Dwelling intensity of horse-chestnut miner (Cameraria ohridella) larvae in various leaves insolation and temperature was measured to determine whether this pest's development follows a predictable pattern or depends more on local microenvironment conditions. Mines growing on leaves of mature host plants (Aesculus hippocastanum L.) in their natural conditions were photographed for two consecutive generations of the pest and in two separated vegetation periods. Apart from meteorological data obtained from the nearest station, the temperature of intact and mined parts of sun-exposed and shaded leaf blades was measured at various daytimes throughout the experiment. Obtained sets of digital data were analysed and combined to model mine area growth as a function of degree-days sum by adopting of Verhulst logistic equation. We showed the predictive potential of our model based on experimental data, and it may be useful in the scheduling of pest control measures in natural conditions. Our analyses also revealed that despite significant differences in microenvironment conditions depending on mines' insolation, the horse-chestnut miner larvae could partially compensate for them and complete their development at similar endpoints expressed as the cumulative sum of degree-days. We conclude that computer-aided analysis of photographic documentation of leaf-miner larval growth followed by mathematical modelling offers a noninvasive, reliable, and inexpensive alternative for monitoring local leaf-miners populations.
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http://dx.doi.org/10.1007/s00484-021-02119-8 | DOI Listing |
Int J Biometeorol
June 2024
Faculty of Natural Sciences, Institute of Biology, Biotechnology and Environmental Protection, Animal Physiology and Ecotoxicology, Team, University of Silesia in Katowice, PL, Bankowa 9, Katowice, 40-007, Poland.
Int J Mol Sci
September 2023
Department of Analytical Chemistry, Medical University of Lublin, Chodźki 4a, 20-093 Lublin, Poland.
The herbivore (kingdom Animalia) and the pathogen (kingdom Fungi) are considered pests and biotic stressors of (chestnut trees). The impact of both pests on the accumulation of secondary metabolites in chestnut leaves was investigated. Specifically, the interactive effect of both pests on metabolite accumulation and their potential role in enhancing the resistance of chestnut trees to biological stress was the focus of this study.
View Article and Find Full Text PDFBiol Futur
June 2023
Institute of Agronomy, Hungarian University of Agriculture and Life Sciences, Kaposvár, S. Guba Str. 40, 7400, Gödöllő, Hungary.
Cameraria ohridella is one of the most invasive pests of horse chestnut. Cyantraniliprole is one of the most perspectively active insecticides, which can transport within the plant in several ways, and its efficacy against this pest has not yet been tested. All three modes of application were effective against the target pest, but there was a difference in the time of action between them.
View Article and Find Full Text PDFInt Microbiol
November 2023
Soil Science Faculty, Lomonosov Moscow State University, 119234, Moscow, Russia.
Mines on tree leaves and undamaged leaves were studied to investigate yeast complexes in urban areas (Aesculus hippocastanum, miner - Cameraria ohridella; Betula verrucosa, miner - Caloptilia betulicola; Populus nigra, miner - Lithocolletis populifoliella; Quercus robur, miner - Tischeria companella; Salix caprea, miner - Trachys minuta; Syringa vulgaris, miner - Caloptilia syringella; Tilia cordata, miner - Phyllonorycter issikii; Ulmus laevis, miner - Carpatolechia fugitivella). The abundance and taxonomic structure of yeasts were studied using a surface plating method on solid media (GPY agar). Identification of yeast species was based on the ITS rDNA nucleotide sequence.
View Article and Find Full Text PDFInsects
April 2023
Institute for Soil Sciences, Centre for Agricultural Research, ELKH, Herman Ottó út 15, H-1022 Budapest, Hungary.
Monitoring insect populations is essential to optimise pest control with the correct protection timing and the avoidance of unnecessary insecticide use. Modern real-time monitoring practices use automatic insect traps, which are expected to be able to estimate the population sizes of pest animals with high species specificity. There are many solutions to overcome this challenge; however, there are only a few data that consider their accuracy under field conditions.
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