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Contemporary methods used in early pregnancy diagnosis (ePD) in cows have been presented. Despite many new diagnostic tests, the choice methods still remain per rectum palpation and ultrasound examinations (US). The clinical examination is performed about 35 days post insemination, US at about 28 days. When compared to per rectum examination, early ultrasound pregnancy diagnosis (eUSPD) in cows enables an earlier diagnosis or exclusion of pregnancy, confirming of viability and/or evaluation of fetus growth. Ultrasound imaging is a relatively simple and safe noninvasive technique. Accuracy (ACC), sensitivity and negative predictive value for pregnancy diagnosis using miniature, portable ultrasounds equipped with sector or linear probes assessed in 30th day after insemination is 83, 83.2 and 79.6% or 89.4, 95.2 and 91.9% respectively. Relatively low accuracy of ultrasound examination depends of both false negative and positive results. Accuracy is also influenced by such factors as: operator’s experience, technical parameters of the apparatus, individual traits of animals, and environmental conditions. Accuracy of eUSPD could be lowered in the case of pregnancy loss. Included in indirect methods of pregnancy diagnosis is examination consisting in qualitative and quantitative detection of specific substances in systemic fluids (blood, plasma and cot) produced during pregnancy. These are: early pregnancy factor ECF detection, progesterone concentration, PAG, IGF-1 and estrogen, test of specific protein B (PBSP) in blood plasma concentration. On the other hand, highly useful in the evaluation of embryo mortality in early pregnancy is the estimation of pregnancy protein DG29. However, due to their low efficiency (time consuming and low accuracy) these tests are not widely applied in practice. All methods of pregnancy diagnosis in cows should be characterized by high accuracy. Most of them have those features, but none of them combine all of them. It would seem that in the future early pregnancy diagnosis should be directed toward diagnosing based on quick, sensitive and inexpensive qualitative tests as well as completing ultrasound examinations.
Monitoring the presence of residues of unauthorized substances, chemical and biological residues, medicinal products and radioactive contamination in food is an important element of the system for protection of consumers against hazardous foods. The aim of the study was to analyze the results of monitoring tests for the presence of antibiotics and chemotherapeutics affecting consumer safety in products of animal origin that were carried out in Poland in the years 2003-2017. The material for analysis were annual reports on the results of tests for the presence of prohibited substances, chemical and biological residues, medicinal products and radioactive contamination in food produced in Poland. Samples for testing were taken at random from food of animal origin produced on farms under the supervision of the Veterinary Inspectorate. The reports present data on monitoring tests carried out in the years 2003-2017. The analysis was based on the results for B1 substances, which include antibacterial substances, antibiotics and chemotherapeutics approved for use in food-producing animals. The results from the last two years of research were analyzed in detail, including the results for prohibited substances with antibacterial action from group A6 (prohibited substances) and, in the case of poultry, for coccidiostats (group B2b).The results of the monitoring studies in Poland indicate that both veterinarians and animal breeders were aware that the proper use of chemotherapeutics and compliance with waiting periods are necessary to ensure food safety. Samples that exceeded the standards represented less than 0.3% of all samples tested in all types of food. According to the results of these studies, antibiotic residues were most frequently found in honey.
The aim of this study was to examine the possibility of using characteristic features (physical and behavioral) of selected animals in the process of creating neural classification models. A set of specific properties constitutes the basis for the use of a classifier in the form of an artificial neural network. Its construction is based on the need to obtain information encoded in the form of an analyzed image. In this study, examples of potential applications of image neural analysis were presented and possibilities of using this technique in the field of veterinary medicine were proposed. Examples of potential applications were listed. The method of identification and description of characteristic areas visible in the ultrasound image of a cow’s uterus were characterized. The need for the skillful gathering of empirical graphic data was considered as vital in order to conduct the extraction of features and the creation of a self-learning representative set.
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