Breeding new and high performing cultivars with market‐preferred traits take more than 10 years in the absence of an integrated pre‐breeding programme. During the early phases of breeding a significant amount of time, space and resources are invested in the selection and genetic advancement stages after initial crosses are performed with parental genotypes. Speed breeding has the potential to reduce the time required for cultivar development, release and commercialization. The objective of this review was to present the key opportunities and challenges of speed breeding to guide pre‐breeding and breeding programmes. Key challenges of speed breeding include: (a) access to suitable facilities, (c) staff trained in the protocol, (b) adopting major changes to breeding programme design and operations, and (d) the need for long‐term funding. The current review highlights the potential advantages of speed breeding for the successful development and release of pure line cultivars in self‐pollinated crops in ~5 years versus 8 to 10 years when using traditional methods.

Genotype-by-environment interaction analysis is key for selection and cultivar release, and to identify suitable production and test environments. The objective of this study was to determine the magnitude of genotype-by-environment interaction (GEI) for storage root yield, yield-related traits and sweet potato virus disease (SPVD) resistance among candidate sweet potato genotypes in Tanzania. Twenty-three newly bred clones and three check varieties were evaluated across six diverse environments using a randomized complete block design with three replications. The Additive Main Effect and Multiplicative Interaction (AMMI) and genotype and genotype-by-environment (GGE) biplot analyses were used to determine GEI of genotypes. Genotype, environment and GEI effects were highly significant (P ≤ 0.01) for the assessed traits. Further, AMMI analysis of variance revealed highly significant (P ≤ 0.001) differences among genotypes, environments and G × E interaction effects for all the studied traits. Both AMMI and GGE biplot analyses identified the following promising genotypes: G2 (Resisto × Ukerewe), G3 (Ukerewe × Ex-Msimbu-1), G4 (03-03 x SPKBH008), G12 (Ukerewe × SPKBH008) and G18 (Resisto × Simama) with high yields, high dry matter content and SPVD resistance across all test environments. The candidate genotypes are recommended for further stability tests and release in Tanzania or similar environments.

Fruit quality traits of sweet watermelon (Citrullus lanatus var. lanatus) are crucial for new product development and commercialization. Sweet watermelon fruit quality traits are affected by the compositions of phytochemical compounds, phytohormones, and fruit flesh firmness which are affected by genes, the growing environment and their interaction. These compositions determine fruit ripening, eating quality, and postharvest shelf-life. Knowledge of the genetic profile and analyses of quality traits in watermelon is vital to develop improved cultivars with enhanced nutritional compositions, consumer-preferred traits, and extended storage life. This review aims to present the opportunities and progress made on the genetic analysis of fruit quality traits in watermelon as a guide for quality breeding based on economic and end-user attributes. The first section of the review highlights the genetic mechanisms involved in the biosynthesis of phytochemical compounds (i.e., sugars, carotenoids, amino acids, organic acids, and volatile compounds), phytohormones (i.e., ethylene and abscisic acid) and fruit flesh structural components (i.e., cellulose, hemicellulose, and pectin) elicited during watermelon fruit development and ripening. The second section pinpoints the progress on the development of molecular markers and quantitative trait loci (QTL) analysis for phytochemical compounds, phytohormones and fruit quality attributes. The review presents gene-editing technology and innovations associated with fruit quality traits for selection and accelerated cultivar development. Finally, the paper discussed gene actions conditioning fruit ripening in citron watermelon (C. lanatus var. citroides [L. H. Bailey] Mansf. ex Greb.) as reference genetic resources to guide current and future breeding. Information presented in this review is useful for watermelon variety design, product profiling and development to serve the diverse value chains of the crop.

Finger millet is a climate‐resilient and highly nutritious small grain crop widely grown in the semi‐arid tropics. It has multiple uses, including for food, feed and beverage preparations. However, finger millet is an under‐utilized and under‐researched crop with a mean yield of <1.0 t/ha despite a potential productivity of up to 8 t/ha. The yield gap is attributed to several production constraints, such as biotic and abiotic stresses, a lack of access to improved seeds and production inputs and poor agronomic management practices. There are valuable genetic resources and genetic variability of finger millet in its centres of diversity and global gene banks for variety design, product development and commercialization. The genetic variability can be harnessed further to integrate essential traits into candidate varieties through conventional and modern breeding methods. Breeding and genetic innovations such as genomics‐assisted breeding, mutation breeding and genome editing would accelerate finger millet breeding and new variety design and deployment. The objective of this review was to document the opportunities, challenges and prospects of finger millet improvement as a guide for variety development and deployment with enhanced grain yield and nutritional contents. The first section describes global production status and yield gains, major production and productivity challenges in finger millet. This is followed by an in‐depth presentation on breeding and genetic progress on variety development with improved agronomic and nutritional quality traits, drought and salinity tolerance, and fungal diseases, weeds and insect pest resistance. Further, the review summarized finger millet's genetic and genomic resources, reference genomes, whole genome re‐sequencing and transcriptomics of finger millet technologies, genetic engineering and genome editing and their integration with conventional breeding methods for variety design with desired end‐use traits. The review provides foundational information to expedite the development of new‐generation finger millet cultivars with desirable product profiles, including high grain yield potential, early maturity, desirable seed colour, compact head type, food and feed nutrients quality and high marketability through modern breeding approaches.

Sorghum (Sorghum bicolor (L.) Moench) is the main food staple for millions of people in Sub-Saharan Africa (SSA) and Asia. Sorghum is relatively drought tolerant and cultivated in arid and semi-arid regions under rain-fed production. However, severe drought stress often leads to crop loss and declined productivity. The development and deployment of high-yielding and drought-adapted genotypes is a cost-effective strategy for sustainable sorghum production globally. The objective of this study was to determine drought tolerance and genotype-by-environment interaction (GEI) effects on grain yields of a population of African sorghum genotypes to identify high-yielding and drought-adapted genotypes for direct production and also for use in breeding programs. Two hundred and twenty-five sorghum genotypes were evaluated under non-stressed (NS), pre-anthesis drought stress (PreADS), and post-anthesis drought stress (PoADS) conditions under field and greenhouse environments using a 15 × 15 alpha lattice design in two replicates. The three water regimes and two environments resulted in six testing environments. Data were collected on grain yield and drought tolerance parameters, and additive main effect and multiplicative interaction (AMMI) analysis were computed. The mean grain yield under NS, PreADS, and PoADS were 3.70, 1.76, and 2.58 t/ha, in that order. The best genotypes adapted to non-stressed environments were G09, and G109, whereas G114 and G56 were suitable for non-stressed and stressed conditions. G72 and G75 displayed the best performance in PreADS conditions only, whereas genotypes G210 and G12 were identified as high performers under PoADS only. The AMMI analysis revealed that genotype (G), environment (E), and GEI were significant (p < 0.05), which accounted for 38.7, 44.6, and 16.6% of the total explained variation in grain yield. AMMI 4 was the best-fitting model for grain yield. Based on AMMI 4 and the Best Linear Unbiased Estimates (BLUPs) calculations, genotypes G119 and G127 with a grain yield of 5.6 t/ha and 6.3 t/ha were selected as being suitable for non-stressed conditions. Genotypes G8 and G71 with BLUPs of 2.5 t/ha and 2.6 t/ha were best-suited for pre-anthesis drought stress conditions, whereas genotypes G115 and G120 with BLUPs of 4.2 t/ha and 4.3 t/ha are recommended for post-anthesis drought-prone environments, respectively. The identified sorghum genotypes are recommended for production in dry agro-ecologies of sub-Saharan Africa characterized by pre-and-post anthesis drought stress. In addition, the identified genotypes are valuable genetic resources to develop novel drought-tolerance material.