Fecha/hora: 11/06/2024 04:48:53

Biblioteca(s): 	INIA Treinta y Tres.	
Tipo de la producción científica: 	Artículos en Revistas Indexadas Internacionales	
Circulación/Nivel: 	A - 2	
Fecha corriente: 	18/09/2014	
Fecha de la última actualización: 	11/10/2019	
Autoria: 	ROEL, A.; PLANT, R.E.	
Afiliación: 	ALVARO ROEL DELLAZOPPA, Instituto Nacional de Investigación Agropecuaria (INIA), Uruguay.	
Título: 	Factors underlying yield variability in two California rice fields.	
Año de publicación: 	2004	
Fuente/Imprenta: 	Agronomy Journal, 2004, v. 96, no. 5, p. 1481-1494.	
DOI: 	10.2134/agronj2004.1481	
Idioma: 	Inglés	
Notas: 	Article history:  Received: Feb 4, 2004 // Published: Sept, 2004.	
Contenido: 	Modern technologies associated with precision agriculture provide the opportunity to more precisely measure yield variability and the ecological processes underlying this variability. Effective analysis of data from these measurements requires statistical methods different from those traditionally employed on data from controlled agronomic experiments. Our objective was to develop and test multivariate statistical methods appropriate for use in analyzing precision agriculture data. We analyzed a data set taken from two commercial California rice fields and consisting of yield spatial trends together with soil core data from a grid of sample points. We used cluster analysis to discern spatiotemporal patterns in grain yield. We applied a Monte Carlo randomization process to the generation of clusters to analyze cluster stability. We then used classification and regression trees (CART) to determine the factors underlying cluster distribution. The clustering procedure successfully identified stable, physically meaningful clusters with recognizable spatial and temporal structure. Thus, the randomization procedure may present an attractive alternative to fuzzy clustering. The CART analysis identified some but not all of the factors underlying the cluster patterns. The number of available data values may have been too small to take advantage of the CART partitioning capabilities.	
Palabras-Clave: 	AGRICULTURA DE PRECISION; ARROZ; CALIFORNIA.	
Categoría del tema: 	F01 Cultivo	
Registro original: 	INIA Treinta y Tres (TT)	
Ejemplares: 	TT - (100075-1) - PXI - AP - DD - PP/Roel/Arb/2004/1 -  -  - DIS