Factor Analysis and Comprehensive Assessment of Phenotypic Selection of Officinal Neem Superior Trees

PENG Xing-min; WU Jiang-chong; WANG You-qiong; ZHENG Yi-xing; MA Li-yi; ZHANG Yan-ping

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Factor Analysis and Comprehensive Assessment of Phenotypic Selection of Officinal Neem Superior Trees

1.
Research Institute of Resource Insects, Chinese Academy of Forestry, Kunming 650224, Yunnan, China

Received Date: 2015-01-05

Abstract

In order to find analysis and assessment methods of phenotypic selection of officinal neem superior trees, and to empirically evaluate the officinal neem resources and to finally provide evidences and guidance in officinal neem breeding, 12 characters correlated with quality and yield in 32 primarily selected superior trees and control were tested. The results are as follows: among characters, at least one was significantly or extremely significantly correlated with another. Accumulative contribution rate of 4 common factors (with latent root >1) was 83.53%, their contribution rate was 31.33% (the first PC, seed shape), 22.98% (the second PC, azadirachtin content), 15.11% (the third PC, seed yield), 14.10% (the fourth PC, ratio of azadirachtin ingredient), respectively. And typical example of variables in analysis and assessment of phenotypic selection were: kernel weight (0.995 11), seed weight (0.956 76), seed length (0.780 12), content of azadirachtin A+B (0.866 67), content of azadirachtin B (0.819 34), content of azadirachtin A (0.680 84), ground diameter (0.939 04), seed yield per tree (0.722 82), ratio of azadirachtin B to A (-0.833 60). Mantel test showed that cluster analysis could reveal the phenotypic differences of 33 trees (r=0.81, p=1.00). Cluster groups could be categorized as: type of high azadirachtin content, type of full size of seeds and kernels, type of larger tree and high seed yield, and type of normal. Criterion of comprehensive assessment of primarily selected superior trees: "Superior" (with score ≥ 0.59), "Medium" (with score -0.190.59), "Poor" (with score ≤-0.19). According to this criterion, primarily selected superior trees were divided into 4 "Superior", 16"Medium", and 12"Poor" trees. With factor analysis and cluster analysis, analysis and assessment of phenotypic selection of officinal neem superior trees can be directly and easily performed and judged, the results could provide evidences and guidance in officinal neem breeding.
- neem,
- officinal superior trees,
- phenotypic selection,
- factor analysis,
- comprehensive assessment

References

[1]	Tomilin C D. The Pesticide Manual.12nd ed.[M].UK: Surrey, British Crop Protection Council,2000.
[2]	National R C. Neem-A Tree for Solving Global Problems[M]. Washington D C: National Academy Press,1992.
[3]	彭兴民,吴疆翀,郑益兴,等. 印楝属(Azadirachta A. Juss.) 植物分类及分布的研究现状[J].植物遗传资源学报, 2012,13(4):583-588.
[4]	Kaushik N, Singh B G, Tomar U K, et al. Regional and habitat variability in azadirachtin content of Indian neem (Azadirachta indica A.Jusieu)[J].Current Science, 2007,92(10):1400-1406.
[5]	吴疆翀. 印楝繁育系统的研究[D]. 北京:中国林业科学研究院,2007.
[6]	彭兴民,吴疆翀, 郑益兴,等. 云南引种印楝实生种群的表型变异[J]. 植物生态学报, 2012,36(6):560-571.
[7]	彭兴民,吴疆翀,郑益兴,等. 云南引种印楝实生栽培种群表型的地理变异[J].林业科学研究,2013,26(4):399-405.
[8]	彭兴民,吴疆翀,程金焕,等. 印楝农药原料林优树选择方法与标准[J].福建林学院学报, 2010,30(3):265-269.
[9]	Sidhu O P, Kumar V, Behl H M. Variability in Neem (Azadirchta indica) with respect to azadirchtin content[J]. J Agri Food Chem, 2003,51(4): 910-915.
[10]	Tomar U K, Singh G, Kaushik N. Screening Azadirachta indica tree for enhancing azadirachtin and oil contents in dry areas of Gujarat[J]. Journal of Forestry Research, 2011, 22(2): 217-224.
[11]	Quinn G P, Keough M J. 生物实验设计与数据分析[M]. 蒋志刚,李春旺,曾岩,译. 北京: 高等教育出版社,2003.
[12]	Tan Y F, Corke H. Factor analysis of physicochemical properties of 63 rice varieties[J]. Journal of the Science of Food and Agriculture, 2002,82(7):745-752.
[13]	Toker C, Cagirgan M I. The use of phenotypic correlations and factor analysis in determining characters for grain yield selection in chickpea(Cicer arietinum L.)[J]. Hereditas, 2004,140(3): 226-228.
[14]	Kurtanjek Z, Horvat D, Magdic D, et al. Factor analysis and modelling for rapid quality assessment of croatian wheat cultivars with different gluten characteristics[J]. Food Technology and Biotechnology, 2008,46(3): 270-277.
[15]	敖妍.因子分析法在文冠果优良单株选择中的应用[J]. 华南农业大学学报, 2009,30(4):70-73.
[16]	马庆华,李永红,梁丽松,等. 冬枣优良单株果实品质的因子分析与综合评价[J]. 中国农业科学, 2010,43(12):2491-2499.
[17]	康立宁,田志刚,刘香英,等. 大豆组织蛋白产品品质的因子分析和综合评价研究[J]. 吉林农业科学, 2012,37(2):45-48.
[18]	宗乾收, 林军, 武永昆, 等. 印楝种仁中印楝素含量的快速液相色谱分析[J]. 农药, 2003,42(4):23-24.
[19]	阮敬. SAS统计分析从入门到精通[M]. 北京:人民邮电出版社出版,2009.
[20]	汤飞宇,程锦,黄文新,等. 高品质陆地棉数量性状的因子分析及品种聚类分析[J].江西农业大学学报, 2008,30(6):1014-1018.
[21]	柳伟伟,胡良平. 主成分分析与探索性因子分析的SAS软件实现[J]. 中西医结合学报, 2010,8(6):589-593.
[22]	胡建军. 烟叶质量评价方法优选与实证研究[D]. 长沙:湖南农业大学. 2009.
[23]	徐克学. 生物数学[M]. 北京: 科学出版社,1999.

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Factor Analysis and Comprehensive Assessment of Phenotypic Selection of Officinal Neem Superior Trees

1. Research Institute of Resource Insects, Chinese Academy of Forestry, Kunming 650224, Yunnan, China

Received Date: 2015-01-05

Abstract: In order to find analysis and assessment methods of phenotypic selection of officinal neem superior trees, and to empirically evaluate the officinal neem resources and to finally provide evidences and guidance in officinal neem breeding, 12 characters correlated with quality and yield in 32 primarily selected superior trees and control were tested. The results are as follows: among characters, at least one was significantly or extremely significantly correlated with another. Accumulative contribution rate of 4 common factors (with latent root >1) was 83.53%, their contribution rate was 31.33% (the first PC, seed shape), 22.98% (the second PC, azadirachtin content), 15.11% (the third PC, seed yield), 14.10% (the fourth PC, ratio of azadirachtin ingredient), respectively. And typical example of variables in analysis and assessment of phenotypic selection were: kernel weight (0.995 11), seed weight (0.956 76), seed length (0.780 12), content of azadirachtin A+B (0.866 67), content of azadirachtin B (0.819 34), content of azadirachtin A (0.680 84), ground diameter (0.939 04), seed yield per tree (0.722 82), ratio of azadirachtin B to A (-0.833 60). Mantel test showed that cluster analysis could reveal the phenotypic differences of 33 trees (r=0.81, p=1.00). Cluster groups could be categorized as: type of high azadirachtin content, type of full size of seeds and kernels, type of larger tree and high seed yield, and type of normal. Criterion of comprehensive assessment of primarily selected superior trees: "Superior" (with score ≥ 0.59), "Medium" (with score -0.190.59), "Poor" (with score ≤-0.19). According to this criterion, primarily selected superior trees were divided into 4 "Superior", 16"Medium", and 12"Poor" trees. With factor analysis and cluster analysis, analysis and assessment of phenotypic selection of officinal neem superior trees can be directly and easily performed and judged, the results could provide evidences and guidance in officinal neem breeding.

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Reference (23)

[1]	Tomilin C D. The Pesticide Manual.12nd ed.[M].UK: Surrey, British Crop Protection Council,2000.
[2]	National R C. Neem-A Tree for Solving Global Problems[M]. Washington D C: National Academy Press,1992.
[3]	彭兴民,吴疆翀,郑益兴,等. 印楝属(Azadirachta A. Juss.) 植物分类及分布的研究现状[J].植物遗传资源学报, 2012,13(4):583-588.
[4]	Kaushik N, Singh B G, Tomar U K, et al. Regional and habitat variability in azadirachtin content of Indian neem (Azadirachta indica A.Jusieu)[J].Current Science, 2007,92(10):1400-1406.
[5]	吴疆翀. 印楝繁育系统的研究[D]. 北京:中国林业科学研究院,2007.
[6]	彭兴民,吴疆翀, 郑益兴,等. 云南引种印楝实生种群的表型变异[J]. 植物生态学报, 2012,36(6):560-571.
[7]	彭兴民,吴疆翀,郑益兴,等. 云南引种印楝实生栽培种群表型的地理变异[J].林业科学研究,2013,26(4):399-405.
[8]	彭兴民,吴疆翀,程金焕,等. 印楝农药原料林优树选择方法与标准[J].福建林学院学报, 2010,30(3):265-269.
[9]	Sidhu O P, Kumar V, Behl H M. Variability in Neem (Azadirchta indica) with respect to azadirchtin content[J]. J Agri Food Chem, 2003,51(4): 910-915.
[10]	Tomar U K, Singh G, Kaushik N. Screening Azadirachta indica tree for enhancing azadirachtin and oil contents in dry areas of Gujarat[J]. Journal of Forestry Research, 2011, 22(2): 217-224.
[11]	Quinn G P, Keough M J. 生物实验设计与数据分析[M]. 蒋志刚,李春旺,曾岩,译. 北京: 高等教育出版社,2003.
[12]	Tan Y F, Corke H. Factor analysis of physicochemical properties of 63 rice varieties[J]. Journal of the Science of Food and Agriculture, 2002,82(7):745-752.
[13]	Toker C, Cagirgan M I. The use of phenotypic correlations and factor analysis in determining characters for grain yield selection in chickpea(Cicer arietinum L.)[J]. Hereditas, 2004,140(3): 226-228.
[14]	Kurtanjek Z, Horvat D, Magdic D, et al. Factor analysis and modelling for rapid quality assessment of croatian wheat cultivars with different gluten characteristics[J]. Food Technology and Biotechnology, 2008,46(3): 270-277.
[15]	敖妍.因子分析法在文冠果优良单株选择中的应用[J]. 华南农业大学学报, 2009,30(4):70-73.
[16]	马庆华,李永红,梁丽松,等. 冬枣优良单株果实品质的因子分析与综合评价[J]. 中国农业科学, 2010,43(12):2491-2499.
[17]	康立宁,田志刚,刘香英,等. 大豆组织蛋白产品品质的因子分析和综合评价研究[J]. 吉林农业科学, 2012,37(2):45-48.
[18]	宗乾收, 林军, 武永昆, 等. 印楝种仁中印楝素含量的快速液相色谱分析[J]. 农药, 2003,42(4):23-24.
[19]	阮敬. SAS统计分析从入门到精通[M]. 北京:人民邮电出版社出版,2009.
[20]	汤飞宇,程锦,黄文新,等. 高品质陆地棉数量性状的因子分析及品种聚类分析[J].江西农业大学学报, 2008,30(6):1014-1018.
[21]	柳伟伟,胡良平. 主成分分析与探索性因子分析的SAS软件实现[J]. 中西医结合学报, 2010,8(6):589-593.
[22]	胡建军. 烟叶质量评价方法优选与实证研究[D]. 长沙:湖南农业大学. 2009.
[23]	徐克学. 生物数学[M]. 北京: 科学出版社,1999.

Factor Analysis and Comprehensive Assessment of Phenotypic Selection of Officinal Neem Superior Trees

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