Nagaraja, T. G., Roe, B. A. and U. DeSilva. (2010). Rumen microbial population dynamics during adaptation to a high-grain diet. Applied and Environmental Microbiology, 76:7482-7490.
  5. Fox D. G., Barry, M. C., Pitt, R. E., Roseler, D. K. and Stone. W. C. (1995). Application of the Cornell net carbohydrate and protein model for cattle consuming forage. Journal of Animal Science, 73:267-277.
  6. Godden, S. M., Lissemore, K. D., Kelton, D. F., Leslie, K. E., Walton, J. S. and Lumsden. J. H. (2001). Relationships between milk urea concentrations and nutritional management, production, and economic variables in Ontario dairy herds. Journal of Dairy Science, 84:1128-1139.
  7. Higgs, R. J., Chase, L. E. and Van Amburgh. M. E. (2012). Development and evaluation of equations in the Cornell Net Carbohydrate and Protein System to predict nitrogen excretion in lactating dairy cows. Journal of Dairy Science, 95:2004-2014.
  8. Kolver, E. S., Muller, L. D., Barry, M. C. and Penno. J. W. (1998). Evaluation and application of the Cornell Net Carbohydrate and Protein System for dairy cows fed diets based on pasture. Journal of Dairy Science, 81:2029-2039.
  9. Krizsan, S. J., Sairanen, A., Höjer, A. and Huhtanen. P. (2014). Evaluation of different feed intake models for dairy cows. Journal of Dairy Science, 97:2387-2397.
  10. Lanzas C., Tedeschi, L. O., Seo, S. and Fox. D. G. (2007). Evaluation of protein fractionation systems used in formulating rations for dairy cattle. Journal of Animal Science, 90:507-521.
  11. Maji, S., Meena, B. S., Paul, P., and Rudroju, V. (2017). Prospect of organic dairy farming in India: A review. Asian Journal of Dairy and Food Research, 36:1-8.
  12. Milligan, R. A., Chase, L. E., Sniffenand, C. J. and Knoblanch. W. A. (1981). Least-cost ration balanced dairy rations: A computer program user’s manual. Animal Science Mimeograph Series, 54.
  13. Moore, D. A. and Varga. G. (1996). BUN and MUN: Urea nitrogen testing in dairy cattle. The Compendium on Continuing Education for the Practicing Veterinarian, 18:712-721.
  14. Pacheco, D., Patton, R. A., Parys, C. and Lapierre. H. (2012). Ability of commercially available dairy ration programs to predict duodenal flows of protein and essential amino acids in dairy cows. Journal of Dairy Science, 95:937-963.
  15. Pell, A. N. (1992). Does ration balancing affect nutrient management? Project of Cornell Nutrition Conference, 23-31.
  16. Sairanen, A., Khalili, H., Nousiainen, J. I., Ahvenjärvi, S. and Huhtanen. P. (2005). The effect of concentrate supplementation on nutrient flow to the omasum in dairy cows receiving freshly cut grass. Journal of Dairy Science, 88:1443-1453.
  17. Sniffen, C. J., O’connor, J. D., Van Soest, P. J., Fox, D. G. and Russell. J. B. (1992). A net carbohydrate and protein system for evaluating cattle diets II: Carbohydrate and protein availability. Journal of Animal Science, 70:3562-3577.
  18. Shen, J. S., Song, L. J., Sun, H. Z., Wang, B., Chai, Z., Chacher, B. and Liu. J. X. (2015). Effects of corn and soybean meal types on rumen fermentation, nitrogen metabolism and productivity in dairy cows. Asian-Australasian Journal of Animal Sciences, 28:351-359.
  19. Stádník L, Atasever S. (2017) Influence of somatic cell count and body condition score on reproduction traits and milk composition of Czech Holstein cows. Indian Journal of Animal Research, 51:771-776.
  20. Tedeschi, L. O., Chalupa, W., Janczewski, E., Fox, D. G., Sniffen, C., Munson, R. and Boston. R. (2008). Evaluation and application of the CPM Dairy nutrition model. Journal of Agricultural Sciences, 146:171-182.
  21. Vafa, T., Naserian, A. A., Heravi Moussavi, A., Valizadeh, R., Danesh Mesgaran, M., and Khorashadizadeh, M. (2010). Effects of different levels of fish oil and canola oil on productive performance of Holstein dairy cows. Indian Journal of Animal Research, 44:79-86.
  22. Van Soest P. J., Sniffen, C. J. and Mertens. D. R. (1981). A net protein system for cattle: The rumen submodel for nitrogen. P. 265. In: Owens F N ed. MP-109. Protein Requirements for Cattle: Proceedings of an International Symposium. Oklahoma State University.
  23. Wright, T. C., Moscardini, S., Luimes, P. H., Susmel, P. and B. W. McBride. (1998). Effects of rumen-undegradable protein and feed intake on nitrogen balance and milk protein production in dairy cows. Journal of Dairy Science, 81:784-793. 
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    Research Article

    volume 53 issue 2 (february 2019) : 227-231,   Doi: 10.18805/ijar.B-868

    Effects of CPM model software on diet energy and nitrogen diagnosis, and lactating performance of dairy cows

    Y
    Y. Chen
    Y
    Y. L. Qu
    J
    J. Bao
    L
    L. C. Liu
    L
    L. Zhen
    1College of Animal Science and Veterinary Medicine, Heilongjiang Bayi Agricultural University, Daqing, China.
    Cite article:- Chen Y., Qu L. Y., Bao J., Liu C. L., Zhen L. (2018). Effects of CPM model software on diet energy and nitrogen diagnosis, and lactating performance of dairy cows. Indian Journal of Animal Research. 53(2): 227-231. doi: 10.18805/ijar.B-868.

    ABSTRACT

    ne hundred twelve China Holstein cows with similar body weight and lactation stage were selected. The average daily milk yield of one half was 20.34±1.61kg and the other was 25.41±2.97kg. In each herd, the cows were randomly assigned to two groups. The control diets (I and II) were the original dairy farm diets, and the test diets (I and II) were the corresponding control diets adjusted by CPM-Dairy (Cornell-Penn-Miner Dairy System). The diagnosis for the two original diets showed the ME and MP balance were greater than the cow requirement. The rumen peptide balance also showed the same tendency. Both test diets had lower CP (%/DM) than the corresponding Control diet by 1.60% and 2.5%, respectively. However, both the RUPs (%/CP) were increased a little in the two test diets. The MP allowed daily milk yield of Control diet I was greater than the actual daily milk yield and ME allowed daily milk yield (P < 0.05), but they didn’t present significant difference in Test diet I (P > 0.05).

    REFERENCES

    1. Allen, M. S., Bradford, B. J. and Harvatine. K. J. (2005). The cow as a model to study food intake regulation. Annual Review of Nutrition, 25:523-547.
    2. AOAC. (1980). Official Methods of Analysis. 13th Ed Washington, D C: association of Official Analytical Chemists.
    3. Cannas, A., Tedeschi, L. O., Fox, D. G., Pell, A. N. and Van Soest. P. J. (2004). A mechanistic model for predicting the nutrient requirements and feed biological values for sheep. Journal of Animal Science, 82:149-169.
    4. Fernando, S. C., Purvis II, H. T., Najar, F. Z., Sukharnikov, L. O., Krehbiel, C. R., Nagaraja, T. G., Roe, B. A. and U. DeSilva. (2010). Rumen microbial population dynamics during adaptation to a high-grain diet. Applied and Environmental Microbiology, 76:7482-7490.
    5. Fox D. G., Barry, M. C., Pitt, R. E., Roseler, D. K. and Stone. W. C. (1995). Application of the Cornell net carbohydrate and protein model for cattle consuming forage. Journal of Animal Science, 73:267-277.
    6. Godden, S. M., Lissemore, K. D., Kelton, D. F., Leslie, K. E., Walton, J. S. and Lumsden. J. H. (2001). Relationships between milk urea concentrations and nutritional management, production, and economic variables in Ontario dairy herds. Journal of Dairy Science, 84:1128-1139.
    7. Higgs, R. J., Chase, L. E. and Van Amburgh. M. E. (2012). Development and evaluation of equations in the Cornell Net Carbohydrate and Protein System to predict nitrogen excretion in lactating dairy cows. Journal of Dairy Science, 95:2004-2014.
    8. Kolver, E. S., Muller, L. D., Barry, M. C. and Penno. J. W. (1998). Evaluation and application of the Cornell Net Carbohydrate and Protein System for dairy cows fed diets based on pasture. Journal of Dairy Science, 81:2029-2039.
    9. Krizsan, S. J., Sairanen, A., Höjer, A. and Huhtanen. P. (2014). Evaluation of different feed intake models for dairy cows. Journal of Dairy Science, 97:2387-2397.
    10. Lanzas C., Tedeschi, L. O., Seo, S. and Fox. D. G. (2007). Evaluation of protein fractionation systems used in formulating rations for dairy cattle. Journal of Animal Science, 90:507-521.
    11. Maji, S., Meena, B. S., Paul, P., and Rudroju, V. (2017). Prospect of organic dairy farming in India: A review. Asian Journal of Dairy and Food Research, 36:1-8.
    12. Milligan, R. A., Chase, L. E., Sniffenand, C. J. and Knoblanch. W. A. (1981). Least-cost ration balanced dairy rations: A computer program user’s manual. Animal Science Mimeograph Series, 54.
    13. Moore, D. A. and Varga. G. (1996). BUN and MUN: Urea nitrogen testing in dairy cattle. The Compendium on Continuing Education for the Practicing Veterinarian, 18:712-721.
    14. Pacheco, D., Patton, R. A., Parys, C. and Lapierre. H. (2012). Ability of commercially available dairy ration programs to predict duodenal flows of protein and essential amino acids in dairy cows. Journal of Dairy Science, 95:937-963.
    15. Pell, A. N. (1992). Does ration balancing affect nutrient management? Project of Cornell Nutrition Conference, 23-31.
    16. Sairanen, A., Khalili, H., Nousiainen, J. I., Ahvenjärvi, S. and Huhtanen. P. (2005). The effect of concentrate supplementation on nutrient flow to the omasum in dairy cows receiving freshly cut grass. Journal of Dairy Science, 88:1443-1453.
    17. Sniffen, C. J., O’connor, J. D., Van Soest, P. J., Fox, D. G. and Russell. J. B. (1992). A net carbohydrate and protein system for evaluating cattle diets II: Carbohydrate and protein availability. Journal of Animal Science, 70:3562-3577.
    18. Shen, J. S., Song, L. J., Sun, H. Z., Wang, B., Chai, Z., Chacher, B. and Liu. J. X. (2015). Effects of corn and soybean meal types on rumen fermentation, nitrogen metabolism and productivity in dairy cows. Asian-Australasian Journal of Animal Sciences, 28:351-359.
    19. Stádník L, Atasever S. (2017) Influence of somatic cell count and body condition score on reproduction traits and milk composition of Czech Holstein cows. Indian Journal of Animal Research, 51:771-776.
    20. Tedeschi, L. O., Chalupa, W., Janczewski, E., Fox, D. G., Sniffen, C., Munson, R. and Boston. R. (2008). Evaluation and application of the CPM Dairy nutrition model. Journal of Agricultural Sciences, 146:171-182.
    21. Vafa, T., Naserian, A. A., Heravi Moussavi, A., Valizadeh, R., Danesh Mesgaran, M., and Khorashadizadeh, M. (2010). Effects of different levels of fish oil and canola oil on productive performance of Holstein dairy cows. Indian Journal of Animal Research, 44:79-86.
    22. Van Soest P. J., Sniffen, C. J. and Mertens. D. R. (1981). A net protein system for cattle: The rumen submodel for nitrogen. P. 265. In: Owens F N ed. MP-109. Protein Requirements for Cattle: Proceedings of an International Symposium. Oklahoma State University.
    23. Wright, T. C., Moscardini, S., Luimes, P. H., Susmel, P. and B. W. McBride. (1998). Effects of rumen-undegradable protein and feed intake on nitrogen balance and milk protein production in dairy cows. Journal of Dairy Science, 81:784-793. 
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