@conference {41230,
	title = {Can a mathematical model accurately predict intake of grazing animals? Testing the Q-Graze model},
	booktitle = {Proceedings of the New Zealand Society of Animal Production},
	volume = {61},
	year = {2001},
	month = {Jan},
	pages = {4-7},
	publisher = {New Zealand Society of Animal Production},
	organization = {New Zealand Society of Animal Production},
	address = {Christchurch},
	abstract = {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{\textquoteright}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 {\textpm} 1.5, 0.6 {\textpm} 1.3, 1.3 {\textpm} 0.7, 1.2 {\textpm} 0.8, 1.5 {\textpm} 1.4 and 10.6 {\textpm} 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. },
	issn = {1176-5283},
	author = {Woodward SJR and Lambert MG and Litherland AJ and Boom CJ}
}
