Association studies and yield stability analysis of fonio (Digitaria iburua Kippis Stapf) genotypes in Nigeria

Document Type : Research paper

Authors

National Cereals Research Institute, Badeggi, PMB 008 Bida, Niger State, Nigeria.

Abstract

Correlation and Path analysis were applied to study the association between yield and various traits in fonio. The Additive Main Effects and Multiplicative Interaction (AMMI) model, alongside Genotype Plus Genotype-by-Environment Interaction (GGE) biplot analysis were used to assess the stability and adaptability of fonio populations across nine locations in Nigeria during the 2022 and 2023 growing seasons. The study evaluated twelve genotypes and one local check, arranged in a randomized complete block design with three replications. Planting was standardized with a spacing of 20 cm×20 cm on plots measuring 3 m×4 m. Significant variability was observed within the population, highlighting substantial potential for genetic improvement. Key traits, including plant height, spike length, panicle length, and the number of spikes per plant, exhibited strong positive phenotypic correlations (0.989, 0.973, 0.977, 0.991, respectively) and genotypic correlations (0.991, 0.974, 0.98, 0.993, respectively) with grain yield, suggesting these traits are primarily governed by genetic factors. Among the evaluated genotypes, IBPL05-19-03 consistently achieved high grain yields across the locations, demonstrating broad environmental adaptability and suitability for diverse conditions. Also, genotype IBPL04-06-04 displayed limited adaptability, making it more suitable for specific micro-environments. Furthermore, genotypes IBPL02-12-01, IBPL04-15-08, IBPL05-19-03, IBPL02-04-02, and IBPL05-07-09 showed stability and general adaptability across varying environments, as evidenced by slope values near 1. The trait-relationship analysis indicated that breeding programs targeting improvements in plant height, panicle length, and tillering capacity could lead to significant yield advancements in fonio. The integration of AMMI and GGE models provided a robust statistical framework in analyzing fonio lines, enabling informed selection and development of genotypes that are both high-yielding and environmentally stable across diverse agro-ecological zones.

Keywords

References

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  • Receive Date: 16 March 2025
  • Revise Date: 08 August 2025
  • Accept Date: 21 September 2025

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