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Effect of different N doses on maize yield and quality
Published June 1, 2021
97-101

 The effect of N doses on the yield and nutritional values of the Sushi (FAO 340) maize hybrid were analysed in three years (2018, 2019, and 2020). The analyses were performed at the Látókép Experimental Station of the University of Debrecen on calcareous chernozem soil, in a striped, small-plot, non-irrigated ...long-term field experiment. In the experiment, in addition to the non-fertilized treatment (A0), the N-fertilizer doses were applied as basic fertilizer and top dressing. The 60 and 120 kg N ha-1 dose (A60, A120) applied as spring basic fertilizer were followed by two phases of top-dressing in V6 (V690, V6120) and V12 (V12150, V12180) phenophases; the amounts were +30 and +30 kg N ha-1.

Maize yields were affected to varying degrees by crop year. The highest yields in 2018 and 2020 were recorded in the same V6150 treatment, while in 2019 the highest yield was obtained in the A120 treatment.

Increasing the N doses resulted in an increase in the protein content of the maize kernel. Depending on the fertilizer treatments and the crop year effect, the protein content of maize kernels varied between 6.2–10.2 g x 100 g-1. In all three years, the protein content was the lowest in the control treatment (A0) and the highest in the V6150 treatment.

The starch content ranged from 70.7 to 77.9 g x 100 g-1 in the average of the three years. In 2020, it was significantly higher in all nutrient treatments than in the other examined two years. The highest starch content - except for 2020 (A120, 77.9 g x 100 g-1) - was recorded in the A0 treatment (74.2, 72.3 g x 100 g-1).

The oil content of maize kernels varied between the values of 3.8 and 5.2 g x 100 g-1 in the average of three years. In terms of oil content, the results for 2018 and 2019 can be considered the same, while in 2020 it was significantly lower. Fertilizer treatments did not significantly affect the oil content of maize in any of the years.

The fertilizer dose applied in the V12 phenological phase was not effective in terms of yield and nutritional content (protein, starch and oil content).

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The impact of climatic factors on the relative chlorophyll content and yield of a maize hybrid in a long-term experiment
Published May 23, 2019
71-77

The impact of the climatic factors of crop year on the relative chlorophyll content of maize was examined for three years. The examinations were carried out on the Látókép Experiment Site of the University of Debrecen on calcareous chernozem soil in a small-plot, non-irrigated long-term field experiment with strip plot design. In addition to... a non-fertilised (control) treatment, nitrogen (N) fertiliser doses were applied as base and top dressing. The 60 and 120 kg N ha-1 base dressing doses were followed by two top dressing doses at the V6 and V12 phenophases.

Averaged over the different fertiliser treatments, SPAD readings increased in all three years as the growing season progressed. The highes SPAD value increase was observed in the average crop year (2017) at the V12 phenophase (11.8), which further increased at the R1 phenophas, by 3,7. No significant Spad value difference was observed between the average (2017) and the dry year (2018) at the V6 growth phase. However, in the wet crop year (2016), the V690 treatment provided the statistically highest relative chlorophyll content (46.8). At the V12 phenophase, the base dressing dose of 120 kg N ha-1+30 kg N ha-1 (V6150) showed to be successful in two years (2016 and 2018), while in 2017, the base dressing dose of A60 was successful. The impact of crop year on relative chlorophyll content can be clearly shown at the R1 growth stage. In all three years, the significantly highest relative chlorophyll content could be achieved at different nutrient levels: A60 in 2016, V6150 in 2017 and V690.

In a wet year (2016), higher yield could be achieved as a result of the 60 kg N ha-1 base dressing and 30 kg N ha-1 at the V6 growth stage (V690) as top dressing in comparison with 2017 and 2018, when higher fertiliser dose (120 kg N ha-1 base dressing and 30 kg N ha-1top dressing at the V6 growth stage) was needed to achieve a significant yield surplus.

Altogether, averaged over the different treatments, the highest yield (12.48 t ha-1) was observed in the wet year, when the relative chlorophyll content was also the highest (50.6).

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Examination of drought stress of two genotype maize hybrids with different fertilization
Published May 20, 2020
53-57

In the growing season of 2019, we analysed stress resulting from climatic factors on maize hybrids of different genotypes, with the aim of gaining a better understanding of the physiological responses of each hybrid, which might support the elaboration of a cost-effective irrigation plan.

Our experiments were carried out at... the Látókép Experimental Station of the University of Debrecen on calcareous chernozem soil in a small-plot long-term field trial with strip plot design. In the scope of the experiment, N-fertilizer doses were applied as basic fertilizer and top-dressing in addition to the non-fertilized (control) treatment. The 60 and 120 kg N/ha doses applied as basic fertilizers in the spring were followed by top-dressing in the V6 phenophase with a +30 kg N/ha dose. Measurements were carried out with the involvement of the Renfor early (FAO 320) and Fornad (FAO 420) late maturity hybrids-

The stomata of the plants became more and more closed with the progression of the phenological phases; their stomatal conductance decreased. However, the hybrids responded differently to environmental stress. In the case of the Renfor hybrid, the highest conductance (669 mmol/m2-s) was recorded in the V12 phenophase with the 150 kg N/ha treatment. The stomata were more open due to the high turgor pressure, allowing plants to evaporate properly. The plant was in its worst physiological condition on 2nd July, at the time of the appearance of the last leaf in the case of the 120 kg N dose (224 mmol/m2-s). The value measured in the V12 phenophase has already shown that the stomata were closing due to the self-regulating system of the plant. It would have been necessary to dispense irrigation water following the measurement. This confirms the finding that water stress can be prevented by measuring stomatal conductance.

In the case of the Fornad hybrid, stomatal conductance was the highest on 12th June (630 mmol/m2-s) in the 90 kg N/ha treatment and it was the lowest (183 mmol/m2-s) in VT (emergence of the last leaf) phenophase in the 60 kg N/ha treatment. In this case, the appropriate time for applying irrigation water would have been early July, when the conditions for the plants were still adequate. Subsequently, the stomata began to close due to a reduction of the water resources available to them.

There was a significant correlation between soil moisture and stomatal conductance, as well as between temperature and stomatal conductance.

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Analysis of sweet corn nutritional values using multivariate statistical methods
Published June 1, 2021
103-108

Processing large amounts of data provided by automated analytical equipment requires carefulness. Most mathematical and statistical methods have strict application conditions. Most of these methods are based on eigenvalue calculations and require variables to be correlated in groups. If this condition is not met, the most popular multivaria...te methods cannot be used. The best procedure for such testing is the Kaiser-Meyer-Olkin test for Sampling Adequacy. Two databases were examined using the KMO test. One of them resulted from the sweet corn measured in the scone of the study, while the other from the 1979 book of János Sváb. For both databases, MSA (measures sampling adequacy) was well below the critical value, thus they are not suitable e.g. for principal component analysis. In both databases, the values of the partial correlation coefficients were much higher than Pearson’s correlation coefficients. Often the signs of partial coefficients did not match the signs of linear correlation coefficients. One of the main reasons for this is that the correlation between the variables is non-linear. Another reason is that control variables have a non-linear effect on a given variable. In such cases, classical methods should be disregarded and expert models better suited to the problem should be chosen in order to analyse the correlation system.

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