Multi-species weed spatial variability and site-specific management maps in cultivated sunflower
- 1 May 2003
- journal article
- Published by Cambridge University Press (CUP) in Weed Science
- Vol. 51 (3), 319-328
- https://doi.org/10.1614/0043-1745(2003)051[0319:MWSVAS]2.0.CO;2
Abstract
Geostatistical techniques were used to describe and map weed spatial distribution in two sunflower fields in Cabello and Monclova, southern Spain. Data from the study were used to design intermittent spraying strategies. Weed species, overall infestation severity (IS) index, and spatial distribution varied considerably between the two sites. Weed species displayed differences in spatial dependence regardless of IS. The IS mapping of each single weed and of the overall infestation was achieved by kriging, and site-specific application maps were then drawn based on the multi-species weed map and the estimated economic threshold (ET). Herbicide treatment was assumed to be needed for an overall IS score of 2 or 3, and the infested “area exceeding the economic threshold” was determined. The overall weed-infested area varied considerably between locations. About 99 and 38% of the total area was moderately infested (IS ≥ 2) at Monclova and Cabello, respectively. Therefore, if a given herbicide were applied just to the areas exceeding the ET, a significant herbicide saving would be realized in Cabello but not in Monclova. A multi-species spatial analysis provides an opportunity to make site-specific management recommendations from a map of the distribution of IS of the total infestation. Furthermore, only in fields with hard-to-control weed species (e.g., nodding broomrape and corn caraway) would site-specific herbicide application maps developed from total weed infestations need to be complemented with targeted site-specific herbicide treatments to prevent further spread of these species, although their IS might be low.Keywords
This publication has 41 references indexed in Scilit:
- Colour and shape analysis techniques for weed detection in cereal fieldsComputers and Electronics in Agriculture, 2000
- GESTINF: a decision model for post-emergence weed management in soybean (Glycine max (L.) Merr.)Crop Protection, 1997
- SEMAGI — an expert system for weed control decision making in sunflowersCrop Protection, 1995
- Competition between Ridolfia segetum and sunflowerWeed Research, 1995
- Precipitation Estimation in Mountainous Terrain Using Multivariate Geostatistics. Part I: Structural AnalysisJournal of Applied Meteorology and Climatology, 1992
- Mapping the conditional probability of soil variablesGeoderma, 1992
- Mathematical models in weed managementCrop Protection, 1991
- Potential for automatic weed detection and selective herbicide applicationCrop Protection, 1991
- An Introduction to Applied Geostatistics.Journal of the American Statistical Association, 1991
- Weed flora of dryland crops in the Córdoba region (Spain)Weed Research, 1990