The prediction of rumen fermentation characteristics in sheep given grass silage diets

Abstract

Eight change-over design experiments (each a duplicated 3X3 Latin square design using six rumen-fistulated wether sheep, live weight 50 to 60 kg) measured rumen fermentation patterns for 24 perennial ryegrass silages. Sheep were offered 800 g dry matter (DM) per day of each silage in two equal meals at 09.00 and 17.00 h. Samples of rumen liquor were taken on days 19 and 21 of each 21-day period, at 08.50 h and at 1-5-h intervals until 16.30 h. Rumen samples were analysed by gas chromatography; silages by high-performance liquid chromatography and by near infra-red reflectance spectroscopy (NIRS) using samples scanned after drying at 100°C (NIRSdry) or in the fresh state (NIRSwet). Mean intake of DM was 737 glday. The range of silage composition was as follows (mean, range, s.d., glkg DM unless specified): metabolizable energy (ME MJ/kg DM) 11-1, 8-8 to 12-6, 0-81; pH 4-0, 3-6 to 5-0, 0-34; lactic acid 86, 4 to 139, 42-6; butyric acid 4-7, 0-1 to 46-7,10-2. Rumen measurements varied substantially both diurnally and between silages. Mean diurnal rumen values for the 24 silages (mean, range, s.d.) were: pH 6-76, 6-55 to 7-09, 0-155; ammonia (mg/l) 132, 70 to 247, 47-7; total volatile fatty acids (TVFA mmolll) 58-2, 45-8 to 72-0, 8-97; (acetate+butyrate)/propionate (ABP) 3-2, 2-2 to 4-8, 0-56. Partial least-square models were developed to predict rumen fermentation (means for six sampling times) using either the silage chemical composition (CHEM glkg DM unless specified : DM, ME (MJ/kg DM), crude protein (CP), ammonia (NH 3 , g N per kg total N), neutralizing value (meq per kg DM), sugar, lactic, formic, acetic, propionic and butyric acids and ethanol) or silage NIRSdry or NIRSwet. Prediction performance was assessed comparing values for R 2 , standard error of cross validation (SECV) and SD/SECV (s.d. of reference population! SECV) obtained by the 'leave one out' cross validation method. NIRSwet gave slightly better prediction accuracy overall than NIRSdry but both were superior to prediction from chemical composition. Values for R 2 , SECV and SD/SECV for pH were 0-The silage predictors with greatest influence in the CHEM model for rumen ABP ratio were sugar, CP and lactic acid (negative) and butyrate and ethanol (positive). NIRS shows considerable promise as a means of predicting rumen fermentation of animals given grass silage diets.