AN IMPROVED ENZYMATIC METHOD BY ADDING GAMMANASE TO DETERMINE DIGESTIBILITY AND PREDICT ENERGY VALUE OF COMPOUND FEEDS AND RAW-MATERIALS FOR CATTLE

Because the current pepsin-cellulase method of De Boever et al. (1986) (Animal Feed Science and Technology, 1986, 14: 203-214) underestimates the digestibility of palm kernel cake, the procedure was adapted by using a cellulase mixture and adding gammanase. In a comparative test on 28 currently used raw materials, the modified method not only increased the digestibility of palm kernel cake (+13.7% units), but also that of soya bean hulls (+4.7%), whereas the other feeds were little affected. Further, new equations to predict metabolizable energy (ME) and net energy lactation (NEL) were derived for normal (n=61; ME 9.3-13.9; NEL 5.4-8.5 MJ kg(-1) DM) as well as for fibre rich (n=37; ME 3.8-12.7; NEL 1.9-7.6 MJ kg(-1) DM) compound feeds and raw materials. For normal concentrates, best multiple linear regressions based on the new enzymatic method (EN), the original pepsin-cellulase digestibility (CE) and on rumen fluid digestibility (RF) had similar residual standard deviations (RSD) of about 0.25 and 0.20 MJ kg(-1) DM for ME and NEL, respectively. For fibre-rich concentrates, the RSDs of RF equations were lower (ME 0.28; NEL 0.20 MJ kg(-1) DM) than those of EN equations (ME 0.43; NEL 0.28 MJ kg(-1) DM) and CE equations (ME 0.50; NEL 0.32 MJ kg(-1) DM). However, when validated, EN equations appeared more accurate than CE and RF equations and the use of tabular values; the ME of 28 mixed feeds was predicted with errors of 2.7%, 2.8%, 3.7% and 3.3%, respectively, whereas for 16 raw materials the errors amounted to 3.3%, 3.6%, 5.0% and 4.3%, respectively. Prediction errors with NEL equations were 0.5-1.1% higher.