Dairy Sheep and Goat Farmers: Socio-Demographic Characteristics and Their Associations with Health Management and Performance on Farms

An attentional residual feature fusion mechanism for sheep face recognition

In the era of globalization and digitization of livestock markets, sheep are considered an essential source of food production worldwide. However, sheep behavior monitoring, disease prevention, and precise management pose urgent challenges in the development of smart ranches. To address these problems, individual identification of sheep has become an increasingly viable solution. Despite the benefits of traditional sheep individual identification methods, such as accurate tracking and record-keeping, they are labor-intensive and inefficient. Popular convolutional neural networks (CNNs) are unable to extract features for specific problems, further complicating the issue. To overcome these limitations, an Attention Residual Module (ARM) is proposed to aggregate the feature mapping between different layers of the CNN. This approach enables the general model of the CNN to be more adaptable to task-specific feature extraction. Additionally, a targeted sheep face recognition dataset containing 4490 images of 38 individual sheep has been constructed. Furthermore, the experimental data was expanded using image enhancement techniques such as rotation and panning. The results of the experiments indicate that the accuracy of the VGG16, GoogLeNet, and ResNet50 networks with the ARM improved by 10.2%, 6.65%, and 4.38%, respectively, compared to these recognition networks without the ARM. Therefore, the proposed method for specific sheep face recognition tasks has been proven effective.

Data on Mapping 444 Dairy Small Ruminant Farms during a Countrywide Investigation Performed in Greece

The small ruminant industry is the most important branch of Greek agriculture. Nevertheless, despite the importance of small ruminant farming for Greece, no detailed mapping of the respective farms has been undertaken and published. The present work refers to mapping the dairy sheep and goat industry in Greece through an extensive, countrywide cross-sectional study, in which information was obtained from 325 sheep and 119 goat farms. The objectives were the collection, the classification and the presentation of data obtained from all these farms through interviews, using a questionnaire and through examination of samples collected during the visits. All the farms enrolled in the study were visited by the investigators. Initially, information was obtained by means of a detailed, structured questionnaire with 442 questions. Moreover, samples of milk were collected from the bulk-tank of each farm and faecal samples were collected from female animals in each farm. The milk samples were processed for cytological and microbiological examination. Staphylococcus spp. and Listeria spp. isolates were recovered and identified at a species level; furthermore, a full antibiotic sensitivity pattern assessment was conducted. Faecal samples were processed by standard parasitological tests for the identification of protozoan, trematode, cestode and gastrointestinal and respiratory nematode parasites. The paper presents the cumulative findings of the study, i.e., the answers to the questions during the interviews and the results of the laboratory examinations performed in the samples; the findings are presented separately for sheep and goat farms. The findings can be used as baseline measurements; individual farms and cohorts of farms can be compared against the current results to draw conclusions against the countrywide situation. Moreover, the current results can be used as reference points for the future, in order to assess changes that might have occurred in the meantime. The study also described the differences between farms with sheep or goats; in total, differences in 137 parameters were identified. Some of these can be attributed to the different management systems practiced; sheep flocks are managed mostly under the intensive or semi-intensive system, whilst goat herds are managed mostly under the semi-extensive or extensive system. These findings can be useful in the health management of small ruminants, in providing evidence-based support and within the scope of precise livestock medicine and health management.

Relationship between Vaccine Application and Climate Factors in Sheep and Goat Farms in Greece

The objectives of the present study were (a) to evaluate the importance of climate-related variables in the vaccination patterns applied in sheep and goat farms in Greece and (b) to assess potential interactions between these factors and previously established important health management- and human resources-related factors applied in the farms. Vaccination patterns against chlamydial abortion, clostridial infections, contagious agalactia, contagious ecthyma, foot-rot, paratuberculosis, pneumonia or staphylococcal mastitis were assessed. Climatic variables (2010–2019 and 2018–2019) were obtained for 444 locations with small ruminant farms throughout Greece. Patterns of vaccine administration in the farms were obtained through interviews with farmers. The following nine outcomes were considered: ‘vaccination against chlamydial abortion’, ‘vaccination against clostridial infections’, ‘vaccination against contagious agalactia’, ‘vaccination against contagious ecthyma’, ‘vaccination against foot-rot’, ‘vaccination against paratuberculosis’, ‘vaccination against bacterial pneumonia’, ‘vaccination against staphylococcal mastitis’ and ‘total number of optional vaccines administered’. Univariable and multivariable analyses were first performed to establish associations of each of the above outcomes with climatic variables. Then, the same approach was employed to assess the importance of climatic variables against health management- and human resources-related factors in the administration of vaccines in the farms of the study. Climatic variables had a higher association with vaccinations against infections in sheep flocks (26 associations) than in goat herds (9 associations) (p = 0.002) and in farms with semi-extensive or extensive management (32 associations) than in farms with intensive or semi-intensive management (8 associations) (p < 0.0001). In 26 cases (38.8% of all analyses evaluated), the climatic variables overshadowed the management- and human resources-related variables assessed as significant predictors for vaccination. In most cases, these referred to sheep flocks (nine cases) and farms with semi-extensive or extensive management (eight cases). For all eight infections, there were changes in the climatic variables found to be significant predictors from the 10-year dataset to the 2-year dataset. The results indicated that, in some cases, climate factors overshadowed factors traditionally considered for the formulation of vaccination programs. This points out the significance of taking into account climate conditions in the health management of small ruminant farms. Future studies can be focused on formulating vaccination programs in accordance with climate factors and also on setting the optimum season(s) for vaccination of animals based on the circulation of the pathogens, the risks for the development of diseases and the stage within the annual production cycle of the animals.

Helminth Infections in Dairy Sheep Found in an Extensive Countrywide Study in Greece and Potential Predictors for Their Presence in Faecal Samples

The aims of the present study were: (a) to describe the prevalence of helminth infections from pooled faecal samples from sheep flocks across Greece and (b) to evaluate flock-related factors potentially associated with the presence of these infections in the flocks. An extensive countrywide study was performed on 325 sheep farms throughout Greece; faecal samples were collected from ewes and processed for the identification of helminth parasites. Helminths were detected in samples from 92.9% of flocks; these included Dicrocoelium dendriticum (16.7% of flocks), Fasciola hepatica (0.6%), Paramphistomum cervi (2.2%), Moniezia spp. (18.8%), Trichostrongylidae (85.5%), Nematodirus spp. (18.8%), Strongyloides papillosus (7.1%), Trichuris spp. (20.0%) and lungworms (17.8%). Mean Trichostrongylidae counts across all flocks in the study were 215 epg. Specifically, for Trichostrongylidae, there were differences between flocks that had or had not received anthelmintics during the two months prior to sampling, as well as between flocks located in various areas of the country. In multivariable analyses, for the outcome 'high (>300) epg counts in faecal samples', the month into the lactation period at sampling and the application of reproductive control practices on the farm emerged as significant factors; for the outcome 'high proportion (>63%) of Teladorsagia spp. in faecal samples', the availability of straw bedding emerged as a significant factor; and for the outcome 'high proportion (>63%) of Haemonchus contortus in faecal samples', the age of the farmer emerged as a significant factor. For the outcome 'presence of Trichuris spp. in faecal samples', the provision of finished feed (concentrate) to animals emerged as a significant factor, whilst, finally, for the outcomes 'presence of D. dendriticum in faecal samples' and 'presence of lungworms in faecal samples,' no significant factors emerged.

The effects of restrictive measures due to the COVID-19 pandemic on the extensive farming system of small ruminants

Vigorous restrictive measures were imposed worldwide to control the spread of the COVID-19 pandemic. However, the effects those measures had on livestock production systems have not yet been sufficiently clarified. The literature has focused mainly on the impact of COVID-19 on the intensive livestock production system, especially the meat and milk supply chain, as well as the welfare of animals, highlighting its fragility, but failed to address the way the restrictive measures affected the extensive farming system of small ruminants. In this study, we aimed to investigate the effect of the restrictive measures during the first wave of the COVID-19 pandemic on the parameters of sheep and goat extensive farming systems. We used a survey and personal interviews to record the breeders' profile and the structural characteristics of the holdings, and we showed that the restrictive measures had no effect on the parameters of small ruminant extensive farming systems, except for the daily work routine of breeders, which was negatively affected in holdings with a high number of sheep. We expect this study to be helpful to policy makers regarding formulating interventions for the resilience and the stability of the sheep and goat extensive farming system in future situations of emergency.

Detection of Zoonotic Gastrointestinal Pathogens in Dairy Sheep and Goats by Using FilmArray® Multiplex-PCR Technology

The objectives of this study were (a) to detect gastrointestinal pathogens in faecal samples of sheep and goats using the FilmArray® GI Panel and (b) to evaluate factors that were associated with their presence. Faecal samples from ewes or does in 70 sheep flocks and 24 goat herds in Greece were tested for the presence of 22 gastrointestinal pathogens by means of the BioFire® FilmArray® Gastrointestinal (GI) Panel. The most frequently detected pathogens were Shiga-like toxin-producing Escherichia coli stx1/stx2 (94.7% of farms), Giardia lamblia (59.6%), and Campylobacter spp. (50.0% of farms). Other pathogens detected were Cryptosporidium spp., Salmonella spp., enterotoxigenic E. coli lt/st, Yersinia enterocolitica, E. coli O157, Rotavirus A, Shigella/enteroinvasive E. coli, and Plesiomonasshigelloides. There was a difference in the prevalence of detection of pathogens between sheep and goat farms only for Salmonella spp.: 18.3% versus 0.0%, respectively. Mixed infections were detected in 76 farms (80.9% of farms), specifically 57 sheep flocks and 19 goat herds, with on average, 2.5 ± 0.1 pathogens detected per farm. The body condition score of ewes in farms, in which only one pathogen was detected in faecal samples, was significantly higher than that of ewes in farms, in which at least two pathogens were detected: 2.55 ± 0.11 versus 2.31 ± 0.04. In sheep flocks, the number of pathogens in faecal samples was significantly higher in farms with semi-extensive management. In goat herds, the number of pathogens in faecal samples was positively correlated with average precipitation and inversely correlated with temperature range in the respective locations.