Analysis of yam yields using the additive main effects and multiplicative interaction (AMMI) model
The AMMI model combines regular analysis of variance for additive main effects with principal component analysis for multiplicative structure within the interaction. It also improves the accuracy of crop yield estimates and selects genotypes with highest yields. Despite knowledge of the model, poten...
| Main Authors: | , |
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| Format: | Journal Article |
| Language: | Inglés Francés |
| Published: |
2002
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| Online Access: | https://hdl.handle.net/10568/92753 |
| _version_ | 1855515289122242560 |
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| author | Egesi, Chiedozie N. Asiedu, Robert |
| author_browse | Asiedu, Robert Egesi, Chiedozie N. |
| author_facet | Egesi, Chiedozie N. Asiedu, Robert |
| author_sort | Egesi, Chiedozie N. |
| collection | Repository of Agricultural Research Outputs (CGSpace) |
| description | The AMMI model combines regular analysis of variance for additive main effects with principal component analysis for multiplicative structure within the interaction. It also improves the accuracy of crop yield estimates and selects genotypes with highest yields. Despite knowledge of the model, potential yield estimates for yam cultivars as is the case for several other crops, are largely unknown. In this study, the AMMI model was used with the objective of assessing yam genotypes yield, selecting stable genotypes, and investigating G x E effects from trials conducted for two years at five locations in Nigeria. The effects of environments, genotypes and genotype-by-environment interaction (G x E) were highly significant (P<0.001). Within environments, AMMI1 estimates ranked genotypes differently from the unadjusted means, and in six out of nine cases AMMI1 estimates changed the top-yielding entry. The AMMI1 estimation also produced sharper and stratified rankings compared with the unadjusted means. The biplot showed four groupings of genotypes: TDa 93-36 generally low yielding and unstable; TDa 291 and TDa 297, low yielding and moderately stable; TDa 294 and TDa 87/01091 high yielding and stable; TDa 92-2 high yielding but unstable. Yam yields were relatively stable at Ibadan and Jos, while yields obtained at Abuja were unstable across both years. Superior yam selections with specific or broad adaptation were identified by AMMI. |
| format | Journal Article |
| id | CGSpace92753 |
| institution | CGIAR Consortium |
| language | Inglés Francés |
| publishDate | 2002 |
| publishDateRange | 2002 |
| publishDateSort | 2002 |
| record_format | dspace |
| spelling | CGSpace927532023-06-12T09:08:17Z Analysis of yam yields using the additive main effects and multiplicative interaction (AMMI) model Egesi, Chiedozie N. Asiedu, Robert dioscorea alata g x e multilocational trials yield stability gxe essais multilocaux stabilité du rendement The AMMI model combines regular analysis of variance for additive main effects with principal component analysis for multiplicative structure within the interaction. It also improves the accuracy of crop yield estimates and selects genotypes with highest yields. Despite knowledge of the model, potential yield estimates for yam cultivars as is the case for several other crops, are largely unknown. In this study, the AMMI model was used with the objective of assessing yam genotypes yield, selecting stable genotypes, and investigating G x E effects from trials conducted for two years at five locations in Nigeria. The effects of environments, genotypes and genotype-by-environment interaction (G x E) were highly significant (P<0.001). Within environments, AMMI1 estimates ranked genotypes differently from the unadjusted means, and in six out of nine cases AMMI1 estimates changed the top-yielding entry. The AMMI1 estimation also produced sharper and stratified rankings compared with the unadjusted means. The biplot showed four groupings of genotypes: TDa 93-36 generally low yielding and unstable; TDa 291 and TDa 297, low yielding and moderately stable; TDa 294 and TDa 87/01091 high yielding and stable; TDa 92-2 high yielding but unstable. Yam yields were relatively stable at Ibadan and Jos, while yields obtained at Abuja were unstable across both years. Superior yam selections with specific or broad adaptation were identified by AMMI. Le modèle AMMI combine l’analyse régulière de la variance pour les principaux effets additifs avec une analyse des composantes principales avec une structure d’intéraction multiplicative. Il améliore aussi l’estimation des rendements et la sélection des génotypes à haut rendement. En dépit de la connaissance du modèle, les estimations de rendements potentiels des variétés d’igname, comme c’est le cas de plusieures autres plantes, sont largement inconnues. Dans cette étude, le modèle AMMI était utilisé avec l’objectif d’estimer le rendement des génotypes d’igname, et d’examiner les effets de l’intéraction GXE dans les essais conduits pour deux ans dans cinq endroits différents. Les effets de l’environnement, génotypes et l’intéraction génotype et l’environnement était très significatifs (p<0.001). Dans les cinq endroits étudiés, les estimations AMMI ont classé les génotypes différement à partir des moyennes non ajustées, et dans six de neuf cas étudiés AMMI1 a modifié le classement des génotypes à haut rendement. L’estimation AMMI1 a aussi produit un classement stratifié pointu en comparaison avec les moyennes non ajustées. Quatre groupements des génotypes ont été obtenus par représentation graphique. La variété TDa 93-36 est généralement à rendement faible et instable, TDa291 et TDa297, à rendement faible et modérement stables ; TDa294 et TDa87/01091 à rendement élévé et stable ; et TDa92-2 à rendement élévé mais instable. Les rendements d’igname étaient relativement stables à Ibadan et Jos, alors que ceux obtenus à Abuja étaient instables pour les deux ans. Les sélections supérieures avec une adaptation spécifique et large étaient identifiées par l’AMMI1. 2002 2018-05-17T09:03:24Z 2018-05-17T09:03:24Z Journal Article https://hdl.handle.net/10568/92753 en fr Limited Access Egesi, C.N. & Asiedu, R. (2002). Analysis of yam yields using the additive main effects and multiplicative interaction (AMMI) model. African Crop Science Journal, 10(3), 195-201. |
| spellingShingle | dioscorea alata g x e multilocational trials yield stability gxe essais multilocaux stabilité du rendement Egesi, Chiedozie N. Asiedu, Robert Analysis of yam yields using the additive main effects and multiplicative interaction (AMMI) model |
| title | Analysis of yam yields using the additive main effects and multiplicative interaction (AMMI) model |
| title_full | Analysis of yam yields using the additive main effects and multiplicative interaction (AMMI) model |
| title_fullStr | Analysis of yam yields using the additive main effects and multiplicative interaction (AMMI) model |
| title_full_unstemmed | Analysis of yam yields using the additive main effects and multiplicative interaction (AMMI) model |
| title_short | Analysis of yam yields using the additive main effects and multiplicative interaction (AMMI) model |
| title_sort | analysis of yam yields using the additive main effects and multiplicative interaction ammi model |
| topic | dioscorea alata g x e multilocational trials yield stability gxe essais multilocaux stabilité du rendement |
| url | https://hdl.handle.net/10568/92753 |
| work_keys_str_mv | AT egesichiedozien analysisofyamyieldsusingtheadditivemaineffectsandmultiplicativeinteractionammimodel AT asiedurobert analysisofyamyieldsusingtheadditivemaineffectsandmultiplicativeinteractionammimodel |