Improving rice yield, its stability, and nutrient use efficiency in sub-Saharan Africa using good agricultural practices
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Context: Increasing rice productivity is key to achieve rice self-sufficiency in sub-Saharan Africa (SSA) where
current consumption surpasses local production, mainly due to low yield associated with sub-optimal manage
ment practices. Good agricultural practices (GAPs) – considered as an integrated practices including soil, water,
weed, pest, and disease management are critical in increasing farmers’ yields. However, there is a lack of
comprehensive assessment of on-farm yield variation with GAPs across production systems and agroecological
zones (AEZs) at the continental level.
Objectives: The objectives of the study were to (i) quantify yield variation with GAPs in three production systems
and (ii) identify major production factors causing yield variation.
Methods: From 2013 – 2022, GAPs were tested on-farm in 987 fields across 34 sites in 20 SSA countries. Yield
data from GAPs plots were compared with farmers’ yields obtained from an independent yield gap survey.
Results: Yield with GAPs varied significantly (p < 0.001) across production systems and AEZs. Mean yields were
5.1, 3.9, and 2.5 t ha–1
in irrigated lowland (IL), rainfed lowland (RL), and rainfed upland (RU), respectively.
Yield gain with GAPs averaged 0.7, 1.1 and 0.8 t ha–1
in IL, RL and RU; and was smaller in sites having higher
farmers’ yields. Overall, 78, 87 and 88 % of the GAPs plots in IL, RL and RU, respectively, had higher yields
compared with farmers’ yields. GAPs significantly (p = 0.01) reduced yield variation across production systems
by 25, 29 and 20 % in IL, RL and RU, respectively. N, P and K use efficiencies, defined as partial factor pro
ductivity (kg grain/kg nutrient applied), were significantly (p < 0.001) higher in IL (59, 153 and 151 kg grain/kg
N, P and K, respectively), followed by RL (47, 123 and 129 kg grain/kg N, P and K) and lowest in RU (31, 81 and
80 kg grain/kg N, P and K), with positive correlations between yield and N, P and K use efficiencies. Across
production systems and AEZs, bunding, levelling, basal N, P and K and total N rates were among the top ranked
management practices influencing yield, where high yielding plots were associated with good levelling and
bunding.
Conclusion: There is substantial potential to further increase productivity by improving on-farm management
practices—particularly to enhance nutrient use efficiency—to close rice yield gaps across diverse production
systems in SSA.
Significance: The study contributes to better understanding of the effect of GAPs on yield and yield variation, and
production factors that influence yield variation at a large geographical area of SSA
Palabras clave
rice, yields, agricultural practices