Hostname: page-component-586b7cd67f-rcrh6 Total loading time: 0 Render date: 2024-11-26T23:39:25.679Z Has data issue: false hasContentIssue false
  • English
  • Français

Effect of automatic cluster remover settings on milkability, milk quality and milking irregularities of crossbred cows

Published online by Cambridge University Press:  06 June 2019

Ahmad Fahim ,
Madan Lal Kamboj ,
Ajayvir Singh Sirohi ,
Mukesh Bhakat  and
Tushar Kumar Mohanty
Ahmad Fahim*
Affiliation:
Livestock Production Management, SVPUAT, Meerut, India
Madan Lal Kamboj
Affiliation:
ICAR-National Dairy Research Institute, Karnal, India
Ajayvir Singh Sirohi
Affiliation:
ICAR- Central Institute for Research on Cattle, Meerut, India
Mukesh Bhakat
Affiliation:
ICAR-National Dairy Research Institute, Karnal, India
Tushar Kumar Mohanty
Affiliation:
ICAR-National Dairy Research Institute, Karnal, India
*
Author for correspondence: Ahmad Fahim, Email: [email protected]
Get access Rights & Permissions [Opens in a new window]

Abstract

Automatic cluster remover (ACR) settings regulate the end of milking by detaching the clusters based on milk flow dropping below a preset level, which needs to be standardised for different breeds of dairy animals based on their production. A study was conducted to find out the best ACR setting for milking Indian crossbred cows based on milkability, milking irregularities and milk quality. Fifty six crossbred dairy cows in lactations 1 to 4 were categorised into three groups based on the level of production; low (N = 16; <12 kg/d), medium (N = 32; 12–18 kg/d) and high (N = 08; >18 kg/d). The ACR settings tested were 0.1, 0.2, 0.3 and 0.4 kg/min, keeping the vacuum level and pulsation settings constant. The ACR settings significantly (P < 0.01) affected the milk yield at all levels of production with a significant effect (P < 0.01) on machine-on time at 0.4 kg/min. The yield during the first 2 min of milking, average flow and peak flow rates were not affected at any level of production. The average electrical conductivity in milk was significantly (P < 0.01) lower for the low and medium yield cows without affecting the mean somatic cell count. At 0.4 kg/min, more cluster reattachments were needed because of significant amount of milk remaining in the udders post-cluster removal.

Keywords

Automatic cluster removercrossbred cowsmilkabilitymilking irregularities
Type
Research Article
Information
Journal of Dairy Research , Volume 86 , Issue 2 , May 2019 , pp. 196 - 200
Copyright
Copyright © Hannah Dairy Research Foundation 2019 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Armstrong, DV, Bickert, WG, Gerrish, JB and Spike, PW (1970) Automatic milking machine removal. Journal of Dairy Science 53, 658.Google Scholar
Besier, J and Bruckmaier, RM (2016) Vacuum levels and milk-flow dependent vacuum drops affect machine milking performance and teat condition in dairy cows. Journal of Dairy Science 99, 3096–3102.Google Scholar
Bruckmaier, RM and Hilger, M (2001) Milk ejection in dairy cows at different degrees of udder filling. Journal of Dairy Research 68, 369–376.Google Scholar
Burke, JK and Jago, JG (2010) The effect of two milk flow-rate thresholds for automatic cup removal on milking duration, production and somatic cell count of peak-lactation dairy cows. In Proceedings of the 4th Australasian Dairy Science Symposium, pp. 376–379.Google Scholar
Clarke, T, Cuthbertson, EM, Greenall, RK, Hannah, MC, Jongman, E and Shoesmith, D (2004) Milking regimes to shorten milking duration. Journal of Dairy Research 71, 419–426.Google Scholar
Fadlemoula, AA, Yousif, IA and Abu Nikhaila, AM (2007) Lactation curve and persistency of crossbred dairy cows in the Sudan. Journal of Applied Science and Research 3, 1127–1133.Google Scholar
Gaspardy, A, Ismach, G, Bajcsy, AC, Veress, G, Markus, S and Komlosi, I (2012) Evaluation of the on-line electrical conductivity of milk in mastitic dairy cows. Acta Veterinaria Hungarica 60, 145–155.Google Scholar
Hennigsson, M, Ostergren, K and Dejmek, P (2005) The electrical conductivity of milk—The effect of dilution and temperature. International Journal of Food Properties 8, 15–22.Google Scholar
Jacobs, JA and Siegford, JM (2012) The impact of automatic milking systems on dairy cow management, behavior, health, and welfare. Journal of Dairy Science 95, 2227–2247.Google Scholar
Jago, JG, Burke, J and Williamson, JH (2010 a) Effect of automatic cluster removal settings on production, udder health, and milking duration. Journal of Dairy Science 93, 2541–2549.Google Scholar
Jago, JG, Burke, J and Williamson, JH (2010 b) Does reducing cups-on time affect milk production, clinical mastitis, somatic cell count or teat condition? In Proceedings of the 5th IDF Mastitis Conference, pp. 468–472.Google Scholar
Jingar, S, Mehla, RK, Singh, M and Roy, AK (2014) Lactation curve pattern and prediction of milk production performance in crossbred cows. Journal of Veterinary Medicine 2014, 1–6.Google Scholar
Krawczel, P, Ferneborg, S, Wiking, L, Dalsgaard, TK, Gregersen, S, Black, R, Larsen, T, Agenas, S, Svennersten-Sjaunja, K and Ternman, E (2017) Milking time and risk of over-milking can be decreased with early teat cup removal based on udder quarter milk flow without loss in milk yield. Journal of Dairy Science 100, 6640–6647.Google Scholar
Lewis, S, Cockroft, PD, Bramley, RA and Jackson, PGG (2000) The likelihood of sub-clinical mastitis in quarters with different types of teat lesions in the dairy cow. Cattle Practice 8, 293–299.Google Scholar
Magliaro, AL and Kensinger, RS (2005) Automatic cluster removal settings effects milk yield and machine-on time in dairy cows. Journal of Dairy Science 88, 148–153.Google Scholar
Mein, GA and Reid, DA (1996) Milking-time tests and guidelines for milking units. In Proceedings of the 35th National Mastitis Council Annual Meeting, Nashville, Tennessee, pp. 235–244.Google Scholar
Natzke, RP, Everett, RW and Bray, DR (1982) Effect of over-milking on udder health. Journal of Dairy Science 65, 117–125.Google Scholar
Rasmussen, MD (1993) Influence of switch level of automatic cluster removers on milking performance and udder health. Journal of Dairy Research 60, 287–297.Google Scholar
Rasmussen, MD (2004) Overmilking and teat condition. In Proceedings of the National Mastitis Council Annual Meeting, Charlotte, pp. 169–175.Google Scholar
Ruegg, P, Rasmussen, MD and Reinemann, D (2005) The seven habits of highly successful milking routines. Milk Money 3, 61–69.Google Scholar
Sagi, R (1978) Milk flow rate and end of milking detectors. In Proceedings of Annual Meeting of the National Mastitis Council, pp. 328–334.Google Scholar
Spencer, SB (1989) Recent research and developments in machine milking- A review. Journal of Dairy Science 72, 1907–1917.Google Scholar
Stewart, SC, Godden, S, Rapnicki, P, Reid, DA, Johnson, A and Eicker, SW (2002) Effects of automatic cluster remover settings on average milking duration, milk flow, and milk yield. Journal of Dairy Science 85, 818–823.Google Scholar
Strapak, P, Antalík, P and Szencziova, I (2011) Milkability evaluation of Holstein dairy cows by Lactocorder. Journal of Agrobiology 28, 139–146.Google Scholar
Tancin, V, Ipema, B, Hogewerf, P and Macuhova, J (2006) Sources of variation in milk flow characteristics at udder and quarter levels. Journal of Dairy Science 89, 978–988.Google Scholar
Thompson, PD (1981) Milking machines – The past twenty-five years. Journal of Dairy Science 64, 1344–1357.Google Scholar
Tonelli (1972) Apparatus for removing the teat cups. Patent, Alfa-Laval AB, Sweden.Google Scholar
Wheelock, JV, Rook, JAF and Dodd, FH (1965) The effect of incomplete milking or of an extended milking interval on the yield and composition of cow's milk. Journal of dairy Research 32, 237–248.Google Scholar
Wieland, M, Melvin, J, Virkler, P and Nydam, D (2016) Influence of cow characteristics and premilking udder preparation on milk flow and teat condition. Dairy Business and Holstein World 10, 37–38.Google Scholar
Zaninelli, M, Tangorra, FM, Costa, A, Rossi, L, Dell'Orto, V and Savoini, G (2016) Improved fuzzy logic system to evaluate milk electrical conductivity signals from on-line sensors to monitor dairy goat mastitis. Sensors 16, 1079–1097.Google Scholar
Supplementary material: PDF

Fahim et al. supplementary material

Figure S1

Download Fahim et al. supplementary material(PDF)
PDF 124.6 KB