Status quo and challenges of rice production in sub-Saharan Africa

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Significant efforts in agronomic research for development have been undertaken to address the challenges in rice cultivation in sub-Saharan Africa. Despite these efforts and achievements, considerable yield gaps in researcher-managed trials as well as farmers’ fields persist. The objectives of this paper are to provide the status quo of rice production and its main challenges,  selected achievements in rice agronomy research mainly by Africa Rice Center, and its partners, and perspectives for future research on rice agronomy. 

Rice is one of the most important staple crops for food security and social stability in large parts of sub-Saharan Africa (SSA). Its consumption has been increasing more rapidly than any other staple crop (Arouna et al., 2021). This rapid increase is driven by high population growth, urbanization, and changing consumer preferences in the region.

Recently reaching one billion inhabitants, SSA has had the highest population growth rate in the world with a mean increase of 2.5% per annum between 2007 and 2016.  During the same period, rice consumption has increased, at a rate of 6% per annum, and is expected to continue to grow in the foreseeable future.

In response to its growing demand in SSA, rice production has increased tenfold since 1961. This has resulted mostly from both an expansion of rice harvested area and, albeit to a lesser extent, an increase in rice production per unit of land (referring to as yield).

Between 2000 and 2020, the harvested area increased from 6.9 million ha to 16.6 million ha, whereas the gain in rice yield was limited, only increasing from 1.7 to 2.1 t/ha.  Recent yield levels are still much lower than the global average which is around 4.8 t /ha.

Furthermore, on average in SSA countries, actual yields are less than half of the potential yield (Yp) or water-limited yield (Yw), suggesting that doubling rice yield is possible. ‘Yp’ is defined as the maximum yield that can be obtained from a crop in a given environment, as determined by simulation models with plausible physiological and agronomic assumptions.

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