The Benefit of Farmers' usage of the Early Warning Application for Climate in Some villages of Aswan Governorate

Abd El-Fattah Noseir, Hala Shokry; Mohamed M. Souka, Eman Diaa EL-Deen; Abd El-Hameed Ali, Beelal Ali

doi:10.21608/asejaiqjsae.2024.348368

The Benefit of Farmers' usage of the Early Warning Application for Climate in Some villages of Aswan Governorate

Document Type : Original Article

Authors

¹ Agricultural Extension and Rural Development Research Institute, Agricultural Research Center, Arab Republic of Egypt.

² Central Laboratory for Agricultural Climate, Agricultural Research Center, Arab Republic of Egypt.

10.21608/asejaiqjsae.2024.348368

Abstract

The main objective of this research was studying the benefit of farmers' usage of the early warning application for climate in some villages of Aswan Governorate, Research data were collected by using personal questionnaire, and the sample was 120 farmers which represent 10% of population. The statistical methods used for data analysis were; frequency, percentage, mean, weighted average, standard deviation, Pearson's correlation coefficient and multiple regression coefficients by using computer and the analytical program Spss.
Below are the most important results of the research:
- More than 83% of respondents was in medium and high category of age, more than 83% of them was married, 45% had a medium level of education, more than half of them gained more than 3000 L.E as a farm income, 56%of them were using the app. for a medium period while 85% of them were using the app. for one hour a day.
- 68.33% of the respondents was medium in the benefit of usage of the early warning application for climate, Significant correlation was determined between the benefit of usage of the early warning application for climate and 5 of independent variables which are age, educational level, farm income, the period of use and the usage rate. And concerning multiple regressions the results indicate that 5 independent variables are responsible for the explanation of 24.1% of the possible total variance in the dependent variable and the regression function was significant at probability level 0.01.

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