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An improved enzymatic method by adding gammanase to determine digestibility and predict energy value of compund feeds and raw materials for cattle. / De Boever, Johan; Cottyn, BG; Vanacker, José; Boucque, CV.

In: Animal Feed Science and Technology, Vol. 47, Nr. 1-2, 01.05.1994, blz. 1-18.

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De Boever, Johan ; Cottyn, BG ; Vanacker, José ; Boucque, CV. / An improved enzymatic method by adding gammanase to determine digestibility and predict energy value of compund feeds and raw materials for cattle. In: Animal Feed Science and Technology. 1994 ; Vol. 47, Nr. 1-2. blz. 1-18.

Bibtex

@article{5c244a247cf245e4a23882d23e04068d,
title = "An improved enzymatic method by adding gammanase to determine digestibility and predict energy value of compund feeds and raw materials for cattle",
abstract = "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.",
author = "{De Boever}, Johan and BG Cottyn and Jos{\'e} Vanacker and CV Boucque",
year = "1994",
month = "5",
day = "1",
doi = "10.1016/0377-8401(94)90155-4",
language = "Undefined/Unknown",
volume = "47",
pages = "1--18",
journal = "Animal Feed Science and Technology",
issn = "0377-8401",
publisher = "ELSEVIER SCIENCE BV",
number = "1-2",

}

RIS

TY - JOUR

T1 - An improved enzymatic method by adding gammanase to determine digestibility and predict energy value of compund feeds and raw materials for cattle

AU - De Boever, Johan

AU - Cottyn, BG

AU - Vanacker, José

AU - Boucque, CV

PY - 1994/5/1

Y1 - 1994/5/1

N2 - 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.

AB - 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.

U2 - 10.1016/0377-8401(94)90155-4

DO - 10.1016/0377-8401(94)90155-4

M3 - A1: Web of Science-article

VL - 47

SP - 1

EP - 18

JO - Animal Feed Science and Technology

JF - Animal Feed Science and Technology

SN - 0377-8401

IS - 1-2

ER -