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Comparison of Genetic Diversity of the Germplasm Resources of Confectionary Sunflower (Helianthus annuus) in China Based on RAPDs and AFLPs 被引量:2
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作者 刘杰 刘公社 Chao Chien JAN 《Acta Botanica Sinica》 CSCD 2003年第3期352-358,共7页
RAPDs and AFLPs were used to determine the genetic relationships among 23 elite cultivars of confectionary sunflowers (Helianthas annuus) from different districts in China. Both approaches uniquely fingerprint each of... RAPDs and AFLPs were used to determine the genetic relationships among 23 elite cultivars of confectionary sunflowers (Helianthas annuus) from different districts in China. Both approaches uniquely fingerprint each of the accessions. Twenty-six RAPD primers resulted in a total of 192 strong DNA fragments, ranging from 0.26 kb to 1.98 kb, among which 165 (86.12%) were polymorphic. The average number of DNA band produced by each primer was 7.38. A total of 576 AFLP markers were produced with 8 primer combinations, ranging from 100 bp to 500 bp, and 341 polymorphic bands (59.20%) were revealed. The polymorphism rate was 76.00% and the average bands amplified by per primer combination were 72. Effective number of alleles per locus of RAPD marker (1.76) was larger than that of the AFLP marker (1.65). The mean PIC value of AFLP markers (0.38) was lower than that of the RAPD markers (0.41), but AFLP marker had much higher Ai value (38.52) than RAPD marker (6.38). Genetic similarities from RAPD data ranged from 47.84% to 82.06% and the average Nei's coefficient was 0.649 5; the Nei's coefficient of similarity from AFLP data ranged from 54.15% to 83.52%, and the average Nei's coefficient was 0.688 4. However, standard deviation (SD) of RAPDs was 0.13 but the SD of AFLPs was 0.08. In general, the RAPD data gave lower similarity values and higher SD values than those based on the AFLP analysis. The correlation coefficient between the two genetic similarity matrices was 0.51, revealing the estimations of genetic relationship provided by the two marker systems were only moderate. However, cluster analyses of RAPD or AFLP data divided the 23 sunflower genotypes into identical 3 groups. 展开更多
关键词 confectionary sunflower RAPD AFLP genetic diversity
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Analysis of the Performance of a Dehulling System for Confectionary Sunflower Seeds
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作者 Ana Karina de Figueiredo Luciana Marcela Rodríguez +1 位作者 Isabel Concepción Riccobene Susana Maria Nolasco 《Food and Nutrition Sciences》 2014年第6期541-548,共8页
Confectionary sunflower, which has a larger size and lower oil content than oilseed sunflower, has a considerable market, since it is used for birdfeed and human consumption. The characteristics of use of confectionar... Confectionary sunflower, which has a larger size and lower oil content than oilseed sunflower, has a considerable market, since it is used for birdfeed and human consumption. The characteristics of use of confectionary sunflower seeds require a dehulling process that is efficient in the removal of the hull and that also allows obtaining a product consisting mainly of whole kernels. Response surface methodology was used to determine an optimal combination of working conditions in the dehulling process of confectionary sunflower seeds. Optimization factors were impact speed, expressed in terms of the peripheral speed (28.3 -41.9 m/s), and moisture content of the seeds (4% -14%, dry basis—db). A central composite rotatable design (CCRD) was used to develop models for the responses (dehulling ability—DA and percentage of whole kernels—WK). Applying the desirability function method, the optimal values of the factors were determined using maximum WK and maximum DA as criteria. The results of the optimization technique suggest that by dehulling Mycogen 9338 confectionary sunflower seeds at 12.3% db and 32.5 m/s, the maximum values of DA and WK (72.6% and 63%, respectively) would be obtained. The moisture value defined as optimal determines a requirement of humidification of the seeds prior to dehulling, establishing the need for a technical and economic feasibility study. 展开更多
关键词 confectionary SUNFLOWER DEHULLING Response Surface METHODOLOGY WHOLE KERNELS
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