M Zabet, M.r Bihamta, A Talei, M Mardi, H Zeynali, Kh Bagheri,
Volume 12, Issue 46 (fall 2009)
Abstract
To study general combining ability(GCA) and gene action for resistance to sunn pest(Eurygaster integriceps) six lines of bread wheat numbered 7214 ,6412,c-75-4,18,14,12 plus azadi variety werw crossed in a half-diallel system. Seven parents and twenty-one hybrids were evaluated in a randomized complete block design with 3 replication at Tehran University Research Station during the years 2005-2006. Analysis of variance indicated that among all of traits except for weight of sunn pest damaged kernel, difference existed at 1% level of significant. Results of combining ability analysis showed that in all traits, additive and non- additive variances in inheritance is important. Considering GCA for resistance to sunn pest line 7214 was the best and line 18 was the worst. Considering specific combining ability(SCA) for resistance to sunn pest damage with regard to all of traits the azadi×c-75-4 hybrid was the best and the 18×12 hybrid was the worst. Study of Hayman genetics parameters confirmed the results of Griffing GCA analysis indicating that in all traits additive and non- additive components are effective in inheritance except 50 kernel weight damaged, sunn pest seed damaged percent and height. But dominant variance is more important in these traits. For all traits except awn length exist over dominance, furthermore in all traits nonsymmetrical distribution of negative and positive effects and environment effect is also important.
O. Mohammadrezapour, M. J. Zeynali,
Volume 22, Issue 1 (Spring 2018)
Abstract
One of the most important issues in the field of optimizing water resources management is the optimal utilization of the dam reservoirs. In the recent decades, the optimal operation of dams has been one of the most interesting issues considered by water resources planners in the country. Due to the complexities of the typical optimization methods, employing an evolutionary algorithm is regarded here. One of the most significant algorithms is the ant colony algorithm. So the aim of this study is to optimize the delivery of Golestan and Voshmgir reservoirs to meet the needs of the down lands using the elite ant colony algorithm, maximum – minimum ants, ranked ants, and particle swarm algorithms, and to compare the performance of these algorithms with each other. The considered decision variable was the release of the reservoirs in the above- mentioned dams. In this study, the data over a 5-year period, from 2006-2007 to 2011-2012, was used for modeling. The results showed that all algorithms could optimize the release amount optimally; however, the elite ant algorithm with the objective function value of 0.6407 estimated the release values with great accuracy in both dams. Also, the particle swarm algorithm with 1.275 of the objective function value was well-matched with the release values. The ranked ant algorithm with 18.924 and Max-Min ant with 26.431 of the objective function valuewere, respectively, at the next levels of performance optimization of the release values from Golestan and Voshgar dams.
