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Author Smoroń, S.; Kowalczyk, A.
Title Nitrogen and Phosphorus dynamics in the surface flowing waters of the loessial areas in Northern Malopolska Type Journal Article
Year 2012 Publication Polish Journal of Environmental Studies Abbreviated Journal (down) Pol. J. Environ. Stud.
Volume 21 Issue 15a Pages 392-395
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Notes CropM Approved no
Call Number MA @ admin @ Serial 4594
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Author Kopacz, M.; Twardy, S.
Title A spatial analysis of biogenic load differentiation of an agricultural origin in the Carpathian basin Type Journal Article
Year 2012 Publication Polish Journal of Environmental Studies Abbreviated Journal (down) Pol. J. Environ. Stud.
Volume 21 Issue 5a Pages 196-200
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Notes CropM, LiveM Approved no
Call Number MA @ admin @ Serial 4587
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Author Kowalczyk, A.; Kuźniar, A.
Title The threats of water erosion in the Grajcarek river basin Type Journal Article
Year 2012 Publication Polish Journal of Environmental Studies Abbreviated Journal (down) Pol. J. Environ. Stud.
Volume 21 Issue 5a Pages 217-221
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Notes CropM Approved no
Call Number MA @ admin @ Serial 4588
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Author Hoffmann, H.; Zhao, G.; Asseng, S.; Bindi, M.; Biernath, C.; Constantin, J.; Coucheney, E.; Dechow, R.; Doro, L.; Eckersten, H.; Gaiser, T.; Grosz, B.; Heinlein, F.; Kassie, B.T.; Kersebaum, K.-C.; Klein, C.; Kuhnert, M.; Lewan, E.; Moriondo, M.; Nendel, C.; Priesack, E.; Raynal, H.; Roggero, P.P.; Rötter, R.P.; Siebert, S.; Specka, X.; Tao, F.; Teixeira, E.; Trombi, G.; Wallach, D.; Weihermüller, L.; Yeluripati, J.; Ewert, F.
Title Impact of spatial soil and climate input data aggregation on regional yield simulations Type Journal Article
Year 2016 Publication PLoS One Abbreviated Journal (down) PLoS One
Volume 11 Issue 4 Pages e0151782
Keywords systems simulation; nitrogen dynamics; winter-wheat; crop models; data resolution; scale; water; variability; calibration; weather
Abstract We show the error in water-limited yields simulated by crop models which is associated with spatially aggregated soil and climate input data. Crop simulations at large scales (regional, national, continental) frequently use input data of low resolution. Therefore, climate and soil data are often generated via averaging and sampling by area majority. This may bias simulated yields at large scales, varying largely across models. Thus, we evaluated the error associated with spatially aggregated soil and climate data for 14 crop models. Yields of winter wheat and silage maize were simulated under water-limited production conditions. We calculated this error from crop yields simulated at spatial resolutions from 1 to 100 km for the state of North Rhine-Westphalia, Germany. Most models showed yields biased by <15% when aggregating only soil data. The relative mean absolute error (rMAE) of most models using aggregated soil data was in the range or larger than the inter-annual or inter-model variability in yields. This error increased further when both climate and soil data were aggregated. Distinct error patterns indicate that the rMAE may be estimated from few soil variables. Illustrating the range of these aggregation effects across models, this study is a first step towards an ex-ante assessment of aggregation errors in large-scale simulations.
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ISSN 1932-6203 ISBN Medium Article
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Notes CropM, ft_macsur Approved no
Call Number MA @ admin @ Serial 4725
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Author Baranowski, P.; Jedryczka, M.; Mazurek, W.; Babula-Skowronska, D.; Siedliska, A.; Kaczmarek, J.
Title Hyperspectral and thermal imaging of oilseed rape (Brassica napus) response to fungal species of the genus Alternaria Type Journal Article
Year 2015 Publication PLoS One Abbreviated Journal (down) PLoS One
Volume 10 Issue 3 Pages e0122913
Keywords Algorithms; Alternaria/*pathogenicity; Brassica napus/microbiology/*physiology
Abstract In this paper, thermal (8-13 µm) and hyperspectral imaging in visible and near infrared (VNIR) and short wavelength infrared (SWIR) ranges were used to elaborate a method of early detection of biotic stresses caused by fungal species belonging to the genus Alternaria that were host (Alternaria alternata, Alternaria brassicae, and Alternaria brassicicola) and non-host (Alternaria dauci) pathogens to oilseed rape (Brassica napus L.). The measurements of disease severity for chosen dates after inoculation were compared to temperature distributions on infected leaves and to averaged reflectance characteristics. Statistical analysis revealed that leaf temperature distributions on particular days after inoculation and respective spectral characteristics, especially in the SWIR range (1000-2500 nm), significantly differed for the leaves inoculated with A. dauci from the other species of Alternaria as well as from leaves of non-treated plants. The significant differences in leaf temperature of the studied Alternaria species were observed in various stages of infection development. The classification experiments were performed on the hyperspectral data of the leaf surfaces to distinguish days after inoculation and Alternaria species. The second-derivative transformation of the spectral data together with back-propagation neural networks (BNNs) appeared to be the best combination for classification of days after inoculation (prediction accuracy 90.5%) and Alternaria species (prediction accuracy 80.5%).
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ISSN 1932-6203 ISBN Medium Article
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Notes CropM, ft_macsur Approved no
Call Number MA @ admin @ Serial 4549
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