Assessment of technical-productive aspects in Italian dairy farms equipped with automatic milking systems: A multivariate statistical analysis approach.

The aim of this study was to assess technical-productive aspects of dairy farms equipped with automatic milking system (AMS) in Northern and Central Italy. A survey was carried out on 62 dairy farms selected through convenience sampling with the following inclusion criteria: adoption of robotic milking for at least 1 yr and ability to provide farm data. Data were collected using a structured questionnaire to obtain a general description of farm characteristics and overall management practices. Through the combination of principal component analysis and k-means cluster analysis, the farms were allocated in 3 clusters. The identified clusters were described and afterward compared using one-way ANOVA or a chi-squared test. The main observed differences between clusters were the average number of lactating cows and AMS installed, average annual milk production, average AMS loading, average annual milk yield per full-time employee, average daily milk yield per cow and AMS, and the average annual veterinary costs per cow. cluster 1 (n = 24) included small-to-medium-sized semi-intensive farms with low AMS loading and low average daily milk yield per cow. In this farm typology, the AMS is not fully used and is likely perceived as a means to improve quality of life rather than profitability. Clusters 2 (n = 31) and 3 (n = 7) included, respectively, small-medium-sized and large intensive farms. These 2 farm typologies are characterized by an intensive approach to dairy cattle breeding, with average higher AMS loading, labor efficiency, and milk yield compared with the farms of cluster 1, likely due to better farm management. This classification could help dairy technicians give farmers customized management advice for the function of the cluster they belong to, and farmers falling in a specific cluster could evaluate whether they are reaching their objectives.

Evidence for swine and human papillomavirus in pig slurry in Italy.

AIMS: The diversity and the geographical distribution of swine papillomaviruses (PVs) are virtually unknown. The occurrence and the diversity of swine PV were therefore investigated in pig slurry collected in Italy, to contribute towards filling this gap in knowledge. METHODS AND RESULTS: Twenty-two slurry samples underwent analysis by nested PCR and DNA sequencing using published and newly designed specific primer pairs for Sus scrofa papillomavirus (SsPV) type 1 and 2 (SsPV1 and 2), along with degenerate PV-specific primers targeting the major coat protein L1 and the helicase protein E1. Overall, three samples (13·6%) were positive for SsPV1 by specific primers, and nucleotide (nt) sequences showed 99-100% nt identity with SsPV1 variant a (EF395818), while SsPV2 was not found in any sample. Using generic primers, eight samples (36·4%) were tested positive for human papillomavirus (HPV), and were characterized as follows: ß1-HPV8, ß1-HPV14, ß1-HPV206, ß2-HPV113, ß2-HPV120 and γ1-HPV173. Moreover, one unclassified γ-type was detected. CONCLUSIONS: Both swine and human PVs were detected in pig slurry in this study. The unexpected presence of HPV in pig waste could be explained as the result of an improper use of the sewage collection pits and/or with improper procedures of the operators. SIGNIFICANCE AND IMPACT OF THE STUDY: This study reports the first detection of SsPV1 in Italy, along with the first detection of HPVs in pig slurry samples in Italy, and expands our knowledge about PV diversity and geographic distribution.

Hepatitis E Virus (Genotype 3) in Slurry Samples from Swine Farming Activities in Italy.

Hepatitis E virus (HEV) is an emergent causative agent of acute hepatitis, transmitted by fecal-oral route. Infection with HEV is a global cause for morbidity and mortality throughout the world: it mainly causes large outbreaks in endemic areas and sporadic autochthonous cases in industrialized countries where HEV infections seem to be an emergent zoonotic disease. Infection of porcine livestock and its relationship with the human cases have been demonstrated. The present study describes an investigation on the prevalence and diversity of HEV in pig slurry in Italy. Slurry samples (24) were collected from ten farms located in North Italy during 2015 and analyzed for HEV, using four broad-range nested PCR assays targeting ORF1 (MTase), ORF2 (capsid) genes, and ORF2/3 regions. Overall, 18 samples (75%) were positive for HEV RNA, and characterized as genotype 3. Nine samples could be subtyped by ORF2 sequencing: Eight belonged to subtype 3f, while one sequence could not be characterized by blast analysis and phylogenetic analysis and may actually represent a new subtype. Furthermore, similarity of 99% was found between 3f Italian HEV sequences of human and swine origins. Real-Time PCR assay was also performed, in order to obtain quantitative data on positive samples. Two swine slurry samples were positive, containing 600 and 1000 UI per mL of sewage. The results of this study show that HEV strains belonging to zoonotic genotype 3 are widely present in swine excreta, and have high degree of identity with strains detected in autochthonous HEV cases. Improving swine farming operations safety and increasing operators' awareness of the zoonotic potential connected with the handling of swine effluents turn out to be key points in order to reduce the environmental and sanitary problem represented by the possible dissemination of HEV to water bodies.

Methodology for quantifying the behavioral activity of dairy cows in freestall barns.

The objectives of this study were to 1) evaluate the validity of automated monitoring systems as assessment method for the behavioral activity of dairy cows compared with video recording, and 2) determine the sampling intervals required to obtain reliable estimates of the daily behavior. To determine lying, standing, and walking, 12 cows were equipped with automatic recording devices (IceTag = 12 cows, HOBO Pendant G = 5 cows), and their behavior was simultaneously recorded using a video recording system. The correspondence between the IceTag, HOBO logger, and video recording data was analyzed using 2 × 2 contingency tables, and we determined the sensitivity, specificity, and predictive value (positive and negative). Both types of loggers demonstrated high sensitivity (Sen ≥ 0.961) and specificity (Sp ≥ 0.951) for lying and standing behaviors with predictive values near 1.00. The HOBO logger can accurately describe the laterality of lying behavior, whereas the IceTag device inadequately recorded walking, with probability predictive values ≤ 0.303. Daily behaviors of the dairy cows were compared for 10 different sampling intervals (1 s, and 1, 2, 3, 4, 5, 10, 15, 30, and 60 min) collected by the IceTag, using linear regression. A strong relationship (R(2) ≥ 0.978) was found between the total lying times from data on a per-second basis and estimates obtained by 1, 2, 3, 4, 5, 10, and 15 min sampling intervals. The sampling intervals of 1 and 2 min were comparable for all aspects of lying behavior (R(2) ≥ 0.813; P > 0.05 for slope = 1, intercept = 0). Long sampling intervals (30 and 60 min) showed positive relationship for estimating time spent lying and standing (R(2) ≥ 0.774), but were inappropriate for predicting these behaviors, because they lacked accuracy and precision. Both the IceTag and HOBO logger accurately measured all aspects of lying and standing behavior. Reliable estimates of lying and standing time can be generated using relatively short interval lengths (e.g., 3, 4, 5, 10, or 15 min). Shorter sampling intervals (≤ 2 min) are required to accurately measure aspects of lying behavior such as number of lying bouts per day. The automated monitoring systems are time- and labor-saving tools that can be used by research or on farm to assess cow comfort related to lying behavior.