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Field sampling strategies for coffee berry borer (Coleoptera: Curculionidae: Scolytinae) infesting berries in coffee farms in Hawaii

Published online by Cambridge University Press:  24 September 2018

Luis F. Aristizábal*
Affiliation:
P.O. Box 5579, Kailua-Kona, HI, 96745, USA
Suzanne Shriner
Affiliation:
Synergistic Hawaii Agriculture Council, Hilo, HI, USA
Robert Hollingsworth
Affiliation:
Daniel K. Inouye US Pacific Basin Agricultural Research Center, Hilo, HI, USA
Gabriel Moura Mascarin
Affiliation:
Embrapa Meio Ambiente, Rodovia SP-340, Tanquinho Velho, Jaguariúna, SP, Brazil
Bernardo Chaves
Affiliation:
Washington State University, Prosser, Irrigated Agriculture Research & Extension Center, Prosser, WA 99350, USA
Traice Matsumoto
Affiliation:
Daniel K. Inouye US Pacific Basin Agricultural Research Center, Hilo, HI, USA
Steven P. Arthurs
Affiliation:
Department of Entomology, Texas A&M University, College Station, TX, USA
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Abstract

The coffee berry borer (CBB), Hypothenemus hampei Ferrari, a recent invader to Hawaii, is impacting coffee growers by reducing yields and quality and increasing production costs. Monitoring strategies are needed to assess infestations and where control operations are warranted, and evaluate their effectiveness. To develop and validate a fixed-precision sequential sampling plan, an intensive CBB sampling programme was conducted in 17 small farms in Kona and Kau districts in the Big Island in 2016/17. At each location, 30 trees/ha were monitored at 2–4 week intervals. Results show that the CBB has an aggregated spatial distribution based on Taylor's power law parameters. According to Green's stop line formula, between 6 and 50 coffee branches per ha (sample unit) are required to estimate infestation rates of 1.5–2.5% infested green berries (suggested economic threshold) with a precision fixed at 10 to 25%. Concurrently, a modified strategy was tested on 14 farms, in which only infested green berries (not total) was counted. The standard and modified sampling methods were highly correlated (R2 ≥ 0.98), while the modified approach required on average only 35 min (27% less time) to complete, with an additional 24 min taken to observe the position of the CBB inside the berry. Our data also show that berry infestation rates of CBB prior to harvest were a good predictor of the total defects resulting in processed green coffee from these farms (Pearson's r coefficient of 0.82). Our findings support improved sampling for the CBB under Hawaiian conditions using a simpler and faster monitoring strategy based on counting green infested berries.

Type
Research Paper
Copyright
Copyright © icipe 2018 

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