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001-es BibID:BIBFORM100395
035-os BibID:(cikkazonosító)516 (WoS)000764830200001 (Scopus)85125038156
Első szerző:Elbeltagi, Ahmed
Cím:Combination of Limited Meteorological Data for Predicting Reference Crop Evapotranspiration Using Artificial Neural Network Method / Ahmed Elbeltagi, Attila Nagy, Safwan Mohammed, Chaitanya B. Pande, Manish Kumar, Shakeel Ahmad Bhat, József Zsembeli, László Huzsvai, János Tamás, Elza Kovács, Endre Harsányi, Csaba Juhász
Dátum:2022
ISSN:2073-4395
Megjegyzések:Reference crop evapotranspiration (ETo) is an important component of the hydrological cycle that is used for water resource planning, irrigation, and agricultural management, as well as in other hydrological processes. The aim of this study was to estimate the ETo based on limited meteorological data using an artificial neural network (ANN) method. The daily data of minimum temperature (Tmin), maximum temperature (Tmax), mean temperature (Tmean), solar radiation (SR), humidity (H), wind speed (WS), sunshine hours (Ssh), maximum global radiation (gradmax), minimum global radiation (gradmin), day length, and ETo data were obtained over the long-term period from 1969 to 2019. The analysed data were divided into two parts from 1969 to 2007 and from 2008 to 2019 for model training and testing, respectively. The optimal ANN for forecasting ETo included Tmax, Tmin, H, and SR at hidden layers (4, 3); gradmin, SR, and WS at (6, 4); SR, day length, Ssh, and Tmean at (3, 2); all collected parameters at hidden layer (5, 4). The results showed different alternative methods for estimation of ETo in case of a lack of climate data with high performance. Models using ANN can help promote the decision-making for water managers, designers, and development planners.
Tárgyszavak:Agrártudományok Növénytermesztési és kertészeti tudományok idegen nyelvű folyóiratközlemény külföldi lapban
folyóiratcikk
Megjelenés:Agronomy-Basel. - 12 : 2 (2022), p. 1-18. -
További szerzők:Nagy Attila (1982-) (környezetgazdálkodási agrármérnök) Mohammed Safwan (1985-) (agrármérnök) Pande, Chaitanya Kumar, Manish Bhat, Shakeel Ahmad Zsembeli József (1967-) (agrármérnök) Huzsvai László (1961-) (talajerőgazdálkodási szakmérnök, agrármérnök) Tamás János (1959-) (környezetgazdálkodási agrármérnök) Kovács Elza (1976-) (okleveles vegyész, angol-magyar szakfordító, anyagmérnök MSc) Harsányi Endre (1976-) (agrármérnök) Juhász Csaba (1962-) (környezetgazdálkodási agrármérnök)
Pályázati támogatás:TKP2020-IKA-04
Egyéb
KP2021-NKTA-32
Egyéb
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DOI
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2.

001-es BibID:BIBFORM091906
Első szerző:Gorliczay Edit (környezetgazdálkodási agrármérnök)
Cím:Examination and statistical evaluation of physico-chemical parameters of windrow composting / Edit Gorliczay, János Tamás, Sándor Kun, László Huzsvai, László Bárány
Dátum:2020
ISSN:1587-1282
Megjegyzések:The treatment and utilization of plant and animal waste and by-products from agriculture is very diverse. Traditional environmental management practices for waste management have been retained through soil conservation and the applied of recycle degradable organic substances in soil. The management of by-products from agriculture (animal husbandry) is important because a closed loop can be created to utilize by-products (manure, feathers) from the production of the main product (eggs, meat, milk) and to form a raw material for a new product.It is important to treat the resulting by-products, especially deep-litter manure,as it has served as a basis for compost-treated manure to develop an organic-based, soil-conditioning product line. Poultry manure by itself is not suitable as a substrate for aerobic decomposition, so it has to be mixed with other substances (zeolite, bentonite, soil), because of its high nutrient capacity, it is an acidifying substance.The aim of this study was to compost the mixture of poultry manure and hen manure by the addition of zeolite and to monitor the composting process. It was also our aim tostatistically determine the effect of the zeolite on parameters describing the composting process.The windrow composting experiments were set up in the composting area of the University of Debrecen, Institute of Water and Environmental Management. The composting experiment was 62 days long, during which the main parameters describing the composting process were continuously monitored: temperature (?C), moisture content (w/w%), electrical conductivity (mS/cm), organic matter content (w/w%), examination of nitrogen forms (w/w%). In this study, three factors were investigated: temperature, humidity, and pH. For statistical evaluation, R software and RStudio user interface were used. We developed a repeated measurement model, in which the fixed and random effects were determined for our parameters under study, and the resulting relationships were shown on interaction plots.Based on our results, the temperature of the prisms has become independent of the ambient temperature and the composting stages can be separated in both the control and the zeolite treated prisms. In the repeated measurement model, we proved that treatment, time and treatment: time interaction were significant at both temperature and pH
Tárgyszavak:Agrártudományok Állattenyésztési tudományok idegen nyelvű folyóiratközlemény hazai lapban
folyóiratcikk
composting
manure
physico-chemical parameters
statistical parameters
Megjelenés:Agrártudományi Közlemények = Acta agraria Debreceniensis. - 1 (2020), p. 33-38. -
További szerzők:Tamás János (1959-) (környezetgazdálkodási agrármérnök) Kun Sándor (1984-) (vegyész) Huzsvai László (1961-) (talajerőgazdálkodási szakmérnök, agrármérnök) Bárány László (1952-) (ügyvezető igazgató)
Pályázati támogatás:GINOP-2.2.1.-15-2017-00043
GINOP
EFOP-3.6.3-VEKOP-16-2017-00008
EFOP
Internet cím:DOI
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3.

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
FIKP
Internet cím:Szerző által megadott URL
DOI
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