کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
84235 158870 2014 14 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Toward anticipating pest responses to fruit farms: Revealing factors influencing the population dynamics of the Oriental Fruit Fly via automatic field monitoring
ترجمه فارسی عنوان
به پیش بینی پاسخ های آفات به مزارع میوه: شناسایی عوامل موثر بر پویایی جمعیت از پرواز میوه های میانه از طریق نظارت خودکار میدان
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر نرم افزارهای علوم کامپیوتر
چکیده انگلیسی


• An automated tool was successfully engineered for monitoring pest populations.
• Observation data revealed important pest population dynamics.
• Revealed how endogenous and exogenous factors affect the pest population.
• 12 days rhythm and 16 days life cycle have been revealed via collected data.

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.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Computers and Electronics in Agriculture - Volume 109, November 2014, Pages 148–161
نویسندگان
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