Reference : Body and milk traits as cow’s energy status indicator
Scientific congresses and symposiums : Poster
Life sciences : Agriculture & agronomy
http://hdl.handle.net/2268/224005
Body and milk traits as cow’s energy status indicator
English
Mäntysaari, P [> >]
Kokkonen, T [> >]
Grelet, Clément mailto [Université de Liège - ULiège > > > Doct. sc. agro. & ingé. biol. (Paysage)]
Mäntysaari, E [> >]
Lidauer, M [> >]
Aug-2017
Yes
International
Book of Abstracts of the 68th Annual Meeting of the European Federation of Animal Science
28/08 au 1/09
Tallin
[en] In early lactation the feed intake (FI) of high producing cow seldom fulfils her energy demands, forcing the cow to mobilize body reserves. A long lasting and deep energy deficiency can cause health and reproduction problems. Also, if FI is considered in the breeding goal, the postpartum energy status (ES) has to be monitored. ES can be estimated by calculating the energy balance (EB) from cow’s energy intake and output. Alternatively, EB can be predicted by indicator traits like changes of body weight (∆BW) and body condition score (∆BCS), milk fat-protein ratio (FP) or milk fatty acid (FA) composition. The precision of these predictions has often been low. This may be related to a lack of precision in estimated EB itself, when standard energy requirements are used in EB. We used plasma non-esterified fatty acids (NEFA) concentration as a biomarker of ES, and addressed associations between NEFA concentration and ES indicators. Data included daily BW, milk and FI and monthly BCS of 102 and 43 cows on the 1st and 2nd lactation. Plasma samples for NEFA were collected twice on lactation weeks 2 and 3 and once on week 20. Milk samples for fat and protein concentration and FA composition (using MIR) were taken on the days of NEFA sampling. Milk FA contents were predicted by calibration equations from University of Liège/CRA-W, Belgium. On lactation weeks 2, 3 and 20 NEFA concentrations were on average 0.60 (±0.32), 0.46 (±0.23) and 0.14 (±0.06) mmol/l. First, a multiple linear regression model to predict NEFA was developed without milk FA. The best fit model (M1) included ∆BW, FP, ∆BCS, BCS×∆BCS, parity and days in milk (AIC -153.2). Five milk FA or FA groups (C10, C16, C18:1, monounsaturated, and saturated FAs) were chosen by step-wise regression on NEFA. With FAs included, the best model (M2) contained ∆BW, ∆BCS, BCS×∆BCS and FAs (AIC -366.5). The correlations between predicted and observed NEFA were 0.73 (M1) and 0.79 (M2), which were clearly higher than the correlation -0.47 between NEFA and EB. Body and milk indicators predict ES better than the calculated EB.
http://hdl.handle.net/2268/224005

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