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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 ,
Suzanne Shriner ,
Robert Hollingsworth ,
Gabriel Moura Mascarin ,
Bernardo Chaves ,
Traice Matsumoto  and
Steven P. Arthurs
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
*
*E-mail: [email protected]
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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.

Keywords

Hypothenemus hampeipest monitoringsequential sampling planCoffea arabica
Type
Research Paper
Information
International Journal of Tropical Insect Science , Volume 38 , Issue 4 , December 2018 , pp. 418 - 426
Copyright
Copyright © icipe 2018 

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References

Aristizábal, L. F., Bustillo, A. E. and Arthurs, S. P. (2016) Integrated pest management of coffee berry borer: Strategies from Latin America that could be useful for coffee farmers in Hawaii. Insects 7, 6. doi:10.3390/insects7010006.Google Scholar
Aristizábal, L. F., Johnson, M., Shriner, S., Hollingsworth, R., Manoukis, N., Myers, R., Bayman, P. and Arthurs, S. P. (2017a) Integrated pest management of coffee berry borer in Hawaii and Puerto Rico: Current status and prospects. Insects 8, 123. doi.org/10.3390/insects8040123.Google Scholar
Aristizábal, L. F., Shriner, S., Hollingsworth, R. and Arthurs, S. P. (2017b) Flight activity and field infestation relationships for coffee berry borer Hypothenemus hampei (Ferrari) in commercial coffee plantations in Kona and Kau Districts, Hawaii. Journal of Economic Entomology 110, 2421–2427. doi: 10.1093/jee/tox215.Google Scholar
Aristizábal, L. F., Lara, O. and Arthurs, S. P. (2012) Implementing an integrated pest management program for coffee berry borer in a specialty coffee plantation in Colombia. Journal of Integrated Pest Management 3, G1–G5.Google Scholar
Baker, P. S. (1989) A sampling plan for a control project against the coffee berry borer (Hypothenemus hampei) in Mexico. Tropical Pest Management 35, 169–172.Google Scholar
Baker, P. S. (1999) The coffee berry borer in Colombia. Final report of the DFID – Cenicafé CABI Bioscience IPM for coffee project. Chinchiná, Colombia, 154 pp.Google Scholar
Bittenbender, H. C. and Easton Smith, V. (2008) Growing Coffee in Hawaii, revised edition. College of Tropical Agriculture and Human Resources (CTAHR), University of Hawaii at Mānoa, 40 pp.Google Scholar
Bittenbender, H. C., Wright, M. and Greco, E. (2017) How to make a coffee berry borer (CBB) trap. College of Tropical Agriculture and Human Resources (CTAHR), University of Hawaii at Mānoa, online publication https://www.ctahr.hawaii.edu/Site/CBBTrap.aspx (accessed 2.27.17).Google Scholar
Burbano, E., Wright, M., Bright, D. E. and Vega, F. E. (2011) New record for the coffee berry borer, Hypothenemus hampei, in Hawaii. Journal of Insect Science 11, 117. doi:10.1673/031.011.11701Google Scholar
Bustillo, A. E. (2006) Una revision sobre la broca del café, Hypothenemus hampei (Coleoptera: Curculionidae: Scolytinae) en Colombia. Revista Colombiana de Entomologia 32, 101–116.Google Scholar
Bustillo, A. E., Cardenas, M. R., Villalba, D., Orozco, J., Benavides, M. P. and Posada, F. J. (1998) Manejo integrado de la broca del café Hypothenemus hampei (Ferrari) en Colombia. Cenicafé, Chinchiná, Colombia. 134 pp.Google Scholar
Duque, H. and Chaves, B. (2000) Estudio sobre la adopcion del manejo integrado de la broca del café. Cenicafé, Chinchiná, Colombia. 90 pp.Google Scholar
Fernandes, F. L., Picanço, M. C., Campos, S. O., Bastos, C. S., Chediak, M., Guedes, R. N. C. and Da Silva, R. S. (2011) Economic injury level for the coffee berry borer (Coleoptera: Curculionidae: Scolytinae) using attractive traps in Brazilian coffee fields. Journal of Economic Entomology 104, 1909–1917.Google Scholar
Fernandes, F. L., Picanço, M. C., Fernandes, M. E. S., Dângelo, R. A. C., Souza, F. F. and Guedes, R. N. C. (2015) A new and highly effective sampling plan using attractant-baited traps for the coffee berry borer (Hypothenemus hampei). Journal of Pest Science 88, 289–299.Google Scholar
Greco, E. B. and Wright, M. G. (2013) Dispersion and sequential sampling plan for Xylosandrus compactus (Coleoptera: Curculionidade) infesting Hawaii coffee plantation. Environmental Entomology 42, 277–282.Google Scholar
Green, R. H. (1970) On fixed precision level sequential sampling. Researches on Population Ecology 12, 249–251.Google Scholar
Hawaii Department of Agriculture (2017) Plant Industry Division, Coffee berry borer information page, http://hdoa.hawaii.gov/pi/ppc/cbbinfo/ (7.31.2017).Google Scholar
ICO (International Coffee Organization) (2014) ICO Annual Review 2013/14, http://www.ico.org/ (7.31.2017).Google Scholar
Jaramillo, J., Borgemeister, C. and Baker, P. (2006) Coffee berry borer Hypothenemus hampei (Coleoptera: Curculionidae): Searching for sustainable control strategies. Bulletin of Entomological Research 96, 223–233.Google Scholar
Kawabata, A. M., Nakamoto, S. T. and Curtiss, R. T. (2015) Recommendations for coffee berry borer integrated pest management in Hawai'i 2015. University of Hawaii, Mänoa publication # IP-33, http://www.ctahr.hawaii.edu/oc/freepubs/pdf/IP-33.pdf (accessed January 30, 2017).Google Scholar
Mariño, Y., Vega, V. J., Garcia, J. M., Verle-Rodrigues, J. C., Garcia, N. M. and Bayman, P. (2017) The coffee berry borer (Coleoptera: Curculionidae) in Puerto Rico: Distribution, infestation, and population per fruit. Journal of Insect Science 17, 58.Google Scholar
Messing, R. H. (2012) The coffee berry borer (Hypothenemus hampei) invades Hawaii: Preliminary investigations of traps response and alternate hosts. Insects 3, 640–652. doi:10.3390/insects3030640.Google Scholar
Moon, R. D. and Wilson, L. T. (2009) Sampling for detection, estimation and IPM decision making, pp. 75–89. In Integrated Pest Management Concepts, Tactics, Strategies and Studies (edited by Radcliffe, E. B., Hutchison, W. D. and Cancelado, R. E.). Cambridge University Press, New York, USA.Google Scholar
Pereira, A. E., Vilela, E. F., Tinoco, R. S., De Lima, J. O. G., Fantine, A. K., Morais, E. G. and França, C. F. (2012) Correlation between numbers captured and infestation levels of the coffee berry-borer, Hypothenemus hampei: A preliminary basis for an action threshold using baited traps. International Journal of Pest Management 58, 183–190.Google Scholar
Pulakkatu-thodi, I., Gutierrez, R. and Wright, M. (2017) Comparison of sampling intensity to estimate infestations of coffee berry borer on Hawaii. Proceedings of the Hawaiian Entomological Society 49, 11–16.Google Scholar
R Core Team (2015) R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria. http://www.R-project.org/.Google Scholar
Rodríguez, D., Cure, J. R., Gutierrez, A. P., Cotes, J. M. and Cantor, F. (2013) A coffee agroecosystem model: II. Dynamics of coffee berry borer. Ecological Modelling 248, 203–214.Google Scholar
Ruiz, C. and Baker, S. P. (2010) Life table of Hypothenemus hampei (Ferrari) in relation to coffee berry phenology under Colombian field conditions. Scientia Agricola (Piracicaba, Braz.) 67, 658–668.Google Scholar
Ruiz, R., Uribe, P. T. and Riley, J. (2000) The effect of sample size and spatial scale on Taylor's power law parameters for coffee berry borer (Coleoptera: Scolytidae). Tropical Agriculture 77, 249–261.Google Scholar
Southwood, T. R. and Henderson, P. A. (2000) Ecological Methods, 3rd edn. Wiley-Blackwell, Oxford, UK. 592 pp.Google Scholar
Taylor, L. R. (1961) Aggregation, variance and the mean. Nature (London) 189, 732–735.Google Scholar
Taylor, L. R. (1984) Assessing and interpreting the spatial distribution of insect populations. Annual Review of Entomology 29, 321–327.Google Scholar
Trujillo, E. H. I., Aristizábal, L. F., Bustillo, A. E. and Jiménez, Q. M. (2006) Evaluación de métodos para cuantificar poblaciones de broca del café, Hypothenemus hampei (Ferrari) (Coleoptera: Curculionidae: Scolytinae) en fincas de caficultores experimentadores. Revista Colombiana de Entomología 32, 39–44.Google Scholar
USDA-NASS (2017) Hawaii Coffee Marketing Preliminary Season Estimates, February 1st, 2017, https://www.nass.usda.gov (2/16/2017).Google Scholar
Vega, F. E., Infante, F. and Johnson, A. J. (2015) The genus Hypothenemus, with emphasis on H. hampei, the coffee berry borer, pp. 427–494. In Bark Beetles, Biology and Ecology of Native and Invasive Species, 1st ed. (edited by Vega, F. E. and Hofstetter, R. W.). Elsevier, London, UK.Google Scholar
Villacorta, A., Wilson, L. T., Cfarrilla, E. and Ochoa, H. (2006) Enumerative and binomial sequential sampling plan for damage caused to coffee by larvae of Leucoptera coffeella (Guérin-Méneville) (Lepidoptera: Lyonetiidae) in Guatemala. Revista Peruviana de Entomología 45, 83–89.Google Scholar