Development of a sequential sampling plan for classifying Thrips tabaci (Thysanoptera: Thripidae) populations in onion fields

Author:

Komondy Lidia1ORCID,Hoepting Christy A2,Pethybridge Sarah J3,Fuchs Marc3,Nault Brian A1ORCID

Affiliation:

1. Department of Entomology, Cornell University, Cornell AgriTech , Geneva, NY 14456 , USA

2. Cornell Regional Vegetable Program, Cornell Cooperative Extension , Albion, NY 14411 , USA

3. Plant Pathology and Plant-Microbe Biology Section, School of Integrative Plant Science, Cornell University, Cornell AgriTech , Geneva, NY 14456 , USA

Abstract

Abstract Onion thrips, Thrips tabaci Lindeman, is a global pest of onion crops, causing substantial economic damage by diminishing bulb yields and transmitting plant pathogens. Insecticides are used to manage T. tabaci infestations with control decisions traditionally based on action thresholds that require visually counting thrips on a fixed, predetermined number of onion plants per field. However, this approach for treatment decisions is inefficient when thrips populations are well above or below the action threshold. The aim of this research was to develop a sequential sampling plan that would provide a rapid and reliable classification of thrips populations in commercial onion fields above or below prespecified management thresholds. The study was conducted in a total of 24 commercial onion fields in New York in 2021 and 2022. Taylor’s power law and Wald’s Sequential Probability Ratio Test were used in concert to develop each sampling plan. Simulated and historical field data of thrips populations were used to further validate the efficacy of each sampling plan. Results demonstrated the sequential sampling plan required an average of 78% fewer samples to make a control decision compared with the traditional fixed-sampling approach. Treatment decisions were reached in 72% of cases after inspecting only 10 plants, while only 6% of the cases required examining more than 25 plants. Comparisons with fixed-sample sizes ranging from 23 to 68 plants revealed a 96% agreement in decision-making and a 78% reduction in sampling effort when using the sequential sampling plans.

Funder

New York State Farm Viability Institute

Publisher

Oxford University Press (OUP)

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