Fitociencia

 

Identification of breeding potential for grain yield and its component traits of common wheat varieties in the east Mediterranean

 

Identificación del potencial de mejoramiento para rendimiento de granos y sus caracteres componentes de variedades comunes de trigo en el este del Mediterráneo

 

Okan Sener*

 

* Mustafa Kemal University, Faculty of Agriculture, Department of Field Crop, 31040 Antakya–Turkey. *Autor responsable: (osener9@gmail.com)

 

Received: April, 2008.
Approved: February, 2009.

 

ABSTRACT

Six experimental lines and one commercial wheat (Triticum aestivum L.) cultivar from diverse backgrounds were intercrossed in a half diallel and analyzed to determine suitable parents for hybrids combinations and promising hybrid combinations. The experiment was established in typical Mediterranean environment, using a randomized complete block design with three replications. General combining ability (GCA) and specific combining ability (SCA) effects were identified for spike length, spikelets per spike, kernel number per spike, kernel weight per spike, thousand kernel weight, and grain yield per plant. Spike length was determined by additive gene effect, though number of spikelets in spike was determined by non–additive genes. Number of kernels per spike, thousand kernel weight and yield per plant were affected by both additive and dominant genes. However, additive genes were more effective on number of kernels per spike and thousand kernel weight than that of dominant genes. Dominant genes were more effective on grain yield per plant than that of additive genes. Of the measured yield components, only spikelets per spike were significantly correlated with grain yield. Based on the path analysis, it was found that spikelets per spike, kernel number per spike and kernel weight per spike had the greatest positive direct effect on grain yield. It was determined that P2 (F6 0314–76/MRL), P4 (HP 1744) and P5 (SERI–82// SHI#4414/CROW "S") were the best combiner for grain yield per plant. The analysis of the results showed that the best specific crosses for grain yield per plant were Pl(GENÇ–99) XP2, P1XP3(PFAU/MILAN) and P5XP7(ATTILA/3/HUI/CARC//CHEN/CHTO/4/ATTILA). They these crosses were the most promising combinations for future breeding.

Key words: Triticum aestivum L., combining ability, path analysis, half–diallel analysis.

 

RESUMEN

Seis líneas experimentales y una variedad comercial de trigo (Tricunt aestivum. L.) provenientes de diversos orígenes, se cruzaron en un medio dialelo y se analizaron para establecer los progenitores adecuados para combinaciones de híbridos así como combinaciones de híbridos prometedoras. El experimento se estableció en un ambiente típicamente mediterráneo, usando un diseño de bloques completos al azar con tres réplicas. Se identificaron los efectos de la aptitud combinatoria general (ACG) y la aptitud combinatoria específica (ACE) para longitud de la espiga, espiguillas por espiga, número de granos por espiga, peso de granos por espiga, peso de mil granos, y rendimiento de granos por planta. La longitud de la espiga se determinó por efecto de genes aditivos, aunque el número de espiguillas en la espiga se determinó por genes no aditivos. El número de granos por espiga, el peso de mil granos y el rendimiento por planta fueron afectados tanto por genes aditivos como dominantes. Sin embargo, los genes aditivos fueron más efectivos para el número de granos por espiga y el peso de mil granos, que los genes dominantes. Los genes dominantes fueron más efectivos para el rendimiento de granos por planta que los genes aditivos. De los componentes del rendimiento estudiados, sólo espiguillas por espiga estuvo significativamente correlacionado con el rendimiento de granos. Con base en el análisis de trayectoria, se encontró que espiguillas por espiga, número de granos por espiga y peso de granos por espiga tuvieron el efecto positivo directo más alto sobre el rendimiento de granos. Se determinó que P2 (F6 0314–76/MRL), P4 (HP 1744) y P5 (SERI–82//SHI#4414/CROW "S") fueron los mejores combinadores para el rendimiento de granos por planta. El análisis de los resultados muestran que las mejores cruzas específicas para el rendimiento de granos por planta fueron P1(GENÇ–99)XP2, P1XP3(PFAU/MILAN) y P5XP7(ATTILA/3/HUI/CARC//CHEN/CHTO/4/ATTILA). Estas cruzas fueron las combinaciones más pto–metedoías pata el mejotamiento futuro.

Palabras clave: Triticum aestivum L., aptitud combinatoria, análisis de trayectoria, análisis de medio dialelo.

 

INTRODUCTION

The Mediterranean climate is found in five regions: the coasts of the Mediterranean Sea, the center and southern coasts of California and northern coast of México, central Chile, the southern tip of Southern Africa, and southwest Australia. Wheat (Triticum aestivum L.) is one of the major components of the agro–ecosystem in the Mediterranean type of climate. Around 10 % of wheat world production, 627 million t, comes from the Mediterranean type of environment (Acevedo et al, 1999). Yield improvement in such environments is highly difficult due to the variation in precipitation. Therefore, selecting new wheat varieties under the best criteria would be crucial for wheat improvement. Selecting best parents and best combinations have been two major steps in breeding self pollinated crops for early generation selection in order to avoid time and labor expenses (Whitehouse et al, 1958). Diallel analysis is a useful method to select suitable parents with their combing abilities in crossings and to establish genetic structure of hybrid population as early as the Fl generation. Without diallel analysis, precision is rarely obtained in selecting suitable parents with their actual value. Although the natural gene pool for wheat breeding has been decreasing over the years, there is still the possibility of broadening the genetic variation for yield and yield components for diverse environmental conditions. Griffing's (1956) combining ability analysis is one of the most useful techniques for selecting parents with respect to performance of the hybrids. This analysis has been exploited for wheat breeding for agronomic traits (Javaid et al, 2001; Joshi et al, 2004; Chowdhary et al, 2007) as well as disease resistance (Hakizimana etal.,2004).

In subtropical environments Chowdhary et al (2007) and Hakim et al (2007) found significant general and specific combining ability (GCA and SCA) for some agronomic traits including grain yield in wheat diallel studies that. They noticed preponderance of additive gene action for most of the traits. However, little is known about the combining abilities of cultivars in the Mediterranean environment.

The objectives of this study were to estimate the general and specific combining ability effects for yield components, as well as to determine the gene action for morphological and yield–related traits. We used path analysis to determine which yield components has the greatest effect on grain yield, and suggested promising parents and hybrid combinations to improve yield of common wheat.

 

MATERIALS AND METHODS

Seven common wheat genotypes, widely varied in terms of their morphological characteristics and their adaptation to growing in the Mediterranean, were selected from the field trials run by Cukurova University, Adana, Turkey. Names or crosses of the parents are presented in Table 1.

Parents were non–reciprocally crossed during 2001 and 2002 growing seasons at the research field of Cukurova University. About 10 spikes were used for each of the 21 cross combinations and approximately 100–150 hybrid seeds were obtained. During 2002 and 2003 growing seasons, hybrid F₁ seeds with their parents were planted in the plots, with 25 cm inter–row spacing, 10 cm intra–row spacing and 100 cm row length, in net cages at the research field of Mustafa Kemal University, Hatay. Randomized complete block design (RCBD) was used with three replications. The soil of the experimental site, developed from alluvial deposits of river terraces, is typical for the eastern Mediterranean region of Turkey and is classified as Chromoxeret by USDA Soil Taxonomy (1998) and as Vertisol by FAO/UNESCO (1974). This soil shows relatively high clay content with the predominant clay minerals smectite and kaolinite. The soil of the experimental plots was a clay silt loam with pH 7.6, 1.7 % organic matter, 0.13 % total N, and water holding capacity of 0.34 cm³ . Based on soil analysis and local recommendations, fertilizer was applied prior to planting at a rate of 160, 80 and 80 kg ha^–1N, P and K. Total precipitation was 660.6 mm during the growing season. Average temperature was 12.6 °C at cropping period (November–June), while the mean relative humidity was around 63.5 %. To avoid side effects, one seed of awnless cv. Gemini was planted in the front rows. For each plot, measurements were done for all plants to assess spike length (cm), spikelets per spike, kernel number per spike, kernel weight per spike (g), thousand kernel weight (g), and grain yield per plant (g). Evaluations were performed according to Griffing (1956) Method 2, Model 1 and analyses were done using the software developed by Burrow and Coors (1994). The path coefficient analyses were conducted for all of the measured traits as described by Kang (1992).

 

RESULTS AND DISCUSSION

Mean phenotypic values obtained from seven common wheat genotypes and their half–diallel F₁ generations are shown in Table 2. Analysis of variance showing mean squares for combining ability for different traits in common wheat is shown in Table 3.

All traits, except spikelets per spike and grain yield per plant, had the GCA/SCA ratio higher than one, meaning that additive gene action was more effective than non–additive (Table 3). Similar findings were previously for GCA for spike length in different environments (Li et al, 1991; Ul Hag and Laila, 1991) and other studies revealed that non additive gene action was also significant (Hasnain et al, 2006; Chowdhary et al, 2007). However, Iqbal et al (1991) reported significant epistatic gene action for this trait.

In the present study there was a significant SCA for spikelets per spike suggesting that non–additive gene action affects the trait, although Kashif and Khaliq (2003) found that additive and non–additive gene action were significant and Rasal et al (1991) reported only additive gene action for spikelets per spike.

Significant GCA and SCA for kernel number per spike indicated both additive and non–additive gene action and the present study corroborates the results ofjavaid etal (2001) and Joshi etal (2004), who also found GCA/SCA>1, suggesting that additive gene action was more important for kernel number per spike than that of dominant one. However, Li et al. (1991) and Rasal et al (1991) reported additive gene action, while Khamandosh et al. (1991) reported non–additive gene action. Additionally, Bebyakin and Starichkova (1992) reported that epistatic gene action was also important for kernel number per spike while Jedynski (1988) suggested the existence of non–allellic interaction. Although any significant values for either GCA or SCA for kernel weight per spike were found in the present study, Li et al. (1991) found higher additive genetic variance while Lone and Zalewski (1991) observed over–dominance.

Thousand kernel weight was determined by both additive and dominant gene actions. For thousand kernel weight, additive and dominant gene action were significant, similar to previous studies (Javaid et al, 2001; Joshi et al, 2004). However, Li et al. (1991) reported only additive gene action for this trait. Other studies concluded that thousand kernel weight was determined by additive, dominant and epistatic (Bebyakin and Starichkova, 1992), as well as non–allelic interactions (Jedynski, 1988). Javaid et al. (2001) also reported that the effect of additive gene action was higher than that of the dominant one for thousand kernel weight since the GCA/SCA ratio is bigger than one.

In the present study parents and hybrids for grain yield per plant were analyzed and there was significant additive and non–additive gene action, and non additive gene action seemed to be more effective. Similar results were reported for other cultivars, where additive (Sharma et al, 1988) and dominant genetic variances were significant (Javaid et al., 2001; Joshi et al., 2004). Khamandosh et al. (1991) reported, however, that non–additive genes play role in determining the grain yield per plant.

After half diallel analysis, the effects of GCA and SCA on agronomic traits of seven common wheat genotypes and their combinations are shown in Table 4. A genotype could be considered as a suitable parent for improving a trait if it has the highest phenotypic value and GCA effect. For this reason, P2 for spike length and kernel weight per spike, all of the others parents except for PI and P4 for spikelets per spike,P2 and P5 for kernel number per spike, P2 and P7 for thousand kernel weight, P2, P4 and P5 for grain yield per plant could be suggested as suitable parents.

The lowest GCA effects for spike length, kernel weight per spike, thousand kernel weight were obtained in P3 and spikelets per spike, kernel number per spike, grain yield per plant in PI (Table 4). These parents also generally had the lowest phenotypic values (Table 2).

The highest SCA values were observed for spike length in P5XP6, for spikelets per spike, kernel number per spike, thousand kernel weight in P5XP7, for kernel weight per spike in P1XP4 and P5XP7 (Table 4). The highest SCA value was also observed for grain yield per plant in P1XP2 (Table 4). However, P1XP3, P1XP6, P2XP4 and P5XP7 for spike length, P1XP3, P2XP5, P3XP6 and P5XP6 for spikelets per spike, P1XP2, P1XP4, P2XP7, P3XP6 and P5XP6 for kernel number per spike, P1XP7, P2XP4, P3XP4 and P3XP6 for kernel weight per spike, P1XP7 and P3XP4 for thousand kernel weight, P1XP3, P2XP7, P5XP6 and P5XP7 hybrids for grain yield per plant, also had high SCA values (Table 4). The mean phenotypic values found were also high for these hybrid combinations (Table 2). Based on mid parent value (data not shown) and higher SCA effects, P1XP3, P1XP6, P2XP4, P5XP6 and P5XP7 for spike length, P2XP5, P5XP6 and P5XP7 for spikelets per spike, P2XP7, P3XP6, P5XP6 and P5XP7 for kernel number per spike, P1XP4, P1XP7, P2XP4, P3XP6 and P5XP7 for kernel weight per spike, P1XP7 and P5XP7 for thousand kernel weight, P1XP2, P1XP3 and P5XP7 hybrids for grain yield per plant could be assigned for promising crosses. The lowest SCA values were obtained for spike length in P3XP6, for spikelets per spike in P3XP5, for kernel number per spike in P1XP3, for kernel weight per spike and thousand kernel weight in P4XP7, for grain yield per plant in P1XP7 hybrids (Table 4), which also had the lowest mean phenotypic values (Table 2). A hybrid combination could be considered if it has the highest phenotypic value and SCA effect.

Correlation and path analysis data showed that all of the yield components revealed a positive association with grain yield (Table 5). However, the positive interaction was significant for spikelets per spike.

Among the yield components, spikelets per spike showed the greatest positive direct effect on grain yield followed by kernel number per spike and thousand kernel weight (Table 5). Among these traits, kernel number per spike and spikelets per spike are more accurate as an indirect selection criterion for determining the high yielding genotypes in common wheat due to its strong positive correlation with grain yield, large positive direct effect on yield, and small negative indirect effect on yield through spike weight. Kernel number per spike has been also reported as a promising trait in increasing grain yield in wheat, especially under drought stress conditions by Deni et al. (2000) and Garcia del Moral et al. (2003).

 

CONCLUSIONS

General and specific combining ability effects differed significantly for most of the traits, indicating that both additive and non–additive genetic effects played a role in the heritability of these traits. It was determined that P2 was the best combiner for spike length and kernel weight per spike; all of the others parents except for PI and P4 were the best combiner for spikelets per spike; P2 and P5 were the best combiner for kernel number per spike; P2 and P7 were the best combiner for thousand kernel weight; and P2, P4 and P5 were the best combiner for grain yield per plant. The promising crosses were: P1XP3, P1XP6, P2XP4 P5XP6 and P5XP7 for spike length; P2XP5, P5XP6 and P5XP7 for spikelets per spike; P2XP7, P3XP6, P5XP6 and P5XP7 for kernel number per spike; P1XP4, P1XP7, P2XP4, P3XP6 and P5XP7 for kernel weight per spike; P1XP7 and P5XP7 for thousand kernel weight; P1XP2, P1XP3; and P5XP7 for grain yield per plant. These hybrids may be used in breeding program to get better hybrid combination for wheat lines and to develop high yielding wheat cultivars for the Mediterranean region. Correlation and path analyses data indicated that spikelets per spike was the most promising plant characteristic which may contribute to seed yield increase in common wheat in a typical eastern Mediterranean climate.

 

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