Geospatial Analysis Of Cassava Commercialisation In Tanzania

Promoting cassava production and solving challenges that are associated with cassava processing and commercialisation has been a priority for government and non-governmental organisations in Tanzania. However, the commercialisation process is hindered by the bulkiness and natural occurrence of toxic substances (cyanogens) in cassava. The bulkiness in cassava raises transportation costs and occurrence of toxic substances poses health hazard to people consuming cassava. The purpose of this study was to analyse distribution of cassava production in Tanzania in relation to number of cassava farmers, area under cassava, yield and production; examine spatial patterns of cassava production so as to identify areas of marked difference and finally, examine spatial relationships in cassava pricing in local markets so as to understand their implications to cassava commercialization process. Through mapping, cassava distribution was analyzed. Moran’s Index of global autocorrelation and local indicator of spatial autocorrelation were used to explore spatial patterns of farmers across the country. Hot spot analysis using Getis-ord GI* was conducted to identify areas with significantly high and low values of cassava yield figures. Price pattern of cassava was also examined using global indicator of autocorrelation (the Moran’s Index). The results revealed that cassava production in Tanzania is concentrated in the southern zone (Mtwara and Lindi regions), Lake Victoria zone (Mara, Kagera and Mwanza regions) and Indian Ocean coast. Each of these regions account for between 7% to 15% of total cassava farmers. Further, hot spot analysis identified 12 significant hot spots in five regions; Mtwara, Lindi, Mara, Mwanza and Pwani. Mtwara accounts for about 33% and Mwaza 25% of these hot spots. Finally, autocorrelation of prices in cassava were discovered implying that prices of cassava in neighbouring markets influence each other. In principal, cassava commercialization can be effective if concentration can be in areas where more farmers, large proportions of land and higher production figures were observed.