Generation Mean Analysis: A Case study of variance components in KSC 500 generations of maize (Zea mays L.)

International Research Journal of Applied and Basic Sciences 2014 Available online at www.irjabs.com ISSN 2251-838X / Vol, 8 (2): 194-200 Science Explorer Publications Generation Mean Analysis: A Case study of variance components in KSC 500 generations of maize (Zea mays L.) Pariya Dorri *1, Saeed Khavari Khorasani 2, Mohsen Shahrokhi 3 1. MSc, Science and Research Branch, Payam nor University, Mashhad,Iran 2. Assistant Professor, Seed and Plant Improvement Division (SPII), Khorasan Razavi Agriculture and Natural Resources Research Center, Mashhad, Iran 3. MSc of Plant Breeding, Science and Research Branch, Islamic Azad University, Tehran, Iran *Corresponding author email: Dorripariya@yahoo.com ABSTRACT: The choice of selection and breeding procedures for genetic improvement of maize or any other crop largely depends on the type and relative amount of genetic components and presence of non-allelic interaction. In this study by using generation mean analysis method (Mather and Jinks 1982), six generations (P1, P2, F1, F2, BC1 and BC2) from cross of corn, R59 (P1) OH43/1-42(P2) was evaluated for several agronomic traits including yield and its components at Torough Agricultural Station of Khorasan-e-Razavi Agriculture and Natural Resources Research Center, Mashhad, Iran, in the 2013 growing season. The experiment was carried out as a randomized complete block design with three replications. The results showed significant differences among generations for all traits. dominance variance was more important than additive variance for most of the traits such as leaves no.,leaf aria, ear length, kernel no.,kernel depth, 1000 grain weight and days to anthesis, which justifies the production of hybrid varieties in maize. Broad sense heritability of traits were 0.23-0.88 for this cross. The estimated number of genes controlling grain yield trait ranged from 2 to 4. Keywords: Additive and dominance effects, Generation mean analysis, Heritability, Heterosis, Maize INTRODUCTION Maize is one of the major cereal crops providing raw material for the food industry and animal feed (Unay et al. 2004). The choice of an efficient breeding program depends to a large extent on knowledge of the type of gene action involved in the expression of the character. Whereas dominance gene action would favor the production of hybrids, additive gene action indicates that standard selection procedures would be effective in bringing about advantageous changes in character (Edwards et al., 1975). Information on genetic variances, levels of dominance, and the importance of genetic effects have contributed to a better understanding of the gene action involved in the expression of heterosis (Wolf and Hallauer, 1997). Maize breeders have successfully exploited heterosis for grain yield by crossing inbred lines to develop desirable hybrids. However, the nature of gene action involved in the expression of heterosis for the grain yield of elite maize hybrids remains unresolved. Melchinger et al. (1986) described how the knowledge about the nature of gene action allows maize breeders to optimize their breeding programs. The choice of selection and breeding procedures for genetic improvement of maize or any other crop depends largely on the knowledge of type of gene action for different characters in the plant materials under investigation. Breeding for improved varieties requires a thorough understanding of the genetic mechanisms governing yield and yield components (Saleem et al. 2002; Unay et al.2004). Sher et al.(2012) elucidate the pattern of inheritance and determine the relative magnitude of various genetic effects for maturity and flowering attributes in subtropical maize also reported dominance gene action and epistatic interaction played major role in governing inheritance of days to pollen shedding. Many researchers reported about the predominance of non-additive genetic effects for days to silking (Alam et al. 2008), plant height (Alam et al. 2008; Akbar et al. 2008), leaf area (Suneetha et al.2000), ear length (Vidal-Martinez et al. 2001; Rezaei and Roohi 2004), ear height (Rezaei and Roohi 2004; Alam et al. 2008), number of rows per ear (Saeed et al. 2000; Vidal- Martinez et al. 2001), number of kernels per row

(Vidal-Martinez et al. 2001; Amer et al. 2002; Srdic et al. 2007) and grain yield (Amer et al.2002; Rezaei and Roohi 2004; 2004; Srdic et al.2007; Singh and Roy 2007). Shahrokhi et al.(2013) observed the considerable role of epistasis in controlling traits, in a study of genetic components in various maize by using six generation of maize (P1, P2, F1, F2, BC1 and BC2). Dhillon and Singh (1976) observed the importance of over-dominance and presence of complementary epistasis in the inheritance of grain yield and days to silking in maize. In a study on the nature and magnitude of gene action, using six generations of maize (P1, P2, F1, F2, BC1 and BC2), Tabassum and Saleem (2005) found that the expression of leaf area per plant, 1000-grain weight and grain yield per plant were mainly governed by over-dominance type of gene action. Kumar et al. (2005) also reported over-dominance gene action for plant height, ear height and grain yield per plant. Furthermore, several authors have reported significant positive heterosis for grain yield (Muraya et al. 2006; Akbar et al. 2008; Fan et al.2009). Alam et al. (2008) reported significantly negative heterosis over the better parent for days to silk. Although many researchers have reported the importance of non-additive gene action for grain yield and some other agronomic traits, but some investigators indicated predominance of additive genetic effects for plant height (Amer et al. 2002; Singh and Roy 2007), ear height (Amer et al. 2002), number of rows per ear (Srdic et al. 2007), number of kernels per row (Saeed et al. 2000), days to maturity (Singh and Roy 2007) and grain yield (Vacaro et al. 2002; Ojo et al. 2007). Kumar et al. (1998) revealed that both additive and non-additive gene action were important for number of kernels per row and grain yield in maize. These discrepancies may be attributed mainly to the type of genetic material and the test environment. The frequent occurrence of a non allelic interaction in quantitative traits reveals their existence in the inheritance of quantitative characters. Much of the information on epistasis stems from studies in crosspollinated crops probably because of the major role of heterosis in these crops and the possible relationship between hybrid vigor and epistasis (Ketata et al., 1976). The importance of non-allelic interaction on the expression of several agronomic traits has been reported in a number of instances. Wolf and Hallauer (1977) reported that an epistatic effect could contribute to the expression of heterosis for specific hybrids. They showed that additive-additive effects were not significant for grain yield whereas additive-dominance and dominance-dominance effects were significant. A few studies have indicated that epistasis was not a significant component of genetic variability in the maize population (Silva and Hallauer, 1975; Ketata et al., 1976; Hinze and Lamkey, 2003). Other studies, however, have shown that epistatic effects are important for the specific combination of inbred lines (Darrah and Hallauer, 1972; Wolf and Hallauer, 1977; Moreno-Gonzalez and Dudley, 1981; Lamkey et al., 1995; Chen et al., 1996; Hinze and Lamkey,2003). Hallauer and Miranda (1988) concluded that epistasis variance is not an important contributor to the genetic variance for yield in maize. Biometric methods that use mean comparison rather than variance component estimation (for example, generation mean analysis and triple test cross) have regularly indicated that Grain yield is the most important trait in maize, while starch content in grain is becoming very attractive because of valueadded food/feed production, as well as biofuel production. Both traits are quantitative and complex in nature. It means their expression is caused, not only by genetic factors, but also by environmental effects and genotype environment interaction. The present study was designed to investigate the inheritance of several agronomic traits including yield and yield components in cross of maize by generation mean analysis. MATERIALS AND METHODS This study, we evaluated six generations (P1, P2, F1, F2, BC1 and BC2) of hybrid, KSC500 (R59 OH43/1-42),in a randomized complete block design with three replications at Torough Agricultural Station of Khorasan-e-Razavi Agriculture and Natural Resources Research Center, Mashhad, Iran, in 201٣. The station is located at the latitude of 36 13' N, longitude of 49 40' E and altitude of 985 meters above the sea level. The annual rainfall is 256 mm and the climate is dry and cold. Soil texture of the experimental site is silty loam. The soil ph is 7.8 8. Each plot consisted of two rows of 5.8m length with 75cm and 17.5cm space between rows and plants within rows, respectively. The plant density was 75500 plant/ha. Three seeds were planted in each hill and thinned to one plant per hill 15 days after seeding. Plots were irrigated as needed to maintain a good crop growth. The plots were kept weed free by hand weeding. During the growth season, days to silk, days to anthesis and days to physiological maturity, were recorded. Furthermore, 10 random competitive plants from P1 and P2, 15 plants from F1, 20 plants from BC1 and BC2 and 30 plants from F2 populations were measured for traits such as number of leaves, number of leaves above the ear, plant and ear height, ear length, 1000 kernel weight, kernel depth, number of kernel rows, number of kernels per row and grain yield. 195

Data were subjected to analysis of variance to verify the differences among generations. Mid-parent heterosis was calculated as the F1 mean deviation from the mid-parent as a percent of mid-parent: H% (MP)= (F1-MP/MP) 100 Furthermore, the means and variances of parental, F1, F2, BC1and BC2 generations were used to estimate the components of gene action by the weighted least squares method (Mather and Jinks, 1982). Variance components (additive, dominance and environment) were estimated as describ ed by Kearsey and Pooni (1996) using the following equations: Environment variance: VE = 1/4 (VP1 + VP2 + 2VF1) Additive variance: V[d] = (2VF2 VBC1 VBC2) Dominance variance: V[h] = 4 (VF2 1/2V[d] E) Average degree of dominance: (H/D) 1/2 = (V[h]/V[d]) 1/2 The accuracy of the additive-dominance model was tested using the following equations (Kearsey and Pooni 1998): A = 2 BC1 P1 F1 B = 2 BC2 P2 F1 C = 4 F2 2F1 P2 P2 Variance components (additive, dominance and environment) were estimated as described by Mather and Jinks (1982) using the following equations: D = 4 VF2 2 (VBC1 + VBC2) H = 4 (VB1 + VB2 - VF2 - VE) EW = 0.25 (VP1 + VP2 + 2VF1) F = (VBC1 - VBC2) In these formulae, V stands for variance and the subscripts refer to generations. EW, D and H are variances of environment, additive and dominance effects, respectively. F is the correlation between H and D in all loci. Broad-sense (h2b) and narrow-sense (h2n) heritability`s were estimated using the following formula: h 2 b= {[VF2-(VP1 VP2)1/2]/VF2} (Mahmud and Kramer 1951) h 2 b= {[VF2-(VP1 VP2+VF1)/3]/VF2} (Allard 1960) h 2 b= {[VF2-(VP1+VP2)/2]/VF2} (Allard 1960) h 2 b= {[VF2-(VP1+VP2+ 2VF1)/4)]/VF2} (Mather and Jinks 1982) h 2 n= [VF2 (VBC1 + VBC2) /2] / VF2 Gene number was estimated by the following formulae (Chen and Line 1995). Although each formula has its restrictions and assumptions, all assume equal gene effects (Dehghani et al. 2002). 1: n= (μf1-μp1)2/{4[σ2bc1-0.5(σ2f1+ σ2p1)]} 2: n= (μp2-μf1)2/{4[σ2bc2-0.5(σ2f1+ σ2p2)]} For the generation mean analysis, at first, additive-dominance model was conducted using weighted least squares. The joint scaling test was carried out to verify the goodness of fit of the model (Kearsey and Pooni 2006). Different software such as Excell 2007, SAS 9.1, SPSS 17, Minitab 15, were used to analyze the data in this study. RESULTS AND DISCUSSION Means analysis Analysis of variances indicated significant difference among generations for all traits. Therefore, it was possible to carry out generation mean analysis for these characters. The means and standard errors of the six generations of cross for 1٥ studied traits are presented in Table 1 and results showed that F1 means were higher than either of the highest parent or mid-parent for all traits under study except for the phonological characters. For phonological traits the condition was mostly reversed because most of the F1 means were lower than the lowest parent or mid-parent. These results indicated over-dominance or partial dominance for all studied characters. Similar results were obtained by Saeed et al. (2000), Vidal-Martinez et al. (2001), Rezaei and Roohi (2004), Srdic et al. (2007), Singh and Roy (2007), Alam et al. (2008) and Shahrokhi et al. (2013). Some F1 hybrids were lower than the highest parent or mid-parent value for number of leaves, number of leaves above the ear, ear height, number of rows, days to silk, days to anthesis and days to physiological maturity in the R59 OH43/1-42 cross. Therefore, negative heterosis was estimated for traits days to silk, days to anthesis and days to physiological maturity (table 1). The highest heterosis was found for grain yield (149.45 ). These results obviously showed that the breeding methods based on hybridization will result in the improved yield in corn. 196

Variance components Variance components for all traits are presented in Table 2. In most of studied traits, dominance variance (H) was more than additive variance (D). Thus hybridization would be more effective than population selection. Average degree of dominance, [(H/D) 1/2 ], were greater than unity for most of the traits (Table 2). The results indicated that these traits were affected by over-dominance effects of some genes controlling the characters under study which is reflected in the low narrow-sense heritability. Oching and Compton (1994) and Petrovic (1998) also showed the importance of dominance relative to additive genetic effects in maize. The average degree of dominance [(H/D) 1/2 ], was less than unity for total height, plant height, ear height, number of rows, number of leaves above the ear,grain yield, day to silk and day to physiological maturity in the R59 OH43/1-42 cross indicating the partial dominance gene action for these traits. Positive value of F for most of traits, except total height, ear height, plant height, leaf area, day to anthesis, day to silk and 1000 grain weight, suggested that dominant alleles were more abundant than the recessive alleles in the parents and indicated the importance of dominance gene action in the inheritance of the traits under study(table 2). Heritability and Genes number Broad-sense and narrow-sense heritability estimates based on variance of different generations are presented in Table 3. In R59 OH43/1-42 cross, grain yield trait had the highest broad-sense heritability (0.88) and ear height (0.23), had the lowest. This again indicates the preponderance of dominance variance in governing the grain yield. Except for narrow-sense heritability estimates of grain yield (0.82), day to silk (0.74), up ear leaves No. (0.58), other heritability estimates were low suggesting the relative importance of dominance effects as compared to additive effects in controlling most of the maize traits under study(table 3). The estimated numbers of genes controlling various traits using different formulae are presented in Table 4. Considering formulae, number of genes controlling the grain yield ranged from 2 to 5 genes. More than one gene were also involved in governing most of the traits under study indicating the polygenic inheritance of these traits in maize. However, the genes controlling quantitative traits could be linked and would, therefore, segregate as a group or effective factor (Milus and Line 1986). If this was true for the present study, the formulae would have under estimated the number of effective factors, and the number of individual genes would have been greater. Table 1. generation mean and standard error (S.E.)of various traits of the cross R59 (P1) OH 43/1-42(P2) of corn Generation total height Plant height Ear height Leaves no. P1 198.27 ± 15.07 c 170.5 ± 9.96 b 78.9 ± 8.49 c 11.93 ± 0.74 c P2 171.97 ± 15.03 d 147.97 ± 12.46 c 55.3 ± 12.03 d 11.27 ± 1.17 c FI 240.13 ± 14.53 a 201.51 ± 12.62 a 104.47 ± 12.74 a 12.22 ± 0.9 c F2 226.8 ± 13.67 ab 190.71 ± 13.93 a 102.6 ± 17.26 ab 13.12 ± 1.08 b Bc1 223.45 ± 15.7 ab 189.32 ± 13.95 a 104.67 ± 13.2 a 13.42 ± 1.05 b Bc2 220.7 ± 9.72 bc 189.12 ± 9.83 a 90.47 ± 10.54 bc 14.17 ± 1.25 a %Heterosis 29.73 26.55 55.69 5.36 Generation leaf area Up ear leaves no. Ear length Rows no. P1 440.33 ± 58.48 bc 5.67 ± 1.24 bc 10.5 ± 1.16 d 19.6 ± 6.86 a P2 358.49 ± 49.32 c 5.43 ± 0.77 bc 11.73 ± 1.44 c 19.2 ± 1.94 a FI 616.86 ± 124.72 a 5.43 ± 1.2 bc 17.36 ± 2.6 a 24.8 ± 9.45 a F2 558.92 ± 92.15 a 5.93 ± 1.33 bc 15.22 ± 2.07 b 18.04 ± 1.82 a Bc1 549.06 ± 99.53 ab 6.87 ± 0.65 ab 16.32 ± 2.04 ab 17.83 ± 2.37 a Bc2 498.56 ± 63.01 ab 6.4 ± 1.09 ab 15.7 ± 2.56 b 32.67 ± 10.78 a %Heterosis 54.44 4.5 56.12 27.84 197

Table 1.continued eneration Kernel no. Kernel depth 1000 grain weight Grain yield P1 21.4 ± 3.61 d 8.56 ± 1.17 b 227.58 ± 11.23 b 5.34 ± 0.64 b P2 26.27 ± 4.27 c 11.18 ± 1.79 a 162.7 ± 40.22 b 5.58 ± 1.12 a FI 40.49 ± 6.42 a 12.39 ± 1.93 a 262.91 ± 13.45 b 13.62 ± 1.53 a F2 34.71 ± 3.63 b 11.56 ± 2.36 a 226.13 ± 22.57 a 11.25 ± 2.88 a Bc1 37.27 ± 5.82 ab 11.22 ± 2.18 a 254.27 ± 36.84 b 12.46 ± 1.33 a Bc2 35.22 ± 7 b 12.12 ± 3.3 a 231.43 ± 20.36 b 12.19 ± 1.38 a %Heterosis 69.88 25.51 34.73 149.45 Generation Days to anthesis Days to silk Days to physiological maturity P1 61.89 ± 7.1 a 62.44 ± 2.7 b 131.22 ± 2.27c c P2 68.22 ± 24.38 a 62.56 ± 1.33 a 132.98 ± 40.63 a FI 64.27 ± 1.6 a 61.43 ± 1.23 ab 132 ± 5.16 b F2 63.9 ± 5.57 a 60.4 ± 7.14 c 133.7 ± 8.12 c Bc1 61.9 ± 7.28 a 59.8 ± 7.42 b 131.2 ± 5.81 b Bc2 63.6 ± 6.72 a 60.7 ± 2.21 ab 133.6 ± 7.34 ab %Heterosis -1.27-1.71-0.08 Table 2. Estimates of the components of variation, dominance ratio, F/(D*H) 1/2 ratio and degree of dominance for various traits of the cross R59 (P1) OH 43/1-42(P2) of corn Traits D H F EW (H/D) 1/2 total height 65.58 37.91-151.94 144.61 0.76 Plant height 77.86 1.66-97.91 125.66 0.15 Ear height 36.00 3.00-64.00 132.25 0.29 Leaves no. 0.54 1.23 0.47 0.89 1.51 leaf area 245.62 5655.01-5936.98 5463.44 4.80 Up ear leaves no. 2.05 0.38 0.87 0.65 0.43 Ear length 0.29 4.19 2.39 4.24 3.83 Rows no. 5.78 0.28 2.56 5.36 0.22 Kernel no. 3.03 49.13 15.02 28.40 4.03 Kernel depth 0.65 9.01 1.34 3.00 3.72 1000 grain weight 201.40 1012.79-89.55 155.68 1.24 Grain yield 13.57 0.14 6.23 1.45 0.10 Days to anthesis 11.96 34.56-40.00 16.37 1.70 Days to silk 75.60 3.48-46.07 12.26 0.21 Days to physiological maturity 88.93 0.65 20.09 21.38 0.09 Table 3. Estimates of the heritability by different methods for various traits of the cross R59 (P1) OH 43/1-42(P2) of corn Trait Broad sense heritability (Hb) Mahmud and Kramer (1951) Allard -1960 Allard-1960 Mather and Jinks (1982) Mean Narrow sense heritability(hn) total height 0.58 0.61 0.34 0.23 0.44 0.18 Plant height 0.44 0.44 0.31 0.24 0.35 0.24 Ear height 0.32 0.32 0.19 0.12 0.23 0.12 Leaves no. 0.34 0.41 0.38 0.39 0.38 0.18 leaf area 0.58 0.59 0.34 0.22 0.43 0.02 Up ear leaves no. 0.62 0.63 0.63 0.63 0.62 0.58 Ear length 0.69 0.69 0.38 0.22 0.49 0.03 Rows no. 0.35 0.38 0.36 0.36 0.36 0.36 Kernel no. 0.63 0.63 0.43 0.33 0.50 0.04 Kernel depth 0.59 0.63 0.50 0.46 0.54 0.06 1000 grain weight 0.74 0.74 0.71 0.69 0.72 0.20 Grain yield 0.93 0.94 0.86 0.82 0.88 0.82 Days to anthesis 0.03 0.28 0.32 0.47 0.27 0.19 Days to silk 0.91 0.93 0.81 0.76 0.85 0.74 Days to physiological maturity 0.76 0.82 0.70 0.68 0.74 0.67 198

Table 4. Estimates of the number of segregation genes for various traits of the cross R59 (P1) OH 43/1-42(P2) Trait formulas 1 2 total height 2 3.8 Plant height 1.6 3.7 Ear height 3.7 3.8 Leaves no. 1.2 0.1 leaf area 0.5 1.9 Up ear leaves no. 1.1 2.5 Ear length 0.2 0 Rows no. 0 1 Kernel no. 0.2 13.3 Kernel depth 0.3 1.7 1000 grain weight 10.5 0.7 Grain yield ٢.٥ ٤.٣ Days to anthesis 0.3 0.1 Days to silk ٠.٣ ٠.٤ Days to physiological maturity 0.6 0 CONCLUSION In most traits dominance variance (H) was more than additive variance (D). Thus hybridization would be more effective than population selection. It was observed that dominance and over dominance effect had a considerable role in controlling leaves no.,leaf aria, ear length, kernel no., kernel depth, 1000 grain weight and days to anthesis in R59 OH43/1-42 cross of maize. Thus effective utilization of this type of gene action together with the dominance gene effect in hybrid breeding is justified in maize considering their significant effects and higher broad-sense heritability of grain yield and other agronomic traits. ACKNOWLEDGMENT We appreciate the support from the Khorasan-e-Razavi Agricultural and Natural Resources Research Center of Mashhad, Iran. REFERENCES Akbar M, Saleem M, Azhar FM, Ashraf MY, Ahmad R. 2008. Combining ability analysis in maize under normal and high temperature conditions. Journal of Agricultural Research 46(1): 27-38. Alam AKMM, Ahmed S, Begum M, Sultan MK.2008. Heterosis and combining ability for grain yield and its contributing characters in maize. Bangladesh Journal of Agricultural Research 33(3): 375-379. Allard RW.1960. Principles of Plant Breeding. 2nd edition. John Wiley and Sons Inc, New York. Amer EA, El-Shenawy AA, Mosa HE. 2002. A comparison of four testers for the evaluation of maize yellow inbreds. Egyptian Journal of Applied Science 17: 597-610. Dehghani H, Moghaddam M, Ghannadha MR, Valizasdeh M, Torabi M. 2002. Inheritance of the latent period of stripe rust in wheat. Journal of Genetics and Breeding 56: 155-163. Dhillon BS, Singh J. 1976. Diallel analysis of yield and other traits of maize varieties. SABRAO Journal 8: 147-152. Fan XM, Zhang YM, Yao WH, Chen HM, Tan J, Xu CX, Han XL, Luo LM, Kang MS. 2009. Classifying maize inbred lines into heterotic groups using a factorial mating design. Agronomy Journal 101: 106-112. Kearsey MJ, Pooni HS. 1998. Genetical Analysis of Quantitative Traits. Chapman and Hall Press. Kumar A, Ganshetti MG, Kumar. 1998. Gene effects in some metric traits of maize (Zea mays L.). Annals of Agricultural Biologi cal Research 3(2): 139-143. Kumar R, Singh M, Narwal MS, Sharma S. 2005. Gene effects for grain yield and its attributes in maize (Zeamays L.). National Journal of Plant Improvement 7(2): 105-107. Mather K and Jinks JL, 1982. Biometrical Genetics. Methuen, London, 162pp. Melchinger AE, Lee M, Lamkey KR, Hallauer AR, Woodman WL. 1990. Genetic diversity for restriction fragment length polymorphisms and heterosis for two diallel sets of maize inbreds. Theoretical and Applied Genetics 80: 488-496. Milus EA, Line RF.1986. Number of genes controlling high-temperature adult-plant resistance to stripe rust in wheat. Phytopathology 76: 93-96. Muraya MM, Ndirangu CM, Omolo EO. 2006. Heterosis and combining ability in diallel crosses involving maize (Zea mays L.) S1 lines. Australian Journal of Experimental Agriculture 46(3): 387-394. Novoselovic D, Baric M, Drezner G, Gunjaca J, Lalic A. 2004. Quantitative inheritance of some wheat plant traits. Genetic and Molecular Biology 27:92-98. Oching JAW, Compton WA. 1994. Genetic effects from full-sib selection in Krug maize. Journal of Genetics and Breeding 48:191-196. Ojo GOS, Adedzwa DK and Bello LL. 2007. Combining ability estimates and heterosis for grain yield and yield components in maize (Zea mays L.). Journal of Sustainable Development in Agriculture and Environment 3: 49-57. Paul KK, Debnath SC. 1999. Combining ability analysis in maize (Zea mays L.). Pakistan Journal of Scientific and Industrial R esearch 42(3): 141-144. Petrovic Z. 1998. Combining abilities and mode of inheritance of yield and yield components in maize.novisad 8: 81-85. 199

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