Genotypes and environment interaction and cluster analysis for fresh forage yield Sorghum bicolor (L.) Moench

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1 International Journal Farming and Allied Sciences Available online at 04 IJFAS Journal-04--/45-4/ 0 November, 04 ISSN IJFAS Genotypes and environment interaction and cluster analysis for fresh forage yield Sorghum bicolor (L.) Moench Mohamad Taghi Feyzbakhsh, Hassan Mokhtarpour, Arezoo Pourfarid * and Fatemeh sheikh. Agricultural Research Center and Natural Resources Golestan Province, Iran. Baharan high Educational institute, Iran, Golestan, Gorgan Corresponding author: Arezoo Pourfarid ABSTRACT: The objective this study was to determine the interaction effect between genotype and environment (G E) and the stability forage sorghum [Sorghum bicolor (L.) Moench] cultivars. In order to evaluate 5 advanced lines Sorghum bicolor (L.) Moench., an experiment was carried out in a randomized complete block design with four replications at Gorgan Agricultural Research Station for three years, from 007 to 00. Combined analysis variance showed significant difference (P<0.0) for fresh forage yield among cultivars and cultivar year interaction. In order to study the response cultivar to different years and determine stable cultivars, stability analysis was done using parametric and nonparametric methods. Results the environmental variance and coefficient variance showed that KFS4 and KFS had the highest stability in different years. Based on non-parametric methods, i. e average, variance and standard deviation rank, cultivars KFS, KFS6 and KFS7 had the highest stability. Results variance and stability and cluster analysis showed that KFS KFS4, KFS0 and KFS had the highest stability in different years. Based on these findings, the use these cultivars is recommended in breeding programs for increasing stability. Keywords: Sorghum, Combine Analysis, Genotype Environment Interaction, Cluster Analysis INTRODUCTION Sorghum bicolor L. Moench is a plant in the Graminae family with numerous consumptions such as forage crop (House, 85). Sorghum is a native plant Africa and South Asia (House, 85). Sorghum is called as camel crops and due to the high tolerance water and temperature stress and also high photosynthesis efficiency; it is considered an important plant in arid and semi arid regions (Anagholi, 000). After wheat, rice, corn and barley, sorghum is the fifth important cereal and is cultivated yearly in 4 million hectares in countries. Grain sorghum constitutes 0 percent the sorghum while the other 0 percent belong to other types sorghums (Zamanian, 6). Although sorghum is adapted to arid and semi arid regions, the findings other studies indicate that this plant can produce suitable yield in desire conditions. Besides yield, one the most important aspects assessing the advanced lines is some factors such as resistance to diseases and insects. The interaction between genotype and environment is one the complicated breeding programs to produce productive and adaptive genotypes and the interaction between genotypes and environments is due to differences between genotypes in different environments or shifting genotypes relative ranking. Stable yield in different locations or years is considered as stability (Durte, 5). The GE interaction usually occurs in the following forms: to 4 years in one location, one year in to 4 locations, and several years in several

2 Intl J Farm & Alli Sci. Vol., (): 45-4, 04 locations. Researchers usually ignore GE interaction especially in yield comparison experiments and the basis genotypes selection is just based on yield means. Thus, breeding and agronomy experts need an applied method that could use GE interaction (Bachiredy,, House, 5, Moghadam, 6). Numerous methods are suggested for the analysis genotype environment interaction and the estimation stability. One these methods is based on different statistics (Kaya and Taner, 00) and all these methods can be divided to parameter and nonparameters groups (Hayward, ). Yet, the use these complicated methods is not easy and statistical stware is required. One the methods to decrease the interaction between genotypes and environments is the selection stable genotypes. Stable genotypes are the ones which have less interaction with environment. Selection stable genotypes will be successful when stability is considered as a genitival trait (Farshadfar, 8). In spite different methods, all breeding experts believe in high stability in yield, but there is no unit definition for stability or in methods that determine it (Kang, 5). Mekbib (004) selected stable and productive bean genotypes after doing stability analysis and comparing different methods, he concluded that inter-location variance standards, Rick equivalence and stability equivalence lead to selecting stable and productive genotypes. He pointed that equivalence method and stability variance can be proper standards in selecting stable and productive bean genotypes or other cereals (Lin, 86). Kang and Fam () also studied the relation between corn yield and yield stability and found that there is a high correlation between grain yield and yield stability(r=0.7). They also found that Rank method could be an ideal method to determine stable genotypes (). Research on the relationship between grain ripening period and yield stability shows early ripening genotypes have higher yield stability. The objective this study is selecting and introducing stable varieties with high yield sorghum cultivars. Determination grain yield, grain oil and grain protein stability 46 sorghum hybrids and lines in 5 areas showed that the varieties with high stability rank could produce high yield in unfavorable weather condition (Mohammad, 8). MATERIALS AND METHODS There were three uncultivated rows between lines in each replication. When plant height reached to 40 cm, nitrogen fertilizer was added to soil just next to the lines and after each harvest 00 kg/ha urea fertilizer was added to soil. The irrigation was leakage and irrigation periods were 7-0 days. Harvesting started when plant height reached to.7-.8 meters. Plants were cut from 0 cm above soil surface. Two middle lines with 5 cm elimination each side were harvested and other side lines were considered as border and after harvesting were eliminated. The collected data were analyzed. After years, variation was confirmed with Bartlet test, and then composed analysis was used. In order to evaluate stability variance, parametric variance method, environmental variance, stability variance (Shokla) and none-parametric ranking methods were used. Based on environmental variance method, the cultivar with less variance in different environments is more stable and in case that it produces good yield will be introduced. Francis and Kanenberg (87) stated that yield distribution the genotypes with higher means might have higher variances. For instance, in Poason's distribution when mean increases, variance will increase, too. So they suggested changing coefficient (or c.v.). In CV., environmental variance is divided to genotypes means and expresses as CV. In fact, CV. cuts the relation between variance and mean. If Si is bigger, Xi's greatness will neutralize that. In this method, varieties with less CV. are more stable (Kang, 5). For noneparametric stability standards, several methods have been suggested and in all them, varieties will rank and stable genotypes are the ones which in all environments have the same rank. These methods are used in cases that trait distribution or the studied character in the society is not defined or when parameter or standard for evaluation cannot be used (Mekbib, 004). In order to analyze stability with none-parametric methods, first genotypes means for each year was calculated. For this purpose genotypes with the most yields are considered as first rank and the least considered as th. Then, for each cultivar, mean, variance and standard deviation were determined. So, genotypes with low rank in years had the most yields. If rank variance a cultivar is low, then the cultivar is stable. Shokla (7) suggested genotype variance estimation in different environments based on the remaining two-side GE interaction classification and called it stability variance and it was calculated from the following formula (Mohammad, 8). P: genotypes number i W i p p q W i SSGE P P q y ij yio yoj yoo j 46

3 Intl J Farm & Alli Sci. Vol., (): 45-4, 04 Q= environment numbers Finally the evaluated lines were classified based on the stability parameters cluster analysis, based on Ward method on the basis second power Euclid distance with SPSS stware 6 th version RESULTS AND DISCUSSION Combined variance analysis was done considering year randomization using Bartet test after monotonous variances. The results combined variance analysis indicated that the effect year on the traits under investigation was significant (p<0.0) (Table). There was significant difference between evaluated genotypes and the interaction between year and genotype for forage yield was significant (Table ). Since, the interaction between year and genotype was significant, grain yield stability analysis was necessary. The significant interaction year x genotype shows that one genotype in different year did not have the same yield and this is a problem to choose ideal genotypes and introduction each genotype for an environment or year is not possible (Acikgo, 00). To analyze stability, parametric methods, environment variance, Coefficient Variability, Shokla stability parameter and non-parameter rank method were used (Table). The results environmental variance and so on KFS, KFS0, KFS are the most stable genotypes. Also, according to non-parametric stability analysis, kfs6 with rank average, had the least grain yield mean and also had the least variance and standard deviation which show that this genotype had good stability in years and also had high yield(0745.) so it can be consider as stable productive genotype. After that KFS7 and KFS had the least ranks, variances and standard deviations which show that these genotypes are stable (Table ). Ranking method is considered a suitable method to select stable productive genotypes (Mekbib, 004, House, 85). Amount Shokla stability variance introduces KFS as the most stable variety and then KFS0, KFS and KFS4 are the most stable ones (Table). The results the stability analysis from environmental variance method, C.V. and Shokla stability variance had some overlaps. According to results these methods, we can say that KF0, KFS, KFS and KFS4 are the most stable genotypes among all evaluated ones (Table ). It can be seen that the results ranking method had no compatibility with three other methods, however according to the nature this method, it is not unexpected. In order to interpret the interaction between genotypes and environment and make the best decision about genotypes, all the parameters should be considered precisely. The best solution is using stability parameters and Cluster analysis together. According to Shokla stability variance (Figure ), environmental changing variance (Figure ), rank and genotype yield (Figure ) and by analyzing with Cluster method, genotypes have been classified and their dandroghraph were drawn. Table. Variance analyze for some agricultural traits forage sorghum in Gorgan ( ) (s.o.v) Year E Variety Year*variety E CV df Dry yield ** ** ** و ns= respectively non-significant and significant in and 5% probability level 47

4 Intl J Farm & Alli Sci. Vol., (): 45-4, 04 Table. Different stability parameter amounts for different fresh forage (kg/ha) sorghum cultivars Genotype KFS KFS KFS KFS6 KFS7 KFS8 KFS KFS0 KFS KFS KFS KFS4 KFS5 KFS6 KFS7 Genotypes means in years(kg/ha) Environment variance Si coefficient Variability CV% Mean ranking R Variance Ranking Ri (Var) standard deviation ranking Ri (S. D. R) Shokla stability variance σ i * For easy evaluation δ i and Si environment variance are divided to KFS0 KFS KFS KFS4 KFS 8 KFS KFS 6 KFS 7 KFS KFS5 KFS KFS KFS7 KFS KFS6 Figure. Sorghum lines dendrograms with at least variance method based on Shokla stability coefficient KFS0 KFS KFS KFS4 KFS KFS KFS6 KFS 7 KFS7 KFS KFS KFS6 KFS 5 KFS 8 KFS Figure. Sorghum lines dendrograms with at least variance method based on environment variance 48

5 Intl J Farm & Alli Sci. Vol., (): 45-4, 04 KFS KFS 8 KFS KFS KFS 7 KFS KFS5 KFS KFS4 KFS KFS0 KFS 6 KFS KFS7 KFS6 Figure. Sorghum lines dendrograms with at least variance method based on rank mean REFERENCES Acikgoz E, Ustun A, Gul I, Anlarsal E, Tekeli AS, Nizam I, Avcoglu R, Geren H, Cakmakci S, Aydinoglo B, Yucel C, Acar M, Ayan I, Uzum A, Bilgili U, Sincik M and Yavuz M. 00. Genotype environment interaction and stability analysis for dry matter and seed yield in field pea (pisum sativum L.). Spanish journal agricultural research,7(): Anagholi A, Kashiri A and Mokhtarpoor H The study comparison between inside forage sorghum cultivars and speedfeed hybrids. Agricultural science and natural resources journal. 7th. 4:7-8. Bachireddy VR, Payne JR, Chin KL and Kang MS.. Conventional selection versus methods that use genotype x environment interaction in sweet corn trials. HortScience 7: Duarte JB and Zimmermann MJD. 5. Correlation action among yield stability parameters in common bean crop science volume, 5():05-. Ehdayi B.. Plant breeding. Shahid Chamran university publication. Fernandez GCJ.. Analysis genotype environment interaction by stability estimates. Horticultural Sciences 7: Francis TR and Kannenberg LW. 78. Yield stability studies in short-season maize: I. A descriptive method for grouping genotypes. Can. J. Plant Sci. 58:0-04. Hayward MD, Bosemard NO & Romagosa I.. Plant breeding (4th edition.) London: Chapman and Hall, U.K. House LR. 85. A guide to sorghum breeding.icrisar. India. In, C.S., M.R. Binns, and L. P. Lefkovitch. 86. Stability analysis: Where do we stand? Crop Sci. 6:84 00.Huhn, M. 0. Non parametric measures phenotypic part. : Theery Euphytica, 47:8-4. Kang MS and Pham HN.. Simultaneous selection for yield and stability in crop performance trials. Consequences for grows. Agronomy Journal, 85: Kang MS and Magari R. 5. STABLE: A basic program for calculating stability and yield-stability statistics. Agronomy J. 87: Kaya Y & Taner S. 00. Estimating genotypic ranks by nonparametric stability analysis in bread wheat (Triticum aestivum L.). Journal Central Europen Agriculture, (4): Lin CS, Binns MR & Lefcovitch LP. 86. Stability analysis: Where do we stand? Crop Science, 6, Mekbib F Yield stability in common bean (phaseolus vulgaris L.) genotypes. Biomedical and sciences, 0(): Moghadam A. 6. Simultaneous selection for yield and yield stability and its comparison with different stability statics. Seed and plant journal. July 00.():-. Mohammad S and Francis CA. 8. Yield stability in relation to maturity in grain Sorghum. Crop Science. : Mohammad S, Francis CA, Rajewski JF and Maranville JW. 87. Genotype x environment interaction and stability analysis protein and oil in grain sorghum. Crop Science (87) 7:6-7. Sabaghnia N, Dehghani H and Sabaghpour SH Nonparametric Methods for Interpreting Genotype Environment Interaction Lentil Genotype. Crop Sci., 46(): Shukla GK. 7. Some statistical aspects partitioning genotype-environment components variability. Heredity :7 45. Zamanian M.. Evaluation different sorghum cultivars in Hamedan cold condition. Seed and plant. Vol 5():