Genomics and Applied Biology 2024, Vol.15, No.6, 307-319 http://bioscipublisher.com/index.php/gab 309 3 Challenges and Opportunities in Yam Breeding 3.1 Major challenges in yam breeding: genetic diversity and complexity Yam breeding, particularly for Dioscorea species, faces significant challenges due to the complexity of their genomes, which are often polyploid. Polyploid genomes, containing multiple sets of chromosomes, introduce layers of genetic intricacy that complicate breeding efforts. These complex genomes contain a high degree of genetic diversity, which, while essential for adaptation and resilience, presents hurdles in selectively breeding for desirable agronomic traits. Traits such as yield, drought tolerance, and disease resistance are controlled by multiple genes, a phenomenon known as polygenic control, which makes it challenging to pinpoint specific genes responsible for these characteristics (Saski et al., 2015). This polygenic nature, combined with high genetic variation, slows down the breeding process as it is difficult to isolate and stabilize desired traits. Another critical challenge in yam breeding is the extensive genetic diversity among yam cultivars, which, although advantageous for the species' adaptability to different environments, complicates selection processes. This diversity means that breeders must carefully consider genotype-by-environment interactions to ensure that the selected traits perform consistently across different growing conditions. Such interactions can influence the expression of key traits, making it challenging to achieve stable trait performance in a single variety that can adapt to a wide range of environments (Agre et al., 2021). Consequently, breeders must conduct extensive multi-environment trials to identify cultivars that can reliably express traits like high yield and resistance to pests and diseases under varied environmental pressures. 3.2 Limitations of traditional breeding methods Traditional yam breeding methods are constrained by long generation times, as yam plants require extended growth periods to develop observable phenotypic traits. This leads to prolonged breeding cycles, often spanning several years, significantly delaying the development of new varieties. Additionally, traditional selection methods rely heavily on phenotypic assessments, which can be inconsistent across different environments, impacting the accuracy and stability of trait evaluation. Such variability poses challenges in selection, as traits that perform well in one environment may not exhibit the same favorable expression in another, limiting the effectiveness and adaptability of new varieties (Asfaw et al., 2020). Traditional breeding approaches also depend on labor-intensive field trials and complex crossbreeding processes, further slowing down the breeding timeline. Field trials require multiple observations and measurements over extended periods to gather sufficient data, consuming significant time and resources. This dependency on lengthy and labor-intensive methods hampers the ability of breeders to respond quickly to emerging agricultural needs, such as shifting disease pressures, climate change, and evolving market demands. Yam’s extended growth cycles and environmental requirements make it difficult to efficiently select individuals with desired traits, resulting in breeding programs that struggle to keep pace with modern agricultural challenges and limiting the speed and adaptability of yam crop improvement. 3.3 Feasibility of genomic selection as a solution Genomic selection (GS) offers a transformative approach to yam breeding by allowing early selection based on genomic estimated breeding values (GEBVs). This approach can significantly reduce the breeding cycle and improve the accuracy of selecting for complex traits, such as yield, disease resistance, and stress tolerance, that are difficult to assess through traditional phenotypic selection alone. By utilizing genome-wide molecular markers, GS enables breeders to make informed, data-driven selection decisions even before plants reach maturity, eliminating the need for extended growth periods to observe full phenotypic traits. This early selection capability not only speeds up the breeding process but also reduces the costs and labor associated with extensive field trials, allowing breeders to focus on plants with the highest genetic potential from the start. This passage discusses the application of Genomic Selection (GS) in yam breeding, particularly in predicting key agronomic traits such as yield and disease resistance. Studies have shown that, by using dense genome-wide markers, GS models can more reliably predict breeding values, overcoming limitations of traditional methods,
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