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Article

Evaluation of the Effect of Conventional and Stabilized Nitrogen Fertilizers on the Nutritional Status of Several Maize Cultivars (Zea mays L.) in Critical Growth Stages Using Plant Analysis

by
Piotr Szulc
1,*,
Daniel Krauklis
2,
Katarzyna Ambroży-Deręgowska
3,
Barbara Wróbel
4,
Waldemar Zielewicz
5,
Gniewko Niedbała
6,
Przemysław Kardasz
7 and
Mohsen Niazian
8
1
Department of Agronomy, Poznań University of Life Sciences, Dojazd 11, 60-632 Poznań, Poland
2
Experimental Station for the Cultivar Testing in Chrząstowo, Research Centre for Cultivar Testing in Słupia Wielka, Chrząstowo 8, 89-100 Nakło nad Notecią, Poland
3
Department of Mathematical and Statistical Methods, Poznań University of Life Sciences, Wojska Polskiego 28, 60-637 Poznań, Poland
4
Institute of Technology and Life Sciences—National Research Institute, 3 Hrabska Avenue, 05-090 Raszyn, Poland
5
Department of Grassland and Natural Landscape Sciences, Poznań University of Life Sciences, Dojazd 11, 60-632 Poznan, Poland
6
Department of Biosystems Engineering, Faculty of Environmental and Mechanical Engineering, Poznań University of Life Sciences, Wojska Polskiego 50, 60-627 Poznań, Poland
7
Field Experimental Station in Winna Góra, Institute of Plant Protection-National Research Institute Winna Góra 13, 63-013 Szlachcin, Poland
8
Field and Horticultural Crops Research Department, Kurdistan Agricultural and Natural Resources Research and Education Center, Agricultural Research, Education and Extension Organization (AREEO), Sanandaj 6616936311, Iran
*
Author to whom correspondence should be addressed.
Agronomy 2023, 13(2), 480; https://doi.org/10.3390/agronomy13020480
Submission received: 13 January 2023 / Revised: 2 February 2023 / Accepted: 3 February 2023 / Published: 6 February 2023

Abstract

:
The study presents the results of a three year field trial aimed at assessing the nutritional status of maize in critical growth stages by means of a plant analysis in the cultivation of three maize cultivars differing in their agronomic and genetic profile. The main research problem was to demonstrate whether the availability of nitrogen from stabilized fertilizers for “stay-green” maize varieties is consistent with the dynamics of the demand for this component. This is very important from both the economic and agronomic aspect of maize cultivation. The research showed a significant response of the maize cultivars to different nitrogen fertilizer formulations, which was observed in the period from the five-leaf stage to the full flowering stage. The advantage of the fertilizer, UltraGran stabilo, over other nitrogen fertilizers in the BBCH 15 stage was demonstrated only for the cultivar, ES Metronom, which produced a greater aerial mass while maintaining the nitrogen concentration at the level of the other two maize cultivars. The nitrogen and potassium content shaped the kernel weight in the ear in the flowering stage, confirming the importance of the interaction of these two elements in forming this feature of maize as the main predictor of the grain yield. This trait (expressed by the R2 coefficient) manifested each year of the study, but especially in the years with optimal weather patterns (i.e., the first year). The response of the maize cultivars to nitrogen fertilizers, especially the cultivar, ES Metronom, was manifested by an increase in the content of nutrients and chlorophyll in the ear leaf, that is considered a predictive organ for grain yield. The fertilizers, Super N-46 and UltraGran stabilo, had a positive effect on the chlorophyll content (CCI parameter) and increased its efficiency of excitation energy transfer (the F0 parameter).

1. Introduction

Food security is a global challenge due to the threat of climate change, and it is an arduous task to feed the growing population [1,2,3]. Therefore, optimizing fertilizers is an imperative way to reduce the misuse of farm inputs and increase farm sustainability [4,5]. Optimized fertilization is a very important aspect in maize cultivation, as it affects the yield size and structure [6]. Maize (Zea mays L.) is a fast-growing plant, with high requirements for essential nutrients, whose lack can slow down its growth and reduce the yields. Intensive agricultural activities (e.g., tillage, non-compliance or poorly chosen crop rotation, and soil structure damage) reduce the nitrogen content in the topsoil, especially during dry weather [7,8]. Nitrogen deficiencies in the soil are compensated for by natural, organic and mineral fertilizer applications. The selection of a fertilizer that does not match the specificity of the cultivated plant, however, causes nitrogen accumulation in the soil, which can lead to undesirable environmental consequences [7,9].
Stabilized fertilizers, i.e., those that contain nitrification or urease inhibitors, are of increasing practical importance in plant fertilization [10]. The main advantages of their use is an increased efficiency of plant fertilization with nitrogen by reducing the number of applications, and they have a wider range of application dates, as well as resulting in improved environmental conditions by reducing the risk of excess nitrogen release into the groundwater and emissions into the atmosphere [11]. High N2O emissions from maize crops result from the differences between the date of a nitrogen fertilizer application and the actual nitrogen requirements of the plants, because fertilizers are applied long before rapid plant growth [12,13]. The search is ongoing for an easily available substance that would be able to inhibit the nitrification process in the soil for a long period of time, without exerting a negative impact on the biological environment and plant yield. For example, some compounds added to nitrogen fertilizers may decrease the ammonium to nitrate conversion rate, and this can help reduce nitrogen losses through the nitrification process. Nitrification inhibitors are compounds that delay the conversion of NH4 to NO3 by suppressing the activity of bacteria of the genus Nitrosomonas. There are at least eight compounds commercially recognized as nitrification inhibitors, and the most well-known and commonly applied are 2-chloro-6-(trichloromethyl)-pyridine (Nitrapyrin), dicyclodiamide (DCD) and 3,4-dimethylpyrazole phosphate (DMPP) (Figure 1). These compounds inhibit microbial activity for several days to weeks, depending on the soil moisture and type. Nitrification inhibitors are more effective on sandy soils or soils poor in organic matter.
Thus far, most studies on the use of nitrogen fertilizers containing nitrification inhibitors have demonstrated that their application, compared to traditional mineral nitrogen or organic fertilizers, reduced the nitrogen losses. This results in an increased availability of nitrogen, and thus, improved plant growth [15]. The presence of amide (urea), amide and ammonium (RSM) and ammonium (ammonium nitrate) forms in nitrogen fertilizer promotes ammonia release. Hydrolysis carried out by the urease enzyme is responsible for the process of ammonia volatilization in the amide form. In the case of the ammonium form, the soil physicochemical properties, including its sorption capacity for exchangeable cations, acidity and soil moisture are mainly responsible for ammonia oxidation. Slowing the release of ammonia from amide fertilizers during the first week after their application can be obtained by using substances that reduce the enzymatic activity of urease known as urease inhibitors. Among the many chemical compounds referred to as inhibitors, only a few meet the strict criteria of non-toxicity in relation to soil organisms and are easily biodegradable after several days of their application (EU Commission Regulation). The popularity of urea is due to its high nitrogen concentration (46%), wide availability, high solubility and compatibility with most fertilizers [10,16]. The disadvantage of urea is that it is highly susceptible to losses caused by ammonia denitrification and oxidation [17]. It is estimated that the loss of nitrogen from soils due to oxidation may reach, according to Bundy [18]—20%, and Watson [19]—up to 47%, while Cantarella et al. [20] estimated these losses at 15–60%. Thousands of chemical compounds are known to act as urease inhibitors in soil [21]. Of these, only a small number of tested chemical compounds meet the necessary requirements, i.e., non-toxicity, effectiveness at low concentrations, and stability, as well as compatibility with urea (both solid and in solution) and degradability in soil [19]. The best known and characterized urease inhibitors are N-(n-butyl) thiophosphoric triamide (NBPT), phenylphosphorodiamide (PPD/PPDA) and hydroquinone [21]. Studies were also carried out on N-(2-nitrophenyl) triamide of phosphoric acid (2-NPT) and ammonium thiosulfate (ATS). Organophosphorus compounds are structural analogs of urea and one of the most effective inhibitors of urease activity, acting by blocking the active sites of the enzyme [19]. Studies have shown that NBPT reduces NH3 losses by 52–54% compared to conventional urea [22,23]. High temperatures, a higher humidity and the presence of straw in the soil may accelerate an inhibitor’s degradation, thereby decreasing its effectiveness in reducing nitrogen losses [24,25]. Soil pH is another factor affecting the effectiveness of NBPT. According to Soares [26], the NBPT inhibitor reduced nitrogen losses by 52–53% in soils with a pH of 5.6 and 6.4, while its efficacy was lower in soils with a pH of 4.5, amounting to only 18%. According to Watson et al. [27], the reduction of ammonia oxidation due to urease as a result of NBPT application can range from 55% to over 90%. Meanwhile, the highest effectiveness in reducing ammonia volatilization was observed in soils with a high pH and low buffer capacity.
On the basis of the current knowledge concerning the response of maize to the application of nitrogen fertilizers, the working hypothesis of the study was formulated as follows: classical and stabilized nitrogen fertilizers would affect the dynamics of initial growth, chlorophyll fluorescence and the nutritional status of maize plants in critical growth stages, as determined by the plant analysis method. In addition, the study determined the dependence of the maize grain yield on the content of N, P, K, Mg and Ca in maize ear leaves at the BBCH 65 stage.

2. Materials and Methods

2.1. Experimental Field

The field experiment was carried out in the years 2017–2019 on the fields of the Experimental Station for the Cultivar Testing in Chrząstowo, belonging to the Research Centre for Cultivar Testing in Słupia Wielka. It was carried out for 3 years in the same random block design (split-plot) with 2 experimental factors in 3 field replicates. The following factors were studied: A—1st order factor-maize cultivar: A1—ES Bombastic (FAO 230-240)-single cross hybrid (SC), A2—ES Abakus (FAO 230-240)-three-way cross hybrid (TC, “stay-green”), and A3—ES Metronom (FAO 240)-single hybrid (SC, “stay-green” + roots power). B—2nd order factor-type of nitrogen fertilizer: B1—control (without N application), B2—ammonium nitrate, B3-urea, B4—ammonium nitrate + N-Lock, B5—urea + N-Lock, B6—Super N-46, and B7—UltraGran stabilo. The same level of mineral fertilization was applied in all experimental plots in the amount of 150 kg N ha−1, 120 kg P2O5 ha−1 and 130 kg K2O ha−1. Nitrogen fertilization was not applied in the control combination (B1). Nitrogen fertilizers were applied as a broadcast fertilization, directly before the maize sowing. After application, they were mixed with the soil. In combinations with standard nitrogen fertilizers (i.e., B4 and B5), an N-Lock nitrogen stabilizer was applied as a spray on day 5 after sowing the nitrogen fertilizer at a rate of 1.7 L ha−1. It contained 200 g of nitrapyrin in the form of a microcapsule suspension and was designed to slow down the nitrification process. Fertilization with P and K was carried out before the maize sowing at 2 dates: in the autumn, of the previous year (under winter plowing) and in the spring immediately before sowing the maize (before the combined seed drill). At the first date, the compound fertilizer Lubofos 12 (P2O5-12%, K2O-20%) was applied, containing 36 kg·ha−1 P2O5 and 60 kg·ha−1 K2O. The remaining dose of P and K was supplemented before the maize sowing in the form of enriched superphosphate (40% P2O5)-84 kg·ha−1 and potassium salt (60% K2O)-70 kg·ha−1. The maize was sown with a precision seeder. The assumed planting density in the study years was 8.3 pcs/m−2 (83,000 grain·ha−1), with a spacing between the rows of 75 cm and a sowing depth of 5–6 cm. The gross plot size was 24 m2 (in 4 rows, with a length: 8 m, and width: 3 m). The net plot area for the observations and measurements was 12 m2. Two middle rows from each experimental plot were used for the observations, measurements and harvesting.

2.2. Soil Conditions

According to the WRB taxonomy, the analyzed soils of the experimental field were classified as: Albic Abruptic Luvisol (i.e., Anoarenic, Aric, Cutanic, Endoloamic, and Ochric). The analyzed soils belonged to the IVa quality class, which is a very good rye complex. In terms of the grain size, the top horizons of the analyzed soils were classified as loamy sands, and the content of the loam fraction was 4%, dust 14% and sand fraction 83%. The eluvial horizon contained slightly less loam and dust fractions. The enrichment (B) and bedrock levels were definitely more compact. The pH determined in the water extract expressed in pH units was about 7.0, while in KCl it was about 0.5 units lower and was in the upper values of the slightly acidic range. The organic carbon content was approx. 1%, which gave 1.7% humus. The total nitrogen content was 0.086%, and the C:N ratio was about 12:1 (Table 1). The content of the assimilable potassium forms was 80.5 mg K kg−1, which qualified these soils to the average enrichment class of this element. The amount of assimilable phosphorus and magnesium placed the studied soils in a very high abundance class, as the content of these components was: 168.2 mg of P kg−1, and 92.5 mg of Mg kg−1, respectively.
The sorption capacity was quite high and amounted to approx. 8 cmol(+) kg−1, and the sorption complex was characterized by a very high saturation with alkaline cations–almost 90% (Table 2). Among the cations, calcium was predominant in the sorption complex, with a proportion of more than 75%, while the other elements occurred in much smaller amounts: Mg—8.5%, K—2.7% and Na—approx. 1%.
The content of water-soluble components and electrical conductivity in the 1:5 extract are summarized in Table 3. Among the components analyzed, calcium was predominant, and the electrical conductivity was at a relatively low level, indicating a lack of salinity.
Table 4 presents the total composition of samples collected from the upper levels of the analyzed experimental plots. The obtained results allowed the classification of the analyzed soil to the so-called “0” degree of contamination, i.e., the natural content of heavy metals, i.e., on these soils any agricultural/horticultural plants can be grown.

2.3. Thermal and Moisture Conditions

In the three-year period of 2017–2019, the lowest average daily temperature during the growing season was recorded in 2017 (13.8 °C) (Table 5), where lower average temperatures were recorded in all months than in 2018 and in the 2007–2019 period (except for May and October). The highest average daily temperature during the growing season was recorded in 2018 and was 2.7 °C higher than in 2017. The highest average daily temperatures in the study years were recorded in 2018 in July (20.1 °C) and August (20.9 °C) and in 2019 in June (21.7 °C) and August (20.6 °C). Total precipitation, from April to October 2017 was 617 mm, and it was the highest in the study years, and also 242 mm higher than in the 2007–2019 multi-year period (Table 5). The highest amount of precipitation was recorded in July (134 mm) and August (143 mm). The lowest precipitation, both in comparison to 2017 and the multi-year period (2007–2019), was recorded in 2018 (290 mm) and 2019 (277 mm). In 2018, the lowest rainfall during the growing season was recorded in May (5 mm) and August (14 mm), and the highest in July (120 mm). In 2019, the lowest precipitation was recorded in April (monthly sum—3 mm), June (18 mm) and July during the flowering of the maize plants (25 mm), respectively. The highest monthly precipitation totals were recorded in May and September during the 2019 growing season.

2.4. Observations and Measurements

2.4.1. Determination of Dry Matter Accumulation Dynamics during the Early Maize Growing Season

  • Single plant dry matter at the 5–6 leaf stage (BBCH 15/16)
Six plants from each plot were collected for analysis using a spade. The root was separated from the aerial plant part. After drying, the dry weight of one plant was determined;
  • Determination of dry matter content at the 5–6 leaf stage (BBCH 15/16)
The determination of the dry matter content in the maize plants was carried out knowing the fresh and dry weight of the collected plants;
  • Plant dry matter yield at the 5–6 leaf stage (BBCH 15/16)
The dry matter yield of the plants at this stage of the maize development was determined knowing the dry weight of a single plant and the number of plants after emergence.

2.4.2. N Content in Plants dm at the 5–6 Leaf Stage (BBCH 15/16)

The mineral contents in the plants’ dry matter were analyzed in the laboratory of the Agronomy Department of the Poznań University of Life Sciences.

2.4.3. N, P, K, Mg and Ca Contents in Leaf Dry Matter at the Tassel Flowering Stage (BBCH 65)

The analysis of the mineral contents in the dry matter of the plants (leaves) was performed in the laboratory of the Agronomy Department of the Poznań University of Life Sciences. In addition, the potassium and calcium were determined using a “Flap 40” flame spectrophotometer, and the phosphorus and magnesium using a “Specol 11” colorimeter.

2.4.4. Chlorophyll Fluorescence Measurements (BBCH 65)

The chlorophyll fluorescence measurements of the maize plants were carried out over two years (2018, 2019) at the tassel flowering stage (BBCH 65) in three field replicates and four biological replicates. Before the measurements, PAR clips were placed on four selected plants from each plot 20 min before the measurement to suppress photosynthesis and adapt the plants to darkness. The measurement for each plant was made on the ear leaf. Fluorescence measurements were performed using an OS5p fluorometer (OPTISCIENCES.INC., Hudson, USA – New Hampshire). The Fv/Fm protocol was selected, which allowed for measuring the following parameters: F0—initial fluorescence, Fm—maximum fluorescence, Fv—variable fluorescence, Fv/Fm—maximum photochemical efficiency of PSII. Similarly, the relative leaf chlorophyll content (CCI) was measured with a 200 plus relative chlorophyll content meter (OPTI-SCIENCES CCM) on the same leaf, using the same order and number of measurements.

2.5. Statistical Analysis

Statistical analyses, such as an analysis of variance (ANOVA) and the Tukey HSD (honestly significant difference) test for pairwise comparisons of means were conducted separately during the years of the study and in 2017–2019, according to the experimental data models designed as a split-plot experiment. In addition, correlation coefficients were used to measure the strength of the statistical relationships between the maize grain yield and the content of one of the elements: nitrogen, phosphorus, potassium, magnesium and calcium in maize leaf blades at the BBCH 65 stage. If the correlation coefficient was significant, the linear regression equation and the coefficient of determination were determined. The regression equations were estimated by the method of least squares. All the calculations were performed using Statistica 13.3 (2017) and MS Excel. The statistical significance was set at a p-value < 0.05.

3. Results

3.1. Dynamics of the Initial Growth of Maize Expressed by Dry Matter Accumulation at the BBCH 15/16 Stage

Significantly, the highest single plant dry weight and dry matter yield were shown to be the cultivars ES Bombastic and ES Metronom, respectively, when compared to the ES Abakus hybrid (Table 6). Analyzing the dry matter content at the discussed maize developmental stage, it was found that the cultivar ES Metronom was characterized by the lowest parameter of the evaluated trait compared to the other two tested maize cultivars (Table 6). Significantly, the highest dry weight of a single plant was found after the application of the following nitrogen fertilizers: B3, B4, B5 and B6 in relation to the control object, namely, B1. Significantly, the highest yield of dry matter was obtained after the application of fertilizers B3–B7 compared to the control object B1 (Table 6). Our study also revealed the interaction of the cultivar with the type of nitrogen fertilizer in shaping the dry weight of a single plant, dry matter yield and dry matter content of maize at the BBCH 15/16 stage (Table 7). None of the nitrogen fertilizers that were tested significantly differentiated the single plant dry weight and dry matter yield for the cultivars ES Bombastic and ES Abakus. For the ES Metronom hybrid, significantly, the highest dry weight of a single plant was found for urea (B3), while the lowest was for the control object (B1). In the case of the dry matter yield, none of the tested nitrogen fertilizers significantly differentiated the value of this feature for the cultivars ES Bombastic and ES Abakus. On the other hand, the lowest yield of dry matter for the cultivar ES Metronom was recorded on the control object B1, while the highest was for the fertilizers B3–B7 (Table 7). In the present study, significantly, the highest content of dry matter was recorded for the cultivar ES Bombastic fertilized with urea + N-Lock (18.13%), and the lowest was for the ES Metronom hybrid fertilized with ammonium nitrate (14.79%) (Table 7).

3.2. Macronutrient Contents

In the present study, none of the experimental factors significantly differentiated the nitrogen content in the dry matter of maize plants at the 7–8 leaf stage (BBCH 15/16) (Table 8). Only the calcium content in the maize leaves in the BBCH 65 stage was significantly dependent on the type of maize hybrid. Significantly, the lowest Ca content in maize leaf blades was found for the cultivar ES Bombastic, while the highest for the cultivar ES Metronom (Table 8). Significantly, the highest content of nitrogen and phosphorus in maize leaf blades at the BBCH 65 stage was recorded after the application of the nitrogen fertilizer UltraGran stabilo (B7), and the lowest was for the control plot (B1). For potassium, its significantly highest content in maize leaves at the BBCH 65 stage was observed after the application of nitrogen fertilizers (B3–B7), and the lowest was for the control object (B1). For magnesium, its lowest content in maize leaves at the BBCH 65 stage was found on the control object (B1), and, significantly, the highest was found after the application of ammonium nitrate (B2). Significantly, the lowest content of calcium in leaf blades in the BBCH 65 stage was found in maize after the application of ammonium nitrate (B2) and urea + N-Lock (B5), while the highest was for the remaining nitrogen fertilizers tested (i.e., B1, B3, B4, B6, and B7) (Table 8).

3.3. Parameters of Chlorophyll Fluorescence and Relative Chlorophyll Content

Significant differences were found in the chlorophyll content of the maize leaves between years, and there was a significant effect of both the cultivar and type of nitrogen fertilizer on the content of photosynthetic pigments (Table 9). A significantly higher chlorophyll content in the maize leaves was recorded in 2018. Significantly, the highest chlorophyll content was determined in the leaves of the cultivar ES Metronome. Of the tested nitrogen fertilizers, UltraGran stabilo (B7), Super N-46 (B6) and urea + N-Lock (B5) significantly exerted the most favorable effect on the chlorophyll content (i.e., they were higher by 48, 36 and 29%, respectively, compared to the control). The maize on the control plot (B1) developed the lowest amount of chlorophyll. Of all the measured fluorescence parameters, significant differences were recorded only for the initial fluorescence (F0). After a plant’s adaptation to darkness, the initial fluorescence is an indicator of the excitation energy loss during its transfer from the antenna complexes to the PSII reaction center. Similarly to the CCI parameter, the initial fluorescence differed significantly between the years and its more favorable values were recorded in 2018. Significant differences in the F0 were also found between the applied nitrogen fertilizers (Table 9). Significantly, the highest values of the F0 parameter were found in maize fertilized with the fertilizers B1 and B2, while significantly, the lowest values were obtained for the fertilizers B6 and B7. The increase in the initial fluorescence was associated with a higher chlorophyll fluorescence resulting from stress, which adversely affected the quantity or quality of the photosynthetic pigments, mainly chlorophyll, and, therefore, it could be concluded that the fertilizers B6 (Super N-46) and B7 (UltraGran stabilo) had a positive effect on the chlorophyll levels (parameter CCI) and increased its efficiency of the excitation energy transfer (parameter F0) (Table 9). The present research also showed the interaction of the cultivar with the type of nitrogen fertilizer in shaping the Fv/m value (Figure 2). It was shown that for cultivar A3, the highest values of the discussed feature were recorded for the fertilizers B6 and B7, while the lowest value was for the cultivar A1 fertilized with ammonium nitrate nitrogen fertilizer (B2).

3.4. Dependence of Maize Grain Yield on the Content of N, P, K, Mg and Ca in Maize Ear Leaves at the BBCH 65 Stage

The study investigated whether there was a linear relationship between the maize grain yield and content of one of the elements: nitrogen, phosphorus, potassium, magnesium and calcium in maize leaf blades at the BBCH 65 stage. Regardless of the tested factors of the experiment, in 2017 the grain yield was 9.73 t·ha−1, and in 2018 it was 7.77 t·ha−1, while in the last year of the research it was 5.71 t·ha−1. In 2017, 2018 and for all the observations obtained in 2017–2019, it was shown that there was a positive linear relationship between the grain yield and nitrogen content in maize leaf blades in the BBCH 65 stage (Table 10); thus, the higher the nitrogen content in maize leaf blades in the BBCH 65 stage, the higher the grain yield. In 2017, the nitrogen content affected the grain yield in over 36%, and in almost 29% in 2018. It was found that increasing the nitrogen content in maize leaf blades at the BBCH 65 stage by one unit increased the average grain yield in 2017 by 0.231 (t·ha−1) and by 0.2 in 2018 (t·ha−1). For each study year and for all the observations obtained in 2017–2019, positive linear relationships were obtained between the grain yield and phosphorus content in maize leaf blades in the BBCH 65 stage (Table 11); thus, the higher the phosphorus content in maize leaf blades in the BBCH 65 stage, the higher the grain yield. In 2017, the phosphorus content had an impact on the grain yield in over 40%, over 42% in 2018, and almost 44% in 2019. It was found that increasing the phosphorus content in maize leaf blades at the BBCH 65 stage by one unit increased the average grain yield in 2017 by 1.688 (t·ha−1), by 1.277 in 2018 (t·ha−1), and by 0.682 (t·ha−1) in 2019. Positive linear relationships between the grain yield and potassium content in maize leaf blades were observed in the BBCH 65 stage in each study year (Table 12); thus, the higher the potassium content in maize leaf blades in the BBCH 65 stage, the higher the grain yield. The resulting linear regression model showed a 53.08% fit to the data in 2017, a 26.07% fit in 2018, and a 34.66% fit in 2019. It was found that increasing the potassium content in maize leaf blades at the BBCH 65 stage by one unit increased the average grain yield in 2017 by 0.22 (t·ha−1), by 0.222 in 2018 (t·ha−1), and by 0.192 (t·ha−1) in 2019. Positive linear relationships between the grain yield and magnesium content in maize leaf blades in the BBCH 65 stage were found in 2017 and 2018 (Table 13). In those years, the increase in magnesium content in maize leaf blades at the BBCH 65 stage resulted in a higher grain yield. When the magnesium content in the leaf blades at the BBCH 65 stage increased by one unit, the grain yield was higher in 2017 by 1.565 (t·ha−1), and by 0.919 in 2018 (t·ha−1). In 2017, the magnesium content affected the grain yield in over 37%, and in almost 32% in 2018. In addition, a significant positive correlation was found between the grain yield and calcium content in maize leaf blades at the BBCH 65 stage only when all the observations obtained in 2017–2019 were analyzed jointly (Table 14); thus, the higher the calcium content in maize leaf blades in the BBCH 65 stage, the higher the grain yield. The resulting linear regression equation showed a 16.71% fit to the data (R2 = 16.71%). When the calcium content in the leaf blades at the BBCH 65 stage increased by one unit, the grain yield was higher by 1.058 (t·ha−1).

4. Discussion

A growth analysis based on the dynamics of dry matter accumulation is a useful method of determining the most sensitive stages of the maize response to external (stress) factors, including the content of available nitrogen and other nutrients. It should be noted that maize is very sensitive to nutrient deficiency, especially in the early growth stages [29,30]. Therefore, determining the optimal level of nitrogen fertilization, which guarantees the utilization of the maize production potential, is one of the most important agriculture issues in the cultivation of this plant. The malnutrition of maize plants with nitrogen in the early growing season impairs the formation of leaves, ears and ear structure elements.
These effects of nitrogen deficiency become apparent very early, and are already apparent in the eight-leaf stage. According to Subedi and Ma [31], plant nitrogen malnutrition before this stage leads to an irreversible reduction in the number of ears and set kernels even up to about 30%. In our study, a significantly higher single plant dry weight and dry matter yield at the BBCH 15/16 stage were found in the cultivars ES Bombastic and ES Metronom compared to the cultivar ES Abakus. The cultivar ES Metronom had the highest value of the discussed trait, and the difference compared with the cultivar ES Abacus was 0.97 g in the dry weight per plant and 81.72 kg·ha−1 in the dry matter yield. Szulc et al. [32] have shown that the “stay-green” maize cultivar is distinguished by a greater vigor of initial growth compared to the traditional hybrid. Of the three cultivars studied, the smallest dry weight of a single plant, as well as the lowest dry matter yield, was recorded for the cultivar ES Abakus (i.e., stay-green). It is a three-way cross hybrid (TC), which in our study was characterized by a weaker initial plant growth and significantly lower uniformity. In addition, the cultivar ES Metronom is a strictly selected genotype in the “roots power” technology. Traditional hybrids have a poorly developed germinal root system that can supply plants with minerals only if their concentration in the soil solution is sufficiently high [33]. In addition, temperatures in the range of 5–12 °C impair the activity of young roots with respect to ion absorption, especially phosphorus and generally all nitrogen ions [34].
The cultivar in the “roots power” technology is characterized by a higher and faster development of the root system. In this study, despite the lowest dry matter content, the ES Metronom hybrid achieved the highest dry matter yield at the BBCH 15/16 stage, which proved that this variety showed the highest initial dynamics of dry matter accumulation. Elsewhere, the initial growth of maize was better in the presence of ammonium nitrogen or ammonium and nitrate combined than in the presence of nitrate nitrogen or urea alone [35,36], but our results did not confirm this statement. A significant difference was recorded between the combinations with urea, ammonium nitrate and urea with N-Lock and Super N-46, and the combination without a nitrogen fertilizer. The main reason for such a small variation in the response to applied nitrogen fertilizers can be attributed to the weather patterns. Low daily temperatures, as well as ground frost during the initial growth of the maize plants in 2017, extreme drought in May 2018 (with a total precipitation: 5 mm) and high temperatures additionally intensifying the drought effect (with a hydrothermal coefficient: 0.1), as well as ground frost and extreme drought in April 2019 (with a monthly rainfall: 3 mm; hydrothermal coefficient: 0.1), did not allow for the optimal uptake of nitrogen from the fertilizers. This was also confirmed by the lack of a significant difference in the nitrogen content in the maize plants in the juvenile phase, both in terms of the cultivar and nitrogen fertilizers applied. According to Grant et al. [37], urease inhibitors delay the hydrolysis of urea in the soil, thereby reducing high ammonia concentrations that negatively affect germinating seeds. These authors observed a decrease in the seed damage caused by a NBPT addition to urea compared to a conventional fertilizer, which increased the plant density and yielding of barley. On the other hand, Qi et al. [38] showed that adding NBPT to urea reduced the damage to germinating seeds and increased rice root growth. Cruchaga et al. [39] reported that NBPT can be absorbed by plants and can alter part of the metabolic pathway responsible for reducing urease activity and glutamine synthesis activity, both of which are associated with nitrogen assimilation. Therefore, it may cause a temporary yellowing of the leaf blade tips due to urea toxicity shortly after application; however, the plants usually recover quickly and there is no negative impact on the plant growth and development, or consequently, the yield [40]. Water and a lack of mineral component balance in relation to the plants’ nutritional needs are the most frequent factors limiting the size of potential yields [29,41].
Failure to adjust the fertilization system to quantitative needs, especially the dynamics of mineral component uptake by plants growing in a field, is the cause of disorders in the functioning of individual nutrients, their low utilization by the plant and an increased risk of environmental pollution [42]. The value of fluorescence in stress-free conditions is only 3–5%; however, as a result of various types of stress, the balance between the supply of assimilation power (ATP and NADPH) produced in photochemical reactions and the reduced demand for these products in the enzymatic reactions of the Calvin–Benson cycle is disturbed [43]. The resulting situation forces the plant to use various processes to dissipate the excess energy absorbed by chlorophyll, and increased fluorescence is one of them. In our study, we found significant differences in the chlorophyll content of the maize leaves across the years of the study, as well as a significant effect of both the cultivar and type of nitrogen fertilizer on the content of these photosynthetic pigments. Significantly higher chlorophyll content in the maize leaves was recorded in 2018. Significantly, the highest chlorophyll content was determined in the leaves of the cultivar ES Metronome. Of the tested nitrogen fertilizers, the UltraGran stabilo (B7), Super N-46 (B6) and urea + N-Lock (B5) fertilizers significantly had the most beneficial effect on the chlorophyll content (being higher by 48, 36 and 29%, respectively, compared to the control). Maize on the control plot (B1) developed the lowest amount of chlorophyll. Of all the measured fluorescence parameters, significant differences were recorded only for the initial fluorescence (F0). The initial fluorescence after a plant’s adaptation to darkness is an indicator of the excitation energy loss during its transfer from the antenna complexes to the PSII reaction center [38]. Similarly to the CCI parameter, the initial fluorescence differed significantly between the years and its more favorable values were observed in 2018. Significant F0 differences were also demonstrated between the applied nitrogen fertilizers. Significantly, the highest values of the F0 parameter were found in maize fertilized with the fertilizers B1 (control object) and B2 (ammonium nitrate), while the significantly lowest values were found for the fertilizers B6 (Super N-46) and B7 (UltraGran stabilo). The increase in initial fluorescence was associated with a higher chlorophyll fluorescence resulting from stress, which adversely affected the quantity or quality of the photosynthetic pigments, mainly chlorophyll; therefore, it can be concluded that the nitrogen fertilizers with an inhibitor (i.e., B6 and B7) had a positive effect on the chlorophyll content (CCI parameter) and increased its efficiency of the excitation energy transfer (F0 parameter).
Plant growth analysis can provide much needed information about the agriculture system, especially about the content and ratios of elements in plants, which can serve as the basis for the development of fertilization recommendations. According to Szczepaniak et al. [44], the ear leaf is a part of the plant that is useful for the development of both the nutritional status indices of maize plants and the grain yield predictions. In the present study, the content of nitrogen, phosphorus, potassium, magnesium and calcium were determined in maize leaf blades at the BBCH 65 stage to determine whether there was a linear relationship between the maize grain yield and the content of one of these elements. It was shown that for each analyzed element, its increase resulted in a higher maize grain yield; thus, in order to obtain the assumed grain yield, one should aim to increase the content of the components in the plant above the critical value and maintain a defined balance of mineral components in the plant [29,45]. It is noteworthy that in the year with the lowest total precipitation (277 mm), the nitrogen and magnesium content in maize leaves at the BBCH 65 stage had no significant effect on the grain yield (Table 11 and Table 14). It was shown that under rainfall deficit conditions (i.e., July—maize flowering), only the phosphorus and potassium content, measured in maize leaves at the BBCH 65 stage, determined the grain yield in more than 43 and 34%, respectively. Hence, optimal potassium nutrition is a prerequisite for the effective control of water balance by the plant. Throughout the growing season, potassium controls the degree of opening of the stomata, thereby regulating the turgor of the plant cells, i.e., the water evaporation from plant tissues. A large amount of available potassium allows the plant to quickly close and open the stomata during periods of temperature increase, with a simultaneous water deficit in the daily cycle, thereby reducing the water losses [46]. Periodic water shortages force the plant to expand its root system, and thus change the direction of nutrient transport between the organs. This transport can only occur when the plant is able to accumulate large amounts of potassium ions in the phloem. Therefore, plants that are well supplied with K+ can develop roots deeper into the soil profile, and thus increase the uptake of nutrients and water [46].

5. Conclusions

The significant response of the studied maize cultivars to the different nitrogen fertilizer formulations was observed in the period from the five-leaf stage to the full flowering stage. The advantage of the fertilizer, UltraGran stabilo, over other nitrogen fertilizers in the BBCH 15 stage was demonstrated only for the cultivar ES Metrononom, which produced a greater aerial mass, while maintaining the nitrogen concentration at the level of the other two maize cultivars. The content of nitrogen and potassium in the flowering stage shaped the kernel weight in the ear, confirming the importance of the interaction of these two elements in forming this feature of maize as the main predictor of the grain yield. This trait (expressed by the R2 coefficient) manifested each year of the study, but especially in the years with the optimal weather patterns (i.e., the first year of the study). The response of the maize cultivars to the nitrogen fertilizers, especially the cultivar ES Metronom, was manifested by an increase in the content of nutrients and chlorophyll in the ear leaf, that is considered a predictive organ for the grain yield. The fertilizers, Super N-46 and UltraGran stabilo, had a positive effect on the chlorophyll content (CCI parameter) and increased its efficiency of the excitation energy transfer (F0 parameter). The differences between the “stay-green” cultivar and the classic cultivar began to appear already in the early growing season, which allowed for the effective control and correction of the plants’ nutritional status. The condition for using the biological progress represented by the “stay-green” maize cultivar is the simultaneous recognition of the yield physiology aspects, and the development of plant nutrition on this basis.

Author Contributions

Conceptualization, P.S and D.K.; methodology, P.S., D.K. and K.A.-D.; software, P.S., B.W., P.K. and D.K.; validation, P.S., D.K., M.N., G.N. and W.Z.; formal analysis, K.A.-D., P.S. and D.K.; investigation, D.K. and P.S.; resources, M.N., P.K., G.N., W.Z. and B.W.; data curation, K.A.-D. and B.W.; writing—original draft preparation, D.K.; writing—review and editing, P.S. and D.K.; visualization, G.N., W.Z., M.N., K.A.-D. and B.W.; supervision, P.S. and D.K.; project administration, K.A.-D. and D.K.; funding acquisition, P.S. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by Poznań University of Life Sciences, Department of Agronomy.

Data Availability Statement

Available upon reasonable request.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Elahi, E.; Khalid, Z.; Zubair Tauni, M.; Zhang, H.; Lirong, X. Extreme weather events risk to crop-production and the adaptation of innovative management strategies to mitigate the risk: A retrospective survey of rural Punjab, Pakistan. Technovation 2022, 117, 102255. [Google Scholar] [CrossRef]
  2. Elahi, E.; Khalid, Z. Estimating smart energy inputs packages using hybrid optimization technique to mitigate environmental emissions of commercial fish farms. Appl. Energy 2022, 326, 119602. [Google Scholar] [CrossRef]
  3. Elahi, E.; Khalid, Z.; Zhang, Z. Understanding farmers intention and willingness to install renewable energy technology: A solution to reduce the environmental emissions of agriculture. Appl. Energy 2022, 309, 118459. [Google Scholar] [CrossRef]
  4. Abbas, A.; Zhao, C.; Wasem, M.; Ahmed Khan, K.; Ahmed, R. Analysis of energy input—Output of farms and assessment of greenhouse gas emissions: A case study of cotton growers. Front. Environ. Sci. 2021, 9, 826838. [Google Scholar] [CrossRef]
  5. Abbas, A.; Zhao, C.; Ullah, W.; Ahmad, R.; Waseem, M.; Zhu, J. Towards sustainable farm production system: A case study of corn farming. Sustainability 2021, 13, 9243. [Google Scholar] [CrossRef]
  6. Milander, J.J. Maize Yield and Components as Influenced by Environment and Agronomic Management. Master’s Thesis, University of Nebraska, Lincoln, NE, USA, 2015; p. 86. [Google Scholar]
  7. Urioste, A.; Hevia, G.; Hepper, E.; Anton, L.; Bono, A.; Buschiazzo, D. Cultivation effects on the distribution of organic carbon, total nitrogen and phosphorus in soils of the semiarid region of Argentinian Pampas. Geoderma 2006, 136, 621–630. [Google Scholar] [CrossRef]
  8. Wei, Y.; Chen, D.; Hu, K.; Willett, I.R.; Langford, J. Policy incentives for reducing nitrate leaching from intensive agriculture in desert oases of Alxa, Inner Mongolia, China. Agric. Water Manag. 2009, 96, 1114–1119. [Google Scholar] [CrossRef]
  9. Heffer, P.; Prud’homme, M. Fertilizer Outlook 2017–2021. In Proceedings of the 85th IFA Annual Conference, Marrakech, Morocco, 21–23 May 2017. [Google Scholar]
  10. Cantarella, H.; Trivelin, P.C.O.; Contin, T.L.M.; Dias, F.L.F.; Rossetto, R.; Marcelino, R.; Coimbra, R.B.; Quaggio, J.A. Ammonia volatilisation from urease inhibitor-treated urea applied to sugarcane trash blankets. Sci Agric. 2008, 65, 397–401. [Google Scholar] [CrossRef]
  11. Drury, C.F.; Yang, X.; Reynolds, W.D.; Calder, W.; Oloya, T.O.; Woodley, A.L. Combining Urease and Nitrification Inhibitors with Incorporation Reduces Ammonia and Nitrous Oxide Emissions and Increases Corn Yields. J. Environ. Qual. 2017, 46, 939–949. [Google Scholar] [CrossRef]
  12. Cassman, K.G.; Dobermann, A.; Walters, D.T. Agroecosystems, nitrogen-use efficiency, and nitrogen management. AMBIO A J. Hum. Environ. 2002, 31, 132–140. [Google Scholar] [CrossRef]
  13. Sawyer, J.; Nafziger, E.; Randall, G.; Bundy, L.; Rehm, G.; Joern, B. Concepts and Rationale for Regional Nitrogen Rate Guidelines for Corn; Iowa State University-University Extension: Ames, IA, USA, 2006; pp. 6–24. [Google Scholar]
  14. Taggert, B.I.; Walker, C.; Chen, D.; Wille, U. Substituted 1,2,3-triazoles: A new class of nitrification inhibitors. Sci. Rep. 2021, 11, 14980. [Google Scholar] [CrossRef] [PubMed]
  15. Cantarella, H.; Otto, R.; Soares, J.R.; Silva, A.G.B. Agronomic efficiency of NBPT as a urease inhibitor: A review. J. Adv. Res. 2018, 13, 19–27. [Google Scholar] [CrossRef] [PubMed]
  16. Chien, S.H.; Prochnow, L.I.; Cantarella, H. Recent developments of fertilizer production and use to improve nutrient efficiency and minimize environmental impacts. Adv. Agron. 2009, 102, 267–322. [Google Scholar] [CrossRef]
  17. Gillette, K.; Malone, R.W.; Kaspar, T.C.; Ma, L.; Parkin, T.B.; Jaynes, D.B.; Fang, Q.X.; Hatfield, J.L.; Feyereisen, G.W.; Kersebaum, K.C. N loss to drain flow and N2O emissions from a corn-soybean rotation with winter rye. Sci. Total Environ. 2017, 618, 982–997. [Google Scholar] [CrossRef] [PubMed]
  18. Bundy, L.G. Managing Urea-Containing Fertilizers. 2001 Area Fertilizer Dealer Meetings, Nov. 27-Dec. 6; University of Wisconsin-Madison: Madison, WI, USA, 2001. [Google Scholar]
  19. Watson, C.J. Urease inhibitors. In Proceedings of the IFA International Workshop on Enhanced—Efficiency Fertilizers, Frankfurt, Germany, 27–30 June 2005; International Fertilizer Industry Association: Paris, France, 2005; Watson, C.J. Urease Activity and Inhibition—Principles and Practice; Proceedings 454; International Fertiliser Society: York, UK, 2005; p. 40. [Google Scholar]
  20. Cantarella, H.; Quaggio, J.A.; Gallo, P.B.; Bolonhezi, D.; Rossetto, R.; Martins, J.L.M.; Paulino, V.J.; Alcantara, P.B. Ammonia losses of NBPT-treated urea under Brazilian soil conditions. In IFA International Workshop on Enhanced-Efficiency Fertilizers, Frankfurt; International Fertilizer Industry Association: Paris, France, 2005. [Google Scholar]
  21. Kiss, S.; Simihaian, M. Improving Efficiency of Urea Fertilizers by Inhibition of Soil Urease Activity; Kluwer Academic Publishers: Dordrecht, The Netherlands, 2002. [Google Scholar]
  22. Pan, B.; Lam, S.K.; Mosier, A.; Luo, Y.; Chen, D. Ammonia volatilization from synthetic fertilizers and its mitigation strategies: A global synthesis. Agric. Ecosyst. Environ. 2016, 232, 283–289. [Google Scholar] [CrossRef]
  23. Silva, A.G.B.; Sequeira, C.H.; Sermarini, R.A.; Otto, R. Urease inhibitor NBPT on ammonia volatilization and crop productivity: A meta-analysis. Agron. J. 2017, 109, 636–645. [Google Scholar] [CrossRef]
  24. Mira, A.B.; Cantarella, H.; Souza-Netto, G.J.M.; Moreira, L.A.; Kamogawa, M.Y.; Otto, R. Optimizing urease inhibitor usage to reduce ammonia emission following urea application over crop residues. Agric. Ecosyst. Environ. 2017, 248, 105–112. [Google Scholar] [CrossRef]
  25. Engel, R.E.; Williams, E.; Wallander, R.; Hilmer, J. Apparent persistence of N-(n-butyl) thiophosphoric triamide is greater in alkaline soils. Soil Sci. Soc. Am. J. 2013, 77, 1424–1429. [Google Scholar] [CrossRef]
  26. Soares, J.R. Efeito de Inibidores de Urease e de Nitrificação na Volatilização de NH3 pela Aplicação Superficial de Ureia no solo [Dissertação]; Instituto Agrônomico de Campinas: Campinas, Brazil, 2011. [Google Scholar]
  27. Watson, C.J.; Miller, H.; Poland, P.; Kilpatrick, D.J.; Allen, M.D.B.; Garrett, M.K.; Christianson, C.B. Soil properties and the ability of the urease inhibitor N-(n-butyl) thiophosphoric triamide (nBTPT) to reduce ammonia volatilization from surface-applied urea. Soil Biol. Biochem. 1994, 26, 1165–1171. [Google Scholar] [CrossRef]
  28. Molga, M. Basics of Agricultural Climatology; PWRiL: Warszawa, Poland, 1986. (In Polish) [Google Scholar]
  29. Gaj, R.; Szulc, P.; Siatkowski, I.; Waligóra, H. Assessment of the effect of the mineral fertilization system on the nutritional status of maize plants and grain yield prediction. Agriculture 2020, 10, 404. [Google Scholar] [CrossRef]
  30. Fageria, N.K.; Baligar, V.C. Enhancing nitrogen use efficiency in crop plants. Adv. Agron. 2005, 88, 97–185. [Google Scholar]
  31. Subedi, K.D.; Ma, B.L. Nitrogen uptake and partitioning in stay-green and leafy maize hybrids. Crop. Sci. 2005, 45, 740–747. [Google Scholar] [CrossRef]
  32. Szulc, P.; Bocianowski, J.; Nowosad, K.; Michalski, T.; Waligóra, H.; Olejarski, P. Assessment of the influence of fertilization and environment al conditions on maize health. Plant Prot. Sci. 2018, 54, 174–182. [Google Scholar] [CrossRef]
  33. Yanai, J.; Linehan, D.J.; Robinson, D.; Young, I.M.; Hackett, C.A.; Kyuma, K.; Kosaki, T. Effects of inorganic nitrogen application on the dynamics of the soil solution composition in the root zone of maize. Plant Soil 1996, 180, 1–9. [Google Scholar] [CrossRef]
  34. Kruczek, A.; Szulc, P. Effect of fertilization method on the uptake and accumulation of mineral components in the initial period of maize development. Int. Agrophysics 2006, 20, 11–22. [Google Scholar]
  35. Wierzbowska, J.; Sienkiewicz, S.; Światły, A. Yield and nitrogen status of maize (Zea mays L.) fertilized with solution of urea-ammonium nitrate enriched with P, Mg or S. Agronomy 2022, 12, 2099. [Google Scholar] [CrossRef]
  36. Ravazzolo, L.; Trevisan, S.; Forestan, C.; Varotto, S.; Sut, S.; Dallacqua, S.; Malagoli, M.; Quaggiotti, S. Nitrate and ammonium affect the overall maize response to nitrogen availability by triggering specific and common transcriptional signatures in roots. Int. J. Mol. Sci. 2020, 21, 686. [Google Scholar] [CrossRef]
  37. Grant, C.A.; Derksen, D.A.; McLaren, D.; Irvine, R.B. Nitrogen fertilizer and urease inhibitor effects on canola seed quality in a one-pass seeding and fertilizing system. Field Crop. Res. 2011, 121, 201–208. [Google Scholar] [CrossRef]
  38. Qi, X.; Wu, W.; Shah, F.; Peng, S.; Huang, J.; Cui, K.; Liu, H.; Nie, L. Ammonia volatilization from urea-application influenced germination and early seedling growth of dry direct-seeded rice. Sci. World J. 2012, 857472. [Google Scholar] [CrossRef]
  39. Cruchaga, S.; Lasa, B.; Jauregui, I.; Gonzáles-Murua, C.; Aparicio-Tejo, P.M.; Ariz, I. Inhibition of endogenous urease activity by NBPT application reveals differential N metabolism responses to ammonium or nitrate nutrition in pea plants: A physiological study. Plant Soil 2013, 373, 813–827. [Google Scholar] [CrossRef]
  40. Artola, E.; Cruchaga, S.; Ariz, I.; Moran, J.F.; Garnica, M.; Houdusse, F.; Maria, J.; Irigoyen, I.; Lasa, B.; Aparicio-Tejo, P.M. Effect of N-(n-butyl) thiophosphoric triamide on urea metabolism and the assimilation of ammonium byTriticum aestivumL. Plant Growth Regul. 2011, 63, 73–79. [Google Scholar] [CrossRef]
  41. Salvagiotti, F.; Prystupa, P.; Ferraris, G.; Courenot, L.; Maganano, L.; Dignani, D.B.; Guttierrez-Bemoem, F. N:P:S stoichiometry in grains and physiological attributes associated with grain yield in maize as affected by phosphorus and sulfur nutrition. Field Crops Res. 2017, 203, 128–138. [Google Scholar] [CrossRef]
  42. Roberts, T.L. Improving nutrient use efficiency. Turk. J. Agric. 2008, 32, 177–182. [Google Scholar]
  43. Duffy, C.D.P.; Ruban, A.V. Dissipative pathways in the photosystem-II antenna in. plants. J. Photochem. Photobiol. B Biol. 2015, 152, 215–226. [Google Scholar] [CrossRef] [PubMed]
  44. Szczepaniak, W.; Grzebisz, W.; Potarzycki, J. An assessment of the effect of potassium fertilizing systems on maize nutritional status in critical stages of growth by plant analysis. J. Elem. 2014, 538–548. [Google Scholar] [CrossRef]
  45. Szulc, P.; Ambroży-Deręgowska, K.; Waligóra, H.; Mejza, I.; Grześ, S.; Zielewicz, W.; Wróbel, B. Dry matter yield of maize (Zea mays L.) as an indicator of mineral fertilizer efficiency. Plants 2021, 10, 535. [Google Scholar] [CrossRef]
  46. Bandurska, H.; Grzebisz, W.; Farat, R. Pierwiastki w środowisku. Potas 4. Potas a stresy abiotyczne: Susza. J. Elem. 2004, 9, 37–48. [Google Scholar]
Figure 1. Nitrification inhibitors [14].
Figure 1. Nitrification inhibitors [14].
Agronomy 13 00480 g001
Figure 2. Average Fv/m values for the combination of the cultivar (A) and type of fertilizer (B). Values marked with at least one same letter are not significantly different.
Figure 2. Average Fv/m values for the combination of the cultivar (A) and type of fertilizer (B). Values marked with at least one same letter are not significantly different.
Agronomy 13 00480 g002
Table 1. Basic chemical properties of the experimental field soil.
Table 1. Basic chemical properties of the experimental field soil.
YearsH2OKCl% N% C% HumusC:N
pH
20177.016.520.0861.0371.7912.1
20186.966.560.0861.0371.7912.1
20197.076.450.0850.9871.7011.6
Table 2. Sorption capacity cmol(+) kg−1.
Table 2. Sorption capacity cmol(+) kg−1.
YearsK+Na+Mg2+Ca2+Suma (S)
TEB
HwT = S + Hw
CEC
V(%) = S/T ∗ 100
20170.230.070.676.197.160.908.0688.4
20180.220.080.706.057.050.988.0387.8
20190.220.080.686.157.130.968.0988.1
Average0.220.080.686.137.110.958.0688.1
Table 3. Content of water-soluble components.
Table 3. Content of water-soluble components.
YearsConductometry
uS·cm−1
1:5
Biocarbonates (HCO3)Na+K+Mg2+Ca2+
mg∙kg−1
201757.35.211.159.713.5122.0
201856.25.010.959.413.2119.0
201946.84.59.456.911.497.0
Table 4. Total elemental content determined in aqua regia.
Table 4. Total elemental content determined in aqua regia.
YearsCuZnNiCrMnFeMgAlP
mg·kg−1
20173.4430.25.9311.38335.2462.3895.13622.3436.2
20183.2729.36.3011.40327.84691.5987.63626.6429.6
20194.2030.55.7311.37340.04511.7821.23606.6444.0
Average3.6430.05.9911.38334.33221.8901.33618.5436.6
Table 5. Average monthly air temperatures and monthly total precipitation in individual growing season.
Table 5. Average monthly air temperatures and monthly total precipitation in individual growing season.
YearsIVVVIVIIVIIIIXXSum/Average
Temperatures [°C]
20176.915.016.817.418.013.09.813.8
201812.417.018.220.120.916.310.616.5
20199.812.121.718.820.614.410.615.4
Many years
(2007–2019)
9.013.717.419.119.313.78.614.4
Precipitation [mm]
20173085621341436499617
201849545120143225290
20193721825448431277
Many years
(2007–2019)
26565892604043375
The Sielianinov hydrothermal coefficient of water availability (1)
20171.41.81.22.52.61.63.22.1
20181.30.10.81.90.20.70.80.8
20190.11.90.30.40.71.90.90.9
Many years
(2007–2019)
1.01.31.11.61.01.01.61.2
(1)—According to Sielianinov [28].
Table 6. Average values of plant dry matter accumulation dynamics for cultivars (A) and fertilizers (B).
Table 6. Average values of plant dry matter accumulation dynamics for cultivars (A) and fertilizers (B).
FactorsLevels of FactorsSingle Plant Dry Weight [g]Dry Matter Yield [kg·ha−1]Dry Matter Content [%]
AA12.38 a191.23 a17.21 a
A21.61 b132.47 b17.13 a
A32.58 a214.19 a16.11 b
BB11.82 b148.84 b16.43 ns
B22.16 ab175.32 ab16.31 ns
B32.36 a191.49 a17.65 ns
B42.31 a187.92 a17.05 ns
B52.23 a184.58 a16.96 ns
B62.25 a186.31 a16.67 ns
B72.20 ab180.61 a16.61 ns
Values in columns marked with the same letter do not differ significantly; ns—not significant.
Table 7. Average values of the dynamics of dry matter accumulation for the combination of the cultivar (A) and fertilizer (B).
Table 7. Average values of the dynamics of dry matter accumulation for the combination of the cultivar (A) and fertilizer (B).
ABSingle Plant Dry Weight [g]Dry Matter Yield [kg·ha−1]Dry Matter Content [%]
A1B11.92 bcdefg152.61 bcdef15.12 ab
B22.55 abc203.25 abc16.56 ab
B32.45 abcd194.14 abcde17.81 ab
B42.69 ab212.22 ab17.51 ab
B52.36 abcdefg194.72 abcde18.13 a
B62.38 abcdef194.70 abcde17.29 ab
B72.31 abcdefg186.98 abcdef18.03 ab
A2B11.71 defg141.30 cdef17.61 ab
B21.54 g126.79 f17.57 ab
B31.68 defg135.79 def17.58 ab
B41.56 fg128.67 ef17.03 ab
B51.58 efg131.70 def16.48 ab
B61.63 defg135.09 def17.20 ab
B71.56 fg127.90 ef16.42 ab
A3B11.84 cdefg152.62 bcdef16.58 ab
B22.39 abcde195.93 abcd14.79 b
B32.95 a244.52 a17.55 ab
B42.69 ab222.85 a16.62 ab
B52.73 ab227.33 a16.28 ab
B62.75 ab229.12 a15.53 ab
B72.73 ab226.96 a15.39 ab
Values in columns marked with the same letter do not differ significantly.
Table 8. Average values of macronutrient content in plant and leaf dry matter for cultivars (A) and fertilizer (B).
Table 8. Average values of macronutrient content in plant and leaf dry matter for cultivars (A) and fertilizer (B).
FactorsLevels of FactorsBBCH 15/16 * (Plant)BBCH 65 * (Leaves)
N
[g·kg−1]
NPKMgCa
[g·kg−1]
AA132.18 ns23.93 ns2.10 ns30.96 ns2.10 ns1.44 b
A233.03 ns25.03 ns2.36 ns31.80 ns2.57 ns1.51 ab
A333.24 ns25.41 ns2.41 ns32.64 ns2.57 ns1.73 a
BB133.45 ns23.20 c1.82 d28.51 b2.14 b1.61 a
B233.05 ns23.36 bc2.03 d31.21 ab2.59 a0.78 b
B332.70 ns23.54 bc2.08 cd31.71 a2.52 ab1.76 a
B432.15 ns24.00 bc2.14 cd32.05 a2.31 ab1.71 a
B532.89 ns25.11 bc2.45 bc32.80 a2.42 ab0.87 b
B631.92 ns25.96 ab2.61 ab32.81 a2.45 ab2.24 a
B733.56 ns28.36 a2.89 a33.55 a2.47 ab1.94 a
Values in columns marked with the same letter do not differ significantly; ns—not significant; * BBCH 15/16—5–6 leaf stage; * BBCH 65—flowering of the upper and lower part of the tassel. Fully developed pistil stigmas.
Table 9. Average values of physiological data for years (Y), cultivars (A) and type of fertilizer (B).
Table 9. Average values of physiological data for years (Y), cultivars (A) and type of fertilizer (B).
FactorsLevels of FactorsF0FmFvFv/mCCI
Y2018169.11 b816.15 ns656.31 ns0.7932 a44.85 a
2019189.85 a851.72 ns659.80 ns0.7718 b32.57 b
AA1181.98 ns821.20 ns643.94 ns0.7769 ns34.18 b
A2180.57 ns824.05 ns651.51 ns0.7832 ns36.91 ab
A3175.88 ns856.56 ns678.72 ns0.7874 ns45.04 a
BB1186.56 a825.25 ns651.94 ns0.7837 ns31.25 d
B2186.36 a821.36 ns638.50 ns0.7732 ns35.41 cd
B3183.69 ab831.32 ns653.88 ns0.7822 ns36.50 bcd
B4180.25 ab844.38 ns667.86 ns0.7847 ns38.63 bc
B5174.15 ab840.86 ns671.88 ns0.7847 ns40.35 abc
B6173.51 b836.22 ns661.63 ns0.7836 ns42.60 ab
B7171.81 b838.17 ns660.69 ns0.7855 ns46.23 a
Values in columns marked with the same letter do not differ significantly; ns—not significant.
Table 10. Linear relationships between grain yield and nitrogen content in maize leaf blades at BBCH 65.
Table 10. Linear relationships between grain yield and nitrogen content in maize leaf blades at BBCH 65.
YearsPearson Correlation Coefficient (r)Linear Regression EquationCoefficient
of Determination (R2)
p-Value
20170.6045y = 4.124 + 0.231x36.54%0.003702
20180.5380y = 2.376 + 0.2x28.95%0.011873
20190.3776--0.091458
2017–20190.3506y = 2.167 + 0.225x12.29%0.004842
Table 11. Linear relationships between grain yield and phosphorus content in maize leaf blades at BBCH 65.
Table 11. Linear relationships between grain yield and phosphorus content in maize leaf blades at BBCH 65.
YearsPearson Correlation Coefficient (r)Linear Regression EquationCoefficient
of Determination (R2)
p-Value
20170.6375y = 5.586 + 1.688x40.64%0.001878
20180.6508y = 4.928 + 1.277x42.36%0.001398
20190.6629y = 4.215 + 0.682x43.94%0.001058
2017–20190.4735y = 3.44 + 1.876x22.42%0.000089
Table 12. Linear relationships between grain yield and potassium content in maize leaf blades at BBCH 65.
Table 12. Linear relationships between grain yield and potassium content in maize leaf blades at BBCH 65.
YearsPearson Correlation Coefficient (r)Linear Regression EquationCoefficient
of Determination (R2)
p-Value
20170.7286y = 2.734 + 0.22x53.08%0.000180
20180.5106y = 0.76 + 0.222x26.07%0.018019
20190.5887y = −0.473 + 0.192x34.66%0.004993
2017–20190.2251--0.076058
Table 13. Linear relationships between grain yield and magnesium content in maize leaf blades at BBCH 65.
Table 13. Linear relationships between grain yield and magnesium content in maize leaf blades at BBCH 65.
YearsPearson Correlation Coefficient (r)Linear Regression EquationCoefficient
of Determination (R2)
p-Value
20170.6078y = 6.066 + 1.565x36.95%0.003467
20180.5687y = 5.457 + 0.919x32.34%0.007139
20190.2342--0.306917
2017–20190.1563--0.221239
Table 14. Linear relationships between grain yield and calcium content in maize leaf blades at BBCH 65.
Table 14. Linear relationships between grain yield and calcium content in maize leaf blades at BBCH 65.
YearsPearson Correlation Coefficient (r)Linear Regression EquationCoefficient
of Determination (R2)
p-Value
20170.2254--0.325911
20180.1902--0.408854
20190.3174--0.160918
2017–20190.4088y = 6.084 + 1.058x16.71%0.000879
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Szulc, P.; Krauklis, D.; Ambroży-Deręgowska, K.; Wróbel, B.; Zielewicz, W.; Niedbała, G.; Kardasz, P.; Niazian, M. Evaluation of the Effect of Conventional and Stabilized Nitrogen Fertilizers on the Nutritional Status of Several Maize Cultivars (Zea mays L.) in Critical Growth Stages Using Plant Analysis. Agronomy 2023, 13, 480. https://doi.org/10.3390/agronomy13020480

AMA Style

Szulc P, Krauklis D, Ambroży-Deręgowska K, Wróbel B, Zielewicz W, Niedbała G, Kardasz P, Niazian M. Evaluation of the Effect of Conventional and Stabilized Nitrogen Fertilizers on the Nutritional Status of Several Maize Cultivars (Zea mays L.) in Critical Growth Stages Using Plant Analysis. Agronomy. 2023; 13(2):480. https://doi.org/10.3390/agronomy13020480

Chicago/Turabian Style

Szulc, Piotr, Daniel Krauklis, Katarzyna Ambroży-Deręgowska, Barbara Wróbel, Waldemar Zielewicz, Gniewko Niedbała, Przemysław Kardasz, and Mohsen Niazian. 2023. "Evaluation of the Effect of Conventional and Stabilized Nitrogen Fertilizers on the Nutritional Status of Several Maize Cultivars (Zea mays L.) in Critical Growth Stages Using Plant Analysis" Agronomy 13, no. 2: 480. https://doi.org/10.3390/agronomy13020480

APA Style

Szulc, P., Krauklis, D., Ambroży-Deręgowska, K., Wróbel, B., Zielewicz, W., Niedbała, G., Kardasz, P., & Niazian, M. (2023). Evaluation of the Effect of Conventional and Stabilized Nitrogen Fertilizers on the Nutritional Status of Several Maize Cultivars (Zea mays L.) in Critical Growth Stages Using Plant Analysis. Agronomy, 13(2), 480. https://doi.org/10.3390/agronomy13020480

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