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| Registros recuperados : 16 | |
| 5. |  | ROEL, A.; PLANT, R. Spatial and temporal analysis of rice yield variability in California. [Resumen]. ln: Conferencia Internacional de Arroz de Clima Templado, 3., 2003, Punta del Este, Uruguay Resúmenes. Montevideo (Uruguay): ACA; INIA; GMA; FLAR, 2003. p. 85 "Instituto Nacional de Investigación Agropecuaria, Uruguay (INIA); Asociación de Cultivadores de Arroz (ACA); Gremial de Molinos Arroceros (GMA); Fondo Latinoamericano de Arroz de Riego (FLAR)"| Biblioteca(s): INIA Treinta y Tres. |
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| 15. | | WILLIAMS, J.F.; HAIR, M.; FISCHER, A.J.; CHEETHAM, D.; ROEL, A.; PLANT, R. Measuring yield impact of bearded sprangletop (Leptochloa fascicularis) in California rice: abstract. ln: Rice Technical Working Group, 28., 2000 Proceedings. Biloxi, Mississippi (USA): Rice Technical Working Group, 2000. p. 158-159| Biblioteca(s): INIA Treinta y Tres. |
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| Registros recuperados : 16 | |
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 | Acceso al texto completo restringido a Biblioteca INIA Treinta y Tres. Por información adicional contacte bibliott@inia.org.uy. |
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Registro completo
|
|
Biblioteca (s) : |
INIA Treinta y Tres. |
|
Fecha actual : |
21/02/2014 |
|
Actualizado : |
03/10/2019 |
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Tipo de producción científica : |
Artículos en Revistas Indexadas Internacionales |
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Circulación / Nivel : |
A - 1 |
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Autor : |
ROEL, A.; FIRPO, H.; PLANT, R.E. |
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Afiliación : |
ROEL DELLAZOPPA, ÁLVARO, Instituto Nacional de Investigación Agropecuaria (INIA), Uruguay. |
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Título : |
Why do some farmers get higher yields? Multivariate analysis of a group of Uruguayan rice farmers. |
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Fecha de publicación : |
2007 |
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Fuente / Imprenta : |
Computers and Electronics in Agriculture, 2007, v. 58, no. 1, p. 78-92. |
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ISSN : |
0168-1699 |
|
DOI : |
10.1016/j.compag.2006.10.001 |
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Idioma : |
Inglés |
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Contenido : |
Abtract:
The technologies of precision agriculture were developed for application to site-specific crop management. Some of them require a high capital outlay, but two key component technologies, spatial analysis and global positioning systems, may both be obtained at relatively low cost. These technologies may be used profitably to improve crop management practices without the expenditures necessary for a full site-specific management program. In this paper we use exploratory spatial data analysis to study georeferenced rice production data collected on the farms of a group of Uruguayan rice growers. The objective was to identify the management practices that most distinguish farmers producing high yields from those producing low yields. A key challenge was to distinguish those differences in farmers? management practices that were due to their different approaches to farming from those that were due to their responses to differences in the land quality of their individual fields. Using a combination of classification and regression trees and graphical analysis, the most distinguishing factors were identified to be early planting, adequate fertilization, and effective irrigation. |
|
Thesagro : |
ARROZ; MANEJO; RENDIMIENTO; URUGUAY. |
|
Asunto categoría : |
F06 Riego |
|
Marc : |
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100 1 $aROEL, A.
245 $aWhy do some farmers get higher yields? Multivariate analysis of a group of Uruguayan rice farmers.$h[electronic resource]
260 $c2007
520 $aAbtract: The technologies of precision agriculture were developed for application to site-specific crop management. Some of them require a high capital outlay, but two key component technologies, spatial analysis and global positioning systems, may both be obtained at relatively low cost. These technologies may be used profitably to improve crop management practices without the expenditures necessary for a full site-specific management program. In this paper we use exploratory spatial data analysis to study georeferenced rice production data collected on the farms of a group of Uruguayan rice growers. The objective was to identify the management practices that most distinguish farmers producing high yields from those producing low yields. A key challenge was to distinguish those differences in farmers? management practices that were due to their different approaches to farming from those that were due to their responses to differences in the land quality of their individual fields. Using a combination of classification and regression trees and graphical analysis, the most distinguishing factors were identified to be early planting, adequate fertilization, and effective irrigation.
650 $aARROZ
650 $aMANEJO
650 $aRENDIMIENTO
650 $aURUGUAY
700 1 $aFIRPO, H.
700 1 $aPLANT, R.E.
773 $tComputers and Electronics in Agriculture, 2007$gv. 58, no. 1, p. 78-92.
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