Prediction model for deoxynivalenol in wheat grain based on weather conditions

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F25328859%3A_____%2F09%3A%230000439" target="_blank" >RIV/25328859:_____/09:#0000439 - isvavai.cz</a>

Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Prediction model for deoxynivalenol in wheat grain based on weather conditions

Popis výsledku v původním jazyce

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 basedon 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 inApril, 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 networkmodel 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.

Název v anglickém jazyce

Prediction model for deoxynivalenol in wheat grain based on weather conditions

Popis výsledku anglicky

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 basedon 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 inApril, 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 networkmodel 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.

Druh

J_x - Nezařazeno - Článek v odborném periodiku (Jimp, Jsc a Jost)

CEP obor

GF - Choroby, škůdci, plevely a ochrana rostlin

OECD FORD obor

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Projekt

Výsledek vznikl pri realizaci vícero projektů. Více informací v záložce Projekty.

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2009

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Plant Protection Science

ISSN

1212-2580

e-ISSN

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Svazek periodika

45

Číslo periodika v rámci svazku

September

Stát vydavatele periodika

CZ - Česká republika

Počet stran výsledku

5

Strana od-do

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Kód UT WoS článku

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EID výsledku v databázi Scopus

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