The present study aimed to evaluate whether the induction and the formation of an accessory corpus luteum (CL) after AI might increase the pregnancy per AI (P/AI) in heat stressed dairy cows. Starting at d 50±3 post-partum, 113 lactating Holstein cows from one commercial herd during summer were scored for body condition, blood sampled and examined by ultrasound. Those bearing a CL>25mm and progesterone (P4) level>2ng/mL were synchronized using a double PGF2α injection given 12 h apart and AI-ed at detected estrus. In total 18 cows, there were not any signs of estrus (n=10) nor a P4 level <2ng/mL at the time of enrolment (n=8) and therefore they were excluded from the study, leading to 95 cows finally enrolled.. At d5 post-AI, cows were randomly allocated into 2 groups: control group (CON, n=45) without any additional treatment, and treatment group (GnRH, n=50), treated with 0.008 mg Buserelin – a GnRH agonist. Blood sampling and ultrasound examination were done at d5, d14 and at d21 after AI, whereas the pregnancy diagnosis was done at d21 and d30 after AI. Average daily temperature and relative humidity values were used to calculate the temperature-humidity index (THI). The average THI during the experiment was 79.5±0.6. At d5, no differences were observed neither between the number of the CL nor between the P4 level in both groups. At d14 and d21, 82% of the GnRH-treated cows had more than one CL versus 0% of the CON cows. Both at d14 and 21, GnRH-treated cows had higher P4 levels compared to the CON cows (p<0.05). In addition, P/AI were higher in the GnRH group than in the CON group (65% vs. 48.3%, p<0.05), whereas late embryonic losses were higher in CON in comparison to GnRH cows (10.6 vs. 4%, respectively). The BCS at the moment of insemination did not affect P/AI (p>0.05). In conclusion, the induction of an accessory CL at d 5 after AI might increase P/AI in heat stressed dairy cows.
The Welfare Quality® consortium has developed and proposed standard protocols for monitoring farm animal welfare. The uptake of the dairy cattle protocol has been below expectation, however, and it has been criticized for the variable quality of the welfare measures and for a limited number of measures having a disproportionally large effect on the integrated welfare categorization. Aiming for a wide uptake by the milk industry, we revised and simplified the Welfare Quality® protocol into a user-friendly tool for cost- and time-efficient on-farm monitoring of dairy cattle welfare with a minimal number of key animal-based measures that are aggregated into a continuous (and thus discriminative) welfare index (WI). The inevitable subjective decisions were based upon expert opinion, as considerable expertise about cattle welfare issues and about the interpretation, importance, and validity of the welfare measures was deemed essential. The WI is calculated as the sum of the severity score (i.e., how severely a welfare problem affects cow welfare) multiplied with the herd prevalence for each measure. The selection of measures (lameness, leanness, mortality, hairless patches, lesions/swellings, somatic cell count) and their severity scores were based on expert surveys (14–17 trained users of the Welfare Quality® cattle protocol). The prevalence of these welfare measures was assessed in 491 European herds. Experts allocated a welfare score (from 0 to 100) to 12 focus herds for which the prevalence of each welfare measure was benchmarked against all 491 herds. Quadratic models indicated a high correspondence between these subjective scores and the WI (R2 = 0.91). The WI allows both numerical (0–100) as a qualitative (“not classified” to “excellent”) evaluation of welfare. Although it is sensitive to those welfare issues that most adversely affect cattle welfare (as identified by EFSA), the WI should be accompanied with a disclaimer that lists adverse or favorable effects that cannot be detected adequately by the current selection of measures.
Recently, in many parts of the world, greater importance has been given to lamb meat as well as to the intensive production of lamb and sheep, due to demand for this type of meat at affordable prices. In Serbia, similar to most European countries, the structure of total sheep meat production comprises about 70% lamb meat and 30% sheep meat. This study assessed resource-based measures on 11 dairy sheep farms and investigated, in a total of 30 lambs, the effects of sex, the presence of bruises and pneumonia in carcasses, and carcass and meat quality. Carcass (carcass length, thigh length, croup width, subcutaneous fat thickness, presence of bruises) and meat quality (pH, temperature, drip, thawing and cooking losses, color, and meat quality classes) traits were measured post mortem. The most common deficiencies on farms were high stocking density, poor hygienic conditions, dirty drinkers, and lack of outdoor access. Regarding sex differences, higher prevalences of carcass bruises and severe pneumonia were recorded in male lambs. Meat pH (pH45min), sensory color score, and prevalence of dark, firm and dry (DFD) meat were higher in lambs with carcass bruises. The occurrence of quality defects (DFD meat) was higher in lambs with severe pneumonia. It can be concluded that it is necessary to improve the welfare conditions on the lamb farms and pre-slaughter conditions in order to achieve better lamb meat quality.
Providing good animal welfare standards is very important for wild animals in captivity, especially in zoos. Therefore, the aim of this study was to perform a welfare assessment of elephants in the Skopje Zoo using species-specific protocols. Two specific protocols were used for the welfare assessment and were combined for a more unified approach. These protocols focused on the assessment of the elephant’s day-time behaviour, including Qualitative Behaviour Assessment (QBA), as well as the following sections: nutrition, physical health, environment, behaviour and management. Data was collected from the Asian and African elephants that were housed together, in the Skopje Zoo. Both species were observed for three consecutive days, during which time QBA was performed and they were observed on their daytime behaviour. Feeding (42% African, 34% Asian elephant) and anticipatory (35% African, 22% Asian elephant) behaviour were predominantly observed daytime behaviours of both elephants, as well as stereotypic behaviour (30%) of the Asian elephant. Concerning the QBA, ‘uncomfortable’ (296 Asian, 234 African elephants) and ‘relaxed’ (271 Asian, 280 African elephants) were the most dominant descriptors for both elephants. The collected data indicated that the elephants were in good physical health. Regular feeding enrichment, as well as environmental enrichment was recommended. There is room for improvement concerning the management practices of the elephants.
Objective: Identify the occurrence of certain virulence genes of Escherichia coli vaginal isolates associated with postpartum dysgalactia syndrome (PDS) in sows. Materials and methods: Two hundred and two sows from 5 Macedonian pig farms were clinically examined for PDS 12 to 24 hours after farrowing. Vaginal swabs for bacteriological testing were taken from PDS-affected (PDSA, n = 47) and PDS-unaffected (PDSU, n = 155) sows. In total, 74 isolates of E coli were tested by multiplex polymerase chain reaction for the presence of virulence genes related to specific pathogenic strains. Results: Genes associated with extra-intestinal pathogenic E coli (ExPEC) strains were the most prevalent among all tested E coli isolates. The most dominant gene among all E coli isolates was fimC. The iss gene was more prevalent in PDSA sows compared to PDSU sows (P = .02). Multivariable logistic regression showed that lower parity sows (P ≤ .001) and presence of the iss (P = .003) and astA genes (P = .03) were correlated with the occurrence of PDS. Implications: Lower parity sows vaginally infected with E coli associated with particular ExPEC strains are at higher risk of developing PDS. Positive vaginal swabs for E coli and iss gene found early after farrowing were associated with PDS in sows. Classification of E coli into specific ExPEC pathotype was not possible by virulence genotyping only.
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