TABLE 3 | Initial soil characteristics (0–30 cm) at the two sites in September 2010.

Values in brackets indicate standard deviation.

DM, dry matter.

\*plant-available concentrations; analyzed with CAL extraction followed by flame photometer (P2O5), FIA measurement (K2O) according to OENORM L 1087:2012-12-01 and CaCl2 extraction followed by AAS measurement (Mg) according to VDLUFA I A <IP_ADDRESS>; soil pH was determined using a glass electrode after CaCl2 extraction (DIN ISO 10390:2005); TOC (total organic carbon) analyzed according to DIN EN 15936:2012-11.

TABLE 4 | Characteristics of digestates and mineral fertilizer.

FM: fresh matter; DM: dry matter; STD: standard deviation.

DF, Degree of freedom; level of significance was p ≤ 0.05.

The highest yields were obtained at both sites in 2012 and 2013. After this, the yields decreased, but remained at a more or less constant level (120 dt ha−1 at the "Valley" site, 112 dt ha−1 at the "Hill" site). As expected, the yield difference between control and treatments was larger for triticale than for clover grass, indicating a more prominent fertilizing effect.

In 2015, the triticale DMY was reduced at the "Hill" site due to infestation with yellow rust (Puccinia striiformis).

**Figure 4** shows that the majority of the triticale plots were harvested too late and the DMC was higher than the optimal value, particularly at the "Valley" site. The DMC varied considerably more at the "Valley" than at the "Hill" site. In 2017, the average DMC at the "Valley" site was 63% with individual maximal values of more than 80%, whereas in the other years values were more within the normal range (46% in 2013, 36% in 2015).

### Silage Maize

At both sites, the highest maize DMY was obtained with mineral fertilizer; however, this was only significant at the "Hill" site (**Figure 5**).

At the "Valley" site, both combination treatments performed as well as the mineral fertilizer.

At the "Hill" site, all treatments with digestates except "solid" were comparable to each other and resulted in the second highest DMY after mineral fertilizer.

In general, the DMY standard deviations were higher and fluctuated more at the "Valley" than at the "Hill" site. This is likely due to the relatively high heterogeneity of the field conditions. In addition, problems with regrowth from the preceding crop Jerusalem artichoke (Helianthus tuberosus) led to massive yield reductions in certain plots, in one replication in particular, despite frequent manual weeding and the occasional herbicide application. It is interesting that the lowest standard deviation at the "Valley" site was found with mineral fertilizer indicating a reliable fertilizing effect, independent of external influences.

digestates and mineral fertilizer in comparison to unfertilized control. Error bars indicate standard deviation of accumulated yields. Means with identical letters are not significantly different from each other (n = 4, p ≤ 0.05). For explanation of treatments, see Table 1.

FIGURE 3 | Mean dry matter yield (DMY) of an intercropping system with winter triticale and undersown clover grass grown at the sites "Valley" and "Hill" from 2012–2017 fertilized with different treatments of separated biogas digestates and mineral fertilizer in comparison to unfertilized control. Checked parts of the columns indicate years in which only clover grass was harvested (2012, 2014, 2016). Error bars indicate standard deviation of accumulated yields. Means with identical letters are not significantly different from each other (n = 4, p ≤ 0.05). For explanation of treatment, see Table 1.

The effect of year was clearly recognizable. 2013 and 2015 were not good years for maize cultivation: wet and cold conditions in spring delayed sowing and/or germination; drought periods with high temperatures in summer months negatively influenced growth (see also **Figure 1** for weather data). In those years, the mineral fertilizer showed the best performance of all treatments. In years with weather conditions favorable for maize cultivation (2014, 2016, 2017) most digestate treatments worked equally well as mineral fertilizer.

The year 2016 was exceptional in that the spring was cold and wet, but there was a short favorable time slot which could be used for sowing. This was followed by a lot of rain in early summer before a dry, hot period set in. At the "Valley" site, this resulted in low DMY (on average 83 dt ha−1 for fertilized plots), but a very satisfactory yield at the "Hill" site (118 dt ha−1 ). Here, the higher altitude and thus lower average temperature, together with the deep soil, were an advantage. Consequently, the water supply lasted longer during the heatwave, ensuring better growth than at the "Valley" site.

The separated solid digestate variant led to the lowest yields of all treatments at both sites (**Figure 5**). This was visible in most years, but also for the accumulated yields. At the "Valley" site, it resulted in yields comparable to the control and to the "liquid" treatment (or even lower in absolute values). At the "Hill" site, it had a DMY higher than the control, but lower than the other treatments.

**Figure 6** shows that the majority of the maize plots were harvested with a dry matter content (DMC) within the optimal range of 30 to 35% TS. In general, DMC was lower and fluctuated less at the "Hill" site.

# DISCUSSION

Significant differences in yield performance were found between the annual, intercropping and perennial cropping systems subjected to the treatment variants. Interactions with site and year effects were also observed.

The highest and most stable biomass yields were found in the intercropping system with triticale and clover grass, irrespective of the site, treatment and year. This was followed by perennial grassland, which also proved to be relatively stable with regard to treatment and year, but provided lower DMY. Maize only produced high yields in years with favorable climatic conditions. Particularly in years with unfavorable conditions, the best maize yields were achieved with mineral fertilizer, whereas in normal years the DMY difference between treatments was small. Thus the influence of the year effect also varied between cropping systems.

In general, the "Valley" site had higher DMY, but the "Hill" site provided better conditions for growth during hot, dry periods due to the lower average temperature and longer water supply. We also observed that the treatments were more effective in terms of yield at the "Hill" site, as the DMY was significantly higher than the control on all fertilized plots in all three systems here.

## Effect of Fertilizer Treatments on Yield Performance of the Three Cropping Systems

The annual system responded most sensitively to influences of treatments, site and year. The yields were significantly influenced by all these factors. As a C4 crop, maize reacts relatively strongly to temperature fluctuations and requires favorable temperatures and sufficient water supply for germination and good establishment, especially if sown in late spring (Maton et al., 2007). In this study, the highest maize yields were achieved with mineral fertilizers, particularly in cooler years and at the cooler "Hill" site. This can be explained by the fact that mineral fertilizer application can be timed to provide plant-available N to coincide with the crop's requirements (Möller, 2009). The N availability of mineral fertilizer is also less dependent on climatic conditions, especially temperature and water supply, than organic fertilizer (Agehara and Warncke, 2005) and the share of mineral N is of course higher than in the digestates (**Table 4**). After sowing, maize first needs to build its root system and is highly dependent on rapidly plant-available N at exactly

the right time (Plénet and Lemaire, 1999). This can best be steered by the application of easily soluble mineral fertilizer.

The effect of more rapid N availability from mineral than from organic fertilizers was particularly evident in the years 2013 and 2015 when temperatures were lower than the long-term average and 2015 also had less than average rainfall during the growing season. In these years, the mineral fertilizer had significantly better results, especially at the "Hill" site, and the solids had a lower performance. In 2013 at the "Valley" site, the solids even resulted in a lower DMY than the unfertilized control. This may have been caused by initial N immobilization, which often occurs after the application of organic matter (Gutser et al., 2005).

Mineral fertilizer had the best effect on maize yield, in terms of both amount and stability, over the years. This was the case for application of mineral fertilizer alone as well as in combination with digestates. The crop's short-term demand for plant-available N was met through the mineral fertilizer and later—once the maize had established—N from the digestate had been mineralized and could provide the maize with a sufficient supply. In addition, the combinations provided at least a certain amount of organic matter (OM). This may be valuable as maize leaves a limited amount of crop residues and its cultivation tends to reduce soil organic matter and humus (Karpenstein-Machan, 2013; Komainda et al., 2018). Several studies have suggested that the combination of organic and mineral fertilizers can improve the regulation of N supply and enhance the effect of the two fertilizer types. As such, it is the most effective way of achieving both high yields and at the same time a build-up of soil organic matter (SOM) (Rauhe, 1987; Körschens et al., 1998; Svensson et al., 2004; Gutser et al., 2005; Möller, 2009). However, as simultaneous application can temporarily immobilize mineral N and increase the risk of N2O emissions, it is recommended that digestates and mineral fertilizer are applied with a time delay (Möller et al., 2009). We followed this recommendation in our field experiments.

In addition, the effect of combined mineral and organic fertilizers versus the application of mineral fertilization alone depends on site conditions. At the cooler "Hill" site, where the soil only warms up slowly in spring, the mineral treatment worked significantly better than the combinations. By contrast, at the "Valley" site, the mineral fertilizer and the combinations had comparable effects.

As expected, and observed at both sites, the yield effects of the different fertilizer types were less pronounced in permanent grassland than in the annual cropping system. As grassland is characterized by year-round soil cover, it can better exploit the long-term fertilizing effects of the organic treatments than the other two systems. These long-term effects result from the more continuous N release as well as better water retention and other factors improving soil fertility. However, grassland proved to be the system with the lowest total yields over 6 years. In addition, the aging effect of the plots in this system needs to be considered. For this reason, it is difficult to assess the effects of fertilizer treatment and system separately, as the system itself degrades over time (increasing gaps, reduction/loss of valuable grass species) and yields subsequently decrease. Therefore, the aging effect on yields may mask the fertilizer effects.

For permanent grasslands, there were also clear site effects. At the warmer "Valley" site, mineral fertilizer resulted in the significantly highest DMY. In contrast, at the "Hill" site, both treatments with solids led to the highest DMY during the experimental period. This was somewhat unexpected as the solids treatments had lower yields in the annual and intercropping systems at both sites. At the beginning of the experiment, we had assumed that organic fertilizers would be less effective the more marginal the site conditions are. As N mineralization and OM turnover are influenced by temperature (Davidson and Janssens, 2006), it was surprising to find the good performance of the treatments with solids at the site with lower average temperature and limited vegetation period. This result was undoubtedly a consequence of an interaction between system, treatment and site, but cannot be sufficiently explained by the data collected in this study. Repeated application of solid digestates could have increased the soil pH at this site, which was relatively low at

the beginning of the experiment (5.5). However, an intermediate soil analysis in fall 2014 showed that the pH had decreased to 5.3 on average on all grassland plots. The smallest decrease was found on plots treated with solids (5.4). Nabel et al. (2017) found that the comparative advantage of digestate fertilization over mineral NPK fertilization on biomass yield became increasingly pronounced over time and explained this through the crucial role of soil carbon content for plant growth. This obviously applies more to perennial systems where the soil is not disturbed and becomes more important the more marginal the soil is. This may serve as an explanation for the surprising performance of the solids at the "Hill" site. However, our hypothesis is that the proportion of nutrient supply provided by OM turnover increases with time and thus renders the grassland system increasingly independent of the direct nutrient effect of the fertilizers.

The intercropping system (here two crops grown in rotation) proved to be a stable and robust system that provided constantly high yields. In this system, the soil was almost always covered (except during early development stages of triticale). Unlike maize, generally all fertilizer treatments worked equally well independent of the site or crop. The yields in the intercropping system appeared to profit from the crop rotation effect, mainly from the biological fixation of atmospheric N2 by the clover in the mixture (not quantified). This is intended to ensure a more constant N supply independent of fertilizer applications, for example during periods of low N availability due to insufficient amounts of mineralized N. The leguminous component of this system differentiates it from the others. Grassland also contains some clover, but in the intercropping system clover is sown afresh every other year resulting in a higher proportion of legumes in the sward and consequently a higher N fixation rate.

The clover grass and triticale both developed intensive root systems; thus the intercropping system produced a considerable amount of crop residues which additionally contributed to the build-up of SOM and the residual supply of mineralized N (Fouda et al., 2013).

In this study, we focused on the effects of the treatments on biomass yield of the cropping systems and mainly limited the explanation of different fertilizer effects to differences in the timeliness of N availability and the capacity of the various fertilizer types to contribute to SOM production. Another aspect that was considered in explaining differences in yield effects of the various fertilizer types was their interaction with the three cropping systems tested here. All cropping systems have their growth peaks at different times, which clearly affects the nutrient demand and uptake during the vegetation period (Herrmann et al., 2017).

## Implications of Different Fertilization Systems

When assessing the suitability of biogas digestates as fertilizers, other aspects in addition to the yield effect need to be considered. Clearly, a farmer who produces biogas needs to dispose of the digestates. In practice, biogas digestates are often separated and used as fertilizer on the farm. However, when other feedstock streams, such as slurry, are co-digested in the biogas plant, the nutrients in the digestates constitute an oversupply at farm level. Therefore, digestates are often transported to other farms. Alternatively, they can be further processed to bio-based mineral fertilizers (Vaneeckhaute et al., 2017). For example, nutrients can be recovered from the liquid fraction by precipitation and filtered off as a mixture of phosphate salts, including struvite (Bilbao et al., 2017; Ehmann et al., 2017). Since this process is costly, the extent to which digestates are directly applied as organic fertilizer or, especially in the case of the liquid fraction, are processed into mineral fertilizer should be carefully considered on a case-by-case basis.

Mineral fertilizer use is always accompanied by the highest costs and environmental impacts, irrespective of whether it is produced chemically (N), from mining (P) or through recovery from biogas digestates (N and P). From a farming practice point of view, mineral fertilizers have the advantage of more predictable N supply on the one hand and easier applicability on the other. The latter is particularly relevant for permanent cropping systems. One major environmental benefit of digestates is that they can help save on mineral N fertilizer, either by complete or partial substitution. In good agricultural practice, gaseous emissions during and after digestate application are kept to a minimum, which was not ensured with the liquid manure spreader used in this study. Application techniques near the soil surface including trailing hoses, trailing shoes and injection would of course reduce gaseous losses (especially in systems and at stages where incorporation is not possible) and at the same time increase the plant-usable N (Möller et al., 2008). The solid fraction should ideally be incorporated into the soil to avoid gaseous N losses (Holly et al., 2017), allow for nutrient release through decomposition and avoid a layer of organic matter remaining on the crop. The application of solids is even more laborious in systems which require multiple cuts over the vegetation period. Although our results showed that solids significantly increased grassland yields, at least at the less favorable "Hill" site, the practicability of solid application remains limited. For this reason, only the liquid fraction is recommended for grassland due to its good infiltration, and also its high N and K but low P contents which correspond well with the nutrient removal by the crops (Messner, 2014).

The application of solid digestates thus appears more appropriate in cropping systems with frequent soil cultivation and on sites where a benefit from OM can be expected. Soil tillage increases the turnover of OM from digestates and crop residues (Blair et al., 2006; Sarker et al., 2018). Although solids were actually not recommendable for maize in terms of their fertilizing effect, their regular application is considered beneficial here for OM replacement (Nkoa, 2014). A study by Nabel et al. (2017) showed that organic fertilization with digestates had a positive influence on soil properties (e.g. increased soil respiration and enhanced water-holding capacity), particularly on marginal sites. The supply of nutrients other than N, including P, K and various microelements, is a further advantage over mineral fertilizer (Risberg, 2015).

In this study, we divided the fertilizer and digestate applications into several doses. In farming practice, this effort may be lowered by reducing the number of fertilizer doses. In grassland, the majority of the N dose would be applied in late winter or early spring, followed by only one more dose later on (Möller et al., 2009). In maize for example, the solids could be applied in one dose before sowing. This may even be possible for the liquids, primarily in the combinations. Lavandier et al. (2011) fertilized silage maize with up to 170 kg N ha−1 , applied in form of liquid digestate in one dose and found that this did not lead to increased Nmin values.

In this study, grassland proved to be the system with lowest yields and highest workload. Nevertheless, permanent grassland is considered the most environmentally friendly way of producing energy crops (Rippel, 2008) and provides a suitable opportunity to maintain ecologically valuable grasslands that are no longer used for fodder production. This is particularly the case when mineral fertilizer is replaced with digestates, because the grassland productivity can be maintained with lower environmental impact (Walsh et al., 2012).

### CONCLUSION

The first hypothesis underlying this study, that the influence of mineral fertilizer and separated biogas digestates on biomass yield is comparable, was confirmed. However, the recommendations that can be deduced from this vary depending on cropping system and site. All three systems tested revealed their own specific strengths and weaknesses; the same applies to the treatments. For perennial or intercropping systems, separated digestates can be fully recommended. In the intercropping of triticale and clover grass, separated digestates were able to substitute mineral fertilizer completely. Contrary to our expectations, the solids performed very well in terms of yield in interaction with grassland at the "Hill" site. However, it was seen that the use of solids in permanent grassland does not exploit their full potential. A higher benefit from solids is expected from application in annual systems where they can contribute positively to the build-up of OM. Any short-term N demand of crops is better met by a combination of digestates (liquid preferable to solid, due to high content of plantavailable ammonia-N) and mineral fertilizer. The combinations performed equally well as mineral fertilizer alone in most of the systems, sites and years and allowed mineral fertilizer input to be reduced by 66%.

The second hypothesis, that fertilization effects are stronger in annual cropping systems (with tillage) than in perennial cropping systems, could be partly confirmed. If the objective is to maximize yield performance, the preferred option is the use of mineral fertilizer alone or in combination with digestates. Since the application of solid digestates and their incorporation into soil is most difficult in perennial systems, the best balance between the goals of high biomass yield and maintenance/increase of SOM content on the one hand, and the practicability of applying solid digestates on the other, can be achieved in the intercropping system.

The third hypothesis, that fertilizing effects are influenced by site factors, particularly in the case of organic fertilizers, could also be confirmed. The effect of organic fertilizer was found to be unpredictable, especially on cooler sites. To avoid yield fluctuations and N losses on such sites, perennial systems are recommended, as they capture N released at different times in the vegetation period. For these sites, the positive effect of solid biogas digestates on soil fertility and SOM can help improve the long-term stability of biomass production.

In summary, the combined application of organic and mineral fertilizer is the best approach to implement the multiple aims in terms of high yields, low-cost farming and minimal negative environmental impacts. The good performance of the combinations, together with reduced expenses for mineral fertilizer, can help improve farmers' acceptance of organic fertilizers.

### AUTHOR CONTRIBUTIONS

AE: carried out the experiments, was involved in sample analysis and analyzed the data. UT and IL: were responsible for the original idea for the research and initial concept of the experiment. All authors contributed to the preparation of the manuscript.

### ACKNOWLEDGMENTS

AE was supported by a scholarship from the Faculty of Agricultural Sciences, University of Hohenheim. The authors are grateful to Peter Weckherlin for the excellent maintenance and management of the field experiments and to Sven Schabel and Anja Neuberdt for their assistance with fieldwork. Particular thanks go to Nicole Gaudet for proofreading the manuscript and to Jens Möhring for statistical advice. Weather data were kindly provided by the Center for Agricultural Technology Augustenberg, Karlsruhe, Germany; maize seeds by KWS Saat SE, Einbeck, Germany; and Triticale seeds 'Tarzan' by Pflanzenzucht Oberlimpurg, Schwäbisch Hall, Germany.

Selected yield data from the years 2012 and 2013 were presented at the International Conference Progress in Biogas III, 10 to 11 September 2014, Stuttgart, Germany.

### REFERENCES

Agehara, S., and Warncke, D. D. (2005). Soil moisture and temperature effects on nitrogen release from organic nitrogen sources. Soil Sci. Soc. Am. J. 69:1844. doi: 10.2136/sssaj2004.0361

Alburquerque, J. A., de La Fuente, C., and Bernal, M. P. (2012a). Chemical properties of anaerobic digestates affecting C and N dynamics in amended soils. Agric. Ecosyst. Environ. 160, 15–22. doi: 10.1016/j.agee.2011.03.007

Alburquerque, J. A., La Fuente, C., de, Campoy, M., Carrasco, L., Nájera, I., Baixauli, C., et al. (2012b). Agricultural use of digestate for horticultural crop production and improvement of soil properties. Eur. J. Agron. 43, 119–128. doi: 10.1016/j.eja.2012.06.001

**Conflict of Interest Statement:** The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Copyright © 2018 Ehmann, Thumm and Lewandowski. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

# Summer Fertigation of Dairy Slurry Reduces Soil Nitrate Concentrations and Subsurface Drainage Nitrate Losses Compared to Fall Injection

Joshua D. Gamble1 , Gary W. Feyereisen1 \*, Sharon K. Papiernik 2 , Chris D. Wente3 and John M. Baker 1

*1 Soil and Water Management Research Unit, Agricultural Research Service, United States Department of Agriculture, Saint Paul, MN, United States, 2 North Central Agricultural Research Laboratory, Agricultural Research Service, United States Department of Agriculture, Brookings, SD, United States, 3 North Central Soil Conservation Research Laboratory, Agricultural Research Service, United States Department of Agriculture, Morris, MN, United States*

### Edited by:

*Claudia Wagner-Riddle, University of Guelph, Canada*

### Reviewed by:

*Jeff John Schoenau, University of Saskatchewan, Canada Aicam Laacouri, University of Minnesota, United States*

> \*Correspondence: *Gary W. Feyereisen<EMAIL_ADDRESS>
### Specialty section:

*This article was submitted to Waste Management in Agroecosystems, a section of the journal Frontiers in Sustainable Food Systems*

> Received: *31 January 2018* Accepted: *23 April 2018* Published: *15 May 2018*

### Citation:

*Gamble JD, Feyereisen GW, Papiernik SK, Wente CD and Baker JM (2018) Summer Fertigation of Dairy Slurry Reduces Soil Nitrate Concentrations and Subsurface Drainage Nitrate Losses Compared to Fall Injection. Front. Sustain. Food Syst. 2:15. doi: 10.3389/fsufs.2018.00015* Leaching of nitrate (NO3-N) from manure-applied cropping systems can represent a substantial N-loss to the environment for dairy farms, particularly in fields with artificial subsurface drainage. In this on-farm study, we used a Before/After analysis to assess the effectiveness of summer fertigation with reduced manure rates (years 2010-2015) vs. fall injection (2007-2009) of dairy slurry in terms of subsequent corn silage yield, corn N removal, soil NO3-N distribution, and NO3-N losses in subsurface tile drainage from a 65-ha field in Minnesota, USA. Yield was similar between periods (average of 18.8 Mg ha−1 ), but crop %N, N removal, and manurial N-use efficiency (MNUE) were 15, 12, and 126% greater during the fertigation than injection period. Fertigation reduced spring soil NO3-N concentrations to 60-cm depth by an average of 53% relative to injection, except in the 15–30 cm increment, where no difference was found. Similarly, fall soil NO3-N concentrations from 30 to 90 cm were 48% lower, on average, under fertigation than injection. Weekly flow-weighted mean NO3-N concentration in tile drainage was lower during fertigation (47.7 mg L−1 ) than injection (56.8 mg L−1 ), although mean weekly drainage depth was greater during fertigation (2.3 vs. 1.1 mm). This resulted in similar weekly loads between periods (mean of 0.96 kg NO3-N ha−1 ). For non-snowmelt flow, relationships between drainage and NO3-N load showed log–log slopes of near 1.0 for injection and 0.97 for fertigation, indicating dilution of concentrations with increased flow during fertigation, but not during injection. Differing intercepts indicated a treatment effect of fertigation independent of flow effects, and corresponded to loads of 5.9 kg NO3-N ha−1 for injection and 4.7 kg NO3-N ha−1 for fertigation, a reduction of 20% at a 10 mm weekly flow depth. The magnitude of the reduction in load increased to 22% at a 25 mm weekly flow depth. Results suggest that summer fertigation with attendant reduction in application rate is a viable method for reducing drainage NO3-N losses without impacting yield of irrigated silage corn in the U.S. Midwest.

Keywords: dairy manure, nitrate losses, soil nitrate, manure injection, fertigation, subsurface drainage, irrigation

# INTRODUCTION

The US dairy industry has changed dramatically in recent decades, with a trend toward geographic consolidation into fewer, large-scale confinement operations. From 1992 to 2012, the total number of dairy farms declined by about 60%, down to about 44,000 farms, while the number of farms with more than 1,000 cows increased by over 200%, up to over 1,800 farms (USDA-NASS, 2014). By 2012, nearly 50% of all dairy cows in the US were on farms of 1,000 cows or more, up from a mere 10% in 1992. This has resulted in a geographic consolidation of dairy manure production, and has also led to an increased reliance on corn (Zea mays L.) silage for animal feed in place of perennial forages like alfalfa (Medicago sativa L.). In Minnesota, many of the larger dairies are located in the Minnesota River basin, a highly impaired drainage that is the primary source of nitrogen, phosphorus, and sediment exported from the state via the Mississippi River (MPCA, 2014). Much of the cropland in this region is tile-drained, facilitating rapid transport of water and nutrients from the point of application to nearby waterways (David et al., 2010). These factors, coupled with the aforementioned manure consolidation and loss of perennial cover, raise questions about the water quality implications of the trend toward larger operations in the dairy industry.

Manure can be a valuable source of crop nutrients, but it can be challenging to synchronize nutrient availability with plant needs because of variability in the timing of organic N and P mineralization into plant-available inorganic forms. This is a particular challenge for corn silage production, because the N demand of corn is large and must be met within a relatively short time frame. The uncertainty regarding the timing of N availability, along with the narrow window for crop N need, leads producers to err on the high side with respect to manure application rates (Tarkalson et al., 2006). Over time, high-rate manure applications can result in elevated soil NO3- N (Muñoz et al., 2003), which in turn can lead to higher NO3-N concentrations in subsurface drainage (Randall and Mulla, 2001).

While the agglomeration of dairy animals into fewer, but larger, operations within the region may pose a significant risk to downstream water quality, it may also present unique opportunities for improvement. Economies of scale may make it practical to apply practices in large operations that would be prohibitively expensive for smaller operations. Herein we describe an on-farm experiment done in collaboration with a large dairy farm in Minnesota, U.S.A. The cooperating farmer was interested in understanding the environmental impacts of the current manure application practice, fall injection, as well as the viability and environmental impact of a unique alternative application technique—summer fertigation, or applying diluted, screened dairy slurry through an irrigation system. Previous research at the cooperating dairy has evaluated the effects of a rye cover crop on drainage NO3-N and P losses (Krueger et al., 2013), the effects of replacing open surface tile inlets with fine gravel inlets on sediment and P losses (Feyereisen et al., 2015), and changes in soil organic carbon related to agronomic management and terrain (Gamble et al., 2017).

Fall injection of manure following corn silage harvest is a common management practice for dairy producers in the region. Early fall represents the best opportunity to access the field in terms of trafficability, and it also allows producers to shift manure application away from the busy planting season. However, nutrients in fall-applied manure are especially vulnerable to leaching loss over winter and into the wet spring months, particularly in fields with artificial subsurface drainage. Krueger et al. (2013) reported annual losses of up to 89 kg NO3-N ha −1 in drainage from fall manure-injected silage corn at the same dairy, a loss of roughly 20% of the total N applied in manure. Greater synchrony between the timing of manure application and peak crop nutrient demand could improve crop nutrient utilization and reduce N losses in drainage (Magdoff et al., 1997).

In irrigated fields, such as those at our cooperating dairy, fertigation is an appealing alternative to fall injection that could better synchronize nutrient availability with plant needs. Applying manure via an irrigation system requires little machinery traffic across the field, making growing season application a realistic option. It could also allow for lower application rates over time, as a greater fraction of applied N should be utilized for plant growth, rather than lost to the environment. However, little research has been done at the field-scale to evaluate summer fertigation as a viable manure application practice for corn silage production. We assessed the effectiveness of summer fertigation with reduced manure rates vs. fall injection of dairy manure in terms of subsequent corn silage yield, soil nitrate-N dynamics, and nitrate-N losses in subsurface tile drainage effluent from a 65-ha silage-corn production field. We hypothesized that converting to summer fertigation with lower application rates from fall injection would increase crop utilization of manurial N and reduce nitrate-N losses in subsurface tile drainage without reducing silage corn yields.

### MATERIALS AND METHODS

### Site Description

The study was conducted on a 65-ha field on a privately owned dairy farm in west-central Minnesota from September 2006 through October 2015. Soils at the site were formed in calcareous loamy glacial till, characteristic of the prairie pothole soils of the Upper Midwest. Soils on higher landscape positions included a well-drained Forman clay loam and moderately welldrained Aastad clay loam. The soil on side slopes surrounding depressions was primarily a somewhat poorly drained Hamerly clay loam, while depressional areas were characterized by poorly drained Parnell silty clay loam, Parnell-Flom silty clay loam, and Nuttie-Hatley clay soils.

The study field is extensively tile drained (**Figure 1**). Mapping of the study site with light detection and ranging (LiDAR) revealed low relief with elevation varying by approximately 5 m across the 65-ha research site. From the resulting topographic map, a watershed of 26.6 ha was delineated in ArcGIS 10.1 (ESRI, Inc., Redlands, CA) for sampling of subsurface drainage. The drainage system included 18 surface inlets designed to quickly drain depressional areas during spring snow melt and after large

rain events. These were open inlets from the start of the study through the fall of 2009. In October 2009, all of the open inlets in the field were converted to gravel inlets and some additional tile drainage was added to the field. These changes resulted in a slight increase in the watershed area, from 26.6 to 26.7 ha. The drainage discharged into the subsurface drainage system of an adjacent field. Approximately 0.74 ha of the study watershed lay on the adjacent field.

Precipitation was measured at the site beginning on 4 September 2007 using a tipping bucket gauge with a manual rain gauge backup. Frozen precipitation was not measured, so October to April precipitation data were obtained from the University of Minnesota West Central Research and Outreach Center (WCROC), located 16 km away. Any other missing precipitation data throughout the study period were filled with data from the WCROC.

# Agronomic Management

The field was planted to corn (Zea mays L.) each year of the study on dates ranging from 22 April to 22 May, and was harvested for silage each late summer/early fall on dates ranging from 28 August to 29 September (**Table 1**). In the fall of 2006, 2007, and 2008, liquid dairy manure was injected by drag-line injection at 97,000–150,000 L ha−1 , with dates of application ranging from 28 August to 4 November. In 2006, manure was pumped directly from the stirred lagoon, while some solids were removed before injection in 2007 and 2008. After all applications, the field was tilled to a depth of 23–30 cm with a disk ripper (Ecolo-Tiger 870, Case IH, Racine, WI, USA), except in 2008 when tillage occurred before manure application. Center pivot irrigators with drop nozzles (T3000 Trashbuster, Nelson Irrigation Corp., Walla Walla, WA, USA) were installed in October 2008, and irrigation began in May 2009 and continued each year throughout the study. No manure was applied in 2009 during the transition to fertigation. Starting in 2010, manure was fertigated via centerpivot irrigation system at 46,000–143,000 L ha−1 (**Table 1**) on dates ranging from 24 June to 9 July. Two applications were made in 2010 as the producer was experimenting with application techniques. During the first application, undiluted manure was applied. During second application, manure was diluted to a 50/50 mixture with well-water, and all subsequent applications were done this way. In 2015, manure was applied to less than a third of the field due to irrigator malfunction, and 84 kg N ha−1 of mineral fertilizer was applied to the remainder of the field.

# Water Sampling

Subsurface flow measurement and water sampling equipment were deployed in a manhole access to a 38-cm submain at the edge of the field. Details of the water monitoring and sampling system can be found in Krueger et al. (2013) and Feyereisen et al. (2015). Briefly, for the 2007–2009 period, stage was measured immediately upstream and downstream from a weir with bubbler level gauges (Model 4230, Teledyne Isco, Inc., Lincoln, Nebraska), and a rating curve was used to calculate flow rate. In March 2010, an area-velocity sensor (Model 2150, Teledyne Isco, Inc.) was installed. Water samples were collected on a flow-interval basis with an automated sampler (Model 3700 or 6712, Teledyne Isco, Inc., Lincoln, Nebraska). The autosampler was programmed (2007–2009) or triggered by the area-velocity sensor (2010-2015) to draw a 100-mL subsample per 300 m3 of flow or 0.7 mm of depth (Harmel and King, 2005). Groups of three subsamples were combined into 300-mL glass jars containing 0.6 mL concentrated H2SO4 (Clesceri et al., 1998). Samples were retrieved weekly, filtered using a 0.2µm nylon filter, and refrigerated. Determination of NO3-N was by cadmium (Cd) reduction with an Alpkem RFA300 (Alpkem Corp., Clackamas, Oregon).

# Crop Yield and N Sampling

In 2007, total wet mass of corn silage was recorded by the farmer by weighing each truckload of corn silage removed from the field, and five approximately 1.5-kg subsamples were collected for dry matter (DM) determination. In all remaining years, corn DM yield was determined by hand harvesting and weighing a 3 m length of row in at least 16 randomly-selected locations, collecting a subsample of three plants in each location.

*† Total N determined via combustion.*

*‡ An irrigator malfunction resulted in a low manure rate so an additional 84 kg N ha*−1*of mineral fertilizer was also applied.*

Subsamples were dried at 65◦C for 48 h for DM determination and ground to pass through a 1 mm sieve for N analysis by dry combustion (Bremner and Mulvaney, 1982) using a Leco TruSpec CHN Analyzer (Leco Corp., St. Joseph, Michigan). Crop N removal was calculated as the product of crop DM yield and N concentration. Manurial N-use efficiency (MNUE) was calculated as the ratio of crop N removal to manure N applied.

### Soil Sampling

Soil samples were collected after corn silage harvest and before manure application, on dates ranging from 25 August to 10 September, and again in spring on dates ranging from 14 May to 9 June. Late summer/early fall samples were collected within the watershed at 21 locations in a grid pattern with approximately 113 m between sample locations (**Figure 1**). Spring soil samples were collected from 15 locations in the watershed from a subset of the fall locations. Samples were collected to a depth of 60 cm in the spring and 90 cm in the fall using a hydraulic sampling probe with a core inner diameter of 6.5 cm, except in fall 2009 when a sampler core with an inner diameter of 3.8 cm was used. Cores were subdivided into 0–5-, 5 to 15-, 15–30-, 30–60-, and 60–90 cm layers, dried at 37◦C, and ground to <0.5 mm for chemical analysis. Soil samples were extracted with 1 M KCl and NO3- N was determined colorimetrically using flow injection analysis (Alpkem Corp., Clackamas, Oregon).

## Experimental Design and Statistical Analysis

Analysis was conducted using the Before/After design of Spooner et al. (1985), splitting the dataset into periods when manure was injected (2007-2009) and when it was applied through fertigation (2010-2015), hereafter referred to as the "injection period" and "fertigation period," respectively. For water samples during the injection period, the corresponding manure application occurred the previous fall. It is important to note that these periods also correspond with the conversion of open tile inlets to closed, gravel inlets in late fall 2009. Previous research suggests no clear difference in NO3-N loading in drainage between open tile inlets and gravel inlets (Smith and Livingston, 2013), though we acknowledge this change in the drainage system as part of any treatment effects observed in our analysis. A transition period from 1 October 2009 to 31 December 2009 during drainage renovation was excluded from analysis here. All statistical analyses described herein were conducted in program R (R Core Team, 2016).

Flow weighted mean (FWM) concentrations were calculated for each week. Loads were calculated by multiplying the sample concentration by the volume of water passing the sampling point during subsampling using the midpoint in flow as the point of divide between samples. Loads and flow depth were then summed by week for further analysis.

### Weekly Mean Flow, Nitrate Concentration, and Nitrate Load Comparisons

We used t-tests to compare average weekly flow depth, FWM NO3-N concentrations, and NO3-N loads between periods (manure injection vs. fertigation). In these comparisons, we used only non-zero weekly values, and data were square transformed (concentrations) or natural log transformed (flow and loads) to meet assumptions of Normality. There were 88 weekly observations during the injection period and 104 weekly observations during the fertigation period with recorded flow. Serial correlation was present in the weekly datasets, so errors were not independent over time. To account for this effect, we adjusted the standard error equation for the t-tests as Ramsey and Schafer (2013):

$$SE = \sqrt{\frac{1+r\_1}{1-r\_1}} \times \frac{s}{\sqrt{n}}\tag{1}$$

where s is the pooled standard deviation, n is the total number of weeks (sample size), and r1 is the first order serial correlation coefficient. Under the condition where r1 is zero (i.e., no serial correlation), the above equation becomes the usual standard error equation. We calculated the first order serial correlation coefficient using the acf function in the "stats" package of program R (R Core Team, 2016). Means reported in the text are back-transformed to the original scale.

### Effects of Manure Rate and Timing on Drainage Nitrate Concentrations

We hypothesized that water samples collected following high rates of manure N application would exhibit higher concentrations than those following lower application rates, regardless of manure application method. Further, we hypothesized that concentrations would remain higher over time (weeks) following high application rates. For this analysis, we created variables in the weekly nitrate concentration dataset to account for two factors related to the potential impacts of manure. The first was a categorical variable to account for the N rate of the most recent manure application for each weekly observation, where manure rates were grouped into equally sized intervals of 0–150, 150–300, and 300–450 kg N ha−1 . The second was a continuous variable that specified the number of weeks since the most recent manure application.

These variables were then regressed onto the weekly FWM nitrate concentrations to determine if and how manure N rates impacted nitrate losses over time. For this analysis, we first fit an intercept-only model to evaluate potential serial correlation in model residuals. This model was then fit with different temporal correlation structures using the gls function in the R package "nlme" (Pinheiro et al., 2013), and results were compared using AIC to determine the correlation structure that best accounted for temporal patterns in the data. These results were confirmed by examining autocorrelation plots of the normalized residuals and plots of the normalized residuals vs. predicted values. Once a suitable correlation structure was selected, all possible explanatory variables were added to the model and significance was determined via t-test of each coefficient in the regression summary output at α = 0.05.

### Nitrate Transport Dynamics

To assess NO3-N transport dynamics, we evaluated the relationship between weekly nitrate load and flow depth for each period. This analysis also allows for comparison of the water quality implications between periods. In this analysis, we fitted a linear regression to the natural logarithm of weekly NO3-N load (kg ha−1 ) vs. natural logarithm of weekly flow depth (mm). When the slope of this regression line equals one, the nutrient concentration remains constant with varying flow depth (Tomer et al., 2003; Ghane et al., 2016). When the slope is greater than one, high flows lead to increased concentration, and/or low flows lead to lower concentrations. Moreover, the slope is the percent increase in contaminant load induced by 1% increase in flow depth.

For this analysis, we followed the same model-fitting procedure as described above. We first fit an intercept only model, then determined the best correlation structure, then added all explanatory variables and determined the significance of each model coefficient at α = 0.05. We hypothesized that the effect of flow on NO3-N loads would vary by season, so we also fit a fixed effect for season, where "snowmelt" was 1 March to 15 April, "growing season" was 16 April to September 30, and "winter" was 1 October to the following 28 February.

### Soil and Crop Analysis

Crop DM yield and crop N were analyzed with mixed-effects ANOVA treating period (injection or fertigation) as a fixed effect and sampling site within year as a random, repeated measure. MNUE was analyzed in the same manner. Fall residual soil NO3-N, and spring soil NO3-N were also analyzed with mixedeffects ANOVA, treating period and depth as categorical fixed effects, and sampling site within year as a random, repeated measure. Mixed effects ANOVA was conducted with the lme and anova.lme functions in the R package "nlme" (Pinheiro et al., 2013).

# RESULTS AND DISCUSSION

### Weather and Drainage

Mean daily air temperature ranged from −29 to 30◦C over the study period. Mean annual temperature was 0.8◦C higher than the 30-year climatological normal of 5.8◦C in 2007, but 0.6 and 0.7◦C below normal in 2008 and 2009 (**Figure 2**, **Table 2**). Mean annual temperatures were 0.8, 0.2, 2.4, and 1.8◦C above normal in 2010, 2011, 2012, and 2015, but 1.1 and 0.8◦C below normal in 2013 and 2014. Averaged over years, mean annual temperature was 0.1◦C lower than normal during the injection period and 0.5◦C higher than normal during the fertigation period. Annual precipitation during the injection period ranged from a high of 720 mm in 2007 to a low of 562 mm in 2009, although in 2009, 194 mm of the precipitation fell during the transition period. An additional 102 mm of water was applied as irrigation during the summer of 2009. During the fertigation period, annual precipitation ranged from 493 mm in 2012 to 854 mm in 2010. Annual irrigation rates ranged from 0 mm in 2015 to 126 mm in 2010, with an annual average of 68 mm yr−1 applied as irrigation, which includes water applied during fertigation. Total water applied (precipitation plus irrigation) was, on average, 79 mm yr−1 higher during the fertigation period (707 mm yr−1 ) than the injection period (628 mm yr−1 ), primarily as a result of the additional water applied as irrigation.

Annual drainage during the three-year injection period ranged from 95 to 160 mm yr−1 , with an annual average of 119 mm. During the six-year fertigation period, annual drainage ranged from 59 to 252 mm yr−1 , with an annual average of 140 mm. During the transition period in fall 2009, there was 165 mm of drainage that was excluded from subsequent analysis. The average ratio of drainage to total water applied was strikingly similar between periods, averaging 0.19 ± 0.03 (mean ± SE) during the injection period and 0.19 ± 0.04 during the fertigation period. This suggests that the changes to the tile drainage system in 2009 had little impact on the fraction of drainage, and that a before/after pairing is appropriate for the two periods. However, because total water inputs were greater during fertigation, the average weekly flow depth was also greater during the fertigation period (µ = 2.3 mm) than the injection period (µ = 1.1 mm; t = 2.22, df = 172, P = 0.0348) when weeks with no flow were excluded (**Figure 3**).

### Nitrate-N Concentrations in Drainage

Weekly FWM NO3-N concentrations ranged from 5.6 to 87.3 mg L −1 , with the highest concentrations generally occurring during the growing season and lowest generally in snowmelt (**Figure 4**). Weekly FWM NO3-N concentrations exhibited substantial autocorrelation, with r1 = 0.59. After accounting for this autocorrelation, we found that NO3-N concentration in tile drainage was 16% lower during fertigation (µ = 47.7 mg L−1 ) than the injection period (µ = 56.8 mg L−1 ; t = 2.96, df = 172, P = 0.0054, **Figure 3**). However, given the difference in flow between periods, this could be a dilution effect of greater flow

TABLE 2 | Annual precipitation, average air temperature, irrigation, tile drainage, and nitrate-N load for the study field.

*† The transition period began October 1, 2009 and ended December 31, 2009.*

during fertigation. This possibility is explored further in section Nitrate Transport Dynamics below.

A 16% reduction in NO3-N concentration is a substantial improvement, but 47.7 mg L−1 is still well above the EPA drinking water standard of 10 mg L−1 . Concentrations exceeding this standard also contribute to downstream acidification, eutrophication, and toxicity to aquatic organisms (Camargo et al., 2005; Camargo and Alonso, 2006). However, by the final two years of the study, average concentration was further reduced to 37 mg L−1 , suggesting continued improvement as manure rates were reduced and the soil N pool was drawn down.

### Nitrate-N Loads

Total load during the three-year injection period was 166.6 kg NO3-N ha−1 , with an annual average of 55.5 kg NO3-N ha−1 yr−1 . Total load during the six-year fertigation period was 282.3 kg N ha−1 , with an annual average of 47.1 kg NO3-N ha−1 yr−1 . The total load during the transition period (winter 2009) was 90.5 kg NO3-N ha−1 , which was excluded from further analysis because of the management transition to fertigation and construction on the drainage system. During the injection period, over half of the losses (86 kg ha−1 , 52% of total) occurred during the growing season of 2008 (**Figure 5**). Total load was low in 2007, and loads were similar among seasons, as were 2009 loads prior to the transition period. During the fertigation period, very few losses were observed during snowmelt and the winter; the majority of loss (89%) occurred during the growing season. Loads were highest during 2010 and 2011 when manure rate remained high. From 2012 to 2015, loads were considerably lower, which corresponded to a reduction in manure rate.

Weekly NO3-N loads ranged from 0 to 25.4 kg NO3-N ha−1 , with the highest weekly loads generally observed during the growing season and the lowest during winter. Weekly loads exhibited substantial autocorrelation, with r1 = 0.44. After accounting for this autocorrelation, we found that weekly mean NO3-N load in tile drainage was similar for the fertigation (µ = 1.28 kg NO3-N ha−1 ) and injection periods (µ = 0.63 kg

NO3-N ha−1 ; t = 1.84, df = 180, P = 0.1222, **Figure 3**). This was caused by greater flow during fertigation, as NO3-N concentrations were lower during this period.

### Soil Nitrate Concentrations

Preliminary analysis indicated that both spring and fall soil NO3-N concentrations varied with depth. Therefore, all further analyses were conducted by depth increment. In the spring, soil NO3-N concentrations were greater during injection than fertigation for all depth increments except 15–30 cm (**Figure 6**). From 0 to 5 cm, geometric mean spring NO3-N concentration was nearly 70% lower during fertigation (µ = 13.0 ppm) than injection years (µ = 39.9 ppm; F = 10.5, P = 0.0022). Likewise from 5 to 15 cm, NO3-N concentration was 55% lower during fertigation (µ = 14.5 ppm) than injection years (µ = 32.5 ppm; F = 8.7, P = 0.0050). From 30 to 60 cm, NO3-N concentration was 35% lower during fertigation (µ = 12.1 ppm) than during injection years (µ = 18.6 ppm; F = 10.0, P = 0.0027).

Fall-residual soil NO3-N concentrations were similar during injection and fertigation periods for the 0–5-, 5–15-, and 15– 30-cm depths. From 30 to 60 cm, NO3-N concentration was nearly 40% lower during fertigation (µ = 6.3 ppm; F = 27.3, P = < 0.0001) than during injection (µ = 10.3 ppm). From 60 to 90 cm, soil NO3-N concentration was 55% lower during fertigation (µ = 6.6 ppm) than injection years (µ = 14.6 ppm; F = 49.6, P ≤ 0.0001).

These results demonstrate that summer fertigation of moderate rates of manure N can reduce the amount of NO3-N in the soil profile during two critical times of the year relative to fall injection. This appears to be a function of both manure timing and placement. Fall injection resulted in higher spring concentrations, but this N was of limited benefit to the crop, as root development is typically just underway by mid-May (Chaudhary and Prihar, 1974). Much of the N mineralized from the manure was, therefore, subject to loss during the wettest time of the year. In contrast, summer fertigation appeared to provide greater synchrony by supplying N just before peak crop demand,

around the six-leaf stage for corn (Magdoff, 1991). This was evident in fall soil NO3-N concentrations, which were reduced in deeper soil increments during fertigation relative to injection. This suggests either less mineralization at these depths during fertigation or less percolation of mineralized N to depth. Given that soil nitrate concentrations were similar in the upper soil increments between periods, we think these patterns suggest that the timing and placement of manure with fertigation resulted in less percolation of NO3-N below the crop root zone.

### Nitrate Transport Dynamics

The model that best accounted for the autocorrelation in weekly NO3-N loads included an autoregressive moving average (ARMA) correlation structure accounting for correlation up to 1 lag (week), along with a 3-lag moving average. We then fit effects of log-transformed flow, season, and period, as well as all twoand three-way interactions among these variables ("full model," hereafter). Results from the full model show that the effect of flow on NO3-N load was similar for winter and the growing season (t = 0.71, P = 0.4789), but differed during snowmelt (t = 6.67, P < 0.0001; **Table 3**). Therefore, snowmelt data are treated separately hereafter, and growing season and winter data were grouped for further analysis ("non-snowmelt" hereafter).

Analysis of log-log plots of NO3-N load vs. flow rate for the non-snowmelt data showed differences in the effect of flow between periods, as evidenced by significantly different slopes (t = 2.08, P = 0.0397) and intercepts (t = 3.64, P = 0.0004; **Figure 7**). During the injection period, the slope was β = 0.996 ± 0.017 (mean ± 95% CI), indicating that for each 1% increase in flow depth, there was a corresponding 1% increase in NO3- N load (i.e., concentration did not vary by flow rate). For the fertigation period, the slope was β1 = 0.966 ± 0.023, indicating that for each 1% increase in flow depth, there was a corresponding 0.97% increase in NO3-N load. Thus, high flows resulted in slightly reduced NO3-N concentrations during the fertigation period. Additionally, the intercept was lower during the fertigation period (β0 = 1.556 ± 0.102) than the injection period (β0 = 1.769 ± 0.080), which indicates a treatment effect of fertigation, independent of flow effects.

For snowmelt, results showed no difference in the effect of flow on NO3-N loads between periods as evidenced by similar slopes (t = 0.16, P = 0.8746) and intercepts (t = 0.20, P = 0.8467). Across both periods, the slope was β1 = 0.801 ± 0.45. Given this high variability, the slope for snowmelt was not different from 1, indicating that NO3-N load was proportional to flow depth in spring snowmelt.

The lower slope and intercept of the log NO3-N load vs. log flow rate line for the fertigation period is evidence of a water quality benefit of the fertigation treatment. The lower intercept for the fertigation period indicates lower NO3-N loads when the natural-log flow depth was 0, which corresponds to a weekly flow depth of 10 mm. The back transformed intercept values were 5.9 kg NO3-N ha−1 for injection and 4.7 kg NO3-N ha−1 for fertigation, a reduction of 20%. Furthermore, the slope was lower during fertigation, which indicates that the magnitude of the reduction in NO3-N load increases with increasing flow beyond 10 mm depth. However, below 10 mm flow, the magnitude of reduction is lower. For example, at a flow depth of 5 mm

\**Significant at the 0.05 probability level.*

\*\**Significant at the 0.01 probability level.*

\*\*\**Significant at the 0.001 probability level.*

the average loads were 2.96 kg NO3-N ha−1 for injection and 2.43 kg NO3-N ha−1 for fertigation, a reduction of only 18%. In contrast, for a weekly flow of 25 mm flow, the magnitude of reduction was 22%, with average loads of 15.0 kg NO3-N ha−1 for injection and 11.7 kg NO3-N ha−1 for fertigation. This represents a substantial reduction in nitrate load, as there were 22 weeks that exceeded 25 mm in flow during the fertigation period. These events accounted for 74% (620 mm) of the total flow and 65% (184 kg NO3-N ha−1 ) of the total load during this period. Given that this represents a 22% reduction in load compared to injection, we would expect a load of 209 kg NO3-N ha−1 for a similar number of 25 mm events, or an additional 25 kg NO3- N ha−1 exported, had injection continued to be used in this field. Our analysis demonstrates that loads were lower during the

tile flow depth and NO3-N loads for non-snowmelt and snowmelt periods. When the slope is one, the nutrient concentration remains constant with varying flow depth. When the slope is greater than one, high flows lead to increased concentration, and/or low flows lead to lower concentrations. Moreover, the slope is the percent increase in contaminant load induced by 1% increase in flow depth.

fertigation period than they would have been during injection under the same meteorological and hydrological conditions.

The dilution of concentrations with increasing flow suggests that the supply of NO3-N available for leaching was reduced during fertigation relative to injection. Tomer et al. (2003) note that large flows may flush contaminants and exhibit an increased concentration, or may lead to diluted concentrations, with the outcome dependent upon location and land-use. Ghane et al. (2016) provide compelling evidence that soil N status is one such land-use characteristic that affects nitrate transport dynamics. The authors evaluated relationships between drainage and NO3- N load and reported log-log slopes of 0.99 for unfertilized and 1.07 for mineral fertilized corn fields with subsurface-drainage in central Minnesota. Our findings are similar in that a lower slope was observed when soil NO3-N concentration was lower (i.e., during fertigation). It is intuitive then, that under low soil NO3-N conditions, increases in flow would cause reduced nitrate-N concentrations in drainage as the soil N supply is leached from the profile and becomes increasingly limiting. In contrast, with higher available soil N, the supply of nitrate-N for leachate is not readily exhausted, and increases in flow can result in consistent or increasing nitrate concentrations in drainage.

Despite the water quality benefit, it is important to note that fertigation may increase the risk of N-loss via other pathways. Research has shown that surface-broadcast of liquid manure results in higher losses of N via ammonia volatilization than manure injection, primarily due to lack of soil incorporation with surface methods (Sommer and Hutchings, 2001; Duncan et al., 2017). Dilution of the slurry with an equal part wellwater results in rapid percolation into the soil, which may help mitigate ammonia losses relative to other surface application methods. Denitrification is another potential N-loss pathway worth exploring. Previous research has shown that manure injection can increase cumulative N2O emissions by 84–152% relative to manure broadcast (Duncan et al., 2017), especially for spring manure applications. However, soil saturation during fertigation may increase N2O emissions relative to other surface application methods. These potential tradeoffs among N-loss pathways associated with switching to fertigation of manure require further exploration.

### Effects of Manure Rate and Time on Drainage Nitrate Concentrations

Our hypothesis was that water samples collected following high rates of manure N application would exhibit higher concentrations than those following lower application rates. Further, we hypothesized that concentrations would remain higher over time following high application rates. Regression analysis indicated that the N rate of the most recent manure application (t = 1.49, P = 0.1383) and the weeks since manure application (t = 1.77, P = 0.0787) had no discernible effect on weekly FWM NO3-N concentrations. We can, therefore, reject our hypotheses regarding the effects of manure N rate and timesince-manure-application on weekly nitrate concentrations. Even when manure rates were relatively low, nitrate concentrations in drainage remained high. This likely occurred because of the cumulative loading effect of repeated high-rate manure applications over the first four years of the study, and resulting carry-over of soil N from year to year.

During the first four years of the study, 345-444 kg total N ha−1 yr−1 were added to the soil N pool in manure, of which 107–147 kg N ha−1 yr−1 was organic N. Slow mineralization of this pool, along with that in SOM, surely contributed to the lack of decline in nitrate concentrations in the weeks following manure application. Furthermore, carry over of organic N into the fertigation years is likely why we observed high nitrate concentrations during 2010 and 2011, despite lower manure rates. So-called "legacy N" can persist in soils for years or even decades (Van Meter et al., 2016). However, decreasing NO3- N concentrations over time suggest that soil N loading was gradually decreasing in response to reduced application rates.

### Crop Yield and N Removal

Crop yield ranged from 10.6 to 21.2 Mg ha−1 yr−1 (**Table 4**) and was similar between periods (F = 0.29, P = 0.593), with mean yields of 18.9 and 18.6 Mg DM ha−1 during the injection and fertigation periods, respectively. In contrast, crop %N and total N removal (kg ha−1 ) were greater during the fertigation than injection period. Following conversion to fertigation, silage corn N at harvest increased from 1.07 to 1.23% (F = 35.5, P < 0.0001), which corresponded to an increase in N removal from 205 to 230 kg N ha−1 yr−1 (F = 6.32, P = 0.0133). This resulted in greater MNUE during fertigation (µ = 1.20 kg/kg) than injection (0.53 kg/kg, F = 68.28, P < 0.0001).

Although there was no difference in yields between periods, data suggest that yields were beginning to decline slightly by 2014 and 2015, down to approximately 17 Mg ha−1 . Manure rates had been dramatically reduced since 2010, perhaps too much so. Crop MNUE was greater than 1 during much of the fertigation period, suggesting that the crop was mining additional N from the soil. Over time, a slight increase in the manure rates may be required to maintain crop nutrition and yield with fertigation, though tradeoffs with water quality should be closely monitored.

### SUMMARY AND CONCLUSIONS

Switching from fall injection to summer fertigation allowed this producer to reduce manure N rates, thereby reducing tile NO3-N concentrations and loads, without impacting corn silage yield. Greater flows were observed during the fertigation period than the injection period because of increased precipitation and irrigation. This resulted in similar weekly NO3-N loads between periods, but over time resulted in decreases in annual loads, due to lower nitrate-N concentrations in tile drainage during fertigation.

Analysis of NO3-N flow dynamics suggested that the change in concentrations between periods was not solely a result of dilution, but also a treatment effect of fertigation, independent of flow effects. The treatment effect was the result of a combination of factors. Manure N rates were reduced during fertigation, which undoubtedly helped reduce losses, but the timing and placement of manure N was also important. Crop N uptake and MNUE were greater during fertigation than injection, which suggests that summer fertigation is a more efficient means of delivering N to the crop. This greater utilization, in turn, enables lower manure application rates and results in reduced N losses in drainage.

Results from the soil analyses support these findings. Spring soil NO3-N concentrations were lower at most depths during fertigation than injection. Lower spring soil concentrations

*† Average yield estimated at the field scale by producer.*

*‡Manurial N-use efficiency, calculated as the ratio of crop N removal to manure N applied (*Table 2*). Not calculated for 2015, when mineral N was applied because of irrigator malfunction.*

should result in lower growing season N losses in drainage, which we observed here. Fall residual soil NO3-N concentrations were also reduced at deeper soil increments with fertigation relative to injection. This suggests that less NO3-N percolated below the crop root zone into drainage tile under fertigation.

Manure N rate and time since manure application had no discernible effect on weekly NO3-N concentrations, most likely due to the cumulative soil N loading effect of repeated manure applications prior to the study. However, decreasing drainage NO3-N concentrations over time suggest that soil N loading was decreasing in response to reduced application rates.

Fertigation requires specialized equipment to pump manure from storage lagoons to the irrigators, as well as the ability to screen solids from the manure slurry to prevent clogging of irrigator nozzles. These and additional economic and technological factors will likely influence producer decisions regarding the suitability of summer fertigation for their operations. However, with increasing awareness of the downstream effects of nitrate pollution, many producers are seeking solutions to NO3-N loss on their farms. We have demonstrated here that summer fertigation reduced NO3-N losses from an irrigated summer-annual cropping system in the US Midwest. Despite this reduction, NO3-N concentrations in the drainage water remained high relative to environmental quality standards. More research is needed to determine if drainage NO3-N concentrations from fertigated silage corn can be further reduced to acceptable levels without impacting silage yield. Additional consideration should be given to potential tradeoffs related to crop injury, crop disease prevalence, risk of pathogen transport to waterways, and alternative N loss pathways with fertigation relative to injection of dairy slurry.

### REFERENCES

### DISCLAIMER

Mention of trade names or commercial products in this publication is solely for the purpose of providing specific information and does not imply recommendation or endorsement by the U.S. Department of Agriculture. USDA is an equal opportunity provider and employer.

### AUTHOR CONTRIBUTIONS

JB, SP, CW, and GF conceived the experiments. JB, SP, and GF designed the experiments. GF, JB, CW, and SP performed the experiments. JG analyzed the data and wrote the manuscript in consultation with GF, SP, JB, and CW.

### FUNDING

Funding was provided by USDA-ARS through the St. Paul, Minnesota, and Morris, Minnesota, locations.

### ACKNOWLEDGMENTS

The authors thank the operators of the cooperating dairy farm for allowing us field access for sample collection and for performing agronomic management during the study. We also thank Todd Schumacher and William Breiter, USDA-ARS, St. Paul, Minnesota; Steve Wagner, USDA-ARS, Morris, Minnesota; David Schneider, USDA-ARS Brookings, South Dakota; and Eric Krueger, Oklahoma State University.

inlets on sediment and phosphorus subsurface drainage losses. J. Environ. Qual. 44, 594–604. doi: 10.2134/jeq2014.05.0219

dairy manure. Soil Sci. Soc. Am. J. 67, 817–825. doi: 10.2136/sssaj20 03.0817

**Conflict of Interest Statement:** The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Copyright © 2018 Gamble, Feyereisen, Papiernik, Wente and Baker. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

# Recycling of Biogas Digestates in Crop Production—Soil and Plant Trace Metal Content and Variability

Ivan Dragicevic\*, Trine A. Sogn and Susanne Eich-Greatorex

Faculty of Environmental Sciences and Natural Resource Management, Norwegian University of Life Sciences, Akershus, Norway

Production of biogas and utilization of the resulting digestates as fertilizers has been increasing in Europe in the last few decades. Depending on the feedstock used for the anaerobic digestion process, these organic fertilizers may be a source of different pollutants, such as trace metals. When applied to soils, digestates may influence the natural metal content and enhance the release of metals to the environment since they can be rich in different trace metals and are usually rich in dissolved organic matter. This study focused on investigating metal presence, seasonal variability of their soluble forms and crop uptake in a 2-year field experiment, using two different biogas digestates as fertilizers. The use of digestates as fertilizers was compared to cattle manure, mineral fertilizer and a control without fertilizer addition, with respect to the presence and distribution of the trace metals Cd, Cu, Zn, Ni, Cr, Mn, and Mo, as well as Al in the soil and plant. The results of the study showed that both biogas digestates have caused a 10–20% increase in the total soil concentration of Ni, Cd and Cr compared to control plots without fertilizer addition. Application of biogas digestates had only a minor effect on metal uptake in plants. Overall, the selected application rate of 100 kg/ha of plant available nitrogen has had little effect on plant metal uptake and crop quality and the use of biogas digestates was comparable to the use of animal manure.

Keywords: organic waste, fertilizer, cadmium, chromium, nickel, zinc

# INTRODUCTION

Over the last few decades, the use of different organic residues as fertilizers has increased. For instance, anaerobic digestion for biogas production results in large amounts of liquid digestate, which contains high amounts of nutrients, such as nitrogen, potassium and phosphorus, and micronutrients in plant-available forms. The fertilization benefit of digestates are well documented (Möller and Müller, 2012; Nkoa, 2014) and long-term application of digestates has been seen to improve soil quality, stimulate crop yields, and even influence positively on the soil bacteria growth (Abubaker et al., 2012).

The most common substrates for biogas production are animal manures (Fantozzi and Buratti, 2009), food waste collected from the municipal households and sewage sludge (Maragkaki et al., 2018) or co-digestion of several substrates. Most of the studies have focused on the use of manure or sewage-sludge based digestates with an emphasis on their nutrient and fertilizer value (Ni et al., 2017; Yun et al., 2018). There are few studies with digestates based on source-separated food waste focused on the optimization of digestate quality as fertilizer through co-digestion

### Edited by:

Tom Misselbrook, Rothamsted Research (BBSRC), United Kingdom

### Reviewed by:

Fiona Nicholson, Agricultural Development Advisory Service, United Kingdom Marianne Thomsen, Aarhus University, Denmark Raul Zornoza, Universidad Politécnica de Cartagena, Spain

\*Correspondence:

Ivan Dragicevic<EMAIL_ADDRESS>
### Specialty section:

This article was submitted to Waste Management in Agroecosystems, a section of the journal Frontiers in Sustainable Food Systems

> Received: 16 February 2018 Accepted: 11 July 2018 Published: 07 August 2018

### Citation:

Dragicevic I, Sogn TA and Eich-Greatorex S (2018) Recycling of Biogas Digestates in Crop Production—Soil and Plant Trace Metal Content and Variability. Front. Sustain. Food Syst. 2:45. doi: 10.3389/fsufs.2018.00045 with other materials, such as sewage sludge (Borowski et al., 2018). Recent findings have shown that food-waste based digestates can be used for growing vegetables and mushrooms, especially when anaerobic digestion is combined with hydroponics (Stoknes et al., 2016).

Modern crop production is focused on both good yield and grain quality, but also on preservation of the environment. There are studies showing that both animal manure (Nicholson et al., 1999; Yang et al., 2017) and sewage sludge (Ashworth and Alloway, 2004; Chen et al., 2017) contain trace metals in variable concentrations. Still, sewage sludge application to agricultural land is strictly regulated because of the trace elements build up in soil, in particular elements such as cadmium, mercury, lead, and chromium. Further, soil leaching studies for trace metals have showed high ecological risk factors with the application of organic wastes such as compost or manure (Cambier et al., 2014). Pollutants may be applied to soil through inorganic or organic fertilizers and may bioaccumulate in soil organisms and plants (Antoniadis et al., 2017a). The organic matter quality and structure in biogas digestates is dependent on the biogas production feedstock and the applied technology, which means that it can have an effect on the trace metal availability. Soil quality is an important factor for crop quality and yield, and will be affected negatively by accumulation of trace metals or other pollutants. One challenge with the field application of biogas digestates is their chemical safety (Törnwall et al., 2017). Naturally, the content of potential contaminants in substrates used for the biogas process determines the content of these contaminants in the digestates. Metal content in biogas digestates and its potential implications for the use as fertilizer has been a subject of increasing interest in recent years (Kupper et al., 2014; Parraga-Aguado et al., 2017). Environmental effects of added trace metals, such as uptake into plants and soil organisms or leaching to water recipients, depends on their mobility in the soil, which in turn is strongly affected by pH and dissolved organic carbon (DOC) content (Antoniadis and Alloway, 2002; Welikala et al., 2018). For instance, Cu, Zn, Cd, and Ni, are generally mobile in soil under common conditions for crop production in a Nordic climate, i.e., in a pH range between ∼6 and 7. On the other hand, As, Sb, and Hg may precipitate in insoluble forms under these conditions. Applying organic fertilizers represents an addition of DOC and may influence the pH in the soil and may thus increase the risk of plant uptake or leaching to water recipients.

In the field experiment described in this study, two digestates based on food waste were used, one digested alone and one co-digested with sewage sludge. The study has focused on the presence and availability/water extractability of the trace metals Cd, Cu, Zn, Ni, Cr, Mn, and Mo, as well as Al in soil after applying biogas digestates and animal manure in a field experiment conducted over two growing seasons. Aluminum was included because one of the digestates studied contains large amounts of Al from phosphate removal in sewage sludge with Al salts. The main hypothesis of this study was that the application of biogas digestates as organic fertilizers would increase the mobility and thus plant availability of trace metals in soil. Results of the study were used to calculate a contamination factor for each metal based on the concentrations from the soil top layer.

## MATERIALS AND METHODS

### Organic Fertilizers

For the field experiment, two commercially produced biogas digestates and cattle manure were used as organic fertilizers. The digestates (DIG) were produced at two municipal biogas plants in the southeastern part of Norway. The respective companies use different feedstock mixtures and different technologies for biogas production. The digestate marked as DIG1 is derived from pretreated (steam-exploded) source-separated household and industry food waste as substrate for the anaerobic digestion process. The second digestate, DIG2, was produced using a mixture of source-separated food waste and sewage sludge (ratio 50:50) as substrate.

The manure was a cattle slurry from the farm at the Norwegian University of Life Sciences in Ås (Norway). Before chemical analysis, all the samples were stored at 4◦C, in the case of NH4 and NO3 analysis no longer than 48 h. Selected characteristics of digestates and manure used in both growing seasons are given in **Table 1**.

# Field Experiment

The field experiment was located at Ås, southeastern Norway (59◦ 39′ 52′′N 10◦ 47′ 40′′E) on a loam soil (13% sand, 57% silt, and 30% clay, as determined by the pipette method; Elonen, 1971). The soil was an epistagnic Retisol according to the World Reference Base for Soil Resources (IUSS working group WRB, 2015). It had a pH value of approximately 6.0, a total organic matter content of 4.2% and total nitrogen content of 0.21% prior to the experiment. The field experiment was started in 2014.

The experiment was organized as a randomized complete block design with three replicates, growing barley (Hordeum vulgare L.) in 2015 and oats (Avena sativa L.) in 2016 as test crops. The field was spring-plowed and harrowed before adding the different fertilizers in April 2015 and mid-May 2016, respectively. The fertilizers were incorporated into the soil by harrowing, and fields were sown within 48 h after application of fertilizers. The size of the experimental area was 39 m × 24 m (0.094 ha), and the size of each treatment plot was 3 × 7 m (0.0021 ha).

Treatments consisted of a control without fertilizer addition (NN), mineral fertilizer (MF), animal manure (AM), and the two digestates. The mineral fertilizer used was an NPK fertilizer with an NPK ratio of 22:3:10. The applied rate per hectare was 100 kg N, 14 kg P, and 45 kg K. The amounts of digestates and manure were determined based on plant-available N NO3-N and NH4-N, **Table 1**) measured in the samples and corresponded to 100 kg N ha−1 . In a recent study it was found that the content of inorganic nitrogen in digestates was a good estimation of the fertilizer value (Sogn et al., 2018). In Norway, farmers are currently obliged to register N amounts but not P addition from organic fertilizers such as manure.

**Table 2** shows total amounts and the main nutrients N, P, and K applied with organic fertilizers in kg ha−1 .

TABLE 1 | Biogas digestates and animal manure characteristics for 2015 and 2016.

Total carbon (Tot. C) was measured in a dried sample. Values behind ± are standard deviation. \*Calculated based on the Tot N values from dry fertilizer samples (55◦c).

TABLE 2 | Amounts of nitrogen (N), phosphorus (P), potassium (K), and total carbon (Tot. C) added in kg per hectare for both growing seasons.

\*Plant available N.

The average yields for the 2015 seasons were 1.87 t ha−1 NN (control plot), 5.31 t ha−1 MF, 4.96 t ha−1 AM, 6.18 t ha−1 DIG1 and 5.64 t ha−1 DIG2. For 2016 season, the yields were 1.2 t ha−1 for NN (control plot), 4.0 t ha−1 for MF, 2.2 t ha−1 for AM, 3.9 t ha−1 for DIG1 and 4.0 t ha−1 for DIG2 plots. The data from 2016 was used for calculating total metal content in oat grains.

### Sample Preparation and Chemical Analysis

In general, the metal content in digestates depends on substrate and applied technology for biogas production. The trace metals investigated in this study are either under Norwegian or EU regulation for application of organic fertilizers, or selected based on previous research findings. Aluminum was included in the analysis because of its high content in the sewage sludge used for the production of DIG2, which in turn is due to removal of phosphorus with Al-salts before the digestion process.

The soil pH was determined by using dried soil with a soil to water ratio of 1:2.5. Total carbon content in dried soil, digestate, and manure samples was determined by a dry combustion method using a Leco Carbon Determinator EC12 (Nelson and Sommers, 1982). Water-soluble concentrations of metals were determined by extracting 5 g of soil/fresh digestates/fresh manure with 25 mL deionized water (Ashworth and Alloway, 2004). Soil water extractions are considered to be good in assessing the plant nutrient availability (van der Paauw, 1971; Sonneveld, 1990). Water-soluble concentrations of metals were analyzed within 48 h after preparing and filtering (Milipore, 0.45µm) the extracts. Water extracts of manure and digestates were also analyzed for DOC by using a Shimadzu TOC analyzer. The concentration of NO3-N and NH4-N in the organic fertilizers was determined in fresh samples by extraction with 2 M KCl and flow injection analysis using FIAstar 5000, FOSS.

For trace metal analysis, soil was sampled from the plow layer (0–20 cm) of each plot once a month from June to August. In 2015, plant material was collected at the same time, whereas in 2016, only grain samples were taken at harvest. The plant samples were dried at 55◦C for 5 days and then stored before sample preparation and analysis. Prior to total metal analysis, the soil, digestate, and manure samples were dried (24 h, 105◦C), sieved and ground. A sample of 0.2–0.3 g was digested in concentrated ultrapure nitric acid (HNO3) prior to ICP-MS analysis by stepwise (90 min) heating up to 250◦C using a Milestone Ultraclave. For the analysis of metal concentrations in soils, digestates, plants, and extracts, an Agilent ICP-MS 8800 TripleQ was used. The ICP-MS analysis has followed minor method validation (depending on the sample matrix) while certified reference materials and reference materials were used for quality control of the applied analytical methods. The filtered samples (extracts of soils and fertilizers) were prepared in 10 % ultrapure nitric acid prior to analysis.

## Statistics and Calculations

Analysis of variance (one-way and two-way ANOVA) was carried out to determine the effect of treatment on total metal concentrations in soil and grains. Two-way ANOVA was applied to the water extract concentrations after digestate application with treatment and sampling time as factors. Different means were separated by t-test. Pearson correlation was carried out to determine the pH and DOC correlation to the water-soluble metal concentration in soil. The statistical programs used were R Commander 3.2.3 and Sigma Plot 14.0. The confidence limit was 95% (p < 0.05).

Principal component analysis (PCA) is a dimension reduction technique, which may be used to demonstrate potential source and spatial distribution of metals in field experiments (Zhang et al., 2018). In the present study, the principal components (PC) were identified by the analysis of the correlation matrix for the data set regarding the water-extracted soil concentrations prepared from soils collected from the field experiment. The PCA analysis was used to identify factors underlying our set of variables (fertilizer treatments, sampling time) in order to determine relationships among them. Results were also used to investigated clustering of samples into groups based on their correlations.

A soil contamination factor (Antoniadis et al., 2017b; Shaheen et al., 2017) was calculated in order to evaluate the potential of long-term accumulation of investigated metals by applying the selected rates of fertilizers. The contamination factor, CF, was determined by the following formula (1):

$$CF = \frac{C\_i}{C\_n} \tag{1}$$

Where, ci represents the mean total concentration of the metal in soil of the organic fertilizer treatment, and cn that of the unfertilized control.

### RESULTS

# Total Metal Concentration in Digestates and Manure

The total concentrations of trace metals and Al in digestates and manure used in 2015 and 2016 are given in **Table 3**. With the exception of Cr, Ni, and Cd (DIG1 2016), trace metal concentrations were below limits set for use in agriculture (Class I). Norwegian regulation in regards to the use of organic fertilizers categorizes all organic wastes in four classes (class 0, 1, 2, and 3). For comparison we have used class 1, since only class 0 and 1 are allowing the use of organic wastes with no or minimum limitations (Authority, 2006). Nickel concentrations in both digestates were higher in 2016 than in 2015. The Cr concentrations, although high, were not increased between 2015 and 2016. Due to the technology used, Al concentration were high in DIG2 in both years. Lead (Pb) concentrations ranged from 0.5 to 6.0 mg kg−1 (data not shown), which was well below regulation values (Class I fertilizers, 60 mg kg−1 ).

## Total Concentration of Metals in Soil

Total metal concentrations in the MF treatment were almost identical to those in the control plots (NN), and results from both NN and MF are presented. Total soil trace metal concentrations are given in **Figure A1**.

When compared to control plots, total soil concentrations of Ni, Cr, Cd, Cu, Zn were significantly increased in the digestate treatments. For Cr, there was a significant decrease from June to August in both seasons. For Ni, the same significant decrease can be seen. For Zn, results from 2016 showed significant increase in total Zn concentration with biogas digestates used as treatments.

### Soil pH and DOC

Generally, pH was higher in NN and AM plots than in the digestate plots at all samplings, with the largest differences in the beginning of the season. The results from MF plots are not included in **Figures 1**, **2** since the values were not significantly different from the NN plots. For both growing seasons, the soil pH from control plots (NN) was in the range 5.8–6.0. Soil pH varied over the course of both growing seasons and depended on the treatment type (**Figure 1**). The pH decreased in both growing seasons from levels around 6.0 to the lowest 5.1. The lowest values for 2015 was DIG1 and for 2016 DIG2 in respect to August samples.

In 2016, a significantly lower pH was found for DIG2 compared to the other treatments at all sampling points.

The addition of the organic fertilizers significantly increased DOC concentrations in the soil for the duration of the growing season. In both growing seasons, the effect was most pronounced in the AM treatment (**Figure 2**).

## Water-Soluble Metal Concentrations in Soil

In general, water-soluble concentrations of the trace metals increased in all treatments over the course of the growing season, both in 2015 and 2016 (**Figure 3**). Concentrations were similar in both years with the exception of Cd, where concentrations were higher in all treatments and at all sampling dates in 2016 compared to 2015. As no significant differences in water-soluble concentrations were observed between treatments for Mn and Mo, the data is not included in **Figure 3**, but concentrations followed the same overall pattern with increasing values over the growing season.

There were no differences in Cd, Cu, and Ni concentrations between treatments at the first sampling date in 2015 and in the case of Cd, differences between treatments remained low throughout the season. In 2016, concentrations at the first sampling were generally higher for Cd than in 2016, and concentrations increased more with time in the organic

Limit for organic fertilizer (class 1) are given for those metals that are a part of Norwegian regulation on organic waste use in the same units as for treatments. AM, animal manure; DIG1, food waste based digestate; DIG2, sewage sludge/food waste digestate.

FIGURE 1 | Soil pH in from plots treated with different fertilizer treatments in 2015 and 2016. Letters show significant difference between each of the treatments (p < 0.05).

treatments than in the control. For Cu, higher concentrations were found in the organic and especially in the digestate treatments at the 2nd and 3rd sampling date in 2015. In 2016, however, the manure treatments had lower concentrations even than the control at the first two sampling dates and only DIG1 addition resulted in higher concentrations than the control. The pattern for Ni was similar in 2015 and 2016 with highest concentrations in both digestate treatments at the last two sampling dates, whereas the manure treatment was on a similar level to the control.

Zn, Cr, and Al already showed significant differences in concentrations at the first sampling date. In the case of Zn, the manure treatment showed higher concentrations than the other treatments both at the first sampling date in 2015 and 2016. For most dates, the concentrations in the organic treatments were significantly increased compared to the control. In July and August 2015, highest concentrations were found in the DIG1 treatment, whereas in 2016, the manure treatment remained the one with highest Zn concentrations throughout the season. Cr concentrations were highest in the two digestate treatments at all sampling dates but also generally also enhanced in the manure treatment compared to the control. Addition of the digestate with the high Al content (DIG2) resulted in higher concentrations of water-soluble Al at all sampling dates compared to the control, but the other two organic treatments showed similar levels either early in the growing season (manure) or at the later sampling dates (DIG1). In the latter case, Al concentrations were at the same low level as in the control early in June but increased strongly until August.

Concentrations of the investigated metals from June to August sampling were in general negatively correlated with pH, with the exception of Zn, and positively correlated with DOC, with R-values above 0.75.

Additional statistical consideration of the results from the section of water-soluble metal concentration was used to assess the influence of the addition of different treatments, pH and DOC. The results of two-way ANOVA analysis are given in **Table 4**.

Water-soluble concentrations of Cu, Cr, and Ni were significantly affected by the factor treatment. Between the factors treatment and sampling time, the F-value is indicating that the sampling time had a more significant role especially for Cd, Cu, and Ni.

The PCA analysis was performed on the entire data set of measured concentrations from June to August for the 2016 season. In **Table 5**, the results for component loadings and eigenvalues of each PC are presented. PC1 had an eigenvalue >2 whereas PC2 had a value below 1 (0.8). Since only PCs with eigenvalues equal to or above 1 can be taken into consideration, only PC1 can be used to explain the variability.

The data structure and component loadings of the first two components, PC1 and PC2 are shown by use of a biplot (**Figure 4**). The first two components describe approximately 97% of the variance (PC1 85%, PC2 12%).

For all the metals, PC1 values were positive. Loading values were above 0.4 for all metals except for Zn. Most of the treatments formed a cluster, except for the DIG1 in July and August (**Figure 4**). The clustering of treatments is strongest for June and July sampling while for August the clustering was more dispersed. Clustering in this type of experimental setup usually implies that used treatments have a similar effect on the metal concentration variability.

# Total Metal Concentrations in Plant Material

In 2015, plants metal content was determined at three times during the growing season at the same time as the soil samples were taken. In 2016, grain metal content was analyzed at harvest. Total concentrations of metals in plant material are given in **Figure 5**. For Cd, during the growing season there was no significant difference between the treatments, where a concentration dilution effect is seen from June to August. Grain concentrations from 2016 were below 0.1 mg kg−1 for all treatments. A different uptake scenario was seen for the plant nutrients Cu and Zn, where total plant concentrations are significantly affected only by the digestates treatments (DIG1 and DIG2). Grain concentrations for Cu were around 0.2 mg kg−1 while for Zn they were around 25 mg kg−1 .

For treatments in season 2015, there was no significant difference in Ni concentrations during the growing season. There were no significant differences in Cr concentration for the used treatments in the sampled plant material for each of the sampling points (season 2015). The same dilution effect as seen for Cd can be also seen for Cr. In general, Cr concentration was lower than concentration of other metals detected in the plant material. The highest concentration of Cr in plant material was found in the plots treated with AM. Still, the grain concentrations in 2016 were very low (below 0.2 µg kg−1 of dry plant material).

TABLE 4 | Results of two-way ANOVA analysis with defined factor of significance for the concentration of selected metals measured in soil extracts using treatments and sampling time as factors and their interactions.

TABLE 5 | Component loadings and eigenvalues for each PC of the selected data set.

Calculated amounts of trace metals taken up per hectare combine the concentrations in grains given in **Figure 5** with the yield (section Field Experiment, year 2016) of the different treatments. Thus, it can be seen (on a per hectare basis) what proportion of the trace metals added with the fertilizers is removed by harvesting.

The highest concentration was seen for Zn, while the lowest was seen for Cd, Ni, and Cr. After Zn, Cu was taken up and transported to the grains in highest amounts.

### Contamination Factors for Soil Treated With Biogas Digestates

The potential metal contamination effect was assessed by using data from the total soil concentration from both growing seasons for the calculation of the contamination factor. Calculated contamination factors (CF) are given in **Figure 7**, using the formula from section Statistics and Calculations.

The general classification of the level of contamination available from the literature (Antoniadis et al., 2017a) usually divides CF into three classes, CF < 1, low degree, 1 ≤ CF < 3, moderate contamination and 3 ≤ CF < 6 with high degree of contamination. For 2015 within the experimental sampling the increase can be seen for Ni (CF = 1.05), Cr (CF = 1.2), and Al (CF= 1.3) for DIG2 treatment (**Figure 6**). In the calculation of CF value from 2016 there is increase for Cd (CF = 1.4) and Cr (CF = 1.2) for both DIG treatments. **Figure 6** shows that the rest of the investigated trace metals have a low or moderate level of contamination.

### DISCUSSION

The trace metals in focus in this study were both plant micronutrients (i.e., Cu, Zn, Ni, Mn, and Mo), and those that are in general not considered to be important or even harmful for plant growth (Cd, Cr, and Al). However, both groups of metals can negatively influence both plant development and soil quality (including runoff water) if present in excessive amounts. The addition of digestate has resulted in a significant increase in the total soil metal concentration, especially in the case of Ni and Zn, but also Cr and Cd. The water-extractable concentrations in the soil have significantly increased for Ni, Zn, and Cr with addition of digestate or manure in both growing seasons. A decrease in pH had an important role in the general increase of the water-soluble concentration of cationic forms of investigated metals. Still, the significant change in the pH and the addition of metals with biogas digestates did not influence metal uptake in plant material from 2015 or in the grain samples from 2016. The PCA has shown that the water-extractable concentrations of trace metals from plots treated digestate are similar to the ones measured for animal manure. In addition, clustering of specific sample points during one growing season as presented in PCA results (biplot) also contributes to the claim that digestates exhibit similar effects when compared to AM.

### Influence of Biogas Digestates Fertilization on Trace Metals as Plant Micronutrients

Application of biogas digestates as fertilizers for both growing seasons has significantly increased Zn and Ni total soil content, while Cu, Mn, and Mo were not significantly increased (**Figure A1**).

Measured levels of total soil Zn are a result of the digestates/manure Zn content, which was in a range 150–250 mg kg−1 (**Table 3**). Under Mediterranean conditions, suggested adequate Zn content is in a range of 100–300 mg kg−1 soil for cereal production (Brunetti et al., 2012). Still, for the north of Europe the values are usually in range of 47–61 mg/kg, which means that the measured concentrations are within the suitable levels for growing cereal crops (Kabata-Pendias, 2011). A similar effect of Zn addition was seen in a published 2 year field study with the use of organic waste based fertilizer (composted municipal solid waste) where measured values of total Zn concentration in soils were also under 300 mg kg−1

and comparable to our experimental results (Yuksel, 2015). The addition of DIG1 treatment significantly increased the total Zn content especially in growing season 2016. Still, measured values for AM treatment were comparable to the values of DIG1. The concentration of Ni in digestates was high. This resulted in significantly higher total Ni soil concentrations (**Figure A1**) when compared to the NN or MF plots. Suitable levels for total Ni concentration in soil is around 50 mg kg−1 for a normal agricultural activity. The levels in our study were below a toxicity threshold (above 100 mg kg−1 in soil) and well within the suitable levels (35–55 mg kg−1 ) for crop production in general (Kabata-Pendias, 2011; Brunetti et al., 2012).

The observed changes for Zn and Ni water-soluble concentrations for DIG treatments were comparable to the levels measured for the AM treatment, especially in the case of Zn. Zn water-extractable concentration in the soil were not significantly higher than the ones measured for AM in season 2016 (**Figure 3**). The mentioned comparison clearly shows that the Zn added through digestates shows similar behavior as the Zn added through AM. Water-soluble Ni concentrations have significantly increased during both growing seasons in the digestate treatments. This may be due to the decrease in pH, as Ni mobility is enhanced under acidic conditions (Zhu et al., 2011). Kim et al. (2015) also confirmed that low pH can increase the release of naturally present Ni from soil.

The Zn concentration in the plant material collected during the 2015 season was significantly higher in the digestate treatments than in all other treatments (**Figure 5**). This reflects the higher availability of Zn as indicated by increased watersoluble concentrations. There were no significant differences in Zn concentration in the grain samples between the digestate and MF or AM treatments. Added digestate treatments had no significant influence on grain Ni concentration and the values were comparable to AM or MF treatments. Despite differences for Ni concentrations in soil-water extracts between treatments, no significant effect of the organic fertilizer treatments on plant Ni concentrations was found (**Figure 5**). The level of Ni concentrations in grains was comparable to that found in other studies with organic fertilizers conducted in Northern Europe (Hamner et al., 2013). Still, the long-term effect of the Zn or Ni accumulation in soil should not be disregarded. Currently, Zn is marked as one of the three metals mostly

contributing to the global environmental pollution through the use of animal manure fertilizing practices (Leclerc and Laurent, 2017). The soil contamination factors for Zn and Ni were below or at the moderate levels for the 2015 season and at moderate contamination level for the 2016 season, which implies a moderate increase in the risk of trace element accumulation. The maximum water-extractable concentration of Ni from soil was around 50 µg L−1 , which is below the 70 µg L−1 defined by the World Health Organization (WHO) drinkingwater regulation (World Health Organization, 2006).

Addition of digestates has not increased significantly the total Cu, Mn, and Mo concentration. The Cu, Mn, and Mo are important micronutrients needed for normal plant growth and development, and change in soil concentration may have a positive effect on plant growth. The recommended values of Cu total soil concentration for cereal growth is ranging between 20 and 40 mg kg−1 , while toxic effects are dependent on the soil type and are usually seen between 60 and 125 mg kg−1 (Kabata-Pendias, 2011). Values measured in both growing seasons are approximately 10 times lower than the upper toxic limit for Cu in soil for all used treatments, which implies a lower concentration of Cu in soil then recommended. The reference values of Mn for soils used I agriculture in Norway is ∼6 mg kg−1 , where values measured in our studies was around 2 mg kg−1 , showing that the addition of biogas digestates has no significant effect on the total Mn concentration in soil. For total Mo concentration in soil the reference value in soils is ∼2 mg kg−1 , which is not different than the values measured in our 2-year experiment (1.2– 1.4 mg kg−1 ). Based on the total concentrations it is clear that the addition of both biogas digestates had no significant influence on the reference values of Mo in soil used for plant production (Kabata-Pendias, 2011; Brunetti et al., 2012).

Copper mobility, measured as water-extractable Cu, generally increased from June to August for all organic fertilizers. Copper mobility is mostly influenced by the changes in soil pH and DOC concentration due to the different treatments. Dissolved organic carbon, i.e., the soluble phase of organically bound carbon is known to affect metal mobility both in soil solution and thus in the soil (Pérez-Esteban et al., 2014). Addition of biogas digestate

has increased the amounts of DOC in soil water extracts. In 2016, a significant increase in DOC was seen in the AM treatment in June. This follows the total amounts added with manure that year. In 2016, a higher volume of manure was added (233 L per plot) than in 2015 because of a lower N concentration. An increase in DOC concentration over the growing season with the use of organic fertilizers (composts) has also been confirmed in a recent study (Manninen et al., 2018). The rather low watersoluble concentration of Mo in our study may be explained by the fact that the strongest adsorption of Mo to the soil occurs at around pH 5 (Smith et al., 1997), which is not different from the pH values measured in the samples from our field experiment in August. Despite a pH change from 6.2 to 5.1 from June to August, no significant changes in water-extractable Mo concentrations were observed.

The total Cu concentrations in plants were significantly increased in the digestates treatments especially at the sampling in August 2015 (**Figure 5**) when compared to control plots, but grain Cu concentrations at harvest (year 2016) were not significantly increased. The contamination factor was below 1 for Cu, Mn, and Mo for all treatments (**Figure 7**), which implies a low risk of soil contamination.

### Influence of Biogas Digestates Fertilization on Trace Metals Not Essential to Plants

For this group of tracemetals (Cr, Cd, and Al), the total soil concentration was significantly higher in the plots treated with biogas digestates (**Figure A1**) when compared to NN and MF plots. Use of both digestates significantly increased total Cr and Cd concentrations in soil (season 2016), while only DIG2 increased the total Al content of the soil. This is due to the high concentration of Cr and Al, but also Cd (2016) in the digestates. Cr concentration in the digestates was above 150 mg Cr/kg DM (**Table 3**), which was higher than the limits set by the Norwegian regulation on organic fertilizers used in agriculture (60 mg/kg dry fertilizer, class I). Slightly higher values were also seen for Cd (**Table 3**), while Al content is not regulated for organic fertilizers in Norway. The Cd content in organic wastes vs. that in mineral fertilizers is an important issue of discussion The maximum allowed total concentration of Cd in soils treated with organic waste such as sludge was 3 mg/kg (Brunetti et al., 2012), and this limit was not been exceeded in the two growing seasons. Toxic values for total Cr concentration in agricultural soils may vary between 150 and 400 mg/kg depending on the soil type (Kabata-Pendias and Pendias, 2001; Kabata-Pendias, 2011). In both seasons, total Cr concentration did not exceed 100 mg kg−1 .

The water-soluble Cd concentrations were low in all treatments in the first season, as Cd additions with the organic fertilizers were low and little Cd was present in the soil initially. It is important to mention that the field experiment was started with the same treatments already in 2014, while the samples were taken and analyzed in the next 2 years (2015 and 2016). This may be important in evaluating potential Cd accumulation in the soils treated with digestates. Research studies with similar levels of Cd in organic fertilizers have also shown that the addition of organic fertilizers (manure) does not cause a significant change in the soil Cd content (Xu et al., 2015). In both growing seasons, Cd was strongly correlated to the pH then to DOC, which is expected and also confirmed in a recent study (van der Sloot et al., 2017), where lower pH was seen to increase the Cd soil waterextracted concentrations. (Van Zwieten et al., 2013) reported that application of organic fertilizers (poultry litter) with pH above 7 has resulted in soil pH decrease during the growing season (Van Zwieten et al., 2013), which has also seen for our experimental set up. There is a significant increase of Cr watersoluble concentrations during both growing seasons (**Figure 3**) for digestate treatments when compared to NN and MF. Still, measured concentrations were below the limit of 50 µg L−1 of total Cr, which is a recommended value for fresh waters (World Health Organization, 2006). The values measured in both seasons were comparable to those found in a similar field experiment reported by Wierzbowska et al. where values were also below 50 µg L−1 (Wierzbowska et al., 2016). In the pH range measured for both growing seasons, Cr(III) is expected to be the predominant form of Cr present in the soil solution (Bradl, 2004; Choppala et al., 2018). The same authors are also suggest that lower pH values (below 6.5) considered as a major factor that is increasing the level of Cr(III) sorption to soil particles. This can be used to explain the low water-extractable Cr concentrations found in our study (**Figure 3**).

Aluminum availability in soil and soil pore water is generally influenced by soil pH and DOC. In our study, both pH and DOC showed good correlations to water-extractable Al concentrations. The high total Al concentration in DIG2 was due to the sewage treatment process where Al salts were used for precipitation of P from sewage water prior to anaerobic digestion. Aluminum phosphates are poorly soluble, and this is clearly reflected in similar levels of water-extractable Al in DIG2 and even though no Al salts were added in the process for DIG1. In general, Al does not occur in toxic forms in the soil at pH values suitable for cereal production (Wang et al., 2006).

Low concentrations in both total and water-soluble forms have resulted in low Cd levels in the plant material (**Figure 5**), with a significant increase in Cd grain concentration only in the AM and DIG2 treatments. The amounts of Cd taken up by grains calculated per hectare were very low for all treatments (**Figure 6**). Cd originating from sewage sludge and similar sources is controlled more strictly than that from mineral fertilizers, although the latter can have a high Cd content (Pizzol et al., 2014). Digestate treatments had no significant effect on plant Cd or Cr concentrations and measured concentrations were comparable with AM or MF. The contamination factor for Cd, Cr, and Al though moderate, were highest from all the CFs measured in this study. The contamination factor for Al is of little relevance unless pH levels decrease below the adequate range (below pH 4) for cereal production, which could firstly affect the barely production.

In our field experiment with cereals, biogas digestates were applied at the same fertilization rates (100 kg /ha available N). At these rates, there was little difference in the effects of the applied fertilizers on soil or crop metal concentrations. Concentrations measured in the cereal grains were well below maximum allowed values found in human exposure studies with cereal crops (Huang et al., 2008). Still, research on accumulation rates over a longer period of application may give valuable insight into soil processes that the use of organic fertilizers can induce in soil. Our field experiment was only conducted for 3 years, and

### REFERENCES

measurements only exist for the last 2 years. Longer time series will be necessary for assessing the plant uptake of trace metals after repeated additions of digestates.

# CONCLUSIONS

In our study, we have reported for the first time results from field experiment conducted through two growing seasons to investigate the application of two different commercial biogas digestates based on food waste and food waste/sewage sludge mixture. The main hypothesis that the application of biogas digestates as organic fertilizers would increase the mobility and thus plant availability of trace metals in soil was not entirely confirmed. While total concentrations of Ni, Cd, Zn, and Cr were increased in soil upon application of digestates, their water-extracted concentrations were below the defined limits established by WHO. In addition, total Cu, Mn, and Mo concentrations were not significantly increased in the soil. Both pH and DOC were important factors in determining the mobility of the trace elements, in most cases increasing the watersoluble concentrations of trace elements from June to August. Plant concentrations did not indicate an increased uptake of trace metals into the cereal crops due to digestate application. Based on these results, the use of digestates can be compared to the use of animal manure or mineral fertilizers with respect to trace metal accumulation in soil and grain uptake. Still, a period of 2 years is too short to conclude on potential trace metal accumulation in soils due to the use of digestates as fertilizers.

# AUTHOR CONTRIBUTIONS

In regards to the work done regarding this manuscript, ID main tasks were sampling during the field experiment, sample analytical lab work, statistical considerations, manuscript draft, and final version preparation. SE-G main tasks were planning and organizing the field experiment, experiment yield measurements, help with the sampling and work on the draft and manuscript final version, while TS main tasks were planning the field experiment and work on the draft and final version of manuscript.

# FUNDING

This research was partly funded by the Norwegian Research Council (Project no. 228747/E20, BiogasFuel).

Elonen, P. (1971). Particle-size analysis of soil. Acta Agralia Fennica 122, 1–122.

World Health Organization (2006). Guidelines for Drinking-Water Quality.

model, principle components analysis and geo statistical analysis. Ecotoxicol. Environ. Saf. 159, 354–362. doi: 10.1016/j.ecoenv.2v.2018.04.072

Zhu, R., Wu, M., and Yang, J. (2011). Mobilities and leachabilities of heavy metals in sludge with humus soil. J. Environ. Sci. 23, 247–254. doi: 10.1016/S1001-0742(10)60399-3

**Conflict of Interest Statement:** The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Copyright © 2018 Dragicevic, Sogn and Eich-Greatorex. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

# APPENDIX

FIGURE A1 | Variability of total metal concentrations in soil samples taken during the growing seasons 2015 and 2016. The values are presented as means ± SD. Letters are showing significance of differences between the treatments (p < 0.05)

# Optimal Placement of Meat Bone Meal Pellets to Spring Oats

### Sofia Delin1 \*, Lena Engström1 and Anneli Lundkvist 2

1 Department of Soil and Environment, Swedish University of Agricultural Sciences, Skara, Sweden, 2 Department of Crop Production Ecology, Swedish University of Agricultural Sciences, Uppsala, Sweden

New technology makes it possible to apply organic fertilizers with higher precision, and organic producers want to know how to exploit these new possibilities to make their production more efficient. This study investigated the effect of band application (in different positions) of pelleted organic fertilizer, compared with broadcasting, on grain yield and weed density in spring oats (Avena sativa L.). Six microplot field experiments were carried out on silty clay and sandy loam in Sweden during the growing season of 2014–2016. In oats seeded at 25 cm row spacing, pelleted meat bone meal was band-applied at one of three distances from the crop row (0, 4, and 12.5 cm) and at two or three incorporation depths (1 and 4 cm on silty clay and 1, 4, and 6 cm on loamy sand). These treatments were compared with broadcast spreading, mineral nitrogen fertilizer, and an unfertilized control. On both soil types, fertilizer placement 4 cm from the crop and 4–6 cm incorporation depth gave the highest yield and crop nitrogen uptake. Yield in this treatment was 800 kg ha−1 higher on clay soil and 1,100 kg ha−1 higher on sandy loam compared with the same organic fertilizer applied by broadcasting, an 80–150% yield increase. On the sandy loam, distance from the crop row had a more significant effect on grain yield (p < 0.001) than soil incorporation depth (p = 0.07). On the silty clay, crop yield was significantly influenced by incorporation depth (p = 0.003) and distance from the crop row (p = 0.04). In five experiments, mineral N fertilizer equivalent (MFE) increased from on average 63% with broadcasting to 85% with placement 4 cm from the crop row and 4 cm incorporation depth. Weed biomass was significantly affected by fertilizer placement on the clay soil, with higher weed biomass with deeper incorporation (p = 0.045) and greater distance from the crop row (p = 0.049). On the sandy loam, there was a tendency for larger weed plants at greater distance from the crop row (p = 0.13) except when seeds and pellets were placed together, which gave the highest weed weight, probably due to lower competition from the crop in this treatment.

Keywords: meat bone meal, organic fertilizer, fertilizer banding, soil incorporation, organic grain production

### INTRODUCTION

Due to their physical properties, organic fertilizers are usually difficult to apply with good precision. Use of pelleted organic fertilizers is therefore an attractive alternative for organic farmers. Pellets can be applied with machines that provide a uniform distribution in the field and are not as limited in time to perfect soil conditions as fertilizer products that require heavy machinery. If the pellets are sufficiently robust, they can be applied with a seeder and incorporated in rows with

### Edited by:

Claudia Wagner-Riddle, University of Guelph, Canada

### Reviewed by:

Eliana Lanfranca Tassi, Istituto per lo studio degli ecosistemi (ISE), Italy Peter Sørensen, Aarhus University, Denmark

> \*Correspondence: Sofia Delin<EMAIL_ADDRESS>
### Specialty section:

This article was submitted to Waste Management in Agroecosystems, a section of the journal Frontiers in Sustainable Food Systems

> Received: 01 February 2018 Accepted: 31 May 2018 Published: 19 June 2018

### Citation:

Delin S, Engström L and Lundkvist A (2018) Optimal Placement of Meat Bone Meal Pellets to Spring Oats. Front. Sustain. Food Syst. 2:27. doi: 10.3389/fsufs.2018.00027 the same precision as seeds or granulated mineral fertilizers. The dose, time of application, and placement can thereby be much better optimized than for other organic fertilizers, which are often heavy, sticky, and difficult to distribute. Modern machinery equipped with RTK GPS and designed for seeding and weed hoeing with high precision is becoming more frequent in Swedish organic production. This gives farmers the possibility to place the pellets with high precision and many farmers want to know more about optimal placement. Meat and bone meal (MBM) is currently a common pelleted fertilizer in Sweden, although products with chicken manure were more common in the past. In the future, and in other countries, other organic materials could be used.

When pellets are broadcast, soil incorporation is often performed with a harrow to mix the pellets with a large volume of soil, but this typically leaves a large fraction of the pellets close to the soil surface. Application in bands with a seeder can achieve deep incorporation of all pellets, and also keeps the pellets more concentrated and less mixed with the soil. The way in which organic fertilizers are placed in soil during application can affect the biological turnover of nitrogen (Sørensen and Jensen, 1995; Sørensen and Amato, 2002). For example, if the fertilizer is mixed with a larger volume of soil, immobilization of nitrogen will be faster (Sørensen and Jensen, 1995), since both the energy source (carbon) and the nitrogen will be available to a larger number of microorganisms. If the fertilizer is instead concentrated to narrow bands in the soil, microbial access to carbon and nitrogen, and thus nitrogen immobilization, will be more limited. Baitilwake et al. (2012) found greater immobilization and nitrification after soil incorporation than surface application of chicken and cattle manure. However, Delin and Strömberg (2011) did not find any differences in net mineralization of nitrogen between surfaceapplied and incorporated chicken manure and cattle slurry, as long as the manure was kept in concentrated lumps, although when the manure was mixed with a larger soil volume both net immobilization and nitrification increased.

Apart from the potential advantages listed above, band application also means that the fertilizer can be applied at an optimal distance from the crop row. In organic farming, wide row spacing is commonly used to facilitate mechanical weed control (Hiltbrunner et al., 2005). This justifies pellet placement close to the row, instead of broadcasting or placement mid-way between rows, as this can increase nutrient availability for the crop and reduce it for weeds (Rasmussen et al., 1996). This has previously been observed with mineral fertilizers (Rasmussen et al., 1996; Blackshaw, 2005) and animal slurry on corn (Schröder et al., 1997; Rasmussen, 2002; Petersen, 2005; Bittman et al., 2012). In the case of animal slurry, placement close to the seed row has been shown to increase yield in spring cereals (Petersen, 2005) and phosphorus (P) uptake in corn (Schröder et al., 1997; Bittman et al., 2012). Rasmussen et al. (1996) observed 55% less weed biomass and 28% higher yield of spring barley after application of fertilizer close to the crop row compared with broadcasting. In a 4-year experiment, Blackshaw (2005) found that subsurface-banded mineral nitrogen fertilizer applied to spring wheat often led to lower weed nitrogen uptake and biomass and higher grain yield than when nitrogen was surfaceapplied. However, no study performed to date on placement of pelleted organic fertilizers to spring cereals has sought to identify the optimal placement of pellets in relation to seed and quantify the production benefits.

The objective of the present study was to investigate how crop nitrogen (N) uptake, grain yield, and weed density in spring cereals on two different soils are affected by band application of pelleted organic fertilizer at different incorporation depths and distances from the crop row, in comparison with broadcast pellets with very shallow incorporation. The hypotheses are that (i) the nitrogen use efficiency of pelleted fertilizers increases with incorporation depth, but the effect decreases with precipitation, (ii) with row spacing of 25 cm or more, the effect on yield of nitrogen in pelleted fertilizers is higher and the weed pressure lower if the fertilizer is placed less than 6 cm from the seed row than if it is broadcast or placed at greater distance from the row, and (iii) any yield loss caused by 25 cm row spacing instead of the conventional 12.5 cm will be smaller than the yield increase caused by band application with optimized placement. In the experiments, a spring oats crop seeded at 25 cm row distance was fertilized with pelleted MBM, as an example relevant for Swedish organic production.

# MATERIALS AND METHODS

### Experimental Sites

Six microplot field experiments were carried out in spring oats (Avena sativa L.) on silty clay and sandy loam soils (**Table 1**) in Sweden (58◦N, 13◦E) during the growing season of 2014- 2016. The sandy loam was on a farm with regular addition of farmyard manure, whereas on the silty clay soil manure has not been applied for a long time. Mean monthly precipitation and temperature in the period May-August 2014–2016 were recorded at a location <20 km from all study sites (**Table 2**). In 2014, the weather was warm and dry in July, followed by heavy precipitation in August, while 2015 had a cool growing season and 2016 had rather dry weather in May (**Table 2**).

TABLE 1 | Soil characteristics in the topsoil (0–30 cm) at the different experimental sites.

\*Soil organic matter.

\*\*Ammonium lactate-extractable phosphorus (P), where values <4 are considered moderately P deficient and <2 very P deficient.

\*\*\*Ammonium lactate-extractable potassium (K), where values <8 are considered moderately K deficient and <4 very K deficient.

TABLE 2 | Mean monthly air temperature and precipitation at the experimental sites in April–August, 2014–2016, compared with \*mean climate for the period 1960–1990.

### Experimental Design