Responses of dairy cows to weekly individualized feeding strategies for dairy cows regarding their metabolic status

Abstract

In dairy farms, cows are commonly fed a mixture of forages and concentrates ad libitum. To improve the energetic status and productivity of dairy cows, individualized feeding strategies have been proposed. One of this strategy is providing supplemental concentrates to adjust the forage-to-concentrate ratio based on factors like individual milk yield or calculated energy balance. This strategy can affect milk production and cow health, though consistent rules for adjustment are lacking. The objectives of this study were to evaluate the effects of an individualized feeding strategy, adjusted weekly based on the body weight gain of dairy cows, on production performance; and to determine if the metabolic status of the cows could be predicted early in lactation to take it into account into the decisions rules of the strategy. A total of 40 multiparous Holstein cows were involved in a 4-mo trial. The cows entered the experiment individually after calving and were initially fed a standard ration with a fixed 3 kg of extra concentrate per day for the first 8 d (on average). The cows were then paired based on calving date, parity (2 or 3), and body weight gain over the initial week. One cow from each pair was assigned to the Standard Feeding (SF) strategy, which continued receiving the fixed ration, while the other was assigned to the Precision Feeding (PF) strategy, which received a variable amount of extra concentrate adjusted weekly based on body weight gain. Measurements included weekly body weight, daily milk yield, and daily intakes of concentrates and forages. Blood samples were collected to measure metabolites (glucose, BHB, NEFA) for metabolic profiling. The results showed no significant differences in overall body weight gain, milk yield, or intakes (concentrates and/or forages). Two metabolic clusters were identified based on blood metabolites (glucose, BHB, NEFA), predicting cows' metabolic status with 90% accuracy. The balanced cluster had higher milk production, feed intake, and lost more body weight than the imbalanced cluster. Alternative variables like body weight gain and total feed intake can be used to predict metabolic clusters, achieving up to 70% accuracy. To conclude, cows fed this precision feeding strategy had similar performances than those fed the standard feeding strategy. Long-term effect of this strategy should be studied. Metabolic profiling predicted cows' metabolic status suggesting its potential for enhancing individualized feeding decisions.