The experimental materials consisted of nine sweet corn inbred lines and three testers, which were obtained from Department of Plant Molecular Biology and Bioinformatics, Tamil Nadu Agricultural University, Coimbatore. The sweet corn parental inbreds used in this study contains sh2 gene (shrunken) for sweetness. The nine inbred lines viz., DBT-25-4-7-34-4-22 (L1), DBT-23-7-3-2-5-8 (L2), DBT-26-1-2-1-42-7 (L3), DBT-17-1-1-37-1-1 (L4), DBT-18-1-18-5-6-3 (L5), DBT-15-1-15-3-32-35 (L6), DBT-15-1-15-3-23-21 (L7), DBT-18-1-18-5-2-5 (L8) and DBT-18-1-18-5-1-5 (L9) were crossed with three testers viz., DBT-15-1-15-3-12-11 (T1), DBT-16-1-11-22-7-9 (T2), and DBT-18-1-18-5-4-7 (T3) in Line × Tester (L × T) mating design. The resulting 27 crosses were grown during the Kharif 2023 along with nine lines and three testers in randomized block design with two replicates each. Five plants per genotype were randomly selected from each replication within the parental lines and the F1 hybrids. Eighteen biometrical traits related to yield and quality traits viz., plant height (cm), cob placement height (cm), days to 50% tasseling, days to 50% silking, anthesis silking interval, tassel length (cm), number of tassel branches, leaf length (cm), leaf breadth (cm), cob length (cm), cob width (cm), number of kernel rows per cob (No‘s), number of kernels per row (No‘s), green cob weight without husk (g), total soluble solids (%), total sugars (%) by anthrone method (Yemm and Willis, 1954), reducing sugars (%)by Nelson and Somogyi method (Somogyi, 1952), and non – reducing sugars (%) were recorded. The mean values were calculated for each trait and used for the combining ability analysis.
The significant differences were examined by analyzing the distinct components of variation for eighteen traits among the genotypes (Table 1). The results showed that variations due to genotypes were significant for all the studied traits, which implies the presence of substantial variation for crop improvement. Similar results had been previously reported by Chinthiya et al. (2019); and Sumalini (2023) for the traits of significant variance due to genotypes. Analysis of variance for combining ability revealed significant differences among the lines and testers for all the characters except leaf breadth (Table 2). SCA variance was found to be greater than GCA variance for all the traits, indicating the presence of non-additive gene action among the genotypes under study (Table 3). Similar results were already reported by Kuselan et al. (2017). Due to the predominance of non-additive gene action in the inheritance of the studied characteristics, heterosis breeding and recombination breeding with extending the duration of selection to later generations would be excellent for producing genotypes that are superior for these traits Kumara et al. (2013), Chinthiya et al. (2019), and Darshan et al., (2019).
To select genotypes with desirable traits and determine relationships among the breeding materials, breeders can improve by understanding gca effects (Sprague and Tatum 1942). The gca effects of parents is presented in Table 4. Among the lines, L1, L2, L3 and L5 recorded significant positive gca effect for green cob weight without husk. In addition, L1 was found to be the significant good combiners for plant height, cob placement height, tassel length, leaf length, total soluble solids, total sugars, reducing sugars and non-reducing sugars. Similarly, L2 showed positively significant gca effect for tassel length, leaf length, cob length, cob width, number of kernel rows per cob and number of kernels per row. L3 found to have negative significant gca effect for days to 50% tasseling, days to 50% silking, tassel length, number of tassel branches, leaf length, cob length, cob width, number of kernel rows per cob, number of kernels per row, total sugars, reducing sugars and non-reducing sugars. The line L5 exhibited significant positive gca effect for plant height, cob width, number of kernel rows per cob, number of kernels per row, total soluble solids, total sugars, reducing sugars and non-reducing sugars along with negative significant gca effect for days to 50% tasseling, days to 50% silking and anthesis silking interval. Among the testers, T1 and T3 found to be significantly good combiners for green cob weight. The tester T1 possessed positive significant gca effect for plant height, cob placement height, tassel length, leaf length, cob length, number of kernel rows per cob and number of kernels per row, total soluble solids, total sugars, reducing sugars and non-reducing sugars. Similarly, T3 recorded significant negative gca effect for days to 50% silking and anthesis silking interval, plant height, number of tassel branches, cob width, number of kernel rows per cob, number of kernels per row, total sugars, reducing sugars and non-reducing sugars. Similarly, Mogesse et al. (2020) noted significant negative GCA values for days to 50% tasseling and days to 50% silking and Abd-Allah Ramadan et al. (2020) reported parents showed negative significant gca effect for ASI and days to 50% flowering while cob length, plant height exhibited positive gca effects. Assefa et al. (2017) observed positive significant gca effect for cob length; Gami et al. (2018) for cob width and cob length.
The sca effect of hybrids is presented in Table 5. The hybrids with good specific combining ability were L1 × T1, L1 × T3, L2 × T1, L3 × T1, L5 × T1, L7 × T3 and L8 × T3 for green cob weight without husk. The L1 × T1 hybrid displayed significant sca effect for plant height, cob placement height, TSS, total sugars, reducing sugars and non-reducing sugars along with green cob weight without husk. The next best hybrid L1 × T3 possessed good sca effect for cob width, number of kernel rows per cob, number of kernels per row, total sugars, reducing and non-reducing sugars along with significantly less anthesis silking interval. The cross L2 × T1 exhibited positive significant SCA for number of kernel rows per cob, number of kernels per row, TSS, total sugars and non-reducing sugars. Followed by the cross L3 × T1 showed significant sca effect for tassel length, number of kernels per row, TSS and reducing sugars while L8 × T3 for TSS and reducing sugars. The other best hybrid L5 × T1 had recorded good SCA for the traits like plant height, cob length, cob width, number of kernel rows per cob, TSS, total sugars, reducing sugars and non-reducing sugars. The higher SCA showed that the crosses have higher dominance effects. Chinthiya et al. (2019) reported predominance of non-additive gene action for all the traits and reported positive significant sca effect for green cob weight and other quality traits. Similarly Arsode et al. (2017) noted significant negative SCA values for days to 50% tasseling and days to 50% silking. Kuselan et al. (2017) observed for rows per cob, number of grains per cob and cob girth. Similarly, Mousa et al. (2021) were also reported that the best combiners were selected based on the estimates of sca effects. The hybrids with strong sca effects were produced by an array of high × low, low × high and high × high parental gca combinations. These positive sca effects could be the result of non-additive gene activation combined with promising genes from relating parents.
