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Biblioteca (s) : |
INIA Las Brujas. |
Fecha : |
30/08/2023 |
Actualizado : |
30/08/2023 |
Tipo de producción científica : |
Artículos en Revistas Indexadas Internacionales |
Autor : |
GASPARRI, P.; HIRIGOYEN, A.; RACHID, C.; BALMELLI, G. |
Afiliación : |
MARIA DEL PILAR GASPARRI PITA, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; ANDRES EDUARDO HIRIGOYEN DOMINGUEZ, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; ANA CECILIA RACHID CASNATI, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; GUSTAVO DANIEL BALMELLI HERNANDEZ, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay. |
Título : |
Predictive model of stump regrowth in Eucalyptus globulus based on pre-harvest information. |
Fecha de publicación : |
2023 |
Fuente / Imprenta : |
New Forests, 2023. https://doi.org/10.1007/s11056-023-09993-7 |
ISSN : |
0169-4286 (print); 1573-5095 (electronic). |
DOI : |
10.1007/s11056-023-09993-7 |
Idioma : |
Inglés |
Notas : |
Article history: Received 22 February 2023; Accepted 22 July 2023; Published 28 July 2023. -- Correspondence author: Gustavo Balmelli; email:
gbalmelli@inia.org.uy -- FUNDING: The study was funded by a scholarship awarded by INIA (National Institute of Agricultural Research) to the first author. -- |
Contenido : |
ABSTRACT.- Eucalyptus species have a great capacity for regeneration after harvest, which allows a second rotation as a coppice crop. The decision whether to manage the next rotation as a coppice crop or to replant depends on the expected economic result of each alternative. The problem that foresters face is the difficulty of predicting the productivity in the next rotation, which will depend largely on the percentage of stumps that resprout. Therefore, the objectives of this work were: (i) to identify the preharvest variables that influence stump regrowth and (ii) to develop a model for predicting the probability of stump regrowth in commercial plantations of Eucalyptus globulus in Uruguay based on pre-harvest information. Thirty-three plots were established in commercial plantations, in which silvicultural management, growth and health status before harvest were recorded, as well as the number of stumps that sprouted after harvest. Significant differences were found in the percentage of resprout for the following variables: genetic material, type of harvest machine, proportion of trees with DBH > 14 cm, proportion of trees with bark cankers, proportion of trees with epicormic shoots, and proportion of trees with apical death. However, the logistic regression model adjusted to predict the probability of regrowth only included as explanatory variables the genetic material, the type of harvesting machine, the proportion of trees with DBH > 14 cm, and the proportion of trees with bark cankers. The use of this model will allow managers of E. globulus plantations to make more informed decisions for the next rotation.
© The Author(s), under exclusive licence to Springer Nature B.V. 2023 MenosABSTRACT.- Eucalyptus species have a great capacity for regeneration after harvest, which allows a second rotation as a coppice crop. The decision whether to manage the next rotation as a coppice crop or to replant depends on the expected economic result of each alternative. The problem that foresters face is the difficulty of predicting the productivity in the next rotation, which will depend largely on the percentage of stumps that resprout. Therefore, the objectives of this work were: (i) to identify the preharvest variables that influence stump regrowth and (ii) to develop a model for predicting the probability of stump regrowth in commercial plantations of Eucalyptus globulus in Uruguay based on pre-harvest information. Thirty-three plots were established in commercial plantations, in which silvicultural management, growth and health status before harvest were recorded, as well as the number of stumps that sprouted after harvest. Significant differences were found in the percentage of resprout for the following variables: genetic material, type of harvest machine, proportion of trees with DBH > 14 cm, proportion of trees with bark cankers, proportion of trees with epicormic shoots, and proportion of trees with apical death. However, the logistic regression model adjusted to predict the probability of regrowth only included as explanatory variables the genetic material, the type of harvesting machine, the proportion of trees with DBH > 14 cm, and ... Presentar Todo |
Palabras claves : |
Blue gum plantations; Health status; Modeling; SISTEMA FORESTAL - INIA; Stump survival; Tree growth. |
Asunto categoría : |
K10 Producción forestal |
Marc : |
LEADER 02834naa a2200265 a 4500 001 1064302 005 2023-08-30 008 2023 bl uuuu u00u1 u #d 022 $a0169-4286 (print); 1573-5095 (electronic). 024 7 $a10.1007/s11056-023-09993-7$2DOI 100 1 $aGASPARRI, P. 245 $aPredictive model of stump regrowth in Eucalyptus globulus based on pre-harvest information.$h[electronic resource] 260 $c2023 500 $aArticle history: Received 22 February 2023; Accepted 22 July 2023; Published 28 July 2023. -- Correspondence author: Gustavo Balmelli; email: gbalmelli@inia.org.uy -- FUNDING: The study was funded by a scholarship awarded by INIA (National Institute of Agricultural Research) to the first author. -- 520 $aABSTRACT.- Eucalyptus species have a great capacity for regeneration after harvest, which allows a second rotation as a coppice crop. The decision whether to manage the next rotation as a coppice crop or to replant depends on the expected economic result of each alternative. The problem that foresters face is the difficulty of predicting the productivity in the next rotation, which will depend largely on the percentage of stumps that resprout. Therefore, the objectives of this work were: (i) to identify the preharvest variables that influence stump regrowth and (ii) to develop a model for predicting the probability of stump regrowth in commercial plantations of Eucalyptus globulus in Uruguay based on pre-harvest information. Thirty-three plots were established in commercial plantations, in which silvicultural management, growth and health status before harvest were recorded, as well as the number of stumps that sprouted after harvest. Significant differences were found in the percentage of resprout for the following variables: genetic material, type of harvest machine, proportion of trees with DBH > 14 cm, proportion of trees with bark cankers, proportion of trees with epicormic shoots, and proportion of trees with apical death. However, the logistic regression model adjusted to predict the probability of regrowth only included as explanatory variables the genetic material, the type of harvesting machine, the proportion of trees with DBH > 14 cm, and the proportion of trees with bark cankers. The use of this model will allow managers of E. globulus plantations to make more informed decisions for the next rotation. © The Author(s), under exclusive licence to Springer Nature B.V. 2023 653 $aBlue gum plantations 653 $aHealth status 653 $aModeling 653 $aSISTEMA FORESTAL - INIA 653 $aStump survival 653 $aTree growth 700 1 $aHIRIGOYEN, A. 700 1 $aRACHID, C. 700 1 $aBALMELLI, G. 773 $tNew Forests, 2023. https://doi.org/10.1007/s11056-023-09993-7
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Biblioteca (s) : |
INIA Las Brujas. |
Fecha actual : |
04/07/2017 |
Actualizado : |
09/01/2018 |
Tipo de producción científica : |
Informes Agroclimáticos |
Autor : |
GIMÉNEZ, A.; CASTAÑO, J.; CAL, A.; TISCORNIA, G.; SCHIAVI, C.; WADSWORTH, C. |
Título : |
Informe agroclimático 2017 - Situación a Abril. |
Fecha de publicación : |
2017 |
Fuente / Imprenta : |
Montevideo (Uruguay): INIA, 2017. |
Páginas : |
4 p. |
Idioma : |
Español |
Palabras claves : |
AGROCLIMA; AGROCLIMATOLOGÍA; BOLETIN AGROCLIMÁTICO; CARACTERIZACIÓN AGROCLIMÁTICA; DIRECCION VIENTO; ESTACIONES AGROMETEOROLOGICAS; ESTACIONES AUTOMATICAS; ESTACIONES INIA; ESTADO DEL TIEMPO; ESTRÉS HÍDRICO; GRAFICAS AGROCLIMATICOS; GRAS; HELIOFANOGRAFO; INFORMACION SATELITAL; INFORME AGROCLIMÁTICO 2017; INUNDACIONES; LLUVIAS DIARIAS; MAXIMA; MEDIA; MINIMA; PANEL SOLAR; PERSPECTIVAS CLIMATICAS; PLUVIOMETRO; PRECIPITACION NACIONAL; PREVENCION HELADAS; PRONOSTICO; SENSOR; SIMETRICO; TANQUE A; TERMOCUPLAS; TERMOHIDROGRAFO; VARIABLES AGROCLIMATICAS; VELETA. |
Thesagro : |
AGROCLIMATOLOGIA; CAMBIO CLIMATICO; CLIMA; CLIMATOLOGIA; ESTACIONES METEOROLOGICAS; ESTRES HIDRICO; EVAPORACION; EVAPOTRANSPIRACION; HUMEDAD; HUMEDAD RELATIVA; LLUVIA; METEOROLOGIA; PERSPECTIVAS; PLUVIOMETROS; PRONOSTICO DEL TIEMPO; SENSORES; SISTEMAS; SISTEMAS DE INFORMACION; SUELO; TEMPERATURA; TERMOMETROS. |
Asunto categoría : |
-- |
URL : |
http://www.ainfo.inia.uy/digital/bitstream/item/7010/1/Informe-agroclimatico-INIA-GRAS-Abril-de-2017.pdf
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Marc : |
LEADER 02139nam a2200817 a 4500 001 1057346 005 2018-01-09 008 2017 bl uuuu u0uu1 u #d 100 1 $aGIMÉNEZ, A. 245 $aInforme agroclimático 2017 - Situación a Abril.$h[electronic resource] 260 $aMontevideo (Uruguay): INIA$c2017 300 $a4 p. 650 $aAGROCLIMATOLOGIA 650 $aCAMBIO CLIMATICO 650 $aCLIMA 650 $aCLIMATOLOGIA 650 $aESTACIONES METEOROLOGICAS 650 $aESTRES HIDRICO 650 $aEVAPORACION 650 $aEVAPOTRANSPIRACION 650 $aHUMEDAD 650 $aHUMEDAD RELATIVA 650 $aLLUVIA 650 $aMETEOROLOGIA 650 $aPERSPECTIVAS 650 $aPLUVIOMETROS 650 $aPRONOSTICO DEL TIEMPO 650 $aSENSORES 650 $aSISTEMAS 650 $aSISTEMAS DE INFORMACION 650 $aSUELO 650 $aTEMPERATURA 650 $aTERMOMETROS 653 $aAGROCLIMA 653 $aAGROCLIMATOLOGÍA 653 $aBOLETIN AGROCLIMÁTICO 653 $aCARACTERIZACIÓN AGROCLIMÁTICA 653 $aDIRECCION VIENTO 653 $aESTACIONES AGROMETEOROLOGICAS 653 $aESTACIONES AUTOMATICAS 653 $aESTACIONES INIA 653 $aESTADO DEL TIEMPO 653 $aESTRÉS HÍDRICO 653 $aGRAFICAS AGROCLIMATICOS 653 $aGRAS 653 $aHELIOFANOGRAFO 653 $aINFORMACION SATELITAL 653 $aINFORME AGROCLIMÁTICO 2017 653 $aINUNDACIONES 653 $aLLUVIAS DIARIAS 653 $aMAXIMA 653 $aMEDIA 653 $aMINIMA 653 $aPANEL SOLAR 653 $aPERSPECTIVAS CLIMATICAS 653 $aPLUVIOMETRO 653 $aPRECIPITACION NACIONAL 653 $aPREVENCION HELADAS 653 $aPRONOSTICO 653 $aSENSOR 653 $aSIMETRICO 653 $aTANQUE A 653 $aTERMOCUPLAS 653 $aTERMOHIDROGRAFO 653 $aVARIABLES AGROCLIMATICAS 653 $aVELETA 700 1 $aCASTAÑO, J. 700 1 $aCAL, A. 700 1 $aTISCORNIA, G. 700 1 $aSCHIAVI, C. 700 1 $aWADSWORTH, C.
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