Indian Journal of Animal Nutrition
  • Year: 1996
  • Volume: 13
  • Issue: 4

Comparative Study of Rumen Degradability of Protein by In Situ and In Vitro (Protease) Techniques

  • Author:
  • T. M. Prabhu, Farooq Mohammed, U. Krishanamoorthy, K. Chandrapal Singh
  • Total Page Count: 7
  • Page Number: 190 to 196

*Department of Livestock Production and Management, Veterinary College, Bangalore-560 024, India.

Department of Animal Nutrition, Veterinary College, University of Agricultural Sciences, Bangalore-560 024, India.

Online published on 29 December, 2011.

Abstract

The possibility of using protease and buffer soluble nitrogen values, to predict the rumen degradahle nitrogen (RDN) has been tested. Five protein feedstuff's (Standards) were chosen to establish the relationship of N degradability obtained by in situ method, with those obtained by in vitro buffer (IVB) and in vitro protease (IVP, 1h and 18h) methods. The application of this relationship to predict in situ RON was tested using feedstuf’’s similar to the standards, but from different source and feedstuffs not belonging to the group of standards. The relationship of in situ RDN (Y) with those of IVB (X) and IVP-1h (X2) and 18h (X3) was Y = 62.1417 + 0.4025 X1 (r = 0.78 ±0.11, P ≤ 0.01), Y = 43.0127 + 0.6003 X2 (r = 0.89 ±0.01, P ≤ 0.01) and Y = 20. 9442 + 0.7366 X (r = 0.88 ±0.01, P ≤ 0.01), respectively. The buffer soluble and lh protease soluble N values of test feeds were significantly different (P<0.05) from in situ RDN values whereas, the difference between 18h protease soluble N and in situ RDN was not significant. The RDN was predicted in test feeds from the regression equations developed with standard samples. The differences between in situ RDN values and those predicted from IVB and IVP-1h methods were non-significant. It was concluded that the IVP-18h procedure can be used as an alternative to the in situ method of estimating degradability of N. Further reasonably good estimates of RDN can also be obtained from IVB and IVP-lh methods using prediction equations.