1967

Journal of Food Protection, Vol. 71, No. 10, 2008. Pages 1967-1973

Environmental Sampling To Predict Fecal Prevalence ofSalmonella in an Intensively Monitored Dairy Herd

J. S. VAN KESSEL,I* J. S. KARNS,' D. R. WOLFGANG, 2 E. HOVINGH, 2 B. M. JAYARAO, 2 C. P. VAN TASSELL, 3 AND

Y. H. SCHUKKEN4

Environmental Microbial Safety Laborator y and 3 1tovine Functional Genomics Laboratory, Animal and Natural Resources Institute, U.S. Departmentof Agriculture. Agricultural Research Service, Beltsville, Mar yland 20705; 2Departinent of Veterinary and Biomedical Sciences, Pennsylvania State

University, Universit y Park, Penns y lvania 16802; and 'Quality Milk Production Services, Cornell University, Ithaca, New York 14853. USA

MS 07-683: Received 21 December 2007/Accepted 2 May 2008

ABSTRACT

Although dairy cattle are known reservoirs for salmonellae, cattle that are shedding this organism are often asymptomaticand difficult to identify. A dairy herd that was experiencing a sustained, subclinical outbreak of Salmonella enferica subsp.enterica Cerro was monitored for 2 years. Fecal samples from the lactating cows were collected every 6 to 8 weeks and testedfor the presence of Salmonella. Fecal prevalence of Salmonella fluctuated throughout the observation period and ranged from8 to 88%. Manure composites and water trough samples were collected along with the fecal samples, and bulk milk and milkfilters were cultured for the presence of Salmonella on a weekly basis. Over 90% of the manure composites—representinghigh-animal-traffic areas—were positive at each sampling. Salmonella was detected in 11% of milk samples and in 66% ofthe milk filters. Results of weekly bulk milk quality testing (i.e., bulk tank somatic cell score, standard plate count, preliminaryincubation count) were typically well within acceptable ranges. Milk quality variables had low correlations with herd Sal-monella fecal prevalence. When observed over time, sampling period average prevalence of Salmonella in milk filters closelyparalleled fecal prevalence of Salmonella in the herd. Based on results of this study, milk filters appear to be an effectivemethod for monitoring shedding prevalence at the herd level. In-line filter testing is also a more sensitive measure of Sal-monella, and perhaps other pathogens, in raw milk than testing the milk alone.

Foodborne illnesses are a major concern in the UnitedStates. In 1999. the Centers for Disease Control and Pre-vention estimated that as many as 76 million human ill-nesses per year were the result of foodborne diseases (18).Although declining incidence has been reported for illness-es caused by Cwnpvlobacter, Shigella, and Listeria, the in-cidence of infection caused by Salmonella and enterohem-orrhagic Escherichia coli has remained relatively stable (4).While efforts to reduce incidence in some areas such asSalmonella infection froni ground beef and eggs were ap-parently successful, the incidence of bacterial infectionsfrom other commodities increased (4).

Bacterial pathogens such as Salmonella and E. colt0157:H7 frequently colonize the gastrointestinal tract ofcattle, and human illnesses caused by these bacteria areoften associated with consumption of beef, raw milk, andraw milk products (6, 17, 19, 22, 23, 27). Efforts at reduc-ing contamination of these foods are focused on mitigatingthe farm-level contamination and at the processing and han-dling systems after the milk or animals have left the farm.On-farm miti gation approaches include increased bioseeur-ity, rodent and bird control, nutritional strategies, vaccina-tion, and management strategies that reduce cross-contam-

Author for correspondence. Tel: 301-504-8287: Fax: 301-504-6608:E-mail: joann.vankessel@ars.usda.gov.Mention of a trade name, vendor, proprietary product, or specific equip-ment is not a guarantee or a warranty by the U.S. Department of Ag-riculture and does not imply an approval to the exclusion of other prod-ucts or vendors that also may be suitable.

ination between animal groups and contamination duringthe milking process (1, 15, 16, 21, 25, 28).

Virulence of salmonellae in humans is highly variable,but all salmonellae are considered to be human pathogens.However, many bacteria that are infectious for humans livecommensally in cows and do not cause disease, includingSalmonella enterica. Salmonella shedding in asymptomaticcows has been well documented, and this infection may ormay not impact health, milk production, or reproduction (3,5, 7, 11, 13). When animals display clinical symptoms ofsalmonellosis, these animals can be isolated from the herdor segregated within the herd. However, in the absence ofclinical symptoms, producers are usually unaware that aherd is infected and, therefore, that exposure to those ani-mals and milk and meat may put people at risk.

We previously described an endemic infection of Sal-monella Cerro in a U.S. dairy herd (26). The fecal sheddingprevalence rate in the lactating cows ranged from 8.4 to88% over a 2-year period, with no symptoms of salmonel-losis observed. Prevalence was monitored by collecting le-cal grab samples from each of the cows (dry and lactating)every 6 to 8 weeks. During that time, bulk milk sampleswere collected weekly and analyzed for standard bacterialcounts and somatic cell counts, as well as for the presenceof Salmonella. In-line milk filters were also tested for thepresence of Salmonella. In-line filters are designed to re-move coarse particles from the milk as milk is pumped intothe bulk tank. The filter is not specifically designed to filter

1968VAN KESSEL ET AL. Food Prot., Vol. 71, No. 10

bacteria. However, other studies have shown that analysisof filters is a useful tool in pathogen surveillance (1. 9).

Whole-herd fecal sampling is disruptive, labor inten-sive, and not always practical as a herd screening method.An alternative indicator method for assessing herd preva-lence would be beneficial for both researchers and produc-ers. Composite manure samples can be collected for anal-ysis, but this collection is not routine, and the matrix com-plexity of the samples presents additional analysis chal-lenges. However, bulk milk samples are currently tested bymost, if not all, dairy farms on a regular basis, and manyof the bacteria and bacterial groups tested are directly re-lated to fecal contamination. The additional step of addinga milk filter to this testing regime is relatively simple.

The objective of this analysis was to characterize therelationship between environmental, bulk milk, and in-linefilter analysis and herd prevalence of Salmonella infection.The ultimate objective was to determine if routine moni-toring of these samples was a useful indicator of the Sal-monella status of the cows in this herd.

MATERIALS AND METHODSFarm description. The herd and the logistics of herd sam-

pling were described previously (26). In short, the farm was lo-cated in Pennsylvania in close proximity to other dairy farms. Theherd consisted of approximately 105 mature cows that werehoused in a three-row free-stall barn and milked twice daily. Thecows were divided into three groups (group 1, group 2, and dry),and each was housed in a separate section of the barn. Cows fromgroup 1 and group 2 were kept in a shared holding pen whilewaiting milking, and used a common alley to return to the barn.Alleys were scraped daily and manure from group I and group 2was pushed through the dry group pen alleys during the cleaningprocess. Heifers were raised at a contract facility separated fromthe farm, and replacement animals were occasionally purchased.After a Salmonella outbreak was detected in September 2004, asampling interval of approximately 6 to 8 weeks for environmen-tal samples and for all cows in the milking herd was implemented.

Sample collection. Fecal samples were collected directlyfrom the rectum, using individual disposable sleeves and placedinto sterile vials. All lactating cows, dry cows, and pre-fresh heif -ers were sampled at each visit (102 to 113 animals). For manurecomposites, grab samples from the alleys (dry cow, group 1,group 2, holding pen, return alley) were mixed, and representativealiquots were placed in Whirl-Pak bags (Nasco, Ft. Atkinson,Wis.). Water samples (500 ml or 1 liter) were obtained from fourtroughs (dry cow, group 2, group la, group lb) by mixing thewater and submersing a sterile bottle in each trough. Source waterwas obtained from the milk house sink after running the tap for5 mm. Bulk milk and in-line milk filters were collected asepticallyonce per week after the morning milking on a day after a milkpickup. Milk was collected in 50-ml conical tubes (three tubes),and filters were placed in sterile bags.

All samples were packed on ice and transported overnight tothe Environmental Microbial Safety Laboratory in Beltsville.Maryland, except for one weekly bulk milk tube (50 ml), whichwas either shipped overnight or hand carried to the milk testinglaboratory at The Pennsylvania State University.

Bacterial analysis. Upon arrival at the laboratory, approxi-mately 25 g of feces or environmental manure composite wasweighed into a filtered stomacher bag (GSl Creos Corporation,

Japan). diluted (2 to 1 [wt/wt]) with 1% buffered peptone waterand pummeled in an automatic bag mixer (BagMixer, InterScienceLaboratories. Inc.. Weymouth. Mass.) for 2 mm. Milk filters werecut into small (30 to 50 cm 2 ) pieces and placed in a filtered stom-acher bag, diluted (2 to 1 [wt/wt]) with 1% buffered peptone waterand pummeled in an automatic bag mixer for 2 mm. The bag wasremoved from the mixer, filter pieces were repositioned to thebottom of the bag, and the bag was pummeled for 2 additionalminutes. For enrichment of Salmonella, 5 ml of filtrate or 5 mlof milk was added to 5 ml of double-strength tetrathionate broth(Difco, Becton Dickinson, Sparks. Md.).

For all samples, enrichment tubes were incubated at 37°C for18 to 24 h, after which 10 l.L1 of the broth was streaked onto XLT4agar (XLT4 agar base with XLT4 supplement; Difco, BectonDickinson). Plates were incubated at 37°C and scored at 24 and48 h for presumptive Salmonella (black colonies). Isolated, pre-sumptive Salmonella colonies (at least six randomly chosen iso-lates per sample) were transferred from XLT4 plates onto XLT4,brilliant green, and L-agar (Lennox broth base with 1.5% agar;Gibco Laboratories, Long Island, N.Y.) and incubated at 37°C for24 h. Colonies that exhibited the Salmonella phenotype (black onXLT4 and pink on brilliant green) were preserved from the L-agarfor future analysis. The isolates were stored at —80°C, and sero-typing was performed as described previously (26).

Water samples were filtered (100 ml) through sterile 0.45-tJ.m cellulosic filters (47 mm; Osmonics. Inc.. Westborough,Mass.). Filters were placed in 10 ml of tetrathionate broth andincubated for 18 to 24 h (37°C). Enrichments were streaked andpreserved as above. Water, bulk milk, and milk filter (filtrate) sam-ples were also directly spiral plated (250 p.1) in triplicate ontoXLT4 agar, using an Autoplate 4000 spiral plater (Spiral Biotech,Gaithersburg. Md.), incubated at 37°C, and scored at 24 and 48 hfor Salmonella, as above.

Bulk milk samples were analyzed for bulk tank somatic cellcount (BTSCC), standard plate count (SPC), preliminary incuba-tion count (PlC), laboratory pasteurization count (LPC), Staph v-lococcus aureus (SA). coagulase-negative Staph vlococci (CNS),Streptococci (SS), coliforms (CC), and noncoliforms (NC), as de-scribed in Jayarao et al. (14).

Statistical analysis. Descriptive statistics were calculated forall response variables. Obvious outliers were investigated and cor-rected or removed where appropriate. Associations between herdfecal prevalence and several monitoring parameters were calcu-lated using correlation coefficients. A linear regression model wasused to identify the optimum predictors of herd fecal prevalenceof Salmonella. Stepwise regression was used to build the optimalpredictive model based on all available well behaved variables.

RESULTSAs reported previously, when lactating and prefresh an-

imals in a Salmonella-positive commercial dairy herd weretested every 6 to S weeks for fecal shedding. the sheddingprevalence of Salmonella spp. ranged from 8 to as high as88%. Although several serotypes were identified, Cerro wasthe predominant scrotype and represented more than 98%of the isolates. The herd manager did not identify any an-imals showing clinical signs of salmonellosis during thestudy period.

Although Salmonella was never detected in the sourcewater, the water troughs were frequently positive (Table 1).Salmonella was isolated from at least one of four troughson the farm in 18 of 21 sampling periods. All troughs tested

Holding Return Compos-penalleyWaterites

+Na75

100++N

100

+N

75100

+N

100

100++25

100

++75

100

++50

100

+50

80++50

100++100

100

++75

100

++0

100++100

100

++100

100++25

100

++50

100

++50

100++0

100

++100

100++100

100

+ 0

60

++25

100

Dry cow

++++++++++++++++++++++

Group 1

++++++++++++++++++++

+

Group 2

++++++++++++++++++++++

J. Food Prot., Vol. 71, No. 10

PREDICTING SALMONELLA PREVALENCE IN A DAIRY HERD1969

TABLE I. Summary of total Salmonella culture results for herd fecal shedding prevalence and for water and manure composite samplesfrom the dairy over a 3- year study period

Manure composites % positiveTrough water

Sampling dateFecal(mo/day/yr) prevalence Dry cow Group I Group lb Group 2

09/13/040.44-+++10/27/040.69NNNN12/15/040.59-+++01/24/050.69++++03/14/050.67-+--04/25/050.58-+++06/06/050.30--++08/01/050.08-++-09/27/050.28+-+-12/04/050.88++++01/31/060.83-++-03/27/060.59----06/05/060.83++++08/07/060.70++++09/25/060.69---+12/04/060.45-++-01/29/070.74--++03/27/070.65----04/30/070.67++++06/05/070.68++++08/06/070.50----09/25/070.33--+-

I N, sample not collected.

negative on the remaining three samplings. None of thetroughs were tested at the sampling on 27 October 2004.Throughout the study, composite manure samples were col-lected from many locations on the farm. Five of the manurecomposites were collected from areas where animals in themilking herd had daily access. These samples were col-lected from the alleys in each of the three group pens, thealley used by both milking groups to access the parlor area,and the shared parlor holding pen. Salmonella was isolatedfrom every one of these composites on 20 of the 22 col-lection days. On the 1 August 2005 collection, the holdingpen tested negative, but Salmonella was cultured from theother three composite samples. On 6 August 2007, thegroup 1 and return alley composites tested negative for Sal-monella, but Salmonella was isolated from the dry cow,group 2, and holding pen composites.

A total of 183 bulk milk samples and 152 in-line milkfilters were tested for Salmonella during the study period.Fewer milk filters were tested because weekly sampling ofthe in-line filters did not begin until 2 months after thebeginning of the Salmonella outbreak (September 2004).Overall, two-thirds (66%) of the milk filters tested positive,but Salmonella was isolated from only 11% of the bulkmilk samples.

When the results of the bulk milk quality analysis wereevaluated, outliers were identified in the dataset. Outlierswere evaluated, and where appropriate, a small numberwere corrected or removed from the dataset prior to sum-mary statistic calculations. Data that were removed from

further analysis were far outside the range of the remainingobservations for those variables. With the exception of afew sampling points, the BTSCC was low enough to sug-gest that the herd did not have a serious mastitis problem,and that milking hygiene was adequate (14). Similarly, bac-terial counts (SPC and LPC) were well within the currentstandards. Bacteria counts of mastitis pathogens were ac-ceptable: very low counts for S. aureus, no Streptococcusagalacriae, and low counts for the other major mastitispathogens.

The fecal Salmonella herd prevalence data was col-lected only once every 6 to 8 weeks while weekly sam-plings of bulk milk and milk filter were obtained. The num-ber of milk and milk filter samples varied from three to fiveper month. Averages were calculated for the presence ofSalmonella in milk and milk filter samples as well as forbulk tank quality measures. Values were averaged based ondate of sample collection or receipt. Values for samplescollected in the interval between farm collections of fecalsamples were averaged, and these values were attributed tothe end date of the sample period (Tables 2 and 3). Despiteattempts to edit extreme values, the distributions of manyof the variable averages were still skewed and extremelyleptokurtotic (extremely peaked and concentrated aroundthe mean). Of the nine variables recorded characterizingbulk tank milk, five of these variables had kurtosis valuesabove 3, and three of those were 6 or larger (Table 4).Additionally, the kurtosis value for manure composites wasvery large (13.27).

1970VAN KESSEL ET AL. J. Food Prot.. Vol. 71. No. 10

TABLE 2. Summary data for Salmonella prevalence in the milk filter and bulk milk throughout the study period'-

Fecals Milk filter Bulk milkStart dateEnd date

Period(mo/day/yr)(mo/day/yr)Prevalence nPrevalencenPrevalence

07/01/04

09/13/040.44108N"

0.001009/13/04

10/27/040.691081.00

0.00

710/27/0412/15/04

0.59

1080.67

6

0.14

712/15/04

01/24/05

0.69

1091.00

3

0.00

301/24/05

03/14/05

0.671110.86

7

0.00

803/14/05

04/25/05

0.581130.83

6

0.17

604/25/05

06/06/050.30

III0.50

6

0.00

606/06/0508/01/05

0.08

1070.13

8

0.00

89

08/01/05

09/27/05

0.28

1020.56

9

0.00

91009/27/05

12/04/050.881080.89

9

0.22

91112/04/05

01/31/000.83

106

1.00

7

0.57

712

01/31/06 03/27/060.59

1031.008

0.00

813

03/27/0606/05/06

0.83

102

0.8211

0.36

1114

06/05/0608/07/06

0.70

1040.63

8

0.13

81508/07/06

09/25/06

0.69104

0.86

7

0.1416

09/25/06

12/04/060.45103

0.78

0.0017

12/04/0601/29/070.74110

0.71 0.2918

01/29/07

03/27/07

0.65

109

0.78 0.0019

03/27/0704/30/07

0.67

1120.20 0.2020

04/30/07

06/05/07

0.681170.80

0.002106/05/07

08/06/070.50107

0.43 0.29

2208/06/07

09/25/070.331110.17 0.00

The data for each period is calculated as an average of the results in the prior sampling interval. The sampling interval was set at 2months for period 1.

b N, sample not collected.

An attempt was made to use stepwise regression toconstruct a prediction model for fecal prevalence of Sal-mnonella. The fraction of fecal and water composite sampleswhere Salmonella were detected was considered. Note thatthese samples were collected at the same time as the indi-vidual fecal samples. The fractions of Salmonella-positivebulk tank milk and in-line milk filters were also available.Unlike the composite samples, these were collected morefrequently, and showed much more variability. Finally, pa-rameters from the bulk tank milk samples with kurtosis val-ues less than 3 were considered. Regression coefficientswere added for milk filter Salmonella prevalence, milk Sal-monella prevalence, CNS, and prevalence of Salmonella inthe water samples. When residuals were evaluated from thismodel, an extreme outlier was noted. An observation withrelatively high observed fecal incidence was associatedwith a very low incidence of Salmonella in milk filters inthe weeks leading up to that sampling. That single obser-vation was removed, and the same process was repeated.Using these data, regression coefficients were added in theorder of milk filter Salmonella prevalence, bulk milk Sal-inonella prevalence and BTSCC. Note that in both casesthe first two variables added to the model were Salmonellaprevalence in the milk filters and Salmonella prevalence inthe milk. When a model using only those two variables wasfit to predict fecal prevalence, using all data, the resultingcorrelation was 0.64, and when the aberrant observationwas excluded, the correlation increased to 0.77. Solutionsfor intercept, milk filter, and milk were 0.21, 0.44, and 0.65,

respectively, for the complete data set and were 0.06, 0.63,and 0.53, respectively, for the reduced data set. Correlationcoefficients were calculated among the milk quality vari-ables, bulk milk and milk filter Salmonella analyses, andfecal Salmonella prevalence (Table 4). The coefficients forfecal prevalence and BTSCC, LPC, milk filter Salmonella,and bulk milk Salmonella were positive with the highestcorrelation coefficient observed between fecal prevalenceand milk filter prevalence (0.68). The remaining correla-tions (PlC, SA, CC, NC) were negative or not substantiallydifferent than 0 (SPC and SS).

A plot showing the longitudinal relationships betweenSalmonella-positive milk and milk filter versus fecal shed-ding prevalence is shown in Figure 1. Note that these rep-resent averages of incidences for samples collected betweenfarm sampling visits.

DISCUSSIONThe association of salmonellae with dairy cattle and

dairy farm environments has been well documented. Thereare more than 2,500 Salmonella serotypes, and many se-rotypes have been isolated from dairy farms. Multiple se-rotypes have been identified simultaneously from the samefarm (2, 10. 30), and the serotypes have variable impact onanimal health. Symptoms of Salmonella infection in cattleare highly variable and may include fever, diarrhea, septi-cemia, reduced milk production, and abortion. For example,Salmonella Newport has increased in prevalence in the lastdecade, and an outbreak of this serotype can cause severe

J. Food Prot., Vol. 71. No. It) PREDICTING SALMONELL4 PREVALENCE IN A DAIRY HERD1971

TABLE 3. Sununarv data fr the niilk qua/ar parameters tested throughout the stud y period"

Milk quality parameters:

Start dateEnd dateBTSCCSPCPlCLPCSACNSSSCCNCPeriod(mo/day/yr) (mo/day/yr)a(Cells/ml)(CFLIImI) (CFUJmI) (CFU/ml) (CFU/mi) )CFU/ml) (CFUImO (CFU/mE) (CFU/mI)

07/01/04209/13/04310/27/04412/15/04501/24/05603/14/05704/25/05806/06/05908/01/05

1009/27/05II12/04/051201/31/061303/27/061406/05/061508/07/06

1609/25/061712/04/061801/29/071903/27/072004/30/072106/05/072208/06/07

09/13/0410193,70010/27/047133,14312/15/047145.57101/24/055165,40003/14/057225.00004/25/055274.40006/06/056199.83308/01/058212.87509/27/059238.77812/04/059182,00001/31/068242.50003/27/067273.71406/05/06II180.70008/07/068233.50009/25/068208.37512/04/068174,87501/29/076176.33303/27/079206,00004/30/074150,75006/05/071156.00008/06/07N"N09/25/07 NN

4261.07224148615212108197349II99160174628026402017110691443686002024829024326868261134474329911532748460304200836507647(111331312350876205.43))3354201333108

3,2484.70400569868115662484618561315889 429932,195185223798181055031.930393722991404225.8764746110123475332,10013202361502041

1.4241,8452015110505252531337515370902503175603131075770304752.23113712411316472552,9902056010901)5205000080000NNNNNNNNNNNNNNNN

The data for each period is calculated as an average of the results in the prior sampling interval. The sampling interval was set at 2months for period 1. BTSCC, bulk tank somatic cell count; SPC. standard plate count; PlC, preliminary incubation count; LPC,laboratory pasteurization count; SA, S. aureus; CNS. coagulase-negative Staphylococci; SS, Streptococci; CC. coliforms; NC, non-coliforms.

h N. sample not collected.

illness and mortalities in both young and adult dairy ani-mals (8, 24). In contrast, many serotypes such as Cerro.Montevideo, and Muenster have been frequently culturedfrom asymptomatic animals (1, 3. 10, 12, 20, 30). Sal/no-ne/la infections are often transient and move through adairy herd relatively quickly, but many dairy herds appearto be colonized with salmonellae (29). Because colonizationand virulence is serotype and strain dependent, and oftendependent on health and immune status, the prevalence ofinfection in a herd is variable (1, 3. 10, 11, 21, 29). Inaddition, the numbers of salmonellae shed by any animalcan vary greatly over time. Occasional analysis of individ-ual fecal samples in this herd indicated a range of Salmo-nella shedding from 0 to 105 CFU/g (data not shown). Allof these factors may impact the levels of organism in en-vironmental samples and hence, whether or not detectionlimits are exceeded.

Tracking the presence and prevalence of Salmonellacan be important from both animal health and human healthperspectives. Salmonella can be introduced onto a farm inmany ways, some of which are manageable, such as pur-chased replacement animals and human traffic, but manyvectors such as wildlife, rodents, and birds are difficult tocontrol. Even highly vigilant management programs cannotguarantee Salmonella-free status of a dairy herd. Althoughtesting every animal could be considered ideal, it is im-practical for most situations. The data presented here clearly

show the utility of testing composite manure samples as ameans for identifying the presence of Salmonella sheddingin this herd at all observed prevalence levels. The five com-posite samplings represented all housing areas for the lac-tating groups and the common traffic and holding areasused in the milking process. Testing of these samples wassuccessful at identifying the presence of Salmonella for allsamplings over a 10-fold range of herd Salmonella preva-lence.

Although composite testing was clearly an effectivemeans for identifying Salmonella in this herd, sampling andtesting of manure composites is not routine in most situa-tions. However, milk samples are regularly collected andtested for BTSCC and various bacterial species and groups.Indicator organisms are often used for tracking pathogensin the environment with varied success. The longitudinalstudy of an endemic infection in a dairy herd that includedregular determinations of fecal shedding prevalence andweekly bulk milk testing provided a unique opportunity toevaluate the utility of using standard bulk milk testing datato predict the presence and perhaps the prevalence of fecalshedding in the herd. The lack of reliable relationships be-tween fecal Salmonella Cerro shedding prevalence and theweekly standard bulk milk quality parameters in this herdindicates these measurements may not be useful in detect-ing colonization by commensal Salmonella serotypes. If thesalmonellae are living commensally in the digestive sys-

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1972VAN KESSEL ET AL. J. Food Prot., Vol. 71, No. 10

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:NNCONC'C"tNC'-''''CCCN-coCN- N'CCCOCO'CIII-

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Sep-04Mr-050t105Apr-06Noe.06Mv-07

FIGURE 1. A comparison of Salmonella prevalence in bulk milk

(broken line) and in-line milk filters (solid line) with herd level

fecal shedding prevalence (circles). The bulk milk and in-line milk

filter prevalences are based on averages of the sampling intervals.

tems of cows, then their presence or absence may not elicit

an immune response or impact other intestinal or mastitis

organisms to an extent that is detectable in milk. From these

data, it is not clear if routine bulk milk quality analysis

would be useful for tracking Salmonella serotypes that have

clinical impact on the herd.

Considering the high fecal prevalence of Salmonella in

this herd, the prevalence (11 %) of Salmonella-positive bulk

milk samples was surprisingly low. However, the presence

of Salmonella in milk was more predictive of fecal Sal-

monella shedding than were any of the milk quality indi-

cators (Table 4). Sampling period averages of bulk milk

Salmonella showed a remarkable similarity in prevalence

pattern compared to herd fecal prevalence (Fig. I). Preva-

lence in bulk milk was approximately 20% of that observed

in milk filters but followed a very similar pattern (Fig. I).

Salmonella contamination in the milk is most likely a result

of fecal contamination, yet, based on the results of the bulk

milk BTSCC and bacterial analysis and observations by the

research team, this herd has demonstrated good hygienic

management practices (14). In contrast to the milk. Sal-

monella was isolated six-fold (66 versus 11%) more fre-

quently from the milk filter and the correlation of filter

prevalence with fecal prevalence was higher than that found

with the milk (0,68 versus 0.55). Although the filters are

designed to trap only the coarse particles, bacteria must be

captured in the matrix of large particles collected with the

filter. Based on the prevalence of Salmonella contamination

in the milk filter, it is certain that more than 11% of the

milk samples were contaminated with Salmonella, but that

the concentrations were routinely below detection levels.

The data from this herd demonstrates that the milk fil-

ters are a very useful tool for identifying the presence of

Salmonella infection in a herd, but also indicate the poten-

tial utility for milk filter analysis to indicate herd preva-

lence. As the data in Figure 1 show, there is a strong re-

lationship (r = 0.68) between milk filter prevalence on a

monthly basis and Salmonella prevalence in the herd. The

increase in predictability from Using both bulk milk and

milk filter rather than either alone is marginal (r = 0.77).

Some herds, such as the one reported here, have endemic

1.00

0.75

0

0.50

0.25

J. Food Prot., Vol. 7!, No. 10

PREDICTING SALMONELLA PREVALENCE IN A DAIRY HERD1973

infections that are notoriously difficult or impossible toclear. Regular milk filter analysis may assist these producersin monitoring herd prevalence.

The data presented here provide several alternatives formonitoring Salmonella in dairy herds. There are a varietyof scenarios in which this might be useful with respect toanimal health monitoring, but it also has great potentialfrom a food safety standpoint. Currently, many states allowraw milk sales. Most of these states have a requirement forregular testing of the milk for potential pathogens. Basedon the data presented here, milk filter testing would be amuch more sensitive screen than would testing milk alonefor Salmonella and potentially other bacterial pathogens.

ACKNOWLEDGMENTSThe authors gratefully acknowledge the assistance of Kimberly Ne-

len as the farm liaison and coordinator; Carolyn Burns and Louise Bylerfor their assistance with sample collection; and Thomas Jacobs, Jr.. Clau-dia Lam, Crystal Rice-Trujillo. Jackie Sonnier, Kim Schauff, and SamShen for laboratory analysis. We also acknowledge the producer for pro-viding us with access to his herd and for all of his generous assistance.

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