Multi-trait selection index for simultaneous selection of water yam (Dioscorea alata L.) genotypes

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2024-01-03

Language

en

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Peer Review

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Open Access Open Access

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CC-BY-4.0

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Ouattara, F., Agre, P., Adejumobi, I.I., Akoroda, M.O., Sorho, F., Ayolié, K. & Bhattacharjee, R. (2024). Multi-trait selection index for simultaneous selection of water yam (Dioscorea alata L.) genotypes. Agronomy, 14(1): 128, 1-21.

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Abstract/Description

Water yam (Dioscorea alata L.) is the most widely cultivated yam species with good agronomic attributes. However, several biotic and abiotic constraints and its lower food quality such as poor pound ability limit its production and use. Therefore, the identification of superior genotypes with suitable characteristics is needed for water yam improvement. This study aims to assess a panel of half-sib (progenies with one parent in common) and full-sib (progenies with the same male and female parents) progenies as well as their parents for selection of desirable ideotypes based on their agronomic and quality characteristics. A total of 280 progenies from bi-parental populations as well as five parents were evaluated, and a significant variation was observed (p < 0.01) in their performances for the eight traits used in the study. A moderate to high broad-sense heritability (30% < H2–H2 ≥ 60%) was observed for all traits except for tuber pound ability (H2 < 30%). Positive correlations were displayed between the traits, while the hierarchical clustering grouped genotypes into three clusters indicating the potential for selection of diverse genotypes for multiple traits from the four families under study. Plant vigor and number of tubers per plant contributed (p < 0.01) positively to the yield per plant in the path coefficient analysis. Using the multi-trait genotype–ideotype distance index (MGIDI), a total of 39 most promising genotypes were identified. These promising genotypes could be further used as progenitors in D. alata improvement programs targeting good agronomic and quality traits targeted for farmers and end users.

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