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001-es BibID:	BIBFORM125468
Első szerző:	Radócz László (Növényorvos)
Cím:	Multispectral UAV-Based Disease Identification Using Vegetation Indices for Maize Hybrids / László Radócz, Csaba Juhász, András Tamás, Árpád Illés, Péter Ragán, László Radócz
Dátum:	2024
ISSN:	2077-0472
Megjegyzések:	Abstract: In the future, the cultivation of maize will become more and more prominent. As the world's demand for food and animal feeding increases, remote sensing technologies (RS technologies), especially unmanned aerial vehicles (UAVs), are developing more and more, and the usability of the cameras (Multispectral-MS) installed on them is increasing, especially for plant disease detection and severity observations. In the present research, two different maize hybrids, P9025 and sweet corn Dessert R78 (CS hybrid), were employed. Four different treatments were performed with three different doses (low, medium, and high dosage) of infection with corn smut fungus (Ustilago maydis [DC] Corda). The fields were monitored two times after the inoculation?20 DAI (days after inoculation) and 27 DAI. The orthomosaics were created in WebODM 2.5.2 software and the study included five vegetation indices (NDVI [Normalized Difference Vegetation Index], GNDVI [Green Normalized Difference Vegetation Index], NDRE [Normalized Difference Red Edge], LCI [Leaf Chlorophyll Index] and ENDVI [Enhanced Normalized Difference Vegetation Index]) with further analysis in QGIS. The gathered data were analyzed using R-based Jamovi 2.6.13 software with different statistical methods. In the case of the sweet maize hybrid, we obtained promising results, as follows: the NDVI values of CS 0 were significantly higher than the high-dosed infection CS 10.000 with a mean difference of 0.05422 *** and a p value of 4.43 ? 10?5 value, suggesting differences in all of the levels of infection. Furthermore, we investigated the correlations of the vegetation indices (VI) for the Dessert R78, where NDVI and GNDVI showed high correlations. NDVI had a strong correlation with GNDVI (r = 0.83), a medium correlation with LCI (r = 0.56) and a weak correlation with NDRE (r = 0.419). There was also a strong correlation between LCI and GNDVI, with r = 0.836. NDRE and GNDVI indices had the correlation coefficients with a CCoeff. of r = 0.716. For hybrid separation analyses, useful results were obtained for NDVI and ENDVI as well.
Tárgyszavak:	Agrártudományok Növénytermesztési és kertészeti tudományok idegen nyelvű folyóiratközlemény külföldi lapban folyóiratcikk UAV Plant protection GIS Vegetation indices Plant disease
Megjelenés:	Agriculture-Basel. - 14 : 11 (2024), p. 1-15. -
További szerzők:	Juhász Csaba (1995-) (okleveles növényorvos, mezőgazdasági mérnök) Tamás András (1986-) (gazdasági agrármérnök, növénytermesztés és kertészeti tudományok) Illés Árpád (1994-) (növényorvos) Ragán Péter (1986-) (környzetgazdálkodási agrármérnök) Radócz László (1965-) (növényvédő agrármérnök)
Pályázati támogatás:	ÚNKP-2023-3 Egyéb
Internet cím:	Szerző által megadott URL DOI Intézményi repozitóriumban (DEA) tárolt változat
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001-es BibID:	BIBFORM109784
035-os BibID:	(Scopus)85152002959 (WoS)000953872600001
Első szerző:	Tamás András (gazdasági agrármérnök, növénytermesztés és kertészeti tudományok)
Cím:	Assessment of NDVI dynamics of maize (Zea mays L.) and its relation to grain yield in a polyfactorial experiment based on remote sensing / Tamás András, Kovács Elza, Horváth Éva, Juhász Csaba, Radócz László, Rátonyi Tamás, Ragán Péter
Dátum:	2023
ISSN:	0551-3677 1338-4376
Megjegyzések:	Remote sensing is an efficient tool to detect vegetation heterogeneity and dynamics of crop development in real-time. In this study, the performance of three maize hybrids (Fornad FAO-420, Merida FAO-380, and Corasano FAO-490-510) was monitored as a function of nitrogen dose (0, 80 and 160 kg N ha?1 ), soil tillage technologies (winter ploughing, strip-tillage, and ripping), and irrigation (rainfed and 3x25 mm) in a warm temperature dry region of East-Central Europe. Dynamics of the Normalized Difference Vegetation Index (NDVI) were followed in the vegetation period of 2021, a year of drought, by using sensors mounted on an unmanned aerial vehicle. N-fertilization resulted in significantly higher NDVI throughout the entire vegetation period (p < 0.001) in each experimental combination. A significant positive effect of irrigation was observed on the NDVI during the drought period (77-141 days after sowing). For both the tillage technologies and hybrids, NDVI was found to be significantly different between treatments, but showing different dynamics. Grain yield was in strong positive correlation with the NDVI between the late vegetative and the early generative stages (r = 0.80-0.84). The findings suggest that the NDVI dynamics is an adequate indicator for evaluating the impact of different treatments on plant development and yield prediction.
Tárgyszavak:	Agrártudományok Növénytermesztési és kertészeti tudományok idegen nyelvű folyóiratközlemény külföldi lapban folyóiratcikk
Megjelenés:	Agriculture-Basel. - 13 : 3 (2023), p. 1-17. -
További szerzők:	Kovács Elza (1976-) (okleveles vegyész, angol-magyar szakfordító, anyagmérnök MSc) Horváth Éva (1993-) (környezetgazdálkodási agrármérnök) Juhász Csaba (1962-) (környezetgazdálkodási agrármérnök) Radócz László (1996-) (Növényorvos) Rátonyi Tamás (1967-) (agrármérnök) Ragán Péter (1986-) (környzetgazdálkodási agrármérnök)
Pályázati támogatás:	TKP2021-NKTA-32 Egyéb
Internet cím:	Intézményi repozitóriumban (DEA) tárolt változat DOI
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