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001-es BibID:	BIBFORM111452
035-os BibID:	(cikkazonosító)1297 (Scopus)85160411163 (WoS)000994795300001
Első szerző:	Harsányi Endre (agrármérnök)
Cím:	Data Mining and Machine Learning Algorithms for Optimizing Maize Yield Forecasting in Central Europe / Endre Harsányi, Bashar Bashir, Sana Arshad, Akasairi Ocwa, Attila Vad, Abdullah Alsalman, István Bácskai, Tamás Rátonyi, Omar Hijazi, Adrienn Széles, Safwan Mohammed
Dátum:	2023
ISSN:	2073-4395
Megjegyzések:	Artificial intelligence, specifically machine learning (ML), serves as a valuable tool for decision support in crop management under ongoing climate change. However, ML implementation to predict maize yield is still limited in Central Europe, especially in Hungary. In this context, we assessed the performance of four ML algorithms (Bagging (BG), Decision Table (DT), Random Forest (RF) and Artificial Neural Network-Multi Layer Perceptron (ANN-MLP)) in predicting maize yield based on four different input scenarios. The collected data included both agricultural data (production (PROD) (ton) and maize cropped area (AREA) (ha)) and climate data (annual mean temperature ?C (Tmean), precipitation (PRCP) (mm), rainy days (RD), frosty days (FD) and hot days (HD)). This research adopted four scenarios, as follows: SC1: AREA+ PROD+ Tmean+ PRCP+ RD+ FD+ HD; SC2: AREA+ PROD; SC3: Tmean+ PRCP+ RD+ FD+ HD; and SC4: AREA+ PROD+ Tmean+ PRCP. In the training stage, ANN-MLP-SC1 and ANN-MLP-SC4 outperformed other ML algorithms; the correlation coefficient (r) was 0.99 for both, while the root mean squared errors (RMSEs) were 107.9 (ANN-MLP-SC1) and 110.7 (ANN-MLP-SC4). In the testing phase, the ANN-MLP-SC4 had the highest r value (0.96), followed by ANN-MLP-SC1 (0.94) and RF-SC2 (0.94). The 10-fold cross validation also revealed that the ANN-MLP-SC4 and ANN-MLP-SC1 have the highest performance. We further evaluated the performance of the ANN-MLP-SC4 in predicting maize yield on a regional scale (Budapest). The ANN-MLP-SC4 succeeded in reaching a high-performance standard (r = 0.98, relative absolute error = 21.87%, root relative squared error = 20.4399% and RMSE = 423.23). This research promotes the use of ANN as an efficient tool for predicting maize yield, which could be highly beneficial for planners and decision makers in developing sustainable plans for crop management.
Tárgyszavak:	Agrártudományok Növénytermesztési és kertészeti tudományok idegen nyelvű folyóiratközlemény külföldi lapban folyóiratcikk maize yield climate multilayer perceptron random forest optimum model
Megjelenés:	Agronomy-Basel. - 13 : 5 (2023), p. 1-22. -
További szerzők:	Bashir, Bashar Arshad, Sana Ocwa, Akasairi (1987-) (Crop scientist) Vad Attila (1981-) (agrármérnök) Alsalman, Abdullah Bácskai István (1985-) (Okleveles gépészmérnök) Rátonyi Tamás (1967-) (agrármérnök) Hijazi, Omar Széles Adrienn (1980-) (okleveles agrármérnök) Mohammed Safwan (1985-) (agrármérnök)
Pályázati támogatás:	TKP2021-NKTA-32 Egyéb
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001-es BibID:	BIBFORM119328
Első szerző:	Ocwa, Akasairi (Crop scientist)
Cím:	Maize Grain Yield and Quality Improvement Through Biostimulant Application: a Systematic Review / Akasairi Ocwa, Safwan Mohammed, Seyed Mohammad Nasir Mousavi, Árpád Illés, Csaba Bojtor, Péter Ragán, Tamás Rátonyi, Endre Harsányi
Dátum:	2024
ISSN:	0718-9508 0718-9516
Megjegyzések:	Increasing the productivity of cereals such as maize while protecting the environment remains a fundamental impetus of healthy food production systems. The use of biostimulants is one of the sustainable strategies to achieve this balance, although the ability of biostimulants to enhance maize productivity varies. Moreover, research on the efcacy of biostimulants is ubiquitous with limited comprehensive global analysis. In this context, this systematic review evaluated the sole and interactive efects of biostimulants on the yield and quality of maize grain from a global perspective. Changes in yield (t ha-1), protein content (%), starch content (%) and oil content (%) of maize grain were assessed. Results revealed that sole and combined application of biostimulants signifcantly improved grain yield. Irrespective of the region, the highest and the lowest grain yields ranged between 16-20 t ha-1 and 1-5 t ha-1, respectively. In sole application, the promising biostimulants were chicken feather (16.5 t ha-1), and endophyte Colletotrichum tofeldiae (14.5 t ha-1). Sewage sludge x NPK (15.4 t ha-1), humic acid x control release urea (12.4 t ha-1), Azospirillum brasilense or Bradyrhizobium japonicum x maize hybrids (11.6 t ha-1), and Rhizophagus intraradices x earthworms (10.0 t ha-1) had higher yield for the interactive efects. The efects of biostimulants on grain quality were minimal, and all attributes improved in the range from 0.1 to 3.7%. Overall, biostimulants had a distinct improvement efect on yield, rather than on the quality of grain. As one way of maximising maize productivity, soil health, and the overall functioning of crop agroecosystems, the integrated application of synergistic microbial and non-microbial biostimulants could provide a viable option. However, the ability to produce consistent yield and quality of grain improvement remains a major concern.
Tárgyszavak:	Agrártudományok Növénytermesztési és kertészeti tudományok idegen nyelvű folyóiratközlemény külföldi lapban folyóiratcikk Biostimulants Grain Maize Oil content Protein content Starch content Yield
Megjelenés:	Journal of Soil Science and Plant Nutrition. - [Epub ahead of print] : - (2024), p.1-41. -
További szerzők:	Mohammed Safwan (1985-) (agrármérnök) Mousavi, Seyed Mohammad Nasir (1988-) (agrármérnök) Illés Árpád (1994-) (növényorvos) Bojtor Csaba (1993-) (okleveles növényorvos) Ragán Péter (1986-) (környzetgazdálkodási agrármérnök) Rátonyi Tamás (1967-) (agrármérnök) Harsányi Endre (1976-) (agrármérnök)
Pályázati támogatás:	TKP2021-NKTA-32 Egyéb
Internet cím:	Szerző által megadott URL DOI Intézményi repozitóriumban (DEA) tárolt változat
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001-es BibID:	BIBFORM112204
035-os BibID:	(cikkazonosító)14 (Scopus)85160908963
Első szerző:	Ocwa, Akasairi (Crop scientist)
Cím:	A bibliographic review of climate change and fertilization as the main drivers of maize yield: implications for food security / Akasairi Ocwa ; Endre Harsanyi ; Adrienn Széles ; Imre János Holb ; Szilárd Szabó ; Tamás Rátonyi ; Safwan Mohammed
Dátum:	2023
ISSN:	2048-7010
Megjegyzések:	Introduction Crop production contribution to food security faces unprecedented challenge of increasing human population. This is due to the decline in major cereal crop yields including maize resulting from climate change and declining soil infertility. Changes in soil nutrient status and climate have continued to occur and in response, new fertilizer recommendations in terms of formulations and application rates are continuously developed and applied globally. In this sense, this review was conducted to: (i) identify the key areas of concentration of research on fertilizer and climate change effect on maize grain yield, (ii) assess the extent of the effect of climate change on maize grain yield, (iii) evaluate the extent of the effect of fertilization practices on maize grain yield, and (iv) examine the effect of interaction between climate change factors and fertilization practices on maize grain yield at global perspective.MethodologyComprehensive search of global literature was conducted in Web of Science (WoS) database. For objective 1, metadata on co-authorship (country, organisation), and co-occurrence of keywords were exported and analysed using VOSviewer software. For objective 2-4, yield data for each treatment presented in the articles were extracted and yield increment calculated.ResultsThe most significant keywords: soil fertility, nutrient use efficiency, nitrogen use efficiency, integrated nutrient management, sustainability, and climate change adaptation revealed efforts to improve maize production, achieve food security, and protect the environment. A temperature rise of 1-4 °C decreased yield by 5-14% in warm areas and increased by < 5% in cold areas globally. Precipitation reduction decreased yield by 25-32%, while CO2concentration increased and decreased yield by 2.4 to 7.3% and 9 to 14.6%, respectively. A promising fertilizer was a combination of urea +nitrapyrin with an average yield of 5.1 and 14.4 t ha?1 under non-irrigation and irrigation, respectively. Fertilization under climate change was projected to reduce yield in the average range of 10.5-18.3% by 2099.ConclusionThe results signified that sole fertilizer intensification is insufficient to attain sustainable maize yield. Therefore, there is need for integrated agronomic research that combines fertilizers and other technologies for enhancing maize yield, and consequently maize contribution to the attainment of global food security under climate change conditions
Tárgyszavak:	Agrártudományok Növénytermesztési és kertészeti tudományok idegen nyelvű folyóiratközlemény külföldi lapban folyóiratcikk Climate change Drought Fertilizers Heat stress Maize Nitrogen Temperature Yield
Megjelenés:	Agriculture & Food Security. - 12 : 1 (2023), p. 1-18. -
További szerzők:	Harsányi Endre (1976-) (agrármérnök) Széles Adrienn (1980-) (okleveles agrármérnök) Holb Imre (1973-) (agrármérnök) Szabó Szilárd (1974-) (geográfus) Rátonyi Tamás (1967-) (agrármérnök) Mohammed Safwan (1985-) (agrármérnök)
Pályázati támogatás:	TKP2021-NKTA-32 Egyéb
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001-es BibID:	BIBFORM108703
Első szerző:	Ocwa, Akasairi (Crop scientist)
Cím:	Mapping evidence of the role of foliar fertilizers in mitigating abiotic stress effects on maize: A review / Akasairi Ocwa, Safwan Mohammed, Attila Vad, Péter Ragán, Tamás Rátonyi, Endre Harsányi
Dátum:	2022
ISBN:	978-83-966062-1-1
Tárgyszavak:	Agrártudományok Növénytermesztési és kertészeti tudományok előadáskivonat könyvrészlet
Megjelenés:	International Congress on Sustainable development in the Human Environment - Current & Future Challenges. ICSDEV (2022)(Alanya) : Proceedings book / eds. Anna Krakowiak-Bal, Atilgan Atilgan, Roman Rolbiecki, Hakan Aktas. - p. 201. -
További szerzők:	Mohammed Safwan (1985-) (agrármérnök) Vad Attila (1981-) (agrármérnök) Ragán Péter (1986-) (környzetgazdálkodási agrármérnök) Rátonyi Tamás (1967-) (agrármérnök) Harsányi Endre (1976-) (agrármérnök)
Internet cím:	Intézményi repozitóriumban (DEA) tárolt változat
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