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J. Dairy Sci. 87:3623-3628
© American Dairy Science Association, 2004.

Evaluation of Rapid Somatic Cell Counters Under Different Analytical Conditions in Ovine Milk

C. Gonzalo1, J. C. Boixo2, J. A. Carriedo1 and F. San Primitivo1

1 Departamento de Producción Animal, Facultad de Veterinaria, Universidad de León, 24071-León, Spain
2 CENSYRA, Villaquilambre, 24193-León, Spain

Corresponding author: C. Gonzalo; e-mail: dp2cga{at}unileon.es.


   ABSTRACT
TOP
 ABSTRACT
INTRODUCTION
 MATERIALS AND METHODS
 RESULTS AND DISCUSSION
 CONCLUSIONS
 ACKNOWLEDGEMENTS
 REFERENCES
 
A total of 31 individual ovine milk samples, ranging between 30 and 2600 x 103 cells/mL, were divided into 8 aliquots/milk with the objective of studying the overall accuracy of 2 rapid somatic cell count (SCC) counters, one based on cytometry on disk (Fossomatic 360) and the other on flow cytometry (Fossomatic 5000), under 4 types of preservation (without preservation, bronopol, sodium azide, and potassium dichromate) and 2 analytical temperatures (40 and 60°C). All analyses were carried out in duplicate. In addition, each sample was analyzed in quadruplicate by reference microscopic method using Pyronin Y-methyl green as a stain. A second experiment using 13 samples divided into 20 aliquots/ sample, enabled repeatability to be studied depending on the values obtained in the SCC and on the SCC equipment used. Comparison of the methods was based on repeatability and accuracy studies (means comparison and regression studies vs. reference method). Both counters gave adequate repeatability and accuracy values in ovine milk, though the SCC obtained by Fossomatic 5000 was closer to the reference method and was somewhat more repeatable than Fossomatic 360. In the regression study, slope and intercept values were statistically different from their theoretical values (1.00 and 0.00, respectively) in the unpreserved samples but not in the preserved ones. In all cases, correlation coefficients very close to 1.00 were obtained. The preserved milk analyzed by flow cytometry gave optimal repeatability values (sr = 16.3 to 19.7 and sr% = 1.9 to 2.4), and their logSCC means (5.62 to 5.64) were not different from the reference value (5.63). Bronopol was the optimal preservative for the Fossomatic method. Analytical temperature did not contribute significantly to SCC variation, although disk cytometry gave slightly more repeatable SCC at 40° than at 60°C.

Key Words: ovine milk • somatic cell count • Fossomatic method • direct microscopic method

Abbreviation key: AZ = sodium azide, BR = bronopol, DMSCC = direct microscopic SCC, FSCC = Fossomatic SCC, F360 = Fossomatic 360, F5000 = Fossomatic 5000, PD = potassium dichromate, WP = without preservative.


   INTRODUCTION
TOP
 ABSTRACT
 INTRODUCTION
MATERIALS AND METHODS
 RESULTS AND DISCUSSION
 CONCLUSIONS
 ACKNOWLEDGEMENTS
 REFERENCES
 
Ovine milk is very important in Mediterranean countries, some of which have well-established milk recording schemes for the SCC of milk (Gonzalo et al., 1994; El-Saied et al., 1998). Accuracy of milk SCC is very important to dairy farmers and to the dairy industry because it is a useful predictor of IMI in dairy ewes (González-Rodríguez et al., 1995; Gonzalo et al., 2002). The Fossomatic SCC method (FSCC) is the most widely used SCC method in milk-testing laboratories, and its performance has been standardized for bovine milk (Schmidt-Madsen, 1975; Heald et al., 1977; Schmidt-Madsen, 1979; IDF, 1995). Basically, the Fossomatic is a DNA-specific counter based on the principle of optical fluorescence (IDF, 1995). The ethidium bromide dye penetrates the cell and forms a fluorescent complex with the nuclear DNA. The sample is exposed to blue light, which excites the dyed cells, making these emit red light. These red light pulses are magnified, counted by a photo multiplier detector, and multiplied by the defined working factor to compute the number of somatic cells per milliliter. In cytometry on disk, the detector counts the number of cells passing by the microscope on a rotating disk. In flow cytometry, the sample is pumped through a flow cell of very small diameter that allows only one somatic cell to pass at a time. Automation of this process means that large numbers of samples can be analyzed per hour in milk-testing laboratories. However, in ovine milk, overall accuracy of automatic SCC methods has been uniquely tested using equipment with a lower speed of sampling processing (90 samples/h) and based on disk cytometry (Gonzalo et al., 1993, 2003). These studies allowed analytical conditions of ovine milk samples for the SCC to be defined in some cases. However, we are not aware of any studies of the performance of high-speed equipment for processing samples, based on disk and flow cytometry. These systems were designed for use with bovine milk and are periodically checked against bovine milk standards. Their performance using milk of other species, therefore, should be studied. In this sense, rapid incubation times and speed of sample processing (e.g., defatting, deproteinizing), characteristic of these devices, could hinder the correct reading of the SCC in ovine milk, which has more total solids than bovine milk. In addition, numbers of sheep per flock in the Mediterranean area are quite considerable (e.g., approximately 400 to 500 ewes per flock in the Castilla y León region), so automatic, high-speed SCC counters are necessary for periodic health checks of all milking ewes. Moreover, standardizing fast FSCC counters for ovine milk is essential in SCC laboratories to order to guarantee accuracy and reproducibility of results.

In addition, recent studies on SCC variation showed that preservation, analytical temperature, and storage type have significant influence on the SCC in ovine milk (Gonzalo et al., 2003). Some of these factors should therefore be considered, especially those used routinely in the laboratory, when studying overall accuracy of different automatic SCC systems in ovine milk.

At present, direct microscopic SCC (DMSCC) is the reference method recommended by the IDF (1995) for SCC as a quality control in automated SCC counters. This well-known reference method is based on staining the milk film with methylene blue stain. Its only negative aspect is its lack of specificity between cells and cytoplasmic particles. These particles are present in ovine milk in reduced concentrations (Schalm et al., 1971; Gonzalo et al., 2003), but they might interfere with milk SCC, so comparisons using DNA-specific dyes, such as pyronin Y-methyl green, improve the performance of DMSCC in ovine milk (Gonzalo et al., 2003).

The objective of our study was to assess performance of 2 rapid FSCC counters, one based on disk cytometry and the other on flow cytometry, under different analytical preservation and temperature conditions. Repeatability and accuracy were evaluated using the DMSCC method (pyronin Y-methyl green stain) as the gold standard.


   MATERIALS AND METHODS
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
RESULTS AND DISCUSSION
 CONCLUSIONS
 ACKNOWLEDGEMENTS
 REFERENCES
 
From Spanish Churra ewes in different stages of lactation, a total of 31 individual 350-mL milk samples, ranging between 30 x 103 and 2600 x 103 cells/mL, were divided into eight 40-mL aliquots that, in turn, were divided into 4 groups according to the preservative used: 2 aliquots with bronopol (BR) (0.2%), 2 aliquots with potassium dichromate (PD) (0.1%), 2 aliquots with sodium azide (AZ) (0.3%), and 2 aliquots without preservative (WP). After heating in a water bath, one aliquot from each group was analyzed at 40°C and the other at 60°C, within 5 h after collection. After the aliquots had been prepared, they were refrigerated (5°C) until analysis. Analyses were carried out using 2 different counters of high-speed sample processing: Fossomatic 360 (F360; 360 samples/h), based on disk cytometry, and Fossomatic 5000 (F5000; 500 samples/ h), based on flow cytometry. In both cases, the analyses were carried out in duplicate. The study was carried out at the milk-testing laboratory of the CENSYRA (National Center for Animal Breeding and Reproduction) in León (Spain). Before and during the experiment, the counters were subjected to quality control intercomparative tests led by CECALAIT (Poligny, France). These ring tests were based on bovine milk standards of known SCC because no ovine milk standards are available in the market. In the experiment, the 2 counters were adjusted to slope (b) = 1.00 and intercept (a) = 0.

In addition, the SCC of each original milk sample was determined in quadruplicate by the direct microscopic method, according to IDF regulation 148A (IDF, 1995). Within 7 h after collection, milk samples were heated to 40°C in a water bath maintained for 15 min at that temperature before being cooled to 20°C with careful stirring. Then, 0.01 mL of milk was spread on a 1 cm2 (5 x 20 mm) area of a degreased microscopic slide and was dried in a horizontal position. The slides were previously treated with poly-L -lysine to increase the adherence of the film of milk. The method used to stain the film was Pyronin Y-methyl green, according to the methodology of Gonzalo et al. (2003). The working factor was 2200 in all cases.

This design enabled the study of repeatability and accuracy of the analytical conditions most frequently used in milk analysis laboratories. A total of 1116 analytical determinations were carried out, 992 by FSCC (360 and 5000) and 124 by DMSCC.

A second experiment was carried out to study repeatability of the FSCC counters only. Twenty subsamples per milk sample from 13 BR preserved ovine milk samples with varied numbers of cells (from 30 x 103 to 2100 x 103 cells/mL) were analyzed at 40°C by F360 and F5000, within 5 h after collection. The coefficients of variation for the results obtained from each sample were calculated for each SCC method.

Statistical Analyses
The DMSCC method and 16 FSCC analytical conditions were compared. These 16 conditions corresponded to 2 FSCC methods (F360 and F5000), 4 preservation types (WP, BR, PD, and AZ), and 2 analytical temperatures (40 and 60°C). Representations of all 17 analytical conditions were: DMSCC for reference method; F360-WP-40, F360-BR-40, F360-PD-40, F360-AZ-40, F360-WP-60, F360-BR-60, F360-PD-60, and F360-AZ-60 for disk cytometry; and F5000-WP-40, F5000-BR-40, F5000-PD-40, F5000-AZ-40, F5000-WP-60, F5000-BR-60, F5000-PD-60, and F5000-AZ-60 for flow cytometry.

These analytical conditions were compared according to 3 types of statistical studies: means comparison, standard deviations of repeatability, and regression.

Means comparison was carried out by using the general linear model (GLM) procedure of SAS (1992). In the statistical model used, ewe effect was considered random and the analytical condition effect fixed:


where Yijk= dependent variable logSCC, µ = mean, Ai= effect of 17 previously defined analytical conditions, Ej= effect of ewe (n = 31), and eijk= the residual effect in which 2 replicates were considered because analytical determinations were performed in duplicate.

Standard deviation of repeatability (srand its relative value: , where is the arithmetic mean of the SCC) for each analytical condition was calculated according to international IDF standard 128A (IDF, 1999), using the formula:


where q = number of samples and wi= absolute difference between duplicate results of FSCC methods. In the case of DMSCC, where the SCC was determined in quadruplicate, the standard deviation and coefficient of variation were calculated for each of the 31 individual milk samples. The mean values of the standard deviations of these samples were also calculated.

In the second experiment, repeatability was evaluated by standard deviation. Coefficients of variation for 20 aliquots/sample were calculated for 13 samples ranging between 30 and 2100 x 103 cells/mL.

Linear regression studies were performed to establish the relationship between DMSCC, used as the reference method, and each of the 16 analytical conditions considered for FSCC. As the SCC analytical conditions were carried out in duplicate for FSCC and in quadruplicate for MDSCC, the arithmetic mean of the 2 or 4 replicates was determined beforehand. Estimates were carried out from 31 observations (pairs of data) for each regression straight line. The corresponding intercept (a), coefficient of regression (b), and coefficient of determination (R2) were estimated in all cases. Analyses of differences between reference and instrumental results were performed by the t-test values observed for hypotheses b = 1.00 and a = 0.00 by using procedure REG in SAS (SAS, 1992).

Finally, a 2 x 4 x 2 factorial experiment consisting of 16 treatment combinations was analyzed using data from 31 ewes. The analytical determinations were carried out in duplicate (replicates). The model (GLM procedure in SAS), where ewe was random and other factors were fixed, consisted of ewe (Ei), FSCC method (Mj), preservation (Pk), analytical temperature (Tl), and interactions: logSCC was Yijklm= µ + Ei+ Mj+ Pk+ Tl+MPjk+ MTjl + PTkl + eijklm.


   RESULTS AND DISCUSSION
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS AND DISCUSSION
CONCLUSIONS
 ACKNOWLEDGEMENTS
 REFERENCES
 
Table 1Go shows the comparison of logSCC mean values obtained for DMSCC and 16 analytical conditions assayed by FSCC. LogSCC varied (P <0.05) between 5.67 and 5.57, whereas the reference value was 5.63 (MDSCC). Flow cytometry (F5000) produced greater (P <0.05) logSCC (5.62 to 5.67) than disk cytometry (F360: 5.57 to 5.61). The preserved milk analyzed by flow cytometry and the WP milk analyzed by disk cytometry produced SCC closest to reference values.


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  		Table 1. Least square means of logSCC obtained by direct microscopic (DMSCC) and Fossomatic (F) methods, geometric and arithmetic means of the SCC, and standard deviation of repeatability (srand sr%) for each of 16 analytical conditions.
 
Regarding repeated SCC, Table 1Go shows the standard deviation of repeatability for the SCC in the aliquots studied. The sr(44.21) and sr% (5.22) values for DMSCC aliquots were consistently greater than those assessed by FSCC, in agreement with the higher repeatability of the electronic methods vs. DSMCC demonstrated in bovine milk (Schmidt-Madsen, 1975). For FSCC, flow cytometry produced less variability among the replicates (sr: 16.27 to 21.07 and sr%: 1.89 to 2.55) than disk cytometry (sr: 17.81 to 35.28 and sr%: 2.31 to 4.56). Except in PD preserved milk, disk cytometry produced greater srvalues at 60°C (sr%: 3.25 to 4.56%) than at 40°C (sr%: 2.33 to 3.31%). These differences were less noticeable in the case of flow cytometry (Table 1Go). Milk preserved with BR and analyzed at 40°C by flow cytometry produced the lowest srvalues (16.27 and 1.89%), and its SCC was therefore the most repeatable. This analytical condition also was most accurate because its mean value (logSCC: 5.64) did not differ from the reference microscopic value (logSCC: 5.63).

A second experiment (Table 2Go) was carried out on BR preserved subsamples analyzed at 40°C, corresponding to 13 samples ranging between 30 and 2100 x 103 cells/ mL. The study clearly demonstrated that coefficients of variation decreased as number of cells increased, in most cases to below 5%, according to the IDF standard (1995). Also, lower coefficients of variation (1.09 to 10.9%) were observed for F5000 than for F360 (1.64 to 30.85%), which confirmed that repeatability was greater for flow cytometry than for disk cytometry. On the whole, the coefficients of variation for the automatic counters were smaller than those for the DMSCC method, which was less repeatable.


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  		Table 2. Repeatability of the Fossomatic methods (20 subsamples/milk) in ovine milk samples with different SCC (x103/mL).
 
Accuracy was estimated by means comparison and regression studies between instrumental and DMSCC results. Because of the repeatability produced by the DMSCC method, 4 analytical determinations were always carried out in each ovine milk sample. Table 3Go lists the standard deviations of the 31 studied milk samples, showing coefficients of variation of ≥7% in the samples with the SCC ≤700 x 103 cells/mL, which means that several analytical determinations must be carried out in the same sample to increase accuracy. This is important to the quality control of SCC instrumentation because a SCC ≤700 x 103 cells/mL includes the IMI discrimination threshold in ovine milk.


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  		Table 3. SCC (x103/mL) arithmetic means, standard deviations, and coefficients of variation of the 31 ovine milk samples analyzed by direct microscopic method in quadruplicate.
 
Correlations between DMSCC and FSCC (Table 4Go) were very high in all cases, close to 1.00. These values coincided with values reported for bovine milk by other authors for different working factors (Grappin and Jeunet, 1974; Heeschen, 1975; Schmidt-Madsen, 1975; Heald et al., 1977; Schmidt-Madsen, 1979). They were also similar to those obtained by Gonzalo et al. (1993, 2003) in ovine milk. However, the slope and intercept of the WP samples were different (P <0.05) from 1.00 and 0.00, respectively, indicating the need to preserve samples before the analytical determination of the SCC. In addition, the slope and intercept given by F360-AZ-60 differed (P <0.05) from their theoretical values, which was compatible with the fact that this analytical condition was the least accurate when compared with DMSCC (Table 1Go). Both SCC devices achieved good exactness of calibration for the rest of the analytical conditions.


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  		Table 4. Coefficients of regression (b), intercept (a), and R2 values based on regression analyses between direct microscopic and Fossomatic methods and analytical conditions.
 
Ewe, FSCC method, preservation, and interaction method x analytical temperature contributed significantly to the SCC variation. Whereas this SCC variation was significant (P <0.001) for the aforementioned method and preservation effects, it was of less importance (P <0.05) in the case of method x temperature interaction. Flow cytometry gave greater (P <0.001) logSCC values (5.64) than disk cytometry (5.60). In contrast, the WP samples produced greater (P <0.05) values (5.64) than the BR (5.62), PD (5.61), and AZ (5.60) preserved samples. Higher SCC in the WP samples and lower SCC in the AZ preserved samples were demonstrated in a previous study using FSCC in ovine milk (Gonzalo et al., 2003). The WP and BR preserved aliquots had the closest logSCC to that of the reference method (5.63) but were greater (P <0.05) than the AZ preserved samples.


   CONCLUSIONS
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS AND DISCUSSION
 CONCLUSIONS
ACKNOWLEDGEMENTS
 REFERENCES
 
The 2 rapid SCC counters gave adequate overall accuracy in ovine milk; however, F5000, based on flow cytometry, was slightly more accurate and repeatable than F360, based on disk cytometry. Analytical temperature did not affect SCC accuracy, but it did affect repeatability, especially in F360. The regression study made evident the need to preserve samples before analytical determination of the SCC. Bronopol was the preservative of choice for FSCC analysis.

With regard to routine sampling from test day or bulk tank milk recordings, variations brought about by such methods may not be so important in determining the health status of sheep. However, uniformity of preservation and analytical temperature are essential for intra- and interlaboratory quality control tests, with the aim of guaranteeing reproducibility of SCC results.


   ACKNOWLEDGEMENTS
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS AND DISCUSSION
 CONCLUSIONS
 ACKNOWLEDGEMENTS
REFERENCES
 
The authors wish to thank the staff members at CENSYRA (National Centre for Animal Breeding and Reproduction), Villaquilambre, León (Spain) for their disinterested collaboration.

Received for publication April 16, 2004. Accepted for publication June 2, 2004.


   REFERENCES
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS AND DISCUSSION
 CONCLUSIONS
 ACKNOWLEDGEMENTS
 REFERENCES
 


El-Saied, U. M., J. A. Carriedo, and F. San Primitivo. 1998. Heritability of test day somatic cell counts and its relationship with milk yield and protein percentage in dairy ewes. J. Dairy Sci. 81:2956–2961.[Abstract]

González-Rodríguez, M. C., C. Gonzalo, F. San Primitivo, and P. Cármenes. 1995. Relationship between somatic cell count and intramammary infection of the half udder in dairy ewes. J. Dairy Sci. 78:2753–2759.[Abstract]

Gonzalo, C., A. Ariznabarreta, J. A. Carriedo, and F. San Primtivo. 2002. Mammary pathogens and their relationship with somatic cell count and milk yield losses in dairy ewes. J. Dairy Sci. 85:1460–1467.[Abstract]

Gonzalo, C., J. A. Baro, J. A. Carriedo, and F. San Primitivo. 1993. Use of the Fossomatic method to determine somatic cell counts in sheep milk. J. Dairy Sci. 76:115–119.[Abstract]

Gonzalo, C., J. A. Carriedo, J. A. Baro, and F. San Primitivo. 1994. Factors influencing variation of test day milk yield, somatic cell count, fat and protein in dairy sheep. J. Dairy Sci. 77:1537–1542.[Abstract]

Gonzalo, C., J. R. Martínez, J. A. Carriedo, and F. San Primitivo. 2003. Fossomatic cell-counting on ewe milk: Comparison with direct microscopy and study of variation factors. J. Dairy Sci. 86:138–145.[Abstract/Free Full Text]

Grappin, R., and R. Jeunet. 1974. Premiers essais de l’appareil Fossomatic pour la détermination automatique du nombre de cellules du lait. Lait 54:627–644.

Heald, C. W., G. M. Jones, S. C. Nickerson, W. N. Patterson, and W. E. Vinson. 1977. Preliminary evaluation of the Fossomatic somatic cell counter for analysis of individual cow samples in a central testing laboratory. J. Food Prot. 40:523–526.

Heeschen, W. 1975. Determination of somatic cells in milk (technical aspects of counting). Bull. Int. Dairy Fed. 85:79–92.

International Dairy Federation. 1995. Enumeration of somatic cells. FIL-IDF Standard no. 148A. IDF, Brussels, Belgium.

International Dairy Federation. 1999. Definition and evaluation of the overall accuracy of indirect methods of milk analysis application to calibration procedure and quality control in the dairy laboratory. FIL-IDF Standard no. 128A. IDF, Brussels, Belgium.

SAS. 1992. SAS/STAT User’s Guide, Version 6. 10th ed. SAS Institute, Inc., Cary, NC.

Schalm, O. W., E. J. Carroll, and N. C. Jain. 1971. Bovine Mastitis. Lea & Febiger, Philadelphia, PA.

Schmidt-Madsen, P. 1975. Fluoro-opto-electronic cell-counting on milk. J. Dairy Res. 42:227–239.

Schmidt-Madsen, P. 1979. Influence of storage and preservation of milk samples on microscopic and Fossomatic somatic cell counts. Nord. Vet.-Med. 31:449–454.


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