Correlation analysis and path analysis for yield and its components in hulless barley.
Barley is the fourth most important cereal crop, cultivated successfully in a wide range of climate. This crop has potentials for growing under drought and saline condition. It requires less input like, fertilizer, irrigation, and insecticides. In the world, barley is increasingly being used as cattle feed. The entire barley kernel is used as feed after grinding . Investigations of genetic variations have been conducted using the morphological traits and biochemical and genetical markers [2, 3]. Recently, integrated method of these methods named Genetical Resources Information (GRIS), a distinct and definite manner based on the overall pattern of genes relations, is used to evaluate the variations to among the genotypes  and among the traits such as yield components . Moghaddam et al.  studied 7 wheat cultivars and 53 lines, they found the remarkable variations in growth aspects and other quantitative ones and expressed that the local cultivars had the longer period of time to spike appearance had the higher height but were lower in number of grain per spike, 1000 grain weight, grain yield and harvest index than the newer ones and some of the local cultivars were similar to newer ones in yield. Belay et al.  evaluated 60 tetraploid local wheat genotypes derived from the central heights of the Ethiopia along with the one commercial variety (Boohai) for the yield and some other aspects. They stated that genetic variation among the genotypes for the mentioned aspects was very significant. Tesemma et al.  illustrated that among the breaded cultivars ready to release, there were some variations for traits such as yield components that may use to select. Synthetics wheat derived from hybridization between wheat as mother parent and corn as father parent via organ culture (embryo rescue) and increase in chromo some number using the chemical mutagen substances, are of high yielding and rather favorable quality wheat so, this work was carried out to study the important agricultural traits and variation among the genotypes to select and transfer the favorable traits and classifications to the later hybridization. Therefore evaluate the correlation between traits can help to performance for switching high performance switching. Zaefizadeh and Goliov  studied the relationship between genotype and environmental conditions (dry and normal) on the amount of chlorophyll content and the amount of superoxide Dismutase. They reported that drought-resistant cultivars had Dismutase Superoxide stress increases but in susceptible cultivars a decrease chlorophyll Superoxide Dismutase was showed. Also a good variety between the native masses of durum wheat in North-West Iran and Azerbaijan in terms of drought resistance and SRAP (Sequence related amplified polymorphism) but any Significant relationship between Coefficient of drought tolerance and SRAP was not found.
The purpose of this research is to investigate genetic diversity in barley cultivar, effective traits on yield, traits correlation with each other ,and also to select the best genotypes. That finally, which genotypes and traits improve performance in the Ardabil region is suitable.
Materials and methods
This study was carried out in Agricultural Research Station of Islamic Azad University of Ardabil located in 3 km west of Ardabil in Hasan Barooq village with a cold semi-arid climate, during the 2007 and 2008 cropping year with 22 barley genotypes. Experimental design was a randomized complete block with three replication. According to 10-year statistics of meteorological station, annual precipitation is 310 mm and mean annual temperature is 8.6[degrees]C. Mean minimum temperature is -22[degrees]C (Dec-Jan) and mean maximum temperature is +30[degrees]C (Jul-Aug). The altitude is 1350 m from sea-level. To determine the physical and chemical characteristics of the soil, it was sampled from the depths of 0-30 and 30-60 cm before soil preparation (Table 1).
Every line in 5 rows and 20 cm intervals and 150 cm in width were planted. Immediately after planting the field was irrigated to soil moisture profiles in root development and saturated and identical for all treatments in addition to the germination easily is done. Irrigation was done with leaking method. After harvest to evaluate the factors affecting the performance traits, plant height, total tiller number , fertile tillers, length of main spike, days to heading, days to maturity, chaff Weight, harvest index, 1000 grain weight, number of seeds per main spike and yield were measured. For analyzing data , software MATATC, SPSS 10 was used and PATH2 Path analysis for performance based on characters remaining stepwise multivariate regression method was performed. Resulted data were subjected to analysis by SPSS procedure and means of treatments were compared using Duncan's multiple range test in 0.01 percent. Then, resulted means were classified into two groups of high and low yielding genotypes by means of cluster method.
Results and discussion
Result of analysis of variance (Table 3) indicated that there were significant differences among the genotypes in the majority of traits. This illustrates the high potential of these genotypes to use them as the genetically source for breeding purposes. Since the traits were slightly and environment also was significant impact convention, there this difference was not unexpected .
The results of correlation (Table 3) showed that positive significant between total tillers with fertile tillers, chaff weight and 1000 grain weight. Means with increasing total tillers these traits also increases. Khayatnezhad et al.  reported negative correlation between harvest index and plant height and Mohammadi  also reported negative correlation between plant height and yield reported.
Also positive correlation between fertile tillers with chaff weight, days to heading with days to maturity and 1000 grain weight, days to maturity with 1000 grain weight, plant height with number of seeds per main spike, and 1000 grain weight with harvest index was obtained. Also the negative correlation obtained between days to heading with plant height and plant heights with 1000 grain weight and harvest index. Khayatnezhad et al.  reported negative correlation between harvest index and plant height and Mohammadi  also detected negative correlation between plant height and yield reported. Results also showed that genotypes with higher plant height have better performance in terms of stress than other genotypes. Khayatnezhad et al.  reported negative correlation between harvest index and plant height and Mohammadi  also found negative correlation between plant height and yield. Number of grains per main spike is one of the most important factors for selection in cereal yield.
In studies related to the performance characteristics of methods for causality effects on yield traits and Interface between the traits used. With the help of this method can be correlation between yield and its components were analyzed and the direct and indirect effects identified [1,2]. Path analysis for the traits is in Table 4.
[FIGURE 1 OMITTED]
The result showed that most direct positive effect on yield by number of seeds per main spike and most negative direct effect were for Days to heading. Also most indirect effects by fertile tillers on chaff Weight were applied. It seems that barley than wheat is a lower number of tillers. So Therefore, to achieve greater performance through genotypes fertile tillers can be used . Genotypes were divided into different groups according to genotype traits (Fig. 1). So we can use fertile tiller in barley genotypes to increase that yields. This test is suggested for different cultivars and in different circumstances is done.
[1.] Nessa, D., H. Islam, S.H. Mirza and M. Azimuddin, 1998. Genetic variability, correlation and path analysis in barley (Hordeum vaulgare L). Bangladesh J. Bot., 32: 181-185.
[2.] Moghaddam, M., B. Ehdie and J.G. Waines, 1997. Genetic variation and interrelationships of agronomic characters in landraces of bread wheat from southeastern Iran. Euphytica, 95: 361-369.
[3.] Ochi-e-Ardabili, M., M. Zaefizadeh, S. Jamaatie-Somarin, M. Hassanzadeh and N. Hazrati, 2009. Study of genetically variation in synthetic genotypes of wheat resulted from hybridizing between wheat and corn plants. Research journal of biological sciences, 4: 990-993.
[4.] Manifesto, M.M., A.R. Schlatter, H.E. Hopp, E.Y. Suarez and J. Dubcovsky, 2001. Quantitative Evaluation of Genetic Diversity in Wheat Germplasm Using Molecular Markers. Crop Breeding Genetics and Cytology, 41: 682690.
[5.] Pecetti, L. and A.B. Damania, 1996. Geographic variation in tetraploid wheat (Triticum turgidum spp. turgidum convar durum) landraces from two provinces in Ethiopia. Genetic Resources and Crop Evolution, 43: 395-407.
[6.] Belay, G.T., H. Tesemma, C. Backer and A. marker, 1993. Variation and interrelationships of agronomic traits in Ethiopian tetraploid wheat landraces. Euphytica, 77: 181-188.
[7.] Tesemma, T., S. Tsegaye, G. Belay, E. Bechere and D. Mitiku, 1998. Stability of performance of tetraploid wheat landraces in the Ethiopian highland. Euphytica, 10: 301-308.
[8.] Zaefizadeh, M., R. Goliov, 2009. The Effect of the Interaction between Genotypes and Drought Stress on the Superoxide Dismutase and Chlorophyll Content in Durum Wheat Landraces. Turk J Boil, 33: 1-7.
[9.] Khayatnezhad, M., M. Zaefizadeh, R. Gholamin and S. Jamaati-e somarein, 2010. Study of Genetic Diversity and Path Analysis for Yield in Durum Wheat Genotypes under Water and Dry Conditions. World Appl Sci J., 9: 655-665.
[10.] Mohammadi, H. and M. Khodambashi-e-emami, 1997. Estimation of genetic parameters for yield and yield components of wheat diallel cross method. Journal of Agricultural Research, 4: 12-15.
Mohammad Zaefizadeh, Islamic Azad University of Ardabil Branch. E-mail: firstname.lastname@example.org
(1) Mohammad Zaefizadeh, (1) Marefat Ghasemi, Jafar Azimi, (2) Majid Khayatnezhad and (1) Babak Ahadzadeh
(1) Islamic Azad University,-Ardabil Branch. Ardabil., Iran
(2) Young Researchers Club, Islamic Azad University, Ardabil Branch, Ardabil, Iran
Mohammad Zaefizadeh, Marefat Ghasemi, Jafar Azimi, Majid Khayatnezhad and Babak Ahadzadeh; Correlation Analysis and Path Analysis for Yield and its Components in Hulless Barley
Table 1: Soil analysis Soil texture Absorbent Soil Potassium type Sand Silt Clay (ppm) Clay Loam 31 41 28 460 Clay 40 36 24 290 Absorbent Total Organic Neutral-reacting Soil Phosphorus nitrogen carbon material type (ppm) (percent) (percent) (percent) Clay Loam 4/8 0/103 0/97 4/8 Clay 2 0/056 0/47 7 Total Electrical Soil acidity conductivity Depth type (PH) (ds /m) Saturation (cm) Clay Loam 7/8 2/66 48 0-30 Clay 8/2 2/4 45 30-60 Table 2: Results of analysis of variance for studied traits MS Main spike Total Fertile S.O.V df length tillers tillers Replication 2 1.00 * 0.46 ** 0.26 ** Genotype 21 1.87 ** 1.33 ** 1.36 ** error 42 0.365 0.095 0.054 MS Days to Days to plant chaff S.O.V heading maturity height Weight Replication 622.4 ** 794.3 ** 2.013 13.405 Genotype 24.56 ** 45.08 ** 278.8 ** 20.74 error 5.86 13.15 6.93 14.16 MS 1000 Number of grain seeds per harvest S.O.V weight main spike index yield Replication 9.87 * 11.96 * 1.01 0.013 Genotype 32.32 ** 114.75 ** 29.41 ** 0.29 ** error 2.78 6.29 2.17 0.076 ** and * significant at the 0.01 and 0.05 levels Table 3: Correlation between traits Main spike Total Fertile Days to S.O.V length tillers tillers heading Main spike length 1 0.33 0.31 0.057 Total tillers 1 0.952 ** 0.189 Fertile tillers 1 0.224 Days to heading 1 Days to maturity plant height chaff Weight 1000 grain weight Number of seeds per main spike harvest index yield 1000 Days to plant chaff grain S.O.V maturity height Weight weight Main spike length 0.052 0.143 0.273 0.149 Total tillers 0.214 -0.043 0.592 ** 0.429 * Fertile tillers 0.234 -0.041 0.622 ** 0.419 Days to heading 0.903** -0.477 * 0.050 0.610 ** Days to maturity 1 -0.312 0.022 0.0527 * plant height 1 0.027 -0.761 ** chaff Weight 1 0.088 1000 grain weight 1 Number of seeds per main spike harvest index yield Number of seeds per harvest S.O.V main spike index yield Main spike length 0.156 -0.303 0.168 Total tillers -0.371 -0.213 0.282 Fertile tillers -0.371 -0.195 0.380 Days to heading -0.350 0.416 0.206 Days to maturity -0.285 0.319 0.343 plant height 0.620 ** -0.432 * 0.158 chaff Weight -0.175 -0.399 0.027 1000 grain weight -0.501 * 0.452 * 0.163 Number of seeds 1 -0.169 0.041 per main spike harvest index 1 0.024 yield 1 Table 4: Partitioning of correlation coefficient analysis direct and indirect effects for mean yield Indirect effect through Main Direct spike Total Fertile Trait name effect length tillers tillers Main spike length 0.048 1 -0.375 0.488 Total tillers -1.082 0.015 1 1.499 Fertile tillers 1.57 0.014 -1.03 1 Days to heading -0.536 0.002 -0.195 0.346 Days to maturity 0.073 0.002 -0.227 0.362 plant height 0.076 0.006 0.046 -0.065 chaff Weight -0.277 0.013 -0.638 0.979 1000 grain weight 0.095 -0.006 -0.455 0.649 Number of seeds 0.247 0.007 0.342 -0.585 per main spike harvest index 0.018 -0.015 0.23 -0.3 Indirect effect through Days to Days to plant chaff Trait name heading maturity height Weight Main spike length -0.031 0.038 0.01 -0.075 Total tillers -0.097 0.153 -0.004 -0.164 Fertile tillers -0.118 0.168 -0.004 -0.173 Days to heading 1 0.657 -0.037 -0.014 Days to maturity -0.482 1 -0.024 -0.007 plant height 0.255 -0.229 1 -0.008 chaff Weight -0.027 0.016 0.002 1 1000 grain weight -0.327 0.38 -0.059 -0.025 Number of seeds 0.187 -0.205 0.047 0.048 per main spike harvest index -0.223 0.223 -0.034 0.11 Indirect effect through 1000 Number of harvest grain seeds per index Trait name weight main spike index Main spike length 0.013 0.037 -0.006 Total tillers 0.039 -0.079 -0.004 Fertile tillers 0.039 -0.09 -0.004 Days to heading 0.057 -0.087 0.007 Days to maturity 0.049 -0.07 0.005 plant height -0.073 0.153 -0.008 chaff Weight 0.008 -0.044 -0.008 1000 grain weight 1 -0.135 0.008 Number of seeds -0.048 1 -0.004 per main spike harvest index 0.043 -0.042 1
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|Title Annotation:||Original Article|
|Author:||Zaefizadeh, Mohammad; Ghasemi, Marefat; Azimi, Jafar; Khayatnezhad, Majid; Ahadzadeh, Babak|
|Publication:||Advances in Environmental Biology|
|Date:||Jan 1, 2011|
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