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"Oluwafemi O. Lawal"

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"Oluwafemi O. Lawal"

Research Article
Phenotypic Stability Analysis of Yield Components in Cashew (Anacardium occidentale L.) Using Additive Main Effect and Multiplicative Interaction (AMMI) and GGE Biplot Analyses
Olawale M. Aliyu, Oluwatosin O. Adeigbe, Oluwafemi O. Lawal
Plant Breed. Biotech. 2014;2(4):354-369.   Published online December 31, 2014
DOI: https://doi.org/10.9787/PBB.2014.2.4.354

Perennial poor fruit-set and variability in tree yield are among major problems of cashew nut production. Thus, development of improved stable genotypes would be a sustainable strategy to address this perpetual problem in order to boost income and livelihood of many smallholder farmers of this important commodity crop. Here, we have applied additive main effect and multiplicative interaction (AMMI) and genotype, genotype by environment (GGE) biplot analysis to a 3-year multi-locational trial data on nine yield component characters of cashew to evaluate phenotypic stability across diverse environments. Variance analysis showed significant variability in the cashew genotypes and strong influence of genotype by environment (GxE) on tree yield as none of the genotypes was stable for any of the yield components across locations. GxE data showed that a substantial portion of the variation was explained by the genotype (highly heritable), accounting for between 10% and 87% of the variation, while the environment accounted for between 0.7% and 37%. Data showed significant higher values of interaction (GxE) than the respective values for environment, and were mostly captured and could be explained by the first principal component axis (IPCA 1) for all the yield component characters. There was an inverse relationship between stability and yield as the best three yielding genotypes (KT_26, IW_222 and IW_31) were found to be the most unstable. Among the yield component tested, hermaphrodite flowers per panicle, nuts per panicle, nuts per tree, nut weight, and tree fruiting efficiency were identified to be critical components for nut yield. Although there was wide variation between the three environments evaluated, the data effectively identified two mega-environments (ME), and two superior genotypes (IW_222 and KT_26) suitable for these two mega-environments. The GxE complex exposes the short-comings of broad recommendations of common agronomic-husbandry technologies across diverse cashew ecologies as each mega-environment would require specific adaptable technologies for optimal plant output. Above all, the data presented here underscore the importance of multi-locational evaluation of genotypes for varietal development in cashew.

Citations

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