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.

The main goal of this research was to investigate the effects of corn smut (Ustilago maydis DC. Corda) infection on the morphological (plant height, and stem diameter), and biochemical parameters of Zea mays L. plants. The biochemical parameters included changes in the relative chlorophyll, malondialdehyde (MDA), and photosynthesis pigments’ contents, as well as the activities of antioxidant enzymes—ascorbate peroxidase (APX), guaiacol peroxidase (POD), and superoxide dismutase (SOD). The second aim of this study was to evaluate the impact of phytohormones (auxin, cytokinin, gibberellin, and ethylene) on corn smut-infected plants. The parameters were measured 7 and 11 days after corn smut infection (DACSI). Two hybrids were grown in a greenhouse, one fodder (Armagnac) and one a sweet corn (Desszert 73). The relative and the absolute amount of photosynthetic pigments were significantly lower in the infected plants in both hybrids 11 DACSI. Activities of the antioxidant enzymes and MDA content were higher in both infected hybrids. Auxin, cytokinin, and gibberellin application diminished the negative effects of the corn smut infection (CSI) in the sweet corn hybrid. Phytohormones i.e., auxin, gibberellin, and cytokinin can be a new method in protection against corn smut.

As a result of global warming related to the development of industry and agriculture, the proportion of atmospheric carbon dioxide has increased, and temperatures have risen to unprecedented levels. As a result, heat stress, aridity, and salinity in soil has increased, leading to significant research focused on soil deterioration and reduced agricultural productivity. Therefore, it is necessary to provide the means to maintain crop productivity. Agricultural research is seeking novel solutions that guarantee stability and increase the production and quality of crops, including innovative models for feeding crops using non-traditional methods, the most important of which is nourishing plants via their leaves to ensure the cessation of their soil consumption. It is considered an integrated pest-control method, and the technique could be included in plant nutrition. Foliar nutrition has been shown to be a perfect substitute for providing secondary nutrients and micronutrients to plants; however, it cannot be substituted for the fertigation or the fertilization of maintain the soil’s macronutrients (nitrogen, phosphorus, and potassium). This study shed light on the most important research, conclusions, and generalizations on the technique of foliar feeding using organic acids and biological treatments, especially for tomato and pepper plants.

This paper aims to examine the effect of various nitrogen (N) supply treatments on the date of emergence of maize hybrids classified in different age groups. The study site was at the University of Debrecen’s Látókép Experiment Station in Hungary. The date of emergence of the tested maize hybrids was monitored under control (0 kg N ha⁻¹), 120 kg ha⁻¹ N + PK, and 300 kg ha⁻¹ N + PK nutrient levels in a long-term field experiment. In 2020, maize hybrids (H1 = FAO 490; H2: FAO 420–440; H3 = FAO 420; H4 = 490; H5 = 320–340; H6 = FAO 350–370) growing under natural precipitation supply conditions without irrigation were included in the study. During the days of emergence, different moisture, protein, oil, starch, and yield production levels were observed, according to the variance analysis. In diverse maize hybrids, increasing or decreasing fertilizer treatment resulted in diverse productivity metrics. Regression analysis revealed that the day of emergence had a greater impact on protein, moisture, starch, and oil content than N fertilizer; however, yield production was influenced by N fertilization, rather than day of emergence. Regarding productivity parameters, this study suggests that H1 has the best productivity until the fourth day of emergence.

Corn smut fungus (Ustilago maydis [DC.] Corda) is a globally widespread pathogen affecting both forage and sweet maize hybrids, with higher significance in sweet maize. Remote sensing technologies demonstrated favorable results for disease monitoring on the field scale. The study focused on the changes in vegetation index (VI) values influenced by the pathogen. In this study, four hybrids, two forage maize and two sweet maize hybrids were examined. Artificial infection was carried out at three different doses: a low (2500 sporidium number/mL), medium (5000 sporidium number/mL) and high dose (10,000 sporidium number/mL) with a non-infected control plot for each hybrid. The experimental plots were monitored using a multispectral UAV sensor of five monochrome channels on three different dates, i.e., 7, 14 and 21 days after infection. Five different indices (NDVI, GNDVI, ENDVI, LCI, and NDRE) were determined in Quantum GIS 3.20. The obtained results demonstrated that the infection had a significant effect on the VI values in sweet maize hybrids. A high-dose infection in the Dessert R 73 hybrid resulted in significantly lower values compared to the non-infected hybrids in three indices (NDVI, LCI and GNDVI). In the case of the NOA hybrids, GNDVI and ENDVI were able to show significant differences between the values of the infection levels.