Neospora caninum antibodies in bulk tank milk from dairy cattle herds in Italy in relation to reproductive and productive parameters and spatial analysis.

Among the available diagnostic techniques, antibody detection in bulk tank milk (BTM) represents a useful tool to estimate and monitor Neospora caninum herd prevalence. To evaluate the prevalence of N. caninum and the effect of parasite infection on herd performances, BTM samples collected from 586 dairy herds located in one of the largest dairy production areas in Italy (Lombardy) were analyzed by an indirect ELISA to detect anti-N. caninum specific antibodies. Generalized linear models (GLMs) were developed. A purely spatial analysis scanning for clusters with high or low rates for N. caninum using the Bernoulli model was performed. A maximum entropy approach was used to estimate the probability of distribution of the parasite based on occurrence records together with environmental variables. Overall, 180 herds resulted positive for N. caninum antibodies on bulk tank milk (P = 30.7 %). A higher risk of seropositivity was evidenced in the provinces of Milano, Cremona, Brescia, and Bergamo (P = 32-40 %); a lower risk was evidenced in Lodi, Pavia, and Mantova (P = 13-24 %). A higher risk of seropositivity was revealed for small-medium farms (101-300 animals) (O.R.=2.8) and for older animals with more than 4 years (O.R.=4.4). Regarding the effect of N. caninum infection on herd performances, the number of inseminations for conception was higher (> 3 inseminations), and the period from calving to conception was longer (> 150 days) for positive farms (O.R.=2.0 and O.R.=2.3, respectively); besides, lower head daily milk production (<20 kg and 21-25 kg) and mature equivalent milk yield (<11,000), and somatic cell counts higher than 300,000 cells/ml were observed for N. caninum positive herds (O.R.=0.4, O.R.=0.4 and O.R.=1.9 respectively). The geographical distribution of N. caninum positive farms with the highest level of probability covers the central sector of the Po Plain where a significant cluster for high risk of parasite infection was shown by spatial scan statistic and Maximum entropy ecological niche modelling. A further significant cluster of low risk occurred in the southern. The climatic and environmental variables with the highest training gain when used in isolation resulted altitude, land use/land cover, and other variables related to temperature and precipitation. Neosporosis is widely distributed in Italian dairy herds and an impact of the parasite on herd performances could be hypothesized. Even if the role of N. caninum in alterations of reproductive and productive parameters should be further explored, veterinarians and farmers should be aware of neosporosis, and control plans should be adopted.

Early Milk Total and Differential Cell Counts as a Diagnostic Tool to Improve Antimicrobial Therapy Protocols.

Mastitis is a major cause of antimicrobial treatments either during lactation or at drying off. From a One Health perspective, there should be a balance between the risk of IMI that may impair cow health and welfare and the reduction of antimicrobial usage to decrease antimicrobial resistance, as may happen when applying selective dry-cow therapy. This reduction may be achieved by an early and accurate diagnosis followed by prudent and rationale therapeutical protocols. This study aims to assess the accuracy of PLCC (neutrophils + lymphocyte count/mL) in identifying cows at risk of having IMI due to major pathogens (S.aureus, Str.agalactiae, Str.uberis, and Str.dysgalactiae), and to simulate the impact of this early diagnosis on the potential number of treatments using a decision-tree model. The results of this study showed that PLCC had an overall accuracy of 77.6%. The results of the decision-tree model based on data from the 12 participating herds, with an overall prevalence of major pathogens of 1.5%, showed a potential decrease in the number of treatments of about 30% (from 3.4% to 2.5%) when PLCC in early lactation (days 5-16) was used to identify cows at risk for major pathogens compared with using SCC at the first milk test (days 17-43). The study confirmed that it is possible to improve animal health and reduce the risk of antimicrobial use through early IMI detection based on PLCC and applying a rationale and prudent antimicrobial protocol.

Linear Mixed-Effects Model to Quantify the Association between Somatic Cell Count and Milk Production in Italian Dairy Herds.

Milk production loss due to mastitis in dairy herds is economically important. Before estimating the economic impacts of mastitis, it is crucial to quantify the association between mastitis and milk production. The objective of this study was to estimate the association between somatic cell count (SCC, as an indicator of intramammary infection due to mastitis) and milk production for dairy cows in Lombardy, Italy. The test-day (TD) records data of 3816 dairy herds located in three different geographical areas of Lombardy from January 2016 to December 2018 were used. After data editing, the final dataset comprised 10,445,464 TD records from 2970 farms and 826,831 cows. The analysis was carried out by using a mixed-effects model with six fixed effects (geographical Area, Breed, Days in Milk, Parity, Season and Year) and nested random effects for each cow and herd. The results confirmed that the SCC had a negative association with milk production. On average, this study found that any two-fold increase of SCC resulted in a milk production loss of 0.830 (95% CI: -0.832, -0.828) kg/cow/day in the whole of Lombardy. These results can be used for economic calculations on the costs of mastitis.

Total and Differential Cell Counts as a Tool to Identify Intramammary Infections in Cows after Calving.

Milk differential somatic cells count (DSCC), made possible under field conditions by the recent availability of a high-throughput milk analyzer may represent an improvement in mastitis diagnosis. While an increasing number of studies reports data on DSCC on individual cow samples, very few concerns DSCC from quarter milk samples. This paper reports for the first time the results of a retrospective study aiming to assess the performance of total (SCC), DSCC, and a novel calculated marker (PLCC) measured on quarter milk samples as a method to identify cows at risk for intramammary infection (IMI) in the first 30 days after calving. Overall, 14,586 valid quarter milk samples (3658 cows) taken in the first 30 days of lactation were considered. Quarters with major pathogens (MP) IMI, as expected, showed significantly higher means for SCC, DSCC, and PLCC. The accuracy, sensitivity, and specificity of the diagnosis based on different cut-offs calculated by ROC analysis are relatively close among DSCC, PLCC, and SCC (up to cut-off of 200,000 cells/mL). However, decision-tree analysis which includes the costs of analysis, but also the costs of the actions taken after test results showed as PLCC has the lowest cost among the three markers, and PLCC and SCC are cost effective when MP prevalence is higher than 6-10%. This diagnostic approach is of high interest particularly when selective dry cow therapy is applied to improve animal health at the herd level.

Raw Milk Microbiota Modifications as Affected by Chlorine Usage for Cleaning Procedures: The Trentingrana PDO Case.

Milk microbiota represents a key point in raw milk cheese production and contributes to the development of typical flavor and texture for each type of cheese. The aim of the present study was to evaluate the influence of chlorine products usage for cleaning and sanitizing the milking equipment on (i) raw milk microbiota; (ii) the deriving whey-starter microbiota; and (iii) Trentingrana Protected Designation of Origin (PDO) cheese microbiota and volatilome. Milk samples from three farms affiliated to a Trentingrana PDO cheese factory were collected three times per week during a 6-weeks period in which a sodium hypochlorite detergent (period C) was used and during a subsequent 6-weeks period of non-chlorine detergent usage (period NC). Samples were subjected to microbiological [Standard Plate Count; coliforms; coagulase-positive staphylococci; and lactic acid bacteria (LAB)] and metagenomic analysis (amplification of V3-V4 regions of 16S rRNA gene performed on Illumina MiSeq platform). In addition, cheese volatilome was determined by SPME-GC-MS. In the transition from period C to period NC, higher SPC and LAB counts in milk were recorded. Milk metagenomic analysis showed a peculiar distinctive microbiota composition for the three farms during the whole experimental period. Moreover, differences were highlighted comparing C and NC periods in each farm. A difference in microbial population related to chlorine usage in bulk milk and vat samples was evidenced. Moreover, chlorine utilization at farm level was found to affect the whey-starter population: the usually predominant Lactobacillus helveticus was significantly reduced during NC period, whereas Lactobacillus delbrueckii had the exact opposite trend. Alpha- and beta-diversity revealed a separation between the two treatment periods with a higher presence of L. helveticus, L. delbrueckii, and Streptococcus thermophilus in cheese samples after NC detergent period. Cheese volatilome analysis showed a slight decrease in lipolysis during C period in the inner part of the cheese wheel. Although preliminary, these results suggest a profound influence on milk and cheese microbiota, as well as on raw milk cheese production and quality, due to the use of chlorine. However, further studies will be needed to better understand the complex relationship between chlorine and microbiota along all the cheese production steps.

Factors Affecting the Patterns of Total Amount and Proportions of Leukocytes in Bovine Milk.

Differential leukocyte count (DSCC) in milk is considered important to improve knowledge of udder immune response. The investigations on milk DSCC were limited by the techniques available until recently, when a high-throughput tool to perform DSCC opened the way to explore these factors in rapid and economically sustainable ways. We hypothesized that DSCC alone does not fully describe the pattern of these cells, since the total amount is also influenced by milk yield and SCC. Therefore, this study was designed to describe DSCC and total amount of different leukocytes in milk during the course of lactation in cows differing in parity and in levels of SCC. This study considered 17,939 individual milk tests from 12 dairy herds in Lombardy Region, where DCC testing was applied in the period of February 2018-December 2019 (23 months). The samples were divided into two subsets-"healthy" (HS) with SCC ≤200,000 cells/mL and "inflamed" (IS) with SCC >200,000 cells/mL. Cow in HS have a P + LT average between 5.0 × 108 and 3.0 × 109 cells. In IS cows, the values were 1.6 × 1010 and 2.5 × 1010. Therefore, the presence of a well-defined inflammatory process increased the overall amount of polymorphonuclear neutrophils (PMN) and lymphocytes (LYM) of 1 log, from 1 × 109 to 1 × 1010. The assessment of the total amount of PMN and LYM, to our knowledge, have never been reported in scientific literature; the values observed may be proposed as benchmarks for studies on udder immune response. When data were analyzed by days in milk (DIM), they showed that cows in first and second lactation have a significantly lower amount of PMN + LYM, when compared to cows in third and higher lactation. However, these differences are numerically not very large (7%), and suggest that, in healthy animals, the number of immune cells is kept as constant as possible. In IS, the analysis of trends based on DIM showed that both DSCC and P + LT have a significant negative trend. These data suggest that only in this group, the presence of high SCC as lactation proceeds is associated with a progressive increase in the number of macrophages. To the best of our knowledge, this is the first study describing the pattern of DSCC and the total amount of PMN + LYM in relation to parity, days in milk, and SCC, and it may be considered as the first contribution in the investigation on mammary gland immune response by the means of differential cell counts in milk.

Differential Somatic Cell Count as a Novel Indicator of Milk Quality in Dairy Cows.

Recent available instruments allow to record the number of differential somatic cell count (DSCC), representing the combined proportion of polymorphonuclear leukocytes and lymphocytes, on a large number of milk samples. Milk DSCC provides indirect information on the udder health status of dairy cows. However, literature is limited regarding the effect of DSCC on milk composition at the individual cow level, as well as its relation to the somatic cell score (SCS). Hence, the aims of this study were to (i) investigate the effect of different levels of DSCC on milk composition (fat, protein, casein, casein index, and lactose) and (ii) explore the combined effect of DSCC and SCS on these traits. Statistical models included the fixed effects of days in milk, parity, SCS, DSCC and the interaction between SCS × DSCC, and the random effects of herd, animal within parity, and repeated measurements within cow. Results evidenced a decrease of milk fat and an increase in milk fatty acids at increasing DSCC levels, while protein, casein and their proportion showed their lowest values at the highest DSCC. A positive association was found between DSCC and lactose. The interaction between SCS and DSCC was important for lactose and casein index, as they varied differently upon high and low SCS and according to DSCC levels.

Differential Somatic Cell Count as a Marker for Changes of Milk Composition in Cows with Very Low Somatic Cell Count.

The recent availability of a high-throughput milk analyzer performing a partial differential somatic cell count (DSCC) opened new opportunities in investigations on bovine udder health. This analyzer has a potential limitation on the accuracy of measurements when the somatic cell count (SCC) is below 50,000 cells/mL, values characterizing a good proportion of lactating cows in many herds. We obtained data for cows below this threshold, assessed the repeatability of these measurements and investigated the relationship between DSCC and udder health, milk composition and yield. Overall, 3022 cow milk test records performed on a Fossomatic™ 7/DC (Foss A/S, Hillerød, Denmark) were considered; 901 of them had an SCC ≤ 50,000 cells/mL. These latter samples were analyzed by qPCR to identify the presence of bacteria. Overall, 20.75% of the samples (187) were positive. However, the health status did not have any significant association with DSCC. The analysis of the association of DSCC on milk fat, protein and casein showed a significant decrease in their proportions as the DSCC increased, whereas it was not observed for milk yield and lactose. Therefore, DSCC in very low SCC cows may be suggested as a marker to identify early changes in milk composition.

Effect of cleaning procedure and hygienic condition of milking equipment on bacterial count of bulk tank milk.

The aim of the study was to describe the characteristics of cleaning procedures for milking equipment applied in intensive dairy farms in Lombardy (Italy) and to study their relationships with bacterial count of bulk milk and hygienic condition of milking machine components. A group of 22 dairy farms was visited twice (winter and summer) in order to collect bulk tank milk and post-rinse water samples and swabs from liners and milk receiver. Samples were analysed to determine: standard plate count (SPC), laboratory pasteurization count (LPC), psychrotrophic bacteria count (PBC), coliform count (CC) and Escherichia coli. Cleaning procedures were monitored using electronic milk flow meters with specific software for the measurement of the duration of each cleaning phase, circulating solution temperature and electrical conductivity, turbulence and water filling percentage of pipelines. The results showed that farms classified as high and low milk total bacteria count significantly differed both in terms of liners and receiver bacterial contamination and in terms of water temperature reached during the detergent phase of cleaning milking equipment. Significant positive correlations were found among total bacteria count in milk and bacterial contamination of the liners. Maximum water temperature reached during the cleaning cycle of milking equipment was very low (34.4±8.9°C on average); most of the observations (88.6%) corresponded to water temperatures <45°C. Cleaning temperature was related to psychrotrophic bacteria count of milk and post-rinse water and coliform count in liners. Routine check and regulation of water temperature during the washing phase of the milking machine can be a simple and effective way to control one of the main risk factors for bacteriological quality of bulk tank milk.