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001-es BibID:BIBFORM084823
035-os BibID:(cikkazonosító)105400
Első szerző:Juhász Csaba (környezetgazdálkodási agrármérnök)
Cím:Seasonal predictability of weather and crop yield in regions of Central European continental climate / Juhász Csaba, Gálya Bernadett, Kovács Elza, Nagy Attila, Tamás János, Huzsvai László
Dátum:2020
ISSN:0168-1699
Megjegyzések:Currently, predictability of weather is uncertain, resulting from increasingly variable weather conditions. Thus, crop yield forecasting based on seasonal weather information remains a challenge for the agricultural sector. In this study, non-linear regression analysis was carried out to model long-term meteorological data. To assess the predictability of weather based on long-term meteorological data representing a continental climate with four seasons, principal component analysis was done. Predictability of crop yield based on previous long-term yield data was tested with the Wald-Wolfowitz Runs method. Finally, non-linear regression analysis was applied to investigate the predictability of maize yield based on winter wheat yield. The hypothesis that the weather of a season would be predictable based on long-term daily temperature and precipitation dataset was disproved, although results showed that for the investigated region, if winter is warm, spring can be expected to be warm, as well. It was also statistically disproved that crop yield would be predictable based on time series analysis of previous yield data. However, a cross effect between the yields of maize and wheat as model crops was proved; when the crop yield of winter wheat is low, that of maize is expected also to be low, while in case of high winter wheat yield, maize yield can be high in cases where there is no climate stress in the flowering and ripening periods. However, as an overall conclusion, even if relations are found between weather variabilities and responding crop yield variations, crop yield cannot be estimated, since weather represented by a chaotic model with scale-independent distribution cannot be predicted in advance.
Tárgyszavak:Agrártudományok Növénytermesztési és kertészeti tudományok idegen nyelvű folyóiratközlemény külföldi lapban
folyóiratcikk
Megjelenés:Computers And Electronics In Agriculture. - 173 (2020), p. 1-10. -
További szerzők:Gálya Bernadett (1987-) (környezetgazdálkodási agrármérnök) Kovács Elza (1976-) (okleveles vegyész, angol-magyar szakfordító, anyagmérnök MSc) Nagy Attila (1982-) (környezetgazdálkodási agrármérnök) Tamás János (1959-) (környezetgazdálkodási agrármérnök) Huzsvai László (1961-) (talajerőgazdálkodási szakmérnök, agrármérnök)
Pályázati támogatás:20428-3/2018/FEKUTSTRAT
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2.

001-es BibID:BIBFORM074006
Első szerző:Nagy Attila (környezetgazdálkodási agrármérnök)
Cím:Wheat and maize yield forecasting for the Tisza river catchment using MODIS NDVI time series and reported crop statistics / Nagy Attila, Fehér János, Tamás János
Dátum:2018
ISSN:0168-1699
Megjegyzések:Stakeholders, policy makers, government planners and agricultural market participants in Central Eastern Europe require accurate and timely information about wheat and maize yield and production. The study site, the lowlands (altitude below 200m) of the Tisza river catchment is by far the most important wheat and corn producing region in the Carpathian basin, and even in Central Eastern Europe. The conventional sampling of on-field data and data processing for crop forecasting requires significant amounts of time before official reports can be released. Several studies have shown that wheat and maize yield can be effectively forecast using satellite remote sensing. In this study, a freely available MODIS NDVI satellite data based wheat and maize yield forecasting methodology was developed and evaluated for estimating yield losses effected by drought. Wheat and maize yield was derived by regressing reported yield values against time series of 15 different peak-season MODIS-derived NDVI. The lowest RMSE values at the river basin level for both wheat and maize yield forecast versus reported yield were found when using at least six or more years of training data. Wheat forecast for the 2000 to 2015 growing seasons were within 0.819 % and 19.08% of final reported yield values. Maize forecast at county level for the 2000 to 2015 growing seasons were within 0.299 % and 17.14% of final reported yield values. The Nash?Sutcliffe efficiency index (E1) is positive with E1 = 0.322 in the case of wheat forecast, and with E1=0.401 in the case of maize forecast, which means the developed and evaluated forecasting method performs acceptable forecast efficiency. Nevertheless the occurrence of extreme drought or extreme precipitation can alter the forecasting efficiency resulting over or underestimation. Overall statement, which based on MODIS NDVI, possible yield losses can easily be forecasted 6-8 weeks before harvesting and applying simple threshold levels, yield losses can be mapped simply.
Tárgyszavak:Agrártudományok Növénytermesztési és kertészeti tudományok idegen nyelvű folyóiratközlemény külföldi lapban
Megjelenés:Computers And Electronics In Agriculture 151 (2018), p. 41-49. -
További szerzők:Fehér János (1952-) (hidrológus) Tamás János (1959-) (környezetgazdálkodási agrármérnök)
Pályázati támogatás:A tanulmány alapjául szolgáló kutatást az Emberei Erőforrások Minisztériuma által meghirdetett Felsőoktatási Intézményi Kiválósági Program támogatta, a Debreceni Egyetem 4.tématerületi programja keretében
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