Effects of Powdery Mildew on 1000-Kernel Weight, Crude Protein Content and Yield of Winter Wheat in Three Consecutive Growing Seasons
In order to clarify the impact posed by wheat powdery mildew (Blumeria graminis f. sp. tritici) on the yield and yield components in different epidemic seasons, field trials were conducted in three growing seasons, 2009–2010, 2010–2011 and 2011–2012, in Langfang City, Hebei Province, China. The rela...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
CAO, Xue-ren [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2014transfer abstract |
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| Schlagwörter: |
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| Umfang: |
8 |
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| Übergeordnetes Werk: |
Enthalten in: Product derivation in practice - de Souza, Leandro Oliveira ELSEVIER, 2015transfer abstract, JIA, Beijing |
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| Übergeordnetes Werk: |
volume:13 ; year:2014 ; number:7 ; pages:1530-1537 ; extent:8 |
| Links: |
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| DOI / URN: |
10.1016/S2095-3119(14)60806-6 |
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ELV033931054 |
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| 520 | |a In order to clarify the impact posed by wheat powdery mildew (Blumeria graminis f. sp. tritici) on the yield and yield components in different epidemic seasons, field trials were conducted in three growing seasons, 2009–2010, 2010–2011 and 2011–2012, in Langfang City, Hebei Province, China. The relationships between 1000-kernel weight, crude protein content of grain and yield and disease index (DI), as well as area under disease progress curve (AUDPC) were studied. The models of the percentage of loss of 1000-kernel weight, crude protein content and yield were constructed using DI at critical point (CP) of growth stages (GS) and AUDPC in the three growing seasons, respectively. The CPs for estimating 1000-kernel weight, crude protein content of grain and yield of wheat caused by powdery mildew were GS 11.1, GS 10.5.3 and GS 10.5.3, respectively. Models based on DI at CP to estimate the percentage of loss of 1000-kernel weight, crude protein content of grain and yield were better than models based on AUDPC. And models of the percentage of loss of 1000-kernel weight, crude protein content and yield for 2011–2012 season were significant different from these for 2009–2010 and 2010–2011 seasons. These results indicated that besides powdery mildew, weather conditions also had influence on 1000-kernel weight, crude protein content of grain and yield loss of wheat when powdery mildew occurred. | ||
| 520 | |a In order to clarify the impact posed by wheat powdery mildew (Blumeria graminis f. sp. tritici) on the yield and yield components in different epidemic seasons, field trials were conducted in three growing seasons, 2009–2010, 2010–2011 and 2011–2012, in Langfang City, Hebei Province, China. The relationships between 1000-kernel weight, crude protein content of grain and yield and disease index (DI), as well as area under disease progress curve (AUDPC) were studied. The models of the percentage of loss of 1000-kernel weight, crude protein content and yield were constructed using DI at critical point (CP) of growth stages (GS) and AUDPC in the three growing seasons, respectively. The CPs for estimating 1000-kernel weight, crude protein content of grain and yield of wheat caused by powdery mildew were GS 11.1, GS 10.5.3 and GS 10.5.3, respectively. Models based on DI at CP to estimate the percentage of loss of 1000-kernel weight, crude protein content of grain and yield were better than models based on AUDPC. And models of the percentage of loss of 1000-kernel weight, crude protein content and yield for 2011–2012 season were significant different from these for 2009–2010 and 2010–2011 seasons. These results indicated that besides powdery mildew, weather conditions also had influence on 1000-kernel weight, crude protein content of grain and yield loss of wheat when powdery mildew occurred. | ||
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10.1016/S2095-3119(14)60806-6 doi GBVA2014011000017.pica (DE-627)ELV033931054 (ELSEVIER)S2095-3119(14)60806-6 DE-627 ger DE-627 rakwb eng 630 640 630 DE-600 640 DE-600 330 VZ 004 VZ 690 VZ 52.43 bkl 52.52 bkl 52.42 bkl 50.38 bkl CAO, Xue-ren verfasserin aut Effects of Powdery Mildew on 1000-Kernel Weight, Crude Protein Content and Yield of Winter Wheat in Three Consecutive Growing Seasons 2014transfer abstract 8 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier In order to clarify the impact posed by wheat powdery mildew (Blumeria graminis f. sp. tritici) on the yield and yield components in different epidemic seasons, field trials were conducted in three growing seasons, 2009–2010, 2010–2011 and 2011–2012, in Langfang City, Hebei Province, China. The relationships between 1000-kernel weight, crude protein content of grain and yield and disease index (DI), as well as area under disease progress curve (AUDPC) were studied. The models of the percentage of loss of 1000-kernel weight, crude protein content and yield were constructed using DI at critical point (CP) of growth stages (GS) and AUDPC in the three growing seasons, respectively. The CPs for estimating 1000-kernel weight, crude protein content of grain and yield of wheat caused by powdery mildew were GS 11.1, GS 10.5.3 and GS 10.5.3, respectively. Models based on DI at CP to estimate the percentage of loss of 1000-kernel weight, crude protein content of grain and yield were better than models based on AUDPC. And models of the percentage of loss of 1000-kernel weight, crude protein content and yield for 2011–2012 season were significant different from these for 2009–2010 and 2010–2011 seasons. These results indicated that besides powdery mildew, weather conditions also had influence on 1000-kernel weight, crude protein content of grain and yield loss of wheat when powdery mildew occurred. In order to clarify the impact posed by wheat powdery mildew (Blumeria graminis f. sp. tritici) on the yield and yield components in different epidemic seasons, field trials were conducted in three growing seasons, 2009–2010, 2010–2011 and 2011–2012, in Langfang City, Hebei Province, China. The relationships between 1000-kernel weight, crude protein content of grain and yield and disease index (DI), as well as area under disease progress curve (AUDPC) were studied. The models of the percentage of loss of 1000-kernel weight, crude protein content and yield were constructed using DI at critical point (CP) of growth stages (GS) and AUDPC in the three growing seasons, respectively. The CPs for estimating 1000-kernel weight, crude protein content of grain and yield of wheat caused by powdery mildew were GS 11.1, GS 10.5.3 and GS 10.5.3, respectively. Models based on DI at CP to estimate the percentage of loss of 1000-kernel weight, crude protein content of grain and yield were better than models based on AUDPC. And models of the percentage of loss of 1000-kernel weight, crude protein content and yield for 2011–2012 season were significant different from these for 2009–2010 and 2010–2011 seasons. These results indicated that besides powdery mildew, weather conditions also had influence on 1000-kernel weight, crude protein content of grain and yield loss of wheat when powdery mildew occurred. crude protein content Elsevier loss Elsevier wheat powdery mildew Elsevier yield Elsevier 1000-kernel weight Elsevier YAO, Dong-ming oth DUAN, Xia-yu oth LIU, Wei oth FAN, Jie-ru oth DING, Ke-jian oth ZHOU, Yi-lin oth Enthalten in Elsevier de Souza, Leandro Oliveira ELSEVIER Product derivation in practice 2015transfer abstract JIA Beijing (DE-627)ELV018624588 volume:13 year:2014 number:7 pages:1530-1537 extent:8 https://doi.org/10.1016/S2095-3119(14)60806-6 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U GBV_ILN_40 GBV_ILN_283 52.43 Kältetechnik VZ 52.52 Thermische Energieerzeugung Wärmetechnik VZ 52.42 Heizungstechnik Lüftungstechnik Klimatechnik VZ 50.38 Technische Thermodynamik VZ AR 13 2014 7 1530-1537 8 045F 630 |
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10.1016/S2095-3119(14)60806-6 doi GBVA2014011000017.pica (DE-627)ELV033931054 (ELSEVIER)S2095-3119(14)60806-6 DE-627 ger DE-627 rakwb eng 630 640 630 DE-600 640 DE-600 330 VZ 004 VZ 690 VZ 52.43 bkl 52.52 bkl 52.42 bkl 50.38 bkl CAO, Xue-ren verfasserin aut Effects of Powdery Mildew on 1000-Kernel Weight, Crude Protein Content and Yield of Winter Wheat in Three Consecutive Growing Seasons 2014transfer abstract 8 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier In order to clarify the impact posed by wheat powdery mildew (Blumeria graminis f. sp. tritici) on the yield and yield components in different epidemic seasons, field trials were conducted in three growing seasons, 2009–2010, 2010–2011 and 2011–2012, in Langfang City, Hebei Province, China. The relationships between 1000-kernel weight, crude protein content of grain and yield and disease index (DI), as well as area under disease progress curve (AUDPC) were studied. The models of the percentage of loss of 1000-kernel weight, crude protein content and yield were constructed using DI at critical point (CP) of growth stages (GS) and AUDPC in the three growing seasons, respectively. The CPs for estimating 1000-kernel weight, crude protein content of grain and yield of wheat caused by powdery mildew were GS 11.1, GS 10.5.3 and GS 10.5.3, respectively. Models based on DI at CP to estimate the percentage of loss of 1000-kernel weight, crude protein content of grain and yield were better than models based on AUDPC. And models of the percentage of loss of 1000-kernel weight, crude protein content and yield for 2011–2012 season were significant different from these for 2009–2010 and 2010–2011 seasons. These results indicated that besides powdery mildew, weather conditions also had influence on 1000-kernel weight, crude protein content of grain and yield loss of wheat when powdery mildew occurred. In order to clarify the impact posed by wheat powdery mildew (Blumeria graminis f. sp. tritici) on the yield and yield components in different epidemic seasons, field trials were conducted in three growing seasons, 2009–2010, 2010–2011 and 2011–2012, in Langfang City, Hebei Province, China. The relationships between 1000-kernel weight, crude protein content of grain and yield and disease index (DI), as well as area under disease progress curve (AUDPC) were studied. The models of the percentage of loss of 1000-kernel weight, crude protein content and yield were constructed using DI at critical point (CP) of growth stages (GS) and AUDPC in the three growing seasons, respectively. The CPs for estimating 1000-kernel weight, crude protein content of grain and yield of wheat caused by powdery mildew were GS 11.1, GS 10.5.3 and GS 10.5.3, respectively. Models based on DI at CP to estimate the percentage of loss of 1000-kernel weight, crude protein content of grain and yield were better than models based on AUDPC. And models of the percentage of loss of 1000-kernel weight, crude protein content and yield for 2011–2012 season were significant different from these for 2009–2010 and 2010–2011 seasons. These results indicated that besides powdery mildew, weather conditions also had influence on 1000-kernel weight, crude protein content of grain and yield loss of wheat when powdery mildew occurred. crude protein content Elsevier loss Elsevier wheat powdery mildew Elsevier yield Elsevier 1000-kernel weight Elsevier YAO, Dong-ming oth DUAN, Xia-yu oth LIU, Wei oth FAN, Jie-ru oth DING, Ke-jian oth ZHOU, Yi-lin oth Enthalten in Elsevier de Souza, Leandro Oliveira ELSEVIER Product derivation in practice 2015transfer abstract JIA Beijing (DE-627)ELV018624588 volume:13 year:2014 number:7 pages:1530-1537 extent:8 https://doi.org/10.1016/S2095-3119(14)60806-6 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U GBV_ILN_40 GBV_ILN_283 52.43 Kältetechnik VZ 52.52 Thermische Energieerzeugung Wärmetechnik VZ 52.42 Heizungstechnik Lüftungstechnik Klimatechnik VZ 50.38 Technische Thermodynamik VZ AR 13 2014 7 1530-1537 8 045F 630 |
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10.1016/S2095-3119(14)60806-6 doi GBVA2014011000017.pica (DE-627)ELV033931054 (ELSEVIER)S2095-3119(14)60806-6 DE-627 ger DE-627 rakwb eng 630 640 630 DE-600 640 DE-600 330 VZ 004 VZ 690 VZ 52.43 bkl 52.52 bkl 52.42 bkl 50.38 bkl CAO, Xue-ren verfasserin aut Effects of Powdery Mildew on 1000-Kernel Weight, Crude Protein Content and Yield of Winter Wheat in Three Consecutive Growing Seasons 2014transfer abstract 8 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier In order to clarify the impact posed by wheat powdery mildew (Blumeria graminis f. sp. tritici) on the yield and yield components in different epidemic seasons, field trials were conducted in three growing seasons, 2009–2010, 2010–2011 and 2011–2012, in Langfang City, Hebei Province, China. The relationships between 1000-kernel weight, crude protein content of grain and yield and disease index (DI), as well as area under disease progress curve (AUDPC) were studied. The models of the percentage of loss of 1000-kernel weight, crude protein content and yield were constructed using DI at critical point (CP) of growth stages (GS) and AUDPC in the three growing seasons, respectively. The CPs for estimating 1000-kernel weight, crude protein content of grain and yield of wheat caused by powdery mildew were GS 11.1, GS 10.5.3 and GS 10.5.3, respectively. Models based on DI at CP to estimate the percentage of loss of 1000-kernel weight, crude protein content of grain and yield were better than models based on AUDPC. And models of the percentage of loss of 1000-kernel weight, crude protein content and yield for 2011–2012 season were significant different from these for 2009–2010 and 2010–2011 seasons. These results indicated that besides powdery mildew, weather conditions also had influence on 1000-kernel weight, crude protein content of grain and yield loss of wheat when powdery mildew occurred. In order to clarify the impact posed by wheat powdery mildew (Blumeria graminis f. sp. tritici) on the yield and yield components in different epidemic seasons, field trials were conducted in three growing seasons, 2009–2010, 2010–2011 and 2011–2012, in Langfang City, Hebei Province, China. The relationships between 1000-kernel weight, crude protein content of grain and yield and disease index (DI), as well as area under disease progress curve (AUDPC) were studied. The models of the percentage of loss of 1000-kernel weight, crude protein content and yield were constructed using DI at critical point (CP) of growth stages (GS) and AUDPC in the three growing seasons, respectively. The CPs for estimating 1000-kernel weight, crude protein content of grain and yield of wheat caused by powdery mildew were GS 11.1, GS 10.5.3 and GS 10.5.3, respectively. Models based on DI at CP to estimate the percentage of loss of 1000-kernel weight, crude protein content of grain and yield were better than models based on AUDPC. And models of the percentage of loss of 1000-kernel weight, crude protein content and yield for 2011–2012 season were significant different from these for 2009–2010 and 2010–2011 seasons. These results indicated that besides powdery mildew, weather conditions also had influence on 1000-kernel weight, crude protein content of grain and yield loss of wheat when powdery mildew occurred. crude protein content Elsevier loss Elsevier wheat powdery mildew Elsevier yield Elsevier 1000-kernel weight Elsevier YAO, Dong-ming oth DUAN, Xia-yu oth LIU, Wei oth FAN, Jie-ru oth DING, Ke-jian oth ZHOU, Yi-lin oth Enthalten in Elsevier de Souza, Leandro Oliveira ELSEVIER Product derivation in practice 2015transfer abstract JIA Beijing (DE-627)ELV018624588 volume:13 year:2014 number:7 pages:1530-1537 extent:8 https://doi.org/10.1016/S2095-3119(14)60806-6 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U GBV_ILN_40 GBV_ILN_283 52.43 Kältetechnik VZ 52.52 Thermische Energieerzeugung Wärmetechnik VZ 52.42 Heizungstechnik Lüftungstechnik Klimatechnik VZ 50.38 Technische Thermodynamik VZ AR 13 2014 7 1530-1537 8 045F 630 |
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10.1016/S2095-3119(14)60806-6 doi GBVA2014011000017.pica (DE-627)ELV033931054 (ELSEVIER)S2095-3119(14)60806-6 DE-627 ger DE-627 rakwb eng 630 640 630 DE-600 640 DE-600 330 VZ 004 VZ 690 VZ 52.43 bkl 52.52 bkl 52.42 bkl 50.38 bkl CAO, Xue-ren verfasserin aut Effects of Powdery Mildew on 1000-Kernel Weight, Crude Protein Content and Yield of Winter Wheat in Three Consecutive Growing Seasons 2014transfer abstract 8 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier In order to clarify the impact posed by wheat powdery mildew (Blumeria graminis f. sp. tritici) on the yield and yield components in different epidemic seasons, field trials were conducted in three growing seasons, 2009–2010, 2010–2011 and 2011–2012, in Langfang City, Hebei Province, China. The relationships between 1000-kernel weight, crude protein content of grain and yield and disease index (DI), as well as area under disease progress curve (AUDPC) were studied. The models of the percentage of loss of 1000-kernel weight, crude protein content and yield were constructed using DI at critical point (CP) of growth stages (GS) and AUDPC in the three growing seasons, respectively. The CPs for estimating 1000-kernel weight, crude protein content of grain and yield of wheat caused by powdery mildew were GS 11.1, GS 10.5.3 and GS 10.5.3, respectively. Models based on DI at CP to estimate the percentage of loss of 1000-kernel weight, crude protein content of grain and yield were better than models based on AUDPC. And models of the percentage of loss of 1000-kernel weight, crude protein content and yield for 2011–2012 season were significant different from these for 2009–2010 and 2010–2011 seasons. These results indicated that besides powdery mildew, weather conditions also had influence on 1000-kernel weight, crude protein content of grain and yield loss of wheat when powdery mildew occurred. In order to clarify the impact posed by wheat powdery mildew (Blumeria graminis f. sp. tritici) on the yield and yield components in different epidemic seasons, field trials were conducted in three growing seasons, 2009–2010, 2010–2011 and 2011–2012, in Langfang City, Hebei Province, China. The relationships between 1000-kernel weight, crude protein content of grain and yield and disease index (DI), as well as area under disease progress curve (AUDPC) were studied. The models of the percentage of loss of 1000-kernel weight, crude protein content and yield were constructed using DI at critical point (CP) of growth stages (GS) and AUDPC in the three growing seasons, respectively. The CPs for estimating 1000-kernel weight, crude protein content of grain and yield of wheat caused by powdery mildew were GS 11.1, GS 10.5.3 and GS 10.5.3, respectively. Models based on DI at CP to estimate the percentage of loss of 1000-kernel weight, crude protein content of grain and yield were better than models based on AUDPC. And models of the percentage of loss of 1000-kernel weight, crude protein content and yield for 2011–2012 season were significant different from these for 2009–2010 and 2010–2011 seasons. These results indicated that besides powdery mildew, weather conditions also had influence on 1000-kernel weight, crude protein content of grain and yield loss of wheat when powdery mildew occurred. crude protein content Elsevier loss Elsevier wheat powdery mildew Elsevier yield Elsevier 1000-kernel weight Elsevier YAO, Dong-ming oth DUAN, Xia-yu oth LIU, Wei oth FAN, Jie-ru oth DING, Ke-jian oth ZHOU, Yi-lin oth Enthalten in Elsevier de Souza, Leandro Oliveira ELSEVIER Product derivation in practice 2015transfer abstract JIA Beijing (DE-627)ELV018624588 volume:13 year:2014 number:7 pages:1530-1537 extent:8 https://doi.org/10.1016/S2095-3119(14)60806-6 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U GBV_ILN_40 GBV_ILN_283 52.43 Kältetechnik VZ 52.52 Thermische Energieerzeugung Wärmetechnik VZ 52.42 Heizungstechnik Lüftungstechnik Klimatechnik VZ 50.38 Technische Thermodynamik VZ AR 13 2014 7 1530-1537 8 045F 630 |
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10.1016/S2095-3119(14)60806-6 doi GBVA2014011000017.pica (DE-627)ELV033931054 (ELSEVIER)S2095-3119(14)60806-6 DE-627 ger DE-627 rakwb eng 630 640 630 DE-600 640 DE-600 330 VZ 004 VZ 690 VZ 52.43 bkl 52.52 bkl 52.42 bkl 50.38 bkl CAO, Xue-ren verfasserin aut Effects of Powdery Mildew on 1000-Kernel Weight, Crude Protein Content and Yield of Winter Wheat in Three Consecutive Growing Seasons 2014transfer abstract 8 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier In order to clarify the impact posed by wheat powdery mildew (Blumeria graminis f. sp. tritici) on the yield and yield components in different epidemic seasons, field trials were conducted in three growing seasons, 2009–2010, 2010–2011 and 2011–2012, in Langfang City, Hebei Province, China. The relationships between 1000-kernel weight, crude protein content of grain and yield and disease index (DI), as well as area under disease progress curve (AUDPC) were studied. The models of the percentage of loss of 1000-kernel weight, crude protein content and yield were constructed using DI at critical point (CP) of growth stages (GS) and AUDPC in the three growing seasons, respectively. The CPs for estimating 1000-kernel weight, crude protein content of grain and yield of wheat caused by powdery mildew were GS 11.1, GS 10.5.3 and GS 10.5.3, respectively. Models based on DI at CP to estimate the percentage of loss of 1000-kernel weight, crude protein content of grain and yield were better than models based on AUDPC. And models of the percentage of loss of 1000-kernel weight, crude protein content and yield for 2011–2012 season were significant different from these for 2009–2010 and 2010–2011 seasons. These results indicated that besides powdery mildew, weather conditions also had influence on 1000-kernel weight, crude protein content of grain and yield loss of wheat when powdery mildew occurred. In order to clarify the impact posed by wheat powdery mildew (Blumeria graminis f. sp. tritici) on the yield and yield components in different epidemic seasons, field trials were conducted in three growing seasons, 2009–2010, 2010–2011 and 2011–2012, in Langfang City, Hebei Province, China. The relationships between 1000-kernel weight, crude protein content of grain and yield and disease index (DI), as well as area under disease progress curve (AUDPC) were studied. The models of the percentage of loss of 1000-kernel weight, crude protein content and yield were constructed using DI at critical point (CP) of growth stages (GS) and AUDPC in the three growing seasons, respectively. The CPs for estimating 1000-kernel weight, crude protein content of grain and yield of wheat caused by powdery mildew were GS 11.1, GS 10.5.3 and GS 10.5.3, respectively. Models based on DI at CP to estimate the percentage of loss of 1000-kernel weight, crude protein content of grain and yield were better than models based on AUDPC. And models of the percentage of loss of 1000-kernel weight, crude protein content and yield for 2011–2012 season were significant different from these for 2009–2010 and 2010–2011 seasons. These results indicated that besides powdery mildew, weather conditions also had influence on 1000-kernel weight, crude protein content of grain and yield loss of wheat when powdery mildew occurred. crude protein content Elsevier loss Elsevier wheat powdery mildew Elsevier yield Elsevier 1000-kernel weight Elsevier YAO, Dong-ming oth DUAN, Xia-yu oth LIU, Wei oth FAN, Jie-ru oth DING, Ke-jian oth ZHOU, Yi-lin oth Enthalten in Elsevier de Souza, Leandro Oliveira ELSEVIER Product derivation in practice 2015transfer abstract JIA Beijing (DE-627)ELV018624588 volume:13 year:2014 number:7 pages:1530-1537 extent:8 https://doi.org/10.1016/S2095-3119(14)60806-6 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U GBV_ILN_40 GBV_ILN_283 52.43 Kältetechnik VZ 52.52 Thermische Energieerzeugung Wärmetechnik VZ 52.42 Heizungstechnik Lüftungstechnik Klimatechnik VZ 50.38 Technische Thermodynamik VZ AR 13 2014 7 1530-1537 8 045F 630 |
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Effects of Powdery Mildew on 1000-Kernel Weight, Crude Protein Content and Yield of Winter Wheat in Three Consecutive Growing Seasons |
| abstract |
In order to clarify the impact posed by wheat powdery mildew (Blumeria graminis f. sp. tritici) on the yield and yield components in different epidemic seasons, field trials were conducted in three growing seasons, 2009–2010, 2010–2011 and 2011–2012, in Langfang City, Hebei Province, China. The relationships between 1000-kernel weight, crude protein content of grain and yield and disease index (DI), as well as area under disease progress curve (AUDPC) were studied. The models of the percentage of loss of 1000-kernel weight, crude protein content and yield were constructed using DI at critical point (CP) of growth stages (GS) and AUDPC in the three growing seasons, respectively. The CPs for estimating 1000-kernel weight, crude protein content of grain and yield of wheat caused by powdery mildew were GS 11.1, GS 10.5.3 and GS 10.5.3, respectively. Models based on DI at CP to estimate the percentage of loss of 1000-kernel weight, crude protein content of grain and yield were better than models based on AUDPC. And models of the percentage of loss of 1000-kernel weight, crude protein content and yield for 2011–2012 season were significant different from these for 2009–2010 and 2010–2011 seasons. These results indicated that besides powdery mildew, weather conditions also had influence on 1000-kernel weight, crude protein content of grain and yield loss of wheat when powdery mildew occurred. |
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In order to clarify the impact posed by wheat powdery mildew (Blumeria graminis f. sp. tritici) on the yield and yield components in different epidemic seasons, field trials were conducted in three growing seasons, 2009–2010, 2010–2011 and 2011–2012, in Langfang City, Hebei Province, China. The relationships between 1000-kernel weight, crude protein content of grain and yield and disease index (DI), as well as area under disease progress curve (AUDPC) were studied. The models of the percentage of loss of 1000-kernel weight, crude protein content and yield were constructed using DI at critical point (CP) of growth stages (GS) and AUDPC in the three growing seasons, respectively. The CPs for estimating 1000-kernel weight, crude protein content of grain and yield of wheat caused by powdery mildew were GS 11.1, GS 10.5.3 and GS 10.5.3, respectively. Models based on DI at CP to estimate the percentage of loss of 1000-kernel weight, crude protein content of grain and yield were better than models based on AUDPC. And models of the percentage of loss of 1000-kernel weight, crude protein content and yield for 2011–2012 season were significant different from these for 2009–2010 and 2010–2011 seasons. These results indicated that besides powdery mildew, weather conditions also had influence on 1000-kernel weight, crude protein content of grain and yield loss of wheat when powdery mildew occurred. |
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In order to clarify the impact posed by wheat powdery mildew (Blumeria graminis f. sp. tritici) on the yield and yield components in different epidemic seasons, field trials were conducted in three growing seasons, 2009–2010, 2010–2011 and 2011–2012, in Langfang City, Hebei Province, China. The relationships between 1000-kernel weight, crude protein content of grain and yield and disease index (DI), as well as area under disease progress curve (AUDPC) were studied. The models of the percentage of loss of 1000-kernel weight, crude protein content and yield were constructed using DI at critical point (CP) of growth stages (GS) and AUDPC in the three growing seasons, respectively. The CPs for estimating 1000-kernel weight, crude protein content of grain and yield of wheat caused by powdery mildew were GS 11.1, GS 10.5.3 and GS 10.5.3, respectively. Models based on DI at CP to estimate the percentage of loss of 1000-kernel weight, crude protein content of grain and yield were better than models based on AUDPC. And models of the percentage of loss of 1000-kernel weight, crude protein content and yield for 2011–2012 season were significant different from these for 2009–2010 and 2010–2011 seasons. These results indicated that besides powdery mildew, weather conditions also had influence on 1000-kernel weight, crude protein content of grain and yield loss of wheat when powdery mildew occurred. |
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These results indicated that besides powdery mildew, weather conditions also had influence on 1000-kernel weight, crude protein content of grain and yield loss of wheat when powdery mildew occurred.</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">In order to clarify the impact posed by wheat powdery mildew (Blumeria graminis f. sp. tritici) on the yield and yield components in different epidemic seasons, field trials were conducted in three growing seasons, 2009–2010, 2010–2011 and 2011–2012, in Langfang City, Hebei Province, China. The relationships between 1000-kernel weight, crude protein content of grain and yield and disease index (DI), as well as area under disease progress curve (AUDPC) were studied. The models of the percentage of loss of 1000-kernel weight, crude protein content and yield were constructed using DI at critical point (CP) of growth stages (GS) and AUDPC in the three growing seasons, respectively. The CPs for estimating 1000-kernel weight, crude protein content of grain and yield of wheat caused by powdery mildew were GS 11.1, GS 10.5.3 and GS 10.5.3, respectively. Models based on DI at CP to estimate the percentage of loss of 1000-kernel weight, crude protein content of grain and yield were better than models based on AUDPC. And models of the percentage of loss of 1000-kernel weight, crude protein content and yield for 2011–2012 season were significant different from these for 2009–2010 and 2010–2011 seasons. These results indicated that besides powdery mildew, weather conditions also had influence on 1000-kernel weight, crude protein content of grain and yield loss of wheat when powdery mildew occurred.</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">crude protein content</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">loss</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">wheat powdery mildew</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">yield</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">1000-kernel weight</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">YAO, Dong-ming</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">DUAN, Xia-yu</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">LIU, Wei</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">FAN, Jie-ru</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">DING, Ke-jian</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">ZHOU, Yi-lin</subfield><subfield code="4">oth</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">Enthalten in</subfield><subfield code="n">Elsevier</subfield><subfield code="a">de Souza, Leandro Oliveira ELSEVIER</subfield><subfield code="t">Product derivation in practice</subfield><subfield code="d">2015transfer abstract</subfield><subfield code="d">JIA</subfield><subfield code="g">Beijing</subfield><subfield code="w">(DE-627)ELV018624588</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:13</subfield><subfield code="g">year:2014</subfield><subfield code="g">number:7</subfield><subfield code="g">pages:1530-1537</subfield><subfield code="g">extent:8</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doi.org/10.1016/S2095-3119(14)60806-6</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_USEFLAG_U</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ELV</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SYSFLAG_U</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_40</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_283</subfield></datafield><datafield tag="936" ind1="b" ind2="k"><subfield code="a">52.43</subfield><subfield code="j">Kältetechnik</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="936" ind1="b" ind2="k"><subfield code="a">52.52</subfield><subfield code="j">Thermische Energieerzeugung</subfield><subfield code="j">Wärmetechnik</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="936" ind1="b" ind2="k"><subfield code="a">52.42</subfield><subfield code="j">Heizungstechnik</subfield><subfield code="j">Lüftungstechnik</subfield><subfield code="j">Klimatechnik</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="936" ind1="b" ind2="k"><subfield code="a">50.38</subfield><subfield code="j">Technische Thermodynamik</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">AR</subfield></datafield><datafield tag="952" ind1=" " ind2=" "><subfield code="d">13</subfield><subfield code="j">2014</subfield><subfield code="e">7</subfield><subfield code="h">1530-1537</subfield><subfield code="g">8</subfield></datafield><datafield tag="953" ind1=" " ind2=" "><subfield code="2">045F</subfield><subfield code="a">630</subfield></datafield></record></collection>
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