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Author Murat, M.; Malinowska, I.; Hoffmann, H.; Baranowski, P.
Title Statistical modelling of agrometeorological time series by exponential smoothing Type Journal Article
Year 2016 Publication International Agrophysics Abbreviated Journal International Agrophysics
Volume 30 Issue 1 Pages 57-65
Keywords exponential smoothing; meteorological time series; statistical forecasting; daily temperature records; weighted moving averages; climate-change; prediction; forecasts; state; weather
Abstract Meteorological time series are used in modelling agrophysical processes of the soil-plant-atmosphere system which determine plant growth and yield. Additionally, longterm meteorological series are used in climate change scenarios. Such studies often require forecasting or projection of meteorological variables, eg the projection of occurrence of the extreme events. The aim of the article was to determine the most suitable exponential smoothing models to generate forecast using data on air temperature, wind speed, and precipitation time series in Jokioinen (Finland), Dikopshof (Germany), Lleida (Spain), and Lublin (Poland). These series exhibit regular additive seasonality or non-seasonality without any trend, which is confirmed by their autocorrelation functions and partial autocorrelation functions. The most suitable models were indicated by the smallest mean absolute error and the smallest root mean squared error.
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Publisher Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0236-8722 ISBN Medium Article
Area Expedition Conference
Notes CropM, ft_macsur Approved no
Call Number MA @ admin @ Serial 4728
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Author van Bussel, L.G.J.; Stehfest, E.; Siebert, S.; Müller, C.; Ewert, F.
Title Simulation of the phenological development of wheat and maize at the global scale Type Journal Article
Year 2015 Publication Global Ecology and Biogeography Abbreviated Journal Glob. Ecol. Biogeogr.
Volume 24 Issue 9 Pages 1018-1029
Keywords Agricultural management; crop calendars; cultivar; variety characteristics; global crop modelling; global harvest dates; phenology; climate-change; winter-wheat; annual crops; photoperiod sensitivity; geographical variation; temperature; responses; adaptation; cultivars; model
Abstract AimTo derive location-specific parameters that reflect the geographic differences among cultivars in vernalization requirements, sensitivity to day length (photoperiod) and temperature, which can be used to simulate the phenological development of wheat and maize at the global scale. LocationGlobal. Methods Based on crop calendar observations and literature describing the large-scale patterns of phenological characteristics of cultivars, we developed algorithms to compute location-specific parameters to represent this large-scale pattern. Vernalization requirements were related to the duration and coldness of winter, sensitivity to day length was assumed to be represented by the minimum and maximum day lengths occurring at a location, and sensitivity to temperature was related to temperature conditions during the vegetative development phase of the crop. Results Application of the derived location-specific parameters resulted in high agreement between simulated and observed lengths of the cropping period. Agreement was especially high for wheat, with mean absolute errors of less than 3 weeks. In the main maize cropping regions, cropping periods were over- and underestimated by 0.5-1.5 months. We also found that interannual variability in simulated wheat harvest dates was more realistic when accounting for photoperiod effects. Main conclusions The methodology presented here provides a good basis for modelling the phenological characteristics of cultivars at the global scale. We show that current global patterns of growing season length as described in cropping calendars can be largely reproduced by phenology models if location-specific parameters are derived from temperature and day length indicators. Growing seasons can be modelled more accurately for wheat than for maize, especially in warm regions. Our method for computing parameters for phenology models from temperature and day length offers opportunities to improve the simulation of crop productivity by crop simulation models developed for large spatial areas and for long-term climate impact projections that account for adaptation in the selection of varieties
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Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 1466-822x ISBN Medium Article
Area Expedition Conference
Notes CropM, ft_macsur Approved no
Call Number MA @ admin @ Serial 4729
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Author Stefańczyk, E.; Sobkowiak, S.; Brylińska, M.; Śliwka, J.
Title Diversity of Fusarium spp. associated with dry rot of potato tubers in Poland Type Journal Article
Year 2016 Publication European Journal of Plant Pathology Abbreviated Journal Eur. J. Plant Pathol.
Volume Issue Pages
Keywords ITS; mycotoxin; pathogenicity; Solanum tuberosum; tef-1α; β-tubulin; sequence data; Trichothecenes; identification; fungus; pathogenicity; temperature; sensitivity; zearalenone; strains; disease
Abstract Fusarium spp. belong to the division Ascomycota and cause important plant diseases; these fungi may contaminate food products with mycotoxins, endangering human and animal health. Several Fusarium spp. have been associated with potato dry rot. The most frequent and devastating of these species are F. sambucinum, F. solani and F. oxysporum, depending on the geographic location and the season. Samples of potato tubers with dry rot symptoms were collected, and their putative fungal isolates were identified as Fusarium species using partial nucleotide sequences of the internal transcribed spacer, translation elongation factor 1-α and β-tubulin genes. Among 149 isolates, 12 species were identified. F. oxysporum was the most frequent (45 % of the isolates), followed by F. avenaceum (12.1 %), F. solani (10.7 %) and F. sambucinum (7.4 %). Phylogenetic analyses confirmed the species identifications and revealed a high diversity of F. solani and a low diversity of F. oxysporum. Potential producers of zearalenone and trichothecenes were identified within the obtained isolates using PCR markers. Isolates that were pathogenic to potatoes in laboratory tests were found in four species: F. sambucinum, F. avenaceum, F. culmorum, and F. graminearum. The effects of increased temperature and mixed inoculum on the pathogenicities of chosen species were evaluated. This study adds 434 potato-derived Fusarium sequences to the NCBI GenBank database and demonstrates that the list of Fusarium species and mycotoxins present in potato tubers may be richer than previously believed, regardless of whether these species cause dry rot or live as saprophytes.
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Language English Summary Language Original Title
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Series Volume Series Issue Edition
ISSN 0929-1873 1573-8469 ISBN Medium Article
Area Expedition Conference
Notes CropM, ft_macsur Approved no
Call Number MA @ admin @ Serial 4721
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Author Conradt, T.; Gornott, C.; Wechsung, F.
Title Extending and improving regionalized winter wheat and silage maize yield regression models for Germany: Enhancing the predictive skill by panel definition through cluster analysis Type Journal Article
Year 2016 Publication Agricultural and Forest Meteorology Abbreviated Journal Agricultural and Forest Meteorology
Volume 216 Issue Pages 68-81
Keywords cluster analysis; crop yield estimation; germany; multivariate regression; silage maize; winter wheat; climate-change; canadian prairies; crop yield; temperature; responses; environments; variability; cultivar; china
Abstract Regional agricultural yield assessments allowing for weather effect quantifications are a valuable basis for deriving scenarios of climate change effects and developing adaptation strategies. Assessing weather effects by statistical methods is a classical approach, but for obtaining robust results many details deserve attention and require individual decisions as is demonstrated in this paper. We evaluated regression models for annual yield changes of winter wheat and silage maize in more than 300 German counties and revised them to increase their predictive power. A major effort of this study was, however, aggregating separately estimated time series models (STSM) into panel data models (PDM) based on cluster analyses. The cluster analyses were based on the per-county estimates of STSM parameters. The original STSM formulations (adopted from a parallel study) contained also the non-meteorological input variables acreage and fertilizer price. The models were revised to use only weather variables as estimation basis. These consisted of time aggregates of radiation, precipitation, temperature, and potential evapotranspiration. Altering the input variables generally increased the predictive power of the models as did their clustering into PDM. For each crop, five alternative clusterings were produced by three different methods, and similarities between their spatial structures seem to confirm the existence of objective clusters about common model parameters. Observed smooth transitions of STSM parameter values in space suggest, however, spatial autocorrelation effects that could also be modeled explicitly. Both clustering and autocorrelation approaches can effectively reduce the noise in parameter estimation through targeted aggregation of input data. (C) 2015 Elsevier B.V. All rights reserved.
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Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0168-1923 ISBN Medium Article
Area Expedition Conference
Notes CropM, ft_macsur Approved no
Call Number MA @ admin @ Serial 4709
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Author Refsgaard, J.C.; Madsen, H.; Andréassian, V.; Arnbjerg-Nielsen, K.; Davidson, T.A.; Drews, M.; Hamilton, D.P.; Jeppesen, E.; Kjellström, E.; Olesen, J.E.; Sonnenborg, T.O.; Trolle, D.; Willems, P.; Christensen, J.H.
Title A framework for testing the ability of models to project climate change and its impacts Type Journal Article
Year 2014 Publication Climatic Change Abbreviated Journal Clim. Change
Volume 122 Issue 1-2 Pages 271-282
Keywords simulation-models; shallow lakes; predictions; calibration; ensembles; terminology; uncertainty; temperature; adaptation; validation
Abstract Models used for climate change impact projections are typically not tested for simulation beyond current climate conditions. Since we have no data truly reflecting future conditions, a key challenge in this respect is to rigorously test models using proxies of future conditions. This paper presents a validation framework and guiding principles applicable across earth science disciplines for testing the capability of models to project future climate change and its impacts. Model test schemes comprising split-sample tests, differential split-sample tests and proxy site tests are discussed in relation to their application for projections by use of single models, ensemble modelling and space-time-substitution and in relation to use of different data from historical time series, paleo data and controlled experiments. We recommend that differential-split sample tests should be performed with best available proxy data in order to build further confidence in model projections.
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Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0165-0009 1573-1480 ISBN Medium Article
Area Expedition Conference
Notes CropM Approved no
Call Number MA @ admin @ Serial 4688
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