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Evaluation of Promising Maize Hybrids at Different Agro-ecological Regions of Bangladesh (set Iii)

F. BEGUM
Plant Breeding Division, BARI

F. AKTAR
Plant Breeding Division, BARI

A. A. MONDAL
Plant Breeding Division, BARI

N. JAHAN
Plant Breeding Division, BARI

S. UDDIN
Plant Breeding Division, BARI

Abstract/ Executive Summary:

The present study assessed genotype-environment interaction (GEI) and stability for grain yield of 11 hybrids including three checks across four different locations during 2014-15. The AMMI model (additive main effects and multiplication interaction) and GGE model (genotypes × environment) were used to assess the additive and multiplication effects of the interaction. Significant variation for genotypes (G), environment (E) and GEI were found for all the characters. The environment Gazipur is poor and Jamalpur, Burirhat and Rhamatpur are rich environments for hybrid maize production. Considering the mean, bi and S²di three parameters, it was evident that all the genotypes showed different response of adaptability under different environmental conditions. Among the hybrids P3× P7 and P₄× P₆ exhibited bi and S²di for all the characters, indicated that the hybrids are stable across the environment. The hybrid P₃× P₇ is good yielded and stable over environments. Considering the yield and potentiality and stability parameter two hybrids were found promising across locations

Keywords: Stability, Imported hybrids, Maize, Agro-ecology

Location: Gazipur, Jamalpur, Burirhut and Rhamatpur

Start Date: 00-00-2014

End Date: 00-00-2015

Program Area: Variety and Species

Commodity: Maize

Objectives:

This study has been undertaken to evaluate the yield potentiality as well as the stability of the imported hybrids of Maize.

Methodology:

The experiment was conducted at four locations viz. Gazipur, Jamalpur, Burirhut and Rhamatpur during rabi 2014-15. Eight developed hybrids and three checks, viz.NK-40, BARI Hybrid Maize 5 (BHM 5) and BARI Hybrid Maize 9 (BHM 9) was evaluated in this trial. Seeds were sown on November to December, 2014 at 4 locations following Randomized Complete Block Design with 3 replications. The unit plot size was 5.0 X 1.5 m. Spacing adopted was 60 X 20 cm between rows and hill, respectively. One healthy seedling per hill was kept after proper thinning. Fertilizers were applied @ 250, 120, 120, 40 and 5 kg/ha of N, P₂0₅, K₂0, S and Zn, respectively. Standard agronomic practices were followed (Quayyum, 1993) and plant protection measures were taken as when required. Two border rows were used for minimize the border effect. All the plants in two rows were considered for plot yield. The grain yield (ton ha^-1) data was assessed and corrected to 12% moisture. The analysis of variance (ANOVA) was used and the GE interaction was estimated by the AMMI model (Zobel et at.,1988) Thus, the mean response of the genotype i in environment j (Yij) is modeled by: Yij = μ + gi +aj +∑λkγikαjk +ρij + eij; In this procedure, the contribution of each genotype and each environment to the GE interaction is assessed by use of the biplot graph display in which yield means are plotted against the scores of the first principal component of the interaction (IPCA1). The computational program for AMMI analysis is supplied by Duarte and Vencovsky (1999).The stability parameters, regression coefficient (bi) and deviation from regression (S²di) were estimated according to Eberhart and Russel (1966). Significance of differences among bi value and unity was tested by t-test, between S²di and zero by F-test.

Source of Information: Annual Research Report, Plant Breeding Division, BARI--2014-15

Article Link (Online Journal):

Funding Source:

Budget:

Total Budget (Tk.) :

Achievement/Findings:

The mean sum of squares for the genotypes was highly significant for yield which revealed the presence of genetic variability in the material under investigation for all the characters studied. The highly significant effects of environment indicate high differential genotypic response across the different environments. The variation in soil structure and moisture across the different environments were considered as a major underlying causal factor for the GXE interaction. Environment relative magnitude was much higher than the genotypic effect, suggesting that performance of each genotype is influenced more by environmental factors. In the AMMI model, GEI is explained by two axes that are highly significant. The first axis (PCA 1) explains the largest part, the second one explains a little less. Environment 4 and 1 showed negative correlation and environment 3 and 2 showed positive correlation. The correlation between the similar environments is larger than the correlation between the dissimilar environments. The environmental mean and genotypic mean ranged from 7.43 t/ha to 12.86 t/ha and 9.01 t/ha to 11.75 t/ha. Five genotypes showed positive phenotypic index while the other genotypes had negative phenotypic index for yield. Thus, positive phenotypic index represents the higher yield and negative represents the lower yield among the genotypes. Again, positive and negative environmental index (Ij) reflects the rich or favorable and poor or unfavorable environments for this character, respectively. Thus the environment of Gazipur was poor where as Jamalpur, Burirhat, and Rahmatpur were suitable for hybrid maize cultivation. Among the hybrids, P₃× P₇ showed the highest yield and it is a stable variety over all environments. P₄×P₆ and all checks exhibited high yielding as well as stable over all environments.

Considering the yield potentiality and stability parameter, P₃× P₇ and P₄× P₆ exhibited high yielding as well as stable over all environments.

Knowledge Management: Report/Proceedings