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Somatic cell count, lactoferrin and NAGase activity in milk of infected and non-infected udder halves of dairy goats
Small Ruminant Research 94 (2010) 161–166
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Somatic cell count, lactoferrin and NAGase activity in milk of infected and non-infected udder halves of dairy goats K. Barth a,∗ , K. Aulrich a , U. Müller b , K. Knappstein c a
Institute of Organic Farming, von Thunen Institut, Federal Research Institute for Rural Areas, Forestry and Fisheries, Trenthorst 32, D-23847 Westerau, Germany b Institute of Animal Science, Physiology and Hygiene Group, University Bonn, Katzenburgweg 7-9, D-53115 Bonn, Germany c Department of Safety and Quality of Milk and Fish Products, Max Rubner-Institute, Federal Research Institute of Nutrition and Food, Hermann-Weigmann-Straße 1, D-24103 Kiel, Germany
a r t i c l e
i n f o
Article history: Received 27 October 2009 Received in revised form 31 May 2010 Accepted 30 July 2010 Available online 9 September 2010 Keywords: Goats Mastitis Somatic cell count Lactoferrin NAGase
a b s t r a c t Based on a repeated sampling the influence of an intramammary infection on the somatic cell count (SCC), the content of lactoferrin (Lf) and the activity of N-acetyl-d-glucosaminidase (NAGase) in goats’ milk was investigated. 58 dairy goats (German Improved Fawn) were sampled weekly over 3 consecutive weeks and the udder halves were classified according to the results of the bacteriological analysis of the foremilk samples and the results of their parallel half into three groups: uninfected halves with an uninfected parallel half (NoInf/NoInf), uninfected halves with an infected parallel half (NoInf/Inf) and infected halves with an uninfected parallel half (Inf/NoInf). None of the goats had two infected halves, thus, this group was omitted. 15 out of the 58 goats were infected on one udder half. The bacteria detected were Staphylococcus aureus (n = 4), coagulase-negative staphylococci (n = 7), corynebacteria (n = 3) and esculin-positive streptococci (n = 1). Log10 SCC, log10 Lf and log10 NAGase were strongly correlated to each other and changed over the sampling period but not uniformly, revealing a significant effect of the sampling day on the variables (F6,98 = 29.13, p < .001). This could not be explained by an underlying effect due to the stage of lactation or the estrus season the animals were in, and therefore needs further investigation. The infection status had a significant effect on log10 SCC (F2,103 = 20.22, p < .001), log10 Lf (F2,103 = 11.18, p < .001) and log10 NAGase (F2,103 = 12.06, p < .001). Inf/NoInf differed significantly from NoInf/NoInf as well as NoInf/Inf for log10 SCC (p < .01) and log10 Lf (p < .001) whereas the NoInf/NoInf did not differ from NoInf/Inf indicating that the infected halves did not influence their uninfected parallel half. For log10 NAGase this was different: infected halves differed significantly from NoInf/NoInf (p < .01) but not from NoInf/Inf which might be caused by a dependency of the udder halves. Results support the approach to monitor mastitis in goats by means of Lf or NAGase instead of SCC. Further studies should explore the effect of other independent variables, such as estrus, on these indicators and aim for thresholds indicating an intramammary infection. © 2010 Elsevier B.V. All rights reserved.
1. Introduction
∗ Corresponding author. Tel.: +49 04539 8880 312; fax: +49 04539 8880 140. E-mail address: [email protected] (K. Barth). 0921-4488/$ – see front matter © 2010 Elsevier B.V. All rights reserved. doi:10.1016/j.smallrumres.2010.07.022
Compared to cows, the evaluation of the udder health in goats is still difficult due to the limitations of the somatic cell count (SCC) as an indicator of intramammary infection. SCC of healthy, uninfected udder halves can range
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between 200,000 and 1 million cells/mL (Raynal-Ljutovac et al., 2007) and until now, although several attempts were made, no generally accepted threshold has been established. The high variability of SCC in goats’ milk is caused by infection but also by physiology (Dulin et al., 1983; Paape et al., 2007). The stage and the number of lactation in particular (e.g. Luengo et al., 2004; Dulin et al., 1983; Paape et al., 2007) as well as estrus (Moroni et al., 2007; McDougall and Voermans, 2002; Barth and Aulrich, 2007) have a great effect on the number of cells in milk. Nevertheless, some countries (e.g. USA, France) determined thresholds for the SCC in bulk milk ranging from 750,000 to 1 Mio cells/mL milk (Pirisi et al., 2007). The use of these thresholds in quality payment systems is not without controversy due to the fact that SCC of goats’ milk is influenced by many factors which cannot be influenced by farm management (Model, Personal Communication, 2008). Thus, the question of an applicable criterion for the evaluation of the quality of the delivered milk and for the detection of mastitis still remains. Besides SCC there are a few other indicators of inflammation which might be much more useful for mastitis monitoring in goats. The antimicrobial protein lactoferrin (Lf) is released by polymorphonuclear leukocytes (PMN) after an inflammation. Chen et al. (2004) showed higher Lf concentrations in bulk milk samples gained from herds with a shorter reaction time in the methylene blue reduction test—a test common in Taiwan to evaluate bulk milk quality. In addition, they inoculated one udder halve of three goats with Staphylococcus aureus causing a significant increase of the Lf content in the milk from the inoculated halves. Hiss et al. (2008) sampled 19 goats over a whole lactation and found Lf decreasing during the change from colostrum to milk, and Lf increasing while lactation progressed. The infection status of the animals was not specified in their study. N-Acetyl--d-glucosaminidase (NAGase) is a lysosomal enzyme and many studies have demonstrated its ability to indicate udder infections in cows (e.g. Miller and Paape, 1988; Chagunda et al., 2005). Timms and Schultz (1985) showed the effect of an intramammary infection with minor pathogens on the NAGase activity in goats’ milk and indicated the greater daily variation of SCC compared to NAGase activity. In their study, the correlation between SCC and NAGase activity was lower (r = .54) than that for cows’ milk reported by other authors (e.g. Obara and Komatsu, 1984). Maisi (1990) showed the consistency of the difference for NAGase activity between infected and non-infected parallel halves in goats over a whole lactation. Leitner et al. (2004) evaluated the NAGase using 50 different goats from 10 herds and detected a significant effect of the infection on the NAGase activity. SCC and NAGase activity did not correlate in their study. One of the difficulties in identifying an appropriate indicator for mastitis in goats from the literature is the lack of comparability between the studies. The gold standard chosen for mastitis identification varies from study to study and often the SCC is used without taking into account that it is influenced by so many factors. To overcome this problem we investigated the content of Lf, NAGase and somatic cells in foremilk samples of udder
halves whose infection status was defined by a repeated bacteriological analysis as recommended by the IDF. 2. Materials and methods 58 dairy goats (breed: German Improved Fawn) belonging to the research farm of the Institute of Organic Farming, Trenthorst, were sampled weekly during morning-milking in September 2007 over 3 consecutive weeks. The goats were in mid to late lactation (175–211 days in milk (DIM)) and in their first (n = 15) to 5th lactation (2nd: 9, 3rd: 11, 4th: 7, 5th: 16). The animals were kept on pasture and due to the seasonality of reproduction, the buck was present in the herd. Two times per day the goats were milked in a Side-by-Side milking parlour (WestfaliaSurge, Boenen, Germany) with the following characteristics: 38 kPa milking vacuum, pulsation rate of 120 min−1 and pre-stimulation during a 40 s period after the attachment of the teat-cups. Pre-milking and cleaning the teats with one tissue per goat is practised regularly before attaching the teat-cups. At the milking time when samples were gained, the first squirts of milk were discarded, and then the teats were cleaned and disinfected with alcohol. Foremilk samples were collected aseptically for cyto-bacteriological analysis and stored at 4 ◦ C until analysis on the same day. Afterwards two further samples were gained to measure the content of Lf and NAGase. They were stored at −18 ◦ C until analysis. Cyto-bacteriological analysis and determination of NAGase activity were performed at the laboratory of the MRI in Kiel. The SCC (cells per mL) was analysed with a fluoro-opto-electronic method by flow cytometry (Fossomatic 5000, Foss, Hillerød, DK) according to ISO 13366-2/2006. The activity of NAGase was analysed following the fluorescence spectroscopic method described by Nogai et al. (1996) but modified for goats’ milk. Samples were incubated with 4-methyl-umbelliferylN-acetyl--d-glucosaminide which is transformed by NAGase to the fluorescent 4-methylumbelliferone and then measured by means of a fluorimeter (Microplate Fluorimeter, Model 7630, Cambridge Technologies, Watertown, MA). Activity expressed as nanomoles methylumbelliferone liberated per minute per mL of sample was calculated using reference samples made from goats’ milk. The limit of quantification is 0.32 nmol/min/mL, the interassay coefficient of variation is 7.8%, the intraassay coefficient of variation 6.2%. Samples for measuring Lf were refrigerated and stored at −18 ◦ C until the analysis at the Institute of Animal Science, Bonn. The Lf concentration was determined by an ELISA-Test, developed from the same institute (Hiss et al., 2008). The least determinable concentration is 0.2 ng mL−1 , the interassay coefficient of variation 9.4% and the intraassay coefficient of variation 6.1%. Evaluation of bacteriological analyses followed the recommendation of the International Dairy Federation (IDF) as implemented in the guidelines of the Deutsche Veterinärmedizinische Gesellschaft (DVG, 2000) for the isolation and identification of mastitis pathogens with a sample volume of 0.05 mL per udder half spread on a whole agar plate. A half was defined as infected if two out of the three samples contained the same pathogen. In addition, halves were classified in three groups according to their infection status and the status of their parallel half to reveal effects of infected halves on uninfected ones: NoInf/NoInf = uninfected half with an uninfected parallel half. NoInf/Inf = uninfected half with an infected parallel half. Inf/NoInf = infected half with an uninfected parallel half. The fourth group of infected halves with an infected parallel half was not present and therefore dismissed. After testing the normal distribution of the data, SCC, Lf and NAGase were log10 -transformed before further statistical analyses. Reproduction season influences SCC. Therefore the date of ovulation was estimated using the date of kidding in 2008, and the number of days between this estimated date and the days of sampling were determined (=days related to estimated ovulation (DRO)). Spearman’s correlation coefficients were calculated to test if DRO as well as DIM were related to the readings of SCC, Lf and NAGase, respectively. The final general linear model tested the effect of the infection status, the number of lactations and the interaction between the infection status and the number of lactations on log10 SCC, log10 Lf and log10 NAGase. Due to the fact that sampling was repeated three times over a period of 3 weeks, day of sampling was used as the inner subject factor in the procedure “GLM Repeated Measures” of SPSS 16.0 for Windows® . Differ-
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Table 1 Least square means (±SEM) of somatic cell count (SCC), lactoferrin (Lf) and N-acetyl--d-glucosaminidase (NAGase) depending on the infection status of the udder half and its parallel half. Status of udder halfa
Log10 SCC Log10 Lf Log10 NAGase
p
NoInf/NoInf
NoInf/Inf
Inf/NoInf
5.918 ± 0.036a 1.306 ± 0.032a 0.405 ± 0.026a
5.910 ± 0.105a 1.333 ± 0.095a 0.566 ± 0.077a,b
6.382 ± 0.105b 1.870 ± 0.095b 0.721 ± 0.077b
<.01 <.001 <.01
a NoInf/NoInf: uninfected half with an uninfected parallel half, NoInf/Inf: uninfected half with an infected parallel half, Inf/NoInf: infected half with an uninfected parallel half. a,b means within the same row followed by different letters differ at p.
ences among factor levels were evaluated using the paired t-test with a Bonferroni correction.
3. Results Infection rate was very low in the sampled herd. In 101 out of 116 halves (87.1%) no pathogens were detected. 4 halves were infected by S. aureus, 7 by coagulase-negative staphylococci, 3 by corynebacteria and 1 by esculinpositive streptococci. 43 goats were without any infection; in 15 goats only one udder half was infected. Thus, the groups describing the infection status of the considered half and its parallel half consisted of 86, 15 and 15 halves for NoInf/NoInf, NoInf/Inf and Inf/NoInf, respectively. Mean readings for log10 SCC, log10 Lf and log10 NAGase were 5.98 (SD = 0.463), 1.36 (SD = 0.464) and 0.46 (SD = 0.317) corresponding to geometric means of 955,000 cells/mL, 22.9 g/mL and 2.88 nmol/min/mL, respectively. The means for DIM and DRO at the three sampling days were 201, 208, 215 and −7, 0 and 7, respectively. Whereas the sampling days represent the progressing lactation with an increase of DIM, this is not transferable to DRO: at each sampling day these data showed a wide range from −27 to 6, −20 to 13 and −13 to 20 for the first, second and third day of sampling, respectively. DRO as well as DIM did not significantly correlate with SCC, Lf and NAGase, respectively. Only on one sampling day the correlation was significant between Lf and DRO (rs = .25, p < .01). Therefore, DRO and DIM were excluded from further analyses. Partial correlation controlled for sampling day showed strong and highly significant relations between log10 SCC, log10 Lf and log10 NAGase. Log10 SCC was significantly correlated with log10 Lf, r = .76, and log10 NAGase, r = .76; log10 Lf was also correlated with log10 NAGase, r = .81 (all p < .001). The multivariate test revealed an effect of the infection status of the udder half (F6,204 = 7.87, p < .001), the number of lactation (F12,309 = 5.315, p < .001) and their interaction (F18,309 = 1.669; p < .05). The infection status had a significant effect on log10 SCC (F2,103 = 20.22, p < .001), log10 Lf (F2,103 = 11.18, p < .001) and log10 NAGase (F2,103 = 12.06, p < .001). Parity significantly affected log10 SCC (F4,103 = 11.49, p < .001), log10 Lf (F4,103 = 5.32, p < .001) and log10 NAGase (F4,103 = 4.92, p < .001). Interaction between infection status and parity showed a significant effect on log10 SCC (F6,103 = 3.66, p < .01) only. The status of the udder half had an effect on log10 SCC, log10 Lf and log10 NAGase. Infected halves had significantly
higher levels for all of these three variables compared with halves without any infection. Only the log10 NAGase activity of uninfected halves with an infected parallel half did not significantly differ from the readings of the infected halves (Table 1). However, these halves showed a tendency for lower activity than the infected halves but higher activity than halves from udders without an infection. Although the multivariate analysis detected a significant effect of the number of lactations on log10 SCC, log10 Lf and log10 NAGase, the multiple comparisons between the means revealed only a few significant (p = .05) differences between the different lactations: for log10 SCC the 3rd and the 5th lactation differed from each other (p = .05, Fig. 1), and also a significant difference of log10 Lf could be seen between primiparous and multiparous goats (p < .05, Fig. 2). LSM of log10 NAGase showed the same tendency as log10 Lf with lowest values in primiparous goats but the differences were not significant (Fig. 3). The day of sampling (F6,98 = 29.132; p < .001) and the interaction between the day of sampling and the number of lactations (F24,404 = 1.916; p < .01) affected log10 SCC, log10 Lf and log10 NAGase. Mauchly’s test showed that for log10 Lf the assumption of sphericity had been violated, 2 (2) = 7.131, p < .05. Therefore degrees of freedom were corrected using GreenhouseGeisser estimates of sphericity (ε = .937). The results indicated that the day of sampling alone had a highly significant effect on log10 SCC (F2,206 = 23.42, p < .001), log10 Lf (F1.87,192.97 = 21.45, p < .001) and log10 NAGase (F2,206 = 40.39, p < .001) but only log10 NAGase was influenced by the interaction between the sampling day and
Fig. 1. Effect of parity on log10 SCC (LSM ± SE); difference between 3rd and 5th lactation is significant p = .05 (Bonferroni correction applied).
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Fig. 2. Effect of parity on log10 Lf (LSM ± SE); differences between 1st and higher lactation numbers are significant p < .05 (Bonferroni correction applied).
Fig. 4. Change of log10 SCC (LSM ± SE) during the sampling period depending on the infection status of the udder half and its parallel half ( NoInf/Inf, Inf/NoInf). NoInf/NoInf,
the number of lactation (F8,206 = 4.03, p < .001). A significant effect of the interaction between the day of sampling and the infection status of the udder half on the outcome variables was not found. The tendency of the least square means of log10 SCC, log10 Lf and log10 NAGase was not equal at the sampling days (Table 2). While log10 SCC and log10 NAGase increased slightly from days 1 to 2 and decreased again on day 3, log10 Lf increased throughout the sampling period. These patterns were independent from the infection status of the udder halves: NoInf/NoInf, NoInf/Inf and Inf/NoInf showed the same tendency for the investigated variables (Figs. 4–6). 4. Discussion Repeated analyses of the bacteriological status of udder quarters as a gold standard for mastitis detection in cows, and therefore recommended by the IDF, is often neglected due to the costs and the restricted practicability on commercial dairy farms. Although the transferability of results is also reduced when the investigated animals belong only to one farm, we decided to carry out our experiment in one herd at a research station. The main goal of the management in this farm is to prevent mastitis by high quality
Fig. 3. Effect of parity on log10 NAGase (LSM ± SE); differences between lactations are not significant (Bonferroni correction applied).
Fig. 5. Change of log10 Lf (LSM ± SE) during the sampling period depending on the infection status of the udder half and its parallel half ( NoInf/Inf, Inf/NoInf). NoInf/NoInf,
standards in milking routine and in hygiene during milking. This approach results in a low prevalence of clinical mastitis and a low infection rate with major pathogens. Nevertheless, 26% of the 58 goats had one infected half and coagulase-negative staphylococci dominated the spectrum of detected pathogens. Thus, the herd can be seen as an
Fig. 6. Change of log10 NAGase (LSM ± SE) during the sampling period depending on the infection status of the udder half and its parallel half NoInf/Inf, Inf/NoInf). ( NoInf/NoInf,
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Table 2 Least square means (±SEM) of somatic cell count (SCC), lactoferrin (Lf) and N-acetyl--d-glucosaminidase (NAGase) at the sampling days. Day of sampling
Log10 SCC Log10 Lf Log10 NAGase
p
1
2
3
6.067 ± 0.058a 1.346 ± 0.055a 0.456 ± 0.040a
6.226 ± 0.048b 1.539 ± 0.045b 0.690 ± 0.041b
5.882 ± 0.060c 1.580 ± 0.042b 0.509 ± 0.033a
<.01 <.001 <.001
a,b,c means within the same row followed by different letters differ at p.
example for an average goat herd with a slightly higher status of udder health, and detected significant differences between healthy and infected halves should not disappear but emerged more clearly when herds with a higher prevalence of mastitis are investigated. The weekly repeated sampling for bacteriological analyses led to three readings for SCC, Lf and NAGase. To avoid the loss of information by averaging the data or disregarding the dependence of the readings per udder half, the repeated measure design was used for data analysis. As expected, SCC was high due to the advanced stage of lactation (Paape et al., 2007) and it being the mating season for the animals, during the time of data collection (Moroni et al., 2007). Parity affects SCC as reported by Paape et al. (2007) but in our study, the difference was only significant between the 3rd and 5th lactation. The number of observations per number of lactation was small and seems to have caused this result. Although the number of infected udder halves was small, and the detected bacteria belonged mostly to the group of minor pathogens, the infected udder halves had significantly higher readings for log10 SCC. An influence of infected halves on their uninfected parallel half was not found. This is in contrast to Dulin et al. (1983) and our own observations (Aulrich and Barth, 2008) where we determined a significant raise of SCC in uninfected halves of infected udders compared to the SCC in milk of udders free of infection. An important finding is the effect of the sampling day on log10 SCC, log10 Lf and log10 NAGase, respectively. Although no close correlation to DRO was determined, the higher values for SCC on sampling day 2 compared to sampling days 1 and 3 may be due to the fact that day 2 was closest to the estrus (average DRO = 0). This corresponds to previous observations that SCC is very variable during estrus (McDougall and Voermans, 2002; Moroni et al., 2007) and as reported by Barth and Aulrich (2007) a sharp increase of SCC on only 1 day followed by a sharp decline is not unusual in dairy goats. This pattern was observed independently from the infection status of the udder halves and also in the present study, no effect of the interaction between sampling day and infection status could be found. NAGase activity was higher than in the study by Timms and Schultz (1985) who found average NAGase activities of 1.51 and 2.58 nmol/min/mL for uninfected and infected udder halves of goats, respectively. The lower average SCC of 337,000 mL−1 for uninfected and 659,000 mL−1 for infected halves determined in their study, indicate that sampling was performed in an earlier stage of lactation. The higher NAGase activities in our study thus correspond to the higher SCC in late lactation. Compared to Timms and Schultz (1985), we also found a stronger correlation
between NAGase activity and SCC. With a correlation coefficient of r = .76 it was in the same range as reported by Obara and Komatsu (1984) for cows’ milk. Although parity had a significant effect on NAGase activity and also the interaction between parity and the sampling day affected NAGase activity, comparison of means revealed no significant differences. Miller and Paape (1988) investigated the effect of parity on NAGase activity in milk of cows but found the differences between parities also not significant. Consistent with the results shown by Leitner et al. (2004), infection status had a significant effect on NAGase activity in our study. In addition, multiple comparisons of means revealed a slightly but not significant difference between the group for NoInf/NoInf and NoInf/Inf in log10 NAGase which might indicate a dependency of the halves within one udder and thus, the effect of the infected half on its uninfected parallel half as shown for SCC by Dulin et al. (1983) and Aulrich and Barth (2008). NAGase activity followed the same pattern as SCC during the sampling period with a sharp increase from sampling day 1 to sampling day 2 and a sharp decrease back to the base level on sampling day 3. As for SCC, the effect of the breeding season the animals were in might be responsible for this observation. The mean Lf content was consistent with the results showed by Hiss et al. (2008) for the investigated stage of lactation but none of the readings in our study was as high as the level observed by Chen et al. (2004) regardless of the mammary glands’ infection status. Primiparous goats had significant lower Lf contents in milk than multiparous goats which has also been shown in cows by Soyeurt et al. (2007). The large variation in Lf as discussed by Arnould et al. (2009) might account for these differences. Analysing 11,301 cow milk samples, Arnould et al. (2009) found a mean Lf content of 137.8 mg/L with a standard deviation of 167.74. Hagiwara et al. (2003) reported Lf contents ranging from 7 to 1150 g/mL and from 7 to 3600 g/mL for healthy and subclinical infected cows. Breeds might also differ in Lf contents as observed by Soyeurt et al. (2007) in cows but this would not explain these large differences. In addition, Chen et al. (2004) used their own method and other control standards. Nevertheless, we also found the significant effect of the infection status on the Lf content as described by Chen et al. (2004), although we investigated naturally infected goats without any symptoms of clinical mastitis instead of artificially infected animals. Compared to SCC and NAGase activity, Lf readings for infected and non-infected udder halves differed more distinctly in our study.
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Lf contents increased from the first to the last day of sampling following the increasing DIM. This might indicate that Lf is not affected by the breeding season as assumed for SCC and NAGase activity. For using Lf as a mastitis indicator this would be advantageous but has to be investigated before. 5. Conclusion Our study showed significant effects of mammary infections on SCC, Lf and NAGase activity in dairy goats. We also revealed effects of parity and the sampling day on SCC, Lf and NAGase activity, respectively. Given that Lf is not affected by the breeding season, it might be used to monitor udder health in goats. Therefore, further investigations on commercial dairy farms should focus on the effect of factors not related to mastitis, e.g. estrus, to prove a potential superiority over SCC as an indicator of mastitis in goats. Acknowledgments The authors thank the technicians of the Institute of Organic Farming, Trenthorst, and the laboratory staff of the MRI, Kiel, and of the Institute of Animal Science, Bonn, for their assistance in gaining and analysing the milk samples. References Arnould, V.M-R., Soyeurt, H., Gengler, N., Colinet, F.G., Georges, M.V., Bertozzi, C., Portetelle, D., Renaville, R., 2009. Genetic analysis of lactoferrin content in bovine milk. J. Dairy Sci. 92, 2151–2158. Aulrich, K., Barth, K., 2008. Intramammary infections caused by coagulasenegative staphylococci and the effect on somatic cell counts in dairy goats. Landbauforschung—vTI Agric. Forestry Res. 58, 59–64. Barth, K., Aulrich, K., 2007. Influence of oestrus on somatic cell count in milk of goats. In: Rubino, R., Sepe, L. (Eds.), International Symposium “The Quality of Goat Products”, pp. 139–141. Chagunda, M.G.G., Larsen, T., Bjerring, M., Ingvartsen, K.L., 2005. Lactate dehydrogenase and N-acetyl-b-d-glucosaminidase activities in bovine milk as measures of clinical mastitis. J. Dairy Sci. 88, 197–198. Chen, P.W., Chen, W.C., Mao, F.C., 2004. Increase of lactoferrin concentration in Mastitic goat milk. Vet. Med. Sci. 66, 345–350. Dulin, A.M., Paape, J.M., Schultze, W.D., Weinland, B.T., 1983. Effect of parity, stage of lactation, and intramammary infection on concentration of somatic cells and cytoplasmic particles in goat milk. J. Dairy Sci. 66, 2426–2433. Deutsche Veterinärmedizinische Gesellschaft (DVG), 2000. Leitlinien zur Entnahme von Milchproben unter antiseptischen Bedingungen und
Leitlinien zur Isolierung und Identifizierung von Mastitiserregern (Guidelines for Milk Sampling Under Aseptic Conditions and Guidelines for the Isolation and Identification of Mastitis Pathogens), ISBN 3-930511-81-9. Hagiwara, S., Kawai, K., Anri, A., Nagahata, H., 2003. Lactoferrin concentrations in milk from normal and subclinical mastitis cows. J. Vet. Med. Sci. 65, 319–323. Hiss, S., Meyer, T., Sauerwein, H., 2008. Lactoferrin concentrations in goat milk throughout lactation. Small Rumin. Res. 80, 87–90. International Dairy Federation (IDF), 1985. Laboratory methods for use in mastitis work. IDF Document 132, Brussels, Belgium. International Organization for Standardization (ISO), 2006. ISO13366-2: Milk-Enumeration of Somatic Cells—Part 2: Guidance on the Operation of Fluoro-opto-electronic Counters. Leitner, G., Merin, U., Silanikove, N., Ezra, E., Chaffer, M., Gollop, N., Winkler, M., Glickman, A., Saran, A., 2004. Effect of subclinical intramammary infection on somatic cell counts, NAGase activity and gross composition of goats’ milk. J. Dairy Res. 71, 311–315. Luengo, C., Sanchez, A., Corrales, J.C., Fernandez, C., Contreras, A., 2004. Influence of intramammary infection and non-infection factors on somatic cell counts in dairy goats. J. Dairy Res. 71, 169–174. Maisi, P., 1990. Milk NAGase, CMT and antitrypsin as indicators of caprine subclinical mastitis infections. Small Rumin. Res. 3, 493–501. McDougall, S., Voermans, M., 2002. Influence of estrus on somatic cell count in dairy goats. J. Dairy Sci. 85, 378–383. Miller, R.H., Paape, M.J., 1988. Effects of parity, bacteriological status, stage of lactation, and dry period on N-acetyl--d-glucosaminidase activity of milk and dry secretion. J. Dairy Sci. 71, 2508–2512. Moroni, P., Pisoni, G., Savoini, G., van Lier, E., Acuna, S., Damian, J.P., Meikle, A., 2007. Influence of estrus of dairy goats on somatic cell count, milk traits, and sex steroid receptors in the mammary gland. J. Dairy Sci. 90, 790–797. Nogai, K., Krömker, V., Gyódi, P., Hamann, J., 1996. Zur fluoreszenzspektroskopischen und photometrischen Bestimmung von N-Acetyl--d-glucosaminidase in Milch—Ein Methodenvergleich. In: Proc. 37. Tagung des Arbeitsgebietes Lebensmittelhygiene der DVG, Part II, pp. 299–306, ISBN 3-930511-35-5. Obara, Y., Komatsu, M., 1984. Relationship between n-acetyl--dglucosaminidase activity and cell count, lactose, chloride, or lactoferrin in cow milk. J. Dairy Sci. 67, 1043–1046. Paape, M.J., Wiggans, G.R., Bannerman, D.D., Thomas, D.L., Sanders, A.H., Contreras, A., Moroni, P., Miller, R.H., 2007. Monitoring goat and sheep milk somatic cell counts. Small Rumin. Res. 68, 114–125. Pirisi, A., Lauret, A., Dubeuf, J.P., 2007. Basic and incentive payments for goat and sheep milk in relation to quality. Small Rumin. Res. 68, 167–178. Raynal-Ljutovac, K., Pirisi, A., de Crémoux, R., Gonzalo, C., 2007. Somatic cells of goat and sheep milk: analytical, sanitary, productive and technological aspects. Small Rumin. Res. 68, 126–144. Soyeurt, H., Colinet, F.G., Arnould, V.M.-R., Dardenne, P., Bertozzi, C., Renaville, R., Portetelle, D., Gengler, N., 2007. Genetic variability of lactoferrin content estimated by mid-infrared spectrometry in bovine milk. J. Dairy Sci. 90, 4443–4450. Timms, L.L., Schultz, L.H., 1985. N-acetyl-B-d-glucosaminidase activity and somatic cells in goat milk. J. Dairy Sci. 68, 3363– 3366.
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Small Ruminant Research journal homepage: www.elsevier.com/locate/smallrumres
Somatic cell count, lactoferrin and NAGase activity in milk of infected and non-infected udder halves of dairy goats K. Barth a,∗ , K. Aulrich a , U. Müller b , K. Knappstein c a
Institute of Organic Farming, von Thunen Institut, Federal Research Institute for Rural Areas, Forestry and Fisheries, Trenthorst 32, D-23847 Westerau, Germany b Institute of Animal Science, Physiology and Hygiene Group, University Bonn, Katzenburgweg 7-9, D-53115 Bonn, Germany c Department of Safety and Quality of Milk and Fish Products, Max Rubner-Institute, Federal Research Institute of Nutrition and Food, Hermann-Weigmann-Straße 1, D-24103 Kiel, Germany
a r t i c l e
i n f o
Article history: Received 27 October 2009 Received in revised form 31 May 2010 Accepted 30 July 2010 Available online 9 September 2010 Keywords: Goats Mastitis Somatic cell count Lactoferrin NAGase
a b s t r a c t Based on a repeated sampling the influence of an intramammary infection on the somatic cell count (SCC), the content of lactoferrin (Lf) and the activity of N-acetyl-d-glucosaminidase (NAGase) in goats’ milk was investigated. 58 dairy goats (German Improved Fawn) were sampled weekly over 3 consecutive weeks and the udder halves were classified according to the results of the bacteriological analysis of the foremilk samples and the results of their parallel half into three groups: uninfected halves with an uninfected parallel half (NoInf/NoInf), uninfected halves with an infected parallel half (NoInf/Inf) and infected halves with an uninfected parallel half (Inf/NoInf). None of the goats had two infected halves, thus, this group was omitted. 15 out of the 58 goats were infected on one udder half. The bacteria detected were Staphylococcus aureus (n = 4), coagulase-negative staphylococci (n = 7), corynebacteria (n = 3) and esculin-positive streptococci (n = 1). Log10 SCC, log10 Lf and log10 NAGase were strongly correlated to each other and changed over the sampling period but not uniformly, revealing a significant effect of the sampling day on the variables (F6,98 = 29.13, p < .001). This could not be explained by an underlying effect due to the stage of lactation or the estrus season the animals were in, and therefore needs further investigation. The infection status had a significant effect on log10 SCC (F2,103 = 20.22, p < .001), log10 Lf (F2,103 = 11.18, p < .001) and log10 NAGase (F2,103 = 12.06, p < .001). Inf/NoInf differed significantly from NoInf/NoInf as well as NoInf/Inf for log10 SCC (p < .01) and log10 Lf (p < .001) whereas the NoInf/NoInf did not differ from NoInf/Inf indicating that the infected halves did not influence their uninfected parallel half. For log10 NAGase this was different: infected halves differed significantly from NoInf/NoInf (p < .01) but not from NoInf/Inf which might be caused by a dependency of the udder halves. Results support the approach to monitor mastitis in goats by means of Lf or NAGase instead of SCC. Further studies should explore the effect of other independent variables, such as estrus, on these indicators and aim for thresholds indicating an intramammary infection. © 2010 Elsevier B.V. All rights reserved.
1. Introduction
∗ Corresponding author. Tel.: +49 04539 8880 312; fax: +49 04539 8880 140. E-mail address: [email protected] (K. Barth). 0921-4488/$ – see front matter © 2010 Elsevier B.V. All rights reserved. doi:10.1016/j.smallrumres.2010.07.022
Compared to cows, the evaluation of the udder health in goats is still difficult due to the limitations of the somatic cell count (SCC) as an indicator of intramammary infection. SCC of healthy, uninfected udder halves can range
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between 200,000 and 1 million cells/mL (Raynal-Ljutovac et al., 2007) and until now, although several attempts were made, no generally accepted threshold has been established. The high variability of SCC in goats’ milk is caused by infection but also by physiology (Dulin et al., 1983; Paape et al., 2007). The stage and the number of lactation in particular (e.g. Luengo et al., 2004; Dulin et al., 1983; Paape et al., 2007) as well as estrus (Moroni et al., 2007; McDougall and Voermans, 2002; Barth and Aulrich, 2007) have a great effect on the number of cells in milk. Nevertheless, some countries (e.g. USA, France) determined thresholds for the SCC in bulk milk ranging from 750,000 to 1 Mio cells/mL milk (Pirisi et al., 2007). The use of these thresholds in quality payment systems is not without controversy due to the fact that SCC of goats’ milk is influenced by many factors which cannot be influenced by farm management (Model, Personal Communication, 2008). Thus, the question of an applicable criterion for the evaluation of the quality of the delivered milk and for the detection of mastitis still remains. Besides SCC there are a few other indicators of inflammation which might be much more useful for mastitis monitoring in goats. The antimicrobial protein lactoferrin (Lf) is released by polymorphonuclear leukocytes (PMN) after an inflammation. Chen et al. (2004) showed higher Lf concentrations in bulk milk samples gained from herds with a shorter reaction time in the methylene blue reduction test—a test common in Taiwan to evaluate bulk milk quality. In addition, they inoculated one udder halve of three goats with Staphylococcus aureus causing a significant increase of the Lf content in the milk from the inoculated halves. Hiss et al. (2008) sampled 19 goats over a whole lactation and found Lf decreasing during the change from colostrum to milk, and Lf increasing while lactation progressed. The infection status of the animals was not specified in their study. N-Acetyl--d-glucosaminidase (NAGase) is a lysosomal enzyme and many studies have demonstrated its ability to indicate udder infections in cows (e.g. Miller and Paape, 1988; Chagunda et al., 2005). Timms and Schultz (1985) showed the effect of an intramammary infection with minor pathogens on the NAGase activity in goats’ milk and indicated the greater daily variation of SCC compared to NAGase activity. In their study, the correlation between SCC and NAGase activity was lower (r = .54) than that for cows’ milk reported by other authors (e.g. Obara and Komatsu, 1984). Maisi (1990) showed the consistency of the difference for NAGase activity between infected and non-infected parallel halves in goats over a whole lactation. Leitner et al. (2004) evaluated the NAGase using 50 different goats from 10 herds and detected a significant effect of the infection on the NAGase activity. SCC and NAGase activity did not correlate in their study. One of the difficulties in identifying an appropriate indicator for mastitis in goats from the literature is the lack of comparability between the studies. The gold standard chosen for mastitis identification varies from study to study and often the SCC is used without taking into account that it is influenced by so many factors. To overcome this problem we investigated the content of Lf, NAGase and somatic cells in foremilk samples of udder
halves whose infection status was defined by a repeated bacteriological analysis as recommended by the IDF. 2. Materials and methods 58 dairy goats (breed: German Improved Fawn) belonging to the research farm of the Institute of Organic Farming, Trenthorst, were sampled weekly during morning-milking in September 2007 over 3 consecutive weeks. The goats were in mid to late lactation (175–211 days in milk (DIM)) and in their first (n = 15) to 5th lactation (2nd: 9, 3rd: 11, 4th: 7, 5th: 16). The animals were kept on pasture and due to the seasonality of reproduction, the buck was present in the herd. Two times per day the goats were milked in a Side-by-Side milking parlour (WestfaliaSurge, Boenen, Germany) with the following characteristics: 38 kPa milking vacuum, pulsation rate of 120 min−1 and pre-stimulation during a 40 s period after the attachment of the teat-cups. Pre-milking and cleaning the teats with one tissue per goat is practised regularly before attaching the teat-cups. At the milking time when samples were gained, the first squirts of milk were discarded, and then the teats were cleaned and disinfected with alcohol. Foremilk samples were collected aseptically for cyto-bacteriological analysis and stored at 4 ◦ C until analysis on the same day. Afterwards two further samples were gained to measure the content of Lf and NAGase. They were stored at −18 ◦ C until analysis. Cyto-bacteriological analysis and determination of NAGase activity were performed at the laboratory of the MRI in Kiel. The SCC (cells per mL) was analysed with a fluoro-opto-electronic method by flow cytometry (Fossomatic 5000, Foss, Hillerød, DK) according to ISO 13366-2/2006. The activity of NAGase was analysed following the fluorescence spectroscopic method described by Nogai et al. (1996) but modified for goats’ milk. Samples were incubated with 4-methyl-umbelliferylN-acetyl--d-glucosaminide which is transformed by NAGase to the fluorescent 4-methylumbelliferone and then measured by means of a fluorimeter (Microplate Fluorimeter, Model 7630, Cambridge Technologies, Watertown, MA). Activity expressed as nanomoles methylumbelliferone liberated per minute per mL of sample was calculated using reference samples made from goats’ milk. The limit of quantification is 0.32 nmol/min/mL, the interassay coefficient of variation is 7.8%, the intraassay coefficient of variation 6.2%. Samples for measuring Lf were refrigerated and stored at −18 ◦ C until the analysis at the Institute of Animal Science, Bonn. The Lf concentration was determined by an ELISA-Test, developed from the same institute (Hiss et al., 2008). The least determinable concentration is 0.2 ng mL−1 , the interassay coefficient of variation 9.4% and the intraassay coefficient of variation 6.1%. Evaluation of bacteriological analyses followed the recommendation of the International Dairy Federation (IDF) as implemented in the guidelines of the Deutsche Veterinärmedizinische Gesellschaft (DVG, 2000) for the isolation and identification of mastitis pathogens with a sample volume of 0.05 mL per udder half spread on a whole agar plate. A half was defined as infected if two out of the three samples contained the same pathogen. In addition, halves were classified in three groups according to their infection status and the status of their parallel half to reveal effects of infected halves on uninfected ones: NoInf/NoInf = uninfected half with an uninfected parallel half. NoInf/Inf = uninfected half with an infected parallel half. Inf/NoInf = infected half with an uninfected parallel half. The fourth group of infected halves with an infected parallel half was not present and therefore dismissed. After testing the normal distribution of the data, SCC, Lf and NAGase were log10 -transformed before further statistical analyses. Reproduction season influences SCC. Therefore the date of ovulation was estimated using the date of kidding in 2008, and the number of days between this estimated date and the days of sampling were determined (=days related to estimated ovulation (DRO)). Spearman’s correlation coefficients were calculated to test if DRO as well as DIM were related to the readings of SCC, Lf and NAGase, respectively. The final general linear model tested the effect of the infection status, the number of lactations and the interaction between the infection status and the number of lactations on log10 SCC, log10 Lf and log10 NAGase. Due to the fact that sampling was repeated three times over a period of 3 weeks, day of sampling was used as the inner subject factor in the procedure “GLM Repeated Measures” of SPSS 16.0 for Windows® . Differ-
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Table 1 Least square means (±SEM) of somatic cell count (SCC), lactoferrin (Lf) and N-acetyl--d-glucosaminidase (NAGase) depending on the infection status of the udder half and its parallel half. Status of udder halfa
Log10 SCC Log10 Lf Log10 NAGase
p
NoInf/NoInf
NoInf/Inf
Inf/NoInf
5.918 ± 0.036a 1.306 ± 0.032a 0.405 ± 0.026a
5.910 ± 0.105a 1.333 ± 0.095a 0.566 ± 0.077a,b
6.382 ± 0.105b 1.870 ± 0.095b 0.721 ± 0.077b
<.01 <.001 <.01
a NoInf/NoInf: uninfected half with an uninfected parallel half, NoInf/Inf: uninfected half with an infected parallel half, Inf/NoInf: infected half with an uninfected parallel half. a,b means within the same row followed by different letters differ at p.
ences among factor levels were evaluated using the paired t-test with a Bonferroni correction.
3. Results Infection rate was very low in the sampled herd. In 101 out of 116 halves (87.1%) no pathogens were detected. 4 halves were infected by S. aureus, 7 by coagulase-negative staphylococci, 3 by corynebacteria and 1 by esculinpositive streptococci. 43 goats were without any infection; in 15 goats only one udder half was infected. Thus, the groups describing the infection status of the considered half and its parallel half consisted of 86, 15 and 15 halves for NoInf/NoInf, NoInf/Inf and Inf/NoInf, respectively. Mean readings for log10 SCC, log10 Lf and log10 NAGase were 5.98 (SD = 0.463), 1.36 (SD = 0.464) and 0.46 (SD = 0.317) corresponding to geometric means of 955,000 cells/mL, 22.9 g/mL and 2.88 nmol/min/mL, respectively. The means for DIM and DRO at the three sampling days were 201, 208, 215 and −7, 0 and 7, respectively. Whereas the sampling days represent the progressing lactation with an increase of DIM, this is not transferable to DRO: at each sampling day these data showed a wide range from −27 to 6, −20 to 13 and −13 to 20 for the first, second and third day of sampling, respectively. DRO as well as DIM did not significantly correlate with SCC, Lf and NAGase, respectively. Only on one sampling day the correlation was significant between Lf and DRO (rs = .25, p < .01). Therefore, DRO and DIM were excluded from further analyses. Partial correlation controlled for sampling day showed strong and highly significant relations between log10 SCC, log10 Lf and log10 NAGase. Log10 SCC was significantly correlated with log10 Lf, r = .76, and log10 NAGase, r = .76; log10 Lf was also correlated with log10 NAGase, r = .81 (all p < .001). The multivariate test revealed an effect of the infection status of the udder half (F6,204 = 7.87, p < .001), the number of lactation (F12,309 = 5.315, p < .001) and their interaction (F18,309 = 1.669; p < .05). The infection status had a significant effect on log10 SCC (F2,103 = 20.22, p < .001), log10 Lf (F2,103 = 11.18, p < .001) and log10 NAGase (F2,103 = 12.06, p < .001). Parity significantly affected log10 SCC (F4,103 = 11.49, p < .001), log10 Lf (F4,103 = 5.32, p < .001) and log10 NAGase (F4,103 = 4.92, p < .001). Interaction between infection status and parity showed a significant effect on log10 SCC (F6,103 = 3.66, p < .01) only. The status of the udder half had an effect on log10 SCC, log10 Lf and log10 NAGase. Infected halves had significantly
higher levels for all of these three variables compared with halves without any infection. Only the log10 NAGase activity of uninfected halves with an infected parallel half did not significantly differ from the readings of the infected halves (Table 1). However, these halves showed a tendency for lower activity than the infected halves but higher activity than halves from udders without an infection. Although the multivariate analysis detected a significant effect of the number of lactations on log10 SCC, log10 Lf and log10 NAGase, the multiple comparisons between the means revealed only a few significant (p = .05) differences between the different lactations: for log10 SCC the 3rd and the 5th lactation differed from each other (p = .05, Fig. 1), and also a significant difference of log10 Lf could be seen between primiparous and multiparous goats (p < .05, Fig. 2). LSM of log10 NAGase showed the same tendency as log10 Lf with lowest values in primiparous goats but the differences were not significant (Fig. 3). The day of sampling (F6,98 = 29.132; p < .001) and the interaction between the day of sampling and the number of lactations (F24,404 = 1.916; p < .01) affected log10 SCC, log10 Lf and log10 NAGase. Mauchly’s test showed that for log10 Lf the assumption of sphericity had been violated, 2 (2) = 7.131, p < .05. Therefore degrees of freedom were corrected using GreenhouseGeisser estimates of sphericity (ε = .937). The results indicated that the day of sampling alone had a highly significant effect on log10 SCC (F2,206 = 23.42, p < .001), log10 Lf (F1.87,192.97 = 21.45, p < .001) and log10 NAGase (F2,206 = 40.39, p < .001) but only log10 NAGase was influenced by the interaction between the sampling day and
Fig. 1. Effect of parity on log10 SCC (LSM ± SE); difference between 3rd and 5th lactation is significant p = .05 (Bonferroni correction applied).
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Fig. 2. Effect of parity on log10 Lf (LSM ± SE); differences between 1st and higher lactation numbers are significant p < .05 (Bonferroni correction applied).
Fig. 4. Change of log10 SCC (LSM ± SE) during the sampling period depending on the infection status of the udder half and its parallel half ( NoInf/Inf, Inf/NoInf). NoInf/NoInf,
the number of lactation (F8,206 = 4.03, p < .001). A significant effect of the interaction between the day of sampling and the infection status of the udder half on the outcome variables was not found. The tendency of the least square means of log10 SCC, log10 Lf and log10 NAGase was not equal at the sampling days (Table 2). While log10 SCC and log10 NAGase increased slightly from days 1 to 2 and decreased again on day 3, log10 Lf increased throughout the sampling period. These patterns were independent from the infection status of the udder halves: NoInf/NoInf, NoInf/Inf and Inf/NoInf showed the same tendency for the investigated variables (Figs. 4–6). 4. Discussion Repeated analyses of the bacteriological status of udder quarters as a gold standard for mastitis detection in cows, and therefore recommended by the IDF, is often neglected due to the costs and the restricted practicability on commercial dairy farms. Although the transferability of results is also reduced when the investigated animals belong only to one farm, we decided to carry out our experiment in one herd at a research station. The main goal of the management in this farm is to prevent mastitis by high quality
Fig. 3. Effect of parity on log10 NAGase (LSM ± SE); differences between lactations are not significant (Bonferroni correction applied).
Fig. 5. Change of log10 Lf (LSM ± SE) during the sampling period depending on the infection status of the udder half and its parallel half ( NoInf/Inf, Inf/NoInf). NoInf/NoInf,
standards in milking routine and in hygiene during milking. This approach results in a low prevalence of clinical mastitis and a low infection rate with major pathogens. Nevertheless, 26% of the 58 goats had one infected half and coagulase-negative staphylococci dominated the spectrum of detected pathogens. Thus, the herd can be seen as an
Fig. 6. Change of log10 NAGase (LSM ± SE) during the sampling period depending on the infection status of the udder half and its parallel half NoInf/Inf, Inf/NoInf). ( NoInf/NoInf,
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Table 2 Least square means (±SEM) of somatic cell count (SCC), lactoferrin (Lf) and N-acetyl--d-glucosaminidase (NAGase) at the sampling days. Day of sampling
Log10 SCC Log10 Lf Log10 NAGase
p
1
2
3
6.067 ± 0.058a 1.346 ± 0.055a 0.456 ± 0.040a
6.226 ± 0.048b 1.539 ± 0.045b 0.690 ± 0.041b
5.882 ± 0.060c 1.580 ± 0.042b 0.509 ± 0.033a
<.01 <.001 <.001
a,b,c means within the same row followed by different letters differ at p.
example for an average goat herd with a slightly higher status of udder health, and detected significant differences between healthy and infected halves should not disappear but emerged more clearly when herds with a higher prevalence of mastitis are investigated. The weekly repeated sampling for bacteriological analyses led to three readings for SCC, Lf and NAGase. To avoid the loss of information by averaging the data or disregarding the dependence of the readings per udder half, the repeated measure design was used for data analysis. As expected, SCC was high due to the advanced stage of lactation (Paape et al., 2007) and it being the mating season for the animals, during the time of data collection (Moroni et al., 2007). Parity affects SCC as reported by Paape et al. (2007) but in our study, the difference was only significant between the 3rd and 5th lactation. The number of observations per number of lactation was small and seems to have caused this result. Although the number of infected udder halves was small, and the detected bacteria belonged mostly to the group of minor pathogens, the infected udder halves had significantly higher readings for log10 SCC. An influence of infected halves on their uninfected parallel half was not found. This is in contrast to Dulin et al. (1983) and our own observations (Aulrich and Barth, 2008) where we determined a significant raise of SCC in uninfected halves of infected udders compared to the SCC in milk of udders free of infection. An important finding is the effect of the sampling day on log10 SCC, log10 Lf and log10 NAGase, respectively. Although no close correlation to DRO was determined, the higher values for SCC on sampling day 2 compared to sampling days 1 and 3 may be due to the fact that day 2 was closest to the estrus (average DRO = 0). This corresponds to previous observations that SCC is very variable during estrus (McDougall and Voermans, 2002; Moroni et al., 2007) and as reported by Barth and Aulrich (2007) a sharp increase of SCC on only 1 day followed by a sharp decline is not unusual in dairy goats. This pattern was observed independently from the infection status of the udder halves and also in the present study, no effect of the interaction between sampling day and infection status could be found. NAGase activity was higher than in the study by Timms and Schultz (1985) who found average NAGase activities of 1.51 and 2.58 nmol/min/mL for uninfected and infected udder halves of goats, respectively. The lower average SCC of 337,000 mL−1 for uninfected and 659,000 mL−1 for infected halves determined in their study, indicate that sampling was performed in an earlier stage of lactation. The higher NAGase activities in our study thus correspond to the higher SCC in late lactation. Compared to Timms and Schultz (1985), we also found a stronger correlation
between NAGase activity and SCC. With a correlation coefficient of r = .76 it was in the same range as reported by Obara and Komatsu (1984) for cows’ milk. Although parity had a significant effect on NAGase activity and also the interaction between parity and the sampling day affected NAGase activity, comparison of means revealed no significant differences. Miller and Paape (1988) investigated the effect of parity on NAGase activity in milk of cows but found the differences between parities also not significant. Consistent with the results shown by Leitner et al. (2004), infection status had a significant effect on NAGase activity in our study. In addition, multiple comparisons of means revealed a slightly but not significant difference between the group for NoInf/NoInf and NoInf/Inf in log10 NAGase which might indicate a dependency of the halves within one udder and thus, the effect of the infected half on its uninfected parallel half as shown for SCC by Dulin et al. (1983) and Aulrich and Barth (2008). NAGase activity followed the same pattern as SCC during the sampling period with a sharp increase from sampling day 1 to sampling day 2 and a sharp decrease back to the base level on sampling day 3. As for SCC, the effect of the breeding season the animals were in might be responsible for this observation. The mean Lf content was consistent with the results showed by Hiss et al. (2008) for the investigated stage of lactation but none of the readings in our study was as high as the level observed by Chen et al. (2004) regardless of the mammary glands’ infection status. Primiparous goats had significant lower Lf contents in milk than multiparous goats which has also been shown in cows by Soyeurt et al. (2007). The large variation in Lf as discussed by Arnould et al. (2009) might account for these differences. Analysing 11,301 cow milk samples, Arnould et al. (2009) found a mean Lf content of 137.8 mg/L with a standard deviation of 167.74. Hagiwara et al. (2003) reported Lf contents ranging from 7 to 1150 g/mL and from 7 to 3600 g/mL for healthy and subclinical infected cows. Breeds might also differ in Lf contents as observed by Soyeurt et al. (2007) in cows but this would not explain these large differences. In addition, Chen et al. (2004) used their own method and other control standards. Nevertheless, we also found the significant effect of the infection status on the Lf content as described by Chen et al. (2004), although we investigated naturally infected goats without any symptoms of clinical mastitis instead of artificially infected animals. Compared to SCC and NAGase activity, Lf readings for infected and non-infected udder halves differed more distinctly in our study.
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Lf contents increased from the first to the last day of sampling following the increasing DIM. This might indicate that Lf is not affected by the breeding season as assumed for SCC and NAGase activity. For using Lf as a mastitis indicator this would be advantageous but has to be investigated before. 5. Conclusion Our study showed significant effects of mammary infections on SCC, Lf and NAGase activity in dairy goats. We also revealed effects of parity and the sampling day on SCC, Lf and NAGase activity, respectively. Given that Lf is not affected by the breeding season, it might be used to monitor udder health in goats. Therefore, further investigations on commercial dairy farms should focus on the effect of factors not related to mastitis, e.g. estrus, to prove a potential superiority over SCC as an indicator of mastitis in goats. Acknowledgments The authors thank the technicians of the Institute of Organic Farming, Trenthorst, and the laboratory staff of the MRI, Kiel, and of the Institute of Animal Science, Bonn, for their assistance in gaining and analysing the milk samples. References Arnould, V.M-R., Soyeurt, H., Gengler, N., Colinet, F.G., Georges, M.V., Bertozzi, C., Portetelle, D., Renaville, R., 2009. Genetic analysis of lactoferrin content in bovine milk. J. Dairy Sci. 92, 2151–2158. Aulrich, K., Barth, K., 2008. Intramammary infections caused by coagulasenegative staphylococci and the effect on somatic cell counts in dairy goats. Landbauforschung—vTI Agric. Forestry Res. 58, 59–64. Barth, K., Aulrich, K., 2007. Influence of oestrus on somatic cell count in milk of goats. In: Rubino, R., Sepe, L. (Eds.), International Symposium “The Quality of Goat Products”, pp. 139–141. Chagunda, M.G.G., Larsen, T., Bjerring, M., Ingvartsen, K.L., 2005. Lactate dehydrogenase and N-acetyl-b-d-glucosaminidase activities in bovine milk as measures of clinical mastitis. J. Dairy Sci. 88, 197–198. Chen, P.W., Chen, W.C., Mao, F.C., 2004. Increase of lactoferrin concentration in Mastitic goat milk. Vet. Med. Sci. 66, 345–350. Dulin, A.M., Paape, J.M., Schultze, W.D., Weinland, B.T., 1983. Effect of parity, stage of lactation, and intramammary infection on concentration of somatic cells and cytoplasmic particles in goat milk. J. Dairy Sci. 66, 2426–2433. Deutsche Veterinärmedizinische Gesellschaft (DVG), 2000. Leitlinien zur Entnahme von Milchproben unter antiseptischen Bedingungen und
Leitlinien zur Isolierung und Identifizierung von Mastitiserregern (Guidelines for Milk Sampling Under Aseptic Conditions and Guidelines for the Isolation and Identification of Mastitis Pathogens), ISBN 3-930511-81-9. Hagiwara, S., Kawai, K., Anri, A., Nagahata, H., 2003. Lactoferrin concentrations in milk from normal and subclinical mastitis cows. J. Vet. Med. Sci. 65, 319–323. Hiss, S., Meyer, T., Sauerwein, H., 2008. Lactoferrin concentrations in goat milk throughout lactation. Small Rumin. Res. 80, 87–90. International Dairy Federation (IDF), 1985. Laboratory methods for use in mastitis work. IDF Document 132, Brussels, Belgium. International Organization for Standardization (ISO), 2006. ISO13366-2: Milk-Enumeration of Somatic Cells—Part 2: Guidance on the Operation of Fluoro-opto-electronic Counters. Leitner, G., Merin, U., Silanikove, N., Ezra, E., Chaffer, M., Gollop, N., Winkler, M., Glickman, A., Saran, A., 2004. Effect of subclinical intramammary infection on somatic cell counts, NAGase activity and gross composition of goats’ milk. J. Dairy Res. 71, 311–315. Luengo, C., Sanchez, A., Corrales, J.C., Fernandez, C., Contreras, A., 2004. Influence of intramammary infection and non-infection factors on somatic cell counts in dairy goats. J. Dairy Res. 71, 169–174. Maisi, P., 1990. Milk NAGase, CMT and antitrypsin as indicators of caprine subclinical mastitis infections. Small Rumin. Res. 3, 493–501. McDougall, S., Voermans, M., 2002. Influence of estrus on somatic cell count in dairy goats. J. Dairy Sci. 85, 378–383. Miller, R.H., Paape, M.J., 1988. Effects of parity, bacteriological status, stage of lactation, and dry period on N-acetyl--d-glucosaminidase activity of milk and dry secretion. J. Dairy Sci. 71, 2508–2512. Moroni, P., Pisoni, G., Savoini, G., van Lier, E., Acuna, S., Damian, J.P., Meikle, A., 2007. Influence of estrus of dairy goats on somatic cell count, milk traits, and sex steroid receptors in the mammary gland. J. Dairy Sci. 90, 790–797. Nogai, K., Krömker, V., Gyódi, P., Hamann, J., 1996. Zur fluoreszenzspektroskopischen und photometrischen Bestimmung von N-Acetyl--d-glucosaminidase in Milch—Ein Methodenvergleich. In: Proc. 37. Tagung des Arbeitsgebietes Lebensmittelhygiene der DVG, Part II, pp. 299–306, ISBN 3-930511-35-5. Obara, Y., Komatsu, M., 1984. Relationship between n-acetyl--dglucosaminidase activity and cell count, lactose, chloride, or lactoferrin in cow milk. J. Dairy Sci. 67, 1043–1046. Paape, M.J., Wiggans, G.R., Bannerman, D.D., Thomas, D.L., Sanders, A.H., Contreras, A., Moroni, P., Miller, R.H., 2007. Monitoring goat and sheep milk somatic cell counts. Small Rumin. Res. 68, 114–125. Pirisi, A., Lauret, A., Dubeuf, J.P., 2007. Basic and incentive payments for goat and sheep milk in relation to quality. Small Rumin. Res. 68, 167–178. Raynal-Ljutovac, K., Pirisi, A., de Crémoux, R., Gonzalo, C., 2007. Somatic cells of goat and sheep milk: analytical, sanitary, productive and technological aspects. Small Rumin. Res. 68, 126–144. Soyeurt, H., Colinet, F.G., Arnould, V.M.-R., Dardenne, P., Bertozzi, C., Renaville, R., Portetelle, D., Gengler, N., 2007. Genetic variability of lactoferrin content estimated by mid-infrared spectrometry in bovine milk. J. Dairy Sci. 90, 4443–4450. Timms, L.L., Schultz, L.H., 1985. N-acetyl-B-d-glucosaminidase activity and somatic cells in goat milk. J. Dairy Sci. 68, 3363– 3366.