NON-GENETIC FACTORS INFLUENCING FEED EFFICIENCY TRAITS IN COWS

Feed efficiency traits such as dry matter intake (DMI) and gross feed efficiency (GFE) are imperative in the improvement of herd performance, profitability and sustainability. These traits are however normally not included in selection indices, because of the difficulty to measure DMI. However, there is now worldwide sufficient comprehensive and accurate prediction equations from milk components, body weight, milk production, lactation number and stage of lactation that can be used. To that effect, the cited study developed prediction equations for DMI and GFE using routinely recorded milk components in milk recording, in order to conduct genetic analyses of these traits. The aim was to identify non-genetic factors influencing them, so as to account for these in genetic analysis models.

The data included comprised of 5 949 records of daily DMI (kg/day) and GFE (kg/kg) as predicted from test-day milkfat and protein content of 1 237 second and third lactation Holstein cows from eight herds. An analysis of variance was carried out to determine the effects of lactation number, lactation stage, age of cow at calving (ACC, in months) and herd-test-day (HTD) on DMI and GFE, using the GLM procedure of SAS.

The results showed that lactation stage, ACC and HTD significantly affected daily DMI and GFE, and therefore failure to include these effects in genetic prediction models may reduce the accuracy of selection for DMI and GFE, resulting in decreased rates of genetic gain. Means in early lactation (24.1 ± 0.08 and 1.37 ±0.01) were significantly higher than in mid (24.0 ± 0 09 and 1.29 ± 0.01) and late lactation (23.3 ± 0.12 and 1.21 ± 0.02) for DMI and GFE, respectively. In later lactation stages, cows partition more nutrients from feed to maintenance of pregnancy and restoration of body reserves for the next lactation. The average DMI and GFE increased significantly with ACC, increasing at the rate of 0.07 kg/day and 0.02 per four months of age, respectively. This may be due to the fact that younger cows partition more nutrients to growth relative to milk production than mature cows.

Conclusions and recommendations: Since lactation stage, age at calving and herd-test-day significantly influence DMI and GFE, these non-genetic factors should be accounted for in genetic analysis models for accurate prediction of breeding values in dairy cows.