Evaluation of drought and heat stress tolerance of diverse sorghum germplasm

The study was developed as part of the project “Exploring wide crosses derived crop biodiversity (sorghum x maize) for climate resilience and food and nutrition security in Eastern and Southern Africa” funded in the 4th cycle of the Benefit Sharing Fund (BSF) of the International Treaty of Plant Genetic Resources for Food and Agriculture (ITPGRFA) of the Food and Agriculture Organisation (FAO) of the United Nations (UN).

 The study made use of one of the reliable but rarely used statistical tools called Path coefficient analysis which enables partitioning and quantification of interrelated independent variables of different components and their direct and indirect effects on grain yield as a response to stress tolerance through regression correlation estimates. Such knowledge will play a pivotal role in enhancing breeding initiatives to improve heat and moisture stress tolerance and in management of cropping systems. The study will make use of a natural and cheap method of simultaneously inducing heat and drought stress on the field by altering planting dates to coincide heat and drought stress period of the season with the reproductive stages of the crop. Though the method is dependent on weather patterns that are not static it mimics the natural environmental conditions hence results will be more applicable to farmers’ conditions. Sorghum is well adapted and has a very low risk of failure, therefore research on such crops of high energy and nutrition need to be promoted.

Hence results of research of this nature may increase adoption and resilience in marginal communities especially for communities prone to malnutrition, HIV prevalence, dominated by the elderly and children (Amadou et al., 2013). Thus the research will identify genotypes that are tolerant to heat and drought stress, predictive ability of different screening techniques, indices and various statistical tools in sorghum and the genotypes to be used will be explored as well.