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Registro Completo |
Biblioteca(s): |
Embrapa Hortaliças. |
Data corrente: |
25/02/1999 |
Data da última atualização: |
25/02/1999 |
Autoria: |
CAMPOS, G. A.; SILVEIRA, M. A. da; AZEVEDO, S. M. de; RESENDE, J. V. |
Título: |
Resistencia de linhagens de tomateiro a murcha bacteriana no Estado do Tocantins. |
Ano de publicação: |
1998 |
Fonte/Imprenta: |
In: REUNIAO ANUAL DA SOCIEDADE BRASILEIRA PARA O PROGRESSO DA CIENCIA,. 50., 1998, Natal, RN. Anais... Natal: SOBER, 1998. |
Páginas: |
nao paginado. |
Descrição Física: |
CD-ROM. |
Idioma: |
Português |
Notas: |
Resumo. |
Palavras-Chave: |
Brasil; Linkage; Resistance; Tocantins. |
Thesagro: |
Hibrido; Linhagem; Lycopersicon Esculentum; Murcha Bacteriana; Ralstonia Solanacearum; Resistência; Tomate. |
Thesaurus Nal: |
hybrids; tomatoes. |
Categoria do assunto: |
-- |
Marc: |
LEADER 00936naa a2200325 a 4500 001 1762982 005 1999-02-25 008 1998 bl uuuu u00u1 u #d 100 1 $aCAMPOS, G. A. 245 $aResistencia de linhagens de tomateiro a murcha bacteriana no Estado do Tocantins. 260 $c1998 300 $anao paginado.$cCD-ROM. 500 $aResumo. 650 $ahybrids 650 $atomatoes 650 $aHibrido 650 $aLinhagem 650 $aLycopersicon Esculentum 650 $aMurcha Bacteriana 650 $aRalstonia Solanacearum 650 $aResistência 650 $aTomate 653 $aBrasil 653 $aLinkage 653 $aResistance 653 $aTocantins 700 1 $aSILVEIRA, M. A. da 700 1 $aAZEVEDO, S. M. de 700 1 $aRESENDE, J. V. 773 $tIn: REUNIAO ANUAL DA SOCIEDADE BRASILEIRA PARA O PROGRESSO DA CIENCIA,. 50., 1998, Natal, RN. Anais... Natal: SOBER, 1998.
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Embrapa Hortaliças (CNPH) |
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Registro Completo
Biblioteca(s): |
Embrapa Milho e Sorgo. |
Data corrente: |
04/12/2023 |
Data da última atualização: |
04/12/2023 |
Tipo da produção científica: |
Artigo em Periódico Indexado |
Circulação/Nível: |
B - 2 |
Autoria: |
COSTA, T. C. e C. da; RAMOS, L. B.; CAMPANHA, M. M.; GONTIJO NETO, M. M. |
Afiliação: |
THOMAZ CORREA E CASTRO DA COSTA, CNPMS; LUCAS BARBOSA RAMOS, UNIVERSIDADE FEDERAL DE SÃO JOÃO DEL-REI; MONICA MATOSO CAMPANHA, CNPMS; MIGUEL MARQUES GONTIJO NETO, CNPMS. |
Título: |
Algorithm for the projection of forest growth and production. |
Ano de publicação: |
2023 |
Fonte/Imprenta: |
Floresta, v. 53, n. 1, p. 99-109, 2023. |
DOI: |
http://doi.org/10.5380/rf.v53i1.85562 |
Idioma: |
Inglês |
Conteúdo: |
The modeling of forest growth and production is an essential tool for forestry management because it allows us to perform simulations and project forest biometric variables in the future, thus assisting in stock planning and economic analyses. In this work, a growth and production model by diameter distribution was proposed with the application of the Weibull function based on the recovery of parameters through simplified functions between the forest attributes and the parameters of the Weibull function. The algorithm was developed in Excel’s VBA language. Validation was performed with data from the Continuous Forest Inventory (CFI) in a stand of Khaya grandifoliola and in rows of Eucalyptus spp. in the ILPF system, which were ordinarily organized into seven date combinations, from the most distant from to the closest to the projection date. The results were evaluated by the percentage standard error (SE%) applied to the projected and observed volumes and by the Kolmogorov‒Smirnov test applied to the diameter distributions to verify adherence. It was possible to identify an exact relationship for parameter c of the Weibull function as a function of the percentiles and for parameter b, improving the parameter recovery method. Another methodological improvement was the use of maximum diameter and maximum height for age to adjust the hypsometric function. The algorithm presented results for total volume with errors up to 20% in 85% of the tests. |
Palavras-Chave: |
Distribuições probabilísticas; Modelagem; Modeling; Probability distributions; Prognose. |
Thesagro: |
Produção Florestal. |
Thesaurus NAL: |
Prognosis. |
Categoria do assunto: |
K Ciência Florestal e Produtos de Origem Vegetal |
URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/doc/1159065/1/Algorithm-for-the-projection-of-forest-growth-and-production.pdf
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Marc: |
LEADER 02210naa a2200253 a 4500 001 2159065 005 2023-12-04 008 2023 bl uuuu u00u1 u #d 024 7 $ahttp://doi.org/10.5380/rf.v53i1.85562$2DOI 100 1 $aCOSTA, T. C. e C. da 245 $aAlgorithm for the projection of forest growth and production.$h[electronic resource] 260 $c2023 520 $aThe modeling of forest growth and production is an essential tool for forestry management because it allows us to perform simulations and project forest biometric variables in the future, thus assisting in stock planning and economic analyses. In this work, a growth and production model by diameter distribution was proposed with the application of the Weibull function based on the recovery of parameters through simplified functions between the forest attributes and the parameters of the Weibull function. The algorithm was developed in Excel’s VBA language. Validation was performed with data from the Continuous Forest Inventory (CFI) in a stand of Khaya grandifoliola and in rows of Eucalyptus spp. in the ILPF system, which were ordinarily organized into seven date combinations, from the most distant from to the closest to the projection date. The results were evaluated by the percentage standard error (SE%) applied to the projected and observed volumes and by the Kolmogorov‒Smirnov test applied to the diameter distributions to verify adherence. It was possible to identify an exact relationship for parameter c of the Weibull function as a function of the percentiles and for parameter b, improving the parameter recovery method. Another methodological improvement was the use of maximum diameter and maximum height for age to adjust the hypsometric function. The algorithm presented results for total volume with errors up to 20% in 85% of the tests. 650 $aPrognosis 650 $aProdução Florestal 653 $aDistribuições probabilísticas 653 $aModelagem 653 $aModeling 653 $aProbability distributions 653 $aPrognose 700 1 $aRAMOS, L. B. 700 1 $aCAMPANHA, M. M. 700 1 $aGONTIJO NETO, M. M. 773 $tFloresta$gv. 53, n. 1, p. 99-109, 2023.
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