Abstract
Precise energy balance estimates for individual cows are of great importance to monitor health, reproduction, and feed management. Energy balance is usually calculated as energy input minus output (EBinout), requiring measurements of feed intake and energy output sources (milk, maintenance, activity, growth, and pregnancy). Except for milk yield, direct measurements of the other sources are difficult to obtain in practice, and estimates contain considerable error sources, limiting on-farm use. Alternatively, energy balance can be estimated from body reserve changes (EBbody) using body weight (BW) and body condition score (BCS). Automated weighing systems exist and new technology performing semi-automated body condition scoring has emerged, so frequent automated BW and BCS measurements are feasible. We present a method to derive individual EBbody estimates from frequently measured BW and BCS and evaluate the performance of the estimated EBbody against the traditional EBinout method. From 76 Danish Holstein and Jersey cows, parity 1 or 2+, on a glycerol-rich or a whole grain-rich total mixed ration, BW was measured automatically at each milking. The BW was corrected for the weight of milk produced and for gutfill. Changes in BW and BCS were used to calculate changes in body protein, body lipid, and EBbody during the first 150d in milk. The EBbody was compared with the traditional EBinout by isolating the term within EBinout associated with most uncertainty; that is, feed energy content (FEC); FEC=(EBbody+EMilk+EMaintenance+Eactivity)/dry matter intake, where the energy requirements are for milk produced (EMilk), maintenance (EMaintenance), and activity (EActivity). Estimated FEC agreed well with FEC values derived from tables (the mean estimate was 0.21MJ of effective energy/kg of dry matter or 2.2% higher than the mean table value). Further, the FEC profile did not suggest systematic bias in EBbody with stage of lactation. The EBbody estimated from daily BW, adjusted for milk and meal-related gutfill and combined with frequent BCS, can provide a successful tool. This offers a pragmatic solution to on-farm calculation of energy balance with the perspective of improved precision under commercial conditions.
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