Water Stress Alters Morphophysiological, Grain Quality and Vegetation Indices of Soybean Cultivars
Rainfall is among the climatic factors that most affect production, as in the Brazilian Cerrado. Non-destructive and automated phenotyping methods are fast and efficient for genotype selection. The objective of this work was to evaluate, under field conditions, the morphophysiological changes, yield...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Cássio Jardim Tavares [verfasserIn] Walter Quadros Ribeiro Junior [verfasserIn] Maria Lucrecia Gerosa Ramos [verfasserIn] Lucas Felisberto Pereira [verfasserIn] Raphael Augusto das Chagas Noqueli Casari [verfasserIn] André Ferreira Pereira [verfasserIn] Carlos Antonio Ferreira de Sousa [verfasserIn] Anderson Rodrigo da Silva [verfasserIn] Sebastião Pedro da Silva Neto [verfasserIn] Liliane Marcia Mertz-Henning [verfasserIn] |
|---|
| Format: |
E-Artikel |
|---|---|
| Sprache: |
Englisch |
| Erschienen: |
2022 |
|---|
| Schlagwörter: |
|---|
| Übergeordnetes Werk: |
In: Plants - MDPI AG, 2013, 11(2022), 4, p 559 |
|---|---|
| Übergeordnetes Werk: |
volume:11 ; year:2022 ; number:4, p 559 |
| Links: |
|---|
| DOI / URN: |
10.3390/plants11040559 |
|---|
| Katalog-ID: |
DOAJ069428972 |
|---|
| LEADER | 01000caa a22002652 4500 | ||
|---|---|---|---|
| 001 | DOAJ069428972 | ||
| 003 | DE-627 | ||
| 005 | 20240414183217.0 | ||
| 007 | cr uuu---uuuuu | ||
| 008 | 230228s2022 xx |||||o 00| ||eng c | ||
| 024 | 7 | |a 10.3390/plants11040559 |2 doi | |
| 035 | |a (DE-627)DOAJ069428972 | ||
| 035 | |a (DE-599)DOAJ71b1465b580442b89f34ee47d997048a | ||
| 040 | |a DE-627 |b ger |c DE-627 |e rakwb | ||
| 041 | |a eng | ||
| 050 | 0 | |a QK1-989 | |
| 100 | 0 | |a Cássio Jardim Tavares |e verfasserin |4 aut | |
| 245 | 1 | 0 | |a Water Stress Alters Morphophysiological, Grain Quality and Vegetation Indices of Soybean Cultivars |
| 264 | 1 | |c 2022 | |
| 336 | |a Text |b txt |2 rdacontent | ||
| 337 | |a Computermedien |b c |2 rdamedia | ||
| 338 | |a Online-Ressource |b cr |2 rdacarrier | ||
| 520 | |a Rainfall is among the climatic factors that most affect production, as in the Brazilian Cerrado. Non-destructive and automated phenotyping methods are fast and efficient for genotype selection. The objective of this work was to evaluate, under field conditions, the morphophysiological changes, yield, and grain quality of soybean (<i<Glycine max</i< L. Merrill) under water stress in the Brazilian Cerrado. The plots comprised six soybean cultivars and the subplots of four water regimes, corresponding to 31, 44, 64 and 100% of crop evapotranspiration replacement. The experiments were conducted from May to September 2018 and 2019. An irrigation system with a bar of sprinklers with different flow rates was used. Gas exchange, vegetation indices (measured using a hyperspectral sensor embedded in a drone), yield and grain quality were evaluated. Water stress had different effects on gas exchange, vegetation indices, grain yield and chemical composition among the cultivars. Embrapa cultivar BRS 7280 Roundup ready (RR) and Nidera cultivar NA 5909 RG (glyphosate resistant) are yield stable and have a greater tolerance to drought. BRS 7280RR showed a higher tolerance to drought and higher water use efficiency (WUE) than all other tested cultivars. Vegetation indices, such as the NDVI (Normalized Difference Vegetation Index), correlated with the morphophysiological traits, such as plant height, were the most responsive variables to water stress. The NDVI can be used to predict soybean yield as a tool in a selection program under drought. | ||
| 650 | 4 | |a NDVI | |
| 650 | 4 | |a photochemical reflectance index | |
| 650 | 4 | |a gas exchange | |
| 650 | 4 | |a automation | |
| 653 | 0 | |a Botany | |
| 700 | 0 | |a Walter Quadros Ribeiro Junior |e verfasserin |4 aut | |
| 700 | 0 | |a Maria Lucrecia Gerosa Ramos |e verfasserin |4 aut | |
| 700 | 0 | |a Lucas Felisberto Pereira |e verfasserin |4 aut | |
| 700 | 0 | |a Raphael Augusto das Chagas Noqueli Casari |e verfasserin |4 aut | |
| 700 | 0 | |a André Ferreira Pereira |e verfasserin |4 aut | |
| 700 | 0 | |a Carlos Antonio Ferreira de Sousa |e verfasserin |4 aut | |
| 700 | 0 | |a Anderson Rodrigo da Silva |e verfasserin |4 aut | |
| 700 | 0 | |a Sebastião Pedro da Silva Neto |e verfasserin |4 aut | |
| 700 | 0 | |a Liliane Marcia Mertz-Henning |e verfasserin |4 aut | |
| 773 | 0 | 8 | |i In |t Plants |d MDPI AG, 2013 |g 11(2022), 4, p 559 |w (DE-627)737288345 |w (DE-600)2704341-1 |x 22237747 |7 nnns |
| 773 | 1 | 8 | |g volume:11 |g year:2022 |g number:4, p 559 |
| 856 | 4 | 0 | |u https://doi.org/10.3390/plants11040559 |z kostenfrei |
| 856 | 4 | 0 | |u https://doaj.org/article/71b1465b580442b89f34ee47d997048a |z kostenfrei |
| 856 | 4 | 0 | |u https://www.mdpi.com/2223-7747/11/4/559 |z kostenfrei |
| 856 | 4 | 2 | |u https://doaj.org/toc/2223-7747 |y Journal toc |z kostenfrei |
| 912 | |a GBV_USEFLAG_A | ||
| 912 | |a SYSFLAG_A | ||
| 912 | |a GBV_DOAJ | ||
| 912 | |a GBV_ILN_20 | ||
| 912 | |a GBV_ILN_22 | ||
| 912 | |a GBV_ILN_23 | ||
| 912 | |a GBV_ILN_24 | ||
| 912 | |a GBV_ILN_39 | ||
| 912 | |a GBV_ILN_40 | ||
| 912 | |a GBV_ILN_60 | ||
| 912 | |a GBV_ILN_62 | ||
| 912 | |a GBV_ILN_63 | ||
| 912 | |a GBV_ILN_65 | ||
| 912 | |a GBV_ILN_69 | ||
| 912 | |a GBV_ILN_70 | ||
| 912 | |a GBV_ILN_73 | ||
| 912 | |a GBV_ILN_95 | ||
| 912 | |a GBV_ILN_105 | ||
| 912 | |a GBV_ILN_110 | ||
| 912 | |a GBV_ILN_151 | ||
| 912 | |a GBV_ILN_161 | ||
| 912 | |a GBV_ILN_213 | ||
| 912 | |a GBV_ILN_230 | ||
| 912 | |a GBV_ILN_285 | ||
| 912 | |a GBV_ILN_293 | ||
| 912 | |a GBV_ILN_602 | ||
| 912 | |a GBV_ILN_2014 | ||
| 912 | |a GBV_ILN_4012 | ||
| 912 | |a GBV_ILN_4037 | ||
| 912 | |a GBV_ILN_4112 | ||
| 912 | |a GBV_ILN_4125 | ||
| 912 | |a GBV_ILN_4126 | ||
| 912 | |a GBV_ILN_4249 | ||
| 912 | |a GBV_ILN_4305 | ||
| 912 | |a GBV_ILN_4306 | ||
| 912 | |a GBV_ILN_4307 | ||
| 912 | |a GBV_ILN_4313 | ||
| 912 | |a GBV_ILN_4322 | ||
| 912 | |a GBV_ILN_4323 | ||
| 912 | |a GBV_ILN_4324 | ||
| 912 | |a GBV_ILN_4325 | ||
| 912 | |a GBV_ILN_4338 | ||
| 912 | |a GBV_ILN_4367 | ||
| 912 | |a GBV_ILN_4700 | ||
| 951 | |a AR | ||
| 952 | |d 11 |j 2022 |e 4, p 559 | ||
| author_variant |
c j t cjt w q r j wqrj m l g r mlgr l f p lfp r a d c n c radcnc a f p afp c a f d s cafds a r d s ards s p d s n spdsn l m m h lmmh |
|---|---|
| matchkey_str |
article:22237747:2022----::aesrsatrmrhpyilgclriqaiynvgttoi |
| hierarchy_sort_str |
2022 |
| callnumber-subject-code |
QK |
| publishDate |
2022 |
| allfields |
10.3390/plants11040559 doi (DE-627)DOAJ069428972 (DE-599)DOAJ71b1465b580442b89f34ee47d997048a DE-627 ger DE-627 rakwb eng QK1-989 Cássio Jardim Tavares verfasserin aut Water Stress Alters Morphophysiological, Grain Quality and Vegetation Indices of Soybean Cultivars 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Rainfall is among the climatic factors that most affect production, as in the Brazilian Cerrado. Non-destructive and automated phenotyping methods are fast and efficient for genotype selection. The objective of this work was to evaluate, under field conditions, the morphophysiological changes, yield, and grain quality of soybean (<i<Glycine max</i< L. Merrill) under water stress in the Brazilian Cerrado. The plots comprised six soybean cultivars and the subplots of four water regimes, corresponding to 31, 44, 64 and 100% of crop evapotranspiration replacement. The experiments were conducted from May to September 2018 and 2019. An irrigation system with a bar of sprinklers with different flow rates was used. Gas exchange, vegetation indices (measured using a hyperspectral sensor embedded in a drone), yield and grain quality were evaluated. Water stress had different effects on gas exchange, vegetation indices, grain yield and chemical composition among the cultivars. Embrapa cultivar BRS 7280 Roundup ready (RR) and Nidera cultivar NA 5909 RG (glyphosate resistant) are yield stable and have a greater tolerance to drought. BRS 7280RR showed a higher tolerance to drought and higher water use efficiency (WUE) than all other tested cultivars. Vegetation indices, such as the NDVI (Normalized Difference Vegetation Index), correlated with the morphophysiological traits, such as plant height, were the most responsive variables to water stress. The NDVI can be used to predict soybean yield as a tool in a selection program under drought. NDVI photochemical reflectance index gas exchange automation Botany Walter Quadros Ribeiro Junior verfasserin aut Maria Lucrecia Gerosa Ramos verfasserin aut Lucas Felisberto Pereira verfasserin aut Raphael Augusto das Chagas Noqueli Casari verfasserin aut André Ferreira Pereira verfasserin aut Carlos Antonio Ferreira de Sousa verfasserin aut Anderson Rodrigo da Silva verfasserin aut Sebastião Pedro da Silva Neto verfasserin aut Liliane Marcia Mertz-Henning verfasserin aut In Plants MDPI AG, 2013 11(2022), 4, p 559 (DE-627)737288345 (DE-600)2704341-1 22237747 nnns volume:11 year:2022 number:4, p 559 https://doi.org/10.3390/plants11040559 kostenfrei https://doaj.org/article/71b1465b580442b89f34ee47d997048a kostenfrei https://www.mdpi.com/2223-7747/11/4/559 kostenfrei https://doaj.org/toc/2223-7747 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 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_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 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_4338 GBV_ILN_4367 GBV_ILN_4700 AR 11 2022 4, p 559 |
| spelling |
10.3390/plants11040559 doi (DE-627)DOAJ069428972 (DE-599)DOAJ71b1465b580442b89f34ee47d997048a DE-627 ger DE-627 rakwb eng QK1-989 Cássio Jardim Tavares verfasserin aut Water Stress Alters Morphophysiological, Grain Quality and Vegetation Indices of Soybean Cultivars 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Rainfall is among the climatic factors that most affect production, as in the Brazilian Cerrado. Non-destructive and automated phenotyping methods are fast and efficient for genotype selection. The objective of this work was to evaluate, under field conditions, the morphophysiological changes, yield, and grain quality of soybean (<i<Glycine max</i< L. Merrill) under water stress in the Brazilian Cerrado. The plots comprised six soybean cultivars and the subplots of four water regimes, corresponding to 31, 44, 64 and 100% of crop evapotranspiration replacement. The experiments were conducted from May to September 2018 and 2019. An irrigation system with a bar of sprinklers with different flow rates was used. Gas exchange, vegetation indices (measured using a hyperspectral sensor embedded in a drone), yield and grain quality were evaluated. Water stress had different effects on gas exchange, vegetation indices, grain yield and chemical composition among the cultivars. Embrapa cultivar BRS 7280 Roundup ready (RR) and Nidera cultivar NA 5909 RG (glyphosate resistant) are yield stable and have a greater tolerance to drought. BRS 7280RR showed a higher tolerance to drought and higher water use efficiency (WUE) than all other tested cultivars. Vegetation indices, such as the NDVI (Normalized Difference Vegetation Index), correlated with the morphophysiological traits, such as plant height, were the most responsive variables to water stress. The NDVI can be used to predict soybean yield as a tool in a selection program under drought. NDVI photochemical reflectance index gas exchange automation Botany Walter Quadros Ribeiro Junior verfasserin aut Maria Lucrecia Gerosa Ramos verfasserin aut Lucas Felisberto Pereira verfasserin aut Raphael Augusto das Chagas Noqueli Casari verfasserin aut André Ferreira Pereira verfasserin aut Carlos Antonio Ferreira de Sousa verfasserin aut Anderson Rodrigo da Silva verfasserin aut Sebastião Pedro da Silva Neto verfasserin aut Liliane Marcia Mertz-Henning verfasserin aut In Plants MDPI AG, 2013 11(2022), 4, p 559 (DE-627)737288345 (DE-600)2704341-1 22237747 nnns volume:11 year:2022 number:4, p 559 https://doi.org/10.3390/plants11040559 kostenfrei https://doaj.org/article/71b1465b580442b89f34ee47d997048a kostenfrei https://www.mdpi.com/2223-7747/11/4/559 kostenfrei https://doaj.org/toc/2223-7747 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 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_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 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_4338 GBV_ILN_4367 GBV_ILN_4700 AR 11 2022 4, p 559 |
| allfields_unstemmed |
10.3390/plants11040559 doi (DE-627)DOAJ069428972 (DE-599)DOAJ71b1465b580442b89f34ee47d997048a DE-627 ger DE-627 rakwb eng QK1-989 Cássio Jardim Tavares verfasserin aut Water Stress Alters Morphophysiological, Grain Quality and Vegetation Indices of Soybean Cultivars 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Rainfall is among the climatic factors that most affect production, as in the Brazilian Cerrado. Non-destructive and automated phenotyping methods are fast and efficient for genotype selection. The objective of this work was to evaluate, under field conditions, the morphophysiological changes, yield, and grain quality of soybean (<i<Glycine max</i< L. Merrill) under water stress in the Brazilian Cerrado. The plots comprised six soybean cultivars and the subplots of four water regimes, corresponding to 31, 44, 64 and 100% of crop evapotranspiration replacement. The experiments were conducted from May to September 2018 and 2019. An irrigation system with a bar of sprinklers with different flow rates was used. Gas exchange, vegetation indices (measured using a hyperspectral sensor embedded in a drone), yield and grain quality were evaluated. Water stress had different effects on gas exchange, vegetation indices, grain yield and chemical composition among the cultivars. Embrapa cultivar BRS 7280 Roundup ready (RR) and Nidera cultivar NA 5909 RG (glyphosate resistant) are yield stable and have a greater tolerance to drought. BRS 7280RR showed a higher tolerance to drought and higher water use efficiency (WUE) than all other tested cultivars. Vegetation indices, such as the NDVI (Normalized Difference Vegetation Index), correlated with the morphophysiological traits, such as plant height, were the most responsive variables to water stress. The NDVI can be used to predict soybean yield as a tool in a selection program under drought. NDVI photochemical reflectance index gas exchange automation Botany Walter Quadros Ribeiro Junior verfasserin aut Maria Lucrecia Gerosa Ramos verfasserin aut Lucas Felisberto Pereira verfasserin aut Raphael Augusto das Chagas Noqueli Casari verfasserin aut André Ferreira Pereira verfasserin aut Carlos Antonio Ferreira de Sousa verfasserin aut Anderson Rodrigo da Silva verfasserin aut Sebastião Pedro da Silva Neto verfasserin aut Liliane Marcia Mertz-Henning verfasserin aut In Plants MDPI AG, 2013 11(2022), 4, p 559 (DE-627)737288345 (DE-600)2704341-1 22237747 nnns volume:11 year:2022 number:4, p 559 https://doi.org/10.3390/plants11040559 kostenfrei https://doaj.org/article/71b1465b580442b89f34ee47d997048a kostenfrei https://www.mdpi.com/2223-7747/11/4/559 kostenfrei https://doaj.org/toc/2223-7747 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 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_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 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_4338 GBV_ILN_4367 GBV_ILN_4700 AR 11 2022 4, p 559 |
| allfieldsGer |
10.3390/plants11040559 doi (DE-627)DOAJ069428972 (DE-599)DOAJ71b1465b580442b89f34ee47d997048a DE-627 ger DE-627 rakwb eng QK1-989 Cássio Jardim Tavares verfasserin aut Water Stress Alters Morphophysiological, Grain Quality and Vegetation Indices of Soybean Cultivars 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Rainfall is among the climatic factors that most affect production, as in the Brazilian Cerrado. Non-destructive and automated phenotyping methods are fast and efficient for genotype selection. The objective of this work was to evaluate, under field conditions, the morphophysiological changes, yield, and grain quality of soybean (<i<Glycine max</i< L. Merrill) under water stress in the Brazilian Cerrado. The plots comprised six soybean cultivars and the subplots of four water regimes, corresponding to 31, 44, 64 and 100% of crop evapotranspiration replacement. The experiments were conducted from May to September 2018 and 2019. An irrigation system with a bar of sprinklers with different flow rates was used. Gas exchange, vegetation indices (measured using a hyperspectral sensor embedded in a drone), yield and grain quality were evaluated. Water stress had different effects on gas exchange, vegetation indices, grain yield and chemical composition among the cultivars. Embrapa cultivar BRS 7280 Roundup ready (RR) and Nidera cultivar NA 5909 RG (glyphosate resistant) are yield stable and have a greater tolerance to drought. BRS 7280RR showed a higher tolerance to drought and higher water use efficiency (WUE) than all other tested cultivars. Vegetation indices, such as the NDVI (Normalized Difference Vegetation Index), correlated with the morphophysiological traits, such as plant height, were the most responsive variables to water stress. The NDVI can be used to predict soybean yield as a tool in a selection program under drought. NDVI photochemical reflectance index gas exchange automation Botany Walter Quadros Ribeiro Junior verfasserin aut Maria Lucrecia Gerosa Ramos verfasserin aut Lucas Felisberto Pereira verfasserin aut Raphael Augusto das Chagas Noqueli Casari verfasserin aut André Ferreira Pereira verfasserin aut Carlos Antonio Ferreira de Sousa verfasserin aut Anderson Rodrigo da Silva verfasserin aut Sebastião Pedro da Silva Neto verfasserin aut Liliane Marcia Mertz-Henning verfasserin aut In Plants MDPI AG, 2013 11(2022), 4, p 559 (DE-627)737288345 (DE-600)2704341-1 22237747 nnns volume:11 year:2022 number:4, p 559 https://doi.org/10.3390/plants11040559 kostenfrei https://doaj.org/article/71b1465b580442b89f34ee47d997048a kostenfrei https://www.mdpi.com/2223-7747/11/4/559 kostenfrei https://doaj.org/toc/2223-7747 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 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_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 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_4338 GBV_ILN_4367 GBV_ILN_4700 AR 11 2022 4, p 559 |
| allfieldsSound |
10.3390/plants11040559 doi (DE-627)DOAJ069428972 (DE-599)DOAJ71b1465b580442b89f34ee47d997048a DE-627 ger DE-627 rakwb eng QK1-989 Cássio Jardim Tavares verfasserin aut Water Stress Alters Morphophysiological, Grain Quality and Vegetation Indices of Soybean Cultivars 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Rainfall is among the climatic factors that most affect production, as in the Brazilian Cerrado. Non-destructive and automated phenotyping methods are fast and efficient for genotype selection. The objective of this work was to evaluate, under field conditions, the morphophysiological changes, yield, and grain quality of soybean (<i<Glycine max</i< L. Merrill) under water stress in the Brazilian Cerrado. The plots comprised six soybean cultivars and the subplots of four water regimes, corresponding to 31, 44, 64 and 100% of crop evapotranspiration replacement. The experiments were conducted from May to September 2018 and 2019. An irrigation system with a bar of sprinklers with different flow rates was used. Gas exchange, vegetation indices (measured using a hyperspectral sensor embedded in a drone), yield and grain quality were evaluated. Water stress had different effects on gas exchange, vegetation indices, grain yield and chemical composition among the cultivars. Embrapa cultivar BRS 7280 Roundup ready (RR) and Nidera cultivar NA 5909 RG (glyphosate resistant) are yield stable and have a greater tolerance to drought. BRS 7280RR showed a higher tolerance to drought and higher water use efficiency (WUE) than all other tested cultivars. Vegetation indices, such as the NDVI (Normalized Difference Vegetation Index), correlated with the morphophysiological traits, such as plant height, were the most responsive variables to water stress. The NDVI can be used to predict soybean yield as a tool in a selection program under drought. NDVI photochemical reflectance index gas exchange automation Botany Walter Quadros Ribeiro Junior verfasserin aut Maria Lucrecia Gerosa Ramos verfasserin aut Lucas Felisberto Pereira verfasserin aut Raphael Augusto das Chagas Noqueli Casari verfasserin aut André Ferreira Pereira verfasserin aut Carlos Antonio Ferreira de Sousa verfasserin aut Anderson Rodrigo da Silva verfasserin aut Sebastião Pedro da Silva Neto verfasserin aut Liliane Marcia Mertz-Henning verfasserin aut In Plants MDPI AG, 2013 11(2022), 4, p 559 (DE-627)737288345 (DE-600)2704341-1 22237747 nnns volume:11 year:2022 number:4, p 559 https://doi.org/10.3390/plants11040559 kostenfrei https://doaj.org/article/71b1465b580442b89f34ee47d997048a kostenfrei https://www.mdpi.com/2223-7747/11/4/559 kostenfrei https://doaj.org/toc/2223-7747 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 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_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 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_4338 GBV_ILN_4367 GBV_ILN_4700 AR 11 2022 4, p 559 |
| language |
English |
| source |
In Plants 11(2022), 4, p 559 volume:11 year:2022 number:4, p 559 |
| sourceStr |
In Plants 11(2022), 4, p 559 volume:11 year:2022 number:4, p 559 |
| format_phy_str_mv |
Article |
| institution |
findex.gbv.de |
| topic_facet |
NDVI photochemical reflectance index gas exchange automation Botany |
| isfreeaccess_bool |
true |
| container_title |
Plants |
| authorswithroles_txt_mv |
Cássio Jardim Tavares @@aut@@ Walter Quadros Ribeiro Junior @@aut@@ Maria Lucrecia Gerosa Ramos @@aut@@ Lucas Felisberto Pereira @@aut@@ Raphael Augusto das Chagas Noqueli Casari @@aut@@ André Ferreira Pereira @@aut@@ Carlos Antonio Ferreira de Sousa @@aut@@ Anderson Rodrigo da Silva @@aut@@ Sebastião Pedro da Silva Neto @@aut@@ Liliane Marcia Mertz-Henning @@aut@@ |
| publishDateDaySort_date |
2022-01-01T00:00:00Z |
| hierarchy_top_id |
737288345 |
| id |
DOAJ069428972 |
| language_de |
englisch |
| fullrecord |
<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a22002652 4500</leader><controlfield tag="001">DOAJ069428972</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20240414183217.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">230228s2022 xx |||||o 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.3390/plants11040559</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)DOAJ069428972</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)DOAJ71b1465b580442b89f34ee47d997048a</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="050" ind1=" " ind2="0"><subfield code="a">QK1-989</subfield></datafield><datafield tag="100" ind1="0" ind2=" "><subfield code="a">Cássio Jardim Tavares</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Water Stress Alters Morphophysiological, Grain Quality and Vegetation Indices of Soybean Cultivars</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2022</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">Rainfall is among the climatic factors that most affect production, as in the Brazilian Cerrado. Non-destructive and automated phenotyping methods are fast and efficient for genotype selection. The objective of this work was to evaluate, under field conditions, the morphophysiological changes, yield, and grain quality of soybean (<i<Glycine max</i< L. Merrill) under water stress in the Brazilian Cerrado. The plots comprised six soybean cultivars and the subplots of four water regimes, corresponding to 31, 44, 64 and 100% of crop evapotranspiration replacement. The experiments were conducted from May to September 2018 and 2019. An irrigation system with a bar of sprinklers with different flow rates was used. Gas exchange, vegetation indices (measured using a hyperspectral sensor embedded in a drone), yield and grain quality were evaluated. Water stress had different effects on gas exchange, vegetation indices, grain yield and chemical composition among the cultivars. Embrapa cultivar BRS 7280 Roundup ready (RR) and Nidera cultivar NA 5909 RG (glyphosate resistant) are yield stable and have a greater tolerance to drought. BRS 7280RR showed a higher tolerance to drought and higher water use efficiency (WUE) than all other tested cultivars. Vegetation indices, such as the NDVI (Normalized Difference Vegetation Index), correlated with the morphophysiological traits, such as plant height, were the most responsive variables to water stress. The NDVI can be used to predict soybean yield as a tool in a selection program under drought.</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">NDVI</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">photochemical reflectance index</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">gas exchange</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">automation</subfield></datafield><datafield tag="653" ind1=" " ind2="0"><subfield code="a">Botany</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Walter Quadros Ribeiro Junior</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Maria Lucrecia Gerosa Ramos</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Lucas Felisberto Pereira</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Raphael Augusto das Chagas Noqueli Casari</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">André Ferreira Pereira</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Carlos Antonio Ferreira de Sousa</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Anderson Rodrigo da Silva</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Sebastião Pedro da Silva Neto</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Liliane Marcia Mertz-Henning</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">In</subfield><subfield code="t">Plants</subfield><subfield code="d">MDPI AG, 2013</subfield><subfield code="g">11(2022), 4, p 559</subfield><subfield code="w">(DE-627)737288345</subfield><subfield code="w">(DE-600)2704341-1</subfield><subfield code="x">22237747</subfield><subfield code="7">nnns</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:11</subfield><subfield code="g">year:2022</subfield><subfield code="g">number:4, p 559</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doi.org/10.3390/plants11040559</subfield><subfield code="z">kostenfrei</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doaj.org/article/71b1465b580442b89f34ee47d997048a</subfield><subfield code="z">kostenfrei</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://www.mdpi.com/2223-7747/11/4/559</subfield><subfield code="z">kostenfrei</subfield></datafield><datafield tag="856" ind1="4" ind2="2"><subfield code="u">https://doaj.org/toc/2223-7747</subfield><subfield code="y">Journal toc</subfield><subfield code="z">kostenfrei</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_DOAJ</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_20</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_22</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_23</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_24</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_39</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_60</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_62</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_63</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_65</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_69</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_70</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_73</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_95</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_105</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_110</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_151</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_161</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_213</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_230</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_285</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_293</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_602</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2014</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4012</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4037</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4112</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4125</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4126</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4249</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4305</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4306</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4307</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4313</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4322</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4323</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4324</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4325</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4338</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4367</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4700</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">AR</subfield></datafield><datafield tag="952" ind1=" " ind2=" "><subfield code="d">11</subfield><subfield code="j">2022</subfield><subfield code="e">4, p 559</subfield></datafield></record></collection>
|
| callnumber-first |
Q - Science |
| author |
Cássio Jardim Tavares |
| spellingShingle |
Cássio Jardim Tavares misc QK1-989 misc NDVI misc photochemical reflectance index misc gas exchange misc automation misc Botany Water Stress Alters Morphophysiological, Grain Quality and Vegetation Indices of Soybean Cultivars |
| authorStr |
Cássio Jardim Tavares |
| ppnlink_with_tag_str_mv |
@@773@@(DE-627)737288345 |
| format |
electronic Article |
| delete_txt_mv |
keep |
| author_role |
aut aut aut aut aut aut aut aut aut aut |
| collection |
DOAJ |
| remote_str |
true |
| callnumber-label |
QK1-989 |
| illustrated |
Not Illustrated |
| issn |
22237747 |
| topic_title |
QK1-989 Water Stress Alters Morphophysiological, Grain Quality and Vegetation Indices of Soybean Cultivars NDVI photochemical reflectance index gas exchange automation |
| topic |
misc QK1-989 misc NDVI misc photochemical reflectance index misc gas exchange misc automation misc Botany |
| topic_unstemmed |
misc QK1-989 misc NDVI misc photochemical reflectance index misc gas exchange misc automation misc Botany |
| topic_browse |
misc QK1-989 misc NDVI misc photochemical reflectance index misc gas exchange misc automation misc Botany |
| format_facet |
Elektronische Aufsätze Aufsätze Elektronische Ressource |
| format_main_str_mv |
Text Zeitschrift/Artikel |
| carriertype_str_mv |
cr |
| hierarchy_parent_title |
Plants |
| hierarchy_parent_id |
737288345 |
| hierarchy_top_title |
Plants |
| isfreeaccess_txt |
true |
| familylinks_str_mv |
(DE-627)737288345 (DE-600)2704341-1 |
| title |
Water Stress Alters Morphophysiological, Grain Quality and Vegetation Indices of Soybean Cultivars |
| ctrlnum |
(DE-627)DOAJ069428972 (DE-599)DOAJ71b1465b580442b89f34ee47d997048a |
| title_full |
Water Stress Alters Morphophysiological, Grain Quality and Vegetation Indices of Soybean Cultivars |
| author_sort |
Cássio Jardim Tavares |
| journal |
Plants |
| journalStr |
Plants |
| callnumber-first-code |
Q |
| lang_code |
eng |
| isOA_bool |
true |
| recordtype |
marc |
| publishDateSort |
2022 |
| contenttype_str_mv |
txt |
| author_browse |
Cássio Jardim Tavares Walter Quadros Ribeiro Junior Maria Lucrecia Gerosa Ramos Lucas Felisberto Pereira Raphael Augusto das Chagas Noqueli Casari André Ferreira Pereira Carlos Antonio Ferreira de Sousa Anderson Rodrigo da Silva Sebastião Pedro da Silva Neto Liliane Marcia Mertz-Henning |
| container_volume |
11 |
| class |
QK1-989 |
| format_se |
Elektronische Aufsätze |
| author-letter |
Cássio Jardim Tavares |
| doi_str_mv |
10.3390/plants11040559 |
| author2-role |
verfasserin |
| title_sort |
water stress alters morphophysiological, grain quality and vegetation indices of soybean cultivars |
| callnumber |
QK1-989 |
| title_auth |
Water Stress Alters Morphophysiological, Grain Quality and Vegetation Indices of Soybean Cultivars |
| abstract |
Rainfall is among the climatic factors that most affect production, as in the Brazilian Cerrado. Non-destructive and automated phenotyping methods are fast and efficient for genotype selection. The objective of this work was to evaluate, under field conditions, the morphophysiological changes, yield, and grain quality of soybean (<i<Glycine max</i< L. Merrill) under water stress in the Brazilian Cerrado. The plots comprised six soybean cultivars and the subplots of four water regimes, corresponding to 31, 44, 64 and 100% of crop evapotranspiration replacement. The experiments were conducted from May to September 2018 and 2019. An irrigation system with a bar of sprinklers with different flow rates was used. Gas exchange, vegetation indices (measured using a hyperspectral sensor embedded in a drone), yield and grain quality were evaluated. Water stress had different effects on gas exchange, vegetation indices, grain yield and chemical composition among the cultivars. Embrapa cultivar BRS 7280 Roundup ready (RR) and Nidera cultivar NA 5909 RG (glyphosate resistant) are yield stable and have a greater tolerance to drought. BRS 7280RR showed a higher tolerance to drought and higher water use efficiency (WUE) than all other tested cultivars. Vegetation indices, such as the NDVI (Normalized Difference Vegetation Index), correlated with the morphophysiological traits, such as plant height, were the most responsive variables to water stress. The NDVI can be used to predict soybean yield as a tool in a selection program under drought. |
| abstractGer |
Rainfall is among the climatic factors that most affect production, as in the Brazilian Cerrado. Non-destructive and automated phenotyping methods are fast and efficient for genotype selection. The objective of this work was to evaluate, under field conditions, the morphophysiological changes, yield, and grain quality of soybean (<i<Glycine max</i< L. Merrill) under water stress in the Brazilian Cerrado. The plots comprised six soybean cultivars and the subplots of four water regimes, corresponding to 31, 44, 64 and 100% of crop evapotranspiration replacement. The experiments were conducted from May to September 2018 and 2019. An irrigation system with a bar of sprinklers with different flow rates was used. Gas exchange, vegetation indices (measured using a hyperspectral sensor embedded in a drone), yield and grain quality were evaluated. Water stress had different effects on gas exchange, vegetation indices, grain yield and chemical composition among the cultivars. Embrapa cultivar BRS 7280 Roundup ready (RR) and Nidera cultivar NA 5909 RG (glyphosate resistant) are yield stable and have a greater tolerance to drought. BRS 7280RR showed a higher tolerance to drought and higher water use efficiency (WUE) than all other tested cultivars. Vegetation indices, such as the NDVI (Normalized Difference Vegetation Index), correlated with the morphophysiological traits, such as plant height, were the most responsive variables to water stress. The NDVI can be used to predict soybean yield as a tool in a selection program under drought. |
| abstract_unstemmed |
Rainfall is among the climatic factors that most affect production, as in the Brazilian Cerrado. Non-destructive and automated phenotyping methods are fast and efficient for genotype selection. The objective of this work was to evaluate, under field conditions, the morphophysiological changes, yield, and grain quality of soybean (<i<Glycine max</i< L. Merrill) under water stress in the Brazilian Cerrado. The plots comprised six soybean cultivars and the subplots of four water regimes, corresponding to 31, 44, 64 and 100% of crop evapotranspiration replacement. The experiments were conducted from May to September 2018 and 2019. An irrigation system with a bar of sprinklers with different flow rates was used. Gas exchange, vegetation indices (measured using a hyperspectral sensor embedded in a drone), yield and grain quality were evaluated. Water stress had different effects on gas exchange, vegetation indices, grain yield and chemical composition among the cultivars. Embrapa cultivar BRS 7280 Roundup ready (RR) and Nidera cultivar NA 5909 RG (glyphosate resistant) are yield stable and have a greater tolerance to drought. BRS 7280RR showed a higher tolerance to drought and higher water use efficiency (WUE) than all other tested cultivars. Vegetation indices, such as the NDVI (Normalized Difference Vegetation Index), correlated with the morphophysiological traits, such as plant height, were the most responsive variables to water stress. The NDVI can be used to predict soybean yield as a tool in a selection program under drought. |
| collection_details |
GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 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_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 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_4338 GBV_ILN_4367 GBV_ILN_4700 |
| container_issue |
4, p 559 |
| title_short |
Water Stress Alters Morphophysiological, Grain Quality and Vegetation Indices of Soybean Cultivars |
| url |
https://doi.org/10.3390/plants11040559 https://doaj.org/article/71b1465b580442b89f34ee47d997048a https://www.mdpi.com/2223-7747/11/4/559 https://doaj.org/toc/2223-7747 |
| remote_bool |
true |
| author2 |
Walter Quadros Ribeiro Junior Maria Lucrecia Gerosa Ramos Lucas Felisberto Pereira Raphael Augusto das Chagas Noqueli Casari André Ferreira Pereira Carlos Antonio Ferreira de Sousa Anderson Rodrigo da Silva Sebastião Pedro da Silva Neto Liliane Marcia Mertz-Henning |
| author2Str |
Walter Quadros Ribeiro Junior Maria Lucrecia Gerosa Ramos Lucas Felisberto Pereira Raphael Augusto das Chagas Noqueli Casari André Ferreira Pereira Carlos Antonio Ferreira de Sousa Anderson Rodrigo da Silva Sebastião Pedro da Silva Neto Liliane Marcia Mertz-Henning |
| ppnlink |
737288345 |
| callnumber-subject |
QK - Botany |
| mediatype_str_mv |
c |
| isOA_txt |
true |
| hochschulschrift_bool |
false |
| doi_str |
10.3390/plants11040559 |
| callnumber-a |
QK1-989 |
| up_date |
2024-07-03T23:12:53.034Z |
| _version_ |
1803601442804596736 |
| fullrecord_marcxml |
<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a22002652 4500</leader><controlfield tag="001">DOAJ069428972</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20240414183217.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">230228s2022 xx |||||o 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.3390/plants11040559</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)DOAJ069428972</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)DOAJ71b1465b580442b89f34ee47d997048a</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="050" ind1=" " ind2="0"><subfield code="a">QK1-989</subfield></datafield><datafield tag="100" ind1="0" ind2=" "><subfield code="a">Cássio Jardim Tavares</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Water Stress Alters Morphophysiological, Grain Quality and Vegetation Indices of Soybean Cultivars</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2022</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">Rainfall is among the climatic factors that most affect production, as in the Brazilian Cerrado. Non-destructive and automated phenotyping methods are fast and efficient for genotype selection. The objective of this work was to evaluate, under field conditions, the morphophysiological changes, yield, and grain quality of soybean (<i<Glycine max</i< L. Merrill) under water stress in the Brazilian Cerrado. The plots comprised six soybean cultivars and the subplots of four water regimes, corresponding to 31, 44, 64 and 100% of crop evapotranspiration replacement. The experiments were conducted from May to September 2018 and 2019. An irrigation system with a bar of sprinklers with different flow rates was used. Gas exchange, vegetation indices (measured using a hyperspectral sensor embedded in a drone), yield and grain quality were evaluated. Water stress had different effects on gas exchange, vegetation indices, grain yield and chemical composition among the cultivars. Embrapa cultivar BRS 7280 Roundup ready (RR) and Nidera cultivar NA 5909 RG (glyphosate resistant) are yield stable and have a greater tolerance to drought. BRS 7280RR showed a higher tolerance to drought and higher water use efficiency (WUE) than all other tested cultivars. Vegetation indices, such as the NDVI (Normalized Difference Vegetation Index), correlated with the morphophysiological traits, such as plant height, were the most responsive variables to water stress. The NDVI can be used to predict soybean yield as a tool in a selection program under drought.</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">NDVI</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">photochemical reflectance index</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">gas exchange</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">automation</subfield></datafield><datafield tag="653" ind1=" " ind2="0"><subfield code="a">Botany</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Walter Quadros Ribeiro Junior</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Maria Lucrecia Gerosa Ramos</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Lucas Felisberto Pereira</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Raphael Augusto das Chagas Noqueli Casari</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">André Ferreira Pereira</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Carlos Antonio Ferreira de Sousa</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Anderson Rodrigo da Silva</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Sebastião Pedro da Silva Neto</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Liliane Marcia Mertz-Henning</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">In</subfield><subfield code="t">Plants</subfield><subfield code="d">MDPI AG, 2013</subfield><subfield code="g">11(2022), 4, p 559</subfield><subfield code="w">(DE-627)737288345</subfield><subfield code="w">(DE-600)2704341-1</subfield><subfield code="x">22237747</subfield><subfield code="7">nnns</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:11</subfield><subfield code="g">year:2022</subfield><subfield code="g">number:4, p 559</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doi.org/10.3390/plants11040559</subfield><subfield code="z">kostenfrei</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doaj.org/article/71b1465b580442b89f34ee47d997048a</subfield><subfield code="z">kostenfrei</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://www.mdpi.com/2223-7747/11/4/559</subfield><subfield code="z">kostenfrei</subfield></datafield><datafield tag="856" ind1="4" ind2="2"><subfield code="u">https://doaj.org/toc/2223-7747</subfield><subfield code="y">Journal toc</subfield><subfield code="z">kostenfrei</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_DOAJ</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_20</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_22</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_23</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_24</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_39</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_60</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_62</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_63</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_65</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_69</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_70</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_73</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_95</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_105</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_110</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_151</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_161</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_213</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_230</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_285</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_293</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_602</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2014</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4012</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4037</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4112</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4125</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4126</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4249</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4305</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4306</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4307</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4313</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4322</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4323</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4324</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4325</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4338</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4367</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4700</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">AR</subfield></datafield><datafield tag="952" ind1=" " ind2=" "><subfield code="d">11</subfield><subfield code="j">2022</subfield><subfield code="e">4, p 559</subfield></datafield></record></collection>
|
| score |
7.400509 |