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Prediction model for cabbage stem weevil ceutorhynchus pallidactylus Mrsh. occurrence on winther rape based on an artificial neural network

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    0468575 - ÚVGZ 2018 RIV GB eng J - Journal Article
    Klem, Karel - Spitzer, T.
    Prediction model for cabbage stem weevil ceutorhynchus pallidactylus Mrsh. occurrence on winther rape based on an artificial neural network.
    Agricultural and Forest Entomology. Roč. 19, č. 3 (2017), s. 302-308. ISSN 1461-9555. E-ISSN 1461-9563
    R&D Projects: GA MZe QJ1530373
    Research Infrastructure: CzeCOS II - 90061
    Institutional support: RVO:67179843
    Keywords : Brassica napus L * cabbage stem weevil * Ceutorhynchus pallidactylus * model * neural network * oilseed rape * weather conditions
    OECD category: Environmental sciences (social aspects to be 5.7)
    Impact factor: 1.490, year: 2017

    Cabbage stem weevil Ceutorhynchus pallidactylus Mrsh. is a important pest of oilseed rape. The impacts of weather conditions and developing a prediction model are key prerequisites for making decisions about chemical plant protection. 2 Based on data from long-term monitoring occurrence of C. pallidactylus (2002–2012), those meteorological parameters with the most significant effects on spring raid intensity were selected and a prediction model based on an artificial neural network was developed. 3 The model was trained using data on the capture of C. pallidactylus between 10 March and 26 April and on weather conditions during January/February and March/April. 4 The winning neural network provides 97% predictive reliability based on mean air temperature for the third March pentad, mean air temperature in the last week of March, mean soil temperature at a depth of 10 cm in the last decade of March, and mean soil temperature at depth of 10 cm for January/February. 5 The occurrence of C. pallidactylus decreased with increasing soil temperature during January/February, in March, the opposite effect was observed. The effect of air temperature on the occurrence of C. pallidactylus uring March has a peak form with a maximum at 3–4 ∘C and 6–7 ∘C in mid-March and at the end of March, respectively.
    Permanent Link: http://hdl.handle.net/11104/0266855

     
     
Number of the records: 1  

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