Estimation of variability, heritability, genetic advance and assessment of frequency distribution for morphological traits in intercross population of maize

Genetic variability analysis is an essential criterion in the selection of crops for improvement programmes and components like Phenotypic Coefficient of Variation, Genotypic Coefficient of Variation, heritability and Genetic Advance as percent of Mean are useful for the exploitation of variability. Skewness and kurtosis indicate the type of gene action and the number of genes governing the trait and selection can be done based on these values. In the present study, variability, heritability, genetic advance, skewness and kurtosis were assessed for the intercross (IC2) population of (UMI1200×CE477) × (UMI1200×VQL1). Fourteen biometrical traits were recorded and the mean values were used for further analysis. Higher PCV values were obtained compared to their respective GCV values for all the traits of the population. Cob length (83.28% and 2.09%) showed the highest heritability and genetic advance suggesting higher genetic gain, which can be improved with simple selection methods and hence, showing additive gene action. Single plant yield showed higher heritability (77.29%) with low genetic advance (0.80%) and hence, requires appropriate selection methods to improve the genetic gain. With the exception of days to tasseling, all the traits showed platykurtic distribution suggesting that the large number of genes are involved in governing the traits. Days to silking, tassel length, the number of tassel branches, leaf length, leaf breadth, cob length, the number of kernels per row, cob weight, 100 kernel weight and single plant yield showed positive skewness suggesting dominant based complementary epistasis and hence, rapid genetic gain can be obtained by intense selection. Days to tasseling, plant height, ear height and the number of kernel rows per cob negative skewness showing duplicate gene action and hence, the rapid genetic gain can be obtained by mild selection.

[1]  F. Hossain,et al.  Incorporation of opaque-2 into ‘UMI 1200’, an elite maize inbred line, through marker-assisted backcross breeding , 2019, Biotechnology & Biotechnological Equipment.

[2]  N. Senthil,et al.  Studies on Frequency Distribution of Sorghum Downy Mildew Resistant BC2F1 Progenies in Maize , 2018, International Journal of Current Microbiology and Applied Sciences.

[3]  N. Pandey,et al.  Marker-assisted introgression of opaque2 allele for rapid conversion of elite hybrids into quality protein maize , 2018, Journal of Genetics.

[4]  S. Hittalmani,et al.  Genetic parameters of two bc2f1 populations for development of superior male sterile lines pertaining to morpho-floral traits for aerobic rice (Oryza sativa L.) , 2016 .

[5]  N. Kishore,et al.  Genetic variability, correlation and path analysis for yield and yield components in promising rice (Oryza sativa L.) genotypes , 2015 .

[6]  M. Choudhary,et al.  Development of β-Carotene Rich Maize Hybrids through Marker-Assisted Introgression of β-carotene hydroxylase Allele , 2014, PloS one.

[7]  M. Lal,et al.  Studies of variability using morphological and quality traits in Quality Protein Maize (Zea mays L.) , 2014 .

[8]  M. Garcia-Casal,et al.  Processing maize flour and corn meal food products , 2013, Annals of the New York Academy of Sciences.

[9]  A. Seetharam,et al.  Variability studies of quantitative characters in maize (Zea mays L.). , 2012 .

[10]  J. Jinks,et al.  The causes and consequences of non-normality in predicting the properties of recombinant inbred lines , 1977, Heredity.

[11]  D. Robson Applications of the k 4 Statistic to Genetic Variance Component Analyses , 1956 .

[12]  H. F. Robinson,et al.  Estimates of Genetic and Environmental Variability in Soybeans1 , 1955 .

[13]  H. F. Robinson,et al.  Estimates of Heritability and the Degree of Dominance in Corn1 , 1949 .

[14]  J. Lush Intra-sire correlations or regressions of offspring on dam as a method of estimating heritability of characteristics. , 1940 .

[15]  R A Fisher,et al.  The Genetical Interpretation of Statistics of the Third Degree in the Study of Quantitative Inheritance. , 1932, Genetics.

[16]  F. H. Harper Elements of practical statistics , 1931 .

[17]  R. Ravikesavan,et al.  Genetic variability and correlation studies of yield and phytic acid in F 2 populations of maize ( Zea mays L . ) , 2018 .

[18]  A. Sarawgi,et al.  GENETIC VARIABILITY ANALYSIS FOR VARIOUS YIELD ATTRIBUTING AND QUALITY TRAITS IN RICE (O. SATIVA L.) , 2013 .

[19]  J. Mahamood Heritability and Genetic Advance for Grain Yield and its Component Characters in Maize (Zea Mays L.) , 2012 .

[20]  J. Weller Marker-assisted introgression. , 2009 .

[21]  D. Samadia Genetic Variability Studies in Lasora (Cordia myxa Roxb.) , 2005 .