The role of extension, marketing and business development services on food security

<p dir="ltr">Data is based on two provinces: KwaZulu Natal and Gauteng provinces. It gives an indication of support given to farmers who benefited from the Comprehensive Agricultural Support Programme (CASP) with emphasis on extension services and business development. The data also provides information on food security of CASP beneficiaries.</p><p dir="ltr">The study used secondary data from the CASP evaluation study that was conducted in 2015 by the University of Pretoria in conjunction with the DPME. The secondary data that was received from the University of Pretoria and Department of Agriculture, Land Reform and Rural Development (DALRRD) was analyzed with the use of Statistical Package for the Social Sciences (SPSS). The analysis only focused on 167 key informants’ data (80 in KZN and 87 in GP). Secondary data was analysed using SPSS focusing on the following indicators to respond to the objectives of the study.</p><p dir="ltr">Secondary data was use for the study. From the acquired master data, a separate dataset with information only on KZN and Gauteng was isolated; an overall final dataset was prepared and cleaned on Statistical Package for the Social Sciences (SPSS). The secondary data was captured on Excel when it was received. The data was then cleaned and transferred to SPSS for analysis. When the secondary data was cleaned, the cleaned database was aligned to better respond to objectives of the study. This database was subjected to descriptive quantitative analysis, including basic statistics, crosstabs, pivot tables, etc. Data from key informant interviews was analysed using qualitative methods.</p><p dir="ltr">Data processing and analysis were done using both qualitative and quantitative methodologies. Utilizing the SPSS, descriptive quantitative analysis was used to analyse the project manager data SPSS. Visuals such as graphs and tables were used to present the data. The database was subjected to extensive descriptive quantitative analysis, including basic statistics such as cross tabs, frequencies and pivot tables. These results were used to draw conclusions as well as recommendations.</p>