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[Objective] The purpose of this paper was to explore the genetic diversity of the tea variety ’Zijuan’ and its mutagenesis progeny.[Method] The selected ’Zijuan’ and ’Zijuan’ mutated progeny were investigated from several aspects of botanical characters, biochemical components and EST-SSR markers. [Result] It was found that the color of buds and leaves of 15 materials were similar to that of ’Zijuan’,only two materials in the leaf shape of mature leaves that were the same as ’Zijuan’,which was lanceolate, and the others were elliptic or long elliptic. There were 9 materials with the same leaf color as ’Zijuan’,all of which are purple green, while 7 materials were yellow-green. Among the variation coefficients of biochemical components in spring and summer, the highest variation coefficient was anthocyanin, which reached 72.16% in spring and 77.86% in summer. The content of anthocyanin changed more in summer than in spring. A total of 165 alleles were detected by microsatellite markers, the average number of alleles was 7.5,the effective number of alleles was 2.562,Shannon information index was 0.997,polymorphic information content was 0.492,observed heterozygosity was 0.629,and expected heterozygosity was 0.565. [Conclusion] The above analysis results of traits, physiological and biochemical characteristics and microsatellite markers showed that the mutant progeny of ’Zijuan’ had a relatively rich genetic diversity. [ABSTRACT FROM AUTHOR]

In order to solve the problem that symbiotic organisms search algorithm converge slowly and easy to fall into the local optimum, combining quantum genetic algorithm theory, this paper proposed a real-coded quantum symbiotic organisms search algorithm( RQSOS). First, this paper presented the concept of the difference degree based on the principle of triangular fuzzy number, and constructed a variable component vector and a pair of probability amplitude of a allele in a chromosome that could carry more information and enhance the diversity of the solutions. Then it proposed the mode of rotary learning based on the Archimedes spiral, which strengthened the exploration ability of the solution space. Finally it updated the difference degree based on SOS, and carried out the population learning and mutation operations based on the value of the difference degree which could make the whole population evolution rapidly towards the optimal direction and reduced the probability of falling into local optimum. It was verified by numerical optimization and cloud task scheduling problem, and the simulation results show that the RQSOS algorithm can significantly improve the convergence speed and optimization ability, which is a feasible and effective algorithm. [ABSTRACT FROM AUTHOR]

[Objective] The present paper aimed to explore the endangered mechanism of natural resources and provide basis for the conservation of wild Fraxinus hupehensis. [Method] The genetic diversity of 196 individuals from 10 natural populations of Fraxinus hupehensis were analyzed by using cpSSR molecular markers, and the the UPGMA cluster of 10 populations was constructed. [Results] The 30 polymorphic hands were amplified from 6 primers. The genetic; diversity at populations level (Percentage of polymorphic loci; FPL = 25.75 % , Nei’s gene diversity index: h = 0.0974 ,Shannon’ s information index: I = 0.1440, the observed number of alleles: Na = 1.2575 , the effective number of alleles: Ne = 1.1712) was lower than that at the species level (PPL = 75.00 % h =0.1720 , I =0. 22732, Na = 1.7500,Ne = 1.2756). The Nm (gene flow) value and the coffieient of gene differentiation (Gst) was 0. 6942 and 0. 4189 Respectively, and the genetic; distance ranged from 0.0329 to 0. 1569. Based on the genetic identity (0.8548-0.9676) ,10 natural populations were divided into 4 groups. [Conclusion ]The total genetic* diversity of F. hupehensis was at a moderate level. The genetic variation mainly occurred within the populations (58. 11%), and the genetic differentiation among the populations was not obvious. Therefore, it is important to protect the populations with rich genetic diversity. [ABSTRACT FROM AUTHOR]