Replication data for: White fly, Bemisia afer (Priesner & Hosny 1934)
International Potato Center Dataverse OAI Archive
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Title |
Replication data for: White fly, Bemisia afer (Priesner & Hosny 1934)
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Identifier |
https://doi.org/10.21223/P3/TMCXDB
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Creator |
Gamarra, Heidy
Carhuapoma, Pablo Kreuze, Jan Kroschel, Jurgen |
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Publisher |
International Potato Center
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Description |
The effect of temperature on the development of immature stages and survival, as well as adult longevity and reproduction of Bemisia afer was studied in controlled incubator chambers at eight constant temperatures from 10º to 28ºC on its host sweetpotato. Data collected in the life-table studies under constant temperature conditions were arranged in incomplete life-table formats as required by ILCYM’s ‘model builder’ to process, analyze and develop the phenology model (development time and its variation, development rate, senescence, mortality, total oviposition and relative oviposition frequency). ILCYM’s ‘validation and simulation’ module was applied for simulating life-table parameters and for model validation. The best fit model was selected based on Akaike’s Information Criterion, a well-known goodness of fit indicator or other built in statistics (R2, Adjusted R2, MSE). The development of the Bemisia afer phenology model and its life-table parameter simulation were conducted using the Insect Life Cycle Modeling (ILCYM) software version 3.0 developed by CIP. It is freely available at CIP’s website https://research.cip.cgiar.org/confluence/display/ilcym/
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Subject |
Agricultural Sciences
Earth and Environmental Sciences Bemisia afer Development time Reproduction Longevity Temperature-Dependent Phenology Model Non-linear equation Life-table parameters Pest risk assessment |
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Language |
English
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Contributor |
Administrator, CIP
International Potato Center CGIAR Research Program on Roots, Tubers and Bananas (RTB) Federal Ministry of Cooperation and Development (BMZ), Germany (PI) Jurgen Kroschel Project: Predicting climate change-induced vulnerability of African agricultural systems to major insect pests through advanced insect phenology modeling and decision aid development for adaptation planning |
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Type |
txt, asc
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