Document Type : Agricultural Entomology
Authors
- Amir Mohseni Amin 1
- Mirreza Jamshidi 2
- maryam forouzan 3
- Mohamad Taghi Tohidi 4
- Abas Khanizad 5
- Asgar Jouzian 6
1 Iranian Research Institute of Plant Protection, Education and Extension Organization, Tehran, Iran
2 Plant Protection Research Department, Lorestan Agricultural and Natural Resources Research and Education Center, AREEO, Khorramabad, Iran.
3 Assistant Professor, West Azerbaijan, Agricultural and Natural Resources Research and Education Center, AREEO, Urmia , Iran
4 Instructor, Kermanshah, Agricultural and Natural Resources Research and Education Center, AREEO, Kermanshah, Iran
5 Instructor, Kurdestan Agricultural and Natural Resources Research and Education Center, AREEO, Sanandaj, Iran
6 Assistant Professor, Ilam, Agricultural and Natural Resources Research and Education Center, AREEO, Ilam, Iran
Abstract
Abstract
Chickpea pod borer, Heliothis viriplaca, is an important pest of rain-fed chickpea (Cicer arietinum L.) fields in most regions of Iran. During 2017-2018, spatial distribution and fixed precision sequential sampling plans of, H. viriplaca population were investigated in rain-fed chickpea fields in Lorestan provinces, Noorabad-Aleshtar and Kuhdasht. Regarding to the fitting of data with Taylor's power law and Iwao’s patchiness, parameters of these methods were used to develop of enumerative sequential sampling plans for each region. Results showed that, Taylor's b and Iwao’s β were significantly>1, indicating that H. viriplaca populations were aggregated in Lorestan provinces. Sample size curves were calculated and compared at 10%, 15% and 25% levels of precision. Also, for each model, Green's or Kuno’s fixed precision sequential sampling plans or both models were validated using 7 independent data sets. Validation results of these models showed that, to achive a precision of 0.25, which is generally accepted in IPM programs, it is necessary to take samples with an average sample number (ASN) of 58 and 66 samples for green’s and kuno’s models, respectively.
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