Development and validation of sampling plans for Frankliniella schultzei on tomato

Tamíris A.de Araújo, Daniela T. Pezzini, Rodrigo S. Ramos, Marcelo C. Picanço, Cristina S. Bastos, Thomas E. Hunt, William D. Hutchison

Research output: Contribution to journalArticlepeer-review

7 Scopus citations

Abstract

Tomato is known to be among the most affected crops for several Frankliniella schultzei transmitted tospoviruses that cause extensive economic losses worldwide. Despite the importance of this insect as a vector in tomato, no research-based economic thresholds or sampling plans have been developed for use in integrated pest management (IPM) programs for this pest on tomato. Here, six sampling schemes and the sampling distribution of F. schultzei on tomato were investigated. We also developed and evaluated eight sampling plans for F. schultzei on tomato using nominal thresholds, numerous field data sets and computer simulation. Beating the tomato plant apical section over a white plastic tray was the best sampling method to assess F. schultzei density. In addition, F. schultzei had an aggregated sampling distribution in tomato fields. Both sequential and conventional plans resulted in similar decision-making outcomes; however, depending on the nominal threshold adopted, the economy of time when using the sequential sampling plans in relation to conventional sampling plans ranged from 30% to 80%. The beating tray sampling method used in this study provided the best accuracy and was most cost-effective for F. schultzei sampling. The nominal thresholds associated with the binomial sequential sampling plans developed are an efficient and time-saving option for managing F. schultzei and the associated tospovirus complex in tomato, contributing toward improved integrated pest management programs for this economic pest of tomato.

Original languageEnglish (US)
Article number105163
JournalCrop Protection
Volume134
DOIs
StatePublished - Aug 2020

Bibliographical note

Funding Information:
We thank the ‘Conselho Nacional de Desenvolvimento Científico e Tecnológico’ (CNPq) , the ‘Coordenação de Aperfeiçoamento de Pessoal de Nível Superior’ (CAPES) , Finance Code 001 , and the ‘Fundação de Amparo à Pesquisa do Estado de Minas Gerais’ (FAPEMIG) for financial support. We are also grateful to Dr. Robert Koch (Department of Entomology, University of Minnesota) for laboratory support during the RVSP software training period, and to Obiratanea da Silva Queiroz (Department of Entomology, University of Minnesota) for analysis and consultation. This work was developed during the PhD sandwich program of the main author funded by CAPES .

Funding Information:
We thank the ‘Conselho Nacional de Desenvolvimento Científico e Tecnológico’ (CNPq), the ‘Coordenação de Aperfeiçoamento de Pessoal de Nível Superior’ (CAPES), Finance Code 001, and the ‘Fundação de Amparo à Pesquisa do Estado de Minas Gerais’ (FAPEMIG) for financial support. We are also grateful to Dr. Robert Koch (Department of Entomology, University of Minnesota) for laboratory support during the RVSP software training period, and to Obiratanea da Silva Queiroz (Department of Entomology, University of Minnesota) for analysis and consultation. This work was developed during the PhD sandwich program of the main author funded by CAPES.

Publisher Copyright:
© 2020 Elsevier Ltd

Keywords

  • Binomial sampling
  • Common blossom thrips
  • Nominal threshold
  • Resampling software
  • Sampling method

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