Abstract
Nitrogen (N) management is a key component to maintaining high productivity of northern highbush blueberry (Vaccinium corymbosum L.) and nitrogen is often supplied by applying ammonium-based fertilizers. It can also be supplied through mineralization of soil organic matter (SOM), although the amount released by SOM is difficult to predict and not always considered in the development and implementation of N fertility programs. Laboratory and field experiments were conducted to estimate the timing and magnitude of net N mineralization from SOM throughout the growing season, identify soil properties that can be measured commercially and used to predict net N mineralization across a range of SOM, and determine whether N requirements for maximizing yield and fruit quality of blueberry vary across soils with different amounts of SOM. The laboratory experiment was conducted for 6 months using soil samples collected from 10 representative commercial blueberry fields in northwest Washington. The soils contained 2% to 42% soil organic carbon (SOC). The mean net N mineralization rates were fastest during the first 3 to 4 months of incubation, corresponding to the period during which N uptake reaches its maximum in blueberry. Results indicated that the soil total N may be a useful predictor of the N supply from SOM (6.34 ± 1.13 kg⋅ha−1 increase in net N mineralization with each 0.1% increase in total N), but there was substantial variability in the N supply that could not by explained by the total N (P < 0.001; r2 = 0.433). The field experiment was conducted from 2019 to 2021 and included four mature, regionally representative, commercial fields of ‘Duke’ blueberry. The fields contained 3% to 28% SOC and were each fertilized with low, medium (control), or high N rates, corresponding to 33 to 50, 67 to 84, or 102 to 118 kg⋅ha−1 N per year, respectively. Although soil inorganic N levels suggested that N mineralization was substantial at sites with higher SOM, sites with lower SOM did not require more fertilizer N than those with higher SOM. Under the conditions of this experiment, even the lowest N rates were sufficient to sustain production for at least 3 years at each site. The findings of this study indicate that SOM may be an important contributor to N fertility in managed blueberry systems, and that yield and fruit quality can be maintained across various N fertilizer rates, including at rates <50 kg⋅ha−1 N. However, the long-term impacts of reducing N application rates remain unclear, and future research should monitor long-term changes in plant health and soil fertility associated with reduced N applications across diverse soils and production systems.
Northern highbush blueberry (Vaccinium corymbosum L.; hereafter referred to as blueberry) is an internationally important specialty crop. Globally, there are 235,000 ha of blueberry, producing almost 1.8 million metric tons of fruit (Brazelton 2022). China leads the industry in terms of both the planted area and production, followed by the United States, which had 42,500 ha of blueberries, worth approximately $1.1 billion in 2022 (US Department of Agriculture, National Agricultural Statistics Service 2023). In the United States, Washington ranks first in blueberry production, with 80,000 metric tons produced in 2022, although seven other states produce at least 10,000 metric tons annually, including California, Florida, Georgia, Michigan, New Jersey, North Carolina, Oregon, and Washington (US Department of Agriculture, National Agricultural Statistics Service 2023). These production regions represent a wide variety of soils and climates, which can present a significant challenge for blueberry producers, particularly regarding nutrient management.
Multiple studies over the past four decades have shown that both excessive and insufficient nitrogen (N) rates can affect yield (Hanson and Retamales 1992; Kozinski 2006; Messiga et al. 2018; Pavlis 2004), fruit quality (Ehret et al. 2014; Mercik and Smolarz 1993; Pavlis 2004), cold hardiness (Smolarz and Mercik 1989), and vegetative growth (Hanson and Retamales 1992; Smolarz and Mercik 1989; Smolarz et al. 1985) across multiple cultivars of blueberry. For example, higher yields were observed when plants were fertilized with 50 or 100 kg⋅ha−1 N than with 0 or 150 kg⋅ha−1 N in an established planting of ‘Bluecrop’ (Smolarz and Mercik 1989). Kozinski (2006) highlighted the deleterious effects of excessive soil N on fruit yield and found that applying N at rates >60 kg⋅ha−1 decreased the yield of a 3- to 5-year-old planting of ‘Bluecrop’. In contrast, Messiga et al. (2018) did not observe differences in the berry yield with broadcast N fertilizer applications ranging from 100 to 287 kg⋅ha−1 N in a 6- to 8-year-old planting of ‘Duke’; however, a control treatment that did not receive any N fertilizer since planting had lower yield than the N-fertilized treatments during most years. Likewise, Vargas and Bryla (2015) found no difference in yield or berry weight when a young planting of ‘Bluecrop’ was fertigated with 100 or 200 kg⋅ha−1 N. Strik and Buller (2014) observed that high N rates (112–269 kg⋅ha−1 N) had no deleterious effects on yield during the first 6 years of production of ‘Elliott’; however, in this case, higher N rates reduced berry weight and increased firmness, the latter of which was likely caused by the smaller size of the berries. Similarly, Ehret et al. (2014) examined rates between 0 and 120 kg⋅ha−1 N and found that higher N rates reduced berry size and increased fruit firmness during one of three years in a new planting of ‘Duke’.
The consequences of applying insufficient or excessive N can extend beyond yield and fruit quality and affect vegetative growth and cold hardiness of blueberry. For example, a study conducted during the establishment of ‘Bluecrop’ found that high rates of granular N fertilizer reduced growth and caused salt damage to the plants because of high concentrations of ammonium in the soil solution (Bryla and Machado 2011; Vargas and Bryla 2015). Furthermore, Smolarz and Mercik (1989) found that excessive N negatively affected acclimation and cold-hardiness of ‘Bluecrop’. If the timing and rate of N applications are not managed properly, then the fruit bud set could be reduced and cold-hardiness might be impacted negatively, eventually leading to lower yield the following year. Given the myriad of possible effects of underapplying or overapplying N, it is important to have well-supported fertilizer recommendations that account for all potential sources of N that can be tailored to local conditions and management systems.
Hanson (2006) reviewed N fertilization of blueberry and concluded that variations in soil properties might explain why N recommendations vary across regions. Although numerous studies have examined the impact of different N rates on the productivity of blueberry, most have been conducted on mineral soils, generally with <10% soil organic matter (SOM) or <5% soil organic carbon (SOC) (Bañados et al. 2012; Ehret et al. 2014; Hanson et al. 2002; Messiga et al. 2018; Smolarz and Mercik 1989). However, blueberry production in higher SOM soils or Histosols (>12%–20% SOC) represents a substantial proportion of total production in some regions (Soil Survey Staff 2014). So far, optimal N rates for production in Histosols have been assessed for lowbush blueberry (V. angustifolium L.) (Paal et al. 2011); however, it remains unclear how variations in SOM influence the amount of fertilizer N needed to maximize the yield and fruit quality of other blueberry types. In general, <5% of the N in SOM is mineralized and available for crop uptake each year (Galloway et al. 2003); however, given the size of the soil N pool, this can be an important source of N for plants, particularly in systems with high SOM and/or under conditions conducive to N mineralization. Indeed, much of the N assimilated by young blueberry plants may come from native N that is already in the soil (Throop and Hanson 1997).
Predicting the amount of N that soils supply through mineralization of SOM can improve N management; therefore, this has been the subject of much research. Potential predictors include carbon (C) or N pools (actual or operationally defined) or proxies for these pools. For example, hot water-extractable organic N (HWEON) has shown to be an accurate and easily measurable predictor of N mineralization in agricultural soils (Curtin et al. 2006, 2017). Additional promising predictors include SOC and permanganate oxidizable C (Zou et al. 2018), C:N ratios (Janssen 1996), and other parameters that represent the size of the SOM pools, including total N (Ros et al. 2011; Ros 2012). Despite the large body of research that has focused on predicting N mineralization, the range of SOM in these studies has been relatively constrained, and they have predominately focused on mineral soils. For example, Stanford and Smith (1972) used several soil orders to assess N mineralization rates, but Histosols were not among them, and SOC in the study ranged from only 0.2% to 3.0%. More recently, Curtin et al. (2017) investigated predictors of N mineralization using soils ranging from 1.3% to 8.8% SOC; however, this range was below the 12% threshold for classifying them as Histosols (Soil Survey Staff 2014). Even though Histosols represent only 1.2% of soils worldwide (Eswaran et al. 1992), they are present in key regions for blueberry production given that similar climatic conditions favor both Histosol formation and blueberry production. When Histosols were included in an evaluation of predictors of N mineralization, the best predictors changed depending on the SOM, suggesting that further investigations of predictors of N mineralization for high-organic matter soils are necessary (Miller et al. 2019).
Despite the importance of N mineralization from SOM, no studies (to our knowledge) have investigated the influence of SOM on N requirements of blueberry. Therefore, the objectives of this study were to determine the magnitude and timing of N mineralization from SOM, identify soil properties that can be used to reliably predict N mineralization, and identify N application rates that maximize yield, fruit quality, and cold hardiness of blueberry across soils with varying amounts of SOM, including Histosols. We hypothesized the following: in Histosols, the N supply from mineralization of SOM would be comparable to or greater than the N supplied by fertilizer application; most of the N supplied by mineralization would be available after the period of maximum plant uptake; the HWEON, SOC, and total N (TN) would be positively correlated to net N mineralization; the C:N ratio would be negatively correlated to net N mineralization; and, of these measurements, HWEON would be the strongest predictor of N mineralization (Curtin et al. 2017). Furthermore, we expected that sites with high SOM would require less N fertilizer than those with low SOM to maximize yield and fruit quality, and that excessive N fertilization would lead to increased vegetative growth and reduced cold hardiness.
Materials and Methods
Description of study sites
Net N mineralization was quantified in the laboratory using soils collected from 10 commercially representative fields (≥5 years old) of trellised ‘Duke’ blueberry. The fields were in northwest Washington and encompassed a wide range of SOC (Table 1). Sites 1 to 4 were also used for a field experiment to examine the effects of different N application rates on the yield and fruit quality of blueberry. These four sites had bushes that were 5 to 15 years old at the start of the experiment, with 0.8- to 0.9-m in-row spacing and 3.4-m between-row spacing; they were irrigated with drip irrigation and established on raised beds [≈1 m (width) × 0.3 m (height)].
Soil properties at ten commercial ‘Duke’ northern highbush blueberry field sites in northwest Washington.
Laboratory experiment
Soil sampling and characterization.
A 6-month laboratory experiment was conducted between May and Nov 2019 to assess the net N mineralization in soil samples collected from each field site. The samples were collected to a depth of 30 cm using a soil probe (diameter, 2.2 cm) at the center and corners of each field (i.e., five independent samples per field for a total of 50 samples across all sites). At each location, samples were taken on top of the raised beds directly between plants. Any mulch, moss, and algae were brushed off before sampling, and easily visible pieces of plant debris were removed. After their collection, the samples were placed in sealable plastic bags, kept on ice in an insulated cooler during transportation, and stored at 4 °C for further analysis. Each sample was analyzed for SOC, TN, and the C:N ratio by dry combustion (Nelson and Sommers 1996) at a commercial laboratory (Brookside Laboratories, New Breman, OH, USA). Because the soils did not contain any carbonates, the total C and SOC were considered interchangeable. The soil pH of each sample was analyzed using the 1:1 water method (McLean 1982).
Incubation.
Soil samples from each site were incubated at 60% field capacity, determined according to Geisseler et al. (2009), to provide optimal moisture conditions for N mineralization. Briefly, the samples were placed in funnels lined with filter paper, wetted from below by capillary action, and allowed to drain freely for 2 to 3 h (analogous to field capacity). Then, the samples were weighed and dried in a forced-air oven at 105 °C. The dry weight of each sample was determined, and the gravimetric water content (GWC) corresponding to 60% field capacity was calculated by subtracting dry weight from the weight at field capacity, multiplying by 0.6, and dividing by the oven-dried weight. For incubation, 6 g of field-moist soil from each sample was weighed in seven individual 50-mL polypropylene centrifuge tubes, and the GWC was adjusted with deionized water. One of the seven tubes from each sample was immediately extracted to measure the initial soil inorganic N. The remaining tubes from each soil sample were placed without caps in a 130BLL controlled environment chamber (Percival Scientific, Inc., Perry, IA, USA) or a freezer-less refrigerator (FFRU17B2QW; Frigidaire, Charlotte, NC, USA) modified with a Ranco® ETC011000–000 temperature controller (Robertshaw, Itasca, IL, USA) and kept at high humidity by covering them with a moist paper towel that was misted regularly and maintaining pans of free water inside the incubator. The temperature of the incubator was adjusted each month to represent growing season soil temperatures at 20 cm (10.6, 14.5, 17.4, 19.8, 20.0, and 16.8 °C for April through September, respectively), which were obtained and averaged from seven AgWeatherNet weather stations located near the 10 sampling sites (https://weather.wsu.edu/). The tubes were weighed weekly, and the GWC was adjusted as needed to maintain the soil at 60% water holding capacity. The mean GWC of the incubated samples was consistently >54% water-holding capacity before adjustment each week. Each month, one tube from each soil sample was selected and extracted to measure soil inorganic N.
Soil inorganic N analysis.
For the analysis of soil inorganic N, 30 mL of 2 M potassium chloride solution was added to each incubated centrifuge tube, and they tubes were shaken for 1 h. After shaking, the solution was filtered through medium-porosity, ashless filter paper (particle retention size, 2–5 μm; Fisherbrand, Hampton, NH, USA). The initial 8 to 10 mL of the sample was discarded to avoid contamination from any nitrate or ammonium present in the filter paper, and the remaining sample was filtered into 15-mL centrifuge tubes and stored at 4 °C for immediate analysis or −18 °C for longer-term storage. Soil nitrate-N concentrations were determined using a modified vanadium (III) reduction method (Doane and Horwáth 2003), with the absorbance read at 540 nm using a Synergy LX Multi-Mode Reader microplate reader (Agilent Technologies, Santa Clara, CA, USA). The extracts and reagent were combined and allowed to develop for 6 to 16 h. Soil ammonium N (NH4-N) concentrations were determined using the salicylate-hypochlorite colorimetric reaction (Verdouw et al. 1978) with absorbance read at 640 nm on the microplate reader. Extracts and reagents were allowed to develop for 2 to 3 h. Reactions for each extract were run in triplicate and checked to verify that the coefficient of variance was <0.1. The standard curve for each microplate had a minimum of five data points and r2 > 0.99. Net N mineralization was calculated by subtracting soil inorganic N [NH4-N and nitrate N (NO3-N)] in the sample that was extracted at the start of the incubation from soil inorganic N in the sample extracted for a given month.
Hot water-extractable organic N.
To determine whether HWEON is a good predictor of net N mineralization, the protocols outlined in the works by Curtin et al. (2006), Cabrera and Beare (1993), and Ghani et al. (2003) were followed. Each soil sample was air-dried and sieved through a 2-mm sieve. The equivalent of 3 g of oven-dried soil was placed in a 50-mL polypropylene centrifuge tube with 30 mL of deionized water and shaken for 30 min at room temperature before centrifuging for 20 min at 3500 rpm. The supernatant was discarded before adding another 30 mL of deionized water to the sample and mixing it for 10 s on a vortex shaker. After being shaken, the samples were placed in a hot water bath at 80 °C for 16 h. Afterward, the samples were vortexed again for 10 s and centrifuged for 20 min at 3500 rpm. The supernatant was filtered through medium-porosity, ashless filter paper (particle retention size, 2–5 μm; Fisherbrand) and placed in 15-mL polypropylene centrifuge tubes for storage at 4 °C. This final sample was divided into two aliquots. One aliquot was used for the analysis of soil inorganic N as described, and the other was frozen and sent, on ice, to a laboratory so that the total dissolved N could be measured (Oregon State University Soil Health Laboratory, Corvallis, OR, USA). The total dissolved N was measured using a total nitrogen module-1 unit (Shimadzu, Kyoto, Japan) connected to a total organic carbon analyzer (TOC-V CSH; Shimadzu) using high-temperature catalytic oxidation with platinum catalyst. The detection limit for N was 0.05 μg/L. Three injections (with a maximum of five injections) of 25 μL were performed for each sample to obtain an SD <0.1. Soil inorganic N was subtracted from the total dissolved N to determine organic N and, thus, HWEON.
Field experiment
Nitrogen application rate treatments.
The field experiment was conducted in 2019–21 at sites 1 to 4 (Table 1). Experimental plots at each site were treated with low, medium (control), or high N rates from granular fertilizer (22, 56, or 90 kg⋅ha−1 N per year). Depending on each grower-collaborator, the fertilizers were manually broadcast on the raised planting beds between bushes, either using a single application (April) or using two split applications (April and May) per year. The treatments were adjusted at each site by modifying only N in the customized fertilizer blend from each grower to ensure that each planting would have adequate levels of other nutrients, including phosphorus, potassium, magnesium, and boron. The N rates were adjusted by altering the levels of urea (CH4N2O), ammonium sulfate [(NH4)2SO4], or monoammonium phosphate [(NH4)H2PO4] in each fertilizer blend. Any differences in phosphorus or sulfur in the treatments were adjusted using triple superphosphate [Ca(H2PO4)2] or magnesium sulfate (MgSO4). The plants were also fertigated with ammonium thiosulfate [(NH4)2S2O3] and a 4–13–15 blended fertilizer through the drip system with 11 to 28 kg⋅ha−1 N per year at each site, for a total of 33 to 55, 67 to 84, and 101 to 118 kg⋅ha−1 N in each treatment, respectively. The treatments were arranged in a randomized complete block design with five replicates per site and between one and three blocks per row, depending on field geometry. Each treatment plot was demarcated by trellis posts, and treatments included 10 to 12 consecutive plants in a row. Within each row, a buffer plant was included on either end nearest the trellis posts for all measurements except for yield.
Soil sampling and analysis.
Three to five soil samples per plot were taken with a soil probe (diameter, 2.2 cm) to a depth of 30 cm at each site at the start of the experiment and composited. Subsequent soil sampling was conducted monthly in 2019 and 2020, and every 2 months in 2021. Each sample was collected between two plants in a plot, avoiding buffer plants on either end of the plots, using the same sampling procedures described previously for the laboratory experiment. Samples were analyzed to determine the SOC, TN, and soil inorganic N as previously described; however, for soil inorganic N from the field experiment, 16 g of field-moist soil was extracted with 40 mL of 2 M potassium chloride solution.
Fruit harvest.
The experimental plots in each field were harvested using an over-the-row machine harvester (the make and model varied with each grower-collaborator and harvest date). Before and after harvesting each plot, the conveyor belts on the harvesters were run until they were clear of blueberries. Harvested fruit was weighed immediately on-site using a field scale (CAS, East Rutherford, NJ, USA). Plants were harvested once or twice per season when the fruit reached a target maturity level (>90% blue), as determined by the grower-collaborators. Site 1 was harvested on 4 Aug 2019, 3 Aug 2020, 24 Jul 2021, and 12 Aug 2021. Site 2 was harvested on 22 Jul 2019, 3 Aug 2019, 12 Aug 2020, 27 Jul 2021, and 13 Aug 2021. Site 3 was harvested on 26 Jul 2019, 9 Aug 2019, 25 Jul 2020, and 3 Aug 2021. Site 4 was harvested on 2 Aug 2019, 10 Aug 2020, 23 Jul 2021, and 11 Aug 2021.
Fruit quality analyses.
Within 24 h before harvest, a representative sample of 50 berries was collected by hand from each plot on both sides of the row. The samples were placed into plastic clamshells and stored on ice packs in insulated coolers for transport to the laboratory. In the laboratory, the firmness of the berries was measured using an automated fruit compression tester (FirmTech II; Bioworks, Wamego, KS, USA). The maximum and minimum compression forces on the tester were set at 250 g and 25 g, respectively. Then, the berries were placed in sealable plastic bags and stored at −18 °C. The samples were later thawed at room temperature, placed between two to three layers of cheesecloth, and manually squeezed to collect 50 mL of juice in centrifuge tubes. Titratable acidity (TA) of the juice was measured using an auto titrator (HI902C; Hanna Instruments, Smithfield, RI, USA) and 10 mL of juice per sample titrated to an endpoint of pH 8.1 using sodium hydroxide (NaOH). Data are presented as the percent citric acid. Another 1 to 2 mL of juice was pipetted onto a refractometer (HI96801; Hanna Instruments) and measured to determine the percent total soluble solids (TSS). The TA and TSS measurements were performed in triplicate.
Leaf tissue N.
Leaf tissue samples were collected at each site on 16 Aug 2019, 3 Aug 2020, and 2 to 4 Aug 2021, according to the guidelines outlined by Hart et al. (2006). Each year, 50 recently expanded leaves were collected randomly from both sides of the row of each plot and placed into paper bags. Then, the leaves were dried for ≈3 d at 60 °C and sent to a commercial laboratory (Brookside Laboratories) for analysis of the total N (McGeehan and Naylor 1988).
Vegetative growth and cold-hardiness.
Whips (shoots that develop from latent buds on the crown or lower laterals located <30 cm above the soil surface) were counted on every plant in each plot, excluding the buffer plants, in Oct 2019 and 2020. Cold hardiness of flower buds was also determined on 25 Oct 2019 and 2 Nov 2020. On both dates, ≈10 lateral branches at midcanopy height, with each containing at least three fruiting buds per lateral branch, were collected from four replicate plots at each site. All samples were collected in the morning, wrapped in moist paper towels, placed in sealable plastic bags, and immediately placed in coolers with ice. Cold hardiness was assayed 24 h after collection using a modified detached shoot assay as described by Arora et al. (2000, 2004) and used by Ehlenfeldt et al. (2007) to measure hardiness among Vaccinium species. The procedure was modified using a circulating water bath (Model PP28R-30; Polyscience Circulating Bath, Niles, IL, USA) filled with a 1:1 ratio (volume/volume) of propylene glycol and water. The fifth replicate and plants fertilized with a medium rate of N (67–84 kg⋅ha−1) were not included in the analysis because of insufficient space in the bath. Before each assay, lateral branches were submersed in chilled water and trimmed to three fruiting buds in a cold room maintained at 4 °C. Then, the branches were placed in labeled 25-× 200-mm glass test tubes containing 4 mL of distilled, chilled water. Nine buds (three per lateral) per replicate were assessed at temperatures ranging from −13 to −26 °C. These temperatures were selected based on historical and concurrent records of cold hardiness in blueberry (Kogan et al. 2023). Thermocouples were attached to extra buds to monitor changes in temperature and determine when to remove the samples. The buds were cooled gradually at a rate of ≈2 °C⋅h−1. After the buds reached a predetermined temperature, assigned buds within a test tube were removed from the bath, placed on ice, and allowed to sit overnight in a refrigerator (4 °C). After 12 h, buds were removed from the ice and allowed to thaw in the refrigerator for another 12 h (simulating a slow thaw in the field). Then, the samples were removed from the refrigerator and allowed to thaw at 23 °C for another 24 h. Control buds from each N treatment were kept in the same refrigerator and evaluated at the same time as those exposed to the temperature treatments. Bud injury was assessed visually by dissecting each bud using a stereoscopic microscope (Nikon SMZ1000; Nikon Instruments Inc., Melville, NY, USA) and determining the number of flowers that were either dead or alive. Tissue that was black or brown was considered dead. The number of buds with dead flowers was divided by the number of total buds to identify the lethal temperature at which 50% of the floral buds were damaged.
Data analysis
Statistical analyses were performed with R software (R Core Team 2020) using the “nlme” package and “lme” function for linear mixed models (Pinheiro et al. 2020). Net N mineralization was converted to kg⋅ha−1 N using the bulk density of the soil for each site from the Web Soil Survey (Soil Survey Staff 2021). In general, there was good agreement between bulk densities obtained from Web Soil Survey and manual measurements on intact cores taken 0 to 15 cm with a slide hammer soil core sampler at sites 1 to 4 (Regular Slide Hammer; AMS, American Falls, ID, USA). For net N mineralization dynamics in the laboratory incubation, an analysis of variance (ANOVA) was run to compare high (>20%) and low (<20%) SOC sites at each timepoint, and linear models were used to assess the correlation between net N mineralization after 4 months (corresponding to the timing of berry harvest) and individual or grouped predictor variables (SOC, total N, C:N, and HWEON). For the field study, linear mixed models included block as a random effect, and year and N rate were treated as fixed effects; a term for interactions between year and N rate was also included. Comparisons were made only within sites because differences in SOC between sites could not be distinguished from other site-specific factors. The assumption of normality was assessed using the Shapiro-Wilk test and quantile-quantile plots, and the assumption of the homogeneity of variance was checked using Levene’s test and by plotting predicted and residual values. When results indicated a significant effect of the N rate (α = 0.05), a post hoc multiple comparisons test was performed (Tukey’s honest significant difference) using the “emmeans” package and function in R (Lenth 2016). Data was visualized using the “ggplot2” package (Wickham 2016).
Results
Dynamics of net N mineralization.
During incubation, net N mineralization was negligible during the first month when the temperature was only 10.6 °C, but it increased sharply over the subsequent 3 months in soils with >20% SOC (Histosols) as temperatures reached 14.5 to 19.8 °C (Fig. 1). In general, net N mineralization slowed over the course of incubation and was considerably higher in soils with >20% SOC than in those with <20% SOC. One site (site 9) had much higher net N mineralization than the others; therefore, the results were analyzed with and without this site to avoid the interpretation of the data being driven by a single site (Fig. 1). After 4 months of incubation (corresponding to soil temperatures in April to July or just before harvest in the field), net N mineralization was positively correlate to SOC and TN, with the latter measurement explaining more of the variation in mineralization [r2 = 0.283 (P < 0.001) and 0.433 (P < 0.001), respectively, when site 9 was not included]. With each 0.1% increase in TN, N mineralization increased by ≈6.34 kg⋅ha−1 (Fig. 2). Cumulative net N mineralization after 4 months was not correlated to HWEON or the C:N ratio alone (P = 0.66 and 0.57, respectively; data not shown). However, inclusion of the C:N ratio with TN improved the model performance slightly over TN alone when site 9 was included, based on an ANOVA of the two models (P = 0.002) and comparisons of the r2, the Akaike Information Criterion, and the Bayesian Information Criterion; however, it did not improve the model when site 9 was excluded (P = 0.122). As such, the principle of parsimony dictated the TN alone was preferred over inclusion of TN and the C:N ratio in the model. Overall, there was more variability in N mineralization after 4 months within sites (the average SE calculated from the five samples per site was 18.4 mg⋅kg−1 NO3-N in dry soil) than between sites (the SE for the 10 sites was 11.3 mg⋅kg−1 NO3-N in dry soil). The average SEs for SOC and TN were 2.28% and 0.11%, respectively, within sites and 4.02% and 0.22%, respectively, between sites.
Cumulative net nitrogen (N) mineralization in soil collected from 10 commercial ‘Duke’ northern highbush blueberry field sites (five samples/site) in northwest Washington and incubated for 6 months at temperatures corresponding to the monthly average 20-cm-deep soil temperatures for the region. Given the much higher N mineralization in samples from site 9 compared with other sites, the data were analyzed and visualized with (right) and without (left) site 9 to prevent a single site from driving the conclusions. However, the overall interpretation did not change based on the inclusion or exclusion of site 9. Colored points represent individual samples, black and white triangles represent the mean values for samples with high (>20%) and low (<20%) soil organic carbon (SOC), respectively, and solid and dashed lines are logarithmic regressions for observations with >20% and <20% SOC, respectively. Differences in N mineralization between the high and low SOC sites at each timepoint are indicated by NS (P ≥ 0.05), * (0.01 ≤ P < 0.05), ** (0.001 ≤ P < 0.01), and *** (P < 0.001). Error bars represent ±1 SE.
Citation: HortScience 59, 6; 10.21273/HORTSCI17632-23
Relationship between net nitrogen (N) mineralization and soil organic carbon (SOC; left panel) or soil total N (right panel) in soil collected from 10 commercial ‘Duke’ northern highbush blueberry field sites in northwest Washington. Colored circles represent individual soil samples from each site, and white circles represent the mean (n = 5) for each site. Error bars represent ±1 SE. The dashed and solid blue lines were fit with site 9 included or excluded as an outlier, respectively. When site 9 is included, cumulative net N mineralization = 3.4 * SOC + 46.0, and cumulative net N mineralization = 142.1 * total N − 36.6.
Citation: HortScience 59, 6; 10.21273/HORTSCI17632-23
Soil inorganic N dynamics in the field.
Seasonal changes in soil NH4-N and NO3-N, respectively, at the four sites used for the field experiment are illustrated in Figs. 3 and 4. In most cases, the levels were not statistically separable among the N treatments at each site, although there was typically a trend for higher soil NH4-N and NO3-N with higher N application rates. In limited instances when differences between treatments were separable, NH4-N was higher with the highest N application rate (101–118 kg⋅ha−1) than with lower rates, as on 2 Jul 2019 at site 2 and on 10 Jun 2020 at site 3. Likewise, NO3-N was higher with the highest N rate than with lower rates on 10 Jun, 5 Jul, and 2 Sep in 2020 at site 3, and on 2 Aug 2021 at sites 1 to 3. In addition to the effects of the N application rates, there were differences in soil inorganic N between years and sites. Soil NO3-N was generally higher at the sites with higher SOC (sites 3 and 4) in 2020, and especially in 2021, although the impact of the SOC on soil inorganic N cannot be separated from site-specific confounding factors.
Soil ammonium-nitrogen (NH4-N) at four commercial field sites of ‘Duke’ northern highbush blueberry in northwest Washington. Soil organic carbon (SOC) at the sites ranged from 3% to 28%. Each site was fertilized with 33 to 55 (●, solid line), 67 to 84 (▪▪▪, dotted line), and 101 to 118 (◼, dashed line) kg⋅ha−1 N per year in 2019–21. Each fertilizer application is represented by an “F”. *Significant differences among the treatments in each month (P ≤ 0.05). Error bars represent ±1 SE.
Citation: HortScience 59, 6; 10.21273/HORTSCI17632-23
Soil nitrate-nitrogen (NO3-N) at four commercial field sites of ‘Duke’ blueberry in northwest Washington, USA. Soil organic carbon (SOC) at the sites ranged from 3% to 28%. Each site was fertilized with 33 to 55 (◼, solid line), 67 to 84 (▪▪▪, dotted line), and 101 to 118 (◼, dashed line) kg⋅ha−1 N per year in 2019–21. Each fertilizer application is represented by an “F”. *Significant differences among the treatments in each month (P ≤ 0.05). Error bars represent ±1 SE.
Citation: HortScience 59, 6; 10.21273/HORTSCI17632-23
Plant response to N fertilizer.
There were no interactions between the N rate × year on yield or the fruit quality measurements, including berry weight, firmness, TSS, and TA at each site (P > 0.05) (Table 2). There was an effect, however, of year on the yield at site 2, as well as on a number of fruit quality variables at several of the sites; however, given the lack of interactions between the N rate × year, results for all metrics are reported as the mean of all three years (Table 3). The N rate had no effect on yield or leaf tissue N at any site; however, medium and high N rates resulted in lower TA at site 1 (P = 0.005) and lower berry weight at site 3 (P = 0.020) than the lowest N rate at both sites (Table 3). In 2019–21, the yield averaged 22.3 to 29.2 Mg⋅ha−1 of fresh fruit per year at each site, whereas berry weight, firmness, TSS, and TA averaged 2.09 to 2.44 g/berry, 143 to 174 g⋅mm−1, 12.9% to 13.6%, and 1.62 to 1.78 g⋅L−1, respectively. Vegetative growth, as indicated by the number of whips per plant, only differed among N rates at sites 1 and 3 (P = 0.037 and P = 0.009, respectively) (Table 2). Plants that received the lowest N rate had more whips than those that received medium (site 1) or high (site 2) N rates (Table 3).
P values for yield, fruit quality, leaf tissue nitrogen (N), and whip number at four commercial ‘Duke’ northern highbush blueberry field sites treated with different N fertilizer rates in northwest Washington in 2019–21.
Yield, fruit quality, leaf tissue nitrogen (N), and whip number at four commercial ‘Duke’ northern highbush blueberry field sites treated with different N fertilizer rates in northwest Washington in 2019–21.i
Cold hardiness differed between years at each site (P < 0.05) and was affected by an interaction between year × the N rate at site 4 (P = 0.004). In this latter case, plants fertilized at the highest N rate were less cold-hardy than those fertilized at the lowest N rate in 2019, but they were more cold-hardy than those fertilized at the lowest N rate in 2020 (Fig. 5). Depending on the site and N rate, cold hardiness ranged from an average of −10 to −26 °C in 2019 and from −17 to −21 °C in 2020.
Lethal temperature at which 50% of the fruit buds were damaged (LT50) at four commercial field sites of ‘Duke’ blueberry in northwest Washington. Soil organic carbon (SOC) at the sites ranged from 3% to 28%. Each site was fertilized with 33 to 55 (●) and 101 to 118 (◼) kg⋅ha−1 N per year in 2019–21. Buds were sampled in late Oct 2019 and early Nov 2020. *Significant differences between the treatments at a given site (P ≤ 0.05). Error bars represent ±1 SE.
Citation: HortScience 59, 6; 10.21273/HORTSCI17632-23
Discussion
Net N mineralization.
As hypothesized, the SOC and TN were positively correlated with net N mineralization after 4 months (Fig. 2). Furthermore, sites with higher SOC (sites 3 and 4) generally had higher NO3-N concentrations than those with lower SOC in 2020 and 2021, regardless of the N fertilizer rate (Figs. 3 and 4). Although NH4-N concentrations showed less variation with SOC, NH4+ may be relatively rapidly nitrified, even in these low pH soils (Li et al. 2018); therefore, NO3− can be a good indicator of net N mineralization. These findings suggest that substantial N mineralization occurred at the higher SOC and TN sites, which underscores the importance of this N source and its potential to reduce the need for N fertilizer. Although blueberry is thought to display a preference for NH4-N, blueberry plants can still acquire NO3− (Alt et al. 2017), and because NH4+ is usually produced as a step in the mineralization of organic N before nitrification (Norton and Stark 2011), mineralized N can be used by blueberry plants largely as NH4+, but also as NO3−. However, synchrony between the timing of N mineralization and plant N uptake is essential. In Michigan, Throop and Hanson (1997) found that N uptake by blueberry peaks in May and June, with little to no uptake occurring afterward. Because N mineralization is strongly dependent on soil temperature, which in northwest Washington is highest in July and August, concerns have been raised that N mineralization from SOM will occur primarily after plant demand for N peaks. However, once incubation temperatures increased to 14.5 °C, substantial net N mineralization was observed, and N mineralization appeared to slow rather than increase with time (Fig. 1). This is consistent with research that showed a decline in net ammonification at higher temperatures in soils with >20% SOC (Maslov and Maslova 2022). Ultimately, these results suggest that N mineralization corresponds well with the timing of N uptake in the evaluated blueberry systems.
Contrary to what was initially hypothesized, TN was the best predictor of net N mineralization after 4 months of incubation. In fact, neither HWEON nor C:N alone was correlated with net N mineralization. The relationship between net N mineralization and TN agrees with previous studies that found that TN was highly correlated to potentially mineralizable N during ≥14 weeks of aerobic incubation (r2 = 0.48–0.60), despite a lower SOC range (0.3%–7.7%) than that of the soils used in our study (Curtin et al. 2017; Schomberg et al. 2009). Interestingly, Miller et al. (2019) also observed a relationship between N mineralization and TN; however, in their case, they found that the relationship was stronger in high SOM soils than in low SOM soils. In addition to the correlation between TN and net N mineralization, the observed correlation between SOC and net N mineralization is also consistent with that reported previously. Schomberg et al. (2009) found a strong correlation between SOC and potentially mineralizable N during a 41-week aerobic incubation (r2 > 0.60), although that study did not include Histosols.
Although the presence and direction of the relationship between SOC or TN and net N mineralization were consistent between the present and previous studies, the effect size of these relationships was much lower in the present study. In our case, net N mineralization increased by 6.34 kg⋅ha−1 with each 0.1% increase in TN, which was an order of magnitude less than that observed previously (Curtin et al. 2017; Schomberg et al. 2009). This could be because of differences in SOM quality between the studies or due to a wider range of SOC in the present study (2%–42%). It is also important to note that most studies that measured net N mineralization in an aerobic laboratory incubation kept a consistent temperature throughout the incubation, contrary to this study, which varied the incubation temperature to better represent field conditions. Given that the temperature sensitivity of net N mineralization varies with SOC (Liu et al. 2017), modifying the temperature throughout the course of the incubation may have influenced the relationship between SOC and net N mineralization.
Soil organic matter quality and C:N, in particular, are good indicators of potentially mineralizable N in tundra soil covered with a thick peat layer, with potentially mineralizable N increasing as the C:N ratio decreases (Marion and Miller 1982). However, there was no discernable trend found between the C:N ratio alone and N mineralization after 4 months of incubation. Our findings are similar to those of Bengtsson et al. (2003) and Bonanomi et al. (2019), who also found that the C:N ratio was a poor indicator of potential N mineralization. Interestingly, even though sites with higher SOC generally had higher soil NO3-N throughout the growing season in 2020 and 2021, the site with the highest SOC (28%) typically had lower soil NO3-N than the site with slightly lower SOC (26%). The fact that SOM quality has been shown to influence N mineralization may explain this disparity in soil inorganic N between the two sites (Lagomarsino et al. 2006), even if net N mineralization could not be predicted by the C:N ratio alone across the sites, because the C:N ratio was considerably higher at the site with 28% SOC (23.2 vs. 16.2 at the site with 26% SOC) (Table 1). Similarly, the site with the highest net N mineralization after 4 months in the laboratory incubation (site 9) (Fig. 2) also had the lowest C:N ratio of any of the sites with >20% SOC, and net N mineralization was more highly correlated with TN and the C:N ratio than with TN alone when this site was included.
Contrary to expectations, there was little to no relationship between HWEON and net N mineralization in the present study. Curtin et al. (2006) showed that HWEON accounted for 50% of the variation in plant N derived from mineralization, and Curtin et al. (2017) found that HWEON had the strongest correlation with potentially mineralizable N of any measured variable during a 14-week aerobic incubation, suggesting that it would be a good indicator across soil types. Given that the latter study intentionally excluded Histosols and used a much smaller range of SOC (2.5%–7.7%) than that used in our study, it is possible that the relationship between HWEON and net N mineralization only occurs in soils with lower SOC. However, there was still no relationship between HWEON and net N mineralization when samples with >12% SOC were removed from the analysis in this study (although this excluded all but 16 data points).
Plant response to N fertilizers.
The rate of N applied had no effect on yield at any site in the present study, and the effects on fruit quality were minimal. Contrary to what was initially hypothesized, higher N rates were not required to maximize yield or fruit quality at sites with lower SOM, suggesting that typical N recommendations for blueberry may be above the plant requirements, even at sites with “low” SOM. However, it should be noted that the sites with the lowest SOC in this study, although representative of the region, still had 3% SOC, which is a level that can sustain agronomically meaningful N mineralization and is higher than SOC levels in soils from other important blueberry growing regions (Lukas et al. 2022). The notion that typical N recommendations may be above the plant requirements is further supported by the leaf tissue N concentrations, which were similar at each N application rate. Although leaf tissue was below normal at some sites, according to thresholds outlined by Hart et al. (2006), recent research of critical leaf tissue nutrient thresholds for blueberries in western Washington indicated that levels between 1.5% and 2.0% N are sufficient (Lukas et al. 2022). Granular fertilizer recommendations for mature plantings in the northwestern United States are between 112 and 168 kg⋅ha−1 N (Bryla and Strik 2015), which are higher than the highest N rate used in our study (101–118 kg⋅ha−1 N). In fact, 33 to 50 kg⋅ha−1 N was adequate to maximize production in established blueberry plants for 3 years at each site in the present study. Strik et al. (2017) likewise demonstrated that lower N rates of 29–73 kg⋅ha−1 N were sufficient for maintaining yield over 9 years in soils with only 3.7% SOM (approximately 1.9% SOC), which was a lower SOM content than that of any soils in our study. Messiga et al. (2018) did not observe any yield increase above 100 to 144 kg⋅ha−1 N for broadcast N fertilizer in soil with 5.3% SOM (approximately 2.6% SOC), and although a control that was unfertilized since planting had lower yield in most years, N application rates between 0 and 100 kg⋅ha−1 N were not included in the study. More recent research in Oregon also found that yield was unaffected by N fertilization rates and further showed that mature blueberry plants can be grown successfully with lower levels of N fertilization than previously recommended (Davis and Strik 2022).
Although higher N application rates appeared to be excessive at each site in the present study, they did not cause any deleterious effects on yield or fruit quality. Salt stress has been observed in young plantings fertilized with ammonium sulfate at rates >100 kg⋅ha−1 N (Bañados 2006; Bryla and Machado 2011). However, salt stress is not usually observed in mature plantings, nor was it observed at any site in the present study. Furthermore, in addition to ammonium sulfate, other sources of N fertilizer were used in the present study, including urea and monoammonium phosphate, both of which have lower salt indices than ammonium sulfate (Bunt 1988).
Excessive N can lead to severe winter injury in blueberry by interfering with plant acclimation to winter temperatures (Smolarz and Mercik 1989). It was initially hypothesized that excess N would lead to increased vegetative growth and decreased cold hardiness. However, at sites where differences in vegetative growth were observed, plants that received the lowest N rate had the most vegetative growth, and differences between sites were much greater than differences between N rate treatments. Furthermore, there was no clear effect of high N rates on the lethal temperatures for fruit bud damage in the present study. Treatment differences were observed at only one site; in this case, higher N rates increased the lethal temperature for bud damage during one year but had the opposite effect the following year. The fact that this relationship was inconsistent between years suggests that these differences were not likely to be because of N application and were, perhaps, not meaningful biologically. Furthermore, the historical mean low temperatures in October and November in the region (which is when these samples were taken) are 4.4 and 0.8 °C, respectively, which are well above the observed temperatures that caused freeze injury in the present study. Thus, the N rate did not appear to impact cold acclimation, and even though the highest N application rate was 68 kg⋅ha−1 N higher than the lowest rate, it was not enough to cause loss in cold hardiness under the conditions of the study.
Conclusions
These results suggest several key implications for N management in blueberry. First, N mineralization from SOM appears to be a meaningful source of available N for uptake, particularly in soils with >16% SOC or >0.8% TN (i.e., where the confidence intervals of the regressions in Fig. 2 no longer overlapped with 0). Second, substantial N mineralization was observed as soon as temperatures increased from 10.6 to 14.5 °C (corresponding to field soil temperatures in May). This timing of N mineralization is particularly important because blueberry plants tend to take up most N during the beginning and middle of the growing season. Therefore, N release from SOM mineralization may be well-timed to coincide with plant uptake, even though soil temperature, a major driver of mineralization, peaks later in the growing season. Third, although TN was found to be a strong predictor of net N mineralization, the amount of unexplained variation in this relationship coupled with variation within fields complicate the ability to adjust N fertilizer recommendations based solely on soil TN. Finally, high N rates were unnecessary for maximizing yield or fruit quality at sites with lower SOM. In fact, rates as low as 33 to 50 kg⋅ha−1 N were sufficient to sustain production for 3 years at sites with 3% to 28% SOC. This is likely a result of lower, yet still agronomically meaningful, N mineralization at these sites with “low” SOM. Furthermore, mature plantings may rely on remobilization of N stored in the roots, reducing their responsiveness to N fertilizers. These results, combined with longer-term observations from other studies, suggest that N fertilizer rates could be reduced to lower input costs with no consequences to plant productivity in mature plantings of blueberry. However, because the duration of this study was only 3 years, future research should assess potential long-term effects of lower N application rates on the health and productivity of mature blueberry plantings, as well as the long-term effects on SOM.
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