Péter Ragán
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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
Adrienn Széles
University of Debrecen
Arpad Illes
University of Debrecen
András Tamás
University of Debrecen
László Radócz
University of Debrecen
Atala Szabó
University of Debrecen
Csaba Bojtor
University of Debrecen
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