Nxumalo Gift Siphiwe

1.

Radócz, L., Nagy, A., Szőllősi, N., Kiss, N. É., Szabó, A., Tamás, J., Nxumalo, G., Radócz, L.: AI-Augmented Systematic Review of Remote Sensing and Predictive Modelling for Mycotoxin Risk Monitoring in Cereal Crops Across Central and Balkan Europe.
Remote Sens. 18 (3), 1-37, (article identifier: 2063), 2026.

doi DEA

Journal metrics:

Q1 Earth and Planetary Sciences (miscellaneous) (2025)

2.

Nxumalo, G., Ramabulana, T. S., Zibuyile, D., Tamás, J., Kiss, N. É., Nagy, A.: AI-Driven Integration of Sentinel-1 SAR for High-Resolution Soil Water Content Estimation to Enhance Precision Irrigation in Smallholder Maize Systems, Vhembe District.
Water. 18, 1-34, (article identifier: 499), 2026.

doi DEA

Journal metrics:

Q1 Aquatic Science (2025)

Q1 Water Science and Technology (2025)

Q1 Geography, Planning and Development (2025)

Q2 Biochemistry (2025)

3.

Radócz, L., Nxumalo, G., Kiss, N. É., Szabó, A., Tamás, J., Nagy, A., Radócz, L.: Comparative Evaluation of UAV Multispectral Sensors for Precision Agriculture: Spectral and Structural Consistency in Maize Canopies.
Drones-Basel. 2026 10 (10), 1-20, (article identifier: 723), 2026.

doi DEA

Journal metrics:

Q1 Artificial Intelligence (2025)

Q1 Computer Science Applications (2025)

Q1 Information Systems (2025)

Q1 Aerospace Engineering (2025)

Q1 Control and Systems Engineering (2025)

4.

Nxumalo, G., Ramabulana, T. S., Nagy, A.: GIS and Remote Sensing Applications for Assessing Soil Contamination in South African Agriculture: A Machine Learning-Enhanced Scoping Review.
Agriculture. 16 (7), 1-36, (article identifier: 797), 2026.

doi DEA

Journal metrics:

Q1 Agronomy and Crop Science (2025)

Q1 Food Science (2025)

Q1 Plant Science (2025)

5.

Pásztor, D., Kovács, G., Nagy, A., Nxumalo, G., Tuba, G., Tamás, J.: Improving Maize Drought Tolerance Under a Continental Climate: A Sap-Flow-Based Evaluation of Biostimulants and Supplemental Irrigation in the Pannonian Basin.
Agronomy. 16 (14), 1-20, (article identifier: 1305), 2026.

doi DEA WoS Scopus

Journal metrics:

Q1 Agronomy and Crop Science (2025)

6.

Nxumalo, G., Ramabulana, T. S., Zibuyile, D., Louis, A., Nagy, A.: Integrating OPTRAM and Machine Learning with Multimodal EO Proxies for Optimized Irrigation Scheduling in Smallholder Systems: a Vhembe District Case Study.
Frontiers in Agronomy. 7, 1-17, (article identifier: 1697188), 2026.

doi DEA

Journal metrics:

Q1 Agricultural and Biological Sciences (miscellaneous) (2025)

Q1 Agronomy and Crop Science (2025)

Q1 Plant Science (2025)

Q1 Soil Science (2025)

7.

Nxumalo, G., Fehér, Z. Z., Tamás, J., Nagy, A.: MODIS-Sentinel-2 Data Fusion for Cloud-Robust Crop Evapotranspiration Estimation in a Nitrate-Sensitive Irrigated Maize System: Evaluating Gap-Filling Strategies for Evidence-Based Irrigation Scheduling.
Water. 18, 1-37, (article identifier: 1644), 2026.

doi DEA

Journal metrics:

Q1 Aquatic Science (2025)

Q1 Water Science and Technology (2025)

Q1 Geography, Planning and Development (2025)

Q2 Biochemistry (2025)

8.

Fehér, Z. Z., Nxumalo, G., Nagy, A.: Multi-Sensor NDVI Fusion for Daily Crop EvapotranspirationMapping: A Six-Year Irrigated Maize Assessment UsingMODIS-Sentinel-2-Landsat (2020-2025).
Sensors. 26 (14), 1-22, (article identifier: 4470), 2026.

doi DEA

Journal metrics:

Q1 Electrical and Electronic Engineering (2025)

Q1 Analytical Chemistry (2025)

Q1 Instrumentation (2025)

Q2 Biochemistry (2025)

Q2 Medicine (miscellaneous) (2025)

Q2 Atomic and Molecular Physics, and Optics (2025)

Q2 Information Systems (2025)

9.

Nxumalo, G., Ramabulana, T. S., Vilakazi, N. F., Nagy, A.: Opportunities and Challenges of Sensor- and Acoustic-Based Irrigation Monitoring Technologies in South Africa: A Scoping Review with Machine Learning-Enhanced Evidence Synthesis.
AgriEngineering. 8 (5), 1-39, (article identifier: 161), 2026.

doi DEA

Journal metrics:

Q1 Horticulture (2025)

Q2 Agronomy and Crop Science (2025)

Q2 Food Science (2025)

Q2 Engineering (miscellaneous) (2025)

10.

Nagy, A., Szabó, A., Fehér, Z. Z., Kiss, N. É., Nxumalo, G., Tamás, J.: Precíziós öntözés adatvezérelt módszerekkel kukoricában.
In: A Magyar Hidrológiai Társaság által rendezett XLIII. Országos Vándorgyűlés dolgozatai. Szerk.: Somlyódi Balázs, Váradi József, Magyar Hidrológiai Társaság, Budapest, 1-12, 2026. ISBN: 9789638172488

DEA

11.

Nxumalo, G., Tamás, J., Nagy, A., Fehér, Z. Z.: Spatio-Temporal Deep Fusion of Optical-SAR Remote Sensing with Physics-Constrained Machine Learning for Operational Crop Water Use Monitoring in Nitrate-Sensitive Agricultural Systems.
In: IEEE 2026: International Geoscience and Remote Sensing Symposium, IEEE-INST Electrical Electroonics Engineers INC, Piscataway, Paer TUP2PB2, 2026.

DEA

12.

Nxumalo, G., Fehér, Z. Z., Tamás, J., Burganakov, U., Nagy, A.: Advancing agricultural water regime using sar technology: soil moisture and etc estimation for sustainable crop production.
In: Abstract Book of the 8th International Scientific Conference on Water, Magyar Agrár-és Élettudományi Egyetem, Gödöllő, 16, 2025. ISBN: 9789636231156(pdf)

DEA

13.

Nxumalo, G., Chauke, H.: Challenges and opportunities in smallholder agriculture digitization in South Africa.
Front. Sustain. Food Syst. 9, (article identifier: 1583224), 2025.

doi DEA WoS Scopus

Journal metrics:

D1 Horticulture

Q1 Agronomy and Crop Science

Q1 Food Science

Q1 Ecology

Q2 Global and Planetary Change

Q2 Management, Monitoring, Policy and Law

14.

Szabó, A., Nxumalo, G., Bódi, E., Ademola, B., Tamás, J., Nagy, A.: Evaluation of ground based spectral imaging for real time maize biomass monitoring.
Front. Plant Sci. 16, 1-15, (article identifier: 1566305), 2025.

doi DEA

Journal metrics:

D1 Plant Science

15.

Nxumalo, G., Radócz, L., Ramabulana, T. S., Nagy, A.: Machine Learning-Enhanced Soil Water Content Estimation Using Sentinel-1 SAR for Precision Irrigation in Eastern Hungary.
In: XIII. Interdiszciplináris doktorandusz konferencia, Pécsi Tudományegyetem Doktorandusz Önkormányzat, Pécs, 21, 2025.

DEA

16.

Nagy, A., Szabó, A., Nxumalo, G., Bódi, E., Tamás, J.: Spectral-based monitoring methods to optimise precision irrigation in maize.
In: EGU General Assembly 2025, European Geosciences Union, Vienna, EGU25-9499, 2025.

doi DEA

17.

Nxumalo, G., Fehér, Z. Z., Ramabulana, T. S., Nagy, A.: Using Earth Observation and AI for Irrigation Management Amidst Meteorological Hazards: A Case Study in Limpopo, South Africa.
In: II. Natural Hazards and Climate Change Conference: International Conference for identifying and tackling challenges together / György Sipos, Szegedi Tudományegyetem, Szeged, 56, 2025.

DEA

18.

Nagy, A., Szabó, A., Elbeltagi, A., Nxumalo, G., Bódi, E., Tamás, J.: Hyperspectral indices data fusion-based machine learning enhanced by MRMR algorithm for estimating maize chlorophyll content.
Front. Plant Sci. 15, 1-18, (article identifier: 1419316), 2024.

doi DEA WoS Scopus

Journal metrics:

D1 Plant Science

19.

Nxumalo, G., Magyar, T., Tamás, J., Nagy, A.: Modelling Soil Moisture Content with Hydrus 2D in aContinental Climate for Effective Maize Irrigation Planning.
Agriculture-Basel. 14 (8), 1-23, (article identifier: 1340), 2024.

doi DEA WoS Scopus

Journal metrics:

Q1 Agronomy and Crop Science

Q1 Plant Science

Q2 Food Science

20.

Nxumalo, G., Magyar, T., Fehér, Z. Z., Tamás, J., Nagy, A.: Modelling soil water balance to plan maize irrigation for optimized water use.
In: KMKTK2024, XIX. Kárpát-medencei Környezettudományi Konferencia Absztrakt füzet = 19th Carpathian Basin Environmental Science Conferencea Book of Abstracts / Buró Botond, Molnár Mihály, Magyar Tudományos Akadémia. Atommagkutató Intézet, Debrecen, 58, 2024. ISBN: 9789638321602

DEA

21.

Nxumalo, G., Kiss, N. É., Fehér, Z. Z., Magyar, T., Bódi, E., Szabó, A., Pásztor, D., Tamás, J., Nagy, A.: Optimizing of alternative water resources reutilization on extreme sandy soil.
In: EGU General Assembly 2024 : SSS9.10 : Novel monitoring techniques and modeling tools to assess soil health for resilient management of soil and water resources in agroecosystems, European Geosciences Union, Vienna, 1(EGU24-18763), 2024.

DEA

22.

Nxumalo, G.: Assessment of remote sensed data for weed species recognition in agricultural fields.
In: EGU General Assembly 2023 : BG9.3 Remote Sensing of Vegetation Biodiversity/ co-organized by BG, European Geosciences Union, Munchen, 1 (EGU23-401), 2023.

doi DEA

23.

Nxumalo, G., Tamás, J., Bódi, E., Nagy, A., Fehér, Z. Z.: Development of a Cloud-Based GIS for Urban Soil Pollution Survey in Debrecen.
In: Absztraktkötet : III. Környezet, Egészség, Biztonság (EHS) Nemzetközi Szimpózium = Book of abstracts : 3 rd International Symposium on Environmental, Health and Safety (ISEHS), Debreceni Egyetem Műszaki Kar, Debrecen, 16, 2023.

DEA

24.

Nxumalo, G., Bashir, B., Alsafadi, K., Bachir, H., Harsányi, E., Arshad, S., Mohammed, S.: Meteorological Drought Variability and Its Impact on Wheat Yields across South Africa.
Int. J. Environ. Res. Public Health. 19 (24), 1-22, (article identifier: 16469), 2022.

doi DEA WoS Scopus

Journal metrics:

Q2 Health, Toxicology and Mutagenesis

Q2 Pollution

Q2 Public Health, Environmental and Occupational Health

Nxumalo Gift Siphiwe

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