If you are experiencing problems downloading PDF or HTML fulltext, our helpdesk recommend clearing your browser cache and trying again. If you need help in clearing your cache, please click here . Still need help? Email email@example.com
Linear and multiple regression analysis was used to evaluate four methods that sampled summer brood tufted apple bud moth (TABM),Platynota idaeusalis (Walker), egg masses, larvae, or fruit injury, to predict apple injury caused by fall brood larvae. Summer brood egg masses were low in number and generally were not a significant factor in the regression models. Only high percentages of summer brood fruit injury or high numbers of larvae were significant. Summer brood larvae was consistently the best predictor of fall brood fruit injury. The best sampling method to predict fall brood fruit injury was 5-min timed counts taken during late July–early August. These counts explained comparatively larger percentages of variation (generally r2 values >0.60) with comparatively less sampling effort.
Document Type: Research Article
Publication date: June 1, 1986
More about this publication?
Journal of Economic Entomology is published bimonthly in February, April, June, August, October, and December. The journal publishes articles on the economic significance of insects and is divided into the following sections: apiculture & social insects; arthropods in relation to plant disease; forum; insecticide resistance and resistance management; ecotoxicology; biological and microbial control; ecology and behavior; sampling and biostatistics; household and structural insects; medical entomology; molecular entomology; veterinary entomology; forest entomology; horticultural entomology; field and forage crops, and small grains; stored-product; commodity treatment and quarantine entomology; and plant resistance. In addition to research papers, Journal of Economic Entomology publishes Letters to the Editor, interpretive articles in a Forum section, Short Communications, Rapid Communications, and Book Reviews.