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Nándor Fodor
Centre for Agricultural Research, Agricultural Institute, Martonvásár, Hungary

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Journal article
Published: 27 July 2021 in Atmosphere
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Accurate estimation of the timing of intensive spring leaf growth initiation at mid and high latitudes is crucial for improving the predictive capacity of biogeochemical and Earth system models. In this study, we focus on the modeling of climatological onset of spring leaf growth in Central Europe and use three spring phenology models driven by three meteorological datasets. The MODIS-adjusted NDVI3g dataset was used as a reference for the period between 1982 and 2010, enabling us to study the long-term mean leaf onset timing and its interannual variability (IAV). The performance of all phenology model–meteorology database combinations was evaluated with one another, and against the reference dataset. We found that none of the constructed model–database combinations could reproduce the observed start of season (SOS) climatology within the study region. The models typically overestimated IAV of the leaf onset, where spatial median SOS dates were best simulated by the models based on heat accumulation. When aggregated for the whole study area, the complex, bioclimatic index-based model driven by the CarpatClim database could capture the observed overall SOS trend. Our results indicate that the simulated timing of leaf onset primarily depends on the choice of model structure, with a secondary contribution from the choice of the driving meteorological dataset.

ACS Style

Réka Dávid; Zoltán Barcza; Anikó Kern; Erzsébet Kristóf; Roland Hollós; Anna Kis; Martin Lukac; Nándor Fodor. Sensitivity of Spring Phenology Simulations to the Selection of Model Structure and Driving Meteorological Data. Atmosphere 2021, 12, 963 .

AMA Style

Réka Dávid, Zoltán Barcza, Anikó Kern, Erzsébet Kristóf, Roland Hollós, Anna Kis, Martin Lukac, Nándor Fodor. Sensitivity of Spring Phenology Simulations to the Selection of Model Structure and Driving Meteorological Data. Atmosphere. 2021; 12 (8):963.

Chicago/Turabian Style

Réka Dávid; Zoltán Barcza; Anikó Kern; Erzsébet Kristóf; Roland Hollós; Anna Kis; Martin Lukac; Nándor Fodor. 2021. "Sensitivity of Spring Phenology Simulations to the Selection of Model Structure and Driving Meteorological Data." Atmosphere 12, no. 8: 963.

Journal article
Published: 22 July 2021 in International Journal of Digital Earth
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Gridded model assessments require at least one climatic and one soil database for carrying out the simulations. There are several parallel soil and climate database development projects that provide sufficient, albeit considerably different, observation based input data for crop model based impact studies. The input database related uncertainty of the Biome-BGCMuSo agro-environmental model outputs was investigated using three and four different gridded climatic and soil databases, respectively covering an area of nearly 100.000 km2 with 1104 grid cells. Spatial, temporal, climate and soil database selection related variances were calculated and compared for four model outputs obtained from 30-year-long simulations. The choice of the input database introduced model output variability that was comparable to the variability the year-to-year change of the weather or the spatial heterogeneity of the soil causes. Input database selection could be a decisive factor in carbon sequestration related studies as the soil carbon stock change estimates may either suggest that the simulated ecosystem is a carbon sink or to the contrary a carbon source on the long run. Careful evaluation of the input database quality seems to be an inevitable and highly relevant step towards more realistic plant production and carbon balance simulations.

ACS Style

Nándor Fodor; László Pásztor; Brigitta Szabó; Annamária Laborczi; Klára Pokovai; Dóra Hidy; Roland Hollós; Erzsébet Kristóf; Anna Kis; Laura Dobor; Anikó Kern; Thomas Grünwald; Zoltán Barcza. Input database related uncertainty of Biome-BGCMuSo agro-environmental model outputs. International Journal of Digital Earth 2021, 1 -20.

AMA Style

Nándor Fodor, László Pásztor, Brigitta Szabó, Annamária Laborczi, Klára Pokovai, Dóra Hidy, Roland Hollós, Erzsébet Kristóf, Anna Kis, Laura Dobor, Anikó Kern, Thomas Grünwald, Zoltán Barcza. Input database related uncertainty of Biome-BGCMuSo agro-environmental model outputs. International Journal of Digital Earth. 2021; ():1-20.

Chicago/Turabian Style

Nándor Fodor; László Pásztor; Brigitta Szabó; Annamária Laborczi; Klára Pokovai; Dóra Hidy; Roland Hollós; Erzsébet Kristóf; Anna Kis; Laura Dobor; Anikó Kern; Thomas Grünwald; Zoltán Barcza. 2021. "Input database related uncertainty of Biome-BGCMuSo agro-environmental model outputs." International Journal of Digital Earth , no. : 1-20.

Journal article
Published: 05 January 2021 in Sustainability
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The Nitrates Directive aims (a) to protect water quality across Europe from nitrates originating from agricultural sources that pollute ground and surface water, and (b) to promote good farming practices. One of the most controversial measures of the directive is the winter prohibition period of fertilization, which has been extended by a month in two steps in recent years. According to the regulation, it is forbidden to apply nitrogen fertilization in Hungary between 31st October and 15th February, even though the winter climate is gradually becoming milder. Using the fertilization data of nearly half a million parcels of land in the Hungarian Nitrate Database, a crop model-based spatial analysis was carried out. Our aim was to test if a shift in the prohibition period starting date from 31st October to 30th November caused any differences in the nitrate amount leached at a 90 cm depth. Detailed nitrate inputs and soil and weather databases were coupled with the 4M crop model. The yield, plant nitrogen uptake, and nitrate leaching under five major crops were simulated, covering a considerable portion of arable land. Shifting the prohibition period starting date did not result in significant changes in the nitrate leaching. Further runs of the 4M model with different weather scenarios are needed to decide whether the modification of the prohibition period significantly affects the amount of nitrate leached.

ACS Style

Sándor Koós; Béla Pirkó; Gábor Szatmári; Péter Csathó; Marianna Magyar; József Szabó; Nándor Fodor; László Pásztor; Annamária Laborczi; Klára Pokovai; Anita Szabó. Influence of the Shortening of the Winter Fertilization Prohibition Period in Hungary Assessed by Spatial Crop Simulation Analysis. Sustainability 2021, 13, 417 .

AMA Style

Sándor Koós, Béla Pirkó, Gábor Szatmári, Péter Csathó, Marianna Magyar, József Szabó, Nándor Fodor, László Pásztor, Annamária Laborczi, Klára Pokovai, Anita Szabó. Influence of the Shortening of the Winter Fertilization Prohibition Period in Hungary Assessed by Spatial Crop Simulation Analysis. Sustainability. 2021; 13 (1):417.

Chicago/Turabian Style

Sándor Koós; Béla Pirkó; Gábor Szatmári; Péter Csathó; Marianna Magyar; József Szabó; Nándor Fodor; László Pásztor; Annamária Laborczi; Klára Pokovai; Anita Szabó. 2021. "Influence of the Shortening of the Winter Fertilization Prohibition Period in Hungary Assessed by Spatial Crop Simulation Analysis." Sustainability 13, no. 1: 417.

Journal article
Published: 01 November 2020 in Geoderma
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Numerous soil water repellency (SWR) studies have investigated the possible causes of this temporal phenomenon, yet there remains a lack of knowledge on the order of importance of the main driving forces of SWR in the context of changing environmental conditions under grassland ecosystems. To study the separate and combined effects of soil texture, climate, and grassland cover type on inducing or altering SWR, four sites from different climatic and soil regions were selected: Ciavolo (CI, IT), Csólyospálos (CSP, HU), Pwllpeiran (PW, UK), Sekule (SE, SK). The investigated parameters were the extent (determined by repellency indices RI, RIc and RIm) and persistence (determined by water drop penetration time (WDPT) and water repellency cessation time, WRCT) of SWR, as well as field water (Sw) and ethanol (Se) sorptivity, water sorptivity of hydrophobic soil state (Swh) water sorptivity of nearly wettable soil state (Sww) and field hydraulic conductivity (K). Our findings showed an area of land has a greater likelihood of being water repellent if it has a sandy soil texture and/or a high frequency of prolonged drought events. Water infiltration was positively correlated with all the sorptivities (r = 0.32–0.88), but was mostly negatively correlated with RI (r = – 0.54 at CI), WDPT (r = – 0.47 at CI) and WRCT (r = – 0.58 at CI). The importance of natural and synanthropized vegetation covers with regards to SWR was not coherent; moving to regions having coarser texture or moving to drier climatic zones led to higher risk of SWR conditions. Climate change has been predicted to lead to more frequent extreme weather events and prolonged dry periods across Europe, which will most likely increase the extent of SWR-affected areas and increase the role of SWR in water management of grassland ecosystems. Therefore, there is a need to determine SWR risk zones to prevent decreases in soil moisture content, soil fertility, carbon and nitrogen sink potentials, as well as biomass production of the related agro-ecosystems.

ACS Style

Renáta Sándor; Massimo Iovino; Lubomir Lichner; Vincenzo Alagna; Daniel Forster; Mariecia Fraser; Jozef Kollár; Peter Šurda; Viliam Nagy; Anita Szabó; Nándor Fodor. Impact of climate, soil properties and grassland cover on soil water repellency. Geoderma 2020, 383, 114780 .

AMA Style

Renáta Sándor, Massimo Iovino, Lubomir Lichner, Vincenzo Alagna, Daniel Forster, Mariecia Fraser, Jozef Kollár, Peter Šurda, Viliam Nagy, Anita Szabó, Nándor Fodor. Impact of climate, soil properties and grassland cover on soil water repellency. Geoderma. 2020; 383 ():114780.

Chicago/Turabian Style

Renáta Sándor; Massimo Iovino; Lubomir Lichner; Vincenzo Alagna; Daniel Forster; Mariecia Fraser; Jozef Kollár; Peter Šurda; Viliam Nagy; Anita Szabó; Nándor Fodor. 2020. "Impact of climate, soil properties and grassland cover on soil water repellency." Geoderma 383, no. : 114780.

Journal article
Published: 21 August 2020 in Sustainability
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We aim to predict Hungarian corn yields for the period of 2020–2100. The purpose of the study was to mutually consider the environmental impact of climate change and the potential human impact indicators towards sustaining corn yield development in the future. Panel data regression methods were elaborated on historic observations (1970–2018) to impose statistical inferences with simulated weather events (2020–2100) and to consider developing human impact for sustainable intensification. The within-between random effect model was performed with three generic specifications to address time constant indicators as well. Our analysis on a gridded Hungarian database confirms that rising temperature and decreasing precipitation will negatively affect corn yields unless human impact dissolves the climate-induced challenges. We addressed the effect of elevated carbon dioxide (CO2) as an important factor of diverse human impact. By superposing the human impact on the projected future yields, we confirm that the negative prospects of climate change can be defeated.

ACS Style

Tibor Marton; Anna Kis; Anna Zubor-Nemes; Anikó Kern; Nándor Fodor. Human Impact Promotes Sustainable Corn Production in Hungary. Sustainability 2020, 12, 6784 .

AMA Style

Tibor Marton, Anna Kis, Anna Zubor-Nemes, Anikó Kern, Nándor Fodor. Human Impact Promotes Sustainable Corn Production in Hungary. Sustainability. 2020; 12 (17):6784.

Chicago/Turabian Style

Tibor Marton; Anna Kis; Anna Zubor-Nemes; Anikó Kern; Nándor Fodor. 2020. "Human Impact Promotes Sustainable Corn Production in Hungary." Sustainability 12, no. 17: 6784.

Preprint content
Published: 23 March 2020
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During the past 15 years, our research group was developing the Biome-BGCMAg (formerly known as Biome-BGCMuSo) biogeochemical model to improve its ability to simulate carbon and water cycle in different ecosystems, with options for managed croplands, grasslands, and forests. We made various model improvements based on the results of model validation and benchmarking. Our goal is to have a model that is suitable for estimating and predicting greenhouse gas fluxes of different ecosystems at various scales under changing management and climate conditions.

The current, most recent model is called Biome-BGCMAg which is a process-based, biogeochemical model that simulates the storage and flux of water, carbon, and nitrogen in the soil-plant-atmosphere system. Biome-BGCMAg was derived from the widely known Biome-BGC v4.1.1 model developed by the Numerical Terradynamic Simulation Group (NTSG), University of Montana, USA. One of the most important model developments is the implementation of a multilayer soil module with water, carbon, nitrogen, and soil organic matter profiles. We implemented drought and anoxic soil state-related plant mortality. Alternative calculation methods for various processes were implemented to support possible algorithm ensemble modelling approach. Optional dynamic allocation algorithm was introduced using predefined phenophases based on growing degree day method. We implemented optional temperature dependence of allocation and possible assimilation downregulation as a function of temperature. Nitrogen budget simulation was improved. Furthermore, human intervention modules were developed to simulate cropland management (e.g. planting, harvest, ploughing, and application of fertilizers) and forest thinning. Dynamic whole plant mortality was implemented in the model to enable more realistic simulation of forest stand development. Last (but not least) conditional management (irrigation and mowing) was introduced to analyze the effect of different management strategies in the future. We started to build a sophisticated R based software to increase the visibility of the model and enable its use by the wider scientific community.

In our first attempt to simulate national scale greenhouse gas budget with Biome-BGCMAg 2.0, we executed the model at 10 x 10 km spatial resolution for Hungary, using eco-physiological parameterization and prescribed management for maize, winter wheat, forests and grassland. The first results revealed that the spatial pattern of net primary production and crop yield is not represented well by the model. Based on the first experiences we introduced new features within Biome-BGCMAg 2.1 that address soil water deficit related photosynthesis down-regulation. Missing stomatal conductance effect on C4 photosynthesis was also addressed by the new developments. 

ACS Style

Dóra Hidy; Nándor Fodor; Roland Hollós; Zoltán Barcza. Building a modelling framework to simulate ecosystem processes under changing climate: the long road from Biome-BGC to Biome-BGCMAg. 2020, 1 .

AMA Style

Dóra Hidy, Nándor Fodor, Roland Hollós, Zoltán Barcza. Building a modelling framework to simulate ecosystem processes under changing climate: the long road from Biome-BGC to Biome-BGCMAg. . 2020; ():1.

Chicago/Turabian Style

Dóra Hidy; Nándor Fodor; Roland Hollós; Zoltán Barcza. 2020. "Building a modelling framework to simulate ecosystem processes under changing climate: the long road from Biome-BGC to Biome-BGCMAg." , no. : 1.

Journal article
Published: 10 December 2019 in Agronomy
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Leaf Area Index (LAI) is an important plant parameter for both farmers and plant scientists to monitor and/or model the growth and the well-being of plants. Since direct LAI measurement techniques are relatively laborious and time-consuming, various indirect methods have been developed and widely used since the early 1990s. The LP-80 ceptometer uses a linear array of PAR (photosynthetically active radiation) sensors for non-destructive LAI measurements that is backed by 15 years of research. Despite this, considerable discrepancy can be found between the expert opinions regarding the optimal illumination conditions recommended for the measurement. The sensitivity of ceptometer-based LAI values to PAR was investigated, and a simple method was devised to correct raw ceptometer data collected under non-ideal light conditions. Inadequate light conditions (PAR < 1700 µmol m−2 s−1) could cause an underestimation of LAI. Using the corrected LAI values, the ceptometer data showed a significantly better fit (higher R2, smaller mean average error and closer to zero mean signed error values) to the destructive LAI data for both wheat and maize. With the help of the correction equations, the use of the LP-80 ceptometer could be extended to days when light conditions are not ideal.

ACS Style

Klára Pokovai; Nándor Fodor. Adjusting Ceptometer Data to Improve Leaf Area Index Measurements. Agronomy 2019, 9, 866 .

AMA Style

Klára Pokovai, Nándor Fodor. Adjusting Ceptometer Data to Improve Leaf Area Index Measurements. Agronomy. 2019; 9 (12):866.

Chicago/Turabian Style

Klára Pokovai; Nándor Fodor. 2019. "Adjusting Ceptometer Data to Improve Leaf Area Index Measurements." Agronomy 9, no. 12: 866.

Journal article
Published: 27 November 2019 in Sustainability
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Sustainable agriculture strives for maintaining or even increasing productivity, quality and economic viability while leaving a minimal foot print on the environment. To promote sustainability and biodiversity conservation, there is a growing interest in some old wheat species that can achieve better grain yields than the new varieties in marginal soil and/or management conditions. Generally, common wheat is intensively studied but there is still a lack of knowledge of the competitiveness of alternative species such as spelt wheat. The aim is to provide detailed analysis of vegetative, generative and spectral properties of spelt and common wheat grown under different nitrogen fertiliser levels. Our results complement the previous findings and highlight the fact that despite the lodging risk increasing together with the N fertiliser level, spelt wheat is a real alternative to common wheat for low N input production both for low quality and fertile soils. Vitality indices such as flag leaf chlorophyll content and normalized difference vegetation index were found to be good precursors of the final yield and the proposed estimation equations may improve the yield forecasting applications. The reliability of the predictions can be enhanced by including crop-specific parameters which are already available around flowering, beside soil and/or weather parameters.

ACS Style

Eszter Sugár; Nándor Fodor; Renáta Sándor; Péter Bónis; Gyula Vida; Tamás Árendás. Spelt Wheat: An Alternative for Sustainable Plant Production at Low N-Levels. Sustainability 2019, 11, 6726 .

AMA Style

Eszter Sugár, Nándor Fodor, Renáta Sándor, Péter Bónis, Gyula Vida, Tamás Árendás. Spelt Wheat: An Alternative for Sustainable Plant Production at Low N-Levels. Sustainability. 2019; 11 (23):6726.

Chicago/Turabian Style

Eszter Sugár; Nándor Fodor; Renáta Sándor; Péter Bónis; Gyula Vida; Tamás Árendás. 2019. "Spelt Wheat: An Alternative for Sustainable Plant Production at Low N-Levels." Sustainability 11, no. 23: 6726.

Special issue
Published: 17 October 2018 in Plant, Cell & Environment
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The superior agronomic and human nutritional properties of grain legumes (pulses) make them an ideal foundation for future sustainable agriculture. Legume‐based farming is particularly important in Africa, where small‐scale agricultural systems dominate the food production landscape. Legumes provide an inexpensive source of protein and nutrients to African households as well as natural fertilization for the soil. While the consumption of traditionally grown legumes has started to decline, the production of soybeans (Glycine max Merr.) is spreading fast, especially across southern Africa. Predictions of future land‐use allocation and production show that the soybean is poised to dominate future production across Africa. Land use models project an expansion of harvest area, while crop models project possible yield increases. Moreover, a seed change in farming strategy is underway. This is being driven largely by the combined cash‐crop value of products such as oils and the high nutritional benefits of soybean as an animal feed. Intensification of soybean production has the potential to reduce the dependence of Africa on soybean imports. However, a successful ‘soybean bonanza’ across Africa necessitates an intensive research, development, extension and policy agenda to ensure that soybean genetic improvements and production technology meet future demands for sustainable production.

ACS Style

Christine H. Foyer; Kadambot Siddique; Amos P.K. Tai; Sven Anders; Nandor Fodor; Fuk-Ling Wong; Ndiko Ludidi; Mark A. Chapman; Brett J. Ferguson; Michael J. Considine; Florian Zabel; P.V. Vara Prasad; Rajeev K. Varshney; Henry T. Nguyen; Hon-Ming Lam. Modelling predicts that soybean is poised to dominate crop production across Africa. Plant, Cell & Environment 2018, 42, 373 -385.

AMA Style

Christine H. Foyer, Kadambot Siddique, Amos P.K. Tai, Sven Anders, Nandor Fodor, Fuk-Ling Wong, Ndiko Ludidi, Mark A. Chapman, Brett J. Ferguson, Michael J. Considine, Florian Zabel, P.V. Vara Prasad, Rajeev K. Varshney, Henry T. Nguyen, Hon-Ming Lam. Modelling predicts that soybean is poised to dominate crop production across Africa. Plant, Cell & Environment. 2018; 42 (1):373-385.

Chicago/Turabian Style

Christine H. Foyer; Kadambot Siddique; Amos P.K. Tai; Sven Anders; Nandor Fodor; Fuk-Ling Wong; Ndiko Ludidi; Mark A. Chapman; Brett J. Ferguson; Michael J. Considine; Florian Zabel; P.V. Vara Prasad; Rajeev K. Varshney; Henry T. Nguyen; Hon-Ming Lam. 2018. "Modelling predicts that soybean is poised to dominate crop production across Africa." Plant, Cell & Environment 42, no. 1: 373-385.

Special issue article
Published: 11 June 2018 in Ecohydrology
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Vegetation and its succession can change the parameters of soil water repellency (SWR) due to the change in amount and composition of soil organic matter. This hypothesis was tested in natural and agricultural environments in Germany, Hungary and Slovakia. The parameters investigated were the extent (determined by the repellency indices RI, RIc and RIm) and persistence (determined by the water drop penetration time, WDPT, and water repellency cessation time, WRCT) of SWR, as well as the potential wettability index, PWI, of organic matter in sandy soils. The SWR parameters and soil organic carbon content, SOC, increased in the course of primary succession at Mehlinger Heide, Germany, and Sekule, Slovakia. Dye‐tracer experiments undertaken at Sekule revealed contrasting flow patterns: (i) preferential flow in water repellent soil under biological soil crust and grass and (ii) piston flow in wettable soil that consists almost of pure quartz sand. The effective flow cross section, ECS, decreased and the degree of preferential flow, DPF, increased in the course of primary succession at Sekule. No consistent trend of the SWR parameters and SOC was observed in the course of secondary succession at Csólyospálos, Hungary. This is the first time that differences between trends in SWR parameters due to primary and secondary succession were observed and related to the composition of SOC and extracellular polymeric substances. It can be concluded that dynamics of soil organic matter composition during the succession controls soil water repellency.

ACS Style

Lubomir Lichner; Vincent J.M.N.L. Felde; Burkhard Büdel; Martin Leue; Horst H. Gerke; Ruth H. Ellerbrock; Jozef Kollár; Marek Rodný; Peter Šurda; Nándor Fodor; Renáta Sándor. Effect of vegetation and its succession on water repellency in sandy soils. Ecohydrology 2018, 11, e1991 .

AMA Style

Lubomir Lichner, Vincent J.M.N.L. Felde, Burkhard Büdel, Martin Leue, Horst H. Gerke, Ruth H. Ellerbrock, Jozef Kollár, Marek Rodný, Peter Šurda, Nándor Fodor, Renáta Sándor. Effect of vegetation and its succession on water repellency in sandy soils. Ecohydrology. 2018; 11 (6):e1991.

Chicago/Turabian Style

Lubomir Lichner; Vincent J.M.N.L. Felde; Burkhard Büdel; Martin Leue; Horst H. Gerke; Ruth H. Ellerbrock; Jozef Kollár; Marek Rodný; Peter Šurda; Nándor Fodor; Renáta Sándor. 2018. "Effect of vegetation and its succession on water repellency in sandy soils." Ecohydrology 11, no. 6: e1991.

Research article
Published: 08 May 2018 in PLoS ONE
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Dairy farming is one the most important sectors of United Kingdom (UK) agriculture. It faces major challenges due to climate change, which will have direct impacts on dairy cows as a result of heat stress. In the absence of adaptations, this could potentially lead to considerable milk loss. Using an 11-member climate projection ensemble, as well as an ensemble of 18 milk loss estimation methods, temporal changes in milk production of UK dairy cows were estimated for the 21st century at a 25 km resolution in a spatially-explicit way. While increases in UK temperatures are projected to lead to relatively low average annual milk losses, even for southern UK regions (<180 kg/cow), the ‘hottest’ 25×25 km grid cell in the hottest year in the 2090s, showed an annual milk loss exceeding 1300 kg/cow. This figure represents approximately 17% of the potential milk production of today’s average cow. Despite the potential considerable inter-annual variability of annual milk loss, as well as the large differences between the climate projections, the variety of calculation methods is likely to introduce even greater uncertainty into milk loss estimations. To address this issue, a novel, more biologically-appropriate mechanism of estimating milk loss is proposed that provides more realistic future projections. We conclude that South West England is the region most vulnerable to climate change economically, because it is characterised by a high dairy herd density and therefore potentially high heat stress-related milk loss. In the absence of mitigation measures, estimated heat stress-related annual income loss for this region by the end of this century may reach £13.4M in average years and £33.8M in extreme years.

ACS Style

Nándor Fodor; Andreas Foskolos; Cairistiona F. E. Topp; Jon M. Moorby; László Pásztor; Christine H. Foyer. Spatially explicit estimation of heat stress-related impacts of climate change on the milk production of dairy cows in the United Kingdom. PLoS ONE 2018, 13, e0197076 .

AMA Style

Nándor Fodor, Andreas Foskolos, Cairistiona F. E. Topp, Jon M. Moorby, László Pásztor, Christine H. Foyer. Spatially explicit estimation of heat stress-related impacts of climate change on the milk production of dairy cows in the United Kingdom. PLoS ONE. 2018; 13 (5):e0197076.

Chicago/Turabian Style

Nándor Fodor; Andreas Foskolos; Cairistiona F. E. Topp; Jon M. Moorby; László Pásztor; Christine H. Foyer. 2018. "Spatially explicit estimation of heat stress-related impacts of climate change on the milk production of dairy cows in the United Kingdom." PLoS ONE 13, no. 5: e0197076.

Book chapter
Published: 01 January 2018 in Jelenlegi PhD kutatások a 75 éves Meteorológiai Tanszéken
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ACS Style

Roland Hollós; Nándor Fodor; Dóra Hidy; Tibor Marton; Emese Bottyán; Zoltán Barcza. Mezőgazdasági célú Integrált Modellrendszer megvalósítása. Jelenlegi PhD kutatások a 75 éves Meteorológiai Tanszéken 2018, 69 -75.

AMA Style

Roland Hollós, Nándor Fodor, Dóra Hidy, Tibor Marton, Emese Bottyán, Zoltán Barcza. Mezőgazdasági célú Integrált Modellrendszer megvalósítása. Jelenlegi PhD kutatások a 75 éves Meteorológiai Tanszéken. 2018; ():69-75.

Chicago/Turabian Style

Roland Hollós; Nándor Fodor; Dóra Hidy; Tibor Marton; Emese Bottyán; Zoltán Barcza. 2018. "Mezőgazdasági célú Integrált Modellrendszer megvalósítása." Jelenlegi PhD kutatások a 75 éves Meteorológiai Tanszéken , no. : 69-75.

Book chapter
Published: 01 January 2017 in Soil Mapping and Process Modeling for Sustainable Land Use Management
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ACS Style

Sameh K. Abd-Elmabod; Abdallah Alaoui; Maria Anaya-Romero; Zsófia Bakacsi; Jasmin Baruck; Igor Bogunovic; Eric C. Brevik; C. Lee Burras; Artemi Cerdà; Sabine Chabrillat; Jesús Rodrigo Comino; Diego De La Rosa; Daniel DePellegrin; Soad El-Ashry; Paula Escribano; Ferran Estebaranz; Kinga Farkas-Iványi; Luuk Fleskens; Nandor Fodor; Marcos Francos; Michele Freppaz; Monica García; Clemens Geitner; Danilo Godone; Sven Grashey-Jansen; Fabian E. Gruber; Kati Heinrich; Gábor Illés; Antonio Jordán; Yones Khaledian; Annamária Laborczi; Beatriz Lozano-García; Oleksandr Menshov; Bradley A. Miller; Ieva Misiune; Miriam Muñoz-Rojas; Agata Novara; Marc Oliva; Andreas Papritz; Luis Parras-Alcántara; László Pásztor; Paulo Pereira; Jonathan D. Phillips; Jenny L. Richter; Emilio Rodríguez-Caballero; Thomas Schmid; Alois Simon; Anna Smetanova; Silvia Stanchi; József Szabó; Gábor Szatmári; Katalin Takács; Robert Traidl; Xavier Úbeda; Martine Van Der Ploeg; Nina Von Albertini; Borut Vrscaj. List of Contributors. Soil Mapping and Process Modeling for Sustainable Land Use Management 2017, 1 .

AMA Style

Sameh K. Abd-Elmabod, Abdallah Alaoui, Maria Anaya-Romero, Zsófia Bakacsi, Jasmin Baruck, Igor Bogunovic, Eric C. Brevik, C. Lee Burras, Artemi Cerdà, Sabine Chabrillat, Jesús Rodrigo Comino, Diego De La Rosa, Daniel DePellegrin, Soad El-Ashry, Paula Escribano, Ferran Estebaranz, Kinga Farkas-Iványi, Luuk Fleskens, Nandor Fodor, Marcos Francos, Michele Freppaz, Monica García, Clemens Geitner, Danilo Godone, Sven Grashey-Jansen, Fabian E. Gruber, Kati Heinrich, Gábor Illés, Antonio Jordán, Yones Khaledian, Annamária Laborczi, Beatriz Lozano-García, Oleksandr Menshov, Bradley A. Miller, Ieva Misiune, Miriam Muñoz-Rojas, Agata Novara, Marc Oliva, Andreas Papritz, Luis Parras-Alcántara, László Pásztor, Paulo Pereira, Jonathan D. Phillips, Jenny L. Richter, Emilio Rodríguez-Caballero, Thomas Schmid, Alois Simon, Anna Smetanova, Silvia Stanchi, József Szabó, Gábor Szatmári, Katalin Takács, Robert Traidl, Xavier Úbeda, Martine Van Der Ploeg, Nina Von Albertini, Borut Vrscaj. List of Contributors. Soil Mapping and Process Modeling for Sustainable Land Use Management. 2017; ():1.

Chicago/Turabian Style

Sameh K. Abd-Elmabod; Abdallah Alaoui; Maria Anaya-Romero; Zsófia Bakacsi; Jasmin Baruck; Igor Bogunovic; Eric C. Brevik; C. Lee Burras; Artemi Cerdà; Sabine Chabrillat; Jesús Rodrigo Comino; Diego De La Rosa; Daniel DePellegrin; Soad El-Ashry; Paula Escribano; Ferran Estebaranz; Kinga Farkas-Iványi; Luuk Fleskens; Nandor Fodor; Marcos Francos; Michele Freppaz; Monica García; Clemens Geitner; Danilo Godone; Sven Grashey-Jansen; Fabian E. Gruber; Kati Heinrich; Gábor Illés; Antonio Jordán; Yones Khaledian; Annamária Laborczi; Beatriz Lozano-García; Oleksandr Menshov; Bradley A. Miller; Ieva Misiune; Miriam Muñoz-Rojas; Agata Novara; Marc Oliva; Andreas Papritz; Luis Parras-Alcántara; László Pásztor; Paulo Pereira; Jonathan D. Phillips; Jenny L. Richter; Emilio Rodríguez-Caballero; Thomas Schmid; Alois Simon; Anna Smetanova; Silvia Stanchi; József Szabó; Gábor Szatmári; Katalin Takács; Robert Traidl; Xavier Úbeda; Martine Van Der Ploeg; Nina Von Albertini; Borut Vrscaj. 2017. "List of Contributors." Soil Mapping and Process Modeling for Sustainable Land Use Management , no. : 1.

Journal article
Published: 17 September 2016 in Landscape & Environment
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With the ongoing DOSoReMI.hu project we aimed to significantly extend the potential, how soil information requirements could be satisfied in Hungary. We started to compile digital soil maps, which fulfil optimally general as well as specific national and international demands from the aspect of thematic, spatial and temporal accuracy. In addition to relevant and available auxiliary, spatial data themes related to soil forming factors and/or to indicative environmental elements we heavily lean on the various national soil databases. The set of the applied digital soil mapping techniques is gradually broadened. In our paper we present some results in the form of brand new soil maps focusing on the territory of Hajdú-Bihar county.

ACS Style

László Pásztor; Annamária Laborczi; Katalin Takács; Gábor Szatmári; Gábor Zoltán Illés; Nándor Fodor; Gábor Négyesi; Zsófia Bakacsi; József Szabó. Spatial distribution of selected soil features in Hajdú-Bihar county represented by digital soil maps. Landscape & Environment 2016, 10, 203 -213.

AMA Style

László Pásztor, Annamária Laborczi, Katalin Takács, Gábor Szatmári, Gábor Zoltán Illés, Nándor Fodor, Gábor Négyesi, Zsófia Bakacsi, József Szabó. Spatial distribution of selected soil features in Hajdú-Bihar county represented by digital soil maps. Landscape & Environment. 2016; 10 (3):203-213.

Chicago/Turabian Style

László Pásztor; Annamária Laborczi; Katalin Takács; Gábor Szatmári; Gábor Zoltán Illés; Nándor Fodor; Gábor Négyesi; Zsófia Bakacsi; József Szabó. 2016. "Spatial distribution of selected soil features in Hajdú-Bihar county represented by digital soil maps." Landscape & Environment 10, no. 3: 203-213.

Journal article
Published: 02 August 2016 in Nature Plants
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The United Nations declared 2016 as the International Year of Pulses (grain legumes) under the banner ‘nutritious seeds for a sustainable future’. A second green revolution is required to ensure food and nutritional security in the face of global climate change. Grain legumes provide an unparalleled solution to this problem because of their inherent capacity for symbiotic atmospheric nitrogen fixation, which provides economically sustainable advantages for farming. In addition, a legume-rich diet has health benefits for humans and livestock alike. However, grain legumes form only a minor part of most current human diets, and legume crops are greatly under-used. Food security and soil fertility could be significantly improved by greater grain legume usage and increased improvement of a range of grain legumes. The current lack of coordinated focus on grain legumes has compromised human health, nutritional security and sustainable food production.

ACS Style

Christine H. Foyer; Hon-Ming Lam; Henry T. Nguyen; Kadambot H. M. Siddique; Rajeev K. Varshney; Timothy D. Colmer; Wallace Cowling; Helen Bramley; Trevor A. Mori; Jonathan M. Hodgson; James W. Cooper; Anthony J. Miller; Karl Kunert; Juan Vorster; Christopher Cullis; Jocelyn A. Ozga; Mark L. Wahlqvist; Yan Liang; Huixia Shou; Kai Shi; Jingquan Yu; Nandor Fodor; Brent N. Kaiser; Fuk-Ling Wong; Babu Valliyodan; Michael J. Considine. Neglecting legumes has compromised human health and sustainable food production. Nature Plants 2016, 2, 16112 .

AMA Style

Christine H. Foyer, Hon-Ming Lam, Henry T. Nguyen, Kadambot H. M. Siddique, Rajeev K. Varshney, Timothy D. Colmer, Wallace Cowling, Helen Bramley, Trevor A. Mori, Jonathan M. Hodgson, James W. Cooper, Anthony J. Miller, Karl Kunert, Juan Vorster, Christopher Cullis, Jocelyn A. Ozga, Mark L. Wahlqvist, Yan Liang, Huixia Shou, Kai Shi, Jingquan Yu, Nandor Fodor, Brent N. Kaiser, Fuk-Ling Wong, Babu Valliyodan, Michael J. Considine. Neglecting legumes has compromised human health and sustainable food production. Nature Plants. 2016; 2 (8):16112.

Chicago/Turabian Style

Christine H. Foyer; Hon-Ming Lam; Henry T. Nguyen; Kadambot H. M. Siddique; Rajeev K. Varshney; Timothy D. Colmer; Wallace Cowling; Helen Bramley; Trevor A. Mori; Jonathan M. Hodgson; James W. Cooper; Anthony J. Miller; Karl Kunert; Juan Vorster; Christopher Cullis; Jocelyn A. Ozga; Mark L. Wahlqvist; Yan Liang; Huixia Shou; Kai Shi; Jingquan Yu; Nandor Fodor; Brent N. Kaiser; Fuk-Ling Wong; Babu Valliyodan; Michael J. Considine. 2016. "Neglecting legumes has compromised human health and sustainable food production." Nature Plants 2, no. 8: 16112.

Original articles
Published: 04 April 2012 in International Journal of Digital Earth
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The 4M crop model was used to investigate the prospective effects of climate change on the agro-ecological characteristics of Hungary. The model was coupled with a detailed meteorological database and spatial soil information systems covering the whole territory of Hungary. Plant-specific model parameters were determined by inverse modeling. Future meteorological data were produced from the present meteorological data by combining a climate change scenario and a stochastic weather generator. Using the available and the generated data, the present and the prospective agro-ecological characteristics of Hungary were determined. According to the simulation results, average yields will decrease considerably (~30%) due to climate change. The rate of nitrate leaching will prospectively decrease as well. The fluctuations of both the yields and the annual nitrate leaching rates will most likely increase approaching the end of the twenty-first century. On the basis of the simulation results, the role of autumn crops is likely to become more significant in Hungary. The achieved results can be generalized for more extended regions based on the concept of spatial (geographical) analogy.

ACS Style

Nándor Fodor; László Pásztor; Tamás Németh. Coupling the 4M crop model with national geo-databases for assessing the effects of climate change on agro-ecological characteristics of Hungary. International Journal of Digital Earth 2012, 7, 391 -410.

AMA Style

Nándor Fodor, László Pásztor, Tamás Németh. Coupling the 4M crop model with national geo-databases for assessing the effects of climate change on agro-ecological characteristics of Hungary. International Journal of Digital Earth. 2012; 7 (5):391-410.

Chicago/Turabian Style

Nándor Fodor; László Pásztor; Tamás Németh. 2012. "Coupling the 4M crop model with national geo-databases for assessing the effects of climate change on agro-ecological characteristics of Hungary." International Journal of Digital Earth 7, no. 5: 391-410.

Original articles
Published: 30 January 2012 in Communications in Soil Science and Plant Analysis
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Development of the Hungarian ecological systems model 4M was initiated because the conditions and methods of Hungarian applications are different from the ones that appear in international crop simulation software packages. Because the majority of ecological systems models, just like the CERES model that was used during the development of 4M, do not have phosphorus and potassium modules, 4M initially was incomplete. Based on the work of Hungarian and foreign experts, a nutrient module was developed and was incorporated into the 4M model. The new module was calibrated and validated for phosphorus and potassium using the results of Hungarian aftereffects and long-term experiments. In principle, the nutrient module can be made suitable for simulating the turnover of any kind of nutrient by giving adequate values to the parameters.

ACS Style

Nándor Fodor; G. Máthéné-Gáspár; Tamás Németh. Modeling the Nutrient Balance of the Soil–Plant System using the 4M Simulation Model. Communications in Soil Science and Plant Analysis 2012, 43, 60 -70.

AMA Style

Nándor Fodor, G. Máthéné-Gáspár, Tamás Németh. Modeling the Nutrient Balance of the Soil–Plant System using the 4M Simulation Model. Communications in Soil Science and Plant Analysis. 2012; 43 (1-2):60-70.

Chicago/Turabian Style

Nándor Fodor; G. Máthéné-Gáspár; Tamás Németh. 2012. "Modeling the Nutrient Balance of the Soil–Plant System using the 4M Simulation Model." Communications in Soil Science and Plant Analysis 43, no. 1-2: 60-70.

Journal article
Published: 01 January 2012 in The Scientific World Journal
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In line with the critical comments formulated in relation to the S-shape global solar radiation estimation method, the original formula was improved via a 5-step procedure. The improved method was compared to four-reference methods on a large North-American database. According to the investigated error indicators, the final 7-parameter S-shape method has the same or even better estimation efficiency than the original formula. The improved formula is able to provide radiation estimates with a particularly low error pattern index () which is especially important concerning the usability of the estimated radiation values in crop models. Using site-specific calibration, the radiation estimates of the improved S-shape method caused an average of () relative error in the calculated biomass. Using only readily available site specific metadata the radiation estimates caused less than 5% relative error in the crop model calculations when they were used for locations in the middle, plain territories of the USA.

ACS Style

Nándor Fodor. Improving the S-Shape Solar Radiation Estimation Method for Supporting Crop Models. The Scientific World Journal 2012, 2012, 1 -10.

AMA Style

Nándor Fodor. Improving the S-Shape Solar Radiation Estimation Method for Supporting Crop Models. The Scientific World Journal. 2012; 2012 ():1-10.

Chicago/Turabian Style

Nándor Fodor. 2012. "Improving the S-Shape Solar Radiation Estimation Method for Supporting Crop Models." The Scientific World Journal 2012, no. : 1-10.

Journal article
Published: 15 October 2011 in Geoderma
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Saturated hydraulic conductivity (Ks) is one of the most important hydraulic properties affecting water flow in soils. Spatial and seasonal variability as well as scale dependency are key factors which make it more difficult to accurately measure the saturated hydraulic conductivity. The uncertainty of the Ks values due to different evaluation methods was investigated using raw measured data obtained on two different Hungarian soils with three different in situ measuring devices (double ring, tension disc and mini disc infiltrometers), as well as with two laboratory methods. Since the very same raw infiltration data could result in significantly different Ks values, we have introduced the evaluation method dependency of the measured Ks values. Our investigations found that the effect of the applied evaluation method for assessing raw measured data can be just as significant as the effect of other factors, such as the scale effect, as well as the spatial and temporal variability.

ACS Style

Nándor Fodor; Renáta Sándor; Tomas Orfanus; Lubomir Lichner; Kálmán Rajkai. Evaluation method dependency of measured saturated hydraulic conductivity. Geoderma 2011, 165, 60 -68.

AMA Style

Nándor Fodor, Renáta Sándor, Tomas Orfanus, Lubomir Lichner, Kálmán Rajkai. Evaluation method dependency of measured saturated hydraulic conductivity. Geoderma. 2011; 165 (1):60-68.

Chicago/Turabian Style

Nándor Fodor; Renáta Sándor; Tomas Orfanus; Lubomir Lichner; Kálmán Rajkai. 2011. "Evaluation method dependency of measured saturated hydraulic conductivity." Geoderma 165, no. 1: 60-68.

Journal article
Published: 15 January 2011 in Agricultural and Forest Meteorology
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Using analogies from soil science a new global radiation estimation method was developed and tested on a large North-American meteorological database. The newly developed procedure was compared to the well-known, Donatelli–Campbell method. Both the overall indicators and the more detailed analysis of the model performance confirmed that the new method is more efficient than the Donatelli–Campbell method. The improved performance is due to the greater number of parameters, as well as to the more adequate function type it uses during the calculation. Results suggest that it is sufficient to have 2 year-long data series for parameterizing the new method to provide at least as accurate radiation estimates as provided by the Donatelli–Campbell method. The new method can be efficiently used for locations with no radiation measurement by combining it with a simple spatial interpolation technique.

ACS Style

Nándor Fodor; János Mika. Using analogies from soil science for estimating solar radiation. Agricultural and Forest Meteorology 2011, 151, 78 -86.

AMA Style

Nándor Fodor, János Mika. Using analogies from soil science for estimating solar radiation. Agricultural and Forest Meteorology. 2011; 151 (1):78-86.

Chicago/Turabian Style

Nándor Fodor; János Mika. 2011. "Using analogies from soil science for estimating solar radiation." Agricultural and Forest Meteorology 151, no. 1: 78-86.