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Paddock selection is an important component of grazing management and is based on either an estimate of herbage mass, or the interval since last grazing for each paddock. Obtaining estimates of herbage mass to guide grazing management can be a time consuming task. A value proposition could therefore assist farmers in deciding whether to invest resources in obtaining such information. A farm-scale simulation exercise was designed to estimate the effect of three levels of knowledge of individual paddock herbage mass on profitability of two typical pasture-based dairy systems in New Zealand; a medium input system stocked at 3. 2 Friesian-Jersey cross bred cows/ha with ~15% imported feed, and a high input system stocked at 4. 5 Friesian cows/ha with ~40% imported feed. The three levels of knowledge were: (1) ‘perfect knowledge’, where herbage mass per paddock is known with perfect accuracy, (2) ‘imperfect knowledge’, where herbage mass per paddock is estimated with an average error of 15%, (3) ‘low knowledge’, where herbage mass is not known, and paddocks are selected based on longest time since last grazing. In both systems, grazing management based on imperfect knowledge increased farm operating profit by ~NZ385/ha at a milk price of NZ6. 33/kg milksolids (fat + protein) compared with low knowledge. Perfect knowledge added a further NZ155/ha to profit. The main driver of these results is the level of accuracy in daily feed allocation, which increases with improved knowledge of herbage availability. This allows feed supply and demand to be better matched, resulting in less incidence of under- and over-feeding, higher milk production, and more optimal post-grazing residual herbage mass to maximise herbage regrowth.
Beukes et al. (Thu,) studied this question.