The use of mid-infrared spectrometry to predict body energy status of Holstein cows

S McParland, G Banos, E Wall, MP Coffey, H Soyeurt, RF Veerkamp, DP Berry

Research output: Contribution to journalArticle

52 Citations (Scopus)

Abstract

Energy balance, especially in early lactation, is known to be associated with subsequent health and fertility in dairy cows. However, its inclusion in routine management decisions or breeding programs is hindered by the lack of quick, easy, and inexpensive measures of energy balance. The objective of this study was to evaluate the potential of mid-infrared (MIR) analysis of milk, routinely available from all milk samples taken as part of large-scale milk recording and milk payment operations, to predict body energy status and related traits in lactating dairy cows. The body energy status traits investigated included energy balance and body energy content. The related traits of body condition score and energy intake were also considered. Measurements on these traits along with milk MIR spectral data were available on 17 different test days from 268 cows (418 lactations) and were used to develop the prediction equations using partial least squares regression. Predictions were externally validated on different independent subsets of the data and the results averaged. The average accuracy of predicting body energy status from MIR spectral data was as high as 75% when energy balance was measured across lactation. These predictions of body energy status were considerably more accurate than predictions obtained from the sometimes proposed fat-to-protein ratio in milk. It is not known whether the prediction generated from MIR data are a better reflection of the true (unknown) energy status than the actual energy status measures used in this study. However, results indicate that the approach described may be a viable method of predicting individual cow energy status for a large scale of application.
Original languageEnglish
Pages (from-to)3651 - 3661
Number of pages11
JournalJournal of Dairy Science
Volume94
Issue number7
Publication statusFirst published - 2011

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spectroscopy
Holstein
cows
energy
energy balance
milk
prediction
spectral analysis
dairy cows
lactation
milk analysis
early lactation
energy content
body condition
least squares
energy intake
breeding
lipids
proteins
testing

Keywords

  • Energy balance
  • Intake
  • Mid-infrared
  • Prediction

Cite this

McParland, S ; Banos, G ; Wall, E ; Coffey, MP ; Soyeurt, H ; Veerkamp, RF ; Berry, DP. / The use of mid-infrared spectrometry to predict body energy status of Holstein cows. In: Journal of Dairy Science. 2011 ; Vol. 94, No. 7. pp. 3651 - 3661.
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McParland, S, Banos, G, Wall, E, Coffey, MP, Soyeurt, H, Veerkamp, RF & Berry, DP 2011, 'The use of mid-infrared spectrometry to predict body energy status of Holstein cows', Journal of Dairy Science, vol. 94, no. 7, pp. 3651 - 3661.

The use of mid-infrared spectrometry to predict body energy status of Holstein cows. / McParland, S; Banos, G; Wall, E; Coffey, MP; Soyeurt, H; Veerkamp, RF; Berry, DP.

In: Journal of Dairy Science, Vol. 94, No. 7, 2011, p. 3651 - 3661.

Research output: Contribution to journalArticle

TY - JOUR

T1 - The use of mid-infrared spectrometry to predict body energy status of Holstein cows

AU - McParland, S

AU - Banos, G

AU - Wall, E

AU - Coffey, MP

AU - Soyeurt, H

AU - Veerkamp, RF

AU - Berry, DP

PY - 2011

Y1 - 2011

N2 - Energy balance, especially in early lactation, is known to be associated with subsequent health and fertility in dairy cows. However, its inclusion in routine management decisions or breeding programs is hindered by the lack of quick, easy, and inexpensive measures of energy balance. The objective of this study was to evaluate the potential of mid-infrared (MIR) analysis of milk, routinely available from all milk samples taken as part of large-scale milk recording and milk payment operations, to predict body energy status and related traits in lactating dairy cows. The body energy status traits investigated included energy balance and body energy content. The related traits of body condition score and energy intake were also considered. Measurements on these traits along with milk MIR spectral data were available on 17 different test days from 268 cows (418 lactations) and were used to develop the prediction equations using partial least squares regression. Predictions were externally validated on different independent subsets of the data and the results averaged. The average accuracy of predicting body energy status from MIR spectral data was as high as 75% when energy balance was measured across lactation. These predictions of body energy status were considerably more accurate than predictions obtained from the sometimes proposed fat-to-protein ratio in milk. It is not known whether the prediction generated from MIR data are a better reflection of the true (unknown) energy status than the actual energy status measures used in this study. However, results indicate that the approach described may be a viable method of predicting individual cow energy status for a large scale of application.

AB - Energy balance, especially in early lactation, is known to be associated with subsequent health and fertility in dairy cows. However, its inclusion in routine management decisions or breeding programs is hindered by the lack of quick, easy, and inexpensive measures of energy balance. The objective of this study was to evaluate the potential of mid-infrared (MIR) analysis of milk, routinely available from all milk samples taken as part of large-scale milk recording and milk payment operations, to predict body energy status and related traits in lactating dairy cows. The body energy status traits investigated included energy balance and body energy content. The related traits of body condition score and energy intake were also considered. Measurements on these traits along with milk MIR spectral data were available on 17 different test days from 268 cows (418 lactations) and were used to develop the prediction equations using partial least squares regression. Predictions were externally validated on different independent subsets of the data and the results averaged. The average accuracy of predicting body energy status from MIR spectral data was as high as 75% when energy balance was measured across lactation. These predictions of body energy status were considerably more accurate than predictions obtained from the sometimes proposed fat-to-protein ratio in milk. It is not known whether the prediction generated from MIR data are a better reflection of the true (unknown) energy status than the actual energy status measures used in this study. However, results indicate that the approach described may be a viable method of predicting individual cow energy status for a large scale of application.

KW - Energy balance

KW - Intake

KW - Mid-infrared

KW - Prediction

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VL - 94

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EP - 3661

JO - Journal of Dairy Science

JF - Journal of Dairy Science

SN - 0022-0302

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