Phenology of the San Jose Scale (Homoptera: Diaspididae)

Jorgensen, Clive D.; Rice, R. E.; Hoyt, S. C.; Westigard, P. H.

doi:10.4039/ent113149-2

Cited by 22 publications

(19 citation statements)

References 15 publications

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“…Male phenoiogy in the western United States has been determined by pheromone trapping studies (Rice and Jones 1977;Rice and Hoyt 1980). These studies were used in the development of a Predictive Extension Timing Estimator (PETE) model (Welch et al 1978) for scale (Jorgensen et al 1981), that simulates male flight activity and estimates crawler emergence based on degree-day (OD) accumulations. The future use of such predictive models for timing controls in the Northeast will depend on the collection of phenological data for model validation for this region.…”

Section: Introductionmentioning

confidence: 99%

Phenology of the San Jose Scale (Homoptera: Diaspididae) in New York State Apple Orchards,

Mague

Reissig

1983

Can Entomol

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Can. Ent. 115: 717-722 (1983) Pheromone trapping studies from 1979 to 1981 showed that there were two periods of San Jose scale, Quadraspidiotus perniciosus (Comstock), male flight activity annually in western New York apple orchards. Spring flight, which resulted from overwintering black caps, began at ca. 94-140 degree-days (base rO°C from 1 March) and occurred during bloom in the apple varieties studied. First generation crawlers emerged at ca. 360 degree-days. Second generation crawlers emerged at ca. 890 degree-days and were active throughout September. Regression analyses showed a logistic relationship between crawler density and fruit infestation, and inverse linear relationships between pheromone trap catches and San Jose scale infestation levels within trees.

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Section: Introductionmentioning

confidence: 99%

Phenology of the San Jose Scale (Homoptera: Diaspididae) in New York State Apple Orchards,

Mague

Reissig

1983

Can Entomol

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“…Densities were expressed as number of SJS males and parasitoids per pheromone trap, and number of SJS crawlers per sticky-tape trap, and summed for each generation. Generations were defined with the SJS phenology model of Jorgensen et al (1981), using meteorological data from the UCIPM website (http://www.ipm.ucdavis.edu/). Lower and upper thresholds for degree-day (DD) accumulation were 10.6 and 32.28C respectively, with appearance of crawlers predicted to be 225.0 DD after the biofix (date when first SJS males were captured), and a generation time of 583.3 DD.…”

Section: Methodsmentioning

confidence: 99%

Effects of dormant insecticide treatments on the San Jose scale (Homoptera: Diaspididae) and its parasitoids Encarsia perniciosi and Aphytis spp . ( Hymenoptera: Aphelinidae )

Badenes‐Pérez¹,

Zalom²,

Bentley³

2002

International Journal of Pest Management

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Populations of the San Jose scale (SJS), Quadraspidiotus perniciosus (Comstock), and its parasitoids, Encarsia perniciosi (Tower) and Aphytis spp. were monitored with double-sided sticky tape and pheromone traps in an almond orchard. A total of 1.21 ha plots within the orchard were treated during winter dormancy with several insecticides, including horticultural mineral oil alone, oil combined with the organophosphate diazinon at different dilution rates, and oil combined with the pyrethroid esfenvalerate in a completely randomized block design. Higher volume diazinon applications (3750 and 1870 l ha 71 ) proved effective against SJS crawlers, as did esfenvalerate. The higher volume applications had greater deposition on Kromecoat 1 cards placed in the top of the tree canopy, where SJS is most abundant. The lower-volume (935 l ha 71 ) application of diazinon provided control of first-generation crawlers similar to the other diazinon applications, but it was generally less effective in controlling subsequent generations. All insecticide treatments were associated with a reduction of parasitoid numbers, especially the esfenvalerate application.

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“…Research results defining the relationships between meteorological conditions and pest development have produced models predicting critical life history or epidemiological events of insects and disease organisms (Brunner and Rice, 1984;Jones et al, 1991;Jorgensen et al, 1981;Rice et al, 1984;Riedl et al, 1976;Sutton et al, 1981). A generalized phenology modeling system, PETE (= predictive extension timing estimator) developed at Michigan State University (Welch et al, 1978) has been adopted by several states as the basis for making IPM decisions (Croft and Knight, 1983).…”

Section: Computers and Modelsmentioning

confidence: 99%