Toward anticipating pest responses to fruit farms: Revealing factors influencing the population dynamics of the Oriental Fruit Fly via automatic field monitoring

Cheng Long Chuang, En Cheng Yang, Chwan Lu Tseng, Chia Pang Chen, Gi Shih Lien, Joe Air Jiang

Research output: Contribution to journalArticle

9 Citations (Scopus)


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.

Original languageEnglish
Pages (from-to)148-161
Number of pages14
JournalComputers and Electronics in Agriculture
Publication statusPublished - Nov 1 2014



  • Bactrocera dorsalis
  • Forecast modeling
  • Information and communications technology
  • Oriental fruit fly
  • Population dynamics
  • Wireless sensor network

ASJC Scopus subject areas

  • Agronomy and Crop Science
  • Horticulture
  • Forestry
  • Computer Science Applications
  • Animal Science and Zoology

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