Improving pasture intake predictions by variable weighting of plant marker concentrations

The standard approach of weighting all markers by one (A) was satisfactory when marker concentration error was set at zero, however intake predictions were poor when the error was non-zero, which is likely. The weighted least-squares intake solutions that were more robust to variance in measured marker concentrations or in assumed faecal recovery rates were those using weights derived by methods D and F. Marker weights from Methods D, E and F resulted in similar intake prediction error variances and correlations. Methods E and F required more botanical information about plant species and method D was simpler, so method D is recommended rather than other methods studied here, including the standard method A. There are problems with using weights derived from an analysis of all published marker data, so better weighting methods may still be found for specific plant and marker datasets.