Risk assessment of soybean rust based on its distribution, variance and influence of environmental parameters in eastern and southern Africa.

Soybean is increasingly becoming an important legume crop in Africa because of its role in providing valuable protein and oil and significant potential for food and animal feed in the region. Commercial soybean production on large farms takes place in Zambia, Zimbabwe and South Africa. However, it is mostly cultivated by small-scale farmers in other parts of Africa where it is planted as a minor food crop among sorghum, maize, or cassava. Approximately 6.6 million households grow soybean in sub-Saharan Africa with an estimated increase in production of 2.3% per year. The importance of soybean is directly linked to its nutritional content as it contains 40% protein and 20% oil in additional to essential minerals. Asian soybean rust (Phakopsora pachyrhizi) is an important disease causing massive yield losses estimated at 10-90%. The spores are perfectly adapted to long distance dispersal through wind patterns resulting in epidemics in new and disperse geographical locations. The risk of the disease establishing itself in new areas is difficult to determine because of a lack of effective monitoring mechanisms and because the disease is inherently difficult to diagnose. The fungus is highly variable with different pathotypes of the pathogen identified in different countries worldwide. Ineffectiveness of known single dominant resistance genes when challenged with isolates of Phakopsora pachyrhizi from different continents has been reported. Early and accurate detection of the fungus combined with prevailing wind patterns, can facilitate the mapping of soybean rust distribution and monitor the risk of spread. Therefore this project aims at developing rapid diagnostic methods to monitor rust before its establishment in the field. The predominant pathotypes of the pathogen present and their distribution in the region will be determined using soybean rust host differentials and molecular analysis using SSR markers. Knowledge of the predominant pathotypes in the region will enhance targeted deployment of resistant germplasm for better disease management.