Impacts of Nitrogen Fertilizer Application Timing and Rate on Sweet Corn Production Under Subtropical Environmental Conditions

Abstract

Sweet corn (Zea mays convar. saccharata var. rugosa) is an important crop in the United States (US), particularly in the southeastern region. While effective nitrogen (N) management is essential for optimizing yields, the sandy soils and variable precipitation in this region impact N uptake. This study evaluates the effects of several N rates (ranging from 224 to 336 kg ha⁻¹) and N fertilizer application timing (N fertilizer applied at emergence and side-dress stages) on sweet corn growth and yield under the subtropical environmental conditions of the southeastern US. Field experiments were conducted over three years in the states of Georgia (2020) and Alabama (2021 and 2022). In general, the weather conditions of each season had a direct impact on sweet corn growth, development, and yield parameters. Among all locations, the season in Alabama (2022) allowed for the highest yields (17,380 kg ha⁻¹), which could be attributed to favorable weather conditions that required moderate nitrogen application rates (224–280 kg ha⁻¹). Contrarily, the weather conditions of Alabama in 2021 and Georgia in 2020 impacted soil N availability, consequently leading to negative effects on sweet corn growth. Overall, N fertilizer management strategies are indicated to be region- and season-specific in order to enhance sweet corn production while protecting the environment from excessive N losses. Further research is still required to refine these strategies and improve predictive models for diverse climatic conditions.

1. Introduction

Sweet corn (Zea mays convar. saccharata var. rugosa) is one of the most important vegetable crops in the United States (US), with annual production exceeding 3 million tons [1]. The southeastern US accounts for 44% of the nation’s total sweet corn production [1]. However, significant precipitation and sandy soils, which are prevalent in the region, can adversely affect nitrogen (N) fertilizer uptake and utilization, leading to reduced crop yields [2,3].

Nitrogen is a critical nutrient for crop productivity, playing an essential role in plant growth and development, which in turn enhances yield and food quality [2,4]. In sweet corn, effective N fertilizer management is particularly important during both vegetative and reproductive stages to optimize growth and kernel structure [5]. Adequate N fertilization prevents deficiencies such as chlorosis, poor ear structure, and yield reductions [2,6,7]. Conversely, excessive N fertilizer applications increase production costs, reduce efficiency, and negatively impact the environment through groundwater pollution and risks to human and animal health [8].

Nevertheless, the total N rate applied is not the only important aspect of N fertilizer management. The timing of N fertilizer application is critical for maximizing the efficiency of N application [9]. This is mostly important in subtropical environmental conditions, where frequent rainfall events and coarse-textured soils allow for soil N leaching [5,9]. At planting date or early growth stages, N fertilizer application supports root development and plant establishment and promotes leaf and stem growth [10,11]. During side-dress or mid-vegetative stages, N fertilizer applications are essential for ear and kernel development, which ultimately determines the final yield [12]. Khan et al. [5] reported significant yield increases with N rates reaching up to 120 kg N ha⁻¹, while Gao et al. [13] achieved the highest yields with 250 kg N ha⁻¹. Similarly, Oktem et al. [9] suggested an optimal N rate of 320 kg N ha⁻¹ to balance yield and structure in sweet corn.

Despite these findings, growers often overapply N fertilizer rates in an effort to maximize yields, leading to increased input costs and environmental degradation [2,14]. However, balancing nutrient management practices is essential to benefit both growers and the environment. Therefore, this study hypothesizes that a reduction in N fertilizer rates can reduce soil N loss while increasing sweet corn nitrogen use efficacy and maximizing yield and kernel structure compared to the current growers’ standard practices. Consequently, the study objectives are to evaluate the effects of N fertilizer rates and application timing on sweet corn growth and yield under the subtropical environmental conditions of the southeastern US, emphasizing the need for balanced nutrient management to improve yield and kernel structure, minimize risks, and protect the environment.

2. Materials and Methods

2.1. Site Description and Experimental Design

Field experiments were conducted at the Vidalia Onion and Vegetable Research Center, University of Georgia (32.01814° N, 82.22138° W) in southeast Georgia in 2020 and the E.V. Smith Research Center, Auburn University (32.50053° N, 85.89281° W) in central Alabama during 2021 and 2022. The soil at all locations was classified as loamy sand (

Table 1. Location, geographic coordinates, year, season, soil type, planting spacing, planting date, harvest date, and accumulated growing degree days from planting to harvest for each field experiment.

Location	Geographic Coordinates	Year	Season	Soil Type	IRS 1 (cm)	PS 2 (cm)	PD 3	Harvest	GDD 4 (°C)
Georgia	32.01814° N, 82.22138° W	2020	Fall	Irvington loamy sand	91.44	17.78	Aug. 26	Nov. 2	928
Alabama	32.50053° N, 85.89281° W	2021	Fall	Kalmia loamy sand	91.44	17.78	Aug. 16	Nov. 1	921
Alabama	32.50053° N, 85.89281° W	2022	Fall	Kalmia loamy sand	91.44	17.78	Aug. 17	Nov. 7	980

¹ IRS = in-row spacing. ² PS: plant spacing. ³ PD: planting date. ⁴ GDD: growing degree days (the base temperature for sweet corn is 10 °C).

). According to the Koppen–Geiger climate classification, all locations experience a humid subtropical or warm temperate climate (Cfa) characterized by hot summers with heavy rainfall and dry winters [15,16].

A two-factorial experimental design evaluating N fertilizer application timing and N fertilizer rate was arranged in a randomized complete block design with three replicates per treatment (r = 3). Individual plots consisted of four rows spaced 91.4 cm apart, with plants spaced 17.7 cm apart within rows (61,813 plants ha⁻¹). Planting occurred on 26 August 2020, 16 August 2021, and 17 August 2022. The sweet corn cultivar Remedy (Syngenta Seeds, Minneapolis, MN, USA) was used, and harvests took place in early November each year (Table 1).

Crop management practices, including soil preparation, irrigation, and the management of pests, weeds, and diseases, were conducted in accordance with established protocols for sweet corn production in the southeastern United States [17]. The integrated pest management strategy employed varied field to field but included the use of biological control agents and selective pesticides to minimize pest populations. Weed control was achieved through a combination of mechanical cultivation and herbicide application. Disease management included regular monitoring of the crop and the application of fungicides as needed. The weekly scouting performed ensured that fields remained free of weeds, insects, and diseases.

N fertilizer was applied in three stages: pre-planting (N_pl), at emergence (N_eme), and at side-dress (N_sd). The fertilizer source at N_pl was 10-10-10 (N-P-K), while at N_eme and N_sd, the source was 34-0-0 (N-P-K). At N_pl, a rate of 34 kg N ha⁻¹ was applied across all treatments. At N_eme, either 56 or 112 kg N ha⁻¹ was applied, followed by N_sd applications of 134, 162, or 190 kg N ha⁻¹, resulting in six treatment combinations (T1–T6), as detailed in

Table 2. Nitrogen fertilizer rates applied at planting, emergence, and side-dress stages, and total nitrogen applied for each experimental field.

Treatments	N Rates (kg ha−1)
	Npl 1	Neme 2	Nsd 3	Total N
1	34	56	134	224
2	34	56	162	252
3	34	56	190	280
4	34	112	134	280
5	34	112	162	308
6	34	112	190	336

¹ N_pl: nitrogen application at planting day. ² N_eme: nitrogen application at emergence stage. ³ N_sd: nitrogen application at side-dress stage.

.

Ammoniacal N (10% of N) was used as the N source for N_pl, while ammonium nitrate (24% of N) and urea N (10% of N) were used for N_eme and N_sd, contributing to a total of 34% N. The N_pl application was performed at 0 days after planting (DAP). The N_eme application occurred at 19, 25, and 16 DAP in 2020, 2021, and 2022, respectively, while N_sd was applied at 40, 44, and 41 DAP in corresponding years. Phosphorus (P) and potassium (K) were applied only at planting using the same 10-10-10 fertilizer source, following regional recommendations [17].

2.2. Weather Conditions

Daily maximum and minimum air temperatures and rainfall events were recorded using the Georgia Automated Weather Network (2020) and the Auburn University Mesonet (2021 and 2022). Accumulated growing degree days (GDD) were determined using Equation (1) [18].

$$\mathrm{G}\mathrm{D}\mathrm{D}={\displaystyle \frac{\left({\mathrm{T}}_{\mathrm{m}\mathrm{a}\mathrm{x}}+{\mathrm{T}}_{\mathrm{m}\mathrm{i}\mathrm{n}}\right)}{2}}-{\mathrm{T}}_{\mathrm{b}\mathrm{a}\mathrm{s}\mathrm{e}}$$

(1)

where T_max and T_min are the average daily maximum and minimum temperatures, respectively, and T_base is the sweet corn base temperature (10 °C) [19].

2.3. Soil Total Nitrogen

Soil samples were collected from 0.30–0.60 m depths to evaluate nitrate (NO₃⁻) and ammonium (NH₄⁺) levels. Five subsamples were collected per plot at specific growth stages: 0, 19, and 40 DAP in Georgia (2020); 0, 25, and 44 DAP in Alabama (2021); and 0, 28, and 40 DAP in Alabama (2022). Additional samples were collected at the silk and maturity (harvest) stages, as presented in

Table 3. Sampling stages for nitrate (NO₃⁻) and ammonium (NH₄⁺), biomass accumulation, and total nitrogen.

Stages	DAP 1
	Soil Total N (NO3− + NH4+)			Biomass and Total N
	2020	2021	2022	2020	2021	2022
PL 2	0	0	0	-	-	-
EME 3	19	25	28	19	25	28
SD 4	40	44	40	40	44	40
Silk	54	66	62	54	66	62
Harvest	68	74	82	68	74	82

¹ DAP: days after planting. ² PL: planting day sampling (day 0). ³ EME: emergence stage sampling. ⁴ SD: side-dress stage sampling.

. Dried samples were analyzed for NO₃⁻ and NH₄⁺ contents at Waters Agricultural Laboratories Inc. (Camilla, GA, USA).

2.4. Biomass Accumulation and Total Nitrogen

Plant tissue samples (leaf and stem) were collected at emergence (EME), side-dress (SD), silk, and maturity (harvest) growth stages during each growing season (Table 3). The leaf area index (LAI) was measured using an optical–electronic area meter (LI-3100, LI-COR Inc., Lincoln, NE, USA) on two representative plants from each plot. Sampled plants were oven-dried at 65.5 °C until reaching a constant weight to determine biomass.

Subsequently, dried samples were sent to Waters Agricultural Laboratories Inc. (Camilla, GA, USA) for total Kjeldahl N (TKN) content analysis. Plant N uptake accumulation (total N) was calculated by multiplying the total dry biomass by the TKN content.

Nitrogen use efficiency (NUE) was determined using Equation (2) [20].

$$\mathrm{N}\mathrm{U}\mathrm{E}\mathrm{ }\left(\mathrm{\%}\right)\mathrm{ }=\mathrm{ }{\displaystyle \frac{\mathrm{N} \mathrm{u}\mathrm{p}\mathrm{t}\mathrm{a}\mathrm{k}\mathrm{e} \mathrm{a}\mathrm{c}\mathrm{c}\mathrm{u}\mathrm{m}\mathrm{u}\mathrm{l}\mathrm{a}\mathrm{t}\mathrm{i}\mathrm{o}\mathrm{n}}{\left(\mathrm{N} \mathrm{f}\mathrm{e}\mathrm{r}\mathrm{t}\mathrm{i}\mathrm{l}\mathrm{i}\mathrm{z}\mathrm{e}\mathrm{r} \mathrm{a}\mathrm{p}\mathrm{p}\mathrm{l}\mathrm{i}\mathrm{e}\mathrm{d}\mathrm{ }-\mathrm{ }\mathrm{r}\mathrm{e}\mathrm{s}\mathrm{i}\mathrm{d}\mathrm{u}\mathrm{a}\mathrm{l}\mathrm{ }\mathrm{N}\mathrm{ }\mathrm{f}\mathrm{e}\mathrm{r}\mathrm{t}\mathrm{i}\mathrm{l}\mathrm{i}\mathrm{z}\mathrm{e}\mathrm{r}\mathrm{ }\mathrm{i}\mathrm{n}\mathrm{ }\mathrm{t}\mathrm{h}\mathrm{e}\mathrm{ }\mathrm{s}\mathrm{o}\mathrm{i}\mathrm{l}\right)}}$$

(2)

2.5. Yield and Ear Structure

Sweet corn ears were hand-harvested at maturity (68–82 DAP) at all locations (Table 1). For each row, the total ear weight and number of ears were recorded. Five randomly selected ears from each plot were measured for ear length (EL), ear diameter (ED), number of kernels per row (KR), number of kernels in an ear row (KIR), and total number of kernels per ear (KTG).

2.6. Statistical Analysis

Statistical analyses were performed using a linear mixed model approach via the PROC GLIMMIX procedure in SAS 9.4 software (SAS Institute Inc., Cary, NC, USA). This method was employed to evaluate the effects of location, N application rates, N application timing, and their interactions on sweet corn growth, yield, and nitrogen-related parameters across different growth stages (sampling events).

The experimental design was treated as a randomized complete block design with fixed effects for location, N application rates, N application timing, and growth stages. Block was included as a random effect to account for variability among replications. Each response variable, including LAI, biomass accumulation, total N, soil total N, NUE, sweet corn yield, and ear structure parameters, was analyzed separately. When significant main effects or interactions were measured (p ≤ 0.05), least-square means comparisons were performed using Tukey’s test, and means were portioned using the slice command in SAS. Statistical significance levels were reported as non-significant (ns), significant at p ≤ 0.05 (*), p ≤ 0.01 (**), or p ≤ 0.001 (***). To further explore relationships among response variables, a correlation-based network analysis was conducted using Pearson’s method in R Studio Version 4.3 (R Studio Team 2020, Boston, MA, USA) [21].

3. Results

3.1. Weather Data and Growing Degree Days

Rainfall events and daily minimum and maximum temperatures for all locations are presented in Figure 1. Total accumulated GDD was 928 for Georgia (2020), 921 in Alabama (2021), and 980 in Alabama (2022).

In Georgia (2020), the average daily minimum and maximum temperatures were 18 and 28 °C, respectively, with a total rainfall accumulation of 175 mm during the growing season. In Alabama (2021), the average daily minimum and maximum temperatures were 17 and 29 °C, with a total rainfall accumulation of 271 mm. Similarly, in Alabama (2022), the average daily minimum and maximum temperatures were 14 and 29 °C, with total rainfall accumulating to 245 mm.

3.2. Leaf Area Index, Biomass Accumulation, Total Nitrogen, and Soil Total Nitrogen

Results indicate that Alabama (2022) outperformed Georgia (2020) and Alabama (2021) in terms of LAI, biomass accumulation, total N, and soil total N across all growth stages (Figure 2). Statistical analysis revealed a significant main effect of location on LAI at the EME, SD, and silk stages. In Georgia (2020), LAI increased from 323 cm² at the EME stage to 1858 cm² at the silk stage, followed by a decline to 1416 cm² at harvest (Figure 2a). Alabama (2021) showed an increase from 852 cm² at EME to 1818 cm² at the SD stage before declining to 1424 cm² at the silk stage and stabilizing at 1364 cm² at harvest. Notably, Alabama (2022) displayed the highest LAI values among all locations, increasing from 1357 cm² at the EME stage to a pronounced peak of 2282 cm² at the SD stage, followed by a decline to 2251 cm² at the silk stage and 1181 cm² at harvest.

Biomass accumulation (Figure 2b) varied significantly at the SD, silk, and harvest stages, with consistent increases from EME to silk stages and a decline at harvest across all locations. Georgia (2020) had the lowest biomass values, starting at 167 kg ha⁻¹ at the EME stage, increasing to 1409 kg ha⁻¹ at SD and 2288 kg ha⁻¹ at silk, before decreasing to 2108 kg ha⁻¹ at harvest. Alabama (2021) recorded 446 kg ha⁻¹ at EME, increasing to 2014 kg ha⁻¹ at SD and 2748 kg ha⁻¹ at silk, with a subsequent decrease to 1857 kg ha⁻¹ at harvest. Alabama (2022) achieved the maximum biomass values, starting at 830 kg ha⁻¹ at EME, rising to 3012 kg ha⁻¹ at SD and 3066 kg ha⁻¹ at silk, before declining to 2695 kg ha⁻¹ at harvest.

Total N uptake (Figure 2c) varied significantly at the EME, SD, silk, and harvest stages. In Georgia (2020), total N uptake increased from 48.7 kg ha⁻¹ at SD to 58.9 kg ha⁻¹ at the silk stage, but data for EME and harvest stages were unavailable. Alabama (2021) showed 15.2 kg ha⁻¹ at EME, increasing to 53.5 kg ha⁻¹ at SD and peaking at 68.5 kg ha⁻¹ at the silk stage, followed by a slight decrease to 40.6 kg ha⁻¹ at harvest. Alabama (2022) demonstrated a sharp increase in total N uptake, starting at 36.5 kg ha⁻¹ at EME, rising to 94.1 kg ha⁻¹ at SD and 162.2 kg ha⁻¹ at silk, with the highest value of 166.2 kg ha⁻¹ recorded at harvest.

Soil total N (Figure 2d) was significantly influenced by location at the EME, SD, and silk stages, with Alabama (2022) generally showing the highest values, except at the silk stage, where Alabama (2021) demonstrated superior levels. In Georgia (2020), soil total N increased from 9.9 kg ha⁻¹ at EME to 53.9 kg ha⁻¹ at SD, followed by a decline to 49.7 kg ha⁻¹ at silk and 9.3 kg ha⁻¹ at harvest. Alabama (2021) showed 5.8 kg ha⁻¹ at EME, 3.4 kg ha⁻¹ at SD, and 194.5 kg ha⁻¹ at silk before decreasing to 98.8 kg ha⁻¹ at harvest. Alabama (2022) recorded 31.8 kg ha⁻¹ at EME, increasing to 60.2 kg ha⁻¹ at SD, 69.2 kg ha⁻¹ at silk, and 93.6 kg ha⁻¹ at harvest.

3.3. Effect of N_eme on Biomass Accumulation, Total Nitrogen, and Soil Total Nitrogen Across Growth Stages

The effect of N_eme application rates (56 and 112 kg ha⁻¹) on biomass accumulation, total N uptake, and soil total N across different growth stages is shown in

Table 4. Effect of N_eme on biomass accumulation, total nitrogen uptake, and soil total nitrogen across growth stages.

Neme 1 (kg ha−1)	Biomass (kg ha−1)		Total N Uptake (kg ha−1)		Soil Total N (kg ha−1)
	SD 2	Silk	SD	Harvest	EME 3	SD
56	2298 a 4	2604 a	69.5 a	98.0 a	12.4 a	27.3 b
112	1992 b	2797 a	61.4 b	108.8 a	19.3 a	50.9 a
p-value 5	**	ns	*	ns	ns	***

¹ N_eme: nitrogen application at emergence stage. ² SD: side-dress stage sampling. ³ EME: emergence stage sampling. ⁴ Values followed by similar lowercase letters among N_eme indicate no significant difference (p > 0.05) according to the Tukey’s mean test. ⁵ Levels of significance (p-value): ns, non-significant; *, significant at p ≤ 0.05; **, significant at p ≤ 0.01; ***, significant at p ≤ 0.001.

. Results indicated significant differences in these variable responses for the interaction between application rate and growth stage.

Biomass increased across growth stages from SD to silk for both N_eme. At the SD stage, the N_eme 56 kg ha⁻¹ resulted in significantly higher biomass (2298 kg ha⁻¹) compared to the N_eme 112 kg ha⁻¹ (1992 kg ha⁻¹). However, at the silk stage, biomass differences between the two application rates were not statistically significant, with values of 2604 kg ha⁻¹ for N_eme 56 kg ha⁻¹ and 2797 kg ha⁻¹ for N_eme 112 kg ha⁻¹.

Total N uptake followed a similar trend, increasing across growth stages. At the SD stage, the N_eme 56 kg ha⁻¹ resulted in higher total N (69.5 kg ha⁻¹) compared to the N_eme 112 kg ha⁻¹ (61.4 kg ha⁻¹). At the harvest stage, total N uptake differences were not statistically significant, with values of 98.0 kg ha⁻¹ and 108.8 kg ha⁻¹ for N_eme 56 kg ha⁻¹ and N_eme 112 kg ha⁻¹, respectively.

Soil total N levels also increased across growth stages from EME to SD for both N_eme. At the EME stage, no significant differences were measured between application rates, with soil total N values of 12.4 kg ha⁻¹ for N_eme 56 kg ha⁻¹ and 19.3 kg ha⁻¹ for N_eme 112 kg ha⁻¹. However, at the SD stage, the N_eme 112 kg ha⁻¹ resulted in significantly higher soil total N (50.9 kg ha⁻¹) compared to the N_eme 56 kg ha⁻¹ (27.3 kg ha⁻¹).

3.4. Effect of N_sd on Leaf Area Index and Soil Total Nitrogen Across Growth Stages

The LAI values did not show significant differences among the N_sd at the SD stage (

Table 5. Effect of N_sd on leaf area index and soil total nitrogen across growth stages.

Nsd 1 (kg ha−1)	LAI 2 (cm2)	Soil Total N (kg ha−1)
	SD 3	Silk
190	1870 a 4	138.9 a
162	2069 a	93.1 b
134	1953 a	81.4 b
p-value 5	ns	*

¹ N_sd: nitrogen application at side-dress stage. ² LAI: leaf area index. ³ SD: side-dress stage sampling. ⁴ Values followed by similar lowercase letters among N_sd indicate no significant difference (p > 0.05) according to Tukey’s mean test. ⁵ Levels of significance (p-value): ns, non-significant; *, significant at p ≤ 0.05.

). In contrast, soil total N at the silk stage showed significant differences among application rates. The N_sd 190 kg ha⁻¹ resulted in the highest soil total N (138.9 kg ha⁻¹), significantly greater than the N_sd 162 kg ha⁻¹ (93.1 kg ha⁻¹) and N_sd 134 kg ha⁻¹ (81.4 kg ha⁻¹).

3.5. Effect of the Interaction Between Location and N_eme on Total Nitrogen and Soil Total Nitrogen Across Growth Stages

A significant interaction between location and N_eme was measured for total N uptake at the harvest stage and soil total N at the SD stage (

Table 6. Effect of the interaction between location and N_eme on total nitrogen and soil total nitrogen uptake across growth stages.

Neme 1 (kg ha−1)	Georgia (2020)	Alabama (2021)	Alabama (2022)
	Harvest
	Total N Uptake (kg ha−1)
56	-	41.40 aB	154.59 bA
112	-	39.78 aB	177.77 aA
p-value 2	-	*	*
Neme (kg ha−1)	SD 3
	Soil total N (kg ha−1)
56	24.36 b 4 B 5	3.78 aB	53.93 aA
112	83.54 aA	2.99 aB	66.41 aA
p-value	**	**	**

¹ N_eme: nitrogen application at emergence stage. ² Levels of significance (p-value): *, significant at p ≤ 0.05; **, significant at p ≤ 0.01. ³ SD: side-dress stage sampling. ⁴ Values followed by similar lowercase letters among N_eme within each location indicate no significant difference (p > 0.05) according to Tukey’s mean test. ⁵ Values followed by similar uppercase letters among locations within N_eme indicate no significant difference (p > 0.05) according to Tukey’s mean test.

).

At the harvest stage, in Alabama (2022), N_eme application significantly affected total N uptake with the application of 112 kg ha⁻¹ resulting in higher total N uptake (177.77 kg ha⁻¹) compared to the N_eme 56 kg ha⁻¹ (154.59 kg ha⁻¹). These values were significantly greater than those recorded in Alabama (2021), where total N uptake was similar for both application rates (41.40 kg ha⁻¹ for 56 kg ha⁻¹ and 39.78 kg ha⁻¹ for 112 kg ha⁻¹). In Georgia (2020), total N uptake at harvest was not statistically analyzed due to missing data.

At the SD stage, in Georgia (2020), the N_eme 112 kg ha⁻¹ resulted in significantly higher soil total N (83.54 kg ha⁻¹) compared to the N_eme 56 kg ha⁻¹ (24.36 kg ha⁻¹). In Alabama (2022), there were no significant differences in soil total N results between the N_eme 112 kg ha⁻¹ (66.41 kg ha⁻¹) and the N_eme 56 kg ha⁻¹ (53.93 kg ha⁻¹). In Alabama (2021), soil total N levels were lower than those measured in Georgia (2020) and Alabama (2022), with no significant differences between application rates (3.78 kg ha⁻¹ for N_eme 56 kg ha⁻¹ and 2.99 kg ha⁻¹ for N_eme 112 kg ha⁻¹).

3.6. Effect of the Interaction Between Location and N_sd on Leaf Area Index, Biomass Accumulation, and Total Nitrogen Across Growth Stages

The interaction between location and N_sd significantly impacted LAI at the EME stage, biomass accumulation at the SD stage, and total N uptake at the EME and SD stages (

Table 7. Effect of the interaction between location and N_sd on leaf area index, biomass accumulation, and total nitrogen uptake across growth stages.

Nsd 1 (kg ha−1)	Georgia (2020)	Alabama (2021)	Alabama (2022)
	EME 2
	LAI (cm2) 3
134	303 a 4 C 5	777 bB	1467 aA
162	322 aC	814 abB	1335 abA
190	344 aC	965 aB	1268 bA
p-value 6	*	*	*
Nsd (kg ha−1)	SD 7
	Biomass (kg ha−1)
134	1179 aC	2116 aB	3217 aA
162	1573 aB	1890 aB	2724 bA
190	1475 aC	2035 aB	3095 aA
p-value	*	*	*
Nsd (kg ha−1)	EME
	Total N uptale (kg ha−1)
134	-	13.00 aB	67.58 aA
162	-	15.01 aA	21.36 bA
190	-	17.71 aA	20.67 bA
p-value	-	*	*
Nsd (kg ha−1)	SD
	Total N uptake (kg ha−1)
134	41.91 aB	57.37 aB	96.44 aA
162	53.83 aB	50.52 aB	83.18 bA
190	50.54 aB	52.61 aB	102.61 aA
p-value	*	*	*

¹ N_sd: nitrogen application at side-dress stage. ² EME: emergence stage sampling. ³ LAI: leaf area index. ⁴ Values followed by similar lowercase letters among N_sd within each location indicate no significant difference (p > 0.05) according to Tukey’s mean test. ⁵ Values followed by similar uppercase letters among locations within each N_sd indicate no significant difference (p > 0.05) according to Tukey’s mean test. ⁶ Levels of significance (p-value): *, significant at p ≤ 0.05. ⁷ SD: side-dress stage sampling.

).

At the EME stage, LAI increased with higher N_sd rates in Georgia (2020) and Alabama (2021) but increased with lower N_sd rates in Alabama (2022). In Georgia (2020), LAI ranged from 303 cm² for N_sd 134 kg ha⁻¹ to 344 cm² for N_sd 190 kg ha⁻¹, with no significant differences among application rates. These values were significantly lower than those recorded in Alabama (2021 and 2022). In Alabama (2021), LAI increased with higher N_sd applications, with 965 cm² recorded for the 190 kg ha⁻¹, significantly higher than the 777 cm² recorded for the N_sd 134 kg ha⁻¹. In contrast, in Alabama (2022), the highest LAI value was measured at N_sd 134 kg ha⁻¹ (1467 cm²), while the lowest LAI was recorded at N_sd 190 kg ha⁻¹ (1268 cm²).

Total N uptake at the EME and SD stages was significantly affected by location and N_sd. At the EME stage, in Alabama (2022), N_sd 134 kg ha⁻¹ recorded the highest total N uptake (67.58 kg ha⁻¹). In Alabama (2021), total N uptake ranged from 13.00 kg ha⁻¹ for N_sd 134 kg ha⁻¹ to 17.71 kg ha⁻¹ for N_sd 190 kg ha⁻¹. Total N uptake for Georgia (2020) was not analyzed due to missing data. At the SD stage, in Alabama (2022), no significant differences were measured between N_sd 134 kg ha⁻¹ (96.44 kg ha⁻¹) and N_sd 190 kg ha⁻¹ (102.61 kg ha⁻¹). In contrast, Alabama (2021) and Georgia (2020) showed lower total N uptake, with no significant differences among N_sd.

Biomass accumulation was also significantly influenced by the interaction between location and N_sd. Alabama (2022) exhibited the highest biomass values across all locations, with 3217 kg ha⁻¹ for N_sd 134 kg ha⁻¹, followed by 3095 kg ha⁻¹ for N_sd 190 kg ha⁻¹, and 2724 kg ha⁻¹ for N_sd 162 kg ha⁻¹. Lower biomass values were recorded in Alabama (2021), where the highest value, 2116 kg ha⁻¹, was measured for N_sd 134 kg ha⁻¹, with no significant differences compared to other application rates. Georgia (2020) showed the lowest biomass values across all locations, with the highest biomass recorded for N_sd 162 kg ha⁻¹ (1573 kg ha⁻¹). However, no significant differences were measured between N_sd 162 kg ha⁻¹, N_sd 190 kg ha⁻¹ (1475 kg ha⁻¹), and N_sd 134 kg ha⁻¹ (1179 kg ha⁻¹).

3.7. Effect of Location on Sweet Corn Yield and Ear Structure Parameters

Location had a significant effect on sweet corn yield, ears per plant, ED, EL, KIR, and KTG, with significant differences measured among all locations (

Table 8. Effect of location on yield, ears per plant, ear diameter, ear length, number of kernels in an ear row, and total number of kernels per ear.

Location	Yield (kg ha−1)	Ears per Plant	ED 1 (cm)	EL 2 (cm)	KIR 3	KTG 4
Georgia (2020)	15,951 ab 5	1 b	4.17 c	17 c	33 a	472 ab
Alabama (2021)	14,470 b	1 b	4.77 a	18 b	36 a	503 ab
Alabama (2022)	17,380 a	1.13 a	4.49 b	19 a	30 b	437 b
p-value 6	***	***	***	***	***	**

¹ ED: ear diameter. ² EL: ear length. ³ KIR: number of kernels in an ear row. ⁴ KTG: total number of kernels per ear. ⁵ Values followed by similar lowercase letters among locations indicate no significant difference (p > 0.05) according to Tukey’s mean test. ⁶ Levels of significance (p-value): **, significant at p ≤ 0.01; ***, significant at p ≤ 0.001.

).

Sweet corn yield was highest in Alabama (2022), with a recorded value of 17,380 kg ha⁻¹, which was significantly greater than Georgia (2020) (15,951 kg ha⁻¹) and Alabama (2021) (14,470 kg ha⁻¹). The number of ears per plant was also significantly higher in Alabama (2022) (1.13 ears per plant) compared to Alabama (2021) and Georgia (2020) (both recorded 1 ear per plant). For ED, Alabama (2021) produced the largest ear diameter (4.77 cm), significantly greater than both Alabama (2022) (4.49 cm) and Georgia (2020) (4.17 cm). The longest ears were measured in Alabama (2022) (19 cm), which were significantly longer than those in Alabama (2021) (18 cm) and Georgia (2020) (17 cm).

Kernel characteristics, including KIR and KTG, also showed significant variations across locations. Alabama (2021) and Georgia (2020) had the highest KIR (36 and 33, respectively), while Alabama (2022) recorded the lowest value (30). For KTG, Alabama (2021) achieved the highest value (503 grains), though not significantly different from Georgia (2020) (472 grains). Alabama (2022) recorded the lowest KTG (437 grains).

3.8. Nitrogen Use Efficiency

The NUE was analyzed across various growth stages, and the results are summarized in

Table 9. Effect of location, N_eme application, and N_sd application on nitrogen use efficiency at emergence, side-dress, silk, and harvest stages.

	NUEeme 1 (%)	NUEsd 2 (%)	NUEsilk 3 (%)	NUEharv 4 (%)
Location
Georgia (2020)	-	43.0 b	15.5 b	21.0 b
Alabama (2021)	23.0 b 5	37.5 b	22.1 b	13.2 c
Alabama (2022)	28.9 a	60.6 a	51.0 a	51.6 a
p-value 6	*	***	***	***
Neme 7 (kg ha−1)
56	26.5 a	58.8 a	31.7 a	29.3 a
112	25.4 a	35.2 b	27.3 b	27.8 a
p-value	ns	***	*	ns
Nsd 8 (kg ha−1)
134	25.9 a	46.3 a	33.7 a	29.8 ab
162	25.2 a	45.2 a	27.6 b	30.5 a
190	26.8 a	49.5 a	27.2 b	25.4 b
p-value	ns	ns	*	**
Location*Neme	ns	ns	ns	ns
Location*Nsd	ns	ns	ns	ns
Neme*Nsd	ns	ns	ns	ns
Location*Neme*Nsd	ns	ns	ns	ns

¹ NUE_eme: Nitrogen use efficiency at emergence stage sampling. ² NUE_sd: Nitrogen use efficiency at side-dress stage sampling. ³ NUE_silk: Nitrogen use efficiency at silk stage sampling. ⁴ NUE_harv: Nitrogen use efficiency at harvest stage sampling. ⁵ Values followed by similar lowercase letters within a column for each factor (location, N_eme, or N_sd) indicate no significant difference (p > 0.05) according to Tukey’s mean test. ⁶ Levels of significance (p-value): ns, non-significant; *, significant at p ≤ 0.05; **, significant at p ≤ 0.01; ***, significant at p ≤ 0.001. ⁷ N_eme: application at emergence stage. ⁸ N_sd: application at side-dress stage.

. There were no significant interactions between location, N_eme, and N_sd on NUE at the emergence stage (NUE_eme), side-dress stage (NUE_sd), silk stage (NUE_silk), or harvest stage (NUE_harv). However, location had a significant effect on NUE_eme, NUE_sd, NUE_silk, and NUE_harv.

The highest NUE_eme was recorded in Alabama (2022) (28.9%), followed by Alabama (2021) (23.0%). No data were reported for Georgia (2020). For NUE_sd, Alabama (2022) also achieved the highest value (60.6%), followed by Georgia (2020) (43.0%) and Alabama (2021) (37.5%). Similarly, NUE_silk was highest in Alabama (2022) (51.0%), which was significantly greater than Alabama (2021) (22.1%) and Georgia (2020) (15.5%). At the harvest stage, the highest NUE_harv was measured in Alabama (2022) (51.6%), followed by Georgia (2020) (21.0%) and Alabama (2021) (13.2%).

The N_eme and N_sd significantly influenced NUE at specific stages (Table 9). For NUE_sd, the N_eme 56 kg ha⁻¹ recorded a significantly higher value (58.8%) compared to the N_eme 112 kg ha⁻¹ (35.2%). Similarly, for NUE_silk, the N_eme 56 kg ha⁻¹ was significantly greater (31.7%) than N_eme 112 kg ha⁻¹ (27.3%).

For N_sd, NUE_silk was significantly higher at an application rate of 134 kg ha⁻¹ (33.7%), compared to 162 kg ha⁻¹ (27.6%) and 190 kg ha⁻¹ (27.2%). At the harvest stage, NUE_harv was highest for N_sd 162 kg ha⁻¹ (30.5%), followed by N_sd 134 kg ha⁻¹ (29.8%) and N_sd 190 kg ha⁻¹ (25.4%).

3.9. Correlation Analysis

The Pearson correlation analysis (Figure 3) revealed that sweet corn yield was positively correlated with the number of ears per plant, ear weight (EW), biomass (BD), total N (TKN), NUE, and EL. In contrast, yield was negatively correlated with KIR and KTG.

The NUE showed positive correlations with the number of ears per plant, BD, TKN, and EL but was negatively correlated with KIR and KTG. Similarly, LAI was positively correlated with EW and BD. Biomass exhibited positive correlations with the number of ears per plant, EW, EL, and TKN but negatively correlated with KIR and KTG. TKN was positively correlated with the number of ears per plant, EL, and soil total N (SN) but was negatively correlated with KIR and KTG. SN was positively correlated with ED. KIR was positively correlated only with KTG, while KTG was also positively correlated with KR.

4. Discussion

This study evaluates the effects of N fertilizer rates and application timings on sweet corn growth and yield in the southeastern US, focusing on balancing agronomic productivity and environmental sustainability. The findings provide valuable insights into N management strategies for sweet corn cultivation under the unique climatic and soil conditions prevalent in the region.

The N fertilizer application rate and timing were critical for achieving high productivity and profitability in sweet corn production [7]. Sweet corn responded differently to N rates depending on environmental conditions, as evidenced by previous studies [7,22]. Proper selection of N rates and application timing is essential for improving yield and ear structure traits, such as ear diameter, ear length, number of ears per plant, and ear weight [4,22,23]. Conversely, excessive N applications can reduce plant growth, impair ear structure, and increase environmental risks [2,14].

Environmental factors, including temperature, rainfall, and drought, significantly influenced N uptake and sweet corn performance [24]. While warm temperatures enhance metabolic activity and N uptake, excessive heat can induce plant stress, thereby reducing nutrient uptake efficiency [25,26]. Adequate moisture supports N uptake, but heavy rainfall may lead to N leaching, while drought reduces N availability and uptake, ultimately lowering yields [2,27]. The sandy to loamy sandy soils prevalent in the southeastern US intensify leaching during heavy rainfall due to their low water-holding capacity [27,28,29].

Rainfall patterns in this study significantly influenced N availability and sweet corn performance. In Georgia (2020), heavy rainfall on the day of N_eme fertilization (19 DAP) likely caused N leaching, as evidenced by low soil total N levels at the EME stage. Following N_sd fertilization, limited rainfall (14.5 mm over 18 days) reduced soil moisture, thereby limiting N uptake, biomass accumulation, and yield [30]. In Alabama (2021), substantial rainfall after N_eme (70 mm) and N_sd (71 mm) fertilization caused N leaching, leading to reduced soil total N, lower biomass accumulation, and lower total N uptake compared to Alabama (2022). In contrast, Alabama (2022) experienced well-distributed rainfall, achieving a balance between adequate soil moisture and manageable N leaching, resulting in higher soil total N and improved N uptake at critical growth stages, including EME, SD, and silk.

Accumulated GDD also influenced sweet corn performance [31,32]. Alabama (2022) had the highest GDD, supporting prolonged and consistent crop development, which resulted in the highest yields (17,380 kg ha⁻¹) [25,31]. In contrast, Georgia (2020) and Alabama (2021) exhibited lower GDD, limiting crop growth durations and reducing yields (15,951 kg ha⁻¹ and 14,470 kg ha⁻¹, respectively).

Location-specific factors significantly influenced LAI, biomass accumulation, total N, and soil total N at all growth stages. Alabama (2022) consistently outperformed other locations, achieving the highest LAI, biomass, and total N at the EME stage, likely due to favorable environmental conditions rather than variations in N rate, as the N_pl (34 kg N ha⁻¹) was uniform across locations [2,4,27]. At the SD and silk stages, Alabama (2022) maintained superior LAI, biomass, and total N levels, reflecting effective utilization of applied N under favorable climatic conditions [7,22,24]. The high soil total N measured in Alabama (2021) during the silk stage suggests non-utilized N due to constrained crop development under less favorable conditions. At harvest, Alabama (2022) recorded the highest biomass and total N, underscoring the cumulative advantages of optimal conditions and effective N management [24].

The variation in parameters across growth stages highlights the importance of phenological stages in plant growth and nutrient uptake [30,33,34]. The higher values of biomass accumulation measured at the silk stage suggest that this stage is a critical period for resource allocation and plant growth [34]. This finding aligns with the well-established understanding that the silk stage represents a peak in photosynthetic capacity and nutrient demand [35,36]. Similarly, the highest LAI values measured at the SD stage indicate a critical period in crop development, as supported by recent studies [36,37,38]. Total nitrogen and soil total N showed distinctive patterns, with increases up to silk or harvest, depending on the location. These trends highlight the dynamic interaction between plant nutrient demand, soil N availability, and environmental factors across phenological stages.

N_eme significantly influenced biomass accumulation, total N, and soil total N across growth stages. At the SD stage, the N_eme 56 kg ha⁻¹ produced higher biomass (2298 kg ha⁻¹) than N_eme 112 kg ha⁻¹ (1992 kg ha⁻¹), indicating that lower N rates better matched early-stage nutrient demands [39,40]. However, by the silk stage, this initial advantage diminished, with no significant differences in biomass measured. Total N at the SD stage was higher under N_eme 56 kg ha⁻¹ (69.5 kg ha⁻¹) compared to N_eme 112 kg ha⁻¹ (61.4 kg ha⁻¹), highlighting the efficiency of lower N rates at earlier growth stages. At harvest, total N levels were similar between N application rates, suggesting that both rates supplied sufficient N for the crop to reach its full physiological potential by harvest [41]. Higher soil total N under N_eme 112 kg ha⁻¹ (50.9 kg ha⁻¹) compared to N_eme 56 kg ha⁻¹ (27.3 kg ha⁻¹) suggests increased residual N, raising concerns about potential leaching under heavy rainfall [42,43].

For N_sd, soil total N at the silk stage increased with higher N_sd rates, with the N_sd 190 kg ha⁻¹ achieving the highest soil total N (138.9 kg ha⁻¹). While this could benefit late-stage development, it also highlights the risk of excessive residual N and potential environmental losses [42,43,44,45].

Sweet corn yield, ear productivity, and kernel structure varied significantly by location. Alabama (2022) recorded the highest yield (17,380 kg ha⁻¹), ears per plant (1.13), and EL (19 cm). These factors, which are positively correlated, underscore the importance of optimal growing conditions, including favorable temperatures, moderate N applications (224–280 kg ha⁻¹), adequate rainfall, and high GDD [4,7,25,44,45,46].

NUE measures how effectively plants use applied N [29,41]. Alabama (2022) achieved the highest NUE across all growth stages (NUE_eme, NUE_sd, NUE_silk, and NUE_harv), reflecting the combined benefits of favorable environmental conditions and precise N management [29,47]. Enhanced NUE was measured with a low N_pl rate (34 kg ha⁻¹), combined with a N_eme rate of 56 kg ha⁻¹ and a moderate N_sd rate (134–162 hg ha⁻¹). These practices emphasize the value of split N applications in improving N uptake, reducing leaching, and minimizing environmental risks [12,29].

Therefore, moderate N application rates (224–280 kg ha⁻¹) appear to provide an optimal balance between crop productivity, N efficiency, and soil health, particularly under conditions where environmental factors align to support crop growth. This range aligns with the measured results in Alabama (2022), where moderate N rates, combined with favorable rainfall and GDD, contributed to superior crop performance.

5. Conclusions

This study demonstrates the importance of selecting appropriate N fertilization rates and application timings to enhance sweet corn growth and yield under the subtropical environmental conditions of the southeastern US. Moderate N rates (224–280 kg ha⁻¹) combined with split applications significantly improved sweet corn growth and yield while minimizing environmental risks. In Alabama (2022), the highest yields (17,380 kg ha⁻¹) and NUE were achieved with the use of moderate N rates combined with favorable rainfall distribution patterns. This highlights the importance of integrating environmental variability into N management strategies. The findings suggest that growers can adopt lower N rates (N_pl: 34 kg ha⁻¹; N_eme: 56 kg ha⁻¹) during planting and early growth stages, along with moderate N rate applications (N_sd: 134–162 hg ha⁻¹) at critical development stages to achieve a balance between productivity and sustainability. Future research should focus on integrating advanced modeling and precision agriculture technologies to refine site-specific N recommendations, accounting for inter-annual climatic variability. By adopting these practices, growers can enhance resource use efficiency, improve economic returns, and contribute to the sustainability of sweet corn production systems in the southeastern US and similar regions.