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  • Environmental factors influence the growth, survival, dissemination and hence the incidence of Fusarium fungi and the disease severity. The objective of this study was to design a model for prediction of deoxynivalenol content in winter wheat grain based on weather conditions, preceding crop and soil cultivation. The grain samples from winter wheat field experiments conducted in 2002-2005 were analyzed for the DON content. Highest positive correlation coefficients were found for sum of precipitation in April, average temperature in April, and sum of precipitation 5 days prior to anthesis. Significant negative correlation was found for average temperature in May and average relative humidity 5 days prior to anthesis. The most appropriate neural network model was then coupled with AgriClim model to simulate spatial and temporal variation of DON content in wheat samples for south Moravia and north-east Austria area.
  • Environmental factors influence the growth, survival, dissemination and hence the incidence of Fusarium fungi and the disease severity. The objective of this study was to design a model for prediction of deoxynivalenol content in winter wheat grain based on weather conditions, preceding crop and soil cultivation. The grain samples from winter wheat field experiments conducted in 2002-2005 were analyzed for the DON content. Highest positive correlation coefficients were found for sum of precipitation in April, average temperature in April, and sum of precipitation 5 days prior to anthesis. Significant negative correlation was found for average temperature in May and average relative humidity 5 days prior to anthesis. The most appropriate neural network model was then coupled with AgriClim model to simulate spatial and temporal variation of DON content in wheat samples for south Moravia and north-east Austria area. (en)
Title
  • Prediction model for deoxynivalenol in wheat grain based on weather conditions
  • Prediction model for deoxynivalenol in wheat grain based on weather conditions (en)
skos:prefLabel
  • Prediction model for deoxynivalenol in wheat grain based on weather conditions
  • Prediction model for deoxynivalenol in wheat grain based on weather conditions (en)
skos:notation
  • RIV/25328859:_____/09:#0000439!RIV10-MZE-25328859
http://linked.open...avai/riv/aktivita
http://linked.open...avai/riv/aktivity
  • P(QF3121), P(QG50041)
http://linked.open...iv/cisloPeriodika
  • September
http://linked.open...vai/riv/dodaniDat
http://linked.open...aciTvurceVysledku
http://linked.open.../riv/druhVysledku
http://linked.open...iv/duvernostUdaju
http://linked.open...titaPredkladatele
http://linked.open...dnocenehoVysledku
  • 335436
http://linked.open...ai/riv/idVysledku
  • RIV/25328859:_____/09:#0000439
http://linked.open...riv/jazykVysledku
http://linked.open.../riv/klicovaSlova
  • prediction model; mycotoxin DON; winter wheat; weather conditions (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...odStatuVydavatele
  • CZ - Česká republika
http://linked.open...ontrolniKodProRIV
  • [6172486717BF]
http://linked.open...i/riv/nazevZdroje
  • Plant Protection Science
http://linked.open...in/vavai/riv/obor
http://linked.open...ichTvurcuVysledku
http://linked.open...cetTvurcuVysledku
http://linked.open...vavai/riv/projekt
http://linked.open...UplatneniVysledku
http://linked.open...v/svazekPeriodika
  • 45
http://linked.open...iv/tvurceVysledku
  • Trnka, Miroslav
  • Klem, Karel
  • Matušinsky, Pavel
  • Váňová, Marie
issn
  • 1212-2580
number of pages
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