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Gene mining
African rice germplasm to improve drought resistance in rainfed production
systems for resource-poor farmers of Africa
M-N. Ndjiondjop,
H. Gridley
Rice has been
cultivated in western and central Africa for centuries and is now a staple
food in the region. But drought is a major problem as it severely depresses
yield in upland and rainfed lowlands, where most of the producers are
resource-poor farmers. Drought resistance in plants, however, is a complex
trait, controlled by the interaction of many genes, as it involves several
physiological, phonological and morphological mechanisms. Consequently,
conventional breeding for drought resistance in Africa has had but limited
success. DNA markers and genetic mapping are expected to provide impetus not
only in gaining a better understanding of the traits associated with drought
but also by contributing to enhanced selection efficiency.
The project seeks
to 1) characterize drought in different environments and identify the most
important traits associated with drought resistance, 2) select and
characterize sources of drought resistance for genetic mapping and
quantitative trait locus (QTL) analysis, and 3) develop advanced lines
combining drought resistance with heavy yield and agronomic and quality
characters acceptable to farmers and consumers. To achieve these objectives
the project will exploit a core germplasm pool (Oryza glaberrima and
O. sativa) of 1) drought-resistant O. glaberrima accessions,
collected and screened in Mali by the Institut d’Economie Rurale (IER), 2)
drought-tolerant interspecific breeding lines developed by the Africa Rice
Centre (WARDA) from crosses between O. glaberrima and O. sativa,
and 3) a range of traditional O. glaberrima and O. sativa
accessions from WARDA’s gene bank. Confirmed sources of resistance among
this core germplasm will be crossed with elite but drought-susceptible O.
sativa lines to develop interspecific and intraspecific populations
segregating for drought resistance. These populations will be phenotyped in
replicated field trials in different environments in Mali and Nigeria. QTL
analysis will be performed to identify, across environments,
drought-improving alleles for future breeding. In other populations,
selection will be conducted to generate agronomically superior
drought-resistant lines.