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Registro Completo |
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Biblioteca(s): |
Embrapa Gado de Corte. |
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Data corrente: |
29/09/2021 |
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Data da última atualização: |
29/09/2021 |
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Tipo da produção científica: |
Artigo em Anais de Congresso |
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Autoria: |
FERREIRA, E. A.; FERREIRA, D. P.; ABREU, J. G. de; ALMEIDA, R. G. de; AZEVEDO, V. H. de; SALES, K. C.; ASSIS, L. M. B.; SANDRI, V. T. |
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Afiliação: |
EDUARDO ANDRÉ FERREIRA, Universidade Federal de Mato Grosso - UFMT; DANIEL PAULO FERREIRA, Universidade Federal de Mato Grosso - UFMT; JOADIL GONÇALVES DE ABREU, Universidade Federal de Mato Grosso - UFMT; ROBERTO GIOLO DE ALMEIDA, CNPGC; VIRGINIA HELENA DE AZEVEDO, Universidade Federal de Mato Grosso - UFMT; KYRON CABRAL SALES, Universidade Federal de Mato Grosso - UFMT; LUCAS MATHEUS BARROS ASSIS, Universidade Federal de Mato Grosso - UFMT; VINICIUS TRINDADE SANDRI, Universidade Federal de Mato Grosso - UFMT. |
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Título: |
Morphological composition of Piatã grass in systems in integration. |
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Ano de publicação: |
2021 |
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Fonte/Imprenta: |
In: WORLD CONGRESS ON INTEGRATED CROP-LIVESTOCK-FORESTRY SYSTEMS: 100% DIGITAL, 2., 2021. WCCLF 2021 proceedings. Campo Grande, MS: Embrapa Gado de Corte, 2021. p. 289-291. |
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Idioma: |
Inglês |
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Palavras-Chave: |
Leaf; Stem. |
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Thesaurus Nal: |
Senescence (aging). |
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Categoria do assunto: |
-- |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/226487/1/MORPHOLOGICAL-COMPOSITION-OF-PIATA-GRASS-IN-SYSTEMS-IN-INTEGRATION.pdf
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Marc: |
LEADER 00757nam a2200217 a 4500
001 2134838
005 2021-09-29
008 2021 bl uuuu u00u1 u #d
100 1 $aFERREIRA, E. A.
245 $aMorphological composition of Piatã grass in systems in integration.$h[electronic resource]
260 $aIn: WORLD CONGRESS ON INTEGRATED CROP-LIVESTOCK-FORESTRY SYSTEMS: 100% DIGITAL, 2., 2021. WCCLF 2021 proceedings. Campo Grande, MS: Embrapa Gado de Corte, 2021. p. 289-291.$c2021
650 $aSenescence (aging)
653 $aLeaf
653 $aStem
700 1 $aFERREIRA, D. P.
700 1 $aABREU, J. G. de
700 1 $aALMEIDA, R. G. de
700 1 $aAZEVEDO, V. H. de
700 1 $aSALES, K. C.
700 1 $aASSIS, L. M. B.
700 1 $aSANDRI, V. T.
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Registro original: |
Embrapa Gado de Corte (CNPGC) |
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Registro Completo
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Biblioteca(s): |
Embrapa Clima Temperado; Embrapa Uva e Vinho. |
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Data corrente: |
01/07/2020 |
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Data da última atualização: |
01/07/2020 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Circulação/Nível: |
A - 2 |
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Autoria: |
BETEMPS, D. L.; PAULA, B. V. de; PARENT, S.-E.; GALARÇA, S. P.; MAYER, N. A.; MARODIN, G. A. B.; ROZANE, D. E.; NATALE, W.; MELO, G. W. B. de; PARENT, L. E.; BRUNETTO, G. |
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Afiliação: |
DÉBORA LEITZKE BETEMPS, UFSM; UFFS; BETANIA VAHL DE PAULA, UFSM; SERGE-ÉTIENNE PARENT, LAVAL UNIVERSITY; SIMONE P. GALARÇA, ASCAR EMATER; NEWTON ALEX MAYER, CPACT; GILMAR A. B. MARODIN, UFRGS; DANILO E. ROZANE, UNESP; WILLIAM NATALE, UFC; GEORGE WELLINGTON BASTOS DE MELO, CNPUV; LÉON E. PARENT, UFSM; LAVAL UNIVERSITY; GUSTAVO BRUNETTO, UFSM. |
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Título: |
Humboldtian Diagnosis of Peach Tree (Prunus persica) Nutrition Using Machine-Learning and Compositional Methods. |
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Ano de publicação: |
2020 |
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Fonte/Imprenta: |
Agronomy, v. 10, n. 6, June 2020. |
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Páginas: |
21 p. |
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ISSN: |
2073-4395 |
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DOI: |
10.3390/agronomy10060900 |
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Idioma: |
Inglês |
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Conteúdo: |
Regional nutrient ranges are commonly used to diagnose plant nutrient status. In contrast, local diagnosis confronts unhealthy to healthy compositional entities in comparable surroundings. Robust local diagnosis requires well-documented data sets processed by machine learning and compositional methods. Our objective was to customize nutrient diagnosis of peach (Prunus persica) trees at local scale. We collected 472 observations from commercial orchards and fertilizer trials across eleven cultivars of Prunus persica and six rootstocks in the state of Rio Grande do Sul (RS), Brazil. The random forest classification model returned an area under curve exceeding 0.80 and classification accuracy of 80% about yield cutoff of 16 Mg ha-1 Centered log ratios (clr) of foliar defective compositions have appropriate geometry to compute Euclidean distances from closest successful compositions in 'enchanting islands'. Successful specimens closest to defective specimens as shown by Euclidean distance allow reaching trustful fruit yields using site-specific corrective measures. Comparing tissue composition of low-yielding orchards to that of the closest successful neighbors in two major Brazilian peach-producing regions, regional diagnosis diered from local diagnosis, indicating that regional standards may fail to fit local conditions. Local diagnosis requires well-documented Humboldtian data sets that can be acquired through ethical collaboration between researchers and stakeholders. |
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Thesagro: |
Pêssego; Porta Enxerto; Prunus. |
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Categoria do assunto: |
-- |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/214306/1/agronomy-10-00900-v2.pdf
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Marc: |
LEADER 02364naa a2200313 a 4500
001 2123550
005 2020-07-01
008 2020 bl uuuu u00u1 u #d
022 $a2073-4395
024 7 $a10.3390/agronomy10060900$2DOI
100 1 $aBETEMPS, D. L.
245 $aHumboldtian Diagnosis of Peach Tree (Prunus persica) Nutrition Using Machine-Learning and Compositional Methods.$h[electronic resource]
260 $c2020
300 $a21 p.
520 $aRegional nutrient ranges are commonly used to diagnose plant nutrient status. In contrast, local diagnosis confronts unhealthy to healthy compositional entities in comparable surroundings. Robust local diagnosis requires well-documented data sets processed by machine learning and compositional methods. Our objective was to customize nutrient diagnosis of peach (Prunus persica) trees at local scale. We collected 472 observations from commercial orchards and fertilizer trials across eleven cultivars of Prunus persica and six rootstocks in the state of Rio Grande do Sul (RS), Brazil. The random forest classification model returned an area under curve exceeding 0.80 and classification accuracy of 80% about yield cutoff of 16 Mg ha-1 Centered log ratios (clr) of foliar defective compositions have appropriate geometry to compute Euclidean distances from closest successful compositions in 'enchanting islands'. Successful specimens closest to defective specimens as shown by Euclidean distance allow reaching trustful fruit yields using site-specific corrective measures. Comparing tissue composition of low-yielding orchards to that of the closest successful neighbors in two major Brazilian peach-producing regions, regional diagnosis diered from local diagnosis, indicating that regional standards may fail to fit local conditions. Local diagnosis requires well-documented Humboldtian data sets that can be acquired through ethical collaboration between researchers and stakeholders.
650 $aPêssego
650 $aPorta Enxerto
650 $aPrunus
700 1 $aPAULA, B. V. de
700 1 $aPARENT, S.-E.
700 1 $aGALARÇA, S. P.
700 1 $aMAYER, N. A.
700 1 $aMARODIN, G. A. B.
700 1 $aROZANE, D. E.
700 1 $aNATALE, W.
700 1 $aMELO, G. W. B. de
700 1 $aPARENT, L. E.
700 1 $aBRUNETTO, G.
773 $tAgronomy$gv. 10, n. 6, June 2020.
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Registro original: |
Embrapa Clima Temperado (CPACT) |
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