Heritability and Correlation Estimates in Maize (Zea mays L.) Under Drought Conditions in Northern Guinea and Sudan Savannas of Nigeria

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World Journal of Agricultural Sciences 8 (6): 598-602, 2012 ISSN 1817-3047 IDOSI Publications, 2012 DOI: 10.5829/idosi.wjas.2012.8.6.1696 Heritability and Correlation Estimates in Maize (Zea mays L.) Under Drought Conditions in Northern Guinea and Sudan Savannas of Nigeria 1 2 D. Aminu and A.U. Izge 1 Department of Crop Production, Faculty of Agriculture, University of Maiduguri, P.M.B. 1069, Maiduguri, Borno State, Nigeria 2 Department of Crop Science, Faculty of Agriculture, Federal University, Dutse, P.M.B. 7156, Dutse, Jigawa State, Nigeria Abstract: During the 2007 cropping season, a nursery plot was established at Faculty of Agriculture Teaching and Research Farm, University of Maiduguri, Nigeria (Latitude 11 14 N and Longitude 13 04 E on an altitude of 354 m above sea level). Nine parental lines (five males and four females) were crossed to generate twenty hybrids using a line x tester design. Twenty-nine entries consisting of the twenty F 1 hybrids plus nine parental lines were laid-out in a randomized complete block design (RCBD) with three replications and were evaluated in two locations (Biu latitude 11 2 N and longitude 13 2 E and Damboa latitude 11 10.5 N and longitude 12 46.3 E) during the cropping seasons of 2008 and 2009. The sowing was carried out in mid and end of August th th (15-30 August) in Sudan and Northern Guinea savannas each year, respectively in order to subject the entries to moisture stress. Evaluations were done to investigate broad-sense heritability and correlations between the traits and total grain yield. The results showed higher heritability estimates of 61.54%, 60.78%, 60.61%, 67.44% and 60.73% for number of stands per plot, anthesis silking interval, plant height, weight of cobs and grain yield, respectively. However, heritability estimates of 47.91%, 50.03%, 58.45% and 55.06% were obtained for days to tasseling, days to silking, ear height and dehusked cobs, respectively. Higher and relatively moderate broad-sense heritability of the traits revealed that variations were transmisible and potential for developing high yielding varieties through selection of desirable plants in succeeding generations exist. The correlation analysis revealed that anthesis silking interval (r = 0.877), number of cobs per plant (r = 0.548g and r = 0.322e), number of cobs per plot (r = 0.828), weight of cobs (r = 0.797e and r = 0.857e), dehusked cobs (r = 0.954g, r = 0.486p and r = 0.876e) and 100-seed weight (r = 0.4623g and r = 0.316e) exhibited positive and significant genotypic (g), phenotypic (p) and environmental (e) correlation with grain yield. Substantial variability exists in parental lines and the hybrids for drought tolerance and grain yield, indicating that there is an opportunity for improvement via selection. The magnitude of genotypic correlations were higher than those of phenotypic and environmental correlation coefficients to grain yield, which means that selection for these traits will improve grain yield. The study also observed that correlations as well as heritability were suitable as models for yield improvement and selection for drought tolerant genotypes. Traits that had higher heritability and positive correlation with grain yield may be considered as important traits in selection programme aiming to maize yield improvement and the breeder may consider these traits as main selection criteria. Key words: Drought Maize Heritability Correlation Traits Line tester INTRODUCTION Maize (Zea mays L.) is a tropical cereal and is currently the third most important cereal, after wheat and rice, cultivated on over 160 million hectares. Africa harvests 29 million hectares, with Nigeria, the largest producer harvesting 3 % [1]. Grain yield is a complex trait conditioned by the interaction of various growth and physiological processes throughout the life cycle. The nature of association between grain yield and its Corresponding Author: D. Aminu, Department of Crop Production, Faculty of Agriculture, University of Maiduguri, P.M.B. 1069, Maiduguri, Borno State, Nigeria. Tel: +2348030636782. 598

components determine the appropriate traits to be used in between rows and 40 cm within rows. All cultural indirect selection for improvement in grain yield [2]. practices recommended for maize production were Heritability estimates have been extensively used by plant followed to ensure a good crop growth and development. breeders in selection of promising genotypes and in Data were recorded on five randomly selected plant prediction of percentage heritability of desirable traits samples from each replication for twelve quantitative traits Morakinyo [3]. Lukhele [4] also used heritability estimates visa vis: number of stands per plot, days to 50% tasseling, to predict yield component in sorghum. From these days to 50% silking, anthesis silking interval, plant height reports, they all affirmed the suitability of these estimates (cm), ear height (cm), number of cobs per plant, number in prediction and selection of promising crop genotypes of cobs per plot, weight of cobs (g), dehusked cobs (g), during crop improvement programmes. 100-seed weight (g) and grain yield (kg/ha). All statistical The correlation studies simply measure the analysis was carried as described by Singh and associations between yield and other traits. It provides Chaudhary [7]. information that selection for one trait will result in progress for all positively correlated characters. El- RESULTS AND DISCUSSION Shouny et al. [5] and Tollenaar et al. [6] identified different traits like ear length, ear diameter, kernels per The results from the heritability estimates for row, ears per plant, 100-seed weight and rows per ear as combined locations and years are presented in Table 1. potential selection criteria in breeding programmes aiming Locations and years played there roles in modifying the at higher yield. heritability estimates for different traits. Low, medium and The present study affirmed that heritability estimates high estimates of broad sense heritability were found in as well as genotypic, phenotypic and environmental different plant traits under study (Table 1). The heritability correlation coefficients were found suitable as models for estimates is important in choosing the suitable yield improvement and selections for drought tolerance in segregating generations for exhibiting the best expression maize. of gene of different studied traits [8]. High broad-sense heritability estimates were MATERIALS AND METHODS detected for number of stands per plot (61.54 %), anthesis silking interval (60.78 %), plant height (60.61 %), During the 2007 cropping season, the nursery weight of cobs (67.44 %) and grain yield (60.73 %). experiment for the formation of the initial breeding These results are in line with earlier results reported by population (F1 hybrids) were conducted at the Faculty of Olakojo and Olaoye [9] and Wannows [8]. However, Agriculture, Teaching and Research Farm, University of moderate broad-sense heritability estimates were obtained Maiduguri (latitudes 11 14 N and longitude 13 04 E on for days to 50 % tasseling (47.91 %), days to 50 % silking an altitude of 354 m above sea level) to produce twenty F 1 (50.03 %) ear height (58.45 %), dehusked cobs (55.06 %), hybrids. The hybrids produced together with their parents while low heritability estimates were recorded for were evaluated during the rainy seasons of 2008 and 2009 number of cobs per plant (37.21 %), number of cobs per in two locations at Biu and Damboa. Biu is located in plant (43.62%) and 100 seed weight (31.99 %). Similar Northern Guinea Savanna and is characterized by a rainy results were reported by Amer and Mosa [10] and Yassien season period of 130-160 days with range of average [11]. annual rainfall of 900-1400 mm (latitude 11 2 N and Estimates of broad-sense heritability were high for longitude 13 2 E), the soil type is clay or black cotton most of the traits studied. Hasib [12] also reported that the soil. Damboa on the other hand is located in Sudan highest heritability estimates were found in grain yield per Savanna (latitude 11 10.5 N and longitude 12 46.3 E on plant (0.993) and plant height (0.900). Hence provides an altitude of 291m above sea level). It has an average better opportunities for selecting plant material regarding annual rainfall of 500-1000 mm distributed within the rainy these traits. High estimates of broad-sense heritability for season period of 100-120 days. most of the traits revealed that variations were transmitted The sowing were conducted in mid to August end to the progeny and indicated potential for developing th th (15 to 30 August) in Sudan and Northern Guinea high yielding varieties through selection of desirable savanna respectively in 2008 and 2009 to subject the plants in succeeding generations. These results were in genotypes to moisture stress. The plot consisted of four line with those obtained by Saleem et al. [13] and Swati rows of 5 m ridges. The plants stand were spaced 75 cm and Ramesh, [14]. 599

Table 1: Estimates for broad-sense heritability (%) for twelve agronomic traits in maize combined across years and locations Broad-sense heritability (%) ---------------------------------------------------------------------------------------------------------------------------------------------------------- Traits Biu and Damboa 2008 Values Biu and Damboa 2009 Values Biu and Damboa 2008 &2009 Pooled Values Number of stands per plot 36.35 54.31 51.69 Days to 50 % tasseling 43.82 47.20 58.82 Days to 50 % silking 45.51 48.04 61.45 Anthesis silking interval 56.37 56.00 59.51 Plant height 64.84 53.49 65.02 Ear height 48.89 51.19 53.57 Number of cobs per plant 52.76 45.61 46.16 Number of cobs per plot 44.87 55.65 53.34 Weight of cobs 32.79 47.26 69.33 Dehusked cobs 66.01 51.86 62.72 100 grains weight 52.08 58.45 43.57 Grain yield 65.66 61.23 65.47 Range 32.79-66.01 45.61-61.25 43.57-69.33 Mean 50.83 52.52 56.72 Table 2: Analysis of genotype (G), phenotype (P) and environmental (E) correlation coefficients for twelve agronomic traits in maize combined across years and locations DTT DTS ASI PHT EHT NCPL NCPT WC DC HSW GRY NSP G 0.974** 0.937** -0.330* 0.538* 0.578* -0.324* 0.488* -0.284* -0.012-0.565* -0.835** P 0.140 0.169-0.007 0.154 0.102-0.019 0.181 0.040 0.037-0.050 0.029 E 0.014 0.032 0.041 0.119 0.051 0.026 0.366* 0.092 0.106-0.012 0.072 DTT G 0.816** 0.297* 0.740** 0.508* -0.218 0.417* 0.602** -0.440* -0.801** -0.082 P 0.683** -0.022 0.392* 0.484* -0.180-0.076-0.108-0.139-0.256* -0.138 E 0.949** 0.067 0.408* 0.631** -0.280* -0.227-0.261-0.290* -0.374* -0.284* DTS G 0.939** 0.804** 0.641** -0.759** 0.759** 0.275* -0.359* -0.671** -0.198 P 0.019 0.405* 0.499* -0.167-0.073-0.113-0.141-0245* -0.135 E 0.046 0.422* 0.637** -0.289* -0.238-0.254-0.271* -0.362*.-0.265 ASI G 0.746** -0.517* 0.668** 0.959** 0.851** 0.809** 0.175 0.877** P -0.017-0.088 0.110 0.052 0.147 0.162 0.109 0.174 E -0.046-0.148 0.033 0.015 0.166 0.200 0.002 0.211 PHT G 0.665** 0.343* 0.138 0.446* -0.011-0.435* -0.440* P 0.383* -0.062 0.012-0.865** -0.097-0.217-0.091 E 0.451* -0.152-0.022-0.201-0.201-0.264* -0.153 EHT G -0.258-0.168-0.306* -0.362* -0.868** -0.828** P -0.173-0.091-0.170-0.194-0.258-0.199 E -0.342* -0.412* -0.288* -0.322* -0.390* -0.342* NCPL G 0.908** 0.014 0.857** 0.806** 0.548* P 0.103 0.154 0.176 0.158 0.186 E 0.148 0.190 0.208 0.132 0.322* NCPT G 0.015 0.577* 0.216 0.828** P 0.096 0.106 0.110 0.120 E 0.108 0.114 0.217 0.444* WC G 0.522* 0.325* 0.797** P 0.512* 0.217 0.464* E 0.980** 0.321* 0.857** DC G 0.916** 0.954** P 0.240 0.486* E 0.351* 0.876** HSW G 0.462* P 0.240 E 0.320* KEYS NSP =Number of stands per plot ASI=Anthesis silking interval, NCPL = Number of cobs per plant DC = Dehusked cobs DTT =Days to 50% tasseling PHT = Plant height, NCPT = Number of cobs per plot HSW= 100seed weight DTS =Days to 50% silking EHT = Ear height, WC = Weight of cobs GRY = Grain yield * = significant ** = highly significant 600

In this study, genotypic correlations were higher in drought tolerant genotypes. Some traits such as anthesis almost all cases than the phenotypic and environmental silking interval, number of cobs per plant, number of cobs correlations, explaining why genotypic correlation per plot, weight cobs, dehusked cobs and 100-seed showed more significant difference between the pairs of weight were positively correlated with grain yield under traits than phenotypic correlation (Table 2). This result is water stress (drought). These traits are the prominent in harmony with those obtained by Duvick et al. [15] and traits identified in this experiment when selecting for Mohammadia et al. [16]. The results revealed that increased total grain yield. Hence provides better genotype coefficient of number of cobs per plot was less opportunities for selecting plant material regarding these than its corresponding estimates of phenotypic and traits. environmental coefficient in the expression of these traits in anthesis silking interval, cobs per plant, weight of cobs, REFERENCES dehusked cobs, 100-grain weight and grain yield which indicated significant role of environment in the expression 1. FAO, 2009. Crop Prospects and Food Situation. of these traits. Similar results have been reported in maize http://www.fao.ogr/docrep/012/al480e/al484e04.htm. by Rafiq et al. [2]. Genotypic correlation coefficient 2. Rafiq, C.M., M. Rafique and A. Hussain, 2010. revealed that anthesis silking interval, number of cobs per Studies on heritability, correlation and path analysis plant, number of cobs per plot, weight of cobs, dehusked in maize (Zea mays L.). Journal of Agricultural cobs and 100-grain weight showed significant positive Research, 48: 1-35. correlation with grain yield. This showed that selection for 3. Morakinyo, J.A., 1996. Heritability, correlation and any of these traits would lead to indirect selection for expected responses to selection of some yield grain yield. The result is in agreement with that reported components in grain sorghum (Sorghum bicolor L. by Mohan et al. [17] and Rafiq et al. [2]. Moench). Nigerian Journal of Genetics, 11: 48-54. Days to 50% tasseling, days to 50% silking, plant 4. Lukhele, P.E., 1981. Estimation of genetic variability in height and ear height exhibited negative genotypic, sorghum population (Sorghum bicolar L. Moench), phenotypic and environmental correlation coefficients MSc. Thesis, Ahmadu Bello University, Zaria. with total grain yield suggesting that these traits were not 5. El-Shouny, K.A., O.H. El-Baguory, K.I.M. Ibrahim closely associated and therefore, may not be jointly and S.A. Al-Ahmad, 2005. Correlation and path selected. Similar work was conducted and reported by coefficient analysis in four yellow maize crosses Olakojo and Olaoye [9] that phenotypic correlation of ear under two planting dates. Arab University Journal of height and grain yield was however, negatively and Science, 13(2): 327-339. significantly correlated and suggested that the two traits 6. Tollenaar, M., A. Ahmadzadeh and E.A. Lee, 2004. were closely associated. Physiological basis of heterosis for grain yield in CONCLUSION 7. maize. Crop Science, 44: 2086-2094. Singh, R.K. and B.D. Chaudhary, 1985. Analysis in Biometrical Genetics, Kalyani Publishers, New Delhi, This study exhibited low, moderate and high India, pp: 303. estimates of broad-sense heritability within the traits 8. Wannows, A.K., H.A. Azzam and S.A. Al-Ahmad, revealing that variations were transmitted to the progeny. 2010.Genetic variances, heritability, correlation and High to moderate heritability indicated considerable path coefficient analysis in yellow maize crosses. potential for development of drought tolerance and high Agriculture and Biology Journal of North America, yielding varieties through selection of desirable plants in 1(4): 630-637. succeeding generation. The results showed that number 9. Olakojo, S.A. and G. Olaoye, 2011. Correlation and of stands per plant, anthesis silking interval, plant height, heritability estimates of maize. African Journal of ear height, weight of cobs, dehusked cobs and grain yield Plant Science, 5(6): 365-369. had high broad-sense heritability. These traits are 10. Amer, E.A. and H.E. Mosa, 2004. Gene effects important in selection programs aiming to maize yield of some plant and yield traits in four maize improvement on drought tolerance and the breeder may crosses. Minofiya Journal of Agricultural Res., consider these traits as the main selection criteria. 1(29): 181-192. The study also showed that genotypic, phenotypic 11. Yassien, H.E., 993. Genetic analysis in three yellow and environment correlations were found suitable as maize (Zea mays L.) crosses. Journal of Agriculture, models for yield improvement and selection for maize Mansoura University, 24(10): 5319-5331. 601

12. Hasib, K.M., 2005. Genetics variability, interaction 15. Duvick, D.N., 2001. Biotechnology in the 1930s; the and path analysis for panicle characters in scented development of hybrid maize. National Review of rice. Hisar Journal, 30(1): 37-39. Genetics, 2: 69-74. 13. Saleem, M.Y., J.I. Mirza and M.A. Haq, 2008. 16. Mohammadia, S., A. Prasanna and N.N. Singh, 2003. Heritability, genetic advance and heterosis in line Sequential path model for determining tester crosses of basmati rice. Journal of Agriculture, interrelationship among grain yield and related 1: 46-52. characters in maize. Crop Science, 42: 1690-1697. 14. Swati, P.G. and B.R. Ramesh, 2004. The nature and 17. Mohan, Y.C., K. Singh and N.V. Rao, 2002. Path divergence in relation to yield traits in rice coefficient analysis for oil and grain yield in maize germplasm. Annals of Agricultural Reseach, genotypes. National Journal of Plant Improvement, 25(4): 598-602. 4(1): 75-76. 602