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Title
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Simplified modelling enhances biocontrol decision making in tomato greenhouses for three important pest species
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Author
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Abstract
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| Generalist and specialist predators are successfully used in biocontrol programs in greenhouse vegetable crops, like tomato. A greenhouse ecosystem is rather simple and provides an excellent opportunity for developing predator–prey decision models. Three systems were selected: (1) the generalist predatory bug Macrolophus pygmaeus and the greenhouse whitefly Trialeurodes vaporariorum, (2) the generalist predatory bug Nesidiocoris tenuis and the tobacco whitefly Bemisia tabaci and (3) the specialist predatory mite Phytoseiulus persimilis and the spider mite Tetranychus urticae. The study is based on an extensive field dataset. No complex mathematical predator–prey models were developed. A binomial variable was given the value of “0” for the period when the pest was not under control. As soon as the population declined after the peak density, this variable was given a value of “1”. The relationship between the densities of the prey and the predator was checked using a logistic regression model. The validated models do not calculate future pest densities but rather predict when pest control should be initiated, based on the number of pests and predators present at a certain time. Numerical simulation of the prey isoclines showed an L-shaped curve for the generalist predators and a linear curve for the specialist predators. Our simple, empirical modelling approach provides satisfactory models for biocontrol purposes. When combined with a standardized monitoring protocol, these models can be implemented in decision tools. In the future, more data will allow a machine learn-ing approach, in which additional parameters like temperature, humidity, and time can be included. |
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Language
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English
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Source (journal)
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Journal of pest science. - Berlin
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Publication
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Heidelberg
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Springer heidelberg
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2020
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ISSN
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1612-4758
[print]
1612-4766
[online]
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DOI
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10.1007/S10340-020-01256-0
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Volume/pages
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p. 1-11
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ISI
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000542061300001
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Full text (Publisher's DOI)
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Full text (open access)
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Full text (publisher's version - intranet only)
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