| 酿酒葡萄杂交F1代果实品质性状的聚类分析与优系筛选 |
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| 引用本文： | 谭伟,邹琴艳,张岩,吴帅,赵遵乐,李晓梅,赵旗峰,李庆亮.酿酒葡萄杂交F1代果实品质性状的聚类分析与优系筛选[J].果树学报,2020(7):971-984. |
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| 作者姓名： | 谭伟 邹琴艳 张岩 吴帅 赵遵乐 李晓梅 赵旗峰 李庆亮 |
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| 作者单位： | 枣庄学院食品科学与制药工程学院;山西省农业科学院果树研究所;枣庄学院生命科学学院 |
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| 基金项目： | 山东省自然科学基金(ZR2019BC092);枣庄学院博士科研基金(1020707);山西省农业科学院院优势课题组自选项目(YYS1704)。 |
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| 摘 要： | 【目的】探索基于果实品质筛选酿酒葡萄杂交F1代优系的方法。【方法】以‘2-1-3’ב阿列尼’、‘2-1-3’ב宝石解百纳’2个酿酒葡萄杂交组合F1代和亲本、对照品种共74份成熟期果实为材料,连续4 a(年)对22个果实主要品质数量性状进行主成分和聚类分析,从中筛选出优系。【结果】69份杂交F1代与亲本、对照品种成熟期果实22个品质性状指标有差异,除果皮总酚含量无F1代介于对照品种‘赤霞珠685’与‘美乐181’之间外,其余21个指标有1~36份F1代介于对照品种之间,果皮单宁含量仅31-5-2-2介于对照品种之间。对74份材料的22个品质指标进行主成分分析,其中前4个主成分贡献率分别为32.26%、26.25%、15.20%、11.58%,累计贡献率达85.28%。根据22个品质指标和4个主成分值,对69份F1代和亲本、对照品种进行聚类分析结合田间观察评选出综合性状优良的杂交单系2份,为31-5-2-1、44-6-7-1。【结论】对葡萄杂交F1代果实品质性状进行主成分分析和聚类分析,可简化酿酒葡萄杂交后代果实品质的评价指标,对酿酒葡萄杂交后代进行综合评价并选出杂交优系,为今后酿酒葡萄新品种选育提供了参考方法。
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| 关 键 词： | 酿酒葡萄 杂交F1代 果实品质 主成分 聚类分析 |
Cluster analysis and selection of optimal lines based on the fruit quality traits of F1 progenies of wine grape |
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| TANWei,ZOU Qinyan,ZHANG Yan,WU Shuai,ZHAO Zunle,LI Xiaomei,ZHAO Qifeng,LI Qingliang.Cluster analysis and selection of optimal lines based on the fruit quality traits of F1 progenies of wine grape[J].Journal of Fruit Science,2020(7):971-984. |
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| Authors: | TANWei ZOU Qinyan ZHANG Yan WU Shuai ZHAO Zunle LI Xiaomei ZHAO Qifeng LI Qingliang |
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| Institution: | (College of Food Science and Pharmaceutical Engineering,Zaozhuang University,Zaozhuang 277160,Shandong,China;Pomology Institute,Shanxi Academy of Agricultural Science,Taigu 030815,Shanxi,China;College of Life Science,Zaozhuang University,Zaozhuang 277160,Shandong,China) |
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| Abstract: | 【Objective】Grape,especially wine grape breeding through crossing is a time consuming process.Selection of superior lines from F1 progenies through fruit character evaluation in early stage is important for breeders.The main purpose of this paper was to explore the method of selecting superior lines from F1 generation of wine grape based on fruit quality evaluation and cluster analysis.【Methods】The mature fruits of 69 F1 generations from two crossing combinations of‘2-1-3’בAreni’and‘2-1-3’בRuby Cabernet’,three parents‘(2-1-3’‘Areni’and‘Ruby Cabernet’)and two control varieties‘(Cabernet Sauvignon 685’and‘Merlot 181’)were used as materials.The vines were all grown in the vineyards of Pomology Institute,Shanxi Academy of Agricultural Science in Taigu,Shanxi Province.During the periods of August to October in 4 years(2013—2016),the fruit quality indexes of berry weight,the ratio of peel to pulp,soluble solids(SS),titratable acid(TA)content,pH value,juice yield of fresh fruit were measured according to the conventional method.The samples were frozen using liquid nitrogen and stored in an ultra-low temperature freezer.The contents of phenolic compounds in peel,pulp and seeds of berries were analyzed for 4 years according to colorimetric method.Then principal component and cluster analysis was performed based on the 4 years’data of 22 fruit quality traits to select superior lines.【Results】There were differences in the 22 fruit quality traits among 74 materials.In the crossing combinations of‘2-1-3’בAreni’and‘2-1-3’בRuby Cabernet’,the fruit characteristics of F1 progeny were quantitative traits with continuous distribution.There was no individual in the F1 progenies,of which the value of the total phenol content in the peel was somewhere in between the two control varieties‘Cabernet Sauvignon 685’and‘Merlot 181’,while there were 1 to 36 individuals in the F1 progenies,of which the values of the other 21 traits were somewhere in between the two control varieties,and the value of tannin content in the peel of 31-5-2-2 strain was exceptionally in between the two control varieties.Principal component analysis performed on 22 quality indexes of 74 materials showed that the contribution rate of the first 4 main components were 32.26%,26.25%,15.20%,and 11.58%,respectively,and the cumulative contribution ratio reached 85.28%.The 22 fruit quality indexes of 74 materials could be simplified to these 4 principal components for comprehensive evaluation of the fruit quality.The four principal components were the composition factor 1 of the phenolic substances in the peel,the composition factor 1 of the phenolic substances in the seed,the composition factor 1 of the fruit quality,and the composition factor 2 of the peel quality.According to the principal component value,the fruit quality of 31-5-2-1 was closest to that of‘Cabernet Sauvignon 685’.According to the 22 fruit quality indicators,cluster analysis of 74 materials showed that the 22 fruit quality indicators of 44-6-7-1 and 44-6-3-6 was closest to that of‘Cabernet Sauvignon 685’and‘Merlot 181’,respectively.According to 4 principal components,cluster analysis of 74 materials showed the 31-5-2-1 and 44-6-3-4 was closest to that of‘Cabernet Sauvignon 685’and‘Merlot 181’,respectively.Based on the results of the principal component analysis and the cluster analysis,31-5-2-1 and 44-6-7-1 were selected as two optimal lines.The average berry weight of the two superior lines were slightly larger than those of the control varieties,the ratio of the peel to pulp was in between the control varieties;the titratable acid content of 44-6-7-1 was higher than those of the control varieties,while the juice yield of 31-5-2-1 was the lowest.In 44-6-7-1,the contents of the total phenols,procyanidins and total anthocyanins in pericarp,procyanidins in pulp were higher than those of the control varieties,while the contents of total phenols and tannins in pulp and seeds were in between the control varieties.In 31-5-2-1,the contents of total phenols and tannins in peel,total flavonoids in pulp were significantly higher than those in the control cultivars,while the contents of proanthocyanidins in peel,total anthocyanins,tannins in pulp and seeds were significantly lower than those in the control cultivars.【Conclusion】The comprehensive application of principal component analysis and cluster analysis based on quality properties could simplify the evaluation indexes of fruit quality of hybrid offsprings of wine grape.Based on this,comprehensive evaluation of hybrid progenies of wine grape and selection of superior hybrid lines could be used as reference method for selecting new wine grape lines in the future. |
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| Keywords: | Wine grape Hybrid F1 progenies Fruit quality Principal components Cluster analysis |
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