Genetic variability, correlation and path analysis in durum wheat germplasm (Triticum durum Desf)

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1 Agricultural Research and Reviews Vol. 1(4), pp , May 2012 Available online at Wudpecker Research Journals Full Length Research Paper Genetic variability, correlation and path analysis in durum wheat germplasm (Triticum durum Desf) Dawit Tsegaye 1 *, Tadesse Dessalegn 1, Yigzaw Dessalegn 2 and Getnet Share 3 1 Bahir Dar University, Bahir Dar, Ethiopia. 2 Amhara Regional Agricultural Research Institute, Bahir Dar, Ethiopia. 3 Adet Agricultural Research Center, Adet, Ethiopia. Accepted 30 March 2012 A study was conducted at Adet Agricultural Research Center, Ethiopia, during summer Genotypic, phenotypic and environmental coefficient of variation, heritability, genetic advance, correlation coefficients and path coefficients analysis were performed for yield and its contributing parameters in 23 durum wheat genotypes. Analysis of variance for traits studied showed significant (P<0.01) differences among the genotypes. Phenotypic coefficient variation values for most characters were closer than the corresponding genotypic coefficient variation values showing little environment effect on the expression of these characters. The estimated values of broad-sense heritability were found between 11% (biological yield) and 90% (days to heading). Heritability values determined were 19%, 52%, 35%, 24%, 52%, 81%, 21%, 30%, 23% and 50% for days to maturity, number of spikelets per spike, number of kernels per spike, number of tillers per plant, spike length, thousand grain weight, harvest index, grain yield, vitreousness and flour protein content, respectively. High heritability coupled with high genetic advance as percent of mean was observed for thousand grain weight, spike length and number of spikelets per spike suggesting selection for these traits would give good response. Biological yield (r p =0.89), number of tillers per plant (r p =0.59) and thousand grain weight (r p =0.51) had high degree of positive association with grain yield. Phenotypic path analysis described that biological yield (0.679) and harvest index (0.48) have direct contribution towards grain yield. It is suggested that these characters can be considered as selection criteria in improving the grain yield of durum wheat genotypes. Key words: Correlation, genetic advance, grain yield, heritability, selection index. INTRODUCTION Durum wheat (Triticum durum Desf.) is an economically important crop and widely grown in most parts of the world and Ethiopia. It is cultivated on 10 to 11% of the world wheat areas and accounting about 8% of the total wheat production (Ganeva et al., 2011). The total area and production of durum wheat is about 20 million hectares and 30 million metric tons globally (Kahrizi et al., 2010). In Ethiopia, durum wheat is producing in several parts of the country particularly on the central highland areas. According to Central Statistics Agency CSA (2011), the average productivity of wheat in Ethiopia is *Corresponding author. d_tsegaye@yahoo.com. estimated to be 18.39q/ha, which is lower than the average world productivity (25q/ha). The development of high yielding varieties with desirable quality characteristics is the major objective in durum wheat breeding programme. Analysis of variability among the traits and the association of a particular character with other traits contributing to yield of a crop would be great importance in planning a successful breeding programme (Mary and Gopalan, 2006). Genetic variability among durum wheat genotypes can be estimated based on qualitative and quantitative traits. The choice of parents is of paramount importance in breeding programme. For effective selection, information on nature and magnitude of variation in population, association of character with yield and among themselves and the extent of

2 Tsegaye et al. 108 environmental influence on the expression of these characters are necessary (Yağdı, 2009). Heritability, degree to which the variability of a character is transmitted to the progeny, serves as a guide to the reliability of phenotypic variability in the selection programme and hence determines its success (Hamdi, 1992). However, Johnson et al. (1955) stated that heritability estimates together with genetic advance are more important than heritability alone to predict the resulting effect of selecting the best individuals. Genetic advance is also considerable importance because it indicates the magnitude of the expected genetic gain from one cycle of selection (Hamdi et al., 2003). High genetic advance coupled with high heritability estimates offers the most effective condition for selection (Larik et al., 2000). Correlation and path coefficient analysis could be used as an important tool to bring information about appropriate cause and effects relationship between yield and some yield components (Khan et al., 2003). Budak (2000) and Yağdı and Sözen (2009) reported the high and positive correlation of grain yield with number of tillers per plant, thousand grain weight, biological yield and harvest index and recommended these traits as selection criteria in durum wheat. Path coefficient analysis provides means to quantify the interrelationship of different yield components and indicate whether the influence is directly reflected in the yield or take some other path ways to produce an effect. Path analysis was used for different crops to determine the direct and indirect effects of yield components (Khaliq et al., 2004; Chaudhary and Joshi, 2005; Yağdı, 2009; Yasin and Singh, 2010). The present investigation was conducted with the objectives to determine the variability of traits, provide information on interrelationships of yield with some important yield components and to partition the observed genotypic correlations into their direct and indirect effects. MATERIALS AND METHODS Experimental materials and design The field experiment was conducted at Adet Agricultural Research Center in 2010 main cropping season. Adet is located in the northwest of Ethiopia at longitude of E and latitude of N with an altitude of 2,240 meter above sea level. The mean annual rainfall of the study area is 1,212mm and the soil type is vertisol with ph value of 6.0. Twenty one exotic durum wheat genotypes received from International Maize and Wheat Improvement Centre: CDSS02Y00201S-0Y-0M-15Y-0Y, CDSS 02Y00331S-0Y-0M-22Y-0Y, CDSS02Y00267S-0Y-0M-2Y-0Y, CDS S02Y0123 3T-0TOPB-0Y-0M-32Y-0Y, CDSS01Y01040T-0TOPB-84Y-0M-0M-0M-0Y, CD SS02Y00276S-0Y-0M-20Y-0Y, CDSS02Y00024S-0Y-0M-24Y-0Y, CDSS01B00420S-0Y-0M-27Y-0Y, CDSS02Y001160S-0Y-0M-5Y-0Y, CDS S02Y00368S-0Y-0M-17Y-0Y, CDSS02Y00221S-0Y-0M-22Y-0Y, CDSS02 Y00270S-0Y-0M-11Y-0Y, CDSS02Y00233S-0Y-0M-9Y-0Y, CDSS01 B S-0Y-0 M-14Y-0Y, CDSS02Y00524S-0Y-0M-6Y-0Y, CDSS01B00094S-7M-0M-0Y-0Y, CDSS02Y00198S-0Y-0M-32Y-0Y, CDSS02Y00062S-0Y-0 M-11Y-0Y, CDSS01B00472S-3M-0M-0Y-0Y, CDSS96B S -1Y -4Y, ICD T 14AP and two released varieties for northwest part of the country; DZ and DZ-2212 were included in the study. The trail was laid down in randomized complete block design with three replications. Each genotype was planted in six rows of 2.5m row length by 0.2m spacing between rows. The distance between replications and plots was 1.5m and 0.2m, respectively. Urea and DAP fertilizers were applied at the recommended rate of 161 and 100 kg/ha, respectively. The whole of the DAP was applied at sowing, while urea was applied in splits with the first half at sowing and the second top-dressed at full tillering stage. Sowing was done by hand drilling at a seed rate of 150kg/ha. Data collection Data on different morphological and quality characters was done on plant and plot basis. Number of spikelets per spike, number of kernels per spike, plant height (cm), number of effective tillers per plant, spike length (cm), stem dry weight (g), leaf dry weight (g) and flag leaf length (cm) were recorded on plant basis; whereas days to heading, days to maturity, thousand grain weight (g), biological yield per plot (g), harvest index per plot (%), grain yield per plot (g), grain moisture content (%), vitreousness (%), ash content (%) and flour protein content (%) were estimated on plot basis. Statistical analysis The mean values of the recorded data were subjected to analysis of variance as per Gomez and Gomez (1984). The mean squares were used to estimate genotypic and phenotypic variance according to Sharma (1998). Phenotypic coefficient of variation (PCV), environmental coefficient of variation (ECV) and genotypic coefficient of variation (GCV) were estimated according to the method suggested by Burton and De Vane (1953). Broad sense heritability was calculated as the ratio the genotypic variance to the phenotypic variance according to Falconer and Mackay (1996). Expected genetic advance as part of the mean (GA) for each character at 5% selection intensity (K=2.056) was computed using the method illustrated by Allard (1960). Expected genetic advance as percent of mean (GAM) was calculated to compare the extent of predicted advance of different traits under selection, using the formula described by Comstock and Robinson (1952). Phenotypic and genotypic correlations coefficients for different characters in possible combination were estimated using variances and covariances as the method described by Sharma (1998). The path coefficient analysis was done with nine characters using estimates of direct and indirect effects of eight characters on grain yield based on phenotypic and genotypic correlation coefficient. Days to heading, days to maturity, number of tillers per plant, thousand grain weight, biological yield, harvest index, vitreousness and flour protein content were used as predictor variables in a path analysis to estimate their direct and indirect effects on grain yield. Path analysis was carried out using GENRES3 for windows version 7.01 (GENRES3, 1994).

3 109 Agric. Res. Rev. RESULTS AND DISCUSSION Genetic variability, heritability and genetic advance Highly significant differences (P<0.01) were observed among genotypes for days to heading, number of spikelets per spike, number of kernels per spike, spike length, thousand grain weight, grain yield, vitreousness and flour protein content, and significant difference (P<0.05) was observed for vitreousness demonstrating the presence of genetic variability among genotypes (Table 1). However, days to maturity, number of tillers per plant, biological yield and harvest index were not significantly different for these genotypes. Maximum PCV was observed on vitreousness (52.85%) followed by number of tillers per plant (19.68%) and grain yield (19.62%). Genotypic coefficient of variation was also maximum for vitreousness (25.1%) and minimum for days to maturity (0.88%). The higher PCV and GCV values for most of the characters could be evidence for the existence of a wide range of variation for such characters. In general, the PCV values for most characters were closer than the corresponding GCV values showing little environment effect on the expression of these characters. Similar results were also observed by Mohammed et al. (2011) and Subhashchandra et al. (2009). Selection on a phenotypic basis may be effective for the genetic improvement of such traits. Days to heading, days to maturity and flour protein content were showed low PCV and GCV values implying the difficulty of improving these traits through simple selection. However, contradicting results were obtained from the works of Tazeen et al. (2009) and Al-Marakby et al. (1994) who found that wide range between PCV and GCV for thousand seed weight in durum wheat. High heritability values were exhibited for days to heading (90%) and thousand grain weight (81%) showed that these characters were governed by additive genes in studied durum wheat genotypes (Table 1). High heritability related to time to heading and thousand grain weight were obtained in the studies conducted previously (Safeer-ul-Hassan et al., 2004; Tazeen et al., 2009). The high heritability magnitude indicates the reliability with which the high chance of the genotype to be recognized by its phenotypic expression (Chandrababu and Sharma, 1999). Low heritability values were observed for biological yield (11%), days to maturity (19%), harvest index (21%), number of tillers per plant (24%), grain yield (30%) and number of kernels per spike (35%) suggesting selection for these characters would not be effective due to predominant effects of non additive genes in this population. Similar results of low heritability for biological yield and grain yield were recorded in durum wheat genotypes that were evaluated previously (Aycicek and Yildirim, 2006; Paul et al., 2006; Maniee et al., 2009; Kahrizi et al., 2010) and contradicting results for number of tillers per plant in the works of Ehdaie and Waines (1989) and Tazeen et al. (2009). Maximum expected genetic advance as percentage of mean was observed on vitreousness (24.6%) followed by thousand grain weight (18.83%) and spike length (16.93%) indicating the presence of additive gene effects; while the same was minimum for days to maturity (0.78%), biological yield (3.37%) and flour protein content (4.90%). Similar results were recorded in other findings (Maniee et al., 2009; Kahrizi et al., 2010). High heritability and genetic gain was recorded for thousand grain weight, spike length and number of spikelets per spike indicating selection for these characters would be more effective (Kashif et al., 2003). Correlation coefficients Phenotypic and genotypic correlation coefficients of grain yield with other characters are presented in Table 2. Grain yield had positive phenotypic correlation with number of tillers per plant (r p =0.33), thousand grain weight (r p =0.42), biological yield (r p =0.82) and harvest index (r p =0.7); and negative phenotypic association with days to heading (r p =-0.34), days to maturity (r p =-0.11) and flour protein content (r p =-0.36). Similar results were observed in the previous works (Budak, 2000; Yağdı and Sözen 2009). The negative association of grain yield with days to heading and days to maturity suggests that early heading and maturing genotypes would give high grain yield. This result is in agreement with the work of Amin et al. (1992) and Arega et al. (2007). At genotypic level, grain yield had positive correlation with number of tillers per plant (r g = 0.59), thousand grain weight (r g = 0.51) and biological yield (r g = 0.89); and negatively associated with vitreousness (r g =-0.35), flour protein content (r g =-0.78), days to heading (r g = -0.43) and days to maturity (r g = - 0.3). Similar results were observed in the previous findings (Nayeem-KA and Baig, 2003; Arega et al., 2007). The positive correlation coefficients of grain yield with most of the traits implying that improving one or more of the traits could result in high grain yield for durum wheat. These results are substantiated with those of Yağdı and Sözen (2009). The genotypic correlation coefficient values for most of the characters were higher in magnitude than the corresponding phenotypic values showing the existence of inherent association among the traits. Negative correlation of grain yield was observed with flour protein content and vitreousness at both phenotypic and genotypic levels. The results are in line with the findings of Chung et al. (2003), Eslami et al. (2005) and El-Khayat et al. (2006). Barnard et al. (2002) reported that the negative correlation which often exists between quality and yield is a further constraint in durum wheat breeding. Flour protein content is generally inversely correlated with important yield related traits such as biological yield and thousand grain weight

4 Tsegaye et al. 110 Table 1: Mean square, genotypic, environment and phenotypic coefficient of variability, heritability and expected genetic advance for different characters of 23 durum wheat genotypes. Variable Mean GCV(%) ECV(%) PCV(%) H 2 (%) GA GAM square Days to heading 16.7** Days to maturity 5.9 ns Number of spikelets per spike 5.3** Number of kernels per spike 70.4** Number of tillers per plant ns Spike length 1.3** Thousand grain weight 27.9** Biological yield ns Harvest index 34.2 ns Grain yield 10.2** Vitreousness * Flour protein content 0.47** *,** significant at 5 and 1% level of probability, respectively; ns Non significant; GCV=genotypic coefficient of variability; ECV=environmental coefficient of variability; PCV=phenotypic coefficient of variability; H 2 (%)=broad sense heritability; GA=genetic advance; GAM=expected genetic advance as percentage of mean. Table 2: Genotypic (below diagonal) and phenotypic (above diagonal) correlations of durum wheat genotypes. Characters DH DM NTP TGW BY HI VIT FPC GY Days to heading Days to maturity Number of tillers per plant Thousand grain weight Biological yield Harvest index Vitreousness Flour protein content Grain yield DH=days to heading; DM=days to maturity; NTP=number of tillers per plant; TGW= thousand grain weight; BY=biological yield; HI=harvest index; VIT= vitreousness; FPC=flour protein content; GY=grain yield. (Yağdı and Sözen, 2009). Path coefficient analysis The path coefficient analysis was done with nine characters using estimates of direct and indirect effects of eight characters on grain yield based on phenotypic and genotypic correlation coefficients (Table 3 and 4). High and positive phenotypic direct effects on grain yield were exhibited by biological yield (0.679) followed by harvest index (0.480) which supports the findings of Talebi et al. (2010) and Mohammed et al. (2011). Hence, these traits should be considered in further selection procedures for higher grain yield. Biological yield showed indirect effect on grain yield through days to maturity and thousand grain weight. Days to heading and flour protein content had negative phenotypic direct effect on grain yield. Thousands grain weight had negative phenotypic direct effect (-0.023) on grain yield though it had positive correlation (0.418) with grain yield yet. Whereas this is in contradiction to the results of Dhaliwal and Suchchain (2003) and Kashif and Khaliq (2004) who reported the positive direct effect of thousand grain weight on grain yield. This might be due to variations of influences of other characters on grain yield via thousand grain weight. Thousands grain weight had positive direct effect on grain yield through biological yield (0.294) and harvest index (0.112). Residual effect was showing that about 74% of the variability in the grain yield in durum wheat was contributed by the characters studied in path analysis. Genotypic path coefficient analysis showed that positive direct effects on grain yield were exerted by number of tillers per plant (0.341), harvest index (0.297) and vitreousness (0.259); while negative direct effect by flour protein content (-0.573), days to maturity (-0.138)

5 111 Agric. Res. Rev. Table 3: Estimates of phenotypic direct (bolded diagonal) and indirect (off-diagonal) effects of different characters on grain yield of durum wheat genotypes. Characters DH DM NTP TGW BY HI VIT FPC DH DM NTP TGW BY HI VIT FPC r p Residual effects= DH=days to heading; DM=days to maturity; NTP=number of tillers per plant; TGW= thousand grain weight; BY=biological yield; HI=harvest index; VIT= vitreousness; FPC=flour protein content; r p =phenotypic correlation coefficient of trait with grain yield Table 4: Estimates of genotypic direct (bolded diagonal) and indirect (off-diagonal) effects of different characters on grain yield of durum wheat genotypes. Characters DH DM NTP TGW BY HI VIT FPC DH DM NTP TGW BY HI VIT FPC r g Residual effects= DH=days to heading; DM=days to maturity; NTP=number of tillers per plant; TGW= thousand grain weight; BY=biological yield; HI=harvest index; VIT= vitreousness; FPC=flour protein content; r g =phenotypic correlation coefficient of trait with grain yield and thousands grain weight (-0.103) (Table 4). Similar results on the negative direct effect of protein content on grain yield was reported by Chung et al. (2003) in bread wheat. Number of tillers per plant, harvest index and biological yield showed indirect genotypic effect on grain yield through vitreousness and thousand grain weight. Thousand grain weight had low negative direct effect ( ) on grain yield though it had high positive correlation with grain yield (0.508). Genotypic path coefficient analysis had explained about 87.5% of the variability in grain yield on the basis of the studied independent characters. Conclusion The present study illustrated the existence of wide ranges of variations for most of the traits among durum wheat genotypes and opportunities of the genetic gain through selection or hybridization. Phenotypic and genotypic correlation analysis showed the positive correlation of grain yield with important agro-morphological characters. Hence, improving one or more of the traits could result in high grain yield for durum wheat. Biological yield, harvest index and number of tillers per plant had positive phenotypic and genotypic direct effect and correlation with grain yield suggesting the possibility of improving grain yield through direct selection of these traits. REFERENCES Allard RW (1960). Principles of Plant Breeding. John Wiley and Sons, New York, pp500. Al-Marakby AM, Mohamed AA, Yasein M, Tolba AM (1994). Heritability

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