Milk losses and quality payment associated with somatic cell counts under different management systems in an arid climate

2015 ◽  
Vol 95 (3) ◽  
pp. 351-360 ◽  
Author(s):  
A. Sadeghi-Sefidmazgi ◽  
P. R. Amer

Sadeghi-Sefidmazgi, A. and Amer, P. R. 2015. Milk losses and quality payment associated with somatic cell counts under different management systems in an arid climate. Can. J. Anim. Sci. 95: 351–360. The objectives of this research were (1) to estimate the economic benefits or new marketing opportunities due to a reduction in milk somatic cell count (SCC) for dairy producers through improved management practices and (2) to quantify the production loss associated with SCC under different management systems. A total of 38 530 average lactation SCC records for 10 216 Holstein cows gathered on 25 dairy farms from January 2009 to October 2012 in Isfahan (Iran) were analyzed under 13 types of herd management practices including 40 levels of health, milking and housing conditions. The results show that there are many well-established management practices associated with higher-quality payment for SCC that have not yet been applied in Isfahan dairy farms. The lowest and highest economic premium opportunity (US$) from SCC were estimated to be for production systems applying washable towels for teat cleaning (5.69) and production systems with no teat disinfection (31.07) per cow per lactation. Results indicate that any increase of one unit in average lactation somatic cell score is expected to cause a significant reduction in average lactation 305-d milk yield from 36.0 to 173.4 kg, depending on the level of management practices employed. In general, farmers with higher milk yield and well-managed practices for mastitis control would lose more milk when an increase occurs in SCC.

2005 ◽  
Vol 48 (2) ◽  
pp. 138-148 ◽  
Author(s):  
F. Goyache ◽  
J. Díez ◽  
S. López ◽  
G. Pajares ◽  
B. Santos ◽  
...  

Abstract. High somatic cell counts (SCC) is associated with mastitis infection, in dairy herds, worldwide. This work describes Machine Learning (ML) techniques designed to improve the information offered to farmers on animals producing high SCCs according to particular herd profiles. The analysed population included 71 dairy farms in Asturias (Northern Spain) and a total of 2,407 lactating cows. Four sources of information were available: a) a questionnaire survey describing facilities, milking routines and management practices of the farms studied; b) dairy recording information; c) classification of the cows suspected of being healthy or subclinical mastitic according to farmers’ expertise; and d) positive or negative scores with respect to the California Mastitis Test (CMT). The decimal logarithm of the SCC (linear score), lactation number, herd size, lactating cows per milker, milk urea concentration, number of clusters per milker and actual SCC are shown to be the most informative attributes for mimicking both farmers’ expertise or CMT performance in order to identify animals producing persistently high SCCs in dairy herds. However, to improve the identification of cows suspected of being non-healthy, the system uses other information related to management and milking routines. Decision rules to predict CMT performance can provide useful, additional information to farmers to improve the management of dairy herds included in milk recording programs.


2009 ◽  
Vol 92 (8) ◽  
pp. 3775-3780 ◽  
Author(s):  
M.J. Haskell ◽  
F.M. Langford ◽  
M.C. Jack ◽  
L. Sherwood ◽  
A.B. Lawrence ◽  
...  

2006 ◽  
Vol 2006 ◽  
pp. 86-86
Author(s):  
G Wellwood ◽  
J K Margerison

Mastitis is a complex disease causing inflammation of the udder, which has been estimated to cost the dairy farmer between £40-£117/cow per year (Stott et al., 2002). Economic loss occurs as a result of discarded milk, reduced milk yield and milk quality, increased vet costs and an increase in replacement costs. The objective of this study was to examine the effect of breed on the incidence of mastitis and somatic cell counts and milk production capabilities of Holstein Friesian, Brown Swiss and Brown Swiss crossbred cows.


1998 ◽  
Vol 81 (7) ◽  
pp. 1917-1927 ◽  
Author(s):  
H.W. Barkema ◽  
Y.H. Schukken ◽  
T.J.G.M. Lam ◽  
M.L. Beiboer ◽  
G. Benedictus ◽  
...  

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