Milk fatty acids as indicators of negative energy balance of dairy cows in early lactation.

Most dairy cows experience negative energy balance (NEB) in early lactation because energy demand for milk synthesis is not met by energy intake. Excessive NEB may lead to metabolic disorders and impaired fertility. To optimize herd management, it is useful to detect cows in NEB in early lactation, but direct calculation of NEB is not feasible in commercial herds. Alternative methods rely on fat-to-protein ratio in milk or on concentrations of non-esterified fatty acids (NEFA) and β-hydroxybutyrate (BHB) in blood. Here, we considered methods to assess energy balance (EB) of dairy cows based on the fatty acid (FA) composition in milk. Short- and medium-chain FAs (primarily, C14:0) are typically synthesized de novo in the mammary gland and their proportions in milk fat decrease during NEB. Long-chain FAs C18:0 and C18:1 cis-9 are typically released from body fat depots during NEB, and their proportions increase. In this study, these FAs were routinely determined by Fourier-transform infrared spectroscopy (FTIR) of individual milk samples. We performed an experiment on 85 dairy cows in early lactation, fed the same concentrate ration of up to 5 kg per day and forage ad libitum. Daily milk yield and feed intake were automatically recorded. During lactation weeks 2, 4, and 6 after calving, two milk samples were collected for FTIR spectroscopy, Tuesday evening and Wednesday morning, blood plasma samples were collected Thursday morning. Net energy content in feed and net energy required for maintenance and lactation were estimated to derive EB, which was used to compare alternative indicators of severe NEB. Linear univariate models for EB based on NEFA concentration (deviance explained = 0.13) and other metabolites in blood plasma were outperformed by models based on concentrations of metabolites in milk: fat (0.27), fat-to-protein ratio (0.18), BHB (0.20), and especially C18:0 (0.28) and C18:1 cis-9 (0.39). Analysis of generalized additive models (GAM) revealed that models based on milk variables performed better than those based on blood plasma (deviance explained 0.46 vs. 0.21). C18:0 and C18:1 cis-9 also performed better in severe NEB prediction for EB cut-off values ranging from -50 to 0 MJ NEL/d. Overall, concentrations of C18:0 and C18:1 cis-9 in milk, milk fat, and milk BHB were the best variables for early detection of cows in severe NEB. Thus, milk FA concentrations in whole milk can be useful to identify NEB in early-lactation cows.

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