Spatial distribution and fixed precision sequential sampling plan of sunn pest (Eurygaster integriceps Put.) immature stages in rainfed wheat fields using 0.1 m2 quadrate size

Document Type : Research Paper

Author

Lorestan Agricultural and Natural Resources Research and Education Center, Borujerd Campus

Abstract

The sunn Pest, Eurygaster integriceps Put. (Heteroptera: Scutelleridae) is the most important harmful insect in Iran, that feed on the leaf, stem and seed of wheat and reduce the quantity and quality of the crop. The method of quadrat sampling is among the oldest techniques in ecology. During 2004 and 2005, spatial distribution and fixed precision sequential sampling plans of Sunn pest immature stages by use of quadrate size 0.1m2 were investigated in rainfed wheat fields in Borujerd north of lorestan province, Iran. Based on R2 of regression, the Taylor's Power Law model provided a more adequate description of variance-mean relationships and Taylor's b were significantly >1 for all insect stages, indicating that immature stages of sunn pest were aggregated in rainfed wheat fields. Green's fixed-precision sequential sampling plan was designed for estimating immature stages of pestdensity at three fixed precision levels (0.1, 0.15 and 0.25), then these models were validated using 7-9 independent data. To achieve a precision of 0.25 in Green's model, which is generally accepted in integrated pest management, IPM programs, it is necessary to take samples for 2nd, 3rd, 4th instars and the total number of 5th instar plus new winged insect with an average sample numbers (ASN) of 62, 87, 67 and 25, respectively. As the precision level was increased to 0.10, average sample sizes increased to 320, 358, 325 and 145, respectively. Use of these models can provide an effective management of sunn pest E. integriceps in rainfed wheat fields and minimize sampling time and cost.  

Keywords

References

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Plant Pest Research
Volume 6, Issue 4
March 2017
Pages 31-48

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  • Receive Date: 13 March 2017
  • Accept Date: 13 March 2017

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