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Variation in phosphorus content of milk from dairy cattle as affected by differences in milk composition

Published online by Cambridge University Press:  21 March 2014

G. KLOP ,
J. L. ELLIS ,
M. C. BLOK ,
G. G. BRANDSMA ,
A. BANNINK  and
J. DIJKSTRA
G. KLOP*
Affiliation:
Animal Nutrition Group, Wageningen University, PO Box 338, 6700 AH Wageningen, The Netherlands
J. L. ELLIS
Affiliation:
Animal Nutrition Group, Wageningen University, PO Box 338, 6700 AH Wageningen, The Netherlands
M. C. BLOK
Affiliation:
Product Board Animal Feed, PO Box 908, 2700 AX Zoetermeer, The Netherlands
G. G. BRANDSMA
Affiliation:
Product Board Animal Feed, PO Box 908, 2700 AX Zoetermeer, The Netherlands
A. BANNINK
Affiliation:
Wageningen UR Livestock Research, PO Box 65, 8200 AB Lelystad, The Netherlands
J. DIJKSTRA
Affiliation:
Animal Nutrition Group, Wageningen University, PO Box 338, 6700 AH Wageningen, The Netherlands
*
*To whom all correspondence should be addressed. Email: [email protected]
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Summary

In view of environmental concerns with regard to phosphorus (P) pollution and the expected global P scarcity, there is increasing interest in improving P utilization in dairy cattle. In high-producing dairy cows, P requirements for milk production comprise a significant fraction of total dietary P requirements. Although variation in P content of milk can affect the efficiency of P utilization for milk production (i.e. the fraction of ingested P that is incorporated in milk), this variation is poorly understood. It was hypothesized that the P content of milk is related to both milk protein and milk lactose content, but not necessarily to milk fat content. Three existing experiments comprising individual animal data on milk yield and fat, protein, lactose and P content of milk (in total 278 observations from 121 cows) were analysed to evaluate this hypothesis using a mixed model analysis. The models including the effects of both protein and lactose content of milk yielded better prediction of milk P content in terms of root-mean-square prediction error (RMSPE) and concordance correlation coefficient (CCC) statistics than models with only protein included as prediction variable; however, estimates of effect sizes varied between studies. The inclusion of milk fat content in equations already including protein and lactose did not further improve prediction of milk P content. Equations developed to describe the relationship between milk protein and lactose contents (g/kg) and milk P content (g/kg) were: (Expt 1) P in milk=−0·44(±0·179)+0·0253(±0·00300)×milk protein+0·0133(±0·00382)×milk lactose (RMSPE: 5·2%; CCC: 0·71); (Expt 2) P in milk=−0·26 (±0·347)+0·0174(±0·00328)×milk protein+0·0143 (±0·00611)×milk lactose (RMSPE: 6·3%; CCC: 0·40); and (Expt 3) P in milk=−0·36(±0·255)+0·0131(±0·00230)×milk protein+0·0193(±0·00490)×milk lactose (RMSPE: 6·5%; CCC: 0·55). Analysis of the three experiments combined, treating study as a random effect, resulted in the following equation to describe the same relationship as in the individual study equations: P in milk=−0·64(±0·168)+0·0223(±0·00236)×milk protein+0·0191(±0·00316)×milk lactose (RMSPE: 6·2%; CCC: 0·61). Although significant relationships between milk protein, milk lactose and milk P were found, a considerable portion of the observed variation remained unexplained, implying that factors other than milk composition may affect the P content of milk. The equations developed may be used to replace current fixed milk P contents assumed in P requirement systems for cattle.

Type
Animal Research Papers
Information
The Journal of Agricultural Science , Volume 152 , Issue 5 , October 2014 , pp. 860 - 869
Copyright
Copyright © Cambridge University Press 2014 

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