Extensive countrywide field investigation of somatic cell counts and total bacterial counts in bulk tank raw milk in goat herds in Greece.

Dairy goat farming is an important sector of the agricultural industry in Greece, with an annual total milk production exceeding 450 000 l and accounting for over 25% of all goat milk produced in the European Union; this milk is used mainly for cheese production. Despite the importance of goat milk for the agricultural sector in Greece, no systematic countrywide investigations in the bulk-tank milk of goats in Greece have been reported. Objectives were to investigate somatic cell counts (SCC) and total bacterial counts (TBC) in raw bulk-tank milk of goat herds in Greece, study factors influencing SCC and TBC therein and evaluate their possible associations with milk content. Throughout Greece, 119 dairy goat herds were visited for milk sampling for somatic cell counting, microbiological examination and composition measurement. Geometric mean SCC and TBC were 0.838 × 106 cells ml-1 and 581 × 103 cfu ml-1, respectively. Multivariable analyses revealed annual frequency of check-ups of milking system and total milk quantity per goat (among 53 variables) to be significant for increased SCC; no factor emerged (among 58 variables) to be significant for increased TBC. Negative correlation of SCC with total protein was found; mean total protein content in the bulk-tank milk in herds with SCC >0.75 × 106 cells ml-1 was 5.1% lower and in herds with SCC >1.5 × 106 cells ml-1, it was 7.8% lower.

The Use of Machine Learning to Predict Prevalence of Subclinical Mastitis in Dairy Sheep Farms.

The objective of the study was to develop a computational model with which predictions regarding the level of prevalence of mastitis in dairy sheep farms could be performed. Data for the construction of the model were obtained from a large Greece-wide field study with 111 farms. Unsupervised learning methodology was applied for clustering data into two clusters based on 18 variables (17 independent variables related to health management practices applied in farms, climatological data at the locations of the farms, and the level of prevalence of subclinical mastitis as the target value). The K-means tool showed the highest significance for the classification of farms into two clusters for the construction of the computational model: median (interquartile range) prevalence of subclinical mastitis among farms was 20.0% (interquartile range: 15.8%) and 30.0% (16.0%) (p = 0.002). Supervised learning tools were subsequently used to predict the level of prevalence of the infection: decision trees, k-NN, neural networks, and Support vector machines. For each of these, combinations of hyperparameters were employed; 83 models were produced, and 4150 assessments were made in total. A computational model obtained by means of Support vector machines (kernel: 'linear', regularization parameter C = 3) was selected. Thereafter, the model was assessed through the results of the prevalence of subclinical mastitis in 373 records from sheep flocks unrelated to the ones employed for the selection of the model; the model was used for evaluation of the correct classification of the data in each of 373 sets, each of which included a test (prediction) subset with one record that referred to the farm under assessment. The median prevalence of the infection in farms classified by the model in each of the two categories was 10.4% (5.5%) and 36.3% (9.7%) (p < 0.0001). The overall accuracy of the model for the results presented by the K-means tool was 94.1%; for the estimation of the level of prevalence (<25.0%/≥25.0%) in the farms, it was 96.3%. The findings of this study indicate that machine learning algorithms can be usefully employed in predicting the level of subclinical mastitis in dairy sheep farms. This can facilitate setting up appropriate health management measures for interventions in the farms.

Isolation of Listeria ivanovii from Bulk-Tank Milk of Sheep and Goat Farms-From Clinical Work to Bioinformatics Studies: Prevalence, Association with Milk Quality, Antibiotic Susceptibility, Predictors, Whole Genome Sequence and Phylogenetic Relationships.

A cross-sectional study was performed in 325 sheep and 119 goat dairy farms in Greece. Samples of bulk-tank milk were examined by standard microbiological techniques for Listeria spp. Listeria monocytogenes was isolated from one (0.3%) and Listeria ivanovii from three (0.9%) sheep farms. No associations between the isolation of L. monocytogenes or L. ivanovii and milk quality were found. No resistance to antibiotics was identified. Three variables emerged as significant predictors of isolation of the organism: the presence of pigs, low average relative humidity and a high number of ewes on the farm. The three L. ivanovii isolates were assessed in silico for identification of plasmids, prophages, antibiotic resistance genes, virulence factors, CRISPRs and CAS genes. Phylogenetic analysis using the core genome revealed that the three strains belonged to the L. ivanovii subsp. ivanovii branch and were especially close to the PAM 55 strain. All strains of the branch appeared to be very similar, with the distance between them being small.

Mortality of Dairy Sheep during the Peri-Parturient Period: Results of a Field Investigation in Greece.

Objectives of the study were (a) to investigate the incidence risk of peri-parturient mortality in dairy flocks in Greece, (b) to study when such mortality occurs in relation to lambing, (c) to identify clinical problems associated with the deaths, and (d) to evaluate potentially associated factors. The deaths of ewes during the peri-parturient period (10 days before to 7 days after lambing) were monitored in 60 flocks over two years. In the ewes that died, detailed post-mortems were performed. The incidence risk of peri-parturient deaths was 0.7%. The daily incidence rate of deaths before, at, and after lambing was 0.05, 0.04, and 0.03%, respectively. Clinical problems most frequently associated with peri-parturient deaths were pregnancy toxaemia, ruminal acidosis and post-partum genital problems. For the occurrence of peri-parturient deaths in flocks, the average lambing rate in the flocks was the only significant factor. Regarding deaths before or after lambing, the season during which lambing took place and the number of animals in the flock, respectively, were found to be significant. Most ewes (54.5%) that died at lambing (dystocia) were primigravidae.

Association of Staphylococcal Populations on Teatcups of Milking Parlours with Vaccination against Staphylococcal Mastitis in Sheep and Goat Farms.

There is a paucity of information regarding staphylococcal populations on teatcups of milking parlours in sheep and goat farms. The objectives were to describe the populations of staphylococci on teatcups in milking parlours in sheep or goat farms in two field investigations throughout Greece and to potentially associate the findings with the use of anti-staphylococcal mastitis vaccinations in the farms visited during the two investigations. In a cross-sectional (255 sheep and 66 goat farms across Greece) and a longitudinal (12 sheep farms, four samplings, throughout lactation) study, swab samples were collected from 1418 teatcups (upper and lower part) for staphylococcal recovery, identification and assessment of biofilm-formation. A total of 328 contaminated teatcups (23.1%) were found in 105 sheep (41.2%) and 35 goat (53.0%) farms. Staphylococci were more frequently recovered from the upper than the lower part of teatcups: 269 versus 139 teatcups, respectively. After identification, 253 staphylococcal isolates were found: Staphylococcus aureus, Staphylococcus equorum, Staphylococcus lentus, and Staphylococcus capitis predominated. Of these isolates, 87.4% were biofilm-forming. The proportion of contaminated teatcups was smaller in farms where vaccination against anti-staphylococcal mastitis in general or vaccination specifically against mastitis caused specifically by biofilm-forming staphylococcal strains was applied, 19.7% or 10.9%, respectively, versus 25.5% in farms without vaccination. In the longitudinal study, contaminated teatcups were identified in 28 (58.3%) sampling occasions, with staphylococci being recovered more frequently from their upper part. The same species as in the cross-sectional study predominated. Of these isolates, 61.9% were biofilm-forming. In farms where vaccination against mastitis caused specifically by biofilm-forming staphylococcal strains was applied, the proportion of contaminated teatcups was smaller: 20.4% versus 48.3% in farms without vaccination. There were no differences in proportions of contaminated teatcups between sampling occasions. In conclusion, the great majority of staphylococci recovered from teatcups of milking parlours in sheep and goat farms included biofilm-forming isolates. Reduced staphylococcal isolation was noted in farms where anti-staphylococcal vaccination was performed; this was possibly the effect of reduced excretion of staphylococci in the milk of vaccinated animals.