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Animal Science Journal (2014) 85, 714–721
doi: 10.1111/asj.12180
ORIGINAL ARTICLE Evaluation of Tunisian milk quality in dairy herds: Inter-relationship between chemical, physical and hygienic criteria Ahmed GARGOURI, Houda HAMED, Besma BEN ALI, Abdelfettah ELFEKI and Radhouane GDOURA Unité de Physiopathologie Environnementale, Valorisation des Molécules Bioactives et Modélisation Mathématique, Département des Sciences de la Vie, Faculté des Sciences de Sfax, Sfax, Tunisia
ABSTRACT The objective of this paper was to evaluate the global milk quality in Tunisian dairy herds. Samples of milk were analyzed for chemical, physical and hygienic parameters. Milk total solids, fat content and density were consistently correlated and one of them can be used as a chemical indicator of milk quality. The somatic cell count value of 689 × 103/mL was higher than the recommended threshold. All milk samples were positive for the major pathogen Staphylococcus aureus. These hygienic parameters were related more closely with chloride content, minerals and electrical conductivity, which allow them to be used as indicators of mammary gland infection. It was concluded that milk producers have at hand rapid and easy tools for assessing the overall quality of milk.
Key words: chemical, physical and hygienic criteria, raw milk, somatic cell count.
INTRODUCTION During the past few years, the dairy industry in Tunisia has made spectacular growth concerning both the number of cattle and milk production, making it possible for Tunisia to change from an importer to a selfsufficiency situation in 2000. Indeed, this industry has become a strategic sector that occupies an important place in the agricultural, economic, social and human health domains. In dairy farms, the improvement in income can only come from two different axes: (i) increasing output by increasing productivity per cow or by increasing the number of milked cows; and (ii) improving the overall quality of milk. Technical, organizational and institutional barriers limiting the volume of milk processed by the sector in a country such as Tunisia have been extensively studied (scarcity of forage, nutritional imbalances, seasonal forage supply and weak supervision of breeders). On the other hand, aspects related to the improvement of the quality of raw milk have been little studied. However, the development of the overall quality (physical, chemical and hygienic) of this product within the specific context of breeding cattle in Tunisia should have been earlier imposed by conducting applied research in this area. When quality is discussed, especially for a product as variable as milk, multiple subjective interpretations may be adopted in accordance with the defined cri© 2014 Japanese Society of Animal Science
teria. Thus, depending on the individual and the levels within the industry, the quality of milk will tend to vary. Some tend to rely on organoleptic or even visual characteristics to evaluate milk (especially upstream and downstream, i.e. farmers and consumers), while others will use quantitative analytical criteria, such as fat and protein contents or the rate of milk contamination with microorganisms (dairy processing). With the development of reliable and repeatable analytical methods, there are three fundamental criteria for characterizing milk quality: physical criteria, chemical criteria and hygienic condition. Physical criteria are indicative of the general appearance of the milk. They are most often associated with the density, acidity and temperature of the milk (Fox 1997; Sraïri et al. 2005). However, the ability of this criteria for assessing the overall quality of the milk is
Correspondence: Ahmed Gargouri, Unité de Physiopathologie Environnementale, Valorisation des Molécules Bioactives et Modélisation Mathématique. Département des Sciences de la Vie. Faculté des Sciences de Sfax, BP 1171, 3000 Sfax, Tunisia. (Email: [email protected]) Received 4 May 2013; accepted for publication 15 November 2013. [Correction added on 17 April 2014, after first online publication: Authors’ affiliation has been amended.]
GLOBAL MILK QUALITY IN DAIRY HERDS
still very limited, unless fraud or deterioration is suspected (acidification due to improper storage, diluting). Thus, this criteria is not enough alone to characterize the quality of milk. Chemical criteria are associated with milk nutrient contents (Fox 1997). In this regard, the industry has developed laboratory analytical methods for assaying the content of various components in milk that provide the nutritional value of the product and its use in dairy processing. These are traditionally the protein, fat, and to a lesser degree calcium contents (Fox 1997; Sraïri et al. 2005). These analyses provide a complete picture of a fundamental aspect of the quality of milk, for both food and industrial uses. In some countries, these criteria are very important and are included in patterns of payment to milk producers. Hygienic criteria aim to complete the picture of quality, endeavoring to characterize microbiological aspects (Fox 1997; Michel et al. 2001; Sraïri et al. 2006). Thus, they reveal an image of microorganism contamination in milk. Various methods have been developed according to the type of microbial flora count. The most commonly used is the measure of total aerobic mesophilic flora (TAF), that is, all the microorganisms in the milk at a temperature of 30°C, total and fecal coliforms and human pathogenic flora: the most coomon are Staphylococcus aureus, Salmonella sp. and Listeria monocytogenes. Inter-relationships between different aspects of dairy milk quality are not well documented. The aim of the present study was to evaluate the association between chemical, physical and hygienic parameters in dairy herds. The objective was also to offer to dairy producers and industries some practical analytical criteria to evaluate overall milk quality, and in particular hygienic quality.
MATERIALS AND METHODS Raw milk collection and storage From May to December 2012, a total of 80 bulk samples of cow (Tunisian Holstein) raw milk was collected into sterile bottles at the morning milking from five farms randomly selected in the region of Sfax (an important milk production area in Tunisia) and transported in thermos-cool boxes (at 4°C) to the laboratory of the Faculty of Science, Sfax University (transport duration not exceeding 1 h). All of the sampled farms are equipped with automated milking systems. There is no grazing area in any of the sample farms and herd nutrition is based on roughages and concentrates (aboveground system). As soon as they were delivered to the laboratory, each bulk milk sample (about 1000 mL) was maintained at 4°C without preservatives. All physicochemical parameters were determined on the day of sampling. In addition, another aliquot of about 100 mL of milk sample was aseptically discarded and stored at −20°C for further bacteriological analysis. For each milk sample, all of the analytical assessments were carried out in duplicate. Animal Science Journal (2014) 85, 714–721
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Chemical criteria of milk Milk total solid was determined by drying the sample at 102°C for 24 h according to the IDF method (IDF 1987). After that, the same samples were ashed in a muffle furnace at 550°C for 5 h to determine milk mineral content (AOAC 1990). Milk was also analyzed for fat content by the Gerber method (IDF 1981). The basis for analyzing chloride content was Mohr’s method using a digital conductivity meter analyzer (Consort C861, Consort bvba, Turnhout, Belgium) according to Gargouri et al. (2013). Milk (20 mL at 25°C) was homogenized with 250 mL of distilled water. Nitric acid (5 drops) was added to the mixture and milk chloride was titrated with silver nitrate (0.08 mol/L). The value indicated by the conductivity meter decreases slightly to reach equivalence. At equivalence, the dosage was stopped and the volume of silver nitrate ‘V in mL’ was determined. Milk chloride content was estimated by the following formula:
Chloride content (g L ) = 0.142 × V
Physical criteria of milk Milk was analyzed for titratable acidity (AOAC 1995). The acidity of milk was expressed in degrees Doronic (°D) which is equivalent to a grade of 0.1 g of lactic acid/L of milk (AOAC 1995), and density was measured using a lactodensitometer (AOAC 1997). The electrical conductivity (EC) was determined at 25°C in milliSiemens (mS/cm) using the same digital conductivity meter analyzer. The alcohol test consists of adding 2 mL of alcohol (70%) to 2 mL of milk and shaking this in a test tube. If a precipitate is formed the test is said to be positive and such milk is held to be of poor hygienic quality.
Hygienic criteria of milk Somatic cell counts (SCC) Total SCCs were determined microscopically in smears stained with May-Grünwald and Giemsa, according to the method of Gargouri et al. (2008) adapted to cow milk and inspired by the approach of Gonzalo et al. (1998) used for ewe’s milk. For each sample of milk, two preparations were performed. The enumeration concerned 16 areas. The working factor was 393 174 in all cases and the average values were used for statistical analyses. The working factor was obtained taking into account field diameter (0.18 mm), observed total area (100 mm2) and milk volume (0.01 mL).
Microbiological analyses Decimal dilutions of milk samples were made in sterile saline and 0.1 mL of the appropriate dilution was plated onto selected media. To determine the mesophilic TAF, dilutions were plated on nutrient agar and incubated at 30°C for 72 h following the standard ISO 4833 (2003). Counts were expressed as colony forming units per mL of milk (cfu/mL). To detect Staphylococcus aureus in milk, 0.1 mL of the dilutions were plated on Baird-Parker agar and incubated at 37°C for 24-36 h. Typical black to grayish colonies were identified as staphylococci using a standard method (ISO 6888-1 1999). Salmonella spp. was detected using the horizontal method ISO 6579 (2002) and Listeria monocytogenes according to ISO 11290-1 (1996). The results were expressed as positive or negative for recovering Listeria monocytogenes in a 25 mL aliquot. © 2014 Japanese Society of Animal Science
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Data analysis Statistical evaluations were performed using SPSS software Version 13 (SPSS Inc., Chicago, IL, USA). Prior to statistical analysis, TAF, Staphylococcus aureus and SCC were transformed to log10 in order to provide for normal distribution and skewness reduction. To evaluate relations among the studied parameters, Pearson correlation coefficients (r) were computed and linear regression equations were constructed. Results are indicated as statistically significant at P < 0.05.
RESULTS AND DISCUSSION The mean, standard error of mean (SEM) and range of each measured parameter of bulk tank milk at the five farms on the sampling day are listed in Table 1.
Chemical criteria of milk The determination of fat in foods and especially in dairy products is important for both regulatory and nutritional information purposes (Britz et al. 2008). The minimum and maximum values recorded of milk fat content are respectively 17 and 41 g/L with an average of 30 g/L (Table 1). We note that 73% of samples had a milk fat content less than 36 g/L (national average). This result can be explained by the extensive use of concentrate in dairy cow rations in the Sfax area where the farming system practiced is only above ground (Ben Salem & Bouraoui 2009; Moujahed et al. 2009; Gargouri et al. 2013). The average amounts of total solids (10.82%) and mineral substances (0.53%) are normally encountered in Tunisian dairy herds (Gargouri et al. 2008; Ben Salem & Bouraoui 2009).
Physical criteria of milk Measurement of some physical properties is used to assess milk quality (Fox 1997). The level of acidity
indicates freshness and determines technological suitability of milk (Wilkinson et al. 2001; Czerniewicz et al. 2006). The milk acidity at sampling day was 20.75°D, which is slightly higher compared with fresh milk (between 15 and 18°D). This level was also mentioned in a previous study (Gargouri et al. 2008). Faulty milking hygiene, agitation during milking and transport to the laboratory may increase active acidity of milk (Jandal 1996; Czerniewicz et al. 2006). Changes in milk acidity can be related to changes in the proportions of salts and proteins. A special role is played by the level of soluble phosphates and citrates, and Ca2+ ions. A part of micellar calcium phosphate passes to the soluble phase, thus increasing the concentration of Ca2+ ions and disturbing the structure of micelles, which considerably affects milk acidity (Czerniewicz et al. 2006). Milk density ranged from 1.027 to 1.034 with an average value of 1.029, in accordance with the study of the APIA (2008) in several Tunisian herds. In this study, 73% of the tested samples had values lower than 1.030, which does not comply with Tunisian standards.
Hygienic criteria of milk As expected, the level of SCC from dairy farmers showed great variations over sampling days. Arithmetic mean SCC per herd during the study ranged from 98 × 103 to 2499 × 103 cells/mL (Table 1). These SCC represent a wide range of raw milk quality that can be encountered in the Tunisian dairy herds (Gargouri et al. 2008, 2013; Rekik et al. 2008), indicating healthy and infected cows were present which provided a wide range of data for examining the correlation among the various parameters measured. The health status of the animals’ udders (mastitis or inflammation) is the most important cause of elevated milk SCC. Age of animal,
Table 1 Means and distribution of milk characteristics at sampling day
Mean Chemical criteria Total solids (%) Minerals (%) Fat content (g/L) Chloride content (g/L) Physical criteria Acidity (°Doronic) Density EC (mS/cm) Hygienic criteria SCC (×103/mL) Log SCC Log TAF Log S.aureus Listeria Salmonella Alcohol test
SEM
Minimum
Maximum
10.82 0.53 30.2 1.13
0.55 0.12 5.8 0.15
10.00 0.30 17.0 0.84
12.45 0.78 41.0 1.41
20.75 1.029 5.39
3.71 0.002 1.36
15.00 1.027 2.72
29.00 1.034 7.94
689 607 5.69 0.37 5.41 1.45 3.36 1.60 Absence Absence Normal milk (40%) Beginning of alteration (37%) Alteration (23%)
98 4.99 2.60 0.30
2499 6.40 8.60 5.99
EC, electrical conductivity; SEM, standard error of mean; SCC, somatic cells count; TAF, total aerobic mesophilic flora.
© 2014 Japanese Society of Animal Science
Animal Science Journal (2014) 85, 714–721
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stage of lactation, season, milk yield, husbandry practices used and climate are also known to influence milk SCC (Verdi & Barbano 1991; Harmon 1994). The mean of SCC (689 × 103/mL, Table 1) was higher than the recommended threshold for healthy cows in the US or in European countries (200 × 103 to 400 × 103 cells/mL). Therefore, 37% of the total samples of this study had more than 400 × 103 cells/mL or herds with probable subclinical mastitis and 23% more than 800 × 103 cells/mL or herds with probable clinical mastitis (Somers et al. 2003). This result indicates the high incidence of infected cows in Tunisian dairy herds. Thus, careful attention to proper milking practices could help to minimize this problem. It is also recommended that the fluid milk processors consider implementation of premium quality payments to motivate dairy farmers to obtain low SCC milk, following the national trend of a reduction in somatic cells of milk (Gargouri et al. 2013). Electrical conductivity, which increases during the infection of dairy cows, is also one of the diagnostic methods for detection of subclinical mastitis. EC is determined by the concentration of anions and cations. According to Kitchen (1981), Norberg et al. (2004) and Gargouri et al. (2013), mastitis increases the EC of milk because of changes in ionic concentrations. As a result of the damage to the udder tissue, concentrations of Na+ and Cl- increase, this leads to increased EC of milk from the infected udder. [Correction added on 17 April 2014, after first online publication: ‘Cl’ has been amended to ‘Cl-’.] In our study, EC at sampling day ranged between 2.72 and 7.94 mS/ cm, with an average of 5.39 mS/cm (Table 1), in line with the observations of Gargouri et al. (2013). Enumeration of total aerobic flora reflects the general microbiological quality of the product. The TAF ranged from 4 × 102 to 4 × 108 (2.6 to 8.6 log10 cfu/mL) with an average of 2 × 107 cfu/mL (5.41 log10 cfu/mL, Table 1), in agreement with other studies in Tunisia (Ksontini et al. 2011). This level was relatively higher compared with the threshold of 5 × 103 to 6 × 105 cfu/mL proposed by Ercolini et al. (2009) and the national and international standards for milk and dairy products. This increase in milk TAF reflects that the procedures used during milking and cleaning equipment are inadequate (Desmasures & Guéguen 1997; Ksontini et al. 2011). This contamination of milk might be due to initial contamination originating from the udder surface, quality of cleaning water, milking utensils and materials used for filtering the milk. Milk residues on equipment surfaces provide nutrients for growth and multiplication of bacteria that contaminate milk from subsequent milkings. Among the contagious pathogens, the most common are Staphylococcus aureus and Streptococcus agalactiae. Staphylococcus aureus was detected in all Animal Science Journal (2014) 85, 714–721
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herds of this study and the mean value was significantly higher (11 × 104 cfu/mL = 3.36 log10 cfu/mL, Table 1). This result demonstrated that Tunisian dairy herds were characterized by high prevalence of this pathogen. It was commented that milking order, milking technique, type of housing, teat dipping and dry cow therapy can affect the prevalence of mastitis pathogens (Hutton et al. 1990; Moret-Stalder et al. 2009). Fortunately, these organisms are easily destroyed by pasteurization. Concerning the two remaining groups, Salmonella and Listeria, the most dangerous pathogens to humans, we were not able to detect their presence in any herd. The alcohol test is widely used as a simple and rapid indicator of milk freshness. It is also a practical means of determining the propensity of milk for heat coagulation. The test aids in detection of abnormal milk, such as colostrum, milk from animals in late lactation, milk from animals suffering from mastitis and milk in which mineral balance has been disturbed. According to this test, 40% of milk samples were normal, 37% were beginning to alter and 23% were altered (Table 1) and not able to be heat processed (abnormal milk). This result can be related to the poor hygienic conditions in which milk has been produced and handled.
Inter-relations between studied parameters The most significant interactions between the different parameters are outlined in Figures 1 and 2. Mean density of tank milk was positively correlated with total solids and negatively correlated with fat content (Table 2 and Fig. 1), as mentioned in previous studies (Mouffok et al. 2013). There was no significant correlation between acidity and all parameters of bulk milk at the sampling day (Table 2). The measuring of the somatic cell count in milk is the standard method, but the analysis technique is problematic for routine use in herds. Measurement of EC of milk for diagnosis of subclinical mastitis is a new technique and is not frequently used by the farmers in Tunisia. In addition, it is a rapid, easy and inexpensive test to indirectly determine the SCC in milk (Gargouri et al. 2013). In the current study, the regression predicting EC according to SCC is reported in Table 3.
Total solids
Fat Content
Density
Figure 1 Significant correlations between chemical parameters in raw milk.
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718 A. GARGOURI et al.
Table 2 Correlation coefficients (r) for relationships between the composition parameters of bulk milk at sampling day
Min FC CC Acidity Density EC SCC TAF SA AT
TS
Mi
FC
CC
Acid.
Den.
EC
SCC
TAF
SA
0.057 −0.831** 0.023 0.193 0.766** 0.021 0.009 0.062 −0.242 0.108
−0.156 0.984** 0.221 −0.009 0.985** 0.985** 0.358 0.650** 0.548**
−0.119 −0.285 −0.761** −0.112 −0.106 −0.210 0.255 −0.069
−0.174 −0.039 0.999** 0.999** 0.323 0.729** 0.522**
0.349 0.174 0.183 0.302 −0.249 0.395
−0.041 −0.041 0.197 −0.359 0.001
0.999** 0.322 0.733** 0.553**
0.332 0.732** 0.553**
0.288 0.519**
0.377
**P < 0.01; ***P < 0.001. Acid., acidity; CC, chloride content; Den., density; EC, electrical conductivity; FC, fat content; Mi, minerals; SA, Staphylococcus aureus; SCC, somatic cells count; TAF, total aerobic mesophilic flora; TS, total solids. [Correction added on 17 April 2014, after first online publication: ‘−174’ in Acidity row and CC column has been corrected to ‘−0.174’.]
Table 3 Classification of milks according to SCC, EC, chloride and minerals thresholds
3
SCC (×10 /mL) Log SCC EC (mS/cm) Chloride (g/L) Minerals (%)
Equation
Normal
Subclinical
Clinical
Somers et al. (2003)
≤400 ≤5.60 ≤5.00 ≤1.10 ≤0.50
400–800 5.60–5.90 5.00–6.10 1.10–1.21 0.50–0.60
≥800 ≥5.90 ≥6.10 ≥1.21 ≥0.60
−15.40 + 3.65 Log SCC −1.13 + 0.39 Log SCC −1.33 + 0.33 Log SCC
EC, electrical conductivity; SCC, somatic cells count. [Correction added on 17 April 2014, after first online publication: Equations under ‘EC(mS/cm)’, ‘Chloride (g/L)’ and ‘Minerals (%)’ have been shifted one row down as they were previously incorrectly placed.]
As observed, milk EC at milking day was directly associated (r = 0.999; P < 0.001) with SCC (EC = −15.40 + 3.65 × Log10 SCC), in agreement with the findings of Sheldrake et al. (1983), Kas¸ikci et al. (2012) and Gargouri et al. (2013). This high correlation might imply that EC alone (or chloride concentration) is a sufficient indicator of hygienic quality of raw cow’s milk and can also be used as an integral component of a control program. Based on this relation and the SCC threshold classifications of Somers et al. (2003), we hypothesize that EC should be < 5.0 mS/cm for healthy cows, between 5.0 and 6.1 mS/cm for herds with probable subclinical mastitis and > 6.1 mS/cm for herds with probable clinical mastitis (Table 3). This classification is similar to that proposed by Gargouri et al. (2013) but different from that suggested by Woolford et al. (1998): healthy cows (EC < 6.45), subclinical mastitis (6.45 < EC < 6.85) and probable clinical mastitis (EC > 6.85). Other different thresholds were also proposed by Bruckmaier et al. (2004), Norberg et al. (2004) and Ilie et al. (2010). This divergence can be explained by the milk fraction being investigated (composite samples, foremilk samples), the milking interval, the variety of diagnostic tests for mastitis (somatic cells, California Mastitis Test score, bacteriological findings), the method of determination of somatic cells (direct microscopy in our study) and the differences in sample temperatures at which EC was measured (Oshima 1978; Fernando et al. 1982; Fernando & Spahr 1983; Nielen et al. 1992; Hamann & Zecconi 1998). © 2014 Japanese Society of Animal Science
Chloride content can be adopted as a hygienic criteria of milk. As expected, the association between this parameter and SCC was higher (Chloride = – 1.13 + 0.39 × Log10 SCC; Table 3) in accordance with others studies (Bruckmaier et al. 2004; Ogola et al. 2007; Gargouri et al. 2013). According to SCC threshold classifications, chloride content appears to be < 1.10, between 1.10 and 1.21, and > 1.21 g/L for healthy, subclinical and clinical mastitic udders, respectively. As with EC and chloride, mineral content was closely correlated with SCC (Mineral = – 1.33 + 0.33 × Log10 SCC; Table 3) as previously reported by Ogola et al. (2007) and Kas¸ikci et al. (2012). They concluded that the minerals from the milk of cows can be used as indicators of mastitis infection. According to SCC threshold classifications, mineral content should be < 0.50% for healthy cows, between 0.50 and 0.60% for herds with probable subclinical mastitis and > 0.60 for herds with probable clinical mastitis (Table 3). Furthermore, EC had a high correlation with chloride content of milk (r = 0.999, P < 0.001) as commented by Fernando et al. (1985) and Gargouri et al. (2013). Therewith, 99% of the variation in milk EC was attributed to the variation in milk chloride concentration. The damage to the udder tissue and the increase in the permeability of mammary epithelium potentiated the transfer of Na+ and Cl− ions from blood to milk (Fernando et al. 1985; Werner-Misof et al. 2007) which leads to increased EC of milk from the infected quarter. Thus one of these criteria can be used to evaluate the hygienic status of dairy herds. Animal Science Journal (2014) 85, 714–721
GLOBAL MILK QUALITY IN DAIRY HERDS
Minerals
Chloride
SCC
EC
Stap. Aureus
Alcohol Test
Total Aerobic Flora
Figure 2 Significant correlations between hygienic parameters in raw milk.
Staphylococcus aureus is globally one of the most important pathogens causing contagious mastitis (Zecconi et al. 2005; Michel et al. 2011) resulting in substantial economic loss (Sears & McCarthy 2003; Seegers et al. 2003). Staphylococcus aureus is often referred to as a contagious pathogen, because it is commonly spread from infected cows to other noninfected cows at milking (Sears & McCarthy 2003; Olde Riekerink et al. 2008). As expected, there was a high association between Staphylococcus aureus and SCC and the majority of the other hygienic parameters (Fig. 2). According to this relation, Staphylococcus aureus is responsible for 53% of cases of mastitis in dairy cows. An intra-mammary infection with Staphylococcus aureus usually results in an increased SCC, as was previously reported (Zadoks et al. 2001; Ogola et al. 2007; Moret-Stalder et al. 2009). In this study, there was also a significant relation between EC and Staphylococcus aureus (r = 0.733, P < 0.01) as mentioned by Kuplulu et al. (1995). The alcohol test is useful as an indication of the mineral balance of milk and not as an index of developed acidity. It was highly correlated with minerals and with the other hygienic parameters (Fig. 2). The TAF was only positively correlated with the alcohol test, but not with the other parameters. Hence, this criterion alone was insufficient to evaluate the hygienic quality of milk.
Conclusions Our study confirmed the high level of milk cell count in Tunisian dairy herds, most likely due to high mastitis infection rates and to poor hygienic practices. This level exceeds the permissible limits in European countries and the USA. This fact was supported by the prevalence of Staphylococcus aureus in all studied Animal Science Journal (2014) 85, 714–721
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herds. Furthermore, additional efforts are required by farmers to improve the mammary health state and hygienic conditions during and after milking. According to the results of this study, several sources of hygienic criteria, such as conductivity, SCC, minerals, chloride content, Staphylococcus aureus flora and alcohol test can be integrated in order to inform the farmer on the status of udder health and milk quality. The most promising parameters for monitoring subclinical mastitis are EC and chloride content of milk. The determination of either of them may prevent bulk milk cell count exceeding particular thresholds. On the other hand, TAF level obtained during milking day was also higher and exceeding the normal threshold, supporting the assumption that all these herds were confronted with problems in milking hygiene. However, this parameter alone was insufficient to evaluate the hygienic quality of milk. This level was only positively correlated with the alcohol test, but not with the other characteristics. In conclusion, the milk producers and processing industry can deploy several simple and rapid tools to evaluate the overall quality of milk, especially hygienic quality.
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Kuplulu S, Vurali R, Izgur H, Kılıcog˘lu C, Bas¸tan A, Kayzmaz M, Erdeger J. 1995. Subklinik mastitisler in tanısında ‘milk checker’ ın kullanılması. Ankara University Veterinary Faculty 42, 281–284. Michel A, Syring C, Steiner A, Graber HU. 2011. Intramammary infections with the contagious Staphylococcus aureus genotype B in Swiss dairy cows are associated with low prevalence of coagulase-negative staphylococci and Streptococcus spp. Veterinary Journal 188, 313–317. Michel V, Hauwuy A, Chamba JF. 2001. La flore microbienne de laits crus de vache: diversité et influence des conditions de production. Le Lait 81, 575–592. Moret-Stalder S, Fournier C, Miserez R, Albini S, Doherr MG, Reist M, Schaeren W, Kirchhofer M, Graber HU, Steiner A, Kaufmann T. 2009. Prevalence study of Staphylococcus aureus in quarter milk samples of dairy cows in the Canton of Bern, Switzerland. Preventive Veterinary Medicine 88, 72–76. Mouffok CE, Madani T, Semara L, Ayache N, Rahal A. 2013. Correlation between body condition score, blood biochemical metabolites and milk yield and quality in Algerian Montbéliarde cattle. Pakistan Veterinary Journal 33, 191–194. Moujahed N, Dabboussi I, Bel Haj Ammar S, Darej S. 2009. Effects of concentrate feeding strategy on milk production and composition in dairy cows. Journal of Dairy Science 3, 3–7. Nielen M, Deluyker H, Schukken YH, Brand A. 1992. Electrical conductivity of milk: measurement, modifiers, and meta analysis of mastitis detection performance. Journal of Dairy Science 75, 606–614. Norberg E, Hogeveen H, Korsgaard IR, Friggens NC, Sloth KHMN, Løvendahl P. 2004. Electrical conductivity of milk: ability to predict mastitis status. Journal of Dairy Science 87, 1099–1107. Ogola H, Shitandi A, Nanua J. 2007. Effect of mastitis on raw milk compositional quality. Journal of Veterinary Science 8, 237–242. Olde Riekerink RGM, Barkema HW, Kelton DF, Scholl DT. 2008. Incidence rate of clinical mastitis on Canadian dairy farms. Journal of Dairy Science 91, 366–1377. Oshima M. 1978. Empirical formula for correcting electrical conductivity values of milk in relation to temperature. Japanese Journal of Zootechnical Science 49, 180–188. Rekik B, Ajili N, Belhani H, Ben Gara A, Rouissi H. 2008. Effect of somatic cell count on milk and protein yields and female fertility in Tunisian Holstein dairy cows. Livestock Science 116, 309–317. Sears PM, McCarthy KK. 2003. Management and treatment of staphylococcal mastitis. Veterinary Clinics of North America: Food Animal Practice 19, 171–185 (vii). Seegers H, Fourichon C, Beaudeau F. 2003. Production effects related to mastitis and mastitis economics in dairy cattle herds. Veterinary Research 34, 475–491. Sheldrake RF, McGregor GD, Hoare RJT. 1983. Somatic cell count, electrical conductivity, and serum albumin concentration for detecting bovine mastitis. Journal of Dairy Science 66, 548–555. Somers JM, O’Brien B, Meaney WJ, Kelly AL. 2003. Heterogeneity of proteolytic enzyme activities in milk samples of different somatic cell count. Journal of Dairy Research 70, 45–50. Sraïri MT, Hasni Alaoui I, Hamama A, Faye B. 2005. Relationship between rearing practices and cows’ milk global
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doi: 10.1111/asj.12180
ORIGINAL ARTICLE Evaluation of Tunisian milk quality in dairy herds: Inter-relationship between chemical, physical and hygienic criteria Ahmed GARGOURI, Houda HAMED, Besma BEN ALI, Abdelfettah ELFEKI and Radhouane GDOURA Unité de Physiopathologie Environnementale, Valorisation des Molécules Bioactives et Modélisation Mathématique, Département des Sciences de la Vie, Faculté des Sciences de Sfax, Sfax, Tunisia
ABSTRACT The objective of this paper was to evaluate the global milk quality in Tunisian dairy herds. Samples of milk were analyzed for chemical, physical and hygienic parameters. Milk total solids, fat content and density were consistently correlated and one of them can be used as a chemical indicator of milk quality. The somatic cell count value of 689 × 103/mL was higher than the recommended threshold. All milk samples were positive for the major pathogen Staphylococcus aureus. These hygienic parameters were related more closely with chloride content, minerals and electrical conductivity, which allow them to be used as indicators of mammary gland infection. It was concluded that milk producers have at hand rapid and easy tools for assessing the overall quality of milk.
Key words: chemical, physical and hygienic criteria, raw milk, somatic cell count.
INTRODUCTION During the past few years, the dairy industry in Tunisia has made spectacular growth concerning both the number of cattle and milk production, making it possible for Tunisia to change from an importer to a selfsufficiency situation in 2000. Indeed, this industry has become a strategic sector that occupies an important place in the agricultural, economic, social and human health domains. In dairy farms, the improvement in income can only come from two different axes: (i) increasing output by increasing productivity per cow or by increasing the number of milked cows; and (ii) improving the overall quality of milk. Technical, organizational and institutional barriers limiting the volume of milk processed by the sector in a country such as Tunisia have been extensively studied (scarcity of forage, nutritional imbalances, seasonal forage supply and weak supervision of breeders). On the other hand, aspects related to the improvement of the quality of raw milk have been little studied. However, the development of the overall quality (physical, chemical and hygienic) of this product within the specific context of breeding cattle in Tunisia should have been earlier imposed by conducting applied research in this area. When quality is discussed, especially for a product as variable as milk, multiple subjective interpretations may be adopted in accordance with the defined cri© 2014 Japanese Society of Animal Science
teria. Thus, depending on the individual and the levels within the industry, the quality of milk will tend to vary. Some tend to rely on organoleptic or even visual characteristics to evaluate milk (especially upstream and downstream, i.e. farmers and consumers), while others will use quantitative analytical criteria, such as fat and protein contents or the rate of milk contamination with microorganisms (dairy processing). With the development of reliable and repeatable analytical methods, there are three fundamental criteria for characterizing milk quality: physical criteria, chemical criteria and hygienic condition. Physical criteria are indicative of the general appearance of the milk. They are most often associated with the density, acidity and temperature of the milk (Fox 1997; Sraïri et al. 2005). However, the ability of this criteria for assessing the overall quality of the milk is
Correspondence: Ahmed Gargouri, Unité de Physiopathologie Environnementale, Valorisation des Molécules Bioactives et Modélisation Mathématique. Département des Sciences de la Vie. Faculté des Sciences de Sfax, BP 1171, 3000 Sfax, Tunisia. (Email: [email protected]) Received 4 May 2013; accepted for publication 15 November 2013. [Correction added on 17 April 2014, after first online publication: Authors’ affiliation has been amended.]
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still very limited, unless fraud or deterioration is suspected (acidification due to improper storage, diluting). Thus, this criteria is not enough alone to characterize the quality of milk. Chemical criteria are associated with milk nutrient contents (Fox 1997). In this regard, the industry has developed laboratory analytical methods for assaying the content of various components in milk that provide the nutritional value of the product and its use in dairy processing. These are traditionally the protein, fat, and to a lesser degree calcium contents (Fox 1997; Sraïri et al. 2005). These analyses provide a complete picture of a fundamental aspect of the quality of milk, for both food and industrial uses. In some countries, these criteria are very important and are included in patterns of payment to milk producers. Hygienic criteria aim to complete the picture of quality, endeavoring to characterize microbiological aspects (Fox 1997; Michel et al. 2001; Sraïri et al. 2006). Thus, they reveal an image of microorganism contamination in milk. Various methods have been developed according to the type of microbial flora count. The most commonly used is the measure of total aerobic mesophilic flora (TAF), that is, all the microorganisms in the milk at a temperature of 30°C, total and fecal coliforms and human pathogenic flora: the most coomon are Staphylococcus aureus, Salmonella sp. and Listeria monocytogenes. Inter-relationships between different aspects of dairy milk quality are not well documented. The aim of the present study was to evaluate the association between chemical, physical and hygienic parameters in dairy herds. The objective was also to offer to dairy producers and industries some practical analytical criteria to evaluate overall milk quality, and in particular hygienic quality.
MATERIALS AND METHODS Raw milk collection and storage From May to December 2012, a total of 80 bulk samples of cow (Tunisian Holstein) raw milk was collected into sterile bottles at the morning milking from five farms randomly selected in the region of Sfax (an important milk production area in Tunisia) and transported in thermos-cool boxes (at 4°C) to the laboratory of the Faculty of Science, Sfax University (transport duration not exceeding 1 h). All of the sampled farms are equipped with automated milking systems. There is no grazing area in any of the sample farms and herd nutrition is based on roughages and concentrates (aboveground system). As soon as they were delivered to the laboratory, each bulk milk sample (about 1000 mL) was maintained at 4°C without preservatives. All physicochemical parameters were determined on the day of sampling. In addition, another aliquot of about 100 mL of milk sample was aseptically discarded and stored at −20°C for further bacteriological analysis. For each milk sample, all of the analytical assessments were carried out in duplicate. Animal Science Journal (2014) 85, 714–721
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Chemical criteria of milk Milk total solid was determined by drying the sample at 102°C for 24 h according to the IDF method (IDF 1987). After that, the same samples were ashed in a muffle furnace at 550°C for 5 h to determine milk mineral content (AOAC 1990). Milk was also analyzed for fat content by the Gerber method (IDF 1981). The basis for analyzing chloride content was Mohr’s method using a digital conductivity meter analyzer (Consort C861, Consort bvba, Turnhout, Belgium) according to Gargouri et al. (2013). Milk (20 mL at 25°C) was homogenized with 250 mL of distilled water. Nitric acid (5 drops) was added to the mixture and milk chloride was titrated with silver nitrate (0.08 mol/L). The value indicated by the conductivity meter decreases slightly to reach equivalence. At equivalence, the dosage was stopped and the volume of silver nitrate ‘V in mL’ was determined. Milk chloride content was estimated by the following formula:
Chloride content (g L ) = 0.142 × V
Physical criteria of milk Milk was analyzed for titratable acidity (AOAC 1995). The acidity of milk was expressed in degrees Doronic (°D) which is equivalent to a grade of 0.1 g of lactic acid/L of milk (AOAC 1995), and density was measured using a lactodensitometer (AOAC 1997). The electrical conductivity (EC) was determined at 25°C in milliSiemens (mS/cm) using the same digital conductivity meter analyzer. The alcohol test consists of adding 2 mL of alcohol (70%) to 2 mL of milk and shaking this in a test tube. If a precipitate is formed the test is said to be positive and such milk is held to be of poor hygienic quality.
Hygienic criteria of milk Somatic cell counts (SCC) Total SCCs were determined microscopically in smears stained with May-Grünwald and Giemsa, according to the method of Gargouri et al. (2008) adapted to cow milk and inspired by the approach of Gonzalo et al. (1998) used for ewe’s milk. For each sample of milk, two preparations were performed. The enumeration concerned 16 areas. The working factor was 393 174 in all cases and the average values were used for statistical analyses. The working factor was obtained taking into account field diameter (0.18 mm), observed total area (100 mm2) and milk volume (0.01 mL).
Microbiological analyses Decimal dilutions of milk samples were made in sterile saline and 0.1 mL of the appropriate dilution was plated onto selected media. To determine the mesophilic TAF, dilutions were plated on nutrient agar and incubated at 30°C for 72 h following the standard ISO 4833 (2003). Counts were expressed as colony forming units per mL of milk (cfu/mL). To detect Staphylococcus aureus in milk, 0.1 mL of the dilutions were plated on Baird-Parker agar and incubated at 37°C for 24-36 h. Typical black to grayish colonies were identified as staphylococci using a standard method (ISO 6888-1 1999). Salmonella spp. was detected using the horizontal method ISO 6579 (2002) and Listeria monocytogenes according to ISO 11290-1 (1996). The results were expressed as positive or negative for recovering Listeria monocytogenes in a 25 mL aliquot. © 2014 Japanese Society of Animal Science
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Data analysis Statistical evaluations were performed using SPSS software Version 13 (SPSS Inc., Chicago, IL, USA). Prior to statistical analysis, TAF, Staphylococcus aureus and SCC were transformed to log10 in order to provide for normal distribution and skewness reduction. To evaluate relations among the studied parameters, Pearson correlation coefficients (r) were computed and linear regression equations were constructed. Results are indicated as statistically significant at P < 0.05.
RESULTS AND DISCUSSION The mean, standard error of mean (SEM) and range of each measured parameter of bulk tank milk at the five farms on the sampling day are listed in Table 1.
Chemical criteria of milk The determination of fat in foods and especially in dairy products is important for both regulatory and nutritional information purposes (Britz et al. 2008). The minimum and maximum values recorded of milk fat content are respectively 17 and 41 g/L with an average of 30 g/L (Table 1). We note that 73% of samples had a milk fat content less than 36 g/L (national average). This result can be explained by the extensive use of concentrate in dairy cow rations in the Sfax area where the farming system practiced is only above ground (Ben Salem & Bouraoui 2009; Moujahed et al. 2009; Gargouri et al. 2013). The average amounts of total solids (10.82%) and mineral substances (0.53%) are normally encountered in Tunisian dairy herds (Gargouri et al. 2008; Ben Salem & Bouraoui 2009).
Physical criteria of milk Measurement of some physical properties is used to assess milk quality (Fox 1997). The level of acidity
indicates freshness and determines technological suitability of milk (Wilkinson et al. 2001; Czerniewicz et al. 2006). The milk acidity at sampling day was 20.75°D, which is slightly higher compared with fresh milk (between 15 and 18°D). This level was also mentioned in a previous study (Gargouri et al. 2008). Faulty milking hygiene, agitation during milking and transport to the laboratory may increase active acidity of milk (Jandal 1996; Czerniewicz et al. 2006). Changes in milk acidity can be related to changes in the proportions of salts and proteins. A special role is played by the level of soluble phosphates and citrates, and Ca2+ ions. A part of micellar calcium phosphate passes to the soluble phase, thus increasing the concentration of Ca2+ ions and disturbing the structure of micelles, which considerably affects milk acidity (Czerniewicz et al. 2006). Milk density ranged from 1.027 to 1.034 with an average value of 1.029, in accordance with the study of the APIA (2008) in several Tunisian herds. In this study, 73% of the tested samples had values lower than 1.030, which does not comply with Tunisian standards.
Hygienic criteria of milk As expected, the level of SCC from dairy farmers showed great variations over sampling days. Arithmetic mean SCC per herd during the study ranged from 98 × 103 to 2499 × 103 cells/mL (Table 1). These SCC represent a wide range of raw milk quality that can be encountered in the Tunisian dairy herds (Gargouri et al. 2008, 2013; Rekik et al. 2008), indicating healthy and infected cows were present which provided a wide range of data for examining the correlation among the various parameters measured. The health status of the animals’ udders (mastitis or inflammation) is the most important cause of elevated milk SCC. Age of animal,
Table 1 Means and distribution of milk characteristics at sampling day
Mean Chemical criteria Total solids (%) Minerals (%) Fat content (g/L) Chloride content (g/L) Physical criteria Acidity (°Doronic) Density EC (mS/cm) Hygienic criteria SCC (×103/mL) Log SCC Log TAF Log S.aureus Listeria Salmonella Alcohol test
SEM
Minimum
Maximum
10.82 0.53 30.2 1.13
0.55 0.12 5.8 0.15
10.00 0.30 17.0 0.84
12.45 0.78 41.0 1.41
20.75 1.029 5.39
3.71 0.002 1.36
15.00 1.027 2.72
29.00 1.034 7.94
689 607 5.69 0.37 5.41 1.45 3.36 1.60 Absence Absence Normal milk (40%) Beginning of alteration (37%) Alteration (23%)
98 4.99 2.60 0.30
2499 6.40 8.60 5.99
EC, electrical conductivity; SEM, standard error of mean; SCC, somatic cells count; TAF, total aerobic mesophilic flora.
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stage of lactation, season, milk yield, husbandry practices used and climate are also known to influence milk SCC (Verdi & Barbano 1991; Harmon 1994). The mean of SCC (689 × 103/mL, Table 1) was higher than the recommended threshold for healthy cows in the US or in European countries (200 × 103 to 400 × 103 cells/mL). Therefore, 37% of the total samples of this study had more than 400 × 103 cells/mL or herds with probable subclinical mastitis and 23% more than 800 × 103 cells/mL or herds with probable clinical mastitis (Somers et al. 2003). This result indicates the high incidence of infected cows in Tunisian dairy herds. Thus, careful attention to proper milking practices could help to minimize this problem. It is also recommended that the fluid milk processors consider implementation of premium quality payments to motivate dairy farmers to obtain low SCC milk, following the national trend of a reduction in somatic cells of milk (Gargouri et al. 2013). Electrical conductivity, which increases during the infection of dairy cows, is also one of the diagnostic methods for detection of subclinical mastitis. EC is determined by the concentration of anions and cations. According to Kitchen (1981), Norberg et al. (2004) and Gargouri et al. (2013), mastitis increases the EC of milk because of changes in ionic concentrations. As a result of the damage to the udder tissue, concentrations of Na+ and Cl- increase, this leads to increased EC of milk from the infected udder. [Correction added on 17 April 2014, after first online publication: ‘Cl’ has been amended to ‘Cl-’.] In our study, EC at sampling day ranged between 2.72 and 7.94 mS/ cm, with an average of 5.39 mS/cm (Table 1), in line with the observations of Gargouri et al. (2013). Enumeration of total aerobic flora reflects the general microbiological quality of the product. The TAF ranged from 4 × 102 to 4 × 108 (2.6 to 8.6 log10 cfu/mL) with an average of 2 × 107 cfu/mL (5.41 log10 cfu/mL, Table 1), in agreement with other studies in Tunisia (Ksontini et al. 2011). This level was relatively higher compared with the threshold of 5 × 103 to 6 × 105 cfu/mL proposed by Ercolini et al. (2009) and the national and international standards for milk and dairy products. This increase in milk TAF reflects that the procedures used during milking and cleaning equipment are inadequate (Desmasures & Guéguen 1997; Ksontini et al. 2011). This contamination of milk might be due to initial contamination originating from the udder surface, quality of cleaning water, milking utensils and materials used for filtering the milk. Milk residues on equipment surfaces provide nutrients for growth and multiplication of bacteria that contaminate milk from subsequent milkings. Among the contagious pathogens, the most common are Staphylococcus aureus and Streptococcus agalactiae. Staphylococcus aureus was detected in all Animal Science Journal (2014) 85, 714–721
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herds of this study and the mean value was significantly higher (11 × 104 cfu/mL = 3.36 log10 cfu/mL, Table 1). This result demonstrated that Tunisian dairy herds were characterized by high prevalence of this pathogen. It was commented that milking order, milking technique, type of housing, teat dipping and dry cow therapy can affect the prevalence of mastitis pathogens (Hutton et al. 1990; Moret-Stalder et al. 2009). Fortunately, these organisms are easily destroyed by pasteurization. Concerning the two remaining groups, Salmonella and Listeria, the most dangerous pathogens to humans, we were not able to detect their presence in any herd. The alcohol test is widely used as a simple and rapid indicator of milk freshness. It is also a practical means of determining the propensity of milk for heat coagulation. The test aids in detection of abnormal milk, such as colostrum, milk from animals in late lactation, milk from animals suffering from mastitis and milk in which mineral balance has been disturbed. According to this test, 40% of milk samples were normal, 37% were beginning to alter and 23% were altered (Table 1) and not able to be heat processed (abnormal milk). This result can be related to the poor hygienic conditions in which milk has been produced and handled.
Inter-relations between studied parameters The most significant interactions between the different parameters are outlined in Figures 1 and 2. Mean density of tank milk was positively correlated with total solids and negatively correlated with fat content (Table 2 and Fig. 1), as mentioned in previous studies (Mouffok et al. 2013). There was no significant correlation between acidity and all parameters of bulk milk at the sampling day (Table 2). The measuring of the somatic cell count in milk is the standard method, but the analysis technique is problematic for routine use in herds. Measurement of EC of milk for diagnosis of subclinical mastitis is a new technique and is not frequently used by the farmers in Tunisia. In addition, it is a rapid, easy and inexpensive test to indirectly determine the SCC in milk (Gargouri et al. 2013). In the current study, the regression predicting EC according to SCC is reported in Table 3.
Total solids
Fat Content
Density
Figure 1 Significant correlations between chemical parameters in raw milk.
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718 A. GARGOURI et al.
Table 2 Correlation coefficients (r) for relationships between the composition parameters of bulk milk at sampling day
Min FC CC Acidity Density EC SCC TAF SA AT
TS
Mi
FC
CC
Acid.
Den.
EC
SCC
TAF
SA
0.057 −0.831** 0.023 0.193 0.766** 0.021 0.009 0.062 −0.242 0.108
−0.156 0.984** 0.221 −0.009 0.985** 0.985** 0.358 0.650** 0.548**
−0.119 −0.285 −0.761** −0.112 −0.106 −0.210 0.255 −0.069
−0.174 −0.039 0.999** 0.999** 0.323 0.729** 0.522**
0.349 0.174 0.183 0.302 −0.249 0.395
−0.041 −0.041 0.197 −0.359 0.001
0.999** 0.322 0.733** 0.553**
0.332 0.732** 0.553**
0.288 0.519**
0.377
**P < 0.01; ***P < 0.001. Acid., acidity; CC, chloride content; Den., density; EC, electrical conductivity; FC, fat content; Mi, minerals; SA, Staphylococcus aureus; SCC, somatic cells count; TAF, total aerobic mesophilic flora; TS, total solids. [Correction added on 17 April 2014, after first online publication: ‘−174’ in Acidity row and CC column has been corrected to ‘−0.174’.]
Table 3 Classification of milks according to SCC, EC, chloride and minerals thresholds
3
SCC (×10 /mL) Log SCC EC (mS/cm) Chloride (g/L) Minerals (%)
Equation
Normal
Subclinical
Clinical
Somers et al. (2003)
≤400 ≤5.60 ≤5.00 ≤1.10 ≤0.50
400–800 5.60–5.90 5.00–6.10 1.10–1.21 0.50–0.60
≥800 ≥5.90 ≥6.10 ≥1.21 ≥0.60
−15.40 + 3.65 Log SCC −1.13 + 0.39 Log SCC −1.33 + 0.33 Log SCC
EC, electrical conductivity; SCC, somatic cells count. [Correction added on 17 April 2014, after first online publication: Equations under ‘EC(mS/cm)’, ‘Chloride (g/L)’ and ‘Minerals (%)’ have been shifted one row down as they were previously incorrectly placed.]
As observed, milk EC at milking day was directly associated (r = 0.999; P < 0.001) with SCC (EC = −15.40 + 3.65 × Log10 SCC), in agreement with the findings of Sheldrake et al. (1983), Kas¸ikci et al. (2012) and Gargouri et al. (2013). This high correlation might imply that EC alone (or chloride concentration) is a sufficient indicator of hygienic quality of raw cow’s milk and can also be used as an integral component of a control program. Based on this relation and the SCC threshold classifications of Somers et al. (2003), we hypothesize that EC should be < 5.0 mS/cm for healthy cows, between 5.0 and 6.1 mS/cm for herds with probable subclinical mastitis and > 6.1 mS/cm for herds with probable clinical mastitis (Table 3). This classification is similar to that proposed by Gargouri et al. (2013) but different from that suggested by Woolford et al. (1998): healthy cows (EC < 6.45), subclinical mastitis (6.45 < EC < 6.85) and probable clinical mastitis (EC > 6.85). Other different thresholds were also proposed by Bruckmaier et al. (2004), Norberg et al. (2004) and Ilie et al. (2010). This divergence can be explained by the milk fraction being investigated (composite samples, foremilk samples), the milking interval, the variety of diagnostic tests for mastitis (somatic cells, California Mastitis Test score, bacteriological findings), the method of determination of somatic cells (direct microscopy in our study) and the differences in sample temperatures at which EC was measured (Oshima 1978; Fernando et al. 1982; Fernando & Spahr 1983; Nielen et al. 1992; Hamann & Zecconi 1998). © 2014 Japanese Society of Animal Science
Chloride content can be adopted as a hygienic criteria of milk. As expected, the association between this parameter and SCC was higher (Chloride = – 1.13 + 0.39 × Log10 SCC; Table 3) in accordance with others studies (Bruckmaier et al. 2004; Ogola et al. 2007; Gargouri et al. 2013). According to SCC threshold classifications, chloride content appears to be < 1.10, between 1.10 and 1.21, and > 1.21 g/L for healthy, subclinical and clinical mastitic udders, respectively. As with EC and chloride, mineral content was closely correlated with SCC (Mineral = – 1.33 + 0.33 × Log10 SCC; Table 3) as previously reported by Ogola et al. (2007) and Kas¸ikci et al. (2012). They concluded that the minerals from the milk of cows can be used as indicators of mastitis infection. According to SCC threshold classifications, mineral content should be < 0.50% for healthy cows, between 0.50 and 0.60% for herds with probable subclinical mastitis and > 0.60 for herds with probable clinical mastitis (Table 3). Furthermore, EC had a high correlation with chloride content of milk (r = 0.999, P < 0.001) as commented by Fernando et al. (1985) and Gargouri et al. (2013). Therewith, 99% of the variation in milk EC was attributed to the variation in milk chloride concentration. The damage to the udder tissue and the increase in the permeability of mammary epithelium potentiated the transfer of Na+ and Cl− ions from blood to milk (Fernando et al. 1985; Werner-Misof et al. 2007) which leads to increased EC of milk from the infected quarter. Thus one of these criteria can be used to evaluate the hygienic status of dairy herds. Animal Science Journal (2014) 85, 714–721
GLOBAL MILK QUALITY IN DAIRY HERDS
Minerals
Chloride
SCC
EC
Stap. Aureus
Alcohol Test
Total Aerobic Flora
Figure 2 Significant correlations between hygienic parameters in raw milk.
Staphylococcus aureus is globally one of the most important pathogens causing contagious mastitis (Zecconi et al. 2005; Michel et al. 2011) resulting in substantial economic loss (Sears & McCarthy 2003; Seegers et al. 2003). Staphylococcus aureus is often referred to as a contagious pathogen, because it is commonly spread from infected cows to other noninfected cows at milking (Sears & McCarthy 2003; Olde Riekerink et al. 2008). As expected, there was a high association between Staphylococcus aureus and SCC and the majority of the other hygienic parameters (Fig. 2). According to this relation, Staphylococcus aureus is responsible for 53% of cases of mastitis in dairy cows. An intra-mammary infection with Staphylococcus aureus usually results in an increased SCC, as was previously reported (Zadoks et al. 2001; Ogola et al. 2007; Moret-Stalder et al. 2009). In this study, there was also a significant relation between EC and Staphylococcus aureus (r = 0.733, P < 0.01) as mentioned by Kuplulu et al. (1995). The alcohol test is useful as an indication of the mineral balance of milk and not as an index of developed acidity. It was highly correlated with minerals and with the other hygienic parameters (Fig. 2). The TAF was only positively correlated with the alcohol test, but not with the other parameters. Hence, this criterion alone was insufficient to evaluate the hygienic quality of milk.
Conclusions Our study confirmed the high level of milk cell count in Tunisian dairy herds, most likely due to high mastitis infection rates and to poor hygienic practices. This level exceeds the permissible limits in European countries and the USA. This fact was supported by the prevalence of Staphylococcus aureus in all studied Animal Science Journal (2014) 85, 714–721
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herds. Furthermore, additional efforts are required by farmers to improve the mammary health state and hygienic conditions during and after milking. According to the results of this study, several sources of hygienic criteria, such as conductivity, SCC, minerals, chloride content, Staphylococcus aureus flora and alcohol test can be integrated in order to inform the farmer on the status of udder health and milk quality. The most promising parameters for monitoring subclinical mastitis are EC and chloride content of milk. The determination of either of them may prevent bulk milk cell count exceeding particular thresholds. On the other hand, TAF level obtained during milking day was also higher and exceeding the normal threshold, supporting the assumption that all these herds were confronted with problems in milking hygiene. However, this parameter alone was insufficient to evaluate the hygienic quality of milk. This level was only positively correlated with the alcohol test, but not with the other characteristics. In conclusion, the milk producers and processing industry can deploy several simple and rapid tools to evaluate the overall quality of milk, especially hygienic quality.
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