Péter Ragán

University of Debrecen
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Articles (8)

Year:

2023

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 3 × 25 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.

Year:

2023

Year:

2022

Year:

2022

Year:

2022

Year:

2022

Year:

2021

Year:

2020

Collaborators (7)

Áron Béni

assistant professor

University of Debrecen

HUNGARY
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Adrienn Széles

University of Debrecen

HUNGARY
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Arpad Illes

University of Debrecen

HUNGARY
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András Tamás

University of Debrecen

HUNGARY
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László Radócz

University of Debrecen

HUNGARY
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Atala Szabó

University of Debrecen

HUNGARY
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Csaba Bojtor

University of Debrecen

HUNGARY
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