Maize varietal replacement in Eastern and Southern Africa: Bottlenecks, drivers and strategies for improvement.

Seed security is vital for food security. Rapid-cycle, climate-adaptive breeding programs and seed systems that deliver new, elite varieties to farmers to replace obsolete ones can greatly improve the productivity of maize-based cropping systems in sub-Saharan Africa (SSA). Despite the importance and benefits of accelerated varietal turnover to climate change adaptation and food security, the rate of maize varietal replacement in SSA is slow. This review outlines the major bottlenecks, drivers, risks, and benefits of active replacement of maize varieties in eastern and southern Africa (ESA) and highlights strategies that are critical to varietal turnover. Although there is an upsurge of new seed companies in ESA and introduction of new varieties with better genetics in the market, some established seed companies continue to sell old (over 15-year-old) varieties. Several recently developed maize hybrids in ESA have shown significant genetic gains under farmers' conditions. Empirical evidence also shows that timely replacement of old products results in better business success as it helps seed companies maintain or improve market share and brand relevance. Therefore, proactive management of product life cycles by seed companies benefits both the farmers and businesses alike, contributing to improved food security and adaptation to the changing climate.

Performance, Variance Components, and Acceptability of Pro-vitamin A-Biofortified Sweetpotato in Southern Africa and Implications in Future Breeding.

In sub-Saharan Africa (SSA), vitamin A deficiency (VAD) is a major cause of blindness in children under 5 years. Sweetpotato (Ipomea batatas L.) is widely grown in this region, and pro-vitamin A varieties could help to combat such problems. Fourteen newly introduced orange-fleshed sweetpotato (OFSP) varieties from the International Potato Centre (CIP) and two local checks were evaluated at four environments using a 4 × 4 triple-lattice design for total tuber yield, marketable yield, unmarketable yield, total tuber numbers, marketable tuber numbers, unmarketable tuber numbers, dry matter content, and sensory characteristics on boiled sweetpotato. Since varieties were previously tested intensively by CIP under diverse conditions, the focus of the current study was to determine their acceptability by farmers. Across-environment ANOVA showed highly significant differences (P < 0.001) for environments, genotypes, and genotype × environment interaction (GE) for all traits studied. Variety Cecelia outperformed the rest in three environments. Cecelia, Erica, Ininda, and Lourdes were found to be the top four most stable and high-yielding varieties. Genetic gains of the top four varieties over the preferred local check Mai Chenje ranged from 135 to 184%, and across-environment broad-sense heritability was 60% for tuber yield. Furthermore, farmers accepted the dry matter content (which was >25%) and taste of all the introduced OFSP varieties. Since there was a high acceptability by farmers, introductions from CIP could help improve human nutrition. Despite the appropriate design, the error variance component was the highest for all traits, and proper field plot techniques were proposed in future breeding and testing activities.

Multi-Site Bundling of Drought Tolerant Maize Varieties and Index Insurance.

Drought Tolerant Maize Varieties (DTMV) and Rainfall Index Insurance (RII) are potential complements, though with limited empirical basis. We employ a multivariate spatial framework to investigate the potential for bundling DTMV with a simulated multi-site and multi-environment RII, designed to insure against mild, moderate and severe drought risk. We use yield data from on-farm trials conducted by the International Maize and Wheat Improvement Center (CIMMYT) and partners over 49 locations in Eastern and Southern Africa spanning 8 countries and 5 mega-environments (dry lowland, dry mid altitude, wet lower mid altitude, low wetland and wet upper mid altitude) in which 19 different improved maize varieties including DTMV were tested at each location. Spatially correlated daily rainfall data are generated from a first-order two-state Markov chain process and used to calibrate the index and predict yields with a hierarchical Bayes multivariate spatial model. Results show high variation in the performance and benefits of different bundles which depend on the maize variety, the risk layer insured, and the type of environment, with high chances of selecting a sub-optimal and unattractive contract. We find that complementing RII with a specific DTMV produces contracts with lower premiums and higher guaranteed returns especially in dry lowland increasing the chances of scaling up RII within this environment.