Abstract
Despite being a legume, snap bean (Phaseolus vulgaris L.) lacks nodulation genes, restricting its ability for nitrogen (N) fixation through rhizobia, making N fertilization essential for maximizing yields. However, conventional fertilizer application may lead to N losses due to a lack of synchronization between plant uptake and N availability. A promising option could be controlled-release fertilizers (CRFs), which can be custom-formulated to synchronize nutrient release with plant growth needs, promoting efficient resource use. Field studies were conducted at the North Florida Research and Education Center-Suwannee Valley (NFREC-SV) in Live Oak, FL, during the spring of 2021 and 2022. The experiments also investigated broadcasting and banding application methods of the University of Florida’s recommended N rate (112 kg·ha−1). The experimental design comprised 10 treatments, including five N rates (0, 56, 112, 168, and 224 kg·ha−1 N) and two fertilizer sources (ammonium nitrate and CRF), applied to ‘Caprice’ in a randomized complete block design with four replications. Results showed a significant yield improvement with N fertilization vs. the zero-N control. However, no yield increase was observed beyond 56 kg·ha−1. This finding could be due to the residual N from a preceding peanut crop rotation in both years. No notable variation in quality metrics (pod length and width) occurred above the 56 kg·ha−1 threshold. The results also revealed that the choice between conventional or CRF did not exert any statistically significant differences in snap bean yield. In addition, fertilizer broadcast and banding treatments yielded the same results.
Originating in Central and South America, snap bean (Phaseolus vulgaris L.) is a significant legume crop. It belongs to the family Fabaceae (Swiader et al. 1992) and is cultivated primarily for its immature pods in regions spanning from Eastern Africa and South America to Eastern Asia and North and Central America, as well as Western and Southeastern Europe (Adams et al. 1985). Snap bean is renowned for high protein levels (Baudoin and Maquet 1999; Mahmoud et al. 2022), vitamins, and dietary fiber. It is also known as green bean, French bean, and string bean (Kelly and Scott 1992). Global consumption of snap bean is increasing because of the growing demand for dried vegetables in the production of health-oriented snack foods (Negash and Getachew 2019).
According to the Food and Agriculture Organization (FAO), the global harvested area for snap bean in 2019 was 33.1 million hectares, with a production of 28.9 million tons (FAOSTAT 2020). The United States is responsible for 71% of the world’s production, and the average American consumes 3.0 kg of snap bean annually (Nadeem et al. 2020). Florida ranks second for the production of snap bean, accounting for 14.3% of the national total. Florida, however, ranks first in the country in terms of total cash receipts, with a 35.3% share, followed by Wisconsin and Georgia (US Department of Agriculture, National Agricultural Statistics Service 2024; US Department of Agriculture, Economic Research Services 2024). Although Wisconsin showed the highest yield (16,320 kg·ha−1), the price received per ton was the lowest among all producing states, whereas Florida has the eighth highest yield (7030 kg·ha−1) and it shows the third highest price received per ton of snap bean (US Department of Agriculture, National Agricultural Statistics Service 2024). Enhancing productivity factors has placed greater emphasis on producing snap bean with high-yield and high-quality pods.
The application of appropriate nitrogen (N) fertilizer rates has played a pivotal role in augmenting the growth and yield of snap bean. N is an essential macronutrient for plant growth and development and is required in large quantities. It is an integral component of proteins, metabolic intermediates, and nucleic acids (Goh and Haynes 1986; Salisbury and Ross 1991). Although N is abundant in the atmosphere as an inert gas (N2), it is not readily available to plants. However, certain bacteria such as Azotobactor and Rhizobium perform biological N fixation to convert N2 into ammonia (NH3), which is further converted to ammonium (NH4+) and then to nitrate (NO3−), a form readily absorbed by the plants. This process involves nitrogenase, a biological N fixation enzyme located within root nodules, facilitating the conversion of atmospheric N. Nonetheless, most croplands still require extra N to attain maximum yields beyond what is already present in the soil. As a result, agricultural systems frequently receive additional N as fertilizers.
Global demand for N fertilizer is projected to reach ∼112 million tons to sustain food production for ≈8 billion people (Gao et al. 2022). Snap bean does not possess nodular genes, leading to restricted nodulation ability that makes the plant less efficient in fixing biological N (Kushwaha 1994). Numerous studies indicate that low root zone soil N content may hinder snap bean cultivation, leading to yield reductions (Araújo et al. 1997; Lynch and White 1992). Providing an adequate N supply to snap bean is crucial for achieving maximum yield, particularly in sandy soils and low organic matter environments where N content tends to be limited. However, N fertilization needs to be implemented with caution, because N is a dynamic element that is consistently at risk of being lost through various pathways like leaching, volatilization, and denitrification (Bowles et al. 2018). Estimates indicate that more than 50% of applied N fertilizer is lost to the environment, resulting in a spectrum of environmental repercussions, including the pollution of ground and surface water bodies, acid rain, and greenhouse gas emissions (Ayele and Atlabachew 2021; Cen et al. 2021; Lapointe et al. 2019; Penuelas et al. 2020; Puga et al. 2019; Wang et al. 2019).
Reports indicate an annual discharge of ∼50 million tons of reactive N into the environment (Bodirsky et al. 2014). Suwannee River Basin (SRB) water bodies have been recognized as nitrate-impaired with the nitrate source primarily attributed to farm-applied fertilizers (Rath et al. 2021). During the past decade, SRB has experienced increased algal blooms in its springs and rivers, prompting the state to intensify its focus on pollution prevention measures. In 1972, the US Congress enacted the Federal Clean Water Act (FCWA) with the purpose of addressing this issue. In response to the FCWA, the Florida Department of Environmental Protection introduced the Total Maximum Daily Load (TMDL) target to be achieved in 20 years for each Basin Management Action Plan. The primary objective of creating TMDL was to define the maximum allowable levels of pollutants that a water body could receive while still adhering to water quality standards (Davis et al. 2018). To achieve the TMDL’s objective of reducing nutrient runoff from farms, it is advisable to implement Best Management Practices (BMPs). BMPs, as per Florida Statutes Chapter 576, are defined as practices or a combination of practices, as determined through research or field testing in representative locations and have been found to be the most effective and feasible approaches for fertilization. These approaches are designed to align with nitrate groundwater quality standards while also taking into account economic and technological factors. By implementing BMPs, enhanced nutrient use efficiency can be achieved, ensuring that the nutrients are properly used, thereby mitigating losses due to leaching, runoff, or volatilization (Liu et al. 2013).
Crop nutrient requirements follow a dynamic pattern: they begin low in the early growth stage, increase sharply in the middle stage, and decrease somewhat in the late stage. Enhancing the synchronization between N supply and crop demand is a fundamental approach to enhance nitrogen use efficiency (Fageria and Baligar 2005). Conventional fertilizer-N (e.g., ammonium nitrate) is water-soluble and becomes immediately available after application; however, it is more susceptible to losses if not readily taken up by the plants. The use of CRF offers the potential to synchronize the pattern of nutrient release with crop demand, thereby optimizing nutrient use efficiency and increasing plant biomass, while reducing nutrient losses in the environment, especially in irrigated sandy soils (Liegel and Walsh 1976) commonly found in Florida. In fact, CRF has been shown to be beneficial in minimizing N leaching in vegetable production systems with sandy soils (Hartz and Smith 2009; Simonne and Hutchinson 2005). Moreover, the rapid growth rate of snap bean (e.g., some cultivars are harvested around 60 d after planting) provides a small window for adequate fertilizer application without any yield impairment.
Although the University of Florida recommends the application of 112 kg of N/ha to snap bean, most of the research to develop such N recommendations was conducted in South Florida. Therefore, it is important to not only investigate and validate such N rates in North Florida, but also to study the source, rate, and method of applications to address three out of the four Rs in nutrient stewardship (i.e., right rate, right placement, right source, and right timing). Considering these factors, the aim of the present study was to compare two sources of N [conventional N fertilizer (ammonium nitrate) and CRF] applied at five N rates. The study also compared two methods of application (broadcasting and banding) at the current recommended N rate.
Material and methods
Location
This study was conducted at the North Florida Research and Education Center-Suwannee Valley (NFREC-SV) in Live Oak, Florida, in the spring seasons of 2021 and 2022 (Fig. 1). Each trial included 40 plots arranged in a randomized complete block design, with 10 treatments, which were a combination of varying N rates (0, 56, 112, 168, and 224 kg·ha−1 N) and sources of N (conventional fertilizer and CRF), and four replications. The number of treatments, sources, rates, and methods of N application is shown in Table 1.
Research experiment sites (A) in Spring 2022 (B) and 2021 (C) growing seasons, respectively, at the North Florida Research and Education Center-Suwannee Valley, Live Oak, FL, USA.
Citation: HortTechnology 34, 5; 10.21273/HORTTECH05442-24
Conventional and controlled-release nitrogen (N) fertilizer treatments implemented for snap bean evaluation in 2021 and 2022.
Soil
Soil orders in the experimental area were Entisol (Chipley-Foxworth-Albany soil complex) and Spodosol (Hurricane, Albany, and Chipley soil series) for 2021 and 2022 growing seasons, respectively. The soil texture was predominantly sandy, with a sand concentration of 94.5% for both series. The trial area for both years was in a full-season peanut (Arachis hypogaea) crop during the prior summer seasons of 2020 and 2021.
Fertilizer sources and application methods
A polymer-coated controlled-release nitrogen fertilizer 40–0–0 (N–P2O5–K2O) (Harrell’s Fertilizer LLC, Lakeland, FL, USA) and ammonium nitrate fertilizer 32–0–0 (N–P2O5–K2O) were used as the sources of N. Both CRF and conventional fertilizers were applied in bands using a drop fertilizer applicator (First Products Inc., Tifton, GA, USA). The “band” was a modified band over the row, resulting in a 30- to 38-cm-wide swath of fertilizer (Fig. 2). Broadcast applications were made with the same applicator but evenly distributed across the plot. Conventional plots received N in three split applications during the season: one at planting (one-third) and two banded side-dress applications during the season (one-third each). The first side-dress application was made at one to two fully expanded trifoliate leaf stage, and the second side-dress application at first opened bloom.
The controlled-release fertilizer (CRF) banding application. (A) Depiction of CRF being applied in a 30- to 38-cm band and (B) closer look at the bandwidth after application of CRF (green granules).
Citation: HortTechnology 34, 5; 10.21273/HORTTECH05442-24
Planting and crop management
The snap bean ‘Caprice’ (HM Claus, Davis, CA, USA) was chosen as the cultivar for this trial as it is a commonly used cultivar in the region. Plots were planted with a 4-row John Deere planter (John Deere, Moline, IL, USA), with spacing within row equal to 4 cm and between rows equal to 76 cm, using a medium “edible bean” John Deere planting plate on 5 Apr and 29 Mar for 2021 and 2022 trials, respectively. The final stand count was not recorded but the seeding rate was 23 plants/m, which translates to an average of 302,638 plants/ha for both years.
Overhead sprinkler irrigation was performed, and individual irrigation events ranged from 50 to 76 mm depending on the snap bean growth stage. Irrigation scheduling was performed based on information from a multidepth dielectric soil moisture sensor (Sentek, Adelaide, Australia) installed in each field. Irrigation events were initiated to maintain adequate soil moisture levels in the top 30 to 40 cm of soil to minimize any leaching events from the root zone.
Pest management was performed through application of Quadris Top (Azoxystrobin at 1.12 kg a.i./ha and difenoconazole at 0.07 kg a.i./ha) in the furrow at planting, and Dual Magnum (S-metolachlor at 1.07 kg a.i./ha) and Ridomil Gold (mefenoxam 0.56 kg a.i./ha) were sprayed after planting and irrigated in with 10 mm of water on the same day of planting. Diseases and insects were managed throughout the season based on a weekly scouting program. Standard fungicide and insecticide applications were performed as needed.
Leaf and soil sampling
Throughout the period from planting to harvest, a total of three leaf tissue samples and three multidepth soil samples were collected. Samples were taken from one of the inner rows of the four rows in each plot. Leaf tissue was sampled by taking the most recently matured leaf from the plants, which included all three “leaflets” on a single “leaf” for the snap bean. Leaf tissue sampling dates were 6 May (31 d after planting [DAP]), 20 May (45 DAP), and 2 Jun (58 DAP) for the 2021 trial, and 29 Apr (31 DAP), 10 May (42 DAP), and 23 May (55 DAP) for the 2022 trial.
Soil samples were taken within one of the middle snap bean rows at three depths: 0 to 30 cm, 30 to 60 cm, and 60 to 90 cm. Soil sampling dates were 6 May (31 DAP), 21 May (46 DAP), and 3 Jun (59 DAP) for the 2021 trial, and 29 Apr (31 DAP), 10 May (42 DAP), and 23 May (55 DAP) for the 2022 trial.
Leaf tissue and soil samples were sent to Waters Agricultural Laboratory in Camilla, GA, for leaf N and nitrate-N analysis, respectively.
Harvesting
A 6.0-m and 7.6-m subsection of the third row from the left in each four-row plot was marked for harvest for 2021 and 2022 trials, respectively. Harvest was performed on 7 Jun and 26 May, totaling 63 and 58 d per experiment in 2021 and 2022, respectively. Snap bean plants were pulled up completely, and all bean pods were removed and collected by hand. After plot weights were recorded, a sub-sample of 20 pods was selected from each plot, from which length and width were recorded, using a ruler and a caliper, respectively. The harvest data were converted to kg·ha−1.
Statistical analysis
For yield and pod quality metrics (length and width), measured at a single time point, a linear mixed-effect model with treatment and year as fixed effects and block as a random effect was used. Leaf N and soil nitrate concentrations were analyzed as repeated measures using linear mixed-effect models, with treatment, date, year (and depth for soil nitrate) as fixed effects and block as a random effect. Inspection of residuals indicated no violations of the underlying assumptions for all the studied variables. Post hoc analysis was performed through mean separation according to Tukey’s test at 5% probability level. All statistical analyses were conducted using R Studio (v4.2.2; Posit Team 2023), using the “lme” function from the “nlme” package to build the mixed-effect models, and marginal means were calculated using the “emmeans” function from “emmeans” package.
Regression analyses were performed to evaluate the relationship between leaf N concentration and yield for each sampling date on both years. Quadratic curves were the best fit for all data. R studio was used to perform such analysis.
Results
Impact of N source and rates on snap bean yield
The yield response analysis of snap bean to all N treatments, including rates (0, 56, 112, 168, and 224 kg·ha−1), sources (CRF vs. conventional fertilizer), and methods of N application (banding vs. broadcasting), was conducted over two consecutive growing seasons (2021 and 2022). There was no significant interaction of year and treatment (P ≥ 0.05), therefore yield data for each treatment was pooled across both years (Fig. 3). All the treatments, including CRF and conventional fertilizer, except for Control-0 and CRF-Br-112 (applied as broadcasting), were applied as banded applications. There was a significant difference in yield, pooled over both years, between the Control-0 and all other treatments (P < 0.01), with the Control-0 exhibiting the lowest yield (Fig. 3A). The CRF-168 achieved the maximum yield in absolute number (20,646.48 kg·ha−1), but there was no statistical difference among the yield of treated plots. Furthermore, no statistically significant difference was observed in methods of N application (CRF-112 and CRF-Br-112) (Fig. 3B). The evaluation of snap bean yield across increasing N rate (irrespective of the source used) revealed that the highest yield was obtained at the rate of 168 kg·ha−1, which was statistically different from 0 and 56 kg·ha−1 (P < 0.01) (Fig. 4). The relative yield outcomes for the N rates across two consecutive growing seasons are shown in Fig. 5. The application of 168 kg·ha−1 N exhibited a 100% relative yield. Conversely, 0 kg·ha−1 N application demonstrated the lowest relative yield. Figure 6 describes the yield response of snap bean across different N rates for the years 2021 and 2022. A quadratic model was best fit to the yield data in both years, with an evident decline in yield at the highest rate of 224 kg·ha−1. In addition, the yield obtained in the 2022 growing season was comparatively higher than in 2021. The results also showed that the choice between conventional and CRF did not produce any statistically significant differences (P > 0.05).
Snap bean yield response across different treatments (A) and between methods of application (B) for 2021 and 2022 spring seasons. Bars represent data averaged over both years, and error bars indicate the standard error of the mean. Treatment definitions are shown in Table 1. Distinct letters indicate statistically significant differences among N rates at 5% level of probability (Tukey’s test).
Citation: HortTechnology 34, 5; 10.21273/HORTTECH05442-24
Snap bean yield across different nitrogen (N) rates pooled over both growing seasons (2021 and 2022). Bars represent averaged data pooled from both years and both methods of application where applicable, and error bars represent standard error of the mean. Distinct letters indicate statistically significant differences among N rates at 5% level of probability (Tukey’s test).
Citation: HortTechnology 34, 5; 10.21273/HORTTECH05442-24
Relative snap bean yield (%) across different nitrogen (N) rates for two consecutive growing seasons: 2021 (A) and 2022 (B), and pooled dataset (C). R2 is the coefficient of determination.
Citation: HortTechnology 34, 5; 10.21273/HORTTECH05442-24
Yield response curve of snap bean across different nitrogen rates pooled over both growing seasons (2021 and 2022). R2 is the coefficient of determination, and RMSE is the root mean square error.
Citation: HortTechnology 34, 5; 10.21273/HORTTECH05442-24
Impact of N source and rates on snap bean quality parameters
Examining the effect of various treatments on bean pod length over the course of two consecutive years revealed that bean pods were significantly longer in 2022 when compared with 2021 (Fig. 7). This observation indicates that factors (i.e., precipitation, solar radiation, days to maturity, soil pH) other than the N treatments in a specific year might have had an effect on the elongation of bean pods. Therefore, further research needs to address soil, weather, and physiological attributes that may affect snap bean quality. In both years, the treatment CRF-168 and the control consistently produced the longest and shortest bean pods, respectively (Fig. 7A). In 2021, the bean pods with the CRF-168, Conv-224, and CRF-112 treatments reached highest length values. In contrast, in 2022, all treatments exhibited longer bean pods (>12.7 cm), regardless of N rate or source, with the exception of the control with an average length of 12.05 cm (Fig. 7A). Notably, when the N rate exceeded 0 kg·ha−1, there was minimal variation in the average pod length between treatments (P > 0.05). Regarding the bean pod width, all treated plots were not statistically different among themselves, but narrower bean pods were observed for the control (P < 0.05). Furthermore, no statistically significant differences in length (Fig. 7B) or width were observed between the CRF treatments applied through broad casting and banding at the rate of 112 kg·ha−1 (CRF-112 and CRF-Br-112, respectively).
The effect of treatments (A) and methods of application (B) on snap bean pod length in two spring growing seasons (2021 and 2022). Bars represent averaged data per treatment, and error bars represent the standard error of the mean. Distinct uppercase and lowercase letters indicate differences between the treatments in each year and differences between years for each treatment (Tukey’s test at 5% level of probability). Treatment definitions are shown in Table 1.
Citation: HortTechnology 34, 5; 10.21273/HORTTECH05442-24
Leaf tissue N concentration
The leaf tissue N concentration was influenced by treatment and its interaction with the other two main factors (year and date) (P < 0.01, Table 2). Therefore, post hoc analysis was performed on the triple interaction among treatment, date, and year. This suggests that leaf N concentration was not only influenced by the treatment but also varied over different dates and years. The highest leaf tissue N concentrations were consistently found for N applied at 168 and 224 kg·ha−1, regardless of the N source (Fig. 8). These findings highlight the impact of fertilization on leaf N concentration of snap bean and provide insights into how such nutrient is taken up by plants over time in different growing seasons, depending on the specific N treatment. In addition, residual N in the soil from the 2021 season might have influenced leaf N concentration in the following year because there is less variation of such variable during the 2022 season; in fact, there were no statistically significant differences in any treatment on 10 May 2022 (Fig. 8). Moreover, no statistically significant differences were identified when comparing the CRF treatments administered through broadcasting and banding at the rate of 112 kg·ha−1, regardless of year and date (P > 0.05).
Analysis of variance (ANOVA) of leaf tissue nitrogen concentration in 2021 to 2022 growing seasons.
Leaf nitrogen (N) concentration of snap bean across different treatments at different sampling dates in 2021 and 2022 growing seasons. Bars represent averaged data per treatment, while error bars represent the standard error of the mean. Different lowercase letters indicate significant statistical differences among treatments (see Table 1 for definitions).
Citation: HortTechnology 34, 5; 10.21273/HORTTECH05442-24
Irrespective of the specific tissue sampling date, this study revealed a quadratic fit model for the relationship between leaf tissue N concentration and snap bean yield (Fig. 9). In comparison with 2022, higher R2 values were observed in 2021. In the context of 2021 and focusing exclusively on the CRF source, R2 values ranged from 0.53 to 0.75 across the sampling dates, providing a quantitative measure of the goodness of fit (Fig. 9). A temporal pattern emerged, with late-season sampling exhibiting lower R2 values as compared with early-season sampling. Using this temporal insight could enhance the precision of early yield predictions, providing valuable information for N management strategies. Across all sampling dates, regardless of the N source and year, the lowest R2 value was consistently noted on the last sampling date (2 Jun 2021 and 23 May 2022).
Relationship between leaf nitrogen (N) concentration (%) and snap bean yield (kg·ha−1) at different sampling dates after application of conventional (Conv) or controlled-release fertilizer (CRF) in 2021 and 2022. Black dots represent the mean value of leaf N concentration for a given N rate applied. R2 is the coefficient of determination.
Citation: HortTechnology 34, 5; 10.21273/HORTTECH05442-24
Soil nitrate-N concentration
The study investigated soil nitrate-N concentration at different depths in response to varying fertilizer treatments during the 2021 and 2022 growing seasons (Supplemental Table 1, Fig. 10). The highest concentration of soil nitrate-N at 0- to 30-cm depth was observed in the highest rate of CRF application for both years (Fig. 10A). Conversely, the lowest soil nitrate-N concentration was consistently found in the control treatment, indicating a clear response to fertilizer application. The method of application showed significant differences only in 2021, where banding CRF at 112 kg·ha−1 provided higher soil nitrate-N at all studied depths (Fig. 10B). Furthermore, a noteworthy trend of decreasing soil nitrate-N concentration with increasing depth was observed consistently across all treatment and method of application groups and for both growing seasons (Fig. 10A and B). During the 2022 spring growing season, there was no statistically significant difference in soil nitrate-N concentration among the treatment groups for depths 30 to 60 cm and 60 to 90 cm (Fig. 10A). It was also observed that the variability of nitrate-N values decreased at deeper soil profile layers. These findings provide valuable insights into the distribution of soil nitrate-N concentration with respect to treatment and soil depth in the sandy soils of North Florida. When compared by sampling dates, the soil nitrate-N concentration differed more pronouncedly in 2021, where the treatments with lowest input amount of N (0 and 56 kg·ha−1) showed the lowest nitrate-N at all sampling dates. In contrast, in 2022, differences in soil nitrate-N levels were observed only during the second sampling event (Supplemental Fig. 1).
Soil nitrate-N concentration across different treatments (A) and methods of application (B) at three depths (0 to 30, 30 to 60, and 60 to 90 cm) for the 2021 and 2022 growing seasons. Bars represent data averaged over all sampling dates, and error bars represent the standard error of the mean. Treatment definitions can be found in Table 1. The same lowercase letter among treatments or methods of application is not statistically significant (Tukey’s test, P > 0.05).
Citation: HortTechnology 34, 5; 10.21273/HORTTECH05442-24
Discussion
This study evaluated different N treatments [combination of sources (Conv and CRF) and rates (0, 56, 112, 168, and 224 kg·ha−1), with an additional comparison of methods of application (banded or broadcast CRF at 112 kg·ha−1)] on snap bean yield and quality traits of pods in North Florida. Banding CRF did not result in higher yield nor improved the quality of snap bean pods when compared with broadcast CRF. Regardless of the amount, N fertilization increased snap bean yield when compared with the Control-0. This observation aligns with the results of several prior investigations conducted by Fageria et al. (2010) and Zucareli et al. (2010, 2011). Furthermore, Kovács et al. (2008) observed that N application positively influences vegetative growth and improves pod quality. Beshir et al. (2015) reported that N application rate of 100 kg·ha−1 resulted in a significant increase in pod production compared with the control. These findings provide sufficient justification that N application helps improve yield and quality of snap bean observed in this study.
The yields of CRF rates of 56, 112, 168, and 224 kg·ha−1 surpassed that of control by 73.0%, 101.2%, 110.7%, and 98.0%, respectively. Conversely, conventional rates of 56, 112, 168, and 224 showed higher yields than the control by 63.73%, 86.76%, 106.07%, and 77.0%, respectively, albeit not statistically significant. This suggests that N treatments used in this trial had little effect on the yield of snap bean, but additional factors not included in the scope of the study may have had some effect on snap bean yield and quality data. The study’s findings showed that there was no statistically significant increase in snap bean yield above 56 kg·ha−1, half of the current recommended rate. This result might be due to N mineralization carryover from the previous peanut crop. Extension reports in Georgia, Alabama, Oklahoma, Virginia, and Florida noted that, on average, there is an N credit of 22 to 67 kg·ha−1 after peanut crop (Buntin et al. 2007; Caddel et al. 2012; Crozier et al. 2010; Maguire and Heckendorn 2011; Virginia Department of Conservation and Recreation 1995; Wright et al. 2011). This highlights the importance of considering historical crop rotation and field conditions in nutrient management.
The study also observed that the application of the highest N rate (224 kg·ha−1) resulted in a reduction in snap bean yield. It is well established that excessive use of various fertilizers, particularly N, can lead to diminishing crop yield and quality (Ozer 2003; Sharma and Bali 2017). This observation underscores the importance of carefully considering and optimizing N application rates in snap bean cultivation to strike a balance between nutrient supply and yield outcomes. Hence, it becomes crucial to implement measures to enhance fertilizer utilization and reduce nutrient inputs, particularly N, to not only alleviate environmental load but also to lower the overall costs associated with agricultural production (Wang et al. 2011).
The differences in snap bean yield observed between the two growing seasons may be due to weather conditions. Liu et al. (2022) also documented that the productivity of snap bean in Florida frequently experiences significant reductions because of heavy rainfall associated with hurricanes and tropical storms.
Conclusion
This study provided valuable insights into optimizing N rates for snap bean cultivation in North Florida. The results of this study confirm a consistent trend observed in previous research, in which an increase in N rate resulted in improved snap bean yield. However, it is important to note that the highest N rate led to a reduction in yield, emphasizing the need for careful consideration and optimization of N application rates to balance nutrient supply and yield outcomes, as excessive N application can diminish crop yield. This study also highlighted the significance of historical crop rotation in nutrient management. The lack of a statistically significant increase in snap bean yield above 56 kg·ha−1 may be attributed to N mineralization carryover from the previous peanut crop, which underscores the importance of considering crop history when determining nutrient management strategies. This study suggests the potential adoption of CRF as a strategic tool to optimize both yield and quality of snap bean particularly when cultivated in sandy soils. Furthermore, this approach also provides an efficient way of applying N to sandy soils to increase the efficiency of N application, minimize leaching, and prevent environmental pollution by the excess of N in the soil. More research is needed to further substantiate these benefits and facilitate the transition to sustainable and efficient nutrient management practices in agriculture. Overall, this study contributes valuable information to the field of snap bean cultivation in sandy soils, offering a path toward increased productivity and reduced environmental impact.
References cited
Adams MW, Coyne DP, Davis JHC, Graham PH, Francis CA. 1985. Common beans (Phaseolus vulgaris L.), p 433–476. In: Summerfield RJ, Roberts EH (eds). Grain Legume Crops. Collins and Sons, London.
Araújo AP, Teixeira MG, De Almeida DL. 1997. Phosphorus efficiency of wild and cultivated genotypes of common bean (Phaseolus vulgaris L.) under biological nitrogen fixation. Soil Biol Biochem. 29(5-6):951–957. https://doi.org/10.1016/S0038-0717(96)00217-9.
Ayele HS, Atlabachew M. 2021. Review of characterization, factors, impacts, and solutions of Lake eutrophication: Lesson for lake Tana, Ethiopia. Environ Sci Pollut Res Int. 28(12):14233–14252. https://doi.org/10.1007/s11356-020-12081-4.
Baudoin J, Maquet A. 1999. Improvement of protein and amino acid contents in seeds of food legumes. A case study in Phaseolus. Biotechnol Agron Soc Environ. 3:220–224.
Beshir H, Walley F, Bueckert R, Tar’an B. 2015. Response of snap bean cultivars to rhizobium inoculation under dry land agriculture in Ethiopia. Agron. 5(3):291–308. https://doi.org/10.3390/agronomy5030291.
Bodirsky BL, Popp A, Lotze-Campen H, Dietrich JP, Rolinski S, Weindl I, Schmitz C, Muller C, Bonsch M, Humpenoder F, Biewald A, Stevanovic M. 2014. Reactive nitrogen requirements to feed the world in 2050 and potential to mitigate nitrogen pollution. Nat Commun. 5:3858. https://doi.org/10.1038/ncomms4858.
Bowles TM, Atallah SS, Campbell EE, Gaudin ACM, Wieder WR, Grandy AS. 2018. Addressing agricultural nitrogen losses in a changing climate. Nat Sustain. 1(8):399–408. https://doi.org/10.1038/s41893-018-0106-0.
Buntin GD, Grey TL, Harris GH, Phillips D, Prostko EP, Raymer P, Smith NB, Sumner PE, Woodruff J. 2007. Canola production in Georgia. UGA Ext. B. 1331. University of Georgia Cooperative Extension, Athens, GA, USA.
Caddel J, Redfearn D, Zhang H, Edwards J, Deng S. 2012. Forage legumes and nitrogen production. Oklahoma Cooperative Extension Service.
Cen Z, Wei L, Muthukumarappan K, Sobhan A, Mcdaniel R. 2021. Assessment of a biochar-based controlled release nitrogen fertilizer coated with polylactic acid. J Soil Sci Plant Nutr. 21(3):2007–2019. https://doi.org/10.1007/s42729-021-00497-x.
Crozier CR, Hardy DH, Kissel DE, Mitchell CC, Oldham JL, Phillips S, Sonon L. 2010. Research-based soil testing and recommendations for cotton in coastal plain soils. Alabama Agricultural Experiment Station, Auburn University.
Davis J, Borisova T, Olexa MT. 2018. An overview of Florida water policy framework and institutions. http://edis.ifas.ufl.edu/fe579.
Fageria NK, Baligar VC. 2005. Enhancing nitrogen use efficiency in crop plants. Adv Agron. 88:97–185.
Fageria NK, Santos dos AB, Moraes MF. 2010. Influence of urea and ammonium sulfate on soil acidity indices in lowland rice production. Commun Soil Sci Plant Anal. 41(13):1565–1575. https://doi.org/10.1080/00103624.2010.485237.
FAOSTAT 2020. Food and Agriculture Organization of the United Nations. Statistics Division. www.fao.org. [accessed 1 May 2024].
Gao Y, Fang Z, Van Zwieten L, Bolan N, Dong D, Quin BF, Meng J, Li F, Wu F, Wang H, Chen W. 2022. A critical review of biochar-based nitrogen fertilizers and their effects on crop production and the environment. Biochar. 4(1):36. https://doi.org/10.1007/s42773-022-00160-3.
Goh KM, Haynes RJ. 1986. Nitrogen and agronomic practice, p 379–442. In: Haynes RJ (ed). Mineral N in the plant-soil system. Academic Press Inc., Orlando, Harcourt, UK.
Hartz K, Smith RF. 2009. Controlled-release fertilizer for vegetable production: The California experience. HortTechnology. 19(1):20–22. https://doi.org/10.21273/HORTTECH.19.1.20.
Kelly JF, Scott MK. 1992. The nutritional value of snap beans versus other vegetables, p 23–46. In: Henry G, Janseen WG (eds). Snap beans in the developing world: Proceedings of an international conference. Cali, Colombia.
Kovács AB, Vágó I, Kremper R. 2008. Growth and yield responses of garden bean (Phaseolus vulgaris L.) to nitrogen and sulphur fertilization. Analele Universităţii din Oradea, Fascicula: Protecţia Mediului. 13(4):93–111.
Kushwaha BL. 1994. Response of French bean (Phaseolus vulgaris L.) to nitrogen application in north Indian plains. Indian J Agron. 39:34–37.
Lapointe BE, Brewton RA, Herren LW, Porter JW, Hu C. 2019. Nitrogen enrichment, altered stoichiometry, and coral reef decline at Looe Key, Florida Keys, USA: A 3-decade study. Mar Biol. 166(8):108 https://doi.org/10.1007/s00227-019-3538-9.
Liegel EA, Walsh LM. 1976. Evaluation of sulfur-coated urea (SCU) applied to irrigated potatoes and corn. Agron J. 68(3):457–463. https://doi.org/10.2134/agronj1976.00021962006800030006x.
Liu D, Anna-Lisa P, Morgan KT, Guodong L. 2022. Effects of oxygen fertilization on damage reduction in flooded snap bean (Phaseolus vulgaris L). Sci Rep. 12(1):4282 https://doi.org/10.1038/s41598-022-08165-5.
Liu R, Zhang P, Wang X, Chen Y, Shen Z. 2013. Assessment of effects of best management practices on agricultural non-point source pollution in Xiangxi River watershed. Agric Water Manag. 117:9–18. https://doi.org/10.1016/j.agwat.2012.10.018.
Lynch J, White JW. 1992. Shoot nitrogen dynamics in tropical common bean. Crop Sci. 32(2):392–397. https://doi.org/10.2135/cropsci1992.0011183X003200020023x.
Maguire RO, Heckendorn SE. 2011. Soil test recommendations for Virginia. Virginia Cooperative Extension, Blacksburg, VA, USA.
Mahmoud FAM, Kandil HBA, Tawfic GA. 2022. Enhancing yield and storability of snap bean by bio-fertilizer as a solutions for climate change-affected sustainable agriculture. Scien J Agric Sci. 4:80–98. https://doi.org/10.21608/SJAS.2022.178262.126.
Nadeem MA, Çilesiz Y, Ali F, Baloch FS, Karaköy T. 2020. Investigation of quality and cooking traits diversity in a global common bean germplasm. Glob J Bot Sci. 8:21–29. https://doi.org/10.12974/2311-858X.2020.08.3.
Negash A, Getachew E. 2019. Quality of snap bean (Phaseolus Vulgaris L.) as influenced by N and P fertilizer rates at Jimma Southwestern Ethiopia. JAC. 59(59):151–157. https://doi.org/10.32861/ajc.59.151.157.
Ozer H. 2003. Sowing date and nitrogen rate effects on growth, yield and yield components of two summer rapeseed cultivars. Eur J Agron. 19(3):453–463. https://doi.org/10.1016/S1161-0301(02)00136-3.
Penuelas J, Gargallo-Garriga A, Janssens IA, Ciais P, Obersteiner M, Klem K, Urban O, Zhu Y-G, Sardans J. 2020. Could global intensification of nitrogen fertilisation increase immunogenic proteins and favour the spread of coeliac pathology? Foods. 9(11):1602. https://doi.org/10.3390/foods9111602.
Posit team. 2023. RStudio: Integrated Development Environment for R. Posit Software, PBC, Boston, MA, USA. http://www.posit.co/.
Puga AP, Queiroz MCD, Ligo AV, Carvalho CS, Pires AMM, Marcatto JDO, Andrade CAD. 2019. Nitrogen availability and ammonia volatilization in biochar-based fertilizers. Arch Agron Soil Sci. 66(7):992–1004. https://doi.org/10.1080/03650340.2019.1650916.
Rath S, Zamora-Re M, Graham W, Dukes M, Kaplan D. 2021. Quantifying nitrate leaching to groundwater from a corn-peanut rotation under a variety of irrigation and nutrient management practices in the Suwannee River Basin, Florida. Agric Water Manage. 246:106634. https://doi.org/10.1016/j.agwat.2020.106634.
Salisbury FB, Ross CW. 1991. Plant physiology (4th ed). Wadsworth, Belmont, CA, USA.
Sharma LK, Bali SK. 2017. A review of methods to improve nitrogen use efficiency in agriculture. Sustainability. 10(1):51. https://doi.org/10.3390/su10010051.
Simonne EH, Hutchinson CM. 2005. Controlled-release fertilizers for vegetable production in the era of best management practices: Teaching new tricks to an old dog. HortTechnology. 15(1):36–46. https://doi.org/10.21273/HORTTECH.15.1.0036.
Swiader JM, Ware GM, Mccolum JP. 1992. Producing vegetable crops (4th ed). Interstate Publishers, Inc., Danville, IL, USA.
US Department of Agriculture, Economic Research Services. 2024. Cash receipts by state. https://data.ers.usda.gov/reports.aspx?ID=17843#P502bbcaf1a8f4c81ab613e7969e3ccd0_18_17iT0R0x32 [accessed 1 May 2024].
US Department of Agriculture, National Agricultural Statistics Service. 2024. Vegetables 2023 Summary, February 2024. US Department of Agriculture, Washington, DC, USA.
Virginia Department of Conservation and Recreation. 1995. Virginia nutrient management standards and criteria. Division of Soil and Water Conservation, Richmond, VA, USA.
Wang RF, An DG, Hu CS, Li LH, Zhang YM, Jia YG, Tong YP. 2011. Relationship between nitrogen uptake and use efficiency of winter wheat grown in the north China plain. Crop Pasture Sci. 62(6):504–514. http://dx.doi.org/10.1071/C.
Wang Y, Ying H, Yin Y, Zheng H, Cui Z. 2019. Estimating soil nitrate leaching of nitrogen fertilizer from global meta-analysis. Sci Total Environ. 657:96–102. https://doi.org/10.1016/j.scitotenv.2018.12.029.
Wright DL, Marois JJ, Sprenkel RK, Rich JR. 2011. Production of ultra narrow row cotton. University of Florida (UF), IFAS Extension. SSAGR-83.
Zucareli C, Prando AM, Junior EUR, Nakagawa J. 2011. Phosphorus on the productivity and seed quality of bean Carioca Precoce cultivated during the rainy season. Rev Ciên Agron. 42:32–38.
Zucareli C, Junior EUR, Oliveira MA, Cavariani C, Nakagawa J. 2010. Physiological and biometric indices in bean under different doses of phosphorus. Semina Ciên Agrár. 31:1313–1324.
