Estimation of genotype x environment interaction for yield in Ethiopia maize (Zea mays L.)

[摘要] English: The study was undertaken to assess the performance of 10 maize genotypes across 15maize growing environments of Ethiopia. The study was conducted from 1999 to 2001.The grain yields of these genotypes were analyzed using different statistical procedures todetermine their G X E interactions and grain yield stability. The main objective of thisstudy was to investigate the G X E interactions and stability performance of genotypes invarious environments by applying different statistical methods of analysis in order tomake useful recommendations for future utilization.Separate and combined analyses of variance across locations and years and five types ofstability parameters were performed, using the AGROBASE 2000 program. In order toperform the stability analyses, data of 10 maize genotypes tested across five locationsand three years were analyzed using the procedures of Finlay and Wilkenson (1963),Eberhart and Russel, (1966) for the joint regression, Wricke (1962) for ecovalence,Shukla (1972) for stability variance and (Gauch and Zobel, 1988) for the AMMI stabilitymodel.Separate trial analyses for the three years showed highly significant (P<0.01) differencesamong genotypes and locations for grain yield. In the year 1999, BH-670 was the bestperformer, followed by (A-7016 x G-7462) x 142-1-e and (A-7032 x G-7462) x 142-1-ewith average yields of 9.59, 9.51 and 9.14 t ha respectively. This ranking changedduring 2000 and 2001, due to the presence of interactions. Across locations and years,(A-7032 x F-7215) x 144-7-b ranked first, followed by (A-7032 x G-7462) x 142-1-e andBH-670. All are three-way hybrids with mean yields of 8.93, 8.79 and 8.74 t harespectively. Among the locations the highest yield of 8.80 t ha was obtained fromAwassa, followed by Bako and Jimma over the three years, indicating the high potentialof these sites for maize production. The results also showed yield variations overlocations and years, confirming the presence of G X E interactions. The average of ANOV A components over the three years indicated that about 42% of the total variancewas accounted for by genotypes and 13% by blocks. This confirmed variability betweengenotypes in their response to environmental factors.Combined analyses of variance across locations found highly significant (P<0.01)differences among locations (L) and genotypes (G) for grain yield. There was a.differential response of genotypes over locations, mainly due to edaphic and climaticfactors. About 34% of the variance components were attributed to locations, while 16%of the variance components were attributed to genotypes and 12% to their interactionsover the three years. This confirms the effect of environmental factors and thus thenecessity of stability analyses for the appropriate genotypes.The combined analyses across locations, years and their interaction indicated highlysignificant differences (P<0.01) among the genotypes for grain yield, which suggestsdifferential responses of genotypes to their environments. Significant G X Einteraction makes the genotype selection processes difficult, which create problems incultivar characterization. Stability analyses with appropriate statistical methods aretherefore required to overcome this problem. Most of these interactions were highlysignificant due to abiotic and biotic factors, which need in-depth studies for betterunderstanding. Generally, when G X E interaction is mainly caused by unpredictableenvironmental factors, breeing efforts should be aimed at the development of stablevarieties with a relatively good performance under a range of environments. When theinteraction is however due to predictable environmental factors the aim should be todevelop either different varieties for different environments or broadly adapted varietiesfor a range of environments.The joint regression model for grain yield indicated highly significant differencesbetween the genotypes. The joint regression model identified (A-7032 X G-7462) X 142-l-e as the most stable genotype, followed by (A-7032 X F-7215) X 144-7-b and (A-7033X F-7189) X 142-1-e. These last two genotypes were the best yielders across allenvironments and both are three-way hybrids.Wricke's (1962) ecovalence considered BH-660 (one of the popular hybrids) as the moststable genotype, followed by (A-7033 X F-7189) X 142-1-e and Gibe-l (an openpollinatedvariety). BH-660 is the most popular hybrid currently under production in thecountry and Gibe-l is a newly released open-pollinated variety (OPV). (A-7032 X G-7462) X 142-1-e and (A-7032 X F-7215) X 144-7-b were categorized as intermediate instability, unlike Kulani and BH-140, which were found to be unstable according to thisstability measurement.According to Shukla's stability variance (1972), BH-660 followed by (A-7033 X F-7189)X 142-I-e and Gibe-l were the most stable genotypes, whereas Kulani and BH-140 wereconsidered as the least stable genotypes. BH-660, the popular three-way hybrid was themost stable genotype as measured by both ecovalence and the stability variance. Jointregression was also in agreement with these results with only slight differences.Additive main effects and multiplicative interactions (AMMI) stability values, and scoresof the interaction principal component analysis (lPCA) showed that BH-660 was the moststable genotype followed by (A-7032 X F-7215) X 144-7-b and (A-7033 X F-7189) X142-1-e, whereas Kulani and BH-140 were considered to be unstable. AMMI gave thesame results as the ecovalence and Shukla in identifying the stable genotypes.

[发布机构] University of the Free State