Heterotic responses among crosses of IITA and CIMMYT early white maize inbred lines under multiple stress environments
Abstract Two major constraints militating against the achievement of food security in West Africa (WA) are recurrent drought and poor soil fertility. Seventeen early maturing maize inbreds from IITA and CIMMYT were used as parents to produce 136 diallel crosses which were evaluated along with four c...
Ausführliche Beschreibung
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| Autor*in: |
Badu-Apraku, B. [verfasserIn] Fakorede, M. A. B. [verfasserIn] Gedil, M. [verfasserIn] Talabi, A. O. [verfasserIn] Annor, B. [verfasserIn] Oyekunle, M. [verfasserIn] Akinwale, R. O. [verfasserIn] Fasanmade, T. Y. [verfasserIn] Akaogu, I. C. [verfasserIn] Aderounmu, M. [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2015 |
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| Schlagwörter: |
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| Übergeordnetes Werk: |
Enthalten in: Euphytica - Dordrecht [u.a.] : Springer Science + Business Media B.V., 1952, 206(2015), 1 vom: 03. Juli, Seite 245-262 |
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| Übergeordnetes Werk: |
volume:206 ; year:2015 ; number:1 ; day:03 ; month:07 ; pages:245-262 |
| Links: |
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| DOI / URN: |
10.1007/s10681-015-1506-0 |
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| Katalog-ID: |
SPR012427756 |
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| 520 | |a Abstract Two major constraints militating against the achievement of food security in West Africa (WA) are recurrent drought and poor soil fertility. Seventeen early maturing maize inbreds from IITA and CIMMYT were used as parents to produce 136 diallel crosses which were evaluated along with four checks in contrasting environments at four locations for 2 year in Nigeria. The objectives of the study were to (i) examine the combining ability of the lines under drought, low soil nitrogen (low N), optimal and across environments; (ii) classify the inbreds into heterotic groups using the specific combining ability (SCA) effects of grain yield, heterotic group’s specific and general combining ability (HSGCA), the heterotic grouping based on general combining ability (GCA) of multiple traits (HGCAMT) and the molecular-based genetic distance methods; (iii) compare the efficiencies of the four heterotic grouping methods in classifying the inbreds and identifying the best testers; and (iv) examine the performance of the inbreds in hybrid combinations across environments. Sum of squares for GCA of inbreds for grain yield and other measured traits were larger than those of the SCA in all environments. The relative importance of GCA to SCA effects for grain yield and other traits increased from stress to nonstress environments with the additive genetic effects accounting for the major portion of the total genetic variation under all research environments. The HSGCA method classified the lines into three groups and was the most efficient because it had the highest breeding efficiency (40 %) in the test environments followed by the HGCAMT, SNP marker-based and the SCA effects of grain yield methods. Inbred TZEI 19 was identified as the best tester across research environments based on HSGCA method. Hybrids ENT 11 × TZEI 19 and TZEI 1 × TZEI 19 were the most outstanding and should be tested extensively in on-farm trials and commercialized. | ||
| 650 | 4 | |a L. |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Heterotic grouping |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Low-soil nitrogen |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Drought tolerance |7 (dpeaa)DE-He213 | |
| 700 | 1 | |a Fakorede, M. A. B. |e verfasserin |4 aut | |
| 700 | 1 | |a Gedil, M. |e verfasserin |4 aut | |
| 700 | 1 | |a Talabi, A. O. |e verfasserin |4 aut | |
| 700 | 1 | |a Annor, B. |e verfasserin |4 aut | |
| 700 | 1 | |a Oyekunle, M. |e verfasserin |4 aut | |
| 700 | 1 | |a Akinwale, R. O. |e verfasserin |4 aut | |
| 700 | 1 | |a Fasanmade, T. Y. |e verfasserin |4 aut | |
| 700 | 1 | |a Akaogu, I. C. |e verfasserin |4 aut | |
| 700 | 1 | |a Aderounmu, M. |e verfasserin |4 aut | |
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10.1007/s10681-015-1506-0 doi (DE-627)SPR012427756 (SPR)s10681-015-1506-0-e DE-627 ger DE-627 rakwb eng 630 640 ASE 48.58 bkl Badu-Apraku, B. verfasserin aut Heterotic responses among crosses of IITA and CIMMYT early white maize inbred lines under multiple stress environments 2015 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Two major constraints militating against the achievement of food security in West Africa (WA) are recurrent drought and poor soil fertility. Seventeen early maturing maize inbreds from IITA and CIMMYT were used as parents to produce 136 diallel crosses which were evaluated along with four checks in contrasting environments at four locations for 2 year in Nigeria. The objectives of the study were to (i) examine the combining ability of the lines under drought, low soil nitrogen (low N), optimal and across environments; (ii) classify the inbreds into heterotic groups using the specific combining ability (SCA) effects of grain yield, heterotic group’s specific and general combining ability (HSGCA), the heterotic grouping based on general combining ability (GCA) of multiple traits (HGCAMT) and the molecular-based genetic distance methods; (iii) compare the efficiencies of the four heterotic grouping methods in classifying the inbreds and identifying the best testers; and (iv) examine the performance of the inbreds in hybrid combinations across environments. Sum of squares for GCA of inbreds for grain yield and other measured traits were larger than those of the SCA in all environments. The relative importance of GCA to SCA effects for grain yield and other traits increased from stress to nonstress environments with the additive genetic effects accounting for the major portion of the total genetic variation under all research environments. The HSGCA method classified the lines into three groups and was the most efficient because it had the highest breeding efficiency (40 %) in the test environments followed by the HGCAMT, SNP marker-based and the SCA effects of grain yield methods. Inbred TZEI 19 was identified as the best tester across research environments based on HSGCA method. Hybrids ENT 11 × TZEI 19 and TZEI 1 × TZEI 19 were the most outstanding and should be tested extensively in on-farm trials and commercialized. L. (dpeaa)DE-He213 Heterotic grouping (dpeaa)DE-He213 Low-soil nitrogen (dpeaa)DE-He213 Drought tolerance (dpeaa)DE-He213 Fakorede, M. A. B. verfasserin aut Gedil, M. verfasserin aut Talabi, A. O. verfasserin aut Annor, B. verfasserin aut Oyekunle, M. verfasserin aut Akinwale, R. O. verfasserin aut Fasanmade, T. Y. verfasserin aut Akaogu, I. C. verfasserin aut Aderounmu, M. verfasserin aut Enthalten in Euphytica Dordrecht [u.a.] : Springer Science + Business Media B.V., 1952 206(2015), 1 vom: 03. Juli, Seite 245-262 (DE-627)312840098 (DE-600)2012322-X 1573-5060 nnns volume:206 year:2015 number:1 day:03 month:07 pages:245-262 https://dx.doi.org/10.1007/s10681-015-1506-0 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER 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_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_206 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_647 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_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 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_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 48.58 ASE AR 206 2015 1 03 07 245-262 |
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10.1007/s10681-015-1506-0 doi (DE-627)SPR012427756 (SPR)s10681-015-1506-0-e DE-627 ger DE-627 rakwb eng 630 640 ASE 48.58 bkl Badu-Apraku, B. verfasserin aut Heterotic responses among crosses of IITA and CIMMYT early white maize inbred lines under multiple stress environments 2015 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Two major constraints militating against the achievement of food security in West Africa (WA) are recurrent drought and poor soil fertility. Seventeen early maturing maize inbreds from IITA and CIMMYT were used as parents to produce 136 diallel crosses which were evaluated along with four checks in contrasting environments at four locations for 2 year in Nigeria. The objectives of the study were to (i) examine the combining ability of the lines under drought, low soil nitrogen (low N), optimal and across environments; (ii) classify the inbreds into heterotic groups using the specific combining ability (SCA) effects of grain yield, heterotic group’s specific and general combining ability (HSGCA), the heterotic grouping based on general combining ability (GCA) of multiple traits (HGCAMT) and the molecular-based genetic distance methods; (iii) compare the efficiencies of the four heterotic grouping methods in classifying the inbreds and identifying the best testers; and (iv) examine the performance of the inbreds in hybrid combinations across environments. Sum of squares for GCA of inbreds for grain yield and other measured traits were larger than those of the SCA in all environments. The relative importance of GCA to SCA effects for grain yield and other traits increased from stress to nonstress environments with the additive genetic effects accounting for the major portion of the total genetic variation under all research environments. The HSGCA method classified the lines into three groups and was the most efficient because it had the highest breeding efficiency (40 %) in the test environments followed by the HGCAMT, SNP marker-based and the SCA effects of grain yield methods. Inbred TZEI 19 was identified as the best tester across research environments based on HSGCA method. Hybrids ENT 11 × TZEI 19 and TZEI 1 × TZEI 19 were the most outstanding and should be tested extensively in on-farm trials and commercialized. L. (dpeaa)DE-He213 Heterotic grouping (dpeaa)DE-He213 Low-soil nitrogen (dpeaa)DE-He213 Drought tolerance (dpeaa)DE-He213 Fakorede, M. A. B. verfasserin aut Gedil, M. verfasserin aut Talabi, A. O. verfasserin aut Annor, B. verfasserin aut Oyekunle, M. verfasserin aut Akinwale, R. O. verfasserin aut Fasanmade, T. Y. verfasserin aut Akaogu, I. C. verfasserin aut Aderounmu, M. verfasserin aut Enthalten in Euphytica Dordrecht [u.a.] : Springer Science + Business Media B.V., 1952 206(2015), 1 vom: 03. Juli, Seite 245-262 (DE-627)312840098 (DE-600)2012322-X 1573-5060 nnns volume:206 year:2015 number:1 day:03 month:07 pages:245-262 https://dx.doi.org/10.1007/s10681-015-1506-0 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER 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_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_206 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_647 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_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 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_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 48.58 ASE AR 206 2015 1 03 07 245-262 |
| allfields_unstemmed |
10.1007/s10681-015-1506-0 doi (DE-627)SPR012427756 (SPR)s10681-015-1506-0-e DE-627 ger DE-627 rakwb eng 630 640 ASE 48.58 bkl Badu-Apraku, B. verfasserin aut Heterotic responses among crosses of IITA and CIMMYT early white maize inbred lines under multiple stress environments 2015 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Two major constraints militating against the achievement of food security in West Africa (WA) are recurrent drought and poor soil fertility. Seventeen early maturing maize inbreds from IITA and CIMMYT were used as parents to produce 136 diallel crosses which were evaluated along with four checks in contrasting environments at four locations for 2 year in Nigeria. The objectives of the study were to (i) examine the combining ability of the lines under drought, low soil nitrogen (low N), optimal and across environments; (ii) classify the inbreds into heterotic groups using the specific combining ability (SCA) effects of grain yield, heterotic group’s specific and general combining ability (HSGCA), the heterotic grouping based on general combining ability (GCA) of multiple traits (HGCAMT) and the molecular-based genetic distance methods; (iii) compare the efficiencies of the four heterotic grouping methods in classifying the inbreds and identifying the best testers; and (iv) examine the performance of the inbreds in hybrid combinations across environments. Sum of squares for GCA of inbreds for grain yield and other measured traits were larger than those of the SCA in all environments. The relative importance of GCA to SCA effects for grain yield and other traits increased from stress to nonstress environments with the additive genetic effects accounting for the major portion of the total genetic variation under all research environments. The HSGCA method classified the lines into three groups and was the most efficient because it had the highest breeding efficiency (40 %) in the test environments followed by the HGCAMT, SNP marker-based and the SCA effects of grain yield methods. Inbred TZEI 19 was identified as the best tester across research environments based on HSGCA method. Hybrids ENT 11 × TZEI 19 and TZEI 1 × TZEI 19 were the most outstanding and should be tested extensively in on-farm trials and commercialized. L. (dpeaa)DE-He213 Heterotic grouping (dpeaa)DE-He213 Low-soil nitrogen (dpeaa)DE-He213 Drought tolerance (dpeaa)DE-He213 Fakorede, M. A. B. verfasserin aut Gedil, M. verfasserin aut Talabi, A. O. verfasserin aut Annor, B. verfasserin aut Oyekunle, M. verfasserin aut Akinwale, R. O. verfasserin aut Fasanmade, T. Y. verfasserin aut Akaogu, I. C. verfasserin aut Aderounmu, M. verfasserin aut Enthalten in Euphytica Dordrecht [u.a.] : Springer Science + Business Media B.V., 1952 206(2015), 1 vom: 03. Juli, Seite 245-262 (DE-627)312840098 (DE-600)2012322-X 1573-5060 nnns volume:206 year:2015 number:1 day:03 month:07 pages:245-262 https://dx.doi.org/10.1007/s10681-015-1506-0 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER 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_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_206 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_647 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_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 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_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 48.58 ASE AR 206 2015 1 03 07 245-262 |
| allfieldsGer |
10.1007/s10681-015-1506-0 doi (DE-627)SPR012427756 (SPR)s10681-015-1506-0-e DE-627 ger DE-627 rakwb eng 630 640 ASE 48.58 bkl Badu-Apraku, B. verfasserin aut Heterotic responses among crosses of IITA and CIMMYT early white maize inbred lines under multiple stress environments 2015 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Two major constraints militating against the achievement of food security in West Africa (WA) are recurrent drought and poor soil fertility. Seventeen early maturing maize inbreds from IITA and CIMMYT were used as parents to produce 136 diallel crosses which were evaluated along with four checks in contrasting environments at four locations for 2 year in Nigeria. The objectives of the study were to (i) examine the combining ability of the lines under drought, low soil nitrogen (low N), optimal and across environments; (ii) classify the inbreds into heterotic groups using the specific combining ability (SCA) effects of grain yield, heterotic group’s specific and general combining ability (HSGCA), the heterotic grouping based on general combining ability (GCA) of multiple traits (HGCAMT) and the molecular-based genetic distance methods; (iii) compare the efficiencies of the four heterotic grouping methods in classifying the inbreds and identifying the best testers; and (iv) examine the performance of the inbreds in hybrid combinations across environments. Sum of squares for GCA of inbreds for grain yield and other measured traits were larger than those of the SCA in all environments. The relative importance of GCA to SCA effects for grain yield and other traits increased from stress to nonstress environments with the additive genetic effects accounting for the major portion of the total genetic variation under all research environments. The HSGCA method classified the lines into three groups and was the most efficient because it had the highest breeding efficiency (40 %) in the test environments followed by the HGCAMT, SNP marker-based and the SCA effects of grain yield methods. Inbred TZEI 19 was identified as the best tester across research environments based on HSGCA method. Hybrids ENT 11 × TZEI 19 and TZEI 1 × TZEI 19 were the most outstanding and should be tested extensively in on-farm trials and commercialized. L. (dpeaa)DE-He213 Heterotic grouping (dpeaa)DE-He213 Low-soil nitrogen (dpeaa)DE-He213 Drought tolerance (dpeaa)DE-He213 Fakorede, M. A. B. verfasserin aut Gedil, M. verfasserin aut Talabi, A. O. verfasserin aut Annor, B. verfasserin aut Oyekunle, M. verfasserin aut Akinwale, R. O. verfasserin aut Fasanmade, T. Y. verfasserin aut Akaogu, I. C. verfasserin aut Aderounmu, M. verfasserin aut Enthalten in Euphytica Dordrecht [u.a.] : Springer Science + Business Media B.V., 1952 206(2015), 1 vom: 03. Juli, Seite 245-262 (DE-627)312840098 (DE-600)2012322-X 1573-5060 nnns volume:206 year:2015 number:1 day:03 month:07 pages:245-262 https://dx.doi.org/10.1007/s10681-015-1506-0 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER 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_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_206 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_647 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_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 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_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 48.58 ASE AR 206 2015 1 03 07 245-262 |
| allfieldsSound |
10.1007/s10681-015-1506-0 doi (DE-627)SPR012427756 (SPR)s10681-015-1506-0-e DE-627 ger DE-627 rakwb eng 630 640 ASE 48.58 bkl Badu-Apraku, B. verfasserin aut Heterotic responses among crosses of IITA and CIMMYT early white maize inbred lines under multiple stress environments 2015 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Two major constraints militating against the achievement of food security in West Africa (WA) are recurrent drought and poor soil fertility. Seventeen early maturing maize inbreds from IITA and CIMMYT were used as parents to produce 136 diallel crosses which were evaluated along with four checks in contrasting environments at four locations for 2 year in Nigeria. The objectives of the study were to (i) examine the combining ability of the lines under drought, low soil nitrogen (low N), optimal and across environments; (ii) classify the inbreds into heterotic groups using the specific combining ability (SCA) effects of grain yield, heterotic group’s specific and general combining ability (HSGCA), the heterotic grouping based on general combining ability (GCA) of multiple traits (HGCAMT) and the molecular-based genetic distance methods; (iii) compare the efficiencies of the four heterotic grouping methods in classifying the inbreds and identifying the best testers; and (iv) examine the performance of the inbreds in hybrid combinations across environments. Sum of squares for GCA of inbreds for grain yield and other measured traits were larger than those of the SCA in all environments. The relative importance of GCA to SCA effects for grain yield and other traits increased from stress to nonstress environments with the additive genetic effects accounting for the major portion of the total genetic variation under all research environments. The HSGCA method classified the lines into three groups and was the most efficient because it had the highest breeding efficiency (40 %) in the test environments followed by the HGCAMT, SNP marker-based and the SCA effects of grain yield methods. Inbred TZEI 19 was identified as the best tester across research environments based on HSGCA method. Hybrids ENT 11 × TZEI 19 and TZEI 1 × TZEI 19 were the most outstanding and should be tested extensively in on-farm trials and commercialized. L. (dpeaa)DE-He213 Heterotic grouping (dpeaa)DE-He213 Low-soil nitrogen (dpeaa)DE-He213 Drought tolerance (dpeaa)DE-He213 Fakorede, M. A. B. verfasserin aut Gedil, M. verfasserin aut Talabi, A. O. verfasserin aut Annor, B. verfasserin aut Oyekunle, M. verfasserin aut Akinwale, R. O. verfasserin aut Fasanmade, T. Y. verfasserin aut Akaogu, I. C. verfasserin aut Aderounmu, M. verfasserin aut Enthalten in Euphytica Dordrecht [u.a.] : Springer Science + Business Media B.V., 1952 206(2015), 1 vom: 03. Juli, Seite 245-262 (DE-627)312840098 (DE-600)2012322-X 1573-5060 nnns volume:206 year:2015 number:1 day:03 month:07 pages:245-262 https://dx.doi.org/10.1007/s10681-015-1506-0 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER 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_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_206 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_647 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_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 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_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 48.58 ASE AR 206 2015 1 03 07 245-262 |
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Enthalten in Euphytica 206(2015), 1 vom: 03. Juli, Seite 245-262 volume:206 year:2015 number:1 day:03 month:07 pages:245-262 |
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Badu-Apraku, B. @@aut@@ Fakorede, M. A. B. @@aut@@ Gedil, M. @@aut@@ Talabi, A. O. @@aut@@ Annor, B. @@aut@@ Oyekunle, M. @@aut@@ Akinwale, R. O. @@aut@@ Fasanmade, T. Y. @@aut@@ Akaogu, I. C. @@aut@@ Aderounmu, M. @@aut@@ |
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Badu-Apraku, B. |
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Badu-Apraku, B. ddc 630 bkl 48.58 misc L. misc Heterotic grouping misc Low-soil nitrogen misc Drought tolerance Heterotic responses among crosses of IITA and CIMMYT early white maize inbred lines under multiple stress environments |
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630 640 ASE 48.58 bkl Heterotic responses among crosses of IITA and CIMMYT early white maize inbred lines under multiple stress environments L. (dpeaa)DE-He213 Heterotic grouping (dpeaa)DE-He213 Low-soil nitrogen (dpeaa)DE-He213 Drought tolerance (dpeaa)DE-He213 |
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ddc 630 bkl 48.58 misc L. misc Heterotic grouping misc Low-soil nitrogen misc Drought tolerance |
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Heterotic responses among crosses of IITA and CIMMYT early white maize inbred lines under multiple stress environments |
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Heterotic responses among crosses of IITA and CIMMYT early white maize inbred lines under multiple stress environments |
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Badu-Apraku, B. |
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Badu-Apraku, B. Fakorede, M. A. B. Gedil, M. Talabi, A. O. Annor, B. Oyekunle, M. Akinwale, R. O. Fasanmade, T. Y. Akaogu, I. C. Aderounmu, M. |
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heterotic responses among crosses of iita and cimmyt early white maize inbred lines under multiple stress environments |
| title_auth |
Heterotic responses among crosses of IITA and CIMMYT early white maize inbred lines under multiple stress environments |
| abstract |
Abstract Two major constraints militating against the achievement of food security in West Africa (WA) are recurrent drought and poor soil fertility. Seventeen early maturing maize inbreds from IITA and CIMMYT were used as parents to produce 136 diallel crosses which were evaluated along with four checks in contrasting environments at four locations for 2 year in Nigeria. The objectives of the study were to (i) examine the combining ability of the lines under drought, low soil nitrogen (low N), optimal and across environments; (ii) classify the inbreds into heterotic groups using the specific combining ability (SCA) effects of grain yield, heterotic group’s specific and general combining ability (HSGCA), the heterotic grouping based on general combining ability (GCA) of multiple traits (HGCAMT) and the molecular-based genetic distance methods; (iii) compare the efficiencies of the four heterotic grouping methods in classifying the inbreds and identifying the best testers; and (iv) examine the performance of the inbreds in hybrid combinations across environments. Sum of squares for GCA of inbreds for grain yield and other measured traits were larger than those of the SCA in all environments. The relative importance of GCA to SCA effects for grain yield and other traits increased from stress to nonstress environments with the additive genetic effects accounting for the major portion of the total genetic variation under all research environments. The HSGCA method classified the lines into three groups and was the most efficient because it had the highest breeding efficiency (40 %) in the test environments followed by the HGCAMT, SNP marker-based and the SCA effects of grain yield methods. Inbred TZEI 19 was identified as the best tester across research environments based on HSGCA method. Hybrids ENT 11 × TZEI 19 and TZEI 1 × TZEI 19 were the most outstanding and should be tested extensively in on-farm trials and commercialized. |
| abstractGer |
Abstract Two major constraints militating against the achievement of food security in West Africa (WA) are recurrent drought and poor soil fertility. Seventeen early maturing maize inbreds from IITA and CIMMYT were used as parents to produce 136 diallel crosses which were evaluated along with four checks in contrasting environments at four locations for 2 year in Nigeria. The objectives of the study were to (i) examine the combining ability of the lines under drought, low soil nitrogen (low N), optimal and across environments; (ii) classify the inbreds into heterotic groups using the specific combining ability (SCA) effects of grain yield, heterotic group’s specific and general combining ability (HSGCA), the heterotic grouping based on general combining ability (GCA) of multiple traits (HGCAMT) and the molecular-based genetic distance methods; (iii) compare the efficiencies of the four heterotic grouping methods in classifying the inbreds and identifying the best testers; and (iv) examine the performance of the inbreds in hybrid combinations across environments. Sum of squares for GCA of inbreds for grain yield and other measured traits were larger than those of the SCA in all environments. The relative importance of GCA to SCA effects for grain yield and other traits increased from stress to nonstress environments with the additive genetic effects accounting for the major portion of the total genetic variation under all research environments. The HSGCA method classified the lines into three groups and was the most efficient because it had the highest breeding efficiency (40 %) in the test environments followed by the HGCAMT, SNP marker-based and the SCA effects of grain yield methods. Inbred TZEI 19 was identified as the best tester across research environments based on HSGCA method. Hybrids ENT 11 × TZEI 19 and TZEI 1 × TZEI 19 were the most outstanding and should be tested extensively in on-farm trials and commercialized. |
| abstract_unstemmed |
Abstract Two major constraints militating against the achievement of food security in West Africa (WA) are recurrent drought and poor soil fertility. Seventeen early maturing maize inbreds from IITA and CIMMYT were used as parents to produce 136 diallel crosses which were evaluated along with four checks in contrasting environments at four locations for 2 year in Nigeria. The objectives of the study were to (i) examine the combining ability of the lines under drought, low soil nitrogen (low N), optimal and across environments; (ii) classify the inbreds into heterotic groups using the specific combining ability (SCA) effects of grain yield, heterotic group’s specific and general combining ability (HSGCA), the heterotic grouping based on general combining ability (GCA) of multiple traits (HGCAMT) and the molecular-based genetic distance methods; (iii) compare the efficiencies of the four heterotic grouping methods in classifying the inbreds and identifying the best testers; and (iv) examine the performance of the inbreds in hybrid combinations across environments. Sum of squares for GCA of inbreds for grain yield and other measured traits were larger than those of the SCA in all environments. The relative importance of GCA to SCA effects for grain yield and other traits increased from stress to nonstress environments with the additive genetic effects accounting for the major portion of the total genetic variation under all research environments. The HSGCA method classified the lines into three groups and was the most efficient because it had the highest breeding efficiency (40 %) in the test environments followed by the HGCAMT, SNP marker-based and the SCA effects of grain yield methods. Inbred TZEI 19 was identified as the best tester across research environments based on HSGCA method. Hybrids ENT 11 × TZEI 19 and TZEI 1 × TZEI 19 were the most outstanding and should be tested extensively in on-farm trials and commercialized. |
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<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a22002652 4500</leader><controlfield tag="001">SPR012427756</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20220110233712.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">201005s2015 xx |||||o 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1007/s10681-015-1506-0</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)SPR012427756</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(SPR)s10681-015-1506-0-e</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">630</subfield><subfield code="a">640</subfield><subfield code="q">ASE</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">48.58</subfield><subfield code="2">bkl</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Badu-Apraku, B.</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Heterotic responses among crosses of IITA and CIMMYT early white maize inbred lines under multiple stress environments</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2015</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">Computermedien</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Online-Ressource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Abstract Two major constraints militating against the achievement of food security in West Africa (WA) are recurrent drought and poor soil fertility. Seventeen early maturing maize inbreds from IITA and CIMMYT were used as parents to produce 136 diallel crosses which were evaluated along with four checks in contrasting environments at four locations for 2 year in Nigeria. The objectives of the study were to (i) examine the combining ability of the lines under drought, low soil nitrogen (low N), optimal and across environments; (ii) classify the inbreds into heterotic groups using the specific combining ability (SCA) effects of grain yield, heterotic group’s specific and general combining ability (HSGCA), the heterotic grouping based on general combining ability (GCA) of multiple traits (HGCAMT) and the molecular-based genetic distance methods; (iii) compare the efficiencies of the four heterotic grouping methods in classifying the inbreds and identifying the best testers; and (iv) examine the performance of the inbreds in hybrid combinations across environments. Sum of squares for GCA of inbreds for grain yield and other measured traits were larger than those of the SCA in all environments. The relative importance of GCA to SCA effects for grain yield and other traits increased from stress to nonstress environments with the additive genetic effects accounting for the major portion of the total genetic variation under all research environments. The HSGCA method classified the lines into three groups and was the most efficient because it had the highest breeding efficiency (40 %) in the test environments followed by the HGCAMT, SNP marker-based and the SCA effects of grain yield methods. Inbred TZEI 19 was identified as the best tester across research environments based on HSGCA method. Hybrids ENT 11 × TZEI 19 and TZEI 1 × TZEI 19 were the most outstanding and should be tested extensively in on-farm trials and commercialized.</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">L.</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Heterotic grouping</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Low-soil nitrogen</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Drought tolerance</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Fakorede, M. A. B.</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Gedil, M.</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Talabi, A. O.</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Annor, B.</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Oyekunle, M.</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Akinwale, R. 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Juli, Seite 245-262</subfield><subfield code="w">(DE-627)312840098</subfield><subfield code="w">(DE-600)2012322-X</subfield><subfield code="x">1573-5060</subfield><subfield code="7">nnns</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:206</subfield><subfield code="g">year:2015</subfield><subfield code="g">number:1</subfield><subfield code="g">day:03</subfield><subfield code="g">month:07</subfield><subfield code="g">pages:245-262</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://dx.doi.org/10.1007/s10681-015-1506-0</subfield><subfield code="z">lizenzpflichtig</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_USEFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SYSFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_SPRINGER</subfield></datafield><datafield tag="912" 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