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Sampling plan for the coffee leaf miner Leucoptera coffeella with sex pheromone traps

Authors :
Raul Narciso C. Guedes
Eraldo R. Lima
Tito Bacca
J. H. M. Viana
M. C. Picanço
Source :
LOCUS Repositório Institucional da UFV, Universidade Federal de Viçosa (UFV), instacron:UFV
Publication Year :
2007
Publisher :
Journal of Applied Entomology, 2007.

Abstract

The population density of the coffee leaf miner Leucoptera coffeella (Gue ´- rin-Meneville & Perrottet) (Lep., Lyonetiidae) can be estimated using pheromone traps in coffee fields as male capture reflects this pest dam- age based on previous correlational study. However, the spatial distribu- tion of pheromone traps and their density are necessary to optimize the sampling procedure with pheromone traps. Therefore, the objectives of the present study were to determine the pheromone trap density required per hectare to sample coffee leaf miner populations and to determine the spatial distribution of the males of this pest species. The males were sampled every 8 days in 12 consecutive evaluations. Taylor's power law and frequency distributions were used to recognize the distri- bution of the male capture data, which followed a negative binomial distribution. A common K was obtained, allowing the establishment of a single conventional sampling plan for the 12 fields investigated. The adjusted sampling plan requires eight traps in an area of 30 ha for a 25% precision error. Kriging-generated maps allowed the simulation of male captures for 8, 12 and 20 traps per 30 ha and the results were compared with those obtained with absolute sampling resulting in R 2 -values of 0.30, 0.57 and 0.60 respectively. The traps were able to identify the more highly infested areas within the field and are a precise and efficient tool for sampling populations of L. coffeella. J. Appl. Entomol.

Details

Language :
English
Database :
OpenAIRE
Journal :
LOCUS Repositório Institucional da UFV, Universidade Federal de Viçosa (UFV), instacron:UFV
Accession number :
edsair.doi.dedup.....e87f9d69baffb5abbd9a7e9a2735aad6