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001-es BibID:BIBFORM084823
035-os BibID:(cikkazonosító)105400 (WoS)000531080400026 (Scopus)85083000007
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:BIBFORM114461
035-os BibID:(cikkazonosító)108159 (WoS)001069940200001 (Scopus)85172443211
Első szerző:Magyar Tamás (környezetgazdálkodás)
Cím:Modeling of soil moisture and water fluxes in a maize field for the optimization of irrigation / Tamás Magyar, Zsolt Fehér, Erika Buday-Bódi, János Tamás, Attila Nagy
Dátum:2023
ISSN:0168-1699
Megjegyzések:Precision irrigation is becoming more and more important in agricultural crop production due to the limited water resources resulting from the negative effects of climate change. Modeling of irrigation can support decision makers in the maintenance of the quantitative and qualitative parameters of the cultivated crops, while improving the efficiency of water consumption. In the present paper, a 3D hydrodynamic model was created in the HYDRUS environment to support the modeling of the temporal changes and spatial variations in the water balance (WB) of a maize cultivated Hungarian study site, thereby providing inputs for irrigation scheduling and variable rate irrigation for stakeholders. Beside soil physical parameters, crop evapotranspiration (ETc) values were also considered as model inputs for the phenological crop development stages of the maize from the sowing to the harvesting. This period was between the 3rd of May and the 10th of September in 2020 and the 20th of May and 14th of September for the year 2021. The performance of the model for soil moisture conditions were validated by on-field soil moisture measurements. The overall performance (full vegetation period) of the model was good (r2 = 0.88 for 2020 and r2 = 0.91 for 2021), but slightly varied among different phenological stages. Based on the model, the water balance of the investigated area was determined without any irrigation, alongside the cumulative water fluxes (CWF) through the boundaries including the root water uptake (RWU) of the maize as well. The results revealed that the incoming precipitation was not sufficient to supplement the water content in the soil to the optimal soil moisture range, except when the precipitation level is high enough to balance it. It was concluded that the water balance was negative for the investigated time periods without any irrigation. The specific water deficit (WD) values were calculated considering the area of the study site, which is 1439 m3/ha for 2020 and 2068 m3/ha for 2021. From the obtained results, optimal irrigation schedules were presented to keep the soil moisture content in the optimal range (20.92-14.41 V/V%) in the modeled area for two different vegetation periods. It was found that due to the irrigation the crop water productivity (CWP) increased by 6% and 4% in 2020 and 2021. Overall, the model is able to cope with changing circumstances that could help to mitigate the negative effects of climate change with the reasonable use of limited water resources in the future.
Tárgyszavak:Agrártudományok Növénytermesztési és kertészeti tudományok idegen nyelvű folyóiratközlemény külföldi lapban
folyóiratcikk
Modeling
Water balance
Maize Irrigation scheduling Root water uptake
Megjelenés:Computers And Electronics In Agriculture. - 213 (2023), p. 1-15. -
További szerzők:Fehér Zsolt Zoltán (1984-) (geoinformatika) Bódi Erika (1989-) (geológus, geográfus) Tamás János (1959-) (környezetgazdálkodási agrármérnök) Nagy Attila (1982-) (környezetgazdálkodási agrármérnök)
Pályázati támogatás:WATERAGRI 858375
Egyéb
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3.

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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