Surveying the relations among traits affecting seed yield in sesame (Sesamum indicum L.)
Abstract To determine the most important traits influencing seed yield of sesame, 18 lines were evaluated in a randomized block design with three replicates in two years during the 2013 and 2014 growing seasons. Following a combined analysis of variance, multivariate statistical analyses such as sim...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Ramazani, Seyyed Hamid Reza [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2016 |
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| Anmerkung: |
© Korean Society of Crop Science and Springer Science+Business Media Dordrecht 2016 |
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| Übergeordnetes Werk: |
Enthalten in: Journal of crop science and biotechnology - Seoul : Korean Soc. of Crop Science, 2009, 19(2016), 4 vom: Dez., Seite 303-309 |
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| Übergeordnetes Werk: |
volume:19 ; year:2016 ; number:4 ; month:12 ; pages:303-309 |
| Links: |
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| DOI / URN: |
10.1007/s12892-016-0053-0 |
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| Katalog-ID: |
SPR028281551 |
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| 520 | |a Abstract To determine the most important traits influencing seed yield of sesame, 18 lines were evaluated in a randomized block design with three replicates in two years during the 2013 and 2014 growing seasons. Following a combined analysis of variance, multivariate statistical analyses such as simple correlation coefficients, factor analysis, stepwise analysis, path analysis, and cluster analysis were administered on combined means. The correlation coefficient analysis showed a significant negative correlation between seed yield and number of capsules per plant and number of seeds per capsule. Correlation between germination period and seed yield was positive and significant at 5% probability level. Factor analysis divided the 14 measured variables into five factors. In the stepwise regression analysis for seed yield as the independent variable, four traits including number of capsules per plant, first capsule height, number of seeds per capsule, and stem length to first capsule were entered into the regression model in four steps with $ r^{2} $ =0.72. The regression coefficient of number of capsules per plant, number of seeds per capsule, and stem length to first capsule were negative and the regression coefficient of the first capsule height was positive and significant at the 5% probability level. The path coefficient analysis based on seed yield as a dependent variable implicated that the number of seeds per capsule had the highest negative direct effect on seed yield. The highest negative indirect effect on seed yield was related to the number of capsules per plant through the number of seeds per capsule. Cluster analysis using Ward’s method divided 18 investigated lines into five clusters. | ||
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10.1007/s12892-016-0053-0 doi (DE-627)SPR028281551 (SPR)s12892-016-0053-0-e DE-627 ger DE-627 rakwb eng Ramazani, Seyyed Hamid Reza verfasserin aut Surveying the relations among traits affecting seed yield in sesame (Sesamum indicum L.) 2016 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Korean Society of Crop Science and Springer Science+Business Media Dordrecht 2016 Abstract To determine the most important traits influencing seed yield of sesame, 18 lines were evaluated in a randomized block design with three replicates in two years during the 2013 and 2014 growing seasons. Following a combined analysis of variance, multivariate statistical analyses such as simple correlation coefficients, factor analysis, stepwise analysis, path analysis, and cluster analysis were administered on combined means. The correlation coefficient analysis showed a significant negative correlation between seed yield and number of capsules per plant and number of seeds per capsule. Correlation between germination period and seed yield was positive and significant at 5% probability level. Factor analysis divided the 14 measured variables into five factors. In the stepwise regression analysis for seed yield as the independent variable, four traits including number of capsules per plant, first capsule height, number of seeds per capsule, and stem length to first capsule were entered into the regression model in four steps with $ r^{2} $ =0.72. The regression coefficient of number of capsules per plant, number of seeds per capsule, and stem length to first capsule were negative and the regression coefficient of the first capsule height was positive and significant at the 5% probability level. The path coefficient analysis based on seed yield as a dependent variable implicated that the number of seeds per capsule had the highest negative direct effect on seed yield. The highest negative indirect effect on seed yield was related to the number of capsules per plant through the number of seeds per capsule. Cluster analysis using Ward’s method divided 18 investigated lines into five clusters. Enthalten in Journal of crop science and biotechnology Seoul : Korean Soc. of Crop Science, 2009 19(2016), 4 vom: Dez., Seite 303-309 (DE-627)617512175 (DE-600)2534833-4 2005-8276 nnns volume:19 year:2016 number:4 month:12 pages:303-309 https://dx.doi.org/10.1007/s12892-016-0053-0 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 19 2016 4 12 303-309 |
| spelling |
10.1007/s12892-016-0053-0 doi (DE-627)SPR028281551 (SPR)s12892-016-0053-0-e DE-627 ger DE-627 rakwb eng Ramazani, Seyyed Hamid Reza verfasserin aut Surveying the relations among traits affecting seed yield in sesame (Sesamum indicum L.) 2016 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Korean Society of Crop Science and Springer Science+Business Media Dordrecht 2016 Abstract To determine the most important traits influencing seed yield of sesame, 18 lines were evaluated in a randomized block design with three replicates in two years during the 2013 and 2014 growing seasons. Following a combined analysis of variance, multivariate statistical analyses such as simple correlation coefficients, factor analysis, stepwise analysis, path analysis, and cluster analysis were administered on combined means. The correlation coefficient analysis showed a significant negative correlation between seed yield and number of capsules per plant and number of seeds per capsule. Correlation between germination period and seed yield was positive and significant at 5% probability level. Factor analysis divided the 14 measured variables into five factors. In the stepwise regression analysis for seed yield as the independent variable, four traits including number of capsules per plant, first capsule height, number of seeds per capsule, and stem length to first capsule were entered into the regression model in four steps with $ r^{2} $ =0.72. The regression coefficient of number of capsules per plant, number of seeds per capsule, and stem length to first capsule were negative and the regression coefficient of the first capsule height was positive and significant at the 5% probability level. The path coefficient analysis based on seed yield as a dependent variable implicated that the number of seeds per capsule had the highest negative direct effect on seed yield. The highest negative indirect effect on seed yield was related to the number of capsules per plant through the number of seeds per capsule. Cluster analysis using Ward’s method divided 18 investigated lines into five clusters. Enthalten in Journal of crop science and biotechnology Seoul : Korean Soc. of Crop Science, 2009 19(2016), 4 vom: Dez., Seite 303-309 (DE-627)617512175 (DE-600)2534833-4 2005-8276 nnns volume:19 year:2016 number:4 month:12 pages:303-309 https://dx.doi.org/10.1007/s12892-016-0053-0 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 19 2016 4 12 303-309 |
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10.1007/s12892-016-0053-0 doi (DE-627)SPR028281551 (SPR)s12892-016-0053-0-e DE-627 ger DE-627 rakwb eng Ramazani, Seyyed Hamid Reza verfasserin aut Surveying the relations among traits affecting seed yield in sesame (Sesamum indicum L.) 2016 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Korean Society of Crop Science and Springer Science+Business Media Dordrecht 2016 Abstract To determine the most important traits influencing seed yield of sesame, 18 lines were evaluated in a randomized block design with three replicates in two years during the 2013 and 2014 growing seasons. Following a combined analysis of variance, multivariate statistical analyses such as simple correlation coefficients, factor analysis, stepwise analysis, path analysis, and cluster analysis were administered on combined means. The correlation coefficient analysis showed a significant negative correlation between seed yield and number of capsules per plant and number of seeds per capsule. Correlation between germination period and seed yield was positive and significant at 5% probability level. Factor analysis divided the 14 measured variables into five factors. In the stepwise regression analysis for seed yield as the independent variable, four traits including number of capsules per plant, first capsule height, number of seeds per capsule, and stem length to first capsule were entered into the regression model in four steps with $ r^{2} $ =0.72. The regression coefficient of number of capsules per plant, number of seeds per capsule, and stem length to first capsule were negative and the regression coefficient of the first capsule height was positive and significant at the 5% probability level. The path coefficient analysis based on seed yield as a dependent variable implicated that the number of seeds per capsule had the highest negative direct effect on seed yield. The highest negative indirect effect on seed yield was related to the number of capsules per plant through the number of seeds per capsule. Cluster analysis using Ward’s method divided 18 investigated lines into five clusters. Enthalten in Journal of crop science and biotechnology Seoul : Korean Soc. of Crop Science, 2009 19(2016), 4 vom: Dez., Seite 303-309 (DE-627)617512175 (DE-600)2534833-4 2005-8276 nnns volume:19 year:2016 number:4 month:12 pages:303-309 https://dx.doi.org/10.1007/s12892-016-0053-0 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 19 2016 4 12 303-309 |
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10.1007/s12892-016-0053-0 doi (DE-627)SPR028281551 (SPR)s12892-016-0053-0-e DE-627 ger DE-627 rakwb eng Ramazani, Seyyed Hamid Reza verfasserin aut Surveying the relations among traits affecting seed yield in sesame (Sesamum indicum L.) 2016 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Korean Society of Crop Science and Springer Science+Business Media Dordrecht 2016 Abstract To determine the most important traits influencing seed yield of sesame, 18 lines were evaluated in a randomized block design with three replicates in two years during the 2013 and 2014 growing seasons. Following a combined analysis of variance, multivariate statistical analyses such as simple correlation coefficients, factor analysis, stepwise analysis, path analysis, and cluster analysis were administered on combined means. The correlation coefficient analysis showed a significant negative correlation between seed yield and number of capsules per plant and number of seeds per capsule. Correlation between germination period and seed yield was positive and significant at 5% probability level. Factor analysis divided the 14 measured variables into five factors. In the stepwise regression analysis for seed yield as the independent variable, four traits including number of capsules per plant, first capsule height, number of seeds per capsule, and stem length to first capsule were entered into the regression model in four steps with $ r^{2} $ =0.72. The regression coefficient of number of capsules per plant, number of seeds per capsule, and stem length to first capsule were negative and the regression coefficient of the first capsule height was positive and significant at the 5% probability level. The path coefficient analysis based on seed yield as a dependent variable implicated that the number of seeds per capsule had the highest negative direct effect on seed yield. The highest negative indirect effect on seed yield was related to the number of capsules per plant through the number of seeds per capsule. Cluster analysis using Ward’s method divided 18 investigated lines into five clusters. Enthalten in Journal of crop science and biotechnology Seoul : Korean Soc. of Crop Science, 2009 19(2016), 4 vom: Dez., Seite 303-309 (DE-627)617512175 (DE-600)2534833-4 2005-8276 nnns volume:19 year:2016 number:4 month:12 pages:303-309 https://dx.doi.org/10.1007/s12892-016-0053-0 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 19 2016 4 12 303-309 |
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10.1007/s12892-016-0053-0 doi (DE-627)SPR028281551 (SPR)s12892-016-0053-0-e DE-627 ger DE-627 rakwb eng Ramazani, Seyyed Hamid Reza verfasserin aut Surveying the relations among traits affecting seed yield in sesame (Sesamum indicum L.) 2016 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Korean Society of Crop Science and Springer Science+Business Media Dordrecht 2016 Abstract To determine the most important traits influencing seed yield of sesame, 18 lines were evaluated in a randomized block design with three replicates in two years during the 2013 and 2014 growing seasons. Following a combined analysis of variance, multivariate statistical analyses such as simple correlation coefficients, factor analysis, stepwise analysis, path analysis, and cluster analysis were administered on combined means. The correlation coefficient analysis showed a significant negative correlation between seed yield and number of capsules per plant and number of seeds per capsule. Correlation between germination period and seed yield was positive and significant at 5% probability level. Factor analysis divided the 14 measured variables into five factors. In the stepwise regression analysis for seed yield as the independent variable, four traits including number of capsules per plant, first capsule height, number of seeds per capsule, and stem length to first capsule were entered into the regression model in four steps with $ r^{2} $ =0.72. The regression coefficient of number of capsules per plant, number of seeds per capsule, and stem length to first capsule were negative and the regression coefficient of the first capsule height was positive and significant at the 5% probability level. The path coefficient analysis based on seed yield as a dependent variable implicated that the number of seeds per capsule had the highest negative direct effect on seed yield. The highest negative indirect effect on seed yield was related to the number of capsules per plant through the number of seeds per capsule. Cluster analysis using Ward’s method divided 18 investigated lines into five clusters. Enthalten in Journal of crop science and biotechnology Seoul : Korean Soc. of Crop Science, 2009 19(2016), 4 vom: Dez., Seite 303-309 (DE-627)617512175 (DE-600)2534833-4 2005-8276 nnns volume:19 year:2016 number:4 month:12 pages:303-309 https://dx.doi.org/10.1007/s12892-016-0053-0 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 19 2016 4 12 303-309 |
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Ramazani, Seyyed Hamid Reza |
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Ramazani, Seyyed Hamid Reza Surveying the relations among traits affecting seed yield in sesame (Sesamum indicum L.) |
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surveying the relations among traits affecting seed yield in sesame (sesamum indicum l.) |
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Surveying the relations among traits affecting seed yield in sesame (Sesamum indicum L.) |
| abstract |
Abstract To determine the most important traits influencing seed yield of sesame, 18 lines were evaluated in a randomized block design with three replicates in two years during the 2013 and 2014 growing seasons. Following a combined analysis of variance, multivariate statistical analyses such as simple correlation coefficients, factor analysis, stepwise analysis, path analysis, and cluster analysis were administered on combined means. The correlation coefficient analysis showed a significant negative correlation between seed yield and number of capsules per plant and number of seeds per capsule. Correlation between germination period and seed yield was positive and significant at 5% probability level. Factor analysis divided the 14 measured variables into five factors. In the stepwise regression analysis for seed yield as the independent variable, four traits including number of capsules per plant, first capsule height, number of seeds per capsule, and stem length to first capsule were entered into the regression model in four steps with $ r^{2} $ =0.72. The regression coefficient of number of capsules per plant, number of seeds per capsule, and stem length to first capsule were negative and the regression coefficient of the first capsule height was positive and significant at the 5% probability level. The path coefficient analysis based on seed yield as a dependent variable implicated that the number of seeds per capsule had the highest negative direct effect on seed yield. The highest negative indirect effect on seed yield was related to the number of capsules per plant through the number of seeds per capsule. Cluster analysis using Ward’s method divided 18 investigated lines into five clusters. © Korean Society of Crop Science and Springer Science+Business Media Dordrecht 2016 |
| abstractGer |
Abstract To determine the most important traits influencing seed yield of sesame, 18 lines were evaluated in a randomized block design with three replicates in two years during the 2013 and 2014 growing seasons. Following a combined analysis of variance, multivariate statistical analyses such as simple correlation coefficients, factor analysis, stepwise analysis, path analysis, and cluster analysis were administered on combined means. The correlation coefficient analysis showed a significant negative correlation between seed yield and number of capsules per plant and number of seeds per capsule. Correlation between germination period and seed yield was positive and significant at 5% probability level. Factor analysis divided the 14 measured variables into five factors. In the stepwise regression analysis for seed yield as the independent variable, four traits including number of capsules per plant, first capsule height, number of seeds per capsule, and stem length to first capsule were entered into the regression model in four steps with $ r^{2} $ =0.72. The regression coefficient of number of capsules per plant, number of seeds per capsule, and stem length to first capsule were negative and the regression coefficient of the first capsule height was positive and significant at the 5% probability level. The path coefficient analysis based on seed yield as a dependent variable implicated that the number of seeds per capsule had the highest negative direct effect on seed yield. The highest negative indirect effect on seed yield was related to the number of capsules per plant through the number of seeds per capsule. Cluster analysis using Ward’s method divided 18 investigated lines into five clusters. © Korean Society of Crop Science and Springer Science+Business Media Dordrecht 2016 |
| abstract_unstemmed |
Abstract To determine the most important traits influencing seed yield of sesame, 18 lines were evaluated in a randomized block design with three replicates in two years during the 2013 and 2014 growing seasons. Following a combined analysis of variance, multivariate statistical analyses such as simple correlation coefficients, factor analysis, stepwise analysis, path analysis, and cluster analysis were administered on combined means. The correlation coefficient analysis showed a significant negative correlation between seed yield and number of capsules per plant and number of seeds per capsule. Correlation between germination period and seed yield was positive and significant at 5% probability level. Factor analysis divided the 14 measured variables into five factors. In the stepwise regression analysis for seed yield as the independent variable, four traits including number of capsules per plant, first capsule height, number of seeds per capsule, and stem length to first capsule were entered into the regression model in four steps with $ r^{2} $ =0.72. The regression coefficient of number of capsules per plant, number of seeds per capsule, and stem length to first capsule were negative and the regression coefficient of the first capsule height was positive and significant at the 5% probability level. The path coefficient analysis based on seed yield as a dependent variable implicated that the number of seeds per capsule had the highest negative direct effect on seed yield. The highest negative indirect effect on seed yield was related to the number of capsules per plant through the number of seeds per capsule. Cluster analysis using Ward’s method divided 18 investigated lines into five clusters. © Korean Society of Crop Science and Springer Science+Business Media Dordrecht 2016 |
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Surveying the relations among traits affecting seed yield in sesame (Sesamum indicum L.) |
| url |
https://dx.doi.org/10.1007/s12892-016-0053-0 |
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| doi_str |
10.1007/s12892-016-0053-0 |
| up_date |
2024-07-03T18:27:26.058Z |
| _version_ |
1803583483869659136 |
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Following a combined analysis of variance, multivariate statistical analyses such as simple correlation coefficients, factor analysis, stepwise analysis, path analysis, and cluster analysis were administered on combined means. The correlation coefficient analysis showed a significant negative correlation between seed yield and number of capsules per plant and number of seeds per capsule. Correlation between germination period and seed yield was positive and significant at 5% probability level. Factor analysis divided the 14 measured variables into five factors. In the stepwise regression analysis for seed yield as the independent variable, four traits including number of capsules per plant, first capsule height, number of seeds per capsule, and stem length to first capsule were entered into the regression model in four steps with $ r^{2} $ =0.72. The regression coefficient of number of capsules per plant, number of seeds per capsule, and stem length to first capsule were negative and the regression coefficient of the first capsule height was positive and significant at the 5% probability level. The path coefficient analysis based on seed yield as a dependent variable implicated that the number of seeds per capsule had the highest negative direct effect on seed yield. The highest negative indirect effect on seed yield was related to the number of capsules per plant through the number of seeds per capsule. 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