Gene Action and Heritability Estimates of Grain Yield and Disease Incidence Traits of Low-N Maize (Zea mays L.) Inbred lines

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1 AGRICULTURE AND BIOLOGY JOURNAL OF NORTH AMERICA ISSN Print: , ISSN Online: , doi: /abjna , ScienceHuβ, Gene Action and Heritability Estimates of Grain Yield and Disease Incidence Traits of Low-N Maize (Zea mays L.) Inbred lines A. E. SALAMI + AND G.O AGBOWURO Department of Crop, Soil and Environmental Sciences, Ekiti State University, Ado-Ekiti, Nigeria + Corresponding author: ayodeji.salami@eksu.edu.com ABSTRACT Six low nitrogen (N) maize inbred lines were utilized to study the gene action of low-n using North Carolina Mating Design II. Three of the lines were considered male and the three others as female. Crosses were made among the parents to generate 9 F 1 s which were evaluated at the Teaching and Research Farm of Ekiti State University, Ado-Ekiti in two seasons of 2014, using two environments created by levels of N (low and high). General Combining Ability for male (GCAmale) were significant (P<0.01) for all the traits studied also, GCAfemale were significantly different for all traits except ear aspect. Specific Combining Ability (SCA) were significant (P<0.01) for all the traits studied except ear rot and leaf blight. Furthermore, there were preponderance of additive genetic variance for grain yield (1.05), ear rot (0.21) and leaf blight (0.16). Conversely, there were prevalence of dominance genetic variance for ear aspect, plant aspect and leaf spot ranging from 0.17 for leaf spot and for plant aspect. Since both additive and dominance gene actions were important for low-traits, the use of reciprocal recurrent selection procedure can be adopted in incorporating the trait into elite maize varieties. Key words: Low N maize, dominance, additive, genetics, North Carolina Design INTRODUCTION Maize (Zea mays L.) is one of the major cereal crops in tropical Africa (Ogunniyan and Olakojo, 2014). It is cultivated worldwide on more than 160 million hectares every year and production was put at 785 million tons (Umar et al., 2014). It is a widely grown crop in most parts of the world, due to its adaptability, versatility, varied varieties and productivity. In Nigeria, Maize is an important crop as it provides food for and helps to sustain the rapidly increasing human population. Apart from proving staple diet for human population, maize is also an important crop in industrial and livestock production in the country (Vacaro et al., 2002). Maize productivity per unit area is very low in tropical environment for various reasons such as poor yield varieties grown, biotic factors (weeds, pests, insects, diseases), unpredictable weather conditions, high post-harvest and storage losses, poor agronomics practices, abiotic stress (drought and low soil fertility). Nitrogen is the most widely deficient nutrient limiting maize growth and can significantly affect yield (Amanda et al., 2008). Most Nigeria soils are inherently low in N and its deficiency is due to the rapid loss of the nutrients through plant uptake or losses through erosion, volatilization or leaching. In view of the importance of maize in Nigeria, improving maize production is considered to be one of the most important strategies for food security in developing country. Efforts are continuously being made to increase its yield through extending land area where it can be grown as well as yield per unit area of land. Nearly all cultivated maize in developed countries receives some form of N fertilizer and N use is increasing in developing countries, where its impacts on raising grain yields from nutrient-poor soils are greatest. The extensive use of N fertilizer not only increase crop input costs, but also can negatively impact soil, water and air quality at both local and ecosystem scale (Tilman et al., 2002). For these reasons, reducing the amount of supplemental N used in maize production by developing low-n tolerance varieties will have significant positive economic and environmental benefits. A pragmatic strategy to boost productivity of maize can be by the use of varieties that are tolerance low-n in soils (Smith et al., 1995). These varieties will be able to produce reasonably well under low-n condition. Reports from several studies have indicated that

2 useful genetic potential exist in maize genotypes for the improvement of nitrogen use efficiency (Heuberger et al., 1995, kling et al., 1996). Combining ability of an inbred rests on its ability to produce superior hybrids in combination with other inbred. General combining ability (GCA) is the average performance of a genotype in hybrid combination while Specific combining ability (SCA) are those cases in which certain combinations perform relatively better or worse than expected on the average. Falconer and Mackay(1996) observed that GCA is directly related to the breeding value of the parent and is associated with additive genetic effects, while SCA is associated with non- additive effects such as dominance, epistasis and genotype x environment interaction effects (Bello and Olaoye, 2009). Information on genetic behavior of low-n traits will help breeders to determine the appropriate breeding strategy to adopt in improving maize varieties that are tolerance to low-n. To carry out genetic studies for any trait(s), estimate of additive, dominance and heritability are critical. This study was conducted to estimate additive, non-additive variances and average degree of dominance as well as narrow sense heritability. MATERIALS AND METHODS The experimental site was located at the Teaching and Research Farm of Ekiti State University, Ado- Ekiti, Nigeria located on N, E. The area is located within a tropical humid climate with district wet and dry seasons. The site has been previously put into cultivation of arable crops like maize, cassava and vegetables. A composite soil sample was taken randomly from the experimental site at the depth of 0-15cm. The soil sample was thoroughly mixed, bulked, air dried, crushed and sieved through 2mm sieve for physical and chemical analyses. The parents of the genetic materials used for this study were low-n genetic materials obtained from International Institute of Tropical Agriculture, Ibadan. The parents are (i) LNTP-YG (ii) TZPBProlC 4 (iii) TZLComp1C 6 LNC 1 (iv)br99tzlcomp4 DMSRSR (v) DMR-ESR-W-LN (vi) TZPBProlC 3 LN SYN. These parents were selfed five times to achieve 96.9% homozygosity before the desired crosses were made. Inbred lines extracted from for open pollinated parents were used for the crosses. Three inbred lines from LNTP-YG, BR99TZL Comp4 DMSRSR and TZPBProlC 4 were considered male and the three other lines, TZLComp1C 6 LNC 1, DMR-ESR-W-LN and TZPBProlC 3 LN SYN were females. Each of the male lines was used to mate each of the three female lines to generate nine crosses. When crosses were being made, ear shoots were covered with ear shoot bags before the silks emerged to prevent natural pollination and contamination by foreign pollens. The shoots covering was done on daily basis, started when the first ear appeared and continued until the last ear emerged. Pollens grains of the predetermined male plants were collected by covering the tassels at the pollen shed time with tassel bag. The pollens grains from the pre-determined male plant were used to pollinate the three pre-determined female plants. Pollen bags were used to cover the pollinated silks to ensure that pollens from another plant do not come in contact with the silk. Lines of the male by female were written on the pollen bags used to cover the ear shoots with permanent marker for the purpose of easy identification or mixed up. The nine crosses were then evaluated in late season of 2014 and early season of 2015 using Randomized Complete Block Design with three replicates. Each plot consisted of two row plot of 5m length. The experiment was carried out in two viz. low-n and high-n conditions. Low and high N conditions of the soil was induced by application of urea fertilizer at the rate of 30kg N ha -1 and 90kg N ha -1. In all the environments, 75cm inter-rows and 50cm intra-rows was used. Three seeds were initially planted per hill but were later thinned to two at 3 weeks after planting (WAP) to give a planting density of 53,333 plants ha - 1.weeds were controlled manually throughout the experiment. Data were collected on ear aspect, ear rot, leaf blight, leaf spot, plant aspect and grain yield. The analysis of variance, the variance components and expected mean square were estimated using the outline in Table 1 with the aid of SAS institute (1995) software. Both general combining abilities (GCA) and specific combining abilities (SCA) were computed for the crosses with respect to grain yield and other agronomic traits. The analysis was based on the model by Singh and Chaudhary (1985 ) as where, Y ijk = u + m i + f i + ( m x f ) ij + e ijk Y ijk is the kth observation of i x jth progeny, u is the general mean, m i is the effect of ith male, f i is the effect of jth female, ( m x f ) ij is the interaction effect, and e ijk is the error associated with each observation. The component variances will have the following genetic interpretations: δ 2 =(MSm-MSmxf)/fr = Cov(H.S.)= (1/4)δ 2 A 51

3 δ 2 = (MSf- MSmxf)/mr = Cov (H.S)= (1/4)δ 2 A (1/4)δ 2 D δ 2 mxf( MSmxf-MSe)/r = Cov(F.S.)-2 Cov (H.S.)= Table 1. Expectation of Mean Square in ANOVA of NC II Design S/V df MS EXPECTED MEAN SQUARE Rep. r-1 Env. e-1 M m-1 M7 δ 2 +r δ 2 fme + rf δ 2 me +re δ 2 mf+ref δ 2 m F f-1 M6 δ 2 +r δ 2fme + rm δ 2 fe +re δ 2 mf +rem δ 2 f M x E (m-1)(e-1) M5 δ 2 + r δ 2 fme+re δ 2 mf F x E (f-1)(e-1) M4 δ 2 + r δ 2 fme+rf δ 2 me M x F (m-1)(f-1) M3 δ 2 + r δ 2 fme+rm δ 2 fe M x F x E (m-1)(f-1)(e-1) M2 δ 2 + r δ 2 fme Pooled error e(r-1)(mf-1) M1 δ 2 S/V: source of variance; df. degree of freedom; M.S: mean square. RESULTS AND DISCUSSION Table 2: Mean Squares from ANOVA for grain yield and disease incidence traits Mean Performance: The analysis of variance showed that the mean squares for all traits are presented in Table 2. Source of Variation df Grain yield Ear Aspect Plant Aspect Ear Rot Leaf Blight Leaf spot Rep ** 0.420** Env(E) ** 1.040** 0.840** 0.370** 0.260** Male (M) ** 0.690** 0.370** 0.780** 0.690** 0.540** Female (F) ** ** 0.400** 0.190** 0.130** M x E ** 0.320** 0.790** 0.780** F x E ** 0.280** M x F ** 0.180** 0.460** ** M x F x E ** 0.490** 0.880** Error *, * * Significant at < 0.05 and < 0.01 levels of probability respectively Means sum of squares due to GCAmale were significant for all the studied traits. Also, the means sum squares for GCAfemale were significant for all traits except ear aspect. In the same manner, SCA sum of means squares were significant for all the studied traits excepts ear rot and leaf blight. Moreover, means sum of squares due to environment were also significant for all the studied traits. This indicated the existence of a high degree of genetic variability to be exploited in breeding program, and it reflected the broad ranges observed for each trait. Hence, it could be noted that, both additive and nonadditive gene actions are important for low N maize improvement. 52

4 Gene Action and Other Genetic Parameters Table 3: Estimation of components of variance and heritability Estimate of additive, dominance, narrow sense heritability and average degree of dominance was presented in Table 3. Grain yield Ear Aspect Plant Aspect Ear Rot Leaf Blight Leaf spot δ 2 A 1.05± ± ± ± ± ±0.34 δ 2 D 0.44± ± ± ± ± ±0.01 h 2 ns (%) Ā dd δ 2 A = additive genetic variance δ 2 D = dominance genetic variance h 2 ns (%) = narrow sense heritability ā = average degree of dominance dd= degree of dominance There were also preponderance of dominance genetic variance for ear aspect, plant aspect and leaf spot ranging from 0.7 for leaf spot to for plant aspect which indicated that the traits are controlled by non-additive genes. Dominance genetic variance is associated with heterozygosity and it is not fixable. The preponderance of non additive gene action for these traits under study indicated that improvement of these characters could be possible through heterosis breeding (Hybridization). There were also the preponderance additive genetic variance for ear rot, leaf blight and grain yield. Additive genetic variance is associated with homozygosity and it is fixable. Average degree of dominance denoted by ā determine the average level of dominance. Average degree of dominance action equal to 0 shows absence of dominance genetic action, when equal to 1 shows that there is a complete dominance action, when it is greater than 0 and less than 1 shows that shows that there is a partial dominance but when greater than 1 shows a case of over dominance genetic action. The results revealed average degree of dominance values for ear aspect, plant aspect, ear rot and grain yield was 0 which shows that there is a complete absence of dominance gene action while leaf blight and leaf spot were 0.44 and 1.13 respectively. The results indicated that additive gene governed most of the studied traits including the grain yield. The results revealed that there were absence of dominance action for these traits except leaf blight and leaf spot. In the absence of dominance action for these traits, additive gene action prevailed. According to Ansari et al., (2004) who reported that, high heritability percentage reflects the large heritable variance which may offer the possibility of improvement through selection. Acquaah, ( 2012) also explained that high heritability would likely to result in high response to selection to advance the population in the desired direction of change. Although, Sardana et al.,(2007) suggested that high heritability may not necessarily lead to increased genetic gain, unless sufficient genetic variability existed in the germplasm. Low narrow sense heritability indicates that the trait is control by non-additive gene while high narrow sense heritability indicates that the trait is control by additive gene. Narrow sense heritability values were low for some studied traits while some are high. Ear rot, leaf blight and grain yield have a narrow sense heritability value percentage above 40% while other studied traits have below 40%. Grain yield have a high narrow sense heritability value of 52%, which shown that it was controlled by additive gene. From the study, grain yield being the most economic part in maize plant recorded higher additive genetic value over non-additive genetic value, it also recorded an average degree of dominance value to be 0 which indicated that there is an absence dominance action and its narrow sense heritability 53

5 value was 52% which indicated greater proportion of additive genetic variation. Therefore, selection for these traits governed by additive genetic variance will be very effective. Existence of additive genetic variance is prerequisite for improvement through selection because this is the only variance that responds to selection. CONCLUSION The present study indicated that we can depend on both additive and non-additive variance for improvement in low N maize yield. REFERENCE Acquaah, G. ( 2012). Principles of plant genetics and breeding. 2nd ed. Wiley-Blackwell, Oxford. Amanda Oliveira Martins, Eliemar Campostrini, Paulo César Magalhães, Lauro José Moreira Guimarães, Frederico Ozanan Machado Durães, Ivanildo Evódio Marriel, and Alena Torres Netto (2008) : Nitrogen-use efficiency of maize genotypes in contrasting environments Crop Breeding and Applied Biotechnology 8: , 2008 Ansari, B. A., Ansari, K. A., and Khund, A. (2004). Extent of heterosis and heritability in some quantitativecharacters of bread wheat. Indus. J. Pl. Sci., 3, Bello, O. B. and Olaoye G. (2009). Combining ability for maize grain and other agronomic characters in the tropical southern savanna ecology of Nigeria. Africa Journal of Biotechnology 8 (11), Falconer, D.S. and T.F.C. Mackay. (1996). Introduction to quantitative genetics. 4th ed. Pearson Prentice Hall, Harlow, England Heuberger, H.T., Kling, J.G. an Horst, W.J.( 1995). Effectof root growth characteristics on nitrogen useefficiency of tropical maize (Zea mays L.) varieties. Pp In Jewell, D.C., Waddington, S.R., Kling J. G. IITA Research Guide No. 9 Morphologhy and growth of maize. Pp. 29 Ogunniyan D. J. and Olakojo S. A. ( 2014 ). Genetic Variability of Agronomic Traits of Low Nitrogen Tolerant Open-Pollinated Maize Accessions as Parents for Top-Cross Hybrids. Journal of Agriculture and Sustainability, S.A.S. Institute, SAS/STAT user s guide. Version 6,4 th ed. Vol. I and II. SAS Inst. Inc. Cary N.C., U.S.A. Sardana, S., Mahjan, R., Gautam, N., & Ram, B. (2007). Genetic variability in pea (Pisum sativum L.)germplasm for utilization. SABRAO J. Breed. Genet., 39(10), Singh R.K. and Chaudhary B. D., (1985) Biometrical Methods in Quantitative Genetics Analysis. 2nd ed. Kalyani Publishers, New Delhi, India. Smith, M.E., Miles, C.A. and Van Beem, J. (1995). Genetic improvement of maize for nitrogen use efficiency. In: Jewell DC, Waddington SR, Ransom JK and Pixley KV (eds). Maize Research for Stress Environments. Proceedings of the 4th Eastern and Southern Africa Regional Maize Conference, Harare, Zimbabwe, 28 March-1April Mexico D.F. CIMMYT. 306 pp. Tilman D, Cassman KG, Matson PA, Naylor RL, Polasky S.( 2002). Agricultural sustainability and intensive production practices. Nature 418: Umar U.U, Ado S. G., Aba D. A., and Bugaje S. M. (2014).Estimates of Combining Ability and `Gene Action in Maize (Zeamays L.) Under Water Stress and Non-stress Conditions.Journal of Biology, Agriculture and Healthcare pp Vacaro, E., Fernandes, J., Neto B., Pegoraro D. G., Nuss C. N. and Conceicao L. H. (2002). Combining ability of twelve maize population. Pesq. Agropec. Bras. Brasilia. 37: