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| 1. |  | BARROS, N. F. de; SILVA, O. M. da; PEREIRA, A. R.; BRAGA, J. M.; LUDWIG, A. Analise do crescimento de Eucalyptus saligna em solo de cerrado sob diferentes niveis N, P e P no Vale do Jequitinhonha, MG. IPEF, Piracicaba, n.26, p.13-17, 1984| Biblioteca(s): Embrapa Florestas. |
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Registro Completo
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Biblioteca(s): |
Embrapa Gado de Leite; Embrapa Meio Ambiente. |
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Data corrente: |
06/09/2023 |
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Data da última atualização: |
08/09/2023 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Circulação/Nível: |
A - 1 |
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Autoria: |
MENDES, R.; BARROS, I. de; D'ANDRÉA, P. A.; D'ANDRÉA-KÜHL, M. S. C.; RODRIGUES, G. S. |
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Afiliação: |
RODRIGO MENDES, CNPMA; INACIO DE BARROS, CNPGL; PAULO ANTÔNIO D’ANDRÉA, MICROGEO BIOTECNOLOGIA AGRÍCOLA; MARIA STEFÂNIA CRUANHES D'ANDRÉA-KÜHL, MICROGEO BIOTECNOLOGIA AGRÍCOLA; GERALDO STACHETTI RODRIGUES, CNPMA. |
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Título: |
A multi-attribute approach to evaluating the impact of biostimulants on crop performance. |
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Ano de publicação: |
2023 |
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Fonte/Imprenta: |
Frontiers in Plant Science, v. 14, 1214112, 2023. |
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ISSN: |
1664-462X |
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DOI: |
https://doi.org/10.3389/fpls.2023.1214112 |
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Idioma: |
Inglês |
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Conteúdo: |
An ever-growing collection of commercial biostimulants is becoming available in a wide variety of forms and compositions to improve crop performance. Given the intricate nature of deciphering the underlying mechanisms of commercial products, which typically comprise various biological components, it is crucial for research in this area to have robust tools to demonstrate their effectiveness in field trials. Here, we took a multi-attribute approach to evaluating the impact of biostimulants on crop performance. First, we assessed the impact of a biostimulant on the soil and rhizosphere microbiomes associated to crops in eight reference farms, including corn (3 farms), soybean (2), cotton (2) and sugarcane (1), in different biomes and production contexts in Brazil and Paraguay. Second, we modeled a set of integrated indicators to measure crop responses to biostimulant application, including five analytical themes as follows: i) crop development and production (9 indicators), ii) soil chemistry (9), iii) soil physics (5), iv) soil biology (6) and v) plant health (10). Amplicon 16S rRNA and ITS sequencing revealed that the use of the biostimulant consistently changes the structure of bacterial and fungal communities associated with the production system for all evaluated crops. In the rhizosphere samples, the most responsive bacterial taxa to biostimulant application were Prevotella in cotton; Prauserella and Methylovirgula in corn; and Methylocapsa in sugar cane. The most responsive fungal taxa to biostimulant use were Arachnomyces in soybean and cotton; and Rhizophlyctis in corn. The proposed integrated indicators yielded highly favorable positive impact indices (averaging at 0.80), indicating that biostimulant-treated fields correlate with better plant development and crop performance. Prominent indices were observed for indicators in four themes: soil biology (average index 0.84), crop production (0.81), soil physics (compaction reduction 0.81), and chemical fertility (0.75). The multi-attribute approach employed in this study offers an effective strategy for assessing the efficacy of biostimulant products across a wide range of crops and production systems. MenosAn ever-growing collection of commercial biostimulants is becoming available in a wide variety of forms and compositions to improve crop performance. Given the intricate nature of deciphering the underlying mechanisms of commercial products, which typically comprise various biological components, it is crucial for research in this area to have robust tools to demonstrate their effectiveness in field trials. Here, we took a multi-attribute approach to evaluating the impact of biostimulants on crop performance. First, we assessed the impact of a biostimulant on the soil and rhizosphere microbiomes associated to crops in eight reference farms, including corn (3 farms), soybean (2), cotton (2) and sugarcane (1), in different biomes and production contexts in Brazil and Paraguay. Second, we modeled a set of integrated indicators to measure crop responses to biostimulant application, including five analytical themes as follows: i) crop development and production (9 indicators), ii) soil chemistry (9), iii) soil physics (5), iv) soil biology (6) and v) plant health (10). Amplicon 16S rRNA and ITS sequencing revealed that the use of the biostimulant consistently changes the structure of bacterial and fungal communities associated with the production system for all evaluated crops. In the rhizosphere samples, the most responsive bacterial taxa to biostimulant application were Prevotella in cotton; Prauserella and Methylovirgula in corn; and Methylocapsa in sugar cane. The most respon... Mostrar Tudo |
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Palavras-Chave: |
Bioestimulante; Fitossanidade; Impact assessment; Multi-attribute indicators. |
|
Thesagro: |
Algodão; Biologia do Solo; Cana de Açúcar; Estimulante de Crescimento Vegetal; Física do Solo; Microrganismo; Milho; Química do Solo; Rizosfera; Soja; Solo. |
|
Thesaurus NAL: |
Growth promotion; Microbiome; Plant development; Rhizosphere; Sustainable agriculture. |
|
Categoria do assunto: |
S Ciências Biológicas |
|
URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/doc/1156510/1/Mendes-multi-attribute-approach-2023.pdf
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|
Marc: |
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022 $a1664-462X
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100 1 $aMENDES, R.
245 $aA multi-attribute approach to evaluating the impact of biostimulants on crop performance.$h[electronic resource]
260 $c2023
520 $aAn ever-growing collection of commercial biostimulants is becoming available in a wide variety of forms and compositions to improve crop performance. Given the intricate nature of deciphering the underlying mechanisms of commercial products, which typically comprise various biological components, it is crucial for research in this area to have robust tools to demonstrate their effectiveness in field trials. Here, we took a multi-attribute approach to evaluating the impact of biostimulants on crop performance. First, we assessed the impact of a biostimulant on the soil and rhizosphere microbiomes associated to crops in eight reference farms, including corn (3 farms), soybean (2), cotton (2) and sugarcane (1), in different biomes and production contexts in Brazil and Paraguay. Second, we modeled a set of integrated indicators to measure crop responses to biostimulant application, including five analytical themes as follows: i) crop development and production (9 indicators), ii) soil chemistry (9), iii) soil physics (5), iv) soil biology (6) and v) plant health (10). Amplicon 16S rRNA and ITS sequencing revealed that the use of the biostimulant consistently changes the structure of bacterial and fungal communities associated with the production system for all evaluated crops. In the rhizosphere samples, the most responsive bacterial taxa to biostimulant application were Prevotella in cotton; Prauserella and Methylovirgula in corn; and Methylocapsa in sugar cane. The most responsive fungal taxa to biostimulant use were Arachnomyces in soybean and cotton; and Rhizophlyctis in corn. The proposed integrated indicators yielded highly favorable positive impact indices (averaging at 0.80), indicating that biostimulant-treated fields correlate with better plant development and crop performance. Prominent indices were observed for indicators in four themes: soil biology (average index 0.84), crop production (0.81), soil physics (compaction reduction 0.81), and chemical fertility (0.75). The multi-attribute approach employed in this study offers an effective strategy for assessing the efficacy of biostimulant products across a wide range of crops and production systems.
650 $aGrowth promotion
650 $aMicrobiome
650 $aPlant development
650 $aRhizosphere
650 $aSustainable agriculture
650 $aAlgodão
650 $aBiologia do Solo
650 $aCana de Açúcar
650 $aEstimulante de Crescimento Vegetal
650 $aFísica do Solo
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650 $aMilho
650 $aQuímica do Solo
650 $aRizosfera
650 $aSoja
650 $aSolo
653 $aBioestimulante
653 $aFitossanidade
653 $aImpact assessment
653 $aMulti-attribute indicators
700 1 $aBARROS, I. de
700 1 $aD'ANDRÉA, P. A.
700 1 $aD'ANDRÉA-KÜHL, M. S. C.
700 1 $aRODRIGUES, G. S.
773 $tFrontiers in Plant Science$gv. 14, 1214112, 2023.
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Embrapa Meio Ambiente (CNPMA) |
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