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| 7. |  | QUECINI, V.; SINSKI, I.; BOSCO, D. D.; REVERS, L. F.; BERND, R. B.; RITSCHEL, P. S.; CAMARGO, U. A. Agrobacterium-mediated genetic transformation of Vitis sp. somatic embryogenesis. In: CONGRESSO BRASILEIRO DE VITICULTURA E ENOLOGIA, 12., 2008, Bento Gonçalves. Anais... Bento Gonçalves: Embrapa Uva e Vinho, 2008. p. 143. Resumo.| Biblioteca(s): Embrapa Uva e Vinho. |
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 | Acesso ao texto completo restrito à biblioteca da Embrapa Pecuária Sudeste. Para informações adicionais entre em contato com cppse.biblioteca@embrapa.br. |
Registro Completo
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Biblioteca(s): |
Embrapa Pecuária Sudeste. |
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Data corrente: |
29/01/2019 |
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Data da última atualização: |
09/11/2023 |
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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: |
PEZZOPANE, J. R. M.; BERNARDI, A. C. de C.; BOSI, C.; CRIPPA, P. H.; SANTOS, P. M.; NARDACHIONE, E. C. |
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Afiliação: |
JOSE RICARDO MACEDO PEZZOPANE, CPPSE; ALBERTO CARLOS DE CAMPOS BERNARDI, CPPSE; Cristiam Bosi, USP/Escola Superior de Agricultura Luiz de Queiroz; Paulo Henrique Crippa, USP/Faculdade de Zootecnia e Engenharia de Alimentos; PATRICIA MENEZES SANTOS, CPPSE; Estefânia Cereda Nardachione, USP/Faculdade de Zootecnia e Engenharia de Alimentos. |
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Título: |
Assessment of Piatã palisadegrass forage mass in integrated livestock production systems using a proximal canopy reflectance sensor. |
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Ano de publicação: |
2019 |
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Fonte/Imprenta: |
European Journal of Agronomy, v. 103, p. 130-139, 2019. |
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Idioma: |
Inglês |
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Conteúdo: |
Estimates of forage mass can help in decision making for pasture management and stocking rate adjustment in pastoral systems. This study aimed to estimate Piatã palisadegrass forage mass under full sun and shaded livestock production systems using vegetation indexes obtained with a proximal canopy reflectance sensor. Pasture canopy reflectance was measured at three fractions of the radiation spectrum (670, 720, and 760 nm). Total forage mass, morphological composition, and leaf area index (LAI) were assessed at the same time as reflectance in all production systems. Reflectance data were used to calculate vegetation indexes (normalized difference vegetation index ? NDVI, normalized difference red edge ? NDVI_RE, simple ratio index ? SRI, modified simple ratio ? MSR, and chlorophyll index) for each assessment. Linear and exponential regression analyses between vegetation indexes and total forage mass, leaf+stem mass, leaf mass, and LAI were performed. The equations generated by these analyses were used to estimate such pasture variables. The best estimates of leaf+stem mass, leaf mass, and LAI were obtained using SRI (R2 between 0.55 and 0.84) for the full sun systems, MSR (R2 from 0.67 to 0.93) for the shaded systems, and NDVI (R2 between 0.65 and 0.91) when all systems were analyzed together. These pasture variables can be estimated by general equations developed for both full sun and shaded livestock production systems. However, total forage mass estimates were less efficient (R2 of 0.03?0.53), due to differences in canopy structure and senescent material content between production systems. MenosEstimates of forage mass can help in decision making for pasture management and stocking rate adjustment in pastoral systems. This study aimed to estimate Piatã palisadegrass forage mass under full sun and shaded livestock production systems using vegetation indexes obtained with a proximal canopy reflectance sensor. Pasture canopy reflectance was measured at three fractions of the radiation spectrum (670, 720, and 760 nm). Total forage mass, morphological composition, and leaf area index (LAI) were assessed at the same time as reflectance in all production systems. Reflectance data were used to calculate vegetation indexes (normalized difference vegetation index ? NDVI, normalized difference red edge ? NDVI_RE, simple ratio index ? SRI, modified simple ratio ? MSR, and chlorophyll index) for each assessment. Linear and exponential regression analyses between vegetation indexes and total forage mass, leaf+stem mass, leaf mass, and LAI were performed. The equations generated by these analyses were used to estimate such pasture variables. The best estimates of leaf+stem mass, leaf mass, and LAI were obtained using SRI (R2 between 0.55 and 0.84) for the full sun systems, MSR (R2 from 0.67 to 0.93) for the shaded systems, and NDVI (R2 between 0.65 and 0.91) when all systems were analyzed together. These pasture variables can be estimated by general equations developed for both full sun and shaded livestock production systems. However, total forage mass estimates were less effici... Mostrar Tudo |
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Palavras-Chave: |
Capim Piatã; Forage mass; ILPF; Piatã palisadegrass forage. |
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Thesagro: |
Pastagem; Sombreamento. |
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Thesaurus NAL: |
Pastures. |
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Categoria do assunto: |
A Sistemas de Cultivo |
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Marc: |
LEADER 02420naa a2200265 a 4500
001 2104948
005 2023-11-09
008 2019 bl uuuu u00u1 u #d
100 1 $aPEZZOPANE, J. R. M.
245 $aAssessment of Piatã palisadegrass forage mass in integrated livestock production systems using a proximal canopy reflectance sensor.$h[electronic resource]
260 $c2019
520 $aEstimates of forage mass can help in decision making for pasture management and stocking rate adjustment in pastoral systems. This study aimed to estimate Piatã palisadegrass forage mass under full sun and shaded livestock production systems using vegetation indexes obtained with a proximal canopy reflectance sensor. Pasture canopy reflectance was measured at three fractions of the radiation spectrum (670, 720, and 760 nm). Total forage mass, morphological composition, and leaf area index (LAI) were assessed at the same time as reflectance in all production systems. Reflectance data were used to calculate vegetation indexes (normalized difference vegetation index ? NDVI, normalized difference red edge ? NDVI_RE, simple ratio index ? SRI, modified simple ratio ? MSR, and chlorophyll index) for each assessment. Linear and exponential regression analyses between vegetation indexes and total forage mass, leaf+stem mass, leaf mass, and LAI were performed. The equations generated by these analyses were used to estimate such pasture variables. The best estimates of leaf+stem mass, leaf mass, and LAI were obtained using SRI (R2 between 0.55 and 0.84) for the full sun systems, MSR (R2 from 0.67 to 0.93) for the shaded systems, and NDVI (R2 between 0.65 and 0.91) when all systems were analyzed together. These pasture variables can be estimated by general equations developed for both full sun and shaded livestock production systems. However, total forage mass estimates were less efficient (R2 of 0.03?0.53), due to differences in canopy structure and senescent material content between production systems.
650 $aPastures
650 $aPastagem
650 $aSombreamento
653 $aCapim Piatã
653 $aForage mass
653 $aILPF
653 $aPiatã palisadegrass forage
700 1 $aBERNARDI, A. C. de C.
700 1 $aBOSI, C.
700 1 $aCRIPPA, P. H.
700 1 $aSANTOS, P. M.
700 1 $aNARDACHIONE, E. C.
773 $tEuropean Journal of Agronomy$gv. 103, p. 130-139, 2019.
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