# Genetic progress in rice yield: preliminary insights from historically released varieties in Sub-Saharan Africa

## TL;DR

This study estimates genetic gains in rice yield from varieties released in Sub-Saharan Africa between 1986 and 2020, showing modest but consistent improvements across different growing conditions.

## Contribution

The study provides the first empirical assessment of genetic gains in rice yield from AfricaRice-bred varieties using multilocation trial data across ecologies in SSA.

## Key findings

- Positive genetic trends were observed across all ecologies, with the highest at 12 kg/ha/year in rainfed lowland.
- Top-performing varieties like ARICA 18 and FARO 59 contributed significantly to yield gains in specific ecologies.
- The study highlights the need for continued investment in modern breeding tools to accelerate rice yield improvements in SSA.

## Abstract

Rice is a vital staple crop in sub-Saharan Africa (SSA), where improving grain yield is critical for food security and economic growth. Assessing genetic gain over time is essential for measuring breeding effectiveness and guiding future strategies and evaluating the return on investment in rice improvement programs. This study aimed to estimate baseline genetic gains in grain yield from AfricaRice-bred released and pre-released varieties between 1986 and 2020 using multilocation data from ERA trials. “ERA trials” are designed to estimate historic rates of genetic gain for grain yield by testing a series of varieties released over different years or different breeding periods or “eras.” Three sets of trials representing irrigated lowland, rainfed lowland, and rainfed upland ecologies were conducted in 2021 and 2022 at AfricaRice breeding stations in Côte d’Ivoire, Nigeria, and Senegal as well as National Agricultural Research and Evaluation Systems (NARES) sites in Burkina Faso, Guinea Conakry, and Mali. The trials were conducted using an alpha- lattice design with three replications, and data were collected on grain yield, plant height, and days to flowering. A two-stage analysis was implemented, where genotype-by-environment (G × E) means from the first stage were used in the second stage to model G × E interaction with a second-order factor analytic model, thereby accommodating genetic heteroscedasticity across environments and enabling estimation of genetic trends. Finlay–Wilkinson regression model identified high-performing and stable varieties in each ecology. Consistent positive genetic trends were estimated across all the ecologies, though gains remained low: 12 kg/ha/year (0.34%) in rainfed lowland, 10 kg/ha/year (0.27%) in rainfed upland, and 7 kg/ha/year (0.14%) in irrigated lowland. The top-performing varieties contributed maximum gains was ARICA 18 in rainfed lowland (16 kg/ha/year), FARO 59 (NERICA 8) in rainfed upland (11 kg/ha/year), and Yiriwamalo in irrigated lowland (8 kg/ha/year).These results highlight the steady progress of AfricaRice breeding programs and underscore the need for continued investment in rapid varietal development using modernized breeding tools to deliver high-yielding, climate-resilient, and market-driven rice varieties for SSA.