TY - JOUR
T1 - Toward anticipating pest responses to fruit farms
T2 - Revealing factors influencing the population dynamics of the Oriental Fruit Fly via automatic field monitoring
AU - Chuang, Cheng Long
AU - Yang, En Cheng
AU - Tseng, Chwan Lu
AU - Chen, Chia Pang
AU - Lien, Gi Shih
AU - Jiang, Joe Air
N1 - Funding Information:
This work was supported in part by the National Science Council of the Executive Yuan and the Council of Agriculture of the Executive Yuan, Taiwan under contracts: NSC 102-3113-P-002-037, NSC 101-2221-E-002-149-MY3, 102AS-7.1.2-BQ-B1. This work was also supported by the National Science Council, National Taiwan University and Intel Corporation under Grants NSC 101-2911-I-002-001, NTU 102R7501 and NTU 102R7616-2. The authors would like to thank their research team members for their valuable suggestions and contributions to this work.
Publisher Copyright:
© 2014 Elsevier B.V.
PY - 2014/11/1
Y1 - 2014/11/1
N2 - The Oriental Fruit Fly (OFF), Bactrocera dorsalis (Hendel), is one of most devastating insect pests that have periodically caused serious damage to fruit farms in Taiwan and many countries in the world. In the past, many studies reported that the population dynamics of OFF was partially correlated to the weather and the historical population development of OFF in the field. By making the best use of modern info-communication technologies (ICTs), long-term pest population data and microclimate variables measured with uniquely fine spatiotemporal resolution are now available to reveal the population dynamics of OFF. An analysis of data over three years using the Vector Auto-Regressive and Moving-Average model with eXogenous variables (VARMAX) was proposed to unravel the regulatory mechanism between the population dynamics of OFF and microclimate factors. In addition, the proposed model provides a 7-day forecast for population dynamics of OFF. The accuracy of 7-day risk level forecasting yielded by the proposed model ranges from 0.87 to 0.97, and the average root-mean squared errors of forecasting the population dynamics fall in the interval between 0.31 and 4.95 per day per farm. The proposed forecasting model can allow authorities to gain a better understanding of the dynamics of OFF and anticipate pest-related problems, so they can make preemptive and effective pest management decisions before the real problems occur.
AB - The Oriental Fruit Fly (OFF), Bactrocera dorsalis (Hendel), is one of most devastating insect pests that have periodically caused serious damage to fruit farms in Taiwan and many countries in the world. In the past, many studies reported that the population dynamics of OFF was partially correlated to the weather and the historical population development of OFF in the field. By making the best use of modern info-communication technologies (ICTs), long-term pest population data and microclimate variables measured with uniquely fine spatiotemporal resolution are now available to reveal the population dynamics of OFF. An analysis of data over three years using the Vector Auto-Regressive and Moving-Average model with eXogenous variables (VARMAX) was proposed to unravel the regulatory mechanism between the population dynamics of OFF and microclimate factors. In addition, the proposed model provides a 7-day forecast for population dynamics of OFF. The accuracy of 7-day risk level forecasting yielded by the proposed model ranges from 0.87 to 0.97, and the average root-mean squared errors of forecasting the population dynamics fall in the interval between 0.31 and 4.95 per day per farm. The proposed forecasting model can allow authorities to gain a better understanding of the dynamics of OFF and anticipate pest-related problems, so they can make preemptive and effective pest management decisions before the real problems occur.
KW - Bactrocera dorsalis
KW - Forecast modeling
KW - Information and communications technology
KW - Oriental fruit fly
KW - Population dynamics
KW - Wireless sensor network
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U2 - 10.1016/j.compag.2014.09.018
DO - 10.1016/j.compag.2014.09.018
M3 - Article
AN - SCOPUS:84908374944
SN - 0168-1699
VL - 109
SP - 148
EP - 161
JO - Computers and Electronics in Agriculture
JF - Computers and Electronics in Agriculture
ER -