26份黄麻种质资源产量性状的主成分聚类分析及其评价
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摘要
为了解所收集黄麻种质资源的产量性状及遗传多样性,为黄麻育种和生产利用提供科学依据。本研究对26份黄麻品种(系)的8个产量性状进行主成分估算,并以前3个主成分为基础,分别作聚类分析和二维排序图。结果表明:参试材料产量相关性状的变异系数为2.54%~14.70%,其中,皮厚、单株鲜皮重、单株鲜骨重、鲜皮晒干率、单株干皮产量5个产量性状的变异系数超过10%,说明产量性状的变异潜力较高。主成分分析表明,单株鲜皮重因子、鲜皮晒干率因子、分枝高因子这3个主因子提供了原始性状88.247%的信息;在欧氏距离聚类图中,当取值D=2.15时,可把26个黄麻育成品种(系)分成4类,第Ⅰ类群包含18份材料,占69.23%,第Ⅱ类群包含5份材料,占19.23%,第Ⅲ类群只有1个品种(系),第Ⅳ类群包括黄麻179和宽叶长果2份材料,各个类群具有不同的特点,在黄麻杂交育种上可根据不同类别的特点加以利用;二维排序表明9(09品-11)、11(89m5-83)、12(09繁-7)、19(福黄麻1号)、21(黄麻831)、25(Y007-10)等6个高产品种(系)的3个主成分构成因子协调最好。将聚类分析和二维排序分析结合起来的分析方法,能较好地为黄麻品种改良以及亲本利用提供科学依据。
In order to gain knowledge of genetic diversity of jute germplasm resources,and provide scientific evidence to the improvment of jute varieties. The yield characters of 26 jute varieties( strains) were investigated based on the principal of numerical classification,and the PCA( define) of 8 yield characters were analyzed. The scatter plot were drawn based on the first 3 principal( PC) and the clustering analysis was carried out based on the genetic coefficients. The results showed that the coefficient variation of 8 yield characters ranged from 2. 54% to 14. 70%,5 yield characters of fiber bark thickness,fresh bark weight per plant,fresh bone weight per plant,fresh bark dry rate,dry bark weight per plant had a high coefficient of variation over 10%,there was variation potential on filed.Principle component analysis indicated that the first 3 PC accounted for 88. 247% of variation among the strains,followed by fresh bone weight per plant factor,fresh bark dry rate factor,branching height factor. According to 3principal components factors score,26 strains could be divided into 4 categories while D = 2. 15,with 18 strains belonging to the first cluster,5 strains belonging to the second cluster,1 strains belonging to the third cluster and 2strains belonging to the fourth cluster. Each group had different characteristics,these varieties( strains) could be used for castor breeding with different purposes. The scatter plot of the former three principal components indicatedthe coefficients of the first three PCs of 9( 09 Pin-11),11( 89m5-83),12( 09 Fan-7),19( Fuhuangma 1),21( Fuhuangma 3),25( Y007-10) were better than others. In general,cluster analysis and scatter plot based on PCs analysis together could make good comprehensive evaluation on jute strains,which could provide scientific evidence for the reasonable selection of germplasm resources for further jute breeding.
In order to gain knowledge of genetic diversity of jute germplasm resources,and provide scientific evidence to the improvment of jute varieties. The yield characters of 26 jute varieties( strains) were investigated based on the principal of numerical classification,and the PCA( define) of 8 yield characters were analyzed. The scatter plot were drawn based on the first 3 principal( PC) and the clustering analysis was carried out based on the genetic coefficients. The results showed that the coefficient variation of 8 yield characters ranged from 2. 54% to 14. 70%,5 yield characters of fiber bark thickness,fresh bark weight per plant,fresh bone weight per plant,fresh bark dry rate,dry bark weight per plant had a high coefficient of variation over 10%,there was variation potential on filed.Principle component analysis indicated that the first 3 PC accounted for 88. 247% of variation among the strains,followed by fresh bone weight per plant factor,fresh bark dry rate factor,branching height factor. According to 3principal components factors score,26 strains could be divided into 4 categories while D = 2. 15,with 18 strains belonging to the first cluster,5 strains belonging to the second cluster,1 strains belonging to the third cluster and 2strains belonging to the fourth cluster. Each group had different characteristics,these varieties( strains) could be used for castor breeding with different purposes. The scatter plot of the former three principal components indicatedthe coefficients of the first three PCs of 9( 09 Pin-11),11( 89m5-83),12( 09 Fan-7),19( Fuhuangma 1),21( Fuhuangma 3),25( Y007-10) were better than others. In general,cluster analysis and scatter plot based on PCs analysis together could make good comprehensive evaluation on jute strains,which could provide scientific evidence for the reasonable selection of germplasm resources for further jute breeding.
引文
[1]熊和平.麻类作物育种学[M].北京:中国农业科学技术出版社,2008:156
[2]陶爱芬,祁建民,李小珍.黄麻分子生物学研究进展及展望[J].中国麻业科学,2010,32(4):232-237
[3]刘新月,裴磊,董双全,等.冬小麦种质材料主要农艺性状研究[J].中国农学通报,2012,28(33):18-24
[4]程新奇,郭安平,肖瑞芝,等.黄麻种质资源的鉴定与利用分析[J].中国麻作,1993(4):1-8
[5]程新奇,肖瑞芝,余隆其,等.长果种黄麻资源高产种质的筛选[J].中国麻作,1992(4):7-11
[6]张彩英,常文锁,谢令琴,等.小麦高代新品种(系)鉴定的聚类分析[J].植物遗传资源科学,2001,2(4):29-33
[7]王绘艳,史雨刚,马昊翔,等.30份春小麦品系主要农艺性状的聚类分析[J].中国农学通报,2014,30(18):60-64
[8]要燕杰,高翔,吴丹,等.小麦农艺性状与品质特性的多元分析与评价[J].植物遗传资源学报,2014,15(1):38-47
[9]Bhati P K,Singh S K,Dhurai Amita Sharma S Y.Genetic divergence for quantitative traits in rice germplasm[J].Electron J Plant Breed,2015,6(2):521-527
[10]韩泽群,姜波.加工番茄品种多性状综合评价方法研究[J].中国农业科学,2014,47(2):357-365
[11]郭丽芬,徐宁生,张跃,等.云南红花种质资源主要农艺性状的遗传多样性分析[J].植物遗传资源学报,2012,13(2):219-225
[12]陶爱芬,祁建民,林培青,等.红麻优异种质产量和品质性状主成分聚类分析与综合评价[J].中国农业科学,2008,41(9):2859-2867
[13]方平平,郑鹭,陶爱芬,等.蓖麻遗传资源产量与品质性状主成分聚类分析及其评价[J].福建农林大学学报:自然科学版,2011,40(3):232-236
[14]张加强,骆霞虹,陈常理,等.叶用芥菜种质表型性状的遗传多样性分析[J].植物遗传资源学报,2015,16(3):535-540
[15]Ashutosh S,Sonika Y,Mukherjee S.Genetic divergence within some genotypes of tossa jute(Corchorus olitorius L.)[J].Environ Ecol,2015,33(2):749-752
[16]王敏,徐萍,刘新江,等.黄淮海地区夏玉米农艺性状与产量的通径分析[J].中国生态农业学报,2011,19(5):1229-1236
[17]张雪花,李浩杰,张锦芳,等.甘蓝型油菜耐湿性初步评价和主成分分析[J].中国油料作物学报,2011,32(2):98-103
[18]陈碧云,许鲲,高桂珍,等.中国白菜型油菜种质表型多样性分析[J].中国油料作物学报,2012,34(1):25-32
[19]刘新龙,马丽,蔡青,等.云南甘蔗品种表型性状的遗传多样性分析[J].植物遗传资源学报,2010,11(6):703-708
[20]慈敦伟,张礼凤,汪宝卿,等.大豆种质资源农艺性状和产量的年份间差异及其关系[J].植物遗传资源学报,2011,12(6):872-880
[21]贺晨帮,宗绪晓.豌豆种质资源形态标记遗传多样性分析[J].植物遗传资源学报,2011,12(1):42-48
[22]何玉华,杨峰,王丽萍,等.云南省地方蚕豆种质资源形态学遗传多样性分析[J].西南农业学报,2014,27(2):512-517
[23]张赤红,曹永生,宗绪晓,等.普通菜豆种质资源形态多样性鉴定与分类研究[J].中国农业科学,2005,38(1):27-32
[24]胡建斌,马双武,简在海,等.中国甜瓜种质资源形态性状遗传多样性分析[J].植物遗传资源学报,2013,14(4):612-619
[25]雷逢进,温祥珍,李亚灵,等.西葫芦品种的株型研究及评价[J].西北农业学报,2010,19(11):104-109
[26]陈书霞,周静,申晓青,等.大蒜种质产量和品质性状主成分聚类分析与综合评价[J].植物遗传资源学报,2012,13(3):429-434
[27]刘科鹏,黄春辉,冷建华,等.‘金魁’猕猴桃果实品质的主成分分析与综合评价[J].果树学报,2012,29(5):867-871
[28]郝朝运,谭乐和,范睿,等.中国部分胡椒属植物表型性状的数量分类[J].热带作物学报,2012,33(5):779-785
[29]祁建民,李维明,林荔辉,等.黄麻种质资源数量分类研究[J].作物学报,1996,22(5):587-594
[30]龚友才,郭安平.长果种黄麻主要亲本数量性状遗传变异与多元分析[J].中国麻作,1992(4):1-7
[31]唐启义,冯明光.DPS统计分析系统:实验设计、统计分析及数据发掘[M].北京:科学出版社,2006:603-610,644-650
[32]郭安平,龚友才.长果种黄麻品种主要农艺性状与单株产量关系的分析[J].中国麻作,1988(4):13-18
[33]郑云雨,祁建民,李维明,等.黄麻产量和纤维品质性状典型相关与双重筛选逐步回归分析[J].福建农业大学学报,1994(1):17-20
[34]林元直,祁建民.圆果黄麻种质资源综合评估的层次分析法[J].福建农学院学报,1992,21(2):219-224
[35]祁建民,王英娇,郑云雨,等.黄麻数量性状相关遗传参数及其多元分析[J].中国麻作,1990(4):4-10
[36]张加强,骆霞虹,陈常理,等.圆果种黄麻主要经济性状与纤维产量的相关及灰色关联分析[J].中国麻业科学,2015(2):70-74,79
[37]龚友才,戴志刚,陈基权,等.长果黄麻新品种‘Y007-10’选育研究[J].热带农业科学,2013,33(11):27-31
[2]陶爱芬,祁建民,李小珍.黄麻分子生物学研究进展及展望[J].中国麻业科学,2010,32(4):232-237
[3]刘新月,裴磊,董双全,等.冬小麦种质材料主要农艺性状研究[J].中国农学通报,2012,28(33):18-24
[4]程新奇,郭安平,肖瑞芝,等.黄麻种质资源的鉴定与利用分析[J].中国麻作,1993(4):1-8
[5]程新奇,肖瑞芝,余隆其,等.长果种黄麻资源高产种质的筛选[J].中国麻作,1992(4):7-11
[6]张彩英,常文锁,谢令琴,等.小麦高代新品种(系)鉴定的聚类分析[J].植物遗传资源科学,2001,2(4):29-33
[7]王绘艳,史雨刚,马昊翔,等.30份春小麦品系主要农艺性状的聚类分析[J].中国农学通报,2014,30(18):60-64
[8]要燕杰,高翔,吴丹,等.小麦农艺性状与品质特性的多元分析与评价[J].植物遗传资源学报,2014,15(1):38-47
[9]Bhati P K,Singh S K,Dhurai Amita Sharma S Y.Genetic divergence for quantitative traits in rice germplasm[J].Electron J Plant Breed,2015,6(2):521-527
[10]韩泽群,姜波.加工番茄品种多性状综合评价方法研究[J].中国农业科学,2014,47(2):357-365
[11]郭丽芬,徐宁生,张跃,等.云南红花种质资源主要农艺性状的遗传多样性分析[J].植物遗传资源学报,2012,13(2):219-225
[12]陶爱芬,祁建民,林培青,等.红麻优异种质产量和品质性状主成分聚类分析与综合评价[J].中国农业科学,2008,41(9):2859-2867
[13]方平平,郑鹭,陶爱芬,等.蓖麻遗传资源产量与品质性状主成分聚类分析及其评价[J].福建农林大学学报:自然科学版,2011,40(3):232-236
[14]张加强,骆霞虹,陈常理,等.叶用芥菜种质表型性状的遗传多样性分析[J].植物遗传资源学报,2015,16(3):535-540
[15]Ashutosh S,Sonika Y,Mukherjee S.Genetic divergence within some genotypes of tossa jute(Corchorus olitorius L.)[J].Environ Ecol,2015,33(2):749-752
[16]王敏,徐萍,刘新江,等.黄淮海地区夏玉米农艺性状与产量的通径分析[J].中国生态农业学报,2011,19(5):1229-1236
[17]张雪花,李浩杰,张锦芳,等.甘蓝型油菜耐湿性初步评价和主成分分析[J].中国油料作物学报,2011,32(2):98-103
[18]陈碧云,许鲲,高桂珍,等.中国白菜型油菜种质表型多样性分析[J].中国油料作物学报,2012,34(1):25-32
[19]刘新龙,马丽,蔡青,等.云南甘蔗品种表型性状的遗传多样性分析[J].植物遗传资源学报,2010,11(6):703-708
[20]慈敦伟,张礼凤,汪宝卿,等.大豆种质资源农艺性状和产量的年份间差异及其关系[J].植物遗传资源学报,2011,12(6):872-880
[21]贺晨帮,宗绪晓.豌豆种质资源形态标记遗传多样性分析[J].植物遗传资源学报,2011,12(1):42-48
[22]何玉华,杨峰,王丽萍,等.云南省地方蚕豆种质资源形态学遗传多样性分析[J].西南农业学报,2014,27(2):512-517
[23]张赤红,曹永生,宗绪晓,等.普通菜豆种质资源形态多样性鉴定与分类研究[J].中国农业科学,2005,38(1):27-32
[24]胡建斌,马双武,简在海,等.中国甜瓜种质资源形态性状遗传多样性分析[J].植物遗传资源学报,2013,14(4):612-619
[25]雷逢进,温祥珍,李亚灵,等.西葫芦品种的株型研究及评价[J].西北农业学报,2010,19(11):104-109
[26]陈书霞,周静,申晓青,等.大蒜种质产量和品质性状主成分聚类分析与综合评价[J].植物遗传资源学报,2012,13(3):429-434
[27]刘科鹏,黄春辉,冷建华,等.‘金魁’猕猴桃果实品质的主成分分析与综合评价[J].果树学报,2012,29(5):867-871
[28]郝朝运,谭乐和,范睿,等.中国部分胡椒属植物表型性状的数量分类[J].热带作物学报,2012,33(5):779-785
[29]祁建民,李维明,林荔辉,等.黄麻种质资源数量分类研究[J].作物学报,1996,22(5):587-594
[30]龚友才,郭安平.长果种黄麻主要亲本数量性状遗传变异与多元分析[J].中国麻作,1992(4):1-7
[31]唐启义,冯明光.DPS统计分析系统:实验设计、统计分析及数据发掘[M].北京:科学出版社,2006:603-610,644-650
[32]郭安平,龚友才.长果种黄麻品种主要农艺性状与单株产量关系的分析[J].中国麻作,1988(4):13-18
[33]郑云雨,祁建民,李维明,等.黄麻产量和纤维品质性状典型相关与双重筛选逐步回归分析[J].福建农业大学学报,1994(1):17-20
[34]林元直,祁建民.圆果黄麻种质资源综合评估的层次分析法[J].福建农学院学报,1992,21(2):219-224
[35]祁建民,王英娇,郑云雨,等.黄麻数量性状相关遗传参数及其多元分析[J].中国麻作,1990(4):4-10
[36]张加强,骆霞虹,陈常理,等.圆果种黄麻主要经济性状与纤维产量的相关及灰色关联分析[J].中国麻业科学,2015(2):70-74,79
[37]龚友才,戴志刚,陈基权,等.长果黄麻新品种‘Y007-10’选育研究[J].热带农业科学,2013,33(11):27-31