Heritability, variability, genetic correlation and path analysis for quantitative traits in durum and bread wheat under dry farming conditions

TL;DR: Two field experiments were carried out during the 2009-2010 growing season at the station of Directorate of Agricultural Researches/Erbil under dry farming conditions, showing high genetic variation, heritability and genetic advance for plant height, number of spikes, 1000 grain weight, biological yield and grain yield in durum wheat.

Abstract: Two field experiments were carried out during the 2009-2010 growing season at the station of Directorate of Agricultural Researches/Erbil under dry farming conditions. The first experiment included 25 strains of durum wheat, and the second included 20 strains of bread wheat. Growth trait, yield and its components were studied, and then data are entered in the statistical genetic analysis, as well as the path coefficient analysis. The results showed high genetic variation, heritability and genetic advance for plant height, number of spikes, 1000 grain weight, biological yield and grain yield in durum wheat. While it was high in all traits in bread wheat. The grain yield was correlated genetically positive and significantly with 1000 grain weight, biological yield and harvest index in durum wheat, while showed genetically positive and significant correlation with all traits in bread wheat. The path coefficient analysis revealed that harvest index and biological yield had the maximum positive direct effects on grain yield in durum wheat reached 0.966 and 0.242, respectively. While the harvest index had the maximum positive direct effect (1.417) on grain yield in bread wheat, which was used as a criterion for the selection of superior genotypes in each group. INTRODUCTION The grain yield is a complex traits which is influenced by many factors, would be plant breeders interested to know the nature of the relationship and the kind between these traits, especially under dry farming conditions, where the water is the main limiting factor in many areas of wheat production around the world due to uneven rainfall distribution during the growing season, so it is important that characterized cultivars cultivated in these areas in the superior performance of grain yield and its components under the limited and non-limited of moisture conditions (Okuyama et al., 2004). Grain yield is the result of many developmental and physiological events that occur during the life cycle of the plant, and grain yield is determined by three main components; the number of spikes/plant, number of grain/spike and weight of grains (Poehlman, 1987). Hochman (1982) and McMaster et al. (1984) referred that the influence of each one of these components on the product of grain depends on the stage of growth that occurs due to water deficit. At elongation stage, the inadequate availability of water or rain affect on the components of grain yield by increasing the number of spikes/plant, grains/spike, and weight of grains/plant, while leading to increased weight of grains during the grain filling stage (McMaster et al.,1984). Simane et al. (1993) reported high correlation between the number of grains/spike and grain yield along the span of Recived 15/3/2011 accepted 10 / 10 /2011. Vol. ( 40 ) No.( 4 )2012 ISSN: 2224-9796 (Online) Mesoptamia J. of Agri ISSN: 1815 – 316 X (Print) 28 water stress.The wheat plants are more sensitive to water stress between the two phases (booting stage) and (grain filling) as compared to all other periods (Fisher et al., 1977 and Hochman, 1982). On the other hand, avoiding of wheat plants to water stress during the tillering and elongation stages is more important than the flowering and grain filling stages (Thompson and Chase, 1992). The breeding program for higher yield depends on the estimation of genetic variability, heritability, genetic advance and the correlations between yield and its components, but it is not sufficient to understand the importance of each one of these components in determining the grain yield (Dewey and Lu, 1959). Path analysis is a standarized partial regression coefficient that measures the direct influence of one variable upon another, it also provides a means of partitioning both direct and indirect effects and effectively measuring the relative importance of causal factors, which, helps to build an effectively selection program. Using this method (Kumar and Hunshal, 1998) observed that the harvest index, biomass yield, spikes/plant and grains/spike had most important direct effects on the grain yield. Under the water deficit conditions, but a long period of grain filling Simane et al.(1998) found high correlation between drought tolerance and spikes/m 2 and grains/spike. Yagdi (2009) found that the 1000 grain weight have high direct effect on grain yield. This research aims to estimates heritability, genetic variation and genetic correlation between different quantitative traits in a number of strains selected from durum and bread wheat, and then to identify the most important traits of a direct effect on the grain yield to be adopted as a criterion for selection. MATEREALS AND METHODES Two field experiments were carried out separated during the season 20092010 at the research station of the Directorate of Agricultural Research in the area of Ainkawa in Erbil/Kurdistan region of Iraq under the circumstances amounted to rain (315 mm) with good distribution depend on meteorological in the search site. The first experiment included 25 advanced strains of durum wheat (Triticum durum Desf.), and second included 20 advanced strains of bread wheat (Triticum aestivum L.) (Table, 1) was originally selected (on the basis of phenotypic characteristics and grain yield in the nursery of the observations had been planted during the season 2008-2009) of 57 and 67 advanced strain of two types, respectively. Each experiment was carried out according to randomized complete block design with three replicates and each experimental unit included a one row of each one of genotype. The grains were dibbled in rows (using 120 kg/ha seeding rate) keeping between row distances at 20 cm. Single row of 2.5 m length served as an experimental unit. Conducted service operations of soil and crop, and when plants reached the flowering stage, were recorded the flag leaf area of mother shoot according to formula (leaf length × width × 0.95) (Thomas, 1975), and at maturity data were recorded for plant height (cm), then harvested plants of each line as a whole to calculate biomass yield (t/ha), grain yield (t/ha), harvest index, spike Genetic statistical analysis for all the traits studied were computed, then the estimates of genetic variation, heritability and coefficints of genetic correlation between traits were done by the components of expected mean squares from Vol. ( 40 ) No.( 4 )2012 ISSN: 2224-9796 (Online) Mesoptamia J. of Agri ISSN: 1815 – 316 X (Print) 29 Table (1): Pedigree of durum and bread wheat strains used in the study. length (cm) and the components of grain yield [number of spikes/m 2 , number of grains/spike and 1000 grain weight (g)]. Durum wheat No. I g crop pop type Selection 1 114239 ICDW UM ICD86-0471-ABL-0TR-8AP-0TR-20AP-0TR 2 114251 ICDW UM ICD85-1340-ABL-6AP-0TR 3 114262 ICDW UM ICD85-0641-ABL-6AP-0TR-2AP-0TR-4AP-0TR 4 114293 ICDW UM ICD84-0322-7AP-TR-20AP-0TR 5 114300 ICDW UM ICD83-0050-4AP-14AP-TR-3AP-0TR 6 114322 ICDW UM ICD78-0064-19AP-4AP-1AP-1AP-1AP-0SH 7 114326 ICDW UM ICD-BM-ABL-413-0AP 8 114347 ICDW UM CD 523-3Y-1Y-2M-0Y 9 114385 ICDW UM 12938-5L-1AP-1AP-4AP-0AP 1