Modelling the interaction between a pest (Aculops lycopersici), two predators (Pronematus ubiquitus and Macrolophus pygmaeus) and climate variables: a 3-year greenhouse study in a tomato crop

Pest management science(2023)

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摘要
BACKGROUND: The tomato russet mite, Aculops lycopersici, is a major pest in tomato crops, causing damage through leaf and stem browning, defoliation and russeting of fruit. Biological control of this mite on tomato plants is difficult. While several phytoseiid mites feed on the pest, they cannot survive, move, or reproduce on tomato plants due to the presence of glandular trichomes. Pronematus ubiquitus has recently been identified as a biocontrol agent of A. lycopersici in tomato crops, but the predator-prey interaction between these two species is not well studied. In this paper, we present a validated logistic regression predator-prey model based on a 3-year study supplemented with additional datasets. Besides the predator and the prey, this model takes into account an extra generalist predator, Macrolophus pygmaeus, and various climate parameters. RESULTS: The population trend of A. lycopersici is best explained by the presence of the predator P. ubiquitus, the relative humidity and the fact that the crop was lit or unlit using artificial light. P. ubiquitus has proved to be an efficient biocontrol agent of A. lycopersici. For P. ubiquitus the presence of M. pygmaeus, the vapour pressure deficit, the number of light hours and radiation explained the population trend best. For both the predator and the prey density-dependent interactions were identified. Model outcomes are discussed in detail. CONCLUSION: Our study provides insights into the potential use of P. ubiquitus as a biocontrol agent for A. lycopersici in tomato crops in combination with M. pygmaeus. However, we highlight the importance of considering the presence of other predators and environmental conditions when developing integrated pest management strategies. (c) 2023 Society of Chemical Industry.
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关键词
tomato russet mite, logistic regression, predatory mites, population model, horticulture, biological control
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