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Shorter sampling periods and accurate estimates of milk volume and components are possible for pasture based dairy herds milked with automated milking systems

Published online by Cambridge University Press:  07 September 2016

Claudia Kamphuis ,
Jennie K Burke ,
Sarah Taukiri ,
Susan-Fay Petch  and
Sally-Anne Turner
Claudia Kamphuis*
Affiliation:
DairyNZ Ltd., Private Bag 3221, Hamilton 3240, New Zealand
Jennie K Burke
Affiliation:
DairyNZ Ltd., Private Bag 3221, Hamilton 3240, New Zealand
Sarah Taukiri
Affiliation:
DairyNZ Ltd., Private Bag 3221, Hamilton 3240, New Zealand
Susan-Fay Petch
Affiliation:
DairyNZ Ltd., Private Bag 3221, Hamilton 3240, New Zealand
Sally-Anne Turner
Affiliation:
DairyNZ Ltd., Private Bag 3221, Hamilton 3240, New Zealand
*
*For correspondence; e-mail: [email protected]
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Abstract

Dairy cows grazing pasture and milked using automated milking systems (AMS) have lower milking frequencies than indoor fed cows milked using AMS. Therefore, milk recording intervals used for herd testing indoor fed cows may not be suitable for cows on pasture based farms. We hypothesised that accurate standardised 24 h estimates could be determined for AMS herds with milk recording intervals of less than the Gold Standard (48 hs), but that the optimum milk recording interval would depend on the herd average for milking frequency. The Gold Standard protocol was applied on five commercial dairy farms with AMS, between December 2011 and February 2013. From 12 milk recording test periods, involving 2211 cow-test days and 8049 cow milkings, standardised 24 h estimates for milk volume and milk composition were calculated for the Gold Standard protocol and compared with those collected during nine alternative sampling scenarios, including six shorter sampling periods and three in which a fixed number of milk samples per cow were collected. Results infer a 48 h milk recording protocol is unnecessarily long for collecting accurate estimates during milk recording on pasture based AMS farms. Collection of two milk samples only per cow was optimal in terms of high concordance correlation coefficients for milk volume and components and a low proportion of missed cow-test days. Further research is required to determine the effects of diurnal variations in milk composition on standardised 24 h estimates for milk volume and components, before a protocol based on a fixed number of samples could be considered. Based on the results of this study New Zealand have adopted a split protocol for herd testing based on the average milking frequency for the herd (NZ Herd Test Standard 8100:2015).

Keywords

Robotic milkingmilk recordingprotocolsampling duration
Type
Research Article
Information
Journal of Dairy Research , Volume 83 , Issue 3 , August 2016 , pp. 326 - 333
Copyright
Copyright © Proprietors of Journal of Dairy Research 2016 

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References

Bucek, P, Zottl, K, Onken, F, Klopčic, M, Radzio, D, Mészarós, G, Barac, Z, Ryba, Š, Dianová, M & Kučera, J 2014 Practical aspects in milk recording in Central and Eastern Europe and its effect on the guidelines. Manuscript available at: http://www.icar.org/index.php/icar-meetings-news/berlin-2014-presentations-pictures-and-inewsletter/ Accessed on June 27th 2016 Google Scholar
Buenger, A, Pasman, T, Bohlsen, E & Reinhardt, F 2002 Transformation of AMS records to 24 hour equivalents. In Performance Recording of Animals – State of the Art 2002, pp. 87–96 (Eds Crettenand, J, Moll, J, Mosconi, C & Wegmann, S.). Interlaken, Switzerland. EAAP publication no. 107. Wageningen, the Netherlands: Wageningen Academic Publishers Google Scholar
Bouloc, N, Dervishi, V, & Delacroix, J 2002 Milk recording and automatic milking systems: simplification by reducing the daily time test from 24 to 12 hours. In Performance Recording of Animals – State of the Art 2002, pp. 57–63. (Eds Crettenand, J, Moll, J, Mosconi, C & Wegmann, S). Interlaken, Switzerland. EAAP publication no. 107. Wageningen, the Netherlands: Wageningen Academic Publishers Google Scholar
Hand, KJ, Lazenby, D, Miglior, F & Kelton, DF 2006 Short communication: Comparison of protocols to estimate twenty-four-hour fat and protein percentages for herds with a robotic milking system. Journal of Dairy Science 89 1723–1726 Google Scholar
ICAR (International Committee for Animal Recording) 2016 Pages 400–401 in ICAR rules, standards, and recommondentations for testing. Section 11- Testing, approval, and checking of milk recording devices. Manuscript available at www.icar.org Accessed on June 27th 2016 Google Scholar
Jago, JG & Burke, JK 2013 Estimating 24-hour milk, fat, and protein yields and somatic cell count for automatically milked cows in pastoral production systems. Proceedings of the New Zealand Society of Animal Production 73 29–32 Google Scholar
Jago, JG, Bright, K, Copeman, P, Davis, K, Jackson, AK, Ohnstad, I, Wieliczko, R & Woolford, MW 2004 Remote automatic selection of cows for milking in a pasture-based automatic milking system. Proceedings of the New Zealand Society of Animal Production 64 241–245 Google Scholar
Kamphuis, C, Dela Rue, B, Turner, S-A & Petch, S-F 2015 Devices used by automated milking systems are similarly accurate in estimating milk yield and in collecting a representative milk sample compared with devices used by farms with conventional milk recording. Journal of Dairy Science 98 3541–3557 Google Scholar
Leclerc, H, Huquet, B, Minery, S, Bourrigan, X, Thomas, G & Saunier, D 2012 Analysis of the accuracy of protocols in robotic milking herds for estimating 24-hour fat and protein (yields and percentage). Session T4 in Proceedings of the 38rd Annual ICAR Meeting, Cork, Ireland. Manuscript available on http://www.icar.org/Cork_2012/Manuscripts/Published/Bourrigan.pdf. Accessed on August 8, 2014 Google Scholar
Lin, LI 1989 A concordance correlation coefficient to evaluate reproducibility. Biometrics 45 255–268 Google Scholar
Lyons, NA, Kerrisk, KL, Dhand, NK, Scott, VE & Garcia, SC 2014 Animal behavior and pasture depletion in a pasture-based automatic milking system. Animal 8 1506–1515 Google Scholar
Miglior, F, de Roos, S, Liu, Z, Mathevon, M, Rosati, A, Schaeffer, LR & VanRaden, P 2002 Report of the ICAR Working Group on lactation calculation methods. Review and update of guidelines for milk recording. In Proceedings of the 33 rd Biennial Session of ICAR, pp. 227–231 Google Scholar
New Zealand Herd Test Standard 2015. Dairy Herd Testing (NZS 8100:2015)Google Scholar
Peeters, R & Galesloot, PJB 2002 Estimating daily fat yield from a single milking on test day for herds with a robotic milking system. Journal of Dairy Science 85 682–688 Google Scholar
VSN International 2013 GenStat for Windows 16th edition. Hemel Hempstead, UK: VSN International. http://www.GenStat.co.uk Google Scholar