Farmers' knowledge of the most important diseases affecting Cattle and how to prevent and treat them at Kafr El-Sheikh Governorate

Abdullah, Ahmed M.; El-Bbarky, Samaa F.; El- Naggar, Mahmoud E.

doi:10.21608/jsas.2024.316426.1481

Farmers' knowledge of the most important diseases affecting Cattle and how to prevent and treat them at Kafr El-Sheikh Governorate

Document Type : Original Article

Authors

¹ Agricultural Economics Dept., Agricultural Extension Branch, Faculty of Agriculture - Kafr El-Sheikh University, Egypt

² Agricultural Extension and Rural Development Research Institute, Sakha, Agricultural Research Center, Egypt

10.21608/jsas.2024.316426.1481

Abstract

This research mainly aimed to identify the knowledge of the farmers surveyed about the most important diseases that affect livestock and how to prevent and treat them in Kafr El-Sheikh Governorate on a sample of 220 respondents. The necessary data to achieve the research objectives were collected using a questionnaire form with a personal interview. Percentages, arithmetic mean, standard deviation, simple correlation coefficient, and multiple regression coefficient were used to analyze the data of this research. The most important results were: The results showed that about 54%, about 55%, about 75%, about 54%, and about 63% of the farmers surveyed had low and medium knowledge of the most important diseases that affect livestock and how to prevent and treat them, and the general animal health specifications that must be available when purchasing it, and infectious diseases (bacterial), parasitic diseases, and non-infectious diseases (internal diseases) respectively, and that the variables included in the research combined are related to the degree of knowledge of the farmers surveyed about the most important diseases that affect livestock and how to prevent and treat them as a dependent variable with a correlation coefficient of 0.501, which is a value that was proven significant at the probability level of 0.01 based on the calculated value of 4.547. The results also indicate that the independent variables combined explain 25.1% of the variance in the dependent variable based on the value of the coefficient of determination R2.

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