Prediction of the voluntary intake of grass silages by beef cattle 3. Precision of alternative prediction models

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Abstract
The precision of a number of new models for predicting silage intake by beef cattle was investigated with independent data using the mean-square prediction error and compared with two previously published models (Agricultural Research Council, 1980; Lewis, 1981). The new models generally performed well relative to the previous models.The new models included a number constructed using the technique of ridge regression which were shown to be consistently better predictors than the models obtained from the same estimation data by stepwise least-squares regression. Better prediction was also obtained by reducing the number of variables in the least-squares models below that required to maximize R2 in the estimation data. The poor performance of the least-squares models with the best R2 may be attributed to collinearity between the independent variates in the estimation data.Most of the models considered overpredicted relative to observed intakes. This may have been the result of differences in breed type and management of the animals between the test data and the estimation data used to construct the models, that is the use of the models with the test data involved a degree of extrapolation.It is concluded that ridge regression and deletion of variables offer a positive step forward in intake prediction compared with models based on maximizing R2 in the estimation data. However, further work is needed to clarify the effect of factors such as breed and rearing system on intake and to clarify the usefulness of various fibre measures in intake prediction. A number of new models are proposed which utilize a range of input variables thus allowing flexibility in their use in practical situations.