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Fifty maize silages with known in vivo organic matter digestibility (VOMD) were used to compare the potential of chemical parameters (dry matter (DM), crude protein (CP), crude fibre (CF), crude fat (Cfat), ash, neutral detergent fibre (NDF), acid detergent fibre (ADF), acid detergent lignin (ADL), starch (STA), in vitro digestibility (with rumen fluid (RFOMD) or commercial cellulases (COMD)) and NLRS (monochromator: 1100-2500 nm) in predicting VOMD and calculated metabolizable (ME) and net energy lactation (NEL). A second series of 51 maize silages with digestibility and energy value based on RFOMD served as test set. Further, the possibilities of NIRS to predict chemical composition and calculated protein value (DVE and OEB) were investigated. NIRS-equations, developed by partial least squares analysis, were tested by internal and external validation. The correlation with VOMD was highest for COMD (r = 0.82), followed by RFOMD (0.81), ADF (-0.77) and NIRS-predicted VOMD (0.75). ADL could explain some supplemental variance in VOMD besides ADF and RFOMD, but not with COMD. Multiple linear regressions to predict ME and NEL, irrespective of being based on chemical parameters, RFOMD or COMD had similar residual standard deviations of about 0.21 and 0.16 MJ kg(-1) DM, respectively. With NIRS the standard error of prediction amounted to 0.28 and 0.20 MJ kg(-1) DM, respectively. The relative ability of NIRS to predict chemical composition was very good for residual moisture, STA, ADF, NDF and CP, moderate for CF and ADL and low for ash. The prediction potential for OEB was moderate and nihil for the little varying DVE-content. (C) 1997 Elsevier Science B.V.