J. Biosci. Agric. Res. | Volume 25, Issue 01, 2047-2059 | https://doi.org/10.18801/jbar.250120.251
Article type: Research article | Received:14.06.2020; Revised: 16.07.2020; First published online: 01 August 2020.
Article type: Research article | Received:14.06.2020; Revised: 16.07.2020; First published online: 01 August 2020.
Morphological characterization and genetic diversity analyses of plant traits contributed to grain yield in maize (Zea mays L.)
Shafikul Islam 1, Aleya Ferdausi 1, Afsana Yeasmin Sweety 1, Amit Das 2, Ashrafi Ferdoush 1 and Md. Ashraful Haque 1
1 Department of Genetics and Plant Breeding, Bangladesh Agricultural University, Mymensingh
2 Department of Agronomy, Bangladesh Agricultural University, Mymensingh, Bangladesh.
✉ Corresponding author: [email protected] (Haque M. A.).
1 Department of Genetics and Plant Breeding, Bangladesh Agricultural University, Mymensingh
2 Department of Agronomy, Bangladesh Agricultural University, Mymensingh, Bangladesh.
✉ Corresponding author: [email protected] (Haque M. A.).
Abstract
Genetic variability and divergence among landraces and cultivars are invaluable resources that lead the breeder to understand the performance of an attribute or genotype, which possess paramount importance in selecting suitable genotypes or traits for hybridization programme. Thirteen maize genotypes were used to estimate the genetic parameters, variability, correlation and path coefficient, principal component analysis (PCA) and cluster analysis. The analysis of variance showed the presence of highly significant morphological variation among the thirteen genotypes. The phenotypic coefficient of variation (PCV) was greater than the genotypic coefficient of variation (GCV) for all the traits studied indicating their interaction with the environment to some extent. Most of the plant traits under study showed high heritability estimates, >60%. The high heritability (91.35%, 86.73%, 61.79% and 96.41%) coupled with high genetic advance (34.45, 107.98, 90.93 and 55.92) and genetic advance in percentage of mean (87.64%, 305.77%, 34.08% and 59.01%) were observed in plant height, kernel numbers row-1, thousand kernel weight and yield per plant; respectively, that designates the role of additive gene expression for these traits which would facilitate better scope for improvement of these traits through direct selection. The correlation analysis exhibited significant positive associations between yield per plant and plant height (0.603), ear girth (0.518), kernel numbers row-1 (0.509), thousand kernel weight (0.806) and kernel width (0.715). Besides it showed a significant positive correlation of thousand kernel weight with plant height (0.583), ear girth (0.590) and kernel width (0.794). Furthermore, the positive direct effects of ear girth (0.749), kernel number row-1(0.771), thousand kernel weight (0.356) and kernel width (0.291) on yield per plant were observed through path analysis. While plant height, ear length, kernel rows ear-1 and kernel length showed negative direct effect on yield per plant. The PCA showed that the first four principal components (PCs) accounted for more than 80% of total variation where PC1 explained 38.9% of total variability which was dominated by thousands kernel weight (0.448), yield per plant (0.444), kernel width (0.381), plant height (0.38), ear girth (0.378) and kernel rows ear-1 (0.318). Cluster analysis exhibited three distinct clusters with five genotypes in cluster I and cluster II, and three genotypes in cluster III. The cluster I having the genotypes BHM-15, BHM-13, BHM-12, BHM-9 and BHM-7 was loaded with the highest mean values of thousand kernel weight (339.67), yield per plant (121.33) and kernel width (9.20). Moreover, these genotypes showed close proximate with kernel width, thousand kernel weight, ear girth, plant height and yield per plant in PCA biplot. Therefore, the analysis of variance, principal component and cluster analyses revealed the presence of wider diversity in the studied maize genotypes. The findings of this study would be useful to select the potential traits and genotypes for further breeding programs to increase the grain yield in maize.
Key Words: Genetic variability, Diversity, Correlation, Path coefficient, PCA and Clustering
Genetic variability and divergence among landraces and cultivars are invaluable resources that lead the breeder to understand the performance of an attribute or genotype, which possess paramount importance in selecting suitable genotypes or traits for hybridization programme. Thirteen maize genotypes were used to estimate the genetic parameters, variability, correlation and path coefficient, principal component analysis (PCA) and cluster analysis. The analysis of variance showed the presence of highly significant morphological variation among the thirteen genotypes. The phenotypic coefficient of variation (PCV) was greater than the genotypic coefficient of variation (GCV) for all the traits studied indicating their interaction with the environment to some extent. Most of the plant traits under study showed high heritability estimates, >60%. The high heritability (91.35%, 86.73%, 61.79% and 96.41%) coupled with high genetic advance (34.45, 107.98, 90.93 and 55.92) and genetic advance in percentage of mean (87.64%, 305.77%, 34.08% and 59.01%) were observed in plant height, kernel numbers row-1, thousand kernel weight and yield per plant; respectively, that designates the role of additive gene expression for these traits which would facilitate better scope for improvement of these traits through direct selection. The correlation analysis exhibited significant positive associations between yield per plant and plant height (0.603), ear girth (0.518), kernel numbers row-1 (0.509), thousand kernel weight (0.806) and kernel width (0.715). Besides it showed a significant positive correlation of thousand kernel weight with plant height (0.583), ear girth (0.590) and kernel width (0.794). Furthermore, the positive direct effects of ear girth (0.749), kernel number row-1(0.771), thousand kernel weight (0.356) and kernel width (0.291) on yield per plant were observed through path analysis. While plant height, ear length, kernel rows ear-1 and kernel length showed negative direct effect on yield per plant. The PCA showed that the first four principal components (PCs) accounted for more than 80% of total variation where PC1 explained 38.9% of total variability which was dominated by thousands kernel weight (0.448), yield per plant (0.444), kernel width (0.381), plant height (0.38), ear girth (0.378) and kernel rows ear-1 (0.318). Cluster analysis exhibited three distinct clusters with five genotypes in cluster I and cluster II, and three genotypes in cluster III. The cluster I having the genotypes BHM-15, BHM-13, BHM-12, BHM-9 and BHM-7 was loaded with the highest mean values of thousand kernel weight (339.67), yield per plant (121.33) and kernel width (9.20). Moreover, these genotypes showed close proximate with kernel width, thousand kernel weight, ear girth, plant height and yield per plant in PCA biplot. Therefore, the analysis of variance, principal component and cluster analyses revealed the presence of wider diversity in the studied maize genotypes. The findings of this study would be useful to select the potential traits and genotypes for further breeding programs to increase the grain yield in maize.
Key Words: Genetic variability, Diversity, Correlation, Path coefficient, PCA and Clustering
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MLA
Islam, et al. “Morphological characterization and genetic diversity analyses of plant traits contributed to grain yield in maize (Zea mays L.)”. Journal of Bioscience and Agriculture Research, 25(01), (2020):2047-2059.
APA
Islam, S., Ferdausi, A., Sweety, A. Y., Das, A., Ferdoush, A. and Haque, M. A. (2020). Morphological characterization and genetic diversity analyses of plant traits contributed to grain yield in maize (Zea mays L.). Journal of Bioscience and Agriculture Research, 25(01), 2047-2059.
Chicago
Islam, S., Ferdausi, A., Sweety, A. Y., Das, A., Ferdoush, A. and Haque, M. A. “Morphological characterization and genetic diversity analyses of plant traits contributed to grain yield in maize (Zea mays L.)”. Journal of Bioscience and Agriculture Research, 25(01), (2020): 2047-2059.
Harvard
Islam, S., Ferdausi, A., Sweety, A. Y., Das, A., Ferdoush, A. and Haque, M. A. 2020. Morphological characterization and genetic diversity analyses of plant traits contributed to grain yield in maize (Zea mays L.). Journal of Bioscience and Agriculture Research, 25(01), pp. 2047-2059.
Vancouver
Islam, S, Ferdausi, A., Sweety, AY, Das, A., Ferdoush, A and Haque, MA. Morphological characterization and genetic diversity analyses of plant traits contributed to grain yield in maize (Zea mays L.). Journal of Bioscience and Agriculture Research, 2020 July 25(01), 2047-2059.
Islam, et al. “Morphological characterization and genetic diversity analyses of plant traits contributed to grain yield in maize (Zea mays L.)”. Journal of Bioscience and Agriculture Research, 25(01), (2020):2047-2059.
APA
Islam, S., Ferdausi, A., Sweety, A. Y., Das, A., Ferdoush, A. and Haque, M. A. (2020). Morphological characterization and genetic diversity analyses of plant traits contributed to grain yield in maize (Zea mays L.). Journal of Bioscience and Agriculture Research, 25(01), 2047-2059.
Chicago
Islam, S., Ferdausi, A., Sweety, A. Y., Das, A., Ferdoush, A. and Haque, M. A. “Morphological characterization and genetic diversity analyses of plant traits contributed to grain yield in maize (Zea mays L.)”. Journal of Bioscience and Agriculture Research, 25(01), (2020): 2047-2059.
Harvard
Islam, S., Ferdausi, A., Sweety, A. Y., Das, A., Ferdoush, A. and Haque, M. A. 2020. Morphological characterization and genetic diversity analyses of plant traits contributed to grain yield in maize (Zea mays L.). Journal of Bioscience and Agriculture Research, 25(01), pp. 2047-2059.
Vancouver
Islam, S, Ferdausi, A., Sweety, AY, Das, A., Ferdoush, A and Haque, MA. Morphological characterization and genetic diversity analyses of plant traits contributed to grain yield in maize (Zea mays L.). Journal of Bioscience and Agriculture Research, 2020 July 25(01), 2047-2059.
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