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A GENERAL METHOD FOR ESTIMATING CEREAL APHID POPULATIONS IN SMALL GRAIN FIELDS BASED ON FREQUENCY OF OCCURRENCE

Published online by Cambridge University Press:  31 May 2012

G.L. Hein
Affiliation:
University of Nebraska, Panhandle Research and Extension Center, 4502 Avenue I, Scottsbluff, Nebraska, USA 69361
N.C. Elliott
Affiliation:
USDA, ARS, SPA, Plant Science Research Laboratory, 1301 North Western Street, Stillwater, Oklahoma, USA 74075
G.J. Michels Jr.
Affiliation:
Texas A&M University, Agricultural Experiment Station, PO Drawer 10, Bushland, Texas, USA 79012
R.W. Kieckhefer
Affiliation:
USDA, ARS, NPA, Northern Grain Insects Research Laboratory, Rural Route #3, Brookings, South Dakota, USA 57006

Abstract

Similarities in population parameters among aphid species led us to investigate the potential for a single set of parameters that can be used to develop a ‘generic’ sampling plan for multiple small grain aphid species. A weighted average for the slope and intercept used to relate the proportion of infested tillers to the number of aphids per tiller was determined from the data in 15 published reports. These average parameter estimates were used to predict the number of aphids per tiller in 48 wheat fields sampled for four aphid species. The predicted estimates were regressed on the observed estimates with neither slopes nor intercepts differing significantly from one or zero, respectively. Therefore, it appears the single model is adequate for predicting aphid density for the aphid species tested.

Résumé

La similitude entre les variables démographiques de différentes espèces de pucerons nous a amenés à nous questionner sur la possibilité d’utiliser un seul ensemble de variables pour mettre au point un plan d’échantillonnage ‘générique’ des diverses espèces de pucerons des petits grains. Une moyenne, pondérée en fonction de la pente et de l’intersect, utilisée pour établir le rapport entre la proportion de talles infestées et le nombre de pucerons par talle a été déterminée à partir des données relevées dans 15 rapports publiés. Ces estimations moyennes des variables ont servi à prédire le nombre de pucerons par talle dans 48 champs de blé où quatre espèces de pucerons ont été échantillonnées. La régression entre les estimations obtenues et les valeurs observées avait une pente qui ne différait pas de 1 et un intersect qui ne différait pas de 0. Il semble donc que ce modèle permette de prédire adéquatement la densité des pucerons dans le cas des espèces rencontrées ici.

[Traduit par la Rédaction]

Type
Articles
Copyright
Copyright © Entomological Society of Canada 1995

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References

Ekbom, B.S. 1987. Incidence counts for estimating densities of Rhopalosiphum padi (Homoptera: Aphididae). Journal of Economic Entomology 80: 933935.Google Scholar
Elliott, N.C., Kieckhefer, R.W., and Walgenbach, D.D.. 1990. Binomial sequential sampling methods for cereal aphids in small grains. Journal of Economic Entomology 83: 13811387.Google Scholar
Feng, M.G., and Nowierski, R.M.. 1992. Spatial distribution and sampling plans for four species of cereal aphids (Homoptera: Aphididae) infesting spring wheat in southwestern Idaho. Journal of Economic Entomology 85: 830837.Google Scholar
Feng, M.G., Nowierski, R.M., and Zeng, Z.. 1993. Populations of Sitobion avenae (Homoptera: Aphididae) and Aphidius ervi (Hymenoptera: Braconidae) on spring wheat in the northwestern United States: Spatial distribution and sequential sampling plans based on numerical and binomial counts. Entomologia Experimentalis et Applicata 67: 109117.Google Scholar
Jones, V.P. 1990. Developing sampling plans for spider mites (Acari: Tetranychidae): Those who don't remember the past may have to repeat it. Journal of Economic Entomology 83: 16561664.Google Scholar
Legg, D.E., Hein, G.L., Nowierski, R.M., Feng, M.G., Peairs, F.B., Karner, M., and Cuperus, G.W.. 1992. Binomial regression models for spring and summer infestations of the Russian wheat aphid (Homoptera: Aphididae) in the southern and western plains states and Rocky Mountain Region of the United States. Journal of Economic Entomology 85: 17791790.Google Scholar
Schaalje, G.B., and Butts, R.A.. 1992. Binomial sampling for predicting density of Russian wheat aphid (Homoptera: Aphididae) on winter wheat in the fall using a measurement error model. Journal of Economic Entomology 85: 11671175.Google Scholar
Teetes, G.L., and Sterling, W.L.A.. 1976. A sequential sampling plan for a white grub in grain sorghum. Southwestern Entomologist 1: 118121.Google Scholar
Ward, S.A., Sunderland, K.D., Chambers, R.J., and Dixon, A.F.G.. 1986. The use of incidence counts for estimation of cereal aphid populations. 3. Population development and the incidence-density relationship. Netherlands Journal of Plant Pathology 92: 175183.Google Scholar