Sweetpotato varieties with high carotene content have high value for human health. This work aims to improve the breeding efficiency of special varieties with high carotene content by combining molecular markers and a...Sweetpotato varieties with high carotene content have high value for human health. This work aims to improve the breeding efficiency of special varieties with high carotene content by combining molecular markers and agronomic traits to evaluate and screen the parents. The cluster analysis was carried out to identify and screen promising parents by utilizing phenotypic results of the agronomic and characteristic traits, and RAPD and ISSR markers of 15 parents and their offspring by group crossing. Among different parental materials, greater variations were observed in two important traits, the carotene content and the storage root yield. Negative correlation was found between the carotene content and both fresh and dried root yields. The most significant positive correlation was between the carotene content of parents and that of their offspring, with the coefficient of correlation value of 0.7932＊＊. The relationship based on the agronomic characters of the trial materials was not in agreement with the known genealogy, while that based on the molecular marker data showed better result. Each primer amplified 13.8 bands oflSSR markers on average, in which the rate of polymorphic loci was 89.6%. 9.4 bands of RAPD markers were arnplified per primer, in which the rate of polymorphic bands was 74.46%. Large genetic variation of carotene content was found among the parents. For analyzing the genetic diversity of sweetpotato, the molecular marker methods were better than morphological traits; ISSR markers were more efficient than RAPD markers. The combination of molecular markers and agronomic trait analysis may provide valuable theoretic basis for selection of parents to breed new varieties with high carotene content.展开更多
In differential evolution （DE）, the salient feature lies in its mutation mechanism that distinguishes it from other evolutionary algorithms. Generally, for most of the DE algorithms, the parents for mutation are ran...In differential evolution （DE）, the salient feature lies in its mutation mechanism that distinguishes it from other evolutionary algorithms. Generally, for most of the DE algorithms, the parents for mutation are randomly chosen from the current population. Hence, all vectors of population have the equal chance to be selected as parents without selective pressure at all. In this way, the information of population cannot be fully exploited to guide the search. To alleviate this drawback and improve the performance of DE, we present a new selection method of parents that attempts to choose individuals for mutation by utilizing the population information effectively. The proposed method is referred as fitnessand-position based selection （FPS）, which combines the fitness and position information of population simultaneously for selecting parents in mutation of DE. In order to evaluate the effectiveness of FPS, FPS is applied to the original DE algorithms, as well as several DE variants, for numerical optimization. Experimental results on a suite of benchmark functions indicate that FPS is able to enhance the performance of most DE algorithms studied. Compared with other selection methods, FPS is also shown to be more effective to utilize information of population for guiding the search of DE.展开更多
基金supported by the National Key Technologies R&D Program of China(2006BAD01A06)the Program of Introducing International Super Agricultural Science and Technology of China (2006G21)the Funds of HarvestPlus, China
文摘Sweetpotato varieties with high carotene content have high value for human health. This work aims to improve the breeding efficiency of special varieties with high carotene content by combining molecular markers and agronomic traits to evaluate and screen the parents. The cluster analysis was carried out to identify and screen promising parents by utilizing phenotypic results of the agronomic and characteristic traits, and RAPD and ISSR markers of 15 parents and their offspring by group crossing. Among different parental materials, greater variations were observed in two important traits, the carotene content and the storage root yield. Negative correlation was found between the carotene content and both fresh and dried root yields. The most significant positive correlation was between the carotene content of parents and that of their offspring, with the coefficient of correlation value of 0.7932＊＊. The relationship based on the agronomic characters of the trial materials was not in agreement with the known genealogy, while that based on the molecular marker data showed better result. Each primer amplified 13.8 bands oflSSR markers on average, in which the rate of polymorphic loci was 89.6%. 9.4 bands of RAPD markers were arnplified per primer, in which the rate of polymorphic bands was 74.46%. Large genetic variation of carotene content was found among the parents. For analyzing the genetic diversity of sweetpotato, the molecular marker methods were better than morphological traits; ISSR markers were more efficient than RAPD markers. The combination of molecular markers and agronomic trait analysis may provide valuable theoretic basis for selection of parents to breed new varieties with high carotene content.
文摘In differential evolution （DE）, the salient feature lies in its mutation mechanism that distinguishes it from other evolutionary algorithms. Generally, for most of the DE algorithms, the parents for mutation are randomly chosen from the current population. Hence, all vectors of population have the equal chance to be selected as parents without selective pressure at all. In this way, the information of population cannot be fully exploited to guide the search. To alleviate this drawback and improve the performance of DE, we present a new selection method of parents that attempts to choose individuals for mutation by utilizing the population information effectively. The proposed method is referred as fitnessand-position based selection （FPS）, which combines the fitness and position information of population simultaneously for selecting parents in mutation of DE. In order to evaluate the effectiveness of FPS, FPS is applied to the original DE algorithms, as well as several DE variants, for numerical optimization. Experimental results on a suite of benchmark functions indicate that FPS is able to enhance the performance of most DE algorithms studied. Compared with other selection methods, FPS is also shown to be more effective to utilize information of population for guiding the search of DE.
