Fecha/hora: 07/06/2024 21:43:11

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: | Spatiotemporal analysis of rice yield variability in two California fields
Año de publicación: | 2004
Fuente/Imprenta: | Agronomy Journal, 2004, v. 96, no. 1, p. 77-90
ISSN: | 0002-1962
DOI: | 10.2134/agronj2004.7700
Idioma: | Inglés
Contenido: | Currently, little is known about the spatial and temporal variability of rice (Oryza sativa L.) yield patterns. This information is needed before implementing any site-specific management strategy. The objective of this research was to characterize the spatial and temporal yield variability of rice grown in commercial fields in California. Rice cultivars M-202 and Koshihikari were grown and managed by a cooperating farmer, who collected yield monitor data over a 4-yr period. Alternative methods of data quality analysis were applied to the data. To evaluate temporal variability, yields from different years must be placed on a common grid. The appropriate size for these grids was tested. Large-scale spatial structure was determined using median polish while small-scale spatial structure was evaluated by computing variograms of the yield residuals after subtracting the trends. Temporal variability was determined using two approaches: (i) computation of the variance among years of the original, trend, and residual yield values at fixed points in the field and (ii) cluster analysis of the standardized trend yield values. Results from the study showed that the grid density necessary to capture the spatial variability depended on site and year. Trend surface spatial behaviors depended on year, indicating a lack of temporal stability. Variograms showed strong spatial structure of yield residuals. Cluster analysis reduced the considerable complexity in a sequence of yield maps of these fields to a few general patterns of variations among years.
Palabras-Clave: | AGRICULTURA DE PRESICION; ARROZ.
Categoría del tema: | F01 Cultivo
Registro original: | INIA Treinta y Tres (TT)
Ejemplares: | TT - (100076-1) - PXI - AP - DD - PP/Roel/Arb/2004/2 -  -  - DIS