Hostname: page-component-848d4c4894-pftt2 Total loading time: 0 Render date: 2024-05-16T06:51:55.579Z Has data issue: false hasContentIssue false

MONITORING WESTERN FLOWER THRIPS (THYSANOPTERA: THRIPIDAE) IN “GRANNY SMITH” APPLE BLOSSOM CLUSTERS

Published online by Cambridge University Press:  31 May 2012

L. Irene Terry
Affiliation:
Department of Entomology, University of Arizona, Tucson, Arizona, USA85721
Gloria DeGrandi-Hoffman
Affiliation:
Carl Hayden Bee Research Laboratory, USDA, ARS, Tucson, Anzona, USA85719

Abstract

The efficiency and accuracy of sampling western flower thrips (Frankliniella occidentalis [Pergande]) from “Granny Smith” apple blossom clusters were analyzed during 1986–1987 to develop a sampling plan for research purposes. The accuracy of the “shake” method was compared with an “extraction” process of each of three blossom cluster types: pink, open, and petalless (petal fall). Thrip extractions from combined clusters revealed that a 9-s and 6-s “shake” removed 84 and 74%, of the thrips, respectively, but a 3-s “shake” removed 53%, and was more variable. Open blossom clusters always had higher thrips densities than either pink or petal fall clusters, regardless of the bloom state. The effects of cardinal position within trees were not consistent over time. Clusters from the top of the canopy had more thrips than lower canopy clusters, and apical clusters had more thrips than basal clusters during peak bloom. Variance component analyses indicated that thrips counts from clusters within tree were more variable than counts among trees, even when cluster types were analyzed separately. Two sets of indices (Iwao’s regression of mean crowding on mean density and Taylor’s regression of log variance on log mean density) for each cluster type indicated aggregated spatial patterns. Precision level sampling plans were developed using Iwao’s regression coefficients.

Résumé

L’efficacité et la précision dans l’échantillonage de Frankliniella occidentalis (Pergande) à partir des inflorescences du pommier “Granny Smith” ont été analysées durant 1986 et 1987 en vue de développer un model d’échantillonage à but de receherche. La précision dans la méthode de “secousse” a été comparée à celle d’un procédé d’extraction de thrips dans chacun des types suivant d’inflorescences : roses, épanouies et sans pétale. Les extraits de F. occidentalis de ces inflorescences révélaient que 9 s et 6 s de “secousse” suffisaient pour isoler respectivement 84 et 74% de lui, tandis que 3 s de secousse en isolait 53% avec plus de variation. Les inflorescences épanouies contenaient toujours une densité élevée par rapport aux inflorescences roses et aux inflorescences sans pétale malgré les étapes. La position géographique des inflorescences avait des effets irreguliers dans le temps. Les inflorescences au sommet des arbres contenaient plus de thrips que celles en dessous, les inflorescences apicales en avait plus que celles en position basale à l’épanouissement maximum des fleurs. Les analyses de variance indiquaient que les nombres de thrips entre inflorscences d’un arbre variaient plus que ceux des inflorescences d’un arbre à l’autre même lorsque les types d’inflorescences étaient analysés séparément. Deux groupes d’indices (la régression d’agrégation moyenne sur la densité moyenne de Iwao et la régression du log de la variance sur le log de la densité moyenne de Taylor) pour chacun des types d’inflorescences indiquaient une distribution agrégée. Les models d’échantillonage ont été développé en utilisant le coefficient de régression de Iwao.

Type
Articles
Copyright
Copyright © Entomological Society of Canada 1988

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Chander, R., and Verma, K.L.. 1978. A technique of sampling blossom thrips of apple. Ind. J. Ent. 40: 453.Google Scholar
DeGrandi-Hoffman, G., Terry, L.I., and Huber, R.T.. 1988. Incorporating fruit set estimates with thrips management to create a decision support system. Hortscience 23: 572574.CrossRefGoogle Scholar
Edelson, J.V. 1985. A sampling method for estimating absolute numbers of thrips on onions. The Southwest Ent. 10: 103106.Google Scholar
Henneberry, T.H., Smith, F.F., and Shriver, D.. 1964. Flower thrips in outdoor rose fields and an improved method of extracting thrips from rose flowers. J. econ. Ent. 57: 410412.CrossRefGoogle Scholar
Irwin, M.E., and Yeargan, K.V.. 1980. Sampling phytophagous thrips on soybean. pp. 283–304 in Kogan, M. (Ed.), Sampling Methods in Soybean Entomology. Springer Verlag, New York. 587 pp.Google Scholar
Irwin, M.E., Yeargan, K.V., and Marson, N.L.. 1979. Spatial and seasonal patterns of phytophagous thrips in soybean fields with comments on sampling techniques. Environ Ent. 8: 131140.CrossRefGoogle Scholar
Iwao, S. 1968. A new regression method for analyzing the aggregation pattern of animal populations. Res. Popul. Ecol. Kyoto Univ. 10: 120.Google Scholar
Kuno, E. 1969. A new method of sequential sampling to obtain the population estimates with a fixed level of precision. Res. Popul. Ecol. Kyoto Univ. 11: 127136.Google Scholar
Lewis, T. 1973. Thrips: Their Biology, Ecology and Economic Importance. Academic Press Inc., New York. 349 pp.Google Scholar
Ota, A. K. 1968. Comparison of three methods of extracting the flower thrips from rose flowers. J. econ. Ent. 61: 17541755.Google Scholar
Salifu, A.B., and Hodgson, C.J.. 1987. Dispersion patterns and sequential sampling plans for Megalurothrips sjostedti (Trybom) (Thysanoptera: Thripidae) in cowpeas. Bull. ent. Res. 77: 441449.CrossRefGoogle Scholar
SAS Institute. 1982. SAS User's Guide: Statistics. SAS Institute, Cary, NC.Google Scholar
Shelton, A.M., Nyrop, J.P., North, R.C., Petzoldt, C., and Foster, R.. 1987. Development and use of a dynamic sequential sampling program for onion thrips, Thrips tabaci (Thysanoptera: Thripidae), on onions. J. econ. Ent. 80(5): 10511056.CrossRefGoogle Scholar
Snedecor, G.W., and Cochran, W.G.. 1982. Statistical Methods. The Iowa State University Press, Ames. 507 pp.Google Scholar
Taylor, L.R. 1961. Aggregation, variance, and the mean. Nature 189: 732735.CrossRefGoogle Scholar