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Selected insect groups of shrubbery complexes of "Biedrusko" Protected Lanscape. Part I: Aphids (Hemiptera: Aphidoidea)
In the research carried out at „Biedrusko” Protected Landscape Area in the years 2003-2005 in shrubberies of Rhamno-Prunetea class 15 species of aphids were found in the shaking method on the bushes, while the richest finds were collected with the method of Moericke’s traps: 118 different aphid species. Expand
Artificial neural networks for modeling ammonia emissions released from sewage sludge composting
Abstract The project was designed to develop, test and validate an original Neural Model describing ammonia emissions generated in composting sewage sludge. The composting mix was to include theExpand
Neural identification of selected apple pests
The results support the hypothesis that artificial neural networks are an effective tool that supports the process of identification of pests in apple orchards, and indicate that multi-layered perceptron (MLP) neural network topology achieve the best classification ability. Expand
The use of neural modelling to estimate the methane production from slurry fermentation processes
Slurry constitutes an important substrate, increasingly often forming part of biogas production in biogas plants due to the significant content of methane in biogas produced from slurry. SlurryExpand
A STUDY OF BIONOMY OF THE PRIVET SAWFLY (Macrophya punctumalbum (L.)) (Hymenoptera, Tenthredinidae) - A PEST OF PARK PLANTS
It was found that the larvae of sawfly went through 5 instar stages and the longevity and fecundity of imagines, larvae development of the species and the level of parasitizing the eggs of the privet sawfly by parasitoids of the Chalcidoidea superfamily. Expand
Detection of the granary weevil based on X-ray images of damaged wheat kernels
Abstract Grain in storage is exposed to a number of adverse factors, including extensive damage to grain kernels caused by infestations of the granary weevil Sitophilus granarius. This pest causes aExpand
The application of the Kohonen neural network in the nonparametric-quality-based classification of tomatoes
By using the classification properties of Kohonen-type networks, a neural model was built for the qualitybased identification of tomatoes and drew up a topological SOFM which features cluster centers of "comparable" cases. Expand
Identification of selected apple pests based on selected graphical parameters
A neural classification model is presented in this paper, optimized using learning sets acquired on the basis of information contained in digital photographs of pests, addressing the problem of identifying 6 selected apple pests. Expand
Neural classifier in the estimation process of maturity of selected varieties of apples
Methods of neural image analysis aimed at estimating the maturity state of selected varieties of apples which are popular in Poland, supported by the use of image analysis methods and classification techniques represented by artificial neural networks are presented. Expand