Subsurface banding increases ammonia emissions under rainfed cotton in Florida sandy soils

Abstract

Ammonia (NH₃) volatilization is a significant pathway for nitrogen (N) loss. The acidic, sandy soils of Florida offer ideal conditions for NH₃ losses in rainfed cotton production systems. To assess NH₃ losses under various N placement methods and rates, the experiment was conducted in 2023 and 2024 using a randomized complete block design with four replications. The study employed two placement methods: surface broadcasting and subsurface banding, and two N rates: 67.5 and 102 kg N/ha. Ammonia emissions were measured using open-chamber traps, with sampling conducted multiple times per week. Daily NH₃ emissions (g/ha/day) were averaged over each week, and cumulative emissions (g/ha) were calculated by summing weekly averages across the sampling period. These cumulative values were then used to estimate total NH₃-N losses, expressed as a percentage of the total N applied. Sampling weeks were referenced as WAF (weeks after fertilization) to standardize timing across both years. Results indicated that both daily and cumulative NH₃; emissions were significantly higher with subsurface banding compared to surface broadcasting, leading to greater N-NH₃; losses under banding. In addition, neither placement method nor N rate significantly influenced cotton lint yield. These findings suggest that, under the conditions of this study, subsurface banding increased NH₃ volatilization losses in rainfed cotton grown on sandy soils in Florida.

1 Introduction

Global agricultural production has increased over the past century, along with the increased use of nitrogen (N) fertilizers (FAO, 2020). The increased use of N fertilizers has led to higher N losses through ammonia (NH₃) volatilization, nitrate leaching, and nitrous oxide emissions, resulting in harmful environmental impacts (Stark and Richards, 2008). These losses can result in lower nitrogen use efficiency (NUE). According to Delgado (2002), global NUE ranges between 33% and 50%, and unaccounted N can be more than $15 billion, resulting in high economic losses. Lower NUE indicates higher N losses, and NH₃ volatilization is a major concern, as more than 60% of applied N can be lost through volatilization (Rochette et al., 2013). However, N fertilizer placement can improve NUE by reducing N losses and enhancing N conservation in soil (Reiter et al., 2008; Li et al., 2018; McClanahan et al., 2020; Singh et al., 2023).

Surface application, such as broadcasting, exposes fertilizers to rapid volatilization due to greater NH₃ diffusion into the atmosphere (Götze et al., 2023). In contrast, subsurface banding is reported to reduce volatilization losses by increasing NH₄⁺ retention and limiting NH₃ escape (Nkebiwe et al., 2016). Previous studies have demonstrated that banded N remains available to crops for a longer duration and enhances fertilizer use efficiency compared to broadcast applications (Canatoy et al., 2024). The field studies have reported one to nine times lower NH₃ losses under subsurface banding of fertilizer compared to surface broadcasting (Bouwman et al., 2002; Prasertsak et al., 2002). However, several studies have reported contradicting results showcasing higher NH₃ losses under subsurface band than surface broadcasting (Rochette et al., 2009a, 2009b).

Ammoniacal N fertilizers, such as urea, undergo conversion to NH₄⁺ and nitrate to be available for plant uptake, a process that begins with urease enzyme-mediated hydrolysis in the soil (Wang et al., 2014, Motasim et al., 2024). The hydrolysis process is facilitated by the consumption of H⁺ ions from the soil, resulting in an increase in soil pH in the vicinity of applied urea (Harty et al., 2023). Increasing soil pH can increase NH₃ concentration and, thus, increased NH₃ volatilization. However, the changes in pH depend on soil buffering capacity and concentration of NH₃ source in soil, influencing the emissions (Rochette et al., 2009a; Harty et al., 2023). The banding of a large amount of N can result in a higher soil pH and may lead to increased NH₃ volatilization, especially in soils with low buffering capacity (Rochette et al., 2009a). Therefore, the efficiency of placement methods to improve NH₃ volatilization depends on soil properties and microbial activity.

In the Florida Panhandle, sandy-textured soils combined with low pH result in a very low buffering capacity, making the soil highly susceptible to pH changes following N fertilization. Surface broadcasting of N fertilizers, a common practice among farmers in this region, often leads to substantial NH₃ volatilization losses, particularly under the humid environmental conditions prevalent in the Panhandle. Among commonly used fertilizers, urea is especially prone to such losses when left exposed on the soil surface. Given these challenges and mixed effect of subsurface band in literature, there is a critical need to evaluate subsurface banding NH₃ volatilization under these conditions as an alternative placement method. Therefore, we conducted a two-year field study to assess the effectiveness of subsurface banding compared to surface broadcasting in reducing NH₃ emissions. We hypothesized that subsurface banding would reduce the NH₃ emissions compared to surface broadcasting.

2 Materials and methods

2.1 Experiment site and materials

Field experiments were conducted in 2023 and 2024 at the University of Florida/IFAS West Florida Research and Extension Center, Jay, FL (30°46′34.5″N, 87°08′15.9″W). Although both trials were conducted at the same research station, they were established in different fields each year to accommodate spatial variability and maintain consistent rotation practices across the station. Soil at the experimental site was a Red Bay fine sandy loam (fine-loamy, kaolinitic, thermic Rhodic Kandiudults) with 0 to 2% slope. The soil properties for both study years are listed in Table 1. For 2023, soil pH was 6.4 and CEC was 7.5 cmol/kg, and for 2024, soil pH was 6.3 and CEC was 8.8 cmol/kg. The minor differences in initial soil pH and CEC between years reflect this inherent variability across field locations within the research station. Weather data during the study were collected from stations operated by the Florida Automated Weather Network, located within 1 km of the experimental site. The field was disked, leveled with a field cultivator, and strip-tilled before planting. Cotton was planted at a seed rate of 89,700 seeds/ha with 91 cm row spacing in 7.62 m × 3.65 m plots using Monosem planter (Monosem NG Plus, A.T.I. Inc., Kansas). Pre-plant soil samples (0–0.30 m depth) were taken in March for both years and were sent to Waters Lab, Camilla, GA, for analysis using Mehlich 3 method (Ziadi and Tran, 2007). Basal fertilizers were applied using Waters lab recommendation, excluding N.

2.2 Experimental design and treatments

The experiment followed a randomized complete block design with a 2 × 2 factorial arrangement and four replications. The treatments consisted of two N application rates (67.5 kg N/ha and 102 kg N/ha) and two N placement methods (surface broadcast and subsurface banding). Urea (46-0-0) (Nutrien Ag., Loveland, CO) was applied in two splits: 33.3% at emergence (3 weeks after planting) and 66.6% before the pinhead growth stage (6–7 weeks after planting). Urea was applied using a Gandy spreader (Gandy Company, Owatonna, MN) for broadcast treatments and a band applicator (First Products, Tifton, GA) for subsurface banding (at >5 cm depth). The depth below 5 cm represents the subsurface banding practice adapted at our research site to ensure soil coverage of fertilizer. Other than that, literature highlights depths above 5 cm as the optimum depth to decrease the diffusion of NH₃ into the atmosphere (Canatoy et al., 2024). Ammonia traps were deployed before each fertilizer application.

2.3 Ammonia measurement

Ammonia sampling was conducted using open-chamber traps as described by Jantalia et al. (2012). These traps, placed between the second and third rows of cotton, consisted of cotton wicks soaked in sulfuric acid to capture NH₃. The wicks and containers were replaced at each sampling to ensure accurate measurements. To protect the traps from rainfall and maintain sampling consistency, each trap was covered by attaching the bottom half of a plastic bottle over the top of the chamber (Supplementary Figure 1). Following rainfall events, any wet traps were promptly replaced with dry ones to minimize sampling bias and ensure data reliability. Each collected sample was analyzed for NH₃ concentration using a phenol-hypochlorite assay, which measured absorbance at 630 nm using a spectrometer (Thermo Fisher Scientific, Waltham, MA). A standard curve was generated using predetermined concentrations of NH₃-N ranging from 0 to 8 mM, and absorbance values were plotted against millimolar concentrations of NH₃-N. The relationship between absorbance (y) and NH₃-N concentration in millimolar (x) was described by the linear regression Equation 1:

This equation was used to convert absorbance values to NH₃-N concentration (mM) which was converted to milligrams (mg). The trap area (0.01008 m²) was used to calculate the amount of fertilizer (mg) applied in that specific area.

Sampling was done over multiple days in a week, and daily NH₃ emissions (g/ha/day) were averaged over weeks. Averaging daily values helped reduce variability caused by day-to-day fluctuations in weather conditions, thereby improving data interpretability and allowing for clearer comparisons across treatments. However, this conservative approach may have limited the detection of short-term emission peaks that could occur immediately following fertilization or rainfall events. Despite this limitation, the method aligned with our primary objective of assessing broader emission trends under different N management practices.

Daily NH₃ emissions over weeks were summed to calculate cumulative NH₃ emissions (g/ha). These cumulative NH₃ emissions were used to determine total NH₃-N losses (%) as percentage loss of total applied N. In this study, “NH₃ emissions” represents the emission loss on a weekly basis from the treatments, whereas “NH₃-N loss” represents the percentage of N applied which was lost as NH₃.

In 2023, samples were taken at 1, 2, 3, 4, and 5 weeks after fertilization (WAF). In 2024, samples were collected at 1, 2, 3, 4, 5, 6, 7, 8, and 9 WAF. The WAF represents weeks after the first application. Sampling was continued after the second application in both years. In 2023, the second application was done at 3 WAF, whereas, in 2024, it was done at 4 WAF.

2.4 Lint yield estimation

Seed cotton yield was estimated by harvesting two non-border rows with a two-row John Deere cotton picker (John Deere, Moline, IL). Seed cotton subsample (300 g) was ginned using a micro-gin to determine lint turnout (%), which was then used to estimate lint yield.

2.5 Data analysis

Data was analyzed using the lmer (Nagle, 2018), agricolae (Kozak, 2020), and doebioresearch packages in R Studio (v 4.2.2) (R Core Team, 2021). A generalized linear mixed-effects model was employed, incorporating blocks and years as random effects and N placement methods and rates and their interaction as fixed effects. The data was assessed for constant variance using the Levene test and normality using the Shapiro-Wilk test, with log transformations applied when assumptions were violated. Treatment means were separated using the Tukey test at 95% significance level (p ≤ 0.05). Graphs were designed using the ggplot2 package in R studio (Wickham and Sievert, 2009).

3 Result and discussion

3.1 Daily and cumulative ammonia emissions, and total N-NH₃ loss (%)

For 2023, there was no significant difference in daily NH₃ emissions between the treatments at any time point (Figure 1A) (p = 0.81). The highest emissions were observed after the application of second fertilizer split (at 3 WAF) for all the treatments (Figure 1A). In 2023, fertilizer application was followed by heavy rainfall at both, which might have resulted in leaching down of N and resulted in no significant differences (Figure 2). However, in 2024, there was a significant effect of placement method on emissions (Figure 1B). Daily emissions were significantly higher under subsurface banding at 1 WAF (772 g/day/ha) as compared to surface broadcast (392 g/day/ha) (p = 0.028). However, there was no difference between daily emissions at any other time point. At 1 WAF, the first split was followed by a small amount of rain and dry period, which might have helped in the accumulation of NH₃ emissions. However, the second application was followed by constant rain, which might have resulted in leaching of N (Figure 2).

Figure 1

Figure 2

In 2023, a significant effect of the placement method on cumulative NH₃ emissions was observed (Figure 1C) (p = 0.01). The subsurface band resulted in significantly higher cumulative emissions (932 g/ha) compared to surface broadcast (860 g/ha) across both rates. In 2024, the interaction effect was observed on cumulative NH₃ emissions (Figure 1D) (p = 0.001). At 67.5 kg N/ha, there was no difference between the placement methods; however, surface broadcast resulted in reduced cumulative NH₃ emissions (2802 g/ha) at higher N rate (102 kg N/ha) than subsurface band (6502 g/ha).

Results from the current study indicate that the subsurface band was unable to reduce daily NH₃; emissions and cumulative NH₃; emissions compared to surface broadcast, which is contradictory to previous findings by Huijsmans et al. (2001); Bittman et al. (2005), and Pfluke et al. (2011). These studies reported that the subsurface band can reduce diffusion of NH₃ into the atmosphere by creating resistance or by reducing the surface area exposed to the atmosphere in surface band. However, NH₃ volatilization is influenced by the complex interactions among soil properties, the urease enzyme, placement method, and N rates. Surface broadcasting distributes fertilizer across a wider soil area, leading to lower localized concentrations. In contrast, subsurface banding concentrates urea in a narrow zone, resulting in higher N concentration and more intense pH increases in the surrounding soil (Rochette et al., 2009b; Tewolde et al., 2023). As mentioned earlier, the low buffering capacity of sandy soil can lead to higher soil pH under the subsurface band, resulting in higher NH₃ emissions and higher N-NH₃ losses. Under the sandy loam texture of acidic soils at research site, this localized pH spike can intensify NH₃; volatilization. This effect appeared more prominent at the higher N rate (102 kg N/ha), where subsurface banding resulted in 132% increase in NH₃; emissions compared to surface broadcast (Figure 1D). This interaction observed between placement and rate may therefore be attributed to the compounded effect of high N concentration and limited pH buffering in the band zone, amplifying NH₃; losses under banded applications at higher rates (Figure 3).

Figure 3

A significant effect of the placement methods was observed for total N-NH₃ loss (%) across 2023 and 2024 (p< 0.001) (Figure 4A). The subsurface band resulted in a significantly higher N loss (4.9%) compared to surface broadcast (3.1%). The NH₃-N losses were very low in general in the current study, which can be attributed to acidic nature soil, favoring NH₄⁺ than NH₃ (Harty et al., 2023). The higher NH₃-N losses under subsurface band can be explained by a higher concentration of N in bands. Our study focused on cotton production with 91-cm row spacing, resulting in a higher concentration of urea (g m^-1 of the band) in bands to compensate for the large row spacing (Rochette et al., 2009b) which might have resulted in higher NH₃-N losses (%). Similarly, Rochette et al. (2009b) reported higher NH₃ concentration and emissions with band application of urea than surface broadcasting. The authors also reported an increase in pH from 6.0 to 8.7 upon band application. From the results of the current study, we can infer that surface broadcasting is more efficient in managing NH₃ losses at higher N rates than subsurface banding on sandy soils.

Figure 4

3.2 Lint yield

There was no significant difference in lint yield among treatments across both study years (p = 0.46) (Figure 4B). Lint yield ranged from 1617 to 1732 kg/ha across all treatments. Although NH₃ losses were higher under subsurface band, the lint yield was comparable to surface broadcasting. Lint yield is a complex trait in cotton, influenced by the interplay of various factors, including weather conditions, soil properties, N availability, and N uptake (Cetin and Basbag, 2010). Nevertheless, the findings of the present study align with previous research (Warren et al., 2008; Halvorson and Del Grosso, 2013), which also reported no significant differences in yield between subsurface banding and surface broadcasting. The application through subsurface band results in a higher concentration of N in narrow bands, which can result in an increase in soil pH (Rochette et al., 2009b). The sudden changes in soil pH might result in a lower N uptake in cotton (Guo et al., 2022). The lower N uptake coupled with higher NH₃-N losses under subsurface band might have resulted in no differences in lint yield in the current study. Results of the current study are in contradiction with other studies which have reported a positive effect of subsurface band over surface broadcast in cotton and corn (Zea mays L.) (Tewolde et al., 2009; Tewolde et al., 2023). However, these studies differed from the current study in terms of N source and soil texture. Tewolde et al. (2009) used poultry litter in the experiment with N content of 2-3% whereas Tewolde et al. (2022) conducted experiment on clay loam soil, which has higher buffering capacity than sandy soil. The N uptake and NH₃ losses are influenced by soil properties and N sources, which might have resulted in contradicting results in the current study.

Considering the lack of yield advantage with subsurface banding and the higher NH₃; losses observed under this method, surface broadcasting may present a more practical option for growers in similar production systems. Furthermore, subsurface banding typically requires more passes and specialized equipment, resulting in higher labor and fuel demands, whereas surface broadcasting is faster and uses simpler machinery (Way et al., 2013). These factors, coupled with comparable lint yields, suggest that surface broadcasting may be a more efficient and feasible N placement method under the conditions of this study.

4 Conclusion

Subsurface band resulted in higher NH₃ emissions compared to surface broadcast. When N was applied at a higher rate, subsurface band resulted in significantly higher cumulative N-NH₃ emissions as compared to surface broadcast. Although NH₃ losses were higher under the subsurface band, there was no difference in lint yield between the subsurface band and surface broadcast. The findings of the current study highlight that subsurface banding was ineffective in reducing NH₃ losses in cotton production systems.

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