A decision support model, Q-Graze, was developed to assist farmers with grazing management decisions based on visual assessments of pasture quality. To evaluate the model’s ability to predict dry matter intake and diet composition, it was tested against pre- and post-grazing herbage mass and composition data from a trial conducted at the Whatawhata Research Centre involving bulls and steers grazing mixed-species hill pasture. Q-Graze was able to predict apparent intakes of grass leaf, grass stem, legume, weed, dead material and total dry matter with means and residual standard deviations 6.4 ± 1.5, 0.6 ± 1.3, 1.3 ± 0.7, 1.2 ± 0.8, 1.5 ± 1.4 and 10.6 ± 2.3 kg DM per animal per day, respectively. These predictions accounted for R2 = 83%, 15%, 76%, 73%, 54% and 55%, respectively of the variation in the apparent intakes calculated from the data. This indicates that Q-Graze is able to predict herbage intake and diet selection of cattle grazing mixed hill-country pastures to a high degree of correlation. The limiting factor was the measurement error of pre- and post-grazing herbage mass, rather than the model design. Model testing for additional animal and pasture types is currently being undertaken.

SJR, Woodward, MG Lambert, AJ Litherland, and CJ Boom

Proceedings of the New Zealand Society of Animal Production, Volume 61, Christchurch, 4-7, 2001
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