Prediction of the voluntary intake potential of grass silage by sheep and dairy cows from laboratory silage measurements
Offer, N.W.; Percival, D.S.; Dewhurst, R.J.; Thomas, C.
Animal Science 66(2): 357-367
Ninety-four silages were made over 5 years from predominantly perennial ryegrass swards using a range of cutting dates (19 May to 18 September), wilting periods (0 to 48 h) and additives (none, acids, inoculants, sugar, sugar + acids, sugar + inoculants). A wide range of silage composition was achieved (CV for dry matter (DM), crude protein (CP), digestible organic matter (DOMD), lactic acid, total volatile fatty acids (VFA) and sugar were 0.22, 0.19, 0.07,0.43, 0.84 and 0.69 respectively). Silage dry-matter intake (SDMI) was measured for 88 silages using lambs (mean live weight (M) 28 kg) given silage as their sole diet in four incomplete block design experiments using four lambs per silage and a standard hay given every third period for covariance correction. Thirty-four of the silages were also evaluated using early lactation cows (M, 561 kg and milk yield 27 kg/day) with 7 kg/day of concentrate in eight incomplete block change-over experiments each using 12 cows. Intakes (SDMI mean, range, s.d. g/kg M0.75) were 56, 25 to 84, 13.7 for lambs and 90, 64 to 119, 13.4 for cows. Scaling lamb SDMI by M1.47 accounted best for the effect of lamb weight on intake (mean, range 5.07, 2.43 to 7.68). Silage predictors were grouped as follows: traditional values (BASAL)-DM, CP, organic matter (OM), DOMD, neutral-detergent fibre (NDF), acid-detergent fibre (ADF), ammonia nitrogen (NH3N), pH, acid hydrolysed ether extract (AHEE); silage fermentation values obtained by high-performance liquid chromatography (HPLC); or by electrometric titration (ET), and near infra-red reflectance spectra (NIRS) obtained on either 100degreeC dried (NIRSdry) or fresh samples (NIRSwet1 using a vertical transport mechanism and NIRSwet2 using a rotating cup). The most useful predictors within each group were firstly identified by step-wise multiple linear regression and models were then derived by partial least squares. Standard errors of cross validation (SECV) obtained by the 'leave one out' method were for lamb SDMI (g/M1.47) 0.81, 0.81, 0.75, 0.52, 0.82 and 0.56 for BASAL, BASAL + HPLC, BASAL + ET, NIRSdry, NIRSwet1 and NIRSwet2 respectively. Corresponding values for cows (g/M0.75) were 7.3, 7.3, 5.9, 5.1, 6.2, and 2.5. Inclusion of fermentation measurements made by ET, but not by HPLC, improved SDMI prediction over that obtained from the BASAL set. However, NIRSdry and NIRSwet2 were the most accurate methods giving values for s.d. (reference population) ISECV of 2.27 and 2.13 for lambs and 2.65 and 5.28 for dairy cows. Use of these methods in advisory silage evaluation should substantially reduce the errors of predicting the intake potential of grass silages.