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Faculdade de Cieências Agrárias e Veterinárias Universidade Estadual Paulista Jaboticabal, São Paulo, Brazil
Corresponding author:
M. Cerón-Muñoz; e-mail:
mceronm{at}hotmail.com.
| ABSTRACT |
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Key Words: fat lactose mastitis milk protein total solids
Abbreviation key: %F = percentage fat, %LT = percentage lactose, MY = milk yield, %P = percentage protein, SCCt = transformed somatic cell count, %TS = percentage total solids
| INTRODUCTION |
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The established association between milk production and SCC in dairy cattle is increasingly used to estimate lost production due to mastitis because important management decisions regarding cost-effective prevention and control of mastitis are based on this relationship (Bartlett et al., 1990). Jones (1986) suggested that SCC of 0.6 to 1 million cells/ml were associated with an 8 to 12% reduction in herd milk production. According to Harmon (1994), the mastitis or elevated SCC is associated with a decrease in lactose,
-lactalbumin, and fat in milk because of reduced synthetic activity in the mammary tissue.
The phenotypic correlations between average SCC during lactation and total production of milk and of its constituents seem to be negative. Welper and Freeman (1992) obtained estimated correlations ranging from –0.15 to –0.01 between SCC and total production of milk, fat, protein, and lactose. However, the lactation average SCC does not use all the information and masks short-term variation in SCCt (Shook and Schutz, 1994). Since SCC in uninfected cows is high at freshening, lowest from peak to mid-lactation, and highest at drying off, a plot of monthly SCC would usually be the inverse of the lactation curve (Reneau, 1986). Harmon (1994) suggested that a modest rise in the SCC of uninfected quarters at the end of lactation is in fact a dilution effect.
Test-day somatic cell records are taken on the same cow at various times, providing longitudinal information that can be related more meaningfully to episodes of infection, and statistical modeling may provide more accurate estimates of the influence of risk factors than lactation average models (Rodriguez-Zas et al., 2000).
In buffalo herds reared in the state of São Paulo, the prevalence of clinical and subclinical mastitis is 1.5% and 18.77% among lactating buffaloes, respectively (Costa et al., 2000), leading to decreased MY and quality. This directly interferes with the production of Mozzarella cheese, originally prepared from buffalo milk. The European Union Directives (92/46CEE and 94/71 CEE) set a limit of 400.00 cells/ml for SCC in raw buffalo milk, when the milk is used for products made with raw milk.
Thus, the objective of the present investigation was to study the influence of factors on the test day on SCC and its relations with the production of milk and of its constituents during lactation in buffalo.
| MATERIALS AND METHODS |
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The data for MY at each monthly test day were obtained from two hand milkings (0500 and 1700 h). The milk constituents were obtained from the morning milking and analyzed by infrared absorption (Bentley 2000 instrument; Chaska, MN). SCC was determined by flow cytometry (Somacount 300 cell counter; Bentley 2000).
For analysis of the SCC variable on the test day, the transformation SCCt = {[log2(SCC/100,000)] + 3] was used (Dabdoub and Shook, 1984). The mixed-model methodology was used according to a repeated-measures scheme, as well as the restricted maximum likelihood method (REML) available in the MIXED software of SAS (1995). In general, the model can be represented as:
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where yijklm = test day of SCCt;
= intercept; vi = random effect of the ith buffalo, with mean = 0 and variance = 1; aj = fixed effect of the jth calving year (j = 1997, ..., 2000); ok = fixed effect of the kth calving order (k = 1, ..., 5); cl = fixed effect of the lth month of lactation (l = 1, ..., 10); (oc)kl = fixed effect of interaction the kth calving order and the lth month of lactation, and eljklm = residue.
The analysis of milk and milk constituents percentage on the test day was carried out according to the mixed-model method applied to a scheme with repeated measures and heterogeneous slopes for the linear effect of SCCt on the month of lactation. In general, the model can be presented as:
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where yijklm = test-day MY and %F, %P, %LT, and %TS;
= intercept; vi = random effect of the ith buffalo, with mean = 0 and variance = 1; aj = fixed effect of the jth calving year (j = 1997, ..., 2000); ok = fixed effect of the kth calving order (k = 1, ..., 5); cl = fixed effect of thelth month of lactation (l = 1, ..., 10); (oc)kl = fixed effect of interaction the kth calving order and the lth month of lactation; ßl = linear regression coefficient for SCCt in the lth month of lactation;
ml = mth SCCt in the lth month of lactation;
l = mean SCCt in the lth month of lactation, and eljklmn = residue.
Due to the seasonality of calving (February to April), the month or station of calving and calendar month of test were omitted from the models.
| RESULTS AND DISCUSSION |
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In cattle, the logarithm of SCC was high at the beginning of the lactation, dropped to a minimum between 40 and 80 d postpartum, and then steadily increased until the end of lactation (Schepers et al., 1997). In the work of Rodriguez-Zas et al. (2000), the SCCt decreased to a nadir at about 60 d of lactation and then increased—although not in a monotonic mode—without regaining the initial level. Rather, SCC increased in older cattle and/or at the end of lactation due to an increased prevalence of infection and permanent glandular damage from previous infections (Bartlett et al., 1990).
ANOVA applied to MY showed that the fixed effects of order and year of parturition were highly significant (P < 0.01). These results may reflect physiological changes in the animals and changes in management and genetic constitution of the herd with time. There was also a highly significant difference between orders of month of lactation. The interaction parity and month of lactation effect were significantly different (P < 0.01). Figure 1
shows that in all parities, MY was greater in the second month of lactation and then decreased. The adjusted mean in the first month of lactation was 6.87 kg, with an increase to 7.55 kg in the second month, and a later decrease until the end of lactation.
Analysis of milk constituents showed highly significant differences for fixed effects of calving year, calving order, and month of lactation. The interaction order of parity by month of lactation effect showed a highly significant difference for lactose (P < 0.01). For protein, fat, and TS, the interaction parity by order of month was not significant (P = 0.051, 0.063, and 0.11, respectively). In the different months of lactation, %F, %P, %LT, and %TS ranged from 6.28 to 8.38%, 4.05 to 4.59%, 4.96 to 5.34%, and 16.94 to 18.55%, respectively (Figure 1
). These values are close to those reported in the literature, which range from 6.71 to 7.65% for %F and from 3.60 to 4.36% for %P (Macedo et al., 1997; Sindhu and Singhal, 1988; Tonhati et al., 2000). Sindhu and Singhal (1988) detected values of 4.83 to 5.48% for lactose, and Macedo et al. (1997) and Sindhu and Singhal (1988) reported values of 15.75 to 18.99% for TS. The peaks of MY, %F, %P, %LT and %TS occurred in the second, ninth, first, and ninth months of lactation, respectively, in agreement with literature reports.
The regression for SCCt showed highly significant differences in all months of lactation for test-day MY and %LT yields, with negative regression coefficients (ßl) for SCCt indicating a reduction in milk and lactose yield. This result is expected for MY reduction as a consequence of the infection of the mammary gland by pathogenic bacteria that vary according to the intensity and duration of the infection (Eberhart et al., 1987). Elevated SCC are associated with a decrease in lactose because of reduced synthetic activity of the mammary tissue (Harmon, 1994).
The regressions of SCCt on %F were highly significant for all months except the eighth month; on %P, they were highly significant in the first and third months; on %TS, they were highly significant in the fourth, sixth, and seventh months (P < 0.01). The %F, %P, and %TS increased with greater SCCt. Kitchen (1981) found no change in fat content, yet total fat yield decreased because of a decline in milk production. Weaver and Kroger (1977) and Ng-Kwai-Hang et al. (1982) observed a significant increase in total protein and noncasein protein as SCC increased. According to the review of Kitchen (1981) cited by Harmon (1994), some studies have shown no change in fat content, but found a decrease in total fat yield because of a decline in milk production.
| CONCLUSIONS |
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| FOOTNOTES |
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Received for publication January 30, 2002. Accepted for publication July 1, 2002.
| REFERENCES |
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ão de leite, gordura e proteína em bubalinos. Rev. Bras. Zool. 29(Suppl. 1):1320–1325.This article has been cited by other articles:
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P. Moroni, C. S. Rossi, G. Pisoni, V. Bronzo, B. Castiglioni, and P. J. Boettcher Relationships between somatic cell count and intramammary infection in buffaloes. J Dairy Sci, March 1, 2006; 89(3): 998 - 1003. [Abstract] [Full Text] [PDF] |
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