<figure><img src="image_60.png" /><figcaption>Figure 1. Distribution of the 3 main forms of mineral N fertilisation (urea in white, nitrogen solution in grey and ammonium nitrate in black) per region (%), average of AGRESTE survey (2014) on the 2010-11 crop year.</figcaption></figure>

Crop average mineral and organic N fertilization were also estimated at regional scale. Evolution of amounts of applied product was also evaluated between the crop years 2005-2006 and 2010-2011. Type and amounts of applied products was estimated per crop type. These data can be used for national scale modelling such as NH₃ emissions through the CADASTRE_NH3 tool also presented in this workshop.

## CONCLUSION

Regional scale is the minimum scale to evaluate N fertilization data as discrepancies between regions are linked with local context, either economic (e.g. product locally produced) or pedoclimatic. Finer distribution of these different forms of N fertilization will help to implement local or regional incentive. The latter can thus target specific regions, crops or products to minimize the environmental impacts.

**Acknowledgements:** This work was supported by a public grant overseen by the French National Research Agency (ANR) as part of the « Investissements d'avenir » program (reference: ANR-10-EQPX-17 - Centre d'accès sécurisé aux données - CASD). It was conducted within the CADASTRE_NH3 (Spatial and temporal high-resolution inventory of ammonia emissions from agricultural soils over France at regional and national scales) project, supported by ADEME the French Agency for Energy and Environment, and the PolQA project (Mitigation policies to improve air quality through agricultural practices, agreement n°1662C0023), supported by the French PRIMEQUAL program (Programme de recherche interorganisme pour une meilleure qualité de l'air à l'échelle locale) and by the French Ministry for an Ecological and Solidary Transition.

## REFERENCES

* AGRESTE, 2014. Enquête Pratiques culturales 2011. In "Agreste Les Dossiers", n°21- July 2014, pp.70.

* Génermont S., Gilliot, J. M., Ramanantenasoa, J., et al., 2015. Cadastre-NH3 : Réalisation de cadastres dynamiques des émissions d'ammoniac liées à la fertilisation azotée aux échelles régionales et nationales - Rapport de fin de contrat, Convention INRA-ADEME n° 1081C0031, pp 107.

* Mignolet, C., Schott, C., and Benoit, M., 2007. Spatial dynamics of farming practices in the Seine basin: methods for agronomic approaches on a regional scale. Sci Total Environ 375, 13-32.

DOI:10.1016/j.scitotenv.2006.12.004
# LARGE SCALE MODELLING OF NITRATE LEACHING FROM ARABLE LAND IN GERMANY

KLEMENT, L.<fnref n="1" />, BACH, M.<fnref n="1" />, BREUER, L.<fnref n="1" />, NENDEL, C.², KERSEBAUM, K.-C.², STELLA, T.², BERG-MOHNICKE, M.²

## INTRODUCTION

In Germany, around 26.3% of groundwater bodies are in a poor chemical state due to contamination with nitrate, according to the latest inventory of the EU Water Framework Directive (BMUB, 2014). For the past decades, Germany failed to impose effective measure to lower the nitrate groundwater concentration below 50 mg l⁻<fnref n="1" /> throughout the country. This also means that Germany is not in compliance with the EU Nitrate Directive, leading the European Commission to file a lawsuit against Germany in late October 2016. Nitrate contamination of groundwater is suspected to increase the cost of drinking water purification for Germany's population by up to 45% (UBA, 2017) and thus is also regularly discussed in the German Press. The agricultural sector has been determined to be the main source of this nitrate contamination. Research on mitigating this contamination has mainly focused only on lowering the nitrogen surplus. However, regional geological and climatic heterogeneity has to be taken into account in order to assess the vulnerability of regions to nitrogen losses.

This study therefore focuses on modeling the nitrate leaching below the root zone (depth of 2 m) using a dynamic, process-based simulation model MONICA - Model of Nitrogen and Carbon dynamics in Agro-ecosystems (Nendel et al., 2011).

## MATERIAL AND METHODS

Nitrate leaching below 2 m soil depth was simulated for a 30 year period (1983 – 2012) using the model MONICA throughout the country. MONICA is a one dimensional model that represents a 1 m² pedon and simulates crop production as well as transport processes in the soil. It was successfully used in various local and regional scale modelling endeavors and fared well in comparative studies. Prior to this study however, modelling on larger or national scale had not been carried out using MONICA yet.

In order to model on the national scale, Germany was grouped into 44 pedo-climatic-regions adapted from the work of Roßberg et al. (2007), based on similar soil and climate conditions. One weather station was picked for each pedo-climatic-region. For the soils, 8 representative soil types are taken from the soil map BUEK1000 (BGR, 2007) to be implemented in the model. Each pedo-climatic-region was simulated with all 8 soil types and a number of realistic crop rotations derived from a total of 9 crops and fertilizing strategies differing in total amount and composition of organic and mineral fertilizations. Crop parameters were calibrated using phenology data for Germany provided by Germany's National Meteorological Service (DWD) in order to improve model fit. A factorial analysis was carried out to allow for greater insight on which input data was additionally needed to describe regional differences.

## RESULTS AND DISCUSSION

Preliminary model results with winter wheat showed that average nitrate leaching range from below 10 kg N ha⁻<fnref n="1" /> up to 80 kg N ha⁻<fnref n="1" /> per year. The highest nitrogen leaching was simulated for northern Germany where more intensive agriculture focused on livestock farming is located. The resulting NO₃ concentrations in leachate range from lower than 25 mg NO₃ l⁻<fnref n="1" /> in high altitude regions up to 225 mg NO₃ l⁻<fnref n="1" /> in regions with intensive agriculture and low recharge rates in the eastern parts of Germany. Further results using trinomial crop rotations will be presented and discussed at the workshop.

<footnote n="1">¹ Institute of Landscape Ecology and Resources Management (ILR), Justus Liebig University Gießen, Germany; ² Institute of Landscape Systems Analysis, ZALF, Leibniz-Centre for Agricultural Landscape Research, Muencheberg, Germany;</footnote>
Phenological calibration has been a key element to improving the fit of modeled crop growth and to ensure that the model applies appropriate nitrogen uptake by the plant, enabling us to model nitrogen dynamics using MONICA. Due to the factorial analysis we were able to further improve the level of detail in our input data, resulting in a better fit of the model, especially in higher altitudes.

## Conclusion

The study, which is unprecedented in this scale for Germany, showed promising results and could potentially be used by political decision makers to develop appropriate mitigation measures and identify regions that are most vulnerable to nitrate groundwater contamination.

In a large scale set up, it is important to acquire knowledge on what parameters are necessary to describe all regional differences that are important to crop growth and nitrate leaching. Even when a model successfully reflects field experiments and local scale settings, further adaptions and input data are needed when used for a large area with a high spatial variability.

Future work will focus on increasing the spatial resolution and to use the results of this study with a second model that routes the fluxes further into the saturated zone and the groundwater layers.

**Acknowledgements:** This study was funded by the German Environment Agency (UBA), Project No. 3715222200

## REFERENCES

* BGR, 2007. Bodenarten der Böden Deutschlands - Bericht über länderübergreifende Auswertungen von Punktinformationen im FISBo. BGR, Hannover.

* BMUB, 2014. Wasserwirtschaft in Deutschland - Teil 2: Gewässerqualität. Bundesministerium für Umwelt, Naturschutz und Reaktorsicherheit (BMUB), Bonn.

* Nendel C., Berg M., Kersebaum K.C., Mirschel W., Specka X., Wegehenkel M., Wenkel K.O., Wieland R., 2011. The MONICA model: Testing predictability for crop growth, soil moisture and nitrogen dynamics. Ecol. Model. 222 (9), 1614–1625.

* Roßberg D., Miche V., Graf R., Neukampf R., 2007. Definition von Boden-Klima-Räumen für die Bundesrepublik Deutschland. J. Kulturpflanzen 59(7), 155-161.

* UBA, 2017. Quantifizierung der landwirtschaftlich verursachten Kosten zur Sicherung der Trinkwasserbereitstellung. Umweltbundesamt (UBA), Dessau-Roßlau.
20th Nitrogen Workshop

Coupling C-N-P-S cycles

June 25-27, 2018

Le Couvent des Jacobins, Rennes – France

**Session III: Local process studies – Oral presentations**
# KEYNOTE PRESENTATION : INTERACTIONS BETWEEN C-N-P CYCLES FROM THE POINT OF VIEW OF SOIL MICROBIAL ECOLOGY

WANEK, W.<fnref n="1" />, MOOSHAMMER, M.², RICHTER, A.³

## INTRODUCTION

In the biosphere the cycles of C, N and P (and S) are intimately linked through their contribution to essential organic biomolecules such as lipids, proteins, nucleic acids and (amino)sugar polymers, together largely constituting the cellular make-up of microbes, plants and animals. Soil microbial communities have been shown to be largely homeostatic in terms of their cellular C:N:P ratio (Xu et al. 2013) but in the environment face resources that by far do not match their elemental composition (Mooshammer et al. 2014b, Zechmeister-Boltenstern et al. 2015). These resource C:N:P imbalances trigger different mechanisms that allow microbes to thrive and grow on these imbalanced food resources (Mooshammer et al. 2014b).

## RESULTS AND DISCUSSION

### Elemental imbalances, decomposer adaptations and microbial processing of organic matter

Elemental imbalances range between 2-50 for C:N, 7-340 for C:P and 3-7 for N:P when microbes decompose soil organic matter, leaf litter, dead roots or wood (Table 1) (Mooshammer et al. 2014b). Adjustments in the production of extracellular enzymes to mine for limiting elements and in element use-efficiencies are most important to bridge this gap (Figure 1). We will demonstrate how changes in microbial carbon-use efficiency (CUE) and growth affect soil carbon sequestration and soil respiration, for example causing increases in soil organic C in grasslands of higher plant diversity. Microbial CUE decreases with increasing resource C:N ratios, though weakly, following stoichiometric reasoning. At the same time we could also show that microbial nitrogen-use efficiency (NUE) increases with increasing resource C:N ratios and C:N imbalances (Mooshammer et al. 2014a). An increase in microbial NUE however also implies a reduction in gross N mineralization and therefore a slow-down of inorganic N cycling. In contrast, factors that cause a decline in microbial NUE trigger faster N mineralization, eventually followed by a more open N cycle with greater N losses from soils.

<table><caption>Table 1. Globally averaged element ratios in potential resources and in soil microbial biomass, and stoichiometric imbalances between resources and microbes calculated as the ratio of X:Y<sub>resource</sub> over X:Y<sub>microbes</sub>.</caption><thead><tr><th>Organic material</th><th>Molar C:N:P</th><th>C:N imbalance</th><th>C:P imbalance</th><th>N:P imbalance</th></tr></thead><tbody><tr><td>Wood</td><td>14.100:40:1</td><td>50</td><td>336</td><td>7</td></tr><tr><td>Dead roots</td><td>4.180:43:1</td><td>14</td><td>100</td><td>7</td></tr><tr><td>Leaf litter</td><td>3.055:43:1</td><td>10</td><td>73</td><td>7</td></tr><tr><td>Soil organic matter</td><td>287:17:1</td><td>2</td><td>7</td><td>3</td></tr><tr><td>Soil microbes</td><td>42:6:1</td><td></td><td></td><td></td></tr></tbody></table>

### Non-stoichiometric controls on microbial C, N and P cycling

Beyond stoichiometric controls on element-use efficiencies we will analyze other potential controls of microbial C, N and P cycle processes. We here focus on whether gross decomposition and mineralization processes are rather driven by extracellular enzyme contents or substrate availability. The content of decomposable substrate and its stabilization or accessibility are overriding factors, controlling the depolymerization of high-molecular weight organic matter in soils, as shown by a lack of relationship with potential soil enzyme activities but strong modulating effects of soil texture, pH and exchangeable calcium at local to continental scales. Microbial activity in soils is therefore strongly constrained by factors that render resources inaccessible, e.g. via soil aggregation or physical binding to mineral surfaces (unpublished data).

<footnote n="1">¹ Department of Microbiology and Ecosystem Science, University of Vienna, Austria; 2 Affiliation, Country; 3 Affiliation, Country</footnote>
Disturbance effects on microbial C, N and P cycling

Predicted changes in the intensity and frequency of climate extremes necessitate a better mechanistic understanding of the stress response of soil microbial communities and related C, N and P processes. By analyzing the resistance and resilience of microbial C, N, and P cycling processes and microbial community composition in decomposing plant litter to transient, but severe, temperature disturbances (freeze-thaw and heat wave) we show a more rapid cycling of C and N but a down-regulation of microbial P cycling shortly after disturbance (Mooshammer et al. 2017). While C and N processes and microbial community structure recovered rapidly to control levels, we found a slow recovery of P mineralization rates. Moreover, the functional and structural responses to the two distinct temperature disturbances were markedly similar, suggesting that direct negative physical effects and costs associated with the stress response were comparable. The decoupling of microbial P processes from C and N processes and its persistent down-regulation after stress is alarming and must be followed in soil systems.

<figure><img src="image_61.png" /><figcaption>Figure 1. Simplified schematic representation of important C:N components and fluxes during organic matter breakdown by litter or soil microbial communities. Differences in C:N:P stoichiometry between (A) soil organic matter and (B) plant litter result in distinct elemental limitations for the microbial communities, with different implications for element mineralization fluxes. Mechanisms for microbial adaptation to resource imbalances are indicated (Mooshammer et al. 2014b).</figcaption></figure>

REFERENCES

Mooshammer, M., F. Hofhansl, A. H. Frank, W. Wanek, I. Hammerle, S. Leitner, J. Schnecker, B. Wild, M. Watzka, K. M. Keiblinger, S. Zechmeister-Boltenstern, and A. Richter. 2017. Decoupling of microbial carbon, nitrogen, and phosphorus cycling in response to extreme temperature events. Science Advances 3.

Mooshammer, M., W. Wanek, I. Hammerle, L. Fuchslueger, F. Hofhansl, M. Takriti, B. Wild, K. M. Keiblinger, S. Zechmeister-Boltenstern, and A. Richter. 2014a. Adjustment of microbial nitrogen use efficiency to carbon: nitrogen imbalances regulates soil nitrogen cycling. Nature Communications 5: 3694.

Mooshammer, M., W. Wanek, S. Zechmeister-Boltenstern, and A. Richter. 2014b. Stoichiometric imbalances between terrestrial decomposer communities and their resources: mechanisms and implications of microbial adaptations to their resources. Frontiers in Microbiology 5:article 22.

Xu, X. F., P. E. Thornton, and W. M. Post. 2013. A global analysis of soil microbial biomass carbon, nitrogen and phosphorus in terrestrial ecosystems. Global Ecology and Biogeography 22:737-749.

Zechmeister-Boltenstern, S., K. M. Keiblinger, M. Mooshammer, J. Penuelas, A. Richter, J. Sardans, and W. Wanek. 2015. The application of ecological stoichiometry to plant-microbial-soil organic matter transformations. Ecological Monographs 85:133-155.
# ZINC CHELATES INFLUENCED N₂O EMISSIONS AND NITRIFYING AND DENITRIFYING COMMUNITIES IN TWO DIFFERENT CROP SYSTEMS

MONTOYA, M.<fnref n="1" />, CASTELLANO-HINOJOSA, A.², VALLEJO, A.<fnref n="1" />, ÁLVAREZ, JM.<fnref n="1" />, BEDMAR, EJ.², RECIO, J.<fnref n="1" />, GUARDIA, G.<fnref n="1" />

## INTRODUCTION

Fertilization with micronutrients (e.g. zinc, Zn) is essential to overcome the global nutritional problems associated with human deficiencies. An adequate nutrient balance requires the management of macronutrients (e.g. nitrogen, N) fertilization (Venterea et al., 2016) and its interactions with micronutrients (e.g. Zn), to find synergistic effects between nutrients, and improve crop quality through biofortification (Cakmak et al., 2017). However, it is pivotal to reduce environmental pollution, e.g. the emission of nitrous oxide (N₂O), without compromising food security in a context of increasing world population. Widespread products which inhibit nitrification, such as dicyandiamide (DCD) or 3,4-dimethylpyrazole phosphate (DMPP), act as metal chelators. Therefore, chelating fertilizers, which are used to apply micronutrients with enhanced efficacy (Alvarez, 2010), could influence nitrification and other metal-dependent biochemical processes such as denitrification. The response of nitrous oxide (N₂O) emissions to N fertilization has been broadly assessed, but little is known about the effect of micronutrient fertilizers and their interaction with nitrogen (N) on greenhouse gas (GHG) emissions and soil microbial processes involved in N₂O fluxes.

## MATERIAL AND METHODS

Two field experiments were located in the National Center of Irrigation Technology, "CENTER" in the Madrid region (Spain). The soil was an alkaline *Typic xerofluvent* with a silt loam texture and low organic matter content in the upper horizon (0-20 cm). The winter wheat (*Triticum aestivum* L. 'Ingenio') and the maize (Zea mays L. 'SY Miami') experiments were carried out from October 2015 to July 2016 and May 2017 to September 2017, respectively. The maize crop was irrigated through sprinklers, while no irrigation was applied to winter wheat. A total of 12 plots (20m² and 144m², respectively) were arranged in a three-replicated randomized block design. Each plot was a result of two N rates as urea (0, N0 and 120 kg N ha⁻<fnref n="1" />, U) with two Zn sources: control, no Zn application (Zn0) and Zn applied with a mixture of chelating compounds (Zn-DTPA-HEDTA-EDTA, ZnCH).

### GHG sampling and analyses

During the first month after fertilization, samples of gases were taken 2-3 times per week considering it is the most critical period of high gas emissions. Afterwards, the frequency of sampling was decreased progressively, but increasing after rainfall events. The GHG (N₂O, CH₄ and CO₂) fluxes were measured using the closed chamber technique (Sanz-Cobena et al., 2012) and their concentrations were quantified by gas chromatography, using a gas chromatograph (GC).

### DNA extraction and quantification of nitrifying and denitrifying microbial communities

Soil samples were taken from the field experiment with wheat. Total DNA was extracted from 500 mg of soil using commercial kit PowerSoil® DNA Isolation and DNA concentration was measured using the Qubit® ssDNA assay kit. The size of nitrifying communities was estimated by quantitative PCR (qPCR) of the *amoA* gene from ammonia-oxidizing Bacteria (AOB) and Archaea (AOA). Similarly, denitrifying communities were estimated by qPCR of the *nirk*, *nirS*, *norB* and *nosZ* genes using primers and thermal conditions described previously. The total bacterial and archaeal communities were quantified using the 16S rRNA gene as a molecular marker. qPCR was performed in an ABI Prism 7900 Sequence Detection System employing the fluorophore SYBR Green to quantify the total

<footnote n="1">¹ ETSI Agronómica, Alimentaria y de Biosistemas, Universidad Politécnica de Madrid, Spain; ² Department of Soil Microbiology and Symbiotic Systems, Estación Experimental del Zaidín, Agencia Estatal CSIC, Spain</footnote>
abundance of targeted genes. Standard curves were obtained using serial dilutions (ranging from 10⁸ down to 10² copies µl⁻¹) of linearized plasmids containing the targeted genes cloned in.

## RESULTS AND DISCUSSION

In maize, cumulative N₂O emissions (Fig. 1) were significantly higher in N fertilized treatments (U), independently of Zn, than in unfertilized N treatments (N0), but small differences were found in wheat. Concerning Zn treatments, cumulative losses were significantly increased with the application of Zn chelate (ZnCH) combined with U in maize. Contrarily, wheat crop showed a decreased in cumulative N₂O emissions with U+ZnCH treatment. Besides, we observed a decrease in the total abundance of nitrifying and denitrifying communities with U+ZnCH treatment in wheat, except the gene involved in transforming N₂O to N₂ (nosZ gene) which was increased. In high moisture conditions, Pramanik and Kim (2016) reported an increase in N₂O losses after the addition of EDTA in a submerged paddy crop which was in agreement with our results in maize. However, the understanding of how Zn chelate modulates soil nitrifying and denitrifying microbiota under irrigated conditions is still under study.

<figure><img src="image_62.png" /><figcaption>Figure 1. Total cumulative N₂O-N emissions in winter wheat and maize crops amended with Zn fertilizer (Zn- DTPA-HEDTA-EDTA, ZnCH) and without Zn (Zn0) combined with two N application rates (0, N0, and 120 kg N ha⁻¹, U).</figcaption></figure>

## CONCLUSION

Our results demonstrated that in the rainfed crop, the application of synthetic chelates can be a promising strategy to decrease N₂O losses. However, the opposite was observed in an irrigated crop.

## REFERENCES

* Alvarez JM., 2010. Influence of soil type and natural Zn chelates on flax response, tensile properties and soil Zn availability. Plant Soil, 328, 217-233.

* Cakmak I., McLaughlin MJ., White P., 2017. Zinc for better crop production and human health.

* Pramanik P., Kim PJ., 2017. Contrasting effects of EDTA applications on the fluxes of methane and nitrous oxide emissions from straw-treated rice paddy soils. Journal of the Science of Food and Agriculture, 97, 278-283.

* Sanz-Cobena A., Sánchez-Martín L., García-Torres L., Vallejo A., 2012. Gaseous emissions of N₂O and NO and NO₃⁻ leaching from urea applied with urease and nitrification inhibitors to a maize (Zea mays) crop. Agr. Ecosyst. Environ. 149, 64-73.

* Venterea R.T., Coulter J.A., Dolan M.S., 2016. Evaluation of intensive "4R" strategies for decreasing nitrous oxide emissions and nitrogen surplus in rainfed corn. J. Environ. Qual., 45, 1186-1195.
# EVALUATION OF N₂O AND NH₃ EMISSIONS FROM THE USE OF DIGESTATE AS FERTILIZER ON SILAGE MAIZE

VERDI L.<fnref n="1" />, KUIKMAN P.J.², ORLANDINI S.<fnref n="1" />, MANCINI M.<fnref n="1" />, NAPOLI M.<fnref n="1" />, DALLA MARTA A.<fnref n="1" />

## INTRODUCTION

Fertilization represent one of the more effective strategy to maximize agricultural production and meet the growing global food demand. In particular, nitrogen (N) represents the main input to maximize crop yields. However, the uncontrolled use of N-based fertilizers and the low efficiency of application methods have led to considerable N losses through volatilization, leaching and soil erosion with consequentially detrimental ecological effects (eutrophication, decrease in biodiversity of natural lands, atmosphere, surface waters and groundwater). Therefore, N-based by-product with a low environmental production cost and high N content represents an effective strategy to reduce those impacts while maintaining high yields. In this sense, the use of digestate from anaerobic digestion of slurries to replace mineral fertilizers is considered an opportunity to reduce environmental impacts of fertilization (Pezzolla et al., 2012). This is mainly due to the low impact of digestate production, as waste of biogas, and to the high N easily available for plants. However, a mismanagement of digestate can led an increase of N₂O and NH₃ emissions with detrimental effects of the environment. The evaluation of N emissions from the use of digestate is fundamental on the assessment on his potential as fertilizer and on the reduction of greenhouse gases emissions from agriculture.

## MATERIAL AND METHODS

The experimental field is located at the Istituto Tecnico Agrario Statale (ITAGR), Firenze (43° 47' 07"N 11° 13' 11" E), Central Italy. Twelve tanks (volume 1 m⁻³ each) creating a controlled environment by preventing any interactions with surroundings conditions were utilized. A silty-clay soil was used and soil layers (0-30; 30-60; 60-90 cm of depth) were kept divided to reproduce soil profile into the tanks. Water supply was provided by a drip irrigation system. 13 seeds of silage maize (Var. Ronaldinho) were sowed on (17th June 2016) to reproduce a field plant density of 12.000 plant ha⁻<fnref n="1" />. Three fertilization treatments were tested: liquid fraction of digestate (pig slurries + triticale straw + olive cake + sorghum silage), urea and no fertilization (control). For each treatment, four replicates (tanks) were carried out in a randomized block design. The dose of each fertilizer was determined in order to supply 150 Kg ha⁻<fnref n="1" /> of N. To this aim, N content and type (NH₄⁺ and NO₃⁻) of digestate (Kg) were laboratory determined (N = 3.14 g Kg⁻<fnref n="1" />; NH₄⁺ = 2.81 g Kg⁻<fnref n="1" />; NO₃⁻ = 0.081 g Kg⁻<fnref n="1" />). According to Vallejo et al. (2005), digestate was manually applied by replacing slurry injection method, while urea was conventionally spread. In both treatments, fertilization was split into two doses: 18 days (F1) and 36 (F2) days after sowing. For the monitoring gas emissions twelve static chambers (one per tank) were constructed as described by Parkin and Venterea (2010). Chambers are composed of two parts: the lid of the chamber (25 cm high and 20 cm of diameter) and the anchor system (15 cm high with a diameter of 20 cm), to be inserted into the soil as support. Anchor system was positioned between plant rows immediately after sowing to reduce roots disturbance. Gas samplings were performed by means of a portable gas analyser (Madur Sensonic X-CGGM 400) that uses Nondispersive Infrared technology (NDIR) for NH₃ detection and electrochemical technology for N₂O. Gas fluxes were calculated starting from the gas concentration into the chamber, chamber dimensions (area and volume), closing time and molecular weight of each gas. Evaluation of fertilization potential was determined through the analysis of yields (t DM ha⁻<fnref n="1" />), N uptake by crops and N soil content before sowing and after harvest. The statistical analysis was performed using IBM SPSS Statistics 20. Dependence of emission fluxes on fertilizers was investigated by means of ANOVA model and Kruskal – Wallis test, when it wasn't possible to satisfy all of the assumption of ANOVA analysis.

## RESULTS AND DISCUSSION

<footnote n="1">¹Department of Agrifood Production and Environmental Sciences (DISPAA), University of Florence, Piazzale delle Cascine 18 – 50144 Firenze, Italy; 2Alterra, Wageningen University and Research Centre, P.O. Box 47, 6700 AA Wageningen, The Netherlands</footnote>
During F1, N₂O emissions were higher in digestate than urea. However, in F2 emissions were higher than F1 but we did not observed significant differences between the two treatments (Tab. 1). In accordance to Bouwman (1996) and Pezzolla et al. (2012), the higher N₂O emissions from digestate are mainly due to its water and organic C content that increases soil denitrification effect with greater potential for the production of N₂O as well, and the spreading method, injection, which enhanced interactions between digestate and soil microbial community. NH₃ emission in F1 were higher in urea than digestate (Tab. 1). In F2, emissions were lower than F1 and no significant differences between the two treatments were observed (Tab. 1). This is mainly due to the relation between NH₃ emissions and soil water content. In F1, the absence of rainfall ensured higher NH₃ emissions in urea that was left on soil surface after spreading with a scarce dissolution of the fertilizer into the soil. In F2, 7.4 mm of rainfall occurred and no differences were observed between digestate and urea NH₃ emissions. Moreover, distribution method plays a key role on NH₃ emission dynamics. In accordance to Wulf et al. (2002), the more the fertiliser is incorporated into the soil, the less NH₃ is lost through volatilization. Therefore, injection of digestate into the soil enhanced lower NH₃ emissions than urea. Concerning cumulative data, they were referred to a 25-days period as we considered 11 days of measurements after each fertilization (22 days in total) plus the period left between the end of F1 measurements and F2 (3 days) (experiment started in 4th of July 2016 and finished on 28th of July 2016). The analysis of N cumulative emissions (N₂O + NH₃) showed that urea lost more N than digestate (Tab. 1). Through the ratio between the emissions from digestate and urea (%) the relative reduction of N emissions obtainable from the use of each fertilizer was assessed. Based on our results, the net reduction of total N emissions produced by the use of digestate (2.867 Kg N ha⁻¹) compared to urea (3.759 Kg N ha⁻¹) is 23.73%. More specifically, the digestate allowed reducing N-NH₃ emissions by 66.32% while increasing N-N₂O emissions by 22.63%, showing that the main factor affecting the impacts of tested fertilizers is volatilization of NH₃. The analysis of yields shows no significant difference between the two treatments (α = 0.05), confirming the fertilization effect of digestate compare to urea (13.63 t DM ha⁻¹ and 13.24 t DM ha⁻¹, respectively). This is also confirmed by N uptake of plants that was not significantly different between the two treatments at a significance level α is = 0.05 (129.79 Kg N ha⁻¹ for digestate and 131.30 Kg N ha⁻¹ for urea). Results on soil analysis after maize harvest showed that tanks fertilized with digestate had a lower content of N than those treated with urea (0.125% and 0.167%, respectively). Therefore, we can assume that N emissions from digestate last longer than expected probably due to denitrification losses occurred between measuring period and harvest. Finally, based on the analysis on water collected from each tank, N was not lost through leaching.

## CONCLUSION

The use of digestate as fertilizer on silage maize is an effective method to lower total emissions of N. Together with a better environmental performance, the measurements on crop production showed that the digestate provide yields comparable to those obtainable with urea. However, N content in digestate is extremely low so that a large amount of product is required to satisfy the nutrient demand of maize. It means that several passes on the field are needed with consequent effects on GHG emissions from tractors, soil compaction and total economic cost. On the other hand, urea is a product of an industrial process that also has significant impacts in terms of gas emissions and economic costs. So that, a complete cost-benefit analysis of the entire process may be necessary to support farmers decisions.
<table><caption>Table 1. N2O and NH3 emission fluxes in first (F1), second fertilization (F2) and cumulative monitoring period of 25 days (Cum) expressed in ppm and Kg N ha-1.</caption><thead><tr><th></th><th></th><th>Unit</th><th>Digestate</th><th>Urea</th><th>Control</th></tr></thead><tbody><tr><td rowspan="3">N<sub>2</sub>O</td><td>F1</td><td>ppm</td><td>11,963</td><td>1,930</td><td>1,540</td></tr><tr><td>F2</td><td>“</td><td>32,390</td><td>32,372</td><td>6,965</td></tr><tr><td>Cum</td><td>“</td><td>44,353</td><td>34,302</td><td>8,505</td></tr><tr><td rowspan="3">NH<sub>3</sub></td><td>F1</td><td>“</td><td>27,750</td><td>100,265</td><td>8,086</td></tr><tr><td>F2</td><td>“</td><td>9,488</td><td>10,250</td><td>7,967</td></tr><tr><td>Cum</td><td>“</td><td>37,238</td><td>110,515</td><td>16,053</td></tr><tr><td>Total N</td><td></td><td>“</td><td>81,591</td><td>144,817</td><td>24,558</td></tr><tr><td rowspan="3">N<sub>2</sub>O</td><td>F1</td><td>Kg N ha<sup>-1</sup></td><td>0,584</td><td>0,094</td><td>0,075</td></tr><tr><td>F2</td><td>“</td><td>1,581</td><td>1,580</td><td>0,340</td></tr><tr><td>Total</td><td>“</td><td>2,165</td><td>1,675</td><td>0,415</td></tr><tr><td rowspan="3">NH<sub>3</sub></td><td>F1</td><td>“</td><td>0,523</td><td>1,891</td><td>0,153</td></tr><tr><td>F2</td><td>“</td><td>0,179</td><td>0,193</td><td>0,165</td></tr><tr><td>Total</td><td>“</td><td>0,702</td><td>2,084</td><td>0,318</td></tr><tr><td>Total N</td><td></td><td>Kg N ha<sup>-1</sup></td><td>2,867</td><td>3,759</td><td>0,733</td></tr></tbody></table>

**Acknowledgements:** The author thank Gerard Velthof for technical assistance during flux equation assessing and Martin Knotters for the statistical support during elaboration of the data. Moreover, author thank Azienda Agricola Marchese De' Frescobaldi, Fattoria di Corte for kindly providing digestate and Roberto Vivoli from DISPAA for his assistance in the field.

REFERENCES

Bouwman A.F., 1996. Direct emission of nitrous oxide from agricultural soils. Nutr. Cycl. Agroecosys. 46, 57-70.

Parkin T.B. and Venterea R.T. 2010. Sampling Protocols. Chapter 3. Chamber-Based Trace Gas Flux Measurements. In: Sampling Protocols. R.F. Follett, editor. p. 3-1 to 3-39. Available at: www.ars.usda.gov/research/GRACEnet

Pezzolla D., Bol R., Gigliotti G., Sawamoto T., Lopez A.L., Cardenas L., Chadwick D., 2012. Greenhouse gas (GHG) emissions from soils amended with digestate derived from anaerobic treatment of food waste. Rapid Commun. Mass Sp. 26, 2422-2430.

Vallejo A., Garcia-Torres L., Diez J.A., Arce A., Lopez-Fernandez S., 2005. Comparison of N losses (NO3 N2O NO) from surface applied, injected or amended pig slurry of an irrigated soil in a Mediterranean climate. Plant Soil 272, 313-325.

Wulf S., Maeting M., Clemens J., 2002. Application technique and slurry co-fermentation effects on ammonia, nitrous oxide and methane emissions after spreading I: Ammonia volatilization. J Environ Qual 31, 1789-1794.
# TRI-ISOTOPE ($^{13}$C, $^{15}$N, $^{33}$P) LABELING METHOD TO QUANTIFY RHIZODEPOSITION FROM A LEGUME

STEVENEL, P.¹, FROSSARD, E.¹, ABIVEN, S.², RAO, I.M.³, TAMBURINI, F.¹, AND OBERSON, A.¹

¹ ETH Zurich, Switzerland; ² University of Zurich, Switzerland; ³ International Center for Tropical Agriculture (CIAT), Cali, Colombia

## INTRODUCTION

Belowground carbon (C), nitrogen (N) and phosphorus (P) inputs of plants via roots and rhizodeposition play a key role in the cycling of these elements. Legume belowground N is an often-overlooked part when estimating the symbiotic $N_2$ fixation. Furthermore, C:N:P ratios of roots and rhizodeposition may affect the decomposition and nutrient release from these inputs. Better understanding the belowground C, N and P amounts and their turnover in soil is therefore crucial for the understanding of cycling of these elements in soil-plant systems.

Rhizodeposition is defined as release of all kinds of compounds lost from living plant roots (Uren 2001). Rhizodeposition of C and N is usually studied using isotope labeling, for C typically using exposure to labeled $CO_2$ (Kuzyakov and Schneckenberger 2004) while for N stem and leaf feeding techniques dominate (Wichern et al. 2008). Studies on belowground P inputs using P radioisotopes are rare. Foyjunnessa et al. (2016) used a stem feeding method to track $^{33}$P labeled belowground P inputs from canola in soil. The percentage of an element derived from rhizodeposition in the soil is calculated on the assumptions that isotopic composition (IC) of roots and rhizodeposition is identical, and that the IC of roots is constant over time (i.e., IC of root system does not significantly change during experimental period) and space (i.e., different root segments have same IC). The validity of these assumptions has hardly been checked.

The overall goal of our project is to study the belowground C, N and P input of a legume in highly weathered tropical soil along a soil P availability gradient. To this end, we i) developed a tri-isotope labeling protocol for simultaneously tracking belowground C, N and P inputs, ii) determined the elemental and isotopic composition of roots and rhizodeposition for C, N and P, and (iii) tested the validity of the assumptions underlying the quantification of rhizodeposition. We will show the outcome of the method testing and discuss the implications.

## MATERIAL AND METHODS

The tropical legume *Canavalia brasiliensis* was used as model plant for the development of the tri-isotope labeling method. This rapidly growing legume develops a strong stem suitable for a cotton wick stem feeding with a solution containing $^{15}$N labeled urea (Wichern et al. 2008) and carrier free $H_3^{33}PO_4$ (Foyjunnessa et al. 2016). The day before stem feeding, plants were in a chamber exposed to a single pulse of $^{13}CO_2$ atmosphere (Kuzyakov and Schneckenberger 2004). In a series of experiments, we assessed the IC of roots and rhizodeposition while a rhizobox experiment allowed determining the $^{15}$N, $^{13}$C and $^{33}$P tracer distributions within the root system over time and space. Experiments were conducted under greenhouse conditions in C-free sand using nutrient solutions with low N and P concentrations. Before harvest, the solution containing rhizodeposition (termed percolate) was evacuated using a peristaltic pump connected to perforated pots, and roots were hand picked carefully. Total C, N and P contained in shoots, root samples and in the percolate was analysed. The $^{33}$P was determined using a beta counter (TRI-CARB 2500 TR, liquid scintillation analyzer, Packard Instruments, Meriden, CT) to derive the specific activity ($^{33}P/^{31}P$). Nitrogen, C, $^{15}N/^{14}N$ and $^{13}C/^{12}C$ of plant and liquid samples were determined by EA-IRMS (vario PYRO cube, Elementar, Germany and IsoPrime100 IRMS, Isoprime, United Kingdom).

## RESULTS AND DISCUSSION

The plants took up all the $^{15}$N and $^{33}$P labeled solution within less than 24 hours. The tri-isotope labeling procedure provided $^{13}$C, $^{15}$N and $^{33}$P labeled roots and rhizodeposition.
A high isotopic enrichment was observed in sand, only 1 day after labeling, reflecting a high enrichment of rhizodeposition released during a short time span. Rapid allocation of assimilated C to rhizodeposits has been reported in earlier studies. However, for N and P the further development with time of the enrichment and activity, respectively, of roots and rhizodeposition suggests that highly enriched rhizodeposits might be an artefact generated with the labeling technique, as by Gasser et al. (2015) reported for ¹⁵N labeled clover.

Progressive translocation of ¹⁵N and ³³P was similarly observed from aerial plant parts to the root system over time. This suggests that for these two isotopes the stem feeding is not a pulse labeling in the strict sense, but is continuous during some days. Young root sections showed a higher ¹⁵N enrichment and higher specific activities than old root sections (Table 1), except for ¹³C isotopic enrichment that decreased due to the dilution effect resulting from growth. N and P were thus translocated for the development of new roots, while newly assimilated C was used for their growth.

## CONCLUSION

Belowground C, N and P inputs can simultaneously be isotope labeled to track their fate in soil-plant systems. However, the assumptions behind the equation used for determining rhizodeposition are most probably violated. The labeling is not homogeneous within the root system and not constant over time. Investigations are ongoing to evaluate the bias induced in rhizodeposition estimates.

<table><caption>Table 1. Total N and ¹⁵N distribution 8 days after stem labelling 50-day old *Canavalia brasilensis* plants.</caption><thead><tr><th></th><th></th><th>DM [g]</th><th>N uptake [mg]</th><th>atom%¹⁵N excess</th><th>recovery [%]</th></tr></thead><tbody><tr><td rowspan="2">shoot</td><td>total</td><td>0.93</td><td>29</td><td>0.83</td><td>74</td></tr><tr><td>total</td><td>0.58</td><td>7.9</td><td>0.31</td><td>8.8</td></tr><tr><td rowspan="2">root</td><td>r1w&lt;0<sup>a</sup></td><td>0.12</td><td>1.1</td><td>0.28</td><td>1.0</td></tr><tr><td>r2-8dal<sup>b</sup></td><td>0.08</td><td>1.2</td><td>0.68</td><td>2.8</td></tr></tbody></table>

## REFERENCES

* Foyjunnessa, McNeill A, Doolette A, Mason S, McLaughlin MJ (2016) Use of P-33 to trace in situ the fate of canola below-ground phosphorus, including wheat uptake in two contrasting soils. Crop & Pasture Science 67: 726-738.

* Gasser M, Hammelehle A, Oberson A, Frossard E, Mayer J (2015) Quantitative evidence of overestimated rhizodeposition using N-15 leaf-labelling. Soil Biol Biochem 85: 10-20.

* Kuzyakov Y, Schneckenberger K (2004) Review of estimation of plant rhizodeposition and their contribution to soil organic matter formation. Arch Agron Soil Sci 50: 115-132.

* Uren NC (2001) Types, amounts, and possible functions of compounds released into the rhizosphere by soil-grown plants. In: R Pinton, Z Varanini, P Nannipieri (eds) The Rhizosphere - Biogeochemistry and Organic Substances at the Soil-Plant interface. Marcel Dekker, New York, USA.

* Wichern F, Eberhardt E, Mayer J, Joergensen RG, Muller T (2008) Nitrogen rhizodeposition in agricultural crops: Methods, estimates and future prospects. Soil Biol Biochem 40: 30-48.

<footnote><sup>a</sup>roots grown 1 week before labeling; <sup>b</sup>roots grown between 2 and 8 days after labeling</footnote>
SILICON INCREASES LEAF LIFE SPAN IN N-DEPRIVED BRASSICA NAPUS L.

HADDAD, C.¹, ARKOUN, M.², YVIN, JC.², ETIENNE, P.*¹, LAINE, P.*¹

¹INRA, UMR 950 Ecophysiologie Végétale, Agronomie et nutrition N,C,S (EVA), France . *PhD supervisors ; ²Centre Mondial de l'Innovation – Roullier, France

INTRODUCTION

*Brassica napus* L. is an oleaginous crop requiring high nitrogen (N) inputs (140-200 kg N ha⁻¹ year⁻¹). Nevertheless, rapeseed is characterized by a poor N remobilization (Avice and Etienne, 2014). Indeed, leaves fall with a high N contents (2-2.5%) that may lead to environmental pollutions by nitrate leaching and the production of greenhouse gases such as nitrous oxide. To improve the agro-environmental balance of rapeseed, the use of biostimulants such as silicon (Si) constitutes an interesting alternative. In this context, the aim of our experiment was to study the effect of Si (a beneficial element for some plants especially to protect them against biotic and abiotic stress; Epstein, 1999) on vegetative growth, N uptake and leaf senescence progression of rapeseed subjected (or not) to N starvation.

MATERIAL AND METHODS

After germination on perlite, rapeseed seedlings were transferred for one week into a plastic tank containing nutrient solution with 1 mM N. Then, plants were separated into two batches : the first was supplied with the same nutrient solution with the addition of silicon (+Si: 1.7mM), and the second (-Si: 0.0 mM) was supplied with the nutrient solution only. After one week of Si pretreatment period, at day 0, each batch was again separated into two groups and grown during 12 days with (-Si+N ; +Si+N) or without N (-Si-N; +Si-N). Afterward, N-deprived plants have been re-supplied with N for 9 days (D21: -Si+rN; +Si+rN). At the end of Si pretreatment, plants were harvested for measurements of Si uptake (monitored by a colorimetric method), N uptake (determined with a continuous flow isotope mass spectrometer), and relative root expression of *BnaNRT1.1*, *BnaNRT2.1*, and *BnaAMT1.1* genes involved in nitrate (NRTs) and ammonium (AMT) uptake. Chlorophyll content and net photosynthetic activity were performed daily by a SPAD-502 chlorophyll meter and LI-COR, respectively, once the beginning of N starvation (day 0).

RESULTS AND DISCUSSION

Our study showed that rapeseed, which is considered a non-Si accumulator species (Hodson et al., 2005), is able to take up and store Si in roots at the end of the Si pretreatment (Fig. 1A). After a short period of Si treatment (7 days), the growth of +Si plants is increased by 1.45 fold compared to -Si plants (data not shown). This biomass increase is associated with an increase in the amount of N in +Si plants (Fig. 1B) and with induction (by 3 fold) of expression of the gene that encodes the *BnaNRT2.1* nitrate transporter (Fig. 1C).

<figure><img src="image_63.png" /></figure>

Figure 1. Silicon (Si) content (A), total nitrogen (N) amounts (B) and relative root expression of the BnaNRT1.1, BnaNRT2.1, and BnaAMT1.1 genes (C) at the end of the Si pretreatment for rapeseed. Asterisks represent significant differences from the control at P<0.05 (*), P<0.001 (**).
Under N starvation (from day 0 to 12), this study has shown that from day 5 and 7 the leaf SPAD and net photosynthetic activity values of +Si plants were significantly higher than those of -Si plants (Figs. 2A and B). These two parameters are usually considered as physiological indicators of leaf senescence (Gombert et al., 2006), and our result suggest that a Si pretreatment induces a delay in leaf senescence in +Si plants submitted to N starvation compared to -Si plants. When N-deprived plants were resupplied with N (days 12 to 21), senescing mature leaves from +Si plants recovered net photosynthetic activity (Fig. 2B) and turned green again (Fig. 2A), while mature leaves from -Si plants continue to senesce and fall at day 16, confirming a reversal of leaf senescence progression only in plants pretreated with Si.

<figure><img src="image_64.png" /><figcaption>Figure 2. Change in SPAD values (A) and net photosynthetic activity (B) of mature leaf from rapeseed. Asterisks represent significant differences from the control at P<0.05 (*), P<0.01 (**).</figcaption></figure>

## CONCLUSION

Si taken up by rapeseed improves biomass and increases N uptake and root expression of a nitrate transporter gene (*BnaNRT2.1*). In N-deprived plants, Si promotes a delay of leaf senescence allowing a better recovery of chlorophyll contents and photosynthetic activity when plant were re-supplied with N. Our study showed that Si is a beneficial element for rapeseed especially to cope to N deficiency by allowing it to increase leaf life span. Thus, Si may improve the agro-environmental balance of rapeseed by reducing the asynchronism between N remobilization from leaves and pods filling.

## REFERENCES

* Avice JC., Etienne P., 2014. Leaf senescence and nitrogen remobilization efficiency in oilseed rape (*Brassica napus* L.). *Journal of Experimental Botany*. 65,3813-3824.

* Epstein E., 1999. Silicon. *Annual review of plant biology*. 50,641-664.

* Gombert J., Etienne P., Ourry A., Le Dily F. 2006. The expression patterns of *SAG12/Cab* genes reveal the spatial and temporal progression of leaf senescence in *Brassica napus* L. with sensitivity to the environment. *Journal of Experimental Botany*. 57,1949-1956.

* Hodson MJ., White PJ., Mead A., Broadley MR. 2005. Phylogenetic variation in the silicon composition of plants. *Annals of Botany*. 96(6):1027-46.
# TILLAGE, SIMULATED ANIMAL TREADING AND SOIL MOISTURE AFFECT DENITRIFICATION, NO₃⁻ LEACHING, AND N₂O AND N₂ EMISSIONS

THOMAS, S.M.¹, FRASER, P.M.¹, HU, W.¹, CLOUGH, T.J.²

¹ Soil, Water and Environment Group, Plant & Food Research, New Zealand. ² Department of Soil and Physical Sciences, Lincoln University, New Zealand

## INTRODUCTION

Nitrification, denitrification, nitrifier-denitrification are highly sensitive to soil oxygen concentration, a property that is temporally dynamic and highly spatially variable. Consequently, farming practices such as tillage and grazing, that modify soil structure, which controls aeration and gas exchange, will affect nitrogen transformations. How much tillage or grazing change soil structural properties largely depends on the loading, initial soil strength and soil wetness. In New Zealand pastoral systems, tillage is often used to establish crops that are later grazed *in situ* during winter when soils are wet. This practice is often used as part of pasture renovation or to supplement pasture feed. In dairy systems, this might occur on 10% of the farm annually. Grazing of winter forage crops has been shown to increase emissions of nitrous oxide (N₂O), an important greenhouse gas (Thomas et al., 2008). There is also evidence that nitrate (NO₃⁻) leaching losses may also be reduced following animal treading (Hill et al., 2015). Despite the potentially large environmental impacts and trade-offs associated with winter grazing of forage crops, there is a paucity of information about the effects of tillage, treading and wetness at time of treading and their influence on total denitrification, its products of N₂ and N₂O, and the leaching of NO₃⁻.

## MATERIAL AND METHODS

We designed a replicated experiment using ¹⁵N-enriched NO₃⁻ to quantify how tillage (intensive cultivation vs. no-tillage), simulated treading (+/- compaction) and the soil moisture content at time of treading (<field capacity vs. > field capacity) affected gaseous losses of N₂O and nitrogen (N₂) and leaching losses of NO₃⁻. Intact soil lysimeters (30 cm diameter x 30 cm deep) were collected post-harvest from a tillage field trial conducted at Lincoln, Canterbury, New Zealand. The soil was a Templeton silt loam (USDA: Udic Ustochrept).

Treading was applied to the surface of the soil lysimeters (three hoof prints, 11 cm in diameter, per lysimeter; covering ~40% of soil surface area) at a pressure of 220 kPa using a hydraulic hoof simulator. Hanging fibreglass wicks applied soil water tensions (6 kPa) to the base of each lysimeter to simulate field conditions. Lysimeters were installed in a constant temperature room (14°C). ¹⁵N-enriched (50 atom %) NO₃⁻ solution was then applied to each lysimeter at a rate of 250 kg N ha⁻¹. To simulate winter wetting and re-wetting conditions, 30 mm of water was applied weekly to the cores. Leachate volumes, NO₃⁻ concentration, ¹⁵N-enrichment of NO₃⁻, and drainage rates were determined following each watering. Soil surface gas fluxes were determined from gas samples collected from headspace chambers, collected daily for the first 4 weeks and three-times per week thereafter. Samples were analysed for N₂O by gas chromatography, and ¹⁵N₂O and ¹⁵N₂ enrichments by isotope ratio mass spectrometry. The experiment ran for 80 days after the ¹⁵N was applied. Soil physical properties (bulk density, porosity, pore size distribution and hydraulic conductivity were determined on additional cores at the start and mid-point of the experiment, and on the main experiment cores at the end of the experiment to improve understanding of how changes in soil physical properties affect the rates and products of denitrification, but are beyond the scope of this paper.

## RESULTS AND DISCUSSION

Treading when soils were wet (> field capacity) enhanced denitrification. More denitrification occurred from the mechanically weakened soil (intensively cultivated), compared to the more structurally intact no-till soil (Table 1). Nearly 30% of the applied ¹⁵N-enriched NO₃⁻ was denitrified from the intensively tilled soil, compared to 18%
from the no tilled soil. While most was lost as N₂ from the intensive tilled soil, and the N₂O to total denitrification ratio was the lowest of all the treatments, it still produced the greatest amount of N₂O (3 % of the total N applied). Untrodden soils or soils trodden when the soil was drier had similar, lower amounts of denitrification (Table 1). Enhanced denitrification, removed a large amount of NO₃⁻-N that might otherwise have leached. The intensively tilled soil, trodden when wet, lost c. 25% less NO₃⁻ in leachate than the treatments that were either uncompacted or trodden when drier (Table 1). Cumulative drainage amounts (c. 300 mm) and water applications depths (360 mm) over the experiment were similar for all treatments.

<table><caption>Table 1. Cumulative NO₃⁻ leaching and gaseous losses via denitrification from lysimeters 80 days after ¹⁵N enriched NO₃⁻ was applied (@ 250 kg N ha⁻¹). Simulated treading (Yes/No) was applied at two moisture contents (< or > Field capacity) to soils that had previously grown forage crops established with intensive or no-tillage cultivation.</caption><thead><tr><th rowspan="2">Tillage</th><th rowspan="2">Moisture at treading</th><th rowspan="2">Simulated treading</th><th rowspan="2">NO<sub>3</sub><sup>-</sup> leached kgN ha<sup>-1</sup></th><th colspan="2">Denitrification</th></tr><tr><th>N<sub>2</sub> emitted kgN ha<sup>-1</sup></th><th>N<sub>2</sub>O emitted kgN ha<sup>-1</sup></th></tr></thead><tbody><tr><td rowspan="3">Intensive</td><td>Field capacity</td><td>No</td><td>146.7</td><td>24.7</td><td>5.5</td></tr><tr><td>Field capacity</td><td>Yes</td><td>169.5</td><td>26.1</td><td>3.9</td></tr><tr><td>Field capacity</td><td>Yes</td><td>112.4</td><td>64.4</td><td>8.2</td></tr><tr><td rowspan="3">o-Till</td><td>Field capacity</td><td>No</td><td>154.9</td><td>26.8</td><td>4.5</td></tr><tr><td>Field capacity</td><td>Yes</td><td>150.8</td><td>30.0</td><td>6.9</td></tr><tr><td>Field capacity</td><td>Yes</td><td>138.1</td><td>41.7</td><td>4.3</td></tr></tbody></table>

Removing NO₃⁻ that might leach could be considered an environmental benefit of enhanced denitrification, however other factors need to be considered. Firstly, much more N₂O, a potent greenhouse gas was produced where treading occurred under wet conditions. Secondly there was a loss of hydraulic conductivity (data not shown) which could lead to surface run off and soil erosion. From an agronomic perspective, the loss of soil NO₃⁻-N is a loss for plant production and may need to be replaced by fertiliser inputs. Furthermore, severe soil damage can impact future crop production or might necessitate further soil amelioration before a new crop or pasture can be established.

## CONCLUSIONS

Large increases in denitrification and N₂O emissions are likely when soils are grazed when wet, especially when tillage is used to establish forage crops for grazing. Hence, grazing or using heavy machinery on wet, tilled soils should be avoided. Our results also demonstrate the need to consider the total environmental and agronomic consequences of increased denitrification, i.e. trade-offs between N₂O emission, NO₃⁻ leaching and future crop productivity. Further work is ongoing to understand how changes in soil physical condition (e.g. soil gas diffusivity) alter denitrification products, and how this information can be used to provide better soil management advice.

**Acknowledgements:** This work was funded from the Plant & Food Research Strategic Science Investment Fund and the MBIE Forages for Reduced Nitrate Leaching Programme.

## REFERENCES

* Hill AM., Di HJ., Cameron K., Podolyan A., 2015. The effect of animal trampling and DCD on ammonia oxidisers, nitrification, and nitrate leaching under simulated winter forage grazing conditions. J Soils Sediments, 15, 972-981

* Thomas SM., Beare MH., Francis GS., Barlow HE., Hedderley DI., 2008. Effects of tillage, simulated cattle grazing and soil moisture on N₂O emissions from a winter forage crop. Plant Soil, 309, 131-145
# AN ORIGINAL EXPERIMENT TO DETERMINE IMPACT OF CATCH CROP INTRODUCTION IN A CROP ROTATION ON SOIL GREENHOUSE GAS EMISSIONS

TALLEC, T.<fnref n="1" />, BOUSSAC, M. <fnref n="1" />, ZAWILSKI, B. <fnref n="1" />, CLAVERIE, N. <fnref n="1" />, BRUT, A. <fnref n="1" />, FERLICOQ, M. <fnref n="1" />, CESCHIA, E. <fnref n="1" />, MORDELET, P. <fnref n="1" />, LE DANTEC, V. <fnref n="1" />

## INTRODUCTION

One quarter of the global N₂O emissions is emitted by agricultural soils. In cropland, long bare soil periods may occur between winter and summer crops with potentially large pools of nitrogen (N) available in the soil that can enhance N₂O emissions. Cover crops have been shown to reduce N₂O production during autumn by decreasing soil mineral N content (Thorup-Kristensen et al., 2003). However the impact of spring mineralization of incorporated cover crop on N₂O production has been little studied and could possibly offset the positive effects observed in autumn (Kaye and Quemada, 2017). A unique paired-plot experiment was carried out in the South-West of France from September 2013 to July 2014 to determine the effect of catch crop introduction in a crop rotation on soil N₂O and CO₂ fluxes (soil respiration, SR).

## MATERIAL AND METHODS

### Experimental site and design

The study was carried out over the Lamasquère site (FR-Lam) near Toulouse. This plot belongs to a livestock farm and is part of the European research infrastructure consortium ICOS and of the Regional Spatial Observatory (OSR). The surface area of the plot is 23.8 ha and soil texture is clayey. The crop rotation is maize for silage/winter wheat, irrigated during the maize growing season. Straw is exported and the field receives both mineral and organic fertilisation. After winter wheat was grown in 2013, the plot was divided into two subplots (1st September 2013). One subplot was sown with white mustard, the other one remaining conventionally managed in bare soil (BS). Catch crop was incorporated into the soil after 3 months of growing (4 December 2013). Then both subplots followed the same management with maize seeded on 23 May 2014.

### Measurements of N₂O and CO₂ fluxes

Each subplot was equipped with a set of six steel automated chambers, coupled to two infrared gas analyzers (LI-820 for CO₂ mixing ratio measurement, Thermofisher 46i for N₂O mixing ratio measurement). The automated chambers closed alternatively every 6 hours during 17.5 minutes each. Potential N₂O and CO₂ accumulation were measured sequentially in each chamber every 10 seconds. To calculate the N₂O fluxes the data were previously fitted with a rising exponential regression model. N₂O fluxes were then calculated following Tallec et al. (accepted).

### Additional measurements

Volumetric soil water content and temperature were monitored every hour at 0-7 cm depth inside each automated chamber (ML2x Thetaprobes, T107 thermistors). Water filled pore space (WFPS), that is a key variable for microbial activity and an indirect proxy of N₂O production and diffusion was calculated. The soil nitrate (NO₃⁻) and ammonium (NH₄⁺) contents were measured monthly from September 2013 to July 2014. Vegetation dynamic (cover crop and maize) was also monitored for dry matter production and green area index.

<footnote n="1">¹ Centre d'Etudes Spatiales de la BIOsphère, UMR 5126 CNES/CNRS/IRD/UPS, 18 avenue Edouard Belin, 31401 Toulouse, France</footnote>
<figure><img src="image_65.png" /><figcaption>Figure 1: Daily dynamics of WFPS at 0-7cm depth, N2O and CO2 fluxes according to the soil use (BS : Bare soil in black color, CC : Catch Crop in grey color). Error bars correspond to ± the standard deviation of the mean.</figcaption></figure>

## RESULTS AND DISCUSSION

During autumn (Figure 1), SR was positively related to the CC roots growing, causing a strong difference in SR between the two subplots. From the maximum level of CC development (data not shown), contribution of root respiration to the total SR was on average 56.5%. The nitrogen uptake from catch crop for its biomass production reduced soil mineral nitrogen content (data not shown). For similar WFPS (60%), lower soil mineral nitrogen content caused lower N₂O emissions during autumn in the CC subplot than in the BS subplot.

In summer, with increasing temperature and similar WFPS (60%) in both subplots, significant higher N₂O emissions occurred in the CC subplot compared to the BS one, particularly after N fertilizer inputs. The catch crop mineralization in addition to nitrogen fertilization significantly increased N₂O emissions and soil respiration probably because of increased microbial activity. Moreover due to enhanced development of maize with higher Nmin availability, SR in the CC subplot was 1.38 to 1.83 time higher than SR measured in the BS subplot.

## CONCLUSION

Introduction of CC in a crop rotation is a promising way to reduce environmental footprint of crops by indirectly decreasing nitrogen leaching and N₂O emissions during autumn and winter seasons. However our study underlined that those positive effects could be partly counteracted during the following growing season. N fertilization practices should also account for the net mineralization of the CC and the N requirements of the following crop to avoid enhance N₂O emissions after the CC is incorporated in the soil. Next step is to evaluate N₂O fluxes and Soil Respiration contribution to greenhouse gas budget over the whole crop year.

## REFERENCES

- Kaye, J. P., Quemada, M., 2017. Using cover crops to mitigate and adapt to climate change. A review. Agron. Sustain. Dev. 37:4, DOI: 10.1007/s13593-016-0410-x.

- Thorup-Kristensen et al., 2003. Catch crops and green manures as biological tools in nitrogen management in temperate zones. Adv. Agronomy, 79, 229-302.
# SUGARCANE TRASH REMOVAL REDUCES AMMONIA VOLATILIZATION AFTER SURFACE UREA APPLICATION

PINHEIRO, P. L.¹, DIETRICH, G.¹, RECOUS, S.², GIOVELLI, R. L.¹, SCHU, A. L.¹, GIACOMINI, S. J.¹

¹ Federal University of Santa Maria, Santa Maria, Brazil; 2 INRA - UMR FARE, Reims, France

## INTRODUCTION

In Brazil about 7.86 million hectares of sugarcane are managed in the green cane trash blanketing system (GCTB), in which trash (7.4 to 24.3 Mg ha⁻¹) is left as mulch on the soil surface. About 60% of this straw is still present on the soil surface at the time of N application of the next sugarcane cycle. When urea is the source of N used and its application occurs on the surface of the straw, high N losses due to volatilization of ammonia (NH₃) are expected (10 to 50% of applied urea-N). Recently, sugarcane straw has been used for other purposes such as energy generation or second generation ethanol. It is expected that total or partial removal of the crop straw will reduce urea-N losses by reducing favorable conditions for the NH₃ volatilization process (eg.: physical barrier reduction and decreased action of the urease enzyme). Thus, the objective of our work was to quantify the volatilization of NH₃ after the application of urea-N at different levels of straw removal after the sugarcane harvest.

## MATERIAL AND METHODS

The study was conducted at the Federal University of Santa Maria in the state of Rio Grande do Sul, Brazil. The experiment was carried out in the first ratoon sugarcane (RB95-6911) in 2016 and 2017. In each year, the experimental design was of randomized blocks in a factorial scheme 4x2 with four replicates. The first factor were four straw levels: 0, 4, 8 and 12 Mg ha⁻¹ (100, 67, 33 and 0% removal). The second factor were two rates of urea-N: 0 and 100 kg ha⁻¹. The urea-N was applied in a single dose at 15/01 and 21/02 in 2016 and 2017, respectively, 52 and 60 days after sugarcane harvest.

The ammonia (NH₃) volatilization was evaluated during 16 days in 2016 and 14 days in 2017, immediately following urea-N application. A semi-open static chamber collector, evaluated previously by Jantalia et al. (2012), was used to quantify the volatilized NH₃. The volatilized NH₃ was collected in a polyurethane foam (0.017 g cm⁻³; 5 mm thick; 2.5 cm wide and 25 cm length) soaked in 50 mL of H₂SO₄ (1 mol dm⁻³) + glycerol (4% v/v) acid solution. After each foam exchange, the chamber was changed place to minimize the effect of the chamber on the NH₃ volatilization process. The NH₃-N contents were determined by distilling and titration. All data were submitted to analysis of variance (ANOVA) and the means of each treatment were compared by the LSD test at the 5% probability level. For the cumulative amount (quantity) of NH₃ at the different levels of straw a linear regression was fitted.

## RESULTS AND DISCUSSION

For the two years, NH₃-N losses after application of urea-N was influenced by precipitation and amount of straw at the soil surface. In 2016, volatilization peaks of NH₃ occurred between day 10 and day 12 after N application after 5.2 mm of rainfall (Figure 1a). In 2017, maximum losses of NH₃-N were observed in the first two days after application of N (Figure 1b), after precipitation of 11.5 mm. In both years, our results showed that higher amounts of straw on the soil surface favored higher NH₃-N losses. We assume that the availability of water in the straw facilitates the solubilization of urea and increases the activity of the urease enzyme which determines the formation of NH₃ (Rochette et al., 2009). In addition, high amounts of straw on the soil surface can reduce or even prevent water infiltration into the soil (Vitti et al., 2007). Thus, the urea is retained in the straw and is susceptible to the action of the enzyme urease, which favors N losses by NH₃ volatilization. Therefore, there is a direct relationship between the amount of straw that remains on the soil and the loss of NH₃-N (Table 1).
<figure><img src="image_66.png" /><figcaption>Figure 1. Rainfall and NH₃-N losses in the first ratoon sugarcane in 2016 (a) and 2017 (b) after 100 kg urea-N ha⁻¹ (N) application over the different straw (S) rates (0, 4, 8 e 12 Mg ha⁻¹). The vertical bar represents the least significant difference (LSD) between the treatments (p < 0.05).</figcaption></figure>

<table><caption>Table 1. Cumulative NH₃-N emission in the first ratoon sugarcane (2016 and 2017) after 100 kg urea-N ha⁻¹ application over the different straw (S) rates (0, 4, 8 e 12 Mg ha⁻¹). *significant differ with t test (p<0.05).</caption><thead><tr><th rowspan="2">Year</th><th colspan="4">Straw level (Mg ha<sup>-1</sup>)</th><th rowspan="2">Regression</th></tr><tr><th>0</th><th>4</th><th>8</th><th>12</th></tr></thead><tbody><tr><td colspan="6">NH<sub>3</sub>-N loss (% of N applied)</td></tr><tr><td>2016</td><td>9.2</td><td>18.2</td><td>22.1</td><td>27.5</td><td>y = 10.4479 + 1.4755*x R<sup>2</sup> = 0.98</td></tr><tr><td>2017</td><td>30.7</td><td>40.8</td><td>53.7</td><td>60.8</td><td>y = 31.0625 + 2.5821*x R<sup>2</sup> = 0.99</td></tr></tbody></table>

## CONCLUSION

The removal of sugarcane straw on the soil reduces the losses of urea-N by ammonia volatilization in sugarcane cropping system. Every 4 Mg ha⁻¹ of straw removed from the crop, 8.1 kg of N ha⁻¹, on average, are saved.

**Acknowledgements:** EMBRAPA-PETROBRAS, CAPES and CNPq.

## REFERENCES

* Jantalia C.P., Halvorson A.D., Follett R.F., Alves B.J. R., Polidoro J.C., Urquiaga S., 2012. Nitrogen source effects on ammonia volatilization as measured with semi-static chambers. Agron. J., 104, 1595-1603.

* Rochette P., Angers D.A., Chantigny M.H., MacDonald J.D., Bissonnette N., Bertrand N., 2009. Ammonia volatilization following surface application of urea to tilled and no-till soils: A laboratory comparison. Soil and Tillage Research, 103, 310-315.

* Vitti A.C., Trivelin P.C.O., Gava G.J.D.C., Franco H.C.J., Bologna I.R., Faroni C.E., 2007. Produtividade da cana-de-açúcar relacionada à localização de adubos nitrogenados aplicados sobre os resíduos culturais em canavial sem queima. Rev. Bras. Cienc. Solo, 31, 491-498.
# EFFECT OF N APPLICATION RATE ON GROWING SEASON AND SPRING-THAW N₂O EMISSIONS IN NORWEGIAN SPRING WHEAT

RUSSENES, A.L.<fnref n="1" />,², KORSAETH, A<fnref n="1" />, BAKKEN, L.R.³, DÖRSCH, P.²

## INTRODUCTION

N₂O emissions from cultivated soils scale positively with the amount of N-fertilizer applied and may increase dramatically when the fertilization rate surpasses the N uptake by plants (Van Groenigen et al., 2010). It is therefore important to identify the N application rate which maximise yields while minimizing N₂O-emissions. In cool-temperate climates, a large proportion of the annual N₂O emission occurs, however, outside the cropping season, which potentially blurs the correlation between N input and N₂O-N loss. For instance, in a recent study in SE Norway, we found a pronounced emission peak during snowmelt in spring wheat stubble (Russenes et al., 2016). To investigate whether winter emissions are affected by N-fertilization levels, we combined growing season and winter N₂O emission data in a spring wheat plot trial with 0, 100, 140, 180 and 220 kg N.

## MATERIAL AND METHODS

The study was conducted in an ongoing plot trial with spring wheat (*Triticum aestivum* L.) in Southeast Norway. N levels varied from 100 to 220 kg N ha⁻<fnref n="1" />, with 40 kg intervals and zero-N controls (hereafter 100N, 140N, 180N, 220N and 0N). The plots were arranged randomly in two blocks (n=2). At sowing, all plots except 0N received 100 kg N ha⁻<fnref n="1" /> as compound fertilizer. At the beginning of stem elongation (BBCH 31), 0, 40, 80 or 120 kg N ha⁻<fnref n="1" /> were applied as top dressing. N₂O emissions were monitored by closed chamber technique in duplicate in each plot from split fertilization to crop harvest, occasionally during winter (on top of the snowpack) and more intensively during spring thaw. Soil air was sampled throughout winter from tailor-made probes (Nadeem et al., 2012) installed at 20, 12.5 and 5 cm depth, as well as at the soil surface and 10 and 20 cm above the soil surface in the snowpack. Soil temperature and volumetric moisture content were measured continuously by sensors at 5 and 20 cm depth in one of the blocks. During the growing season, NO₃⁻- and NH₄⁺ content was determined on the date of flux sampling in each plot by extracting soil from 0–20 cm depth. Wheat yield was calculated and grain analyzed for grain moisture and protein. OneWay Anova and Fischer 95 % comparison of LSD, using Minitab® 17.2.1 were used to calculate differences between fertilizer levels.

## RESULTS AND DISCUSSION

In the growing season, N₂O emission fluxes were largest on the day after top dressing, ranging from 14.6 - 95.8 µg N m⁻² h⁻<fnref n="1" />. Emission rates were greater, though not significantly, in treatments that had received additional N at stem elongation, and this difference persisted until 30 days after the split fertilization. A significantly higher flux was observed in the 220N treatment one week after top dressing (p = 0.023). Flux rates decreased gradually, until an increase in water filled pore space (WFPS) resulted in larger fluxes towards the end of the growing season. Here, emissions were significantly larger in 180N and 220N than in 100N and 140N, but there was no difference between 0N and 220N. Concentrations of extractable NO₃⁻- and NH₄⁺ matched the amount of added N, and gradually declined towards low levels at crop maturation. Cumulative N₂O fluxes during the growing season increased with increasing N-addition showing significant differences between N fertilization levels (p=0,025). Emissions were significantly larger in 180N and 220N than in 0N or 100N. 140N did not differ significantly from other treatments. Together, our results indicate that there must be additional factors other than the amount of fertilizer N affecting N₂O emissions during the growing season. N₂O emission rates during winter (before spring-thaw; 24.6 to 54.0 µg N m⁻² h⁻<fnref n="1" />) were comparable in magnitude to those measured in the growing season. The

<footnote n="1">¹ Department of Agricultural Technology and System Analysis, Norwegian Institute of Bioeconomy Research, Norway; ² Faculty of Environmental Sciences and Natural Resource Management, Norwegian University of Life Science, Norway; ³ Faculty of Chemistry, Biotechnology and Food Science, Norwegian University of Life Science, Norway.</footnote>
highest N₂O emission rates were measured during spring thaw with rates more than double of those observed during the growing season (101.6 - 144.0 µg N m⁻<fnref n="1" /> h⁻<fnref n="1" />). N₂O emission rates during spring thaw did not differ significantly between N treatments. When cumulating the emissions, we found that spring thaw triggered substantial N₂O emissions throughout the 20-days after onset of spring thaw. This suggests that a relatively large proportion of the annual emission occurs during a short period during spring thaw without any significant N-fertilization effect. Yield scaled emissions varied little between the N treatments (Tab. 1), but when scaled for grain yield, N₂O emission were largest in non-fertilized plots, illustrating the importance of adjusting N fertilization for the uptake and utilization of N by plants as precise as possible. Throughout winter, N₂O concentrations built gradually up under the snow cover in the wheat field. The soil temperature fluctuated around the freezing point both at 5 and 20 cm depth, with repeated freeze-thaw cycles (Fig. 1). When comparing the amounts accumulated to the cumulative emissions during thawing, only 6 % to 21.2 % of the emission was accounted for by release of accumulated N₂O, indicating that N₂O mostly is produced *de novo* during thawing.

<table><caption>Table 1 Cumulative N₂O emissions (kg N ha⁻<fnref n="1" /> period⁻<fnref n="1" />) for the different periods, grain yields (t ha⁻<fnref n="1" />) and emission intensity (kg N₂O-N emitted per t grain ha⁻<fnref n="1" />). Different letters indicate significant differences between fertilization levels at p < 0.05.</caption><thead><tr><th rowspan="2">Applied N<br>kg ha<sup>-1</sup></th><th colspan="5">Cumulative kg N<sub>2</sub>O-N ha<sup>-1</sup></th><th rowspan="2">Yield<br>t grain ha<sup>-1</sup></th><th rowspan="2">N<sub>2</sub>O<br>intensity<sup>1</sup></th><th rowspan="2">N<sub>2</sub>O<br>intensity<sup>2</sup></th></tr><tr><th>Season<br>20.06-<br>30.08.11</th><th>Thawing<br>08.03-<br>27.03.12</th><th>Winter/Thawing<br>02.12.11-27.03.12</th><th>Season+<br>Winter/Thawing</th><th>Yield<br>t grain ha<sup>-1</sup></th></tr></thead><tbody><tr><td></td><td>0.26 ± 0.09<sup>a</sup></td><td>0.34 ± 0.04</td><td>0.67 ± 0.16<sup>a</sup></td><td>0.93 ± 0.29<sup>a</sup></td><td>2.26 ± 0.74<sup>a</sup><br>5.81 ± 0.38</td><td>0.117</td><td>0.412</td></tr><tr><td>100</td><td>0.26 ± 0.08<sup>a</sup></td><td>0.31 ± 0.16</td><td>0.76 ± 0.09<sup>a</sup></td><td>1.02 ± 0.33<sup>ab</sup></td><td>b<br>6.70 ± 0.40</td><td>0.045</td><td>0.175</td></tr><tr><td>140</td><td>0.41 ± 0.09<sup>ab</sup></td><td>0.34 ± 0.19</td><td>0.84 ± 0.11<sup>ab</sup></td><td>1.25 ± 0.39<sup>bc</sup></td><td>b<br>7.42 ± 0.31</td><td>0.061</td><td>0.186</td></tr><tr><td>180</td><td>0.48 ± 0.12<sup>b</sup></td><td>0.44 ± 0.07</td><td>0.74 ± 0.13<sup>a</sup></td><td>1.22 ± 0.32<sup>abc</sup></td><td>b<br>7.01 ± 0.47</td><td>0.065</td><td>0.164</td></tr><tr><td>220</td><td>0.45 ± 0.12<sup>b</sup></td><td>0.35 ± 0.16</td><td>1.01 ± 0.21<sup>b</sup></td><td>1.46 ± 0.49<sup>c</sup></td><td>b</td><td>0.064</td><td>0.208</td></tr></tbody></table>

<figure><img src="image_67.png" /><figcaption>Figure 1. Accumulation of N₂O throughout winter in three soil depths and soil temperatures 5 and 20 cm.</figcaption></figure>

<footnote n="1">¹growing season emission relative to grain yield, ²total emission (growing season+winter/thawing) relative to grain yield</footnote>
## CONCLUSION

N₂O emissions during growing season are positively related to the amount of N added by split application, but when scaled to grain yield, the differences are minimal apart from the higher emissions found in unfertilized plots. To minimize the environmental impact while securing high yield output, it is therefore important to adjust N fertilizer levels to the actual crop production. N₂O production and emission during winter and spring thaw do not seem to be affected by N fertilization applied in the growing season. Subnivean N₂O accumulation throughout winter contributed less than 20 % to spring-thaw emissions, indicating that *de novo* production is the main source of N₂O emission during spring thaw.

## REFERENCES

* Nadeem, S., Hansen, S., Bleken, M.A., Dörsch, P., 2012. N₂O emission from organic barley cultivation as affected by green manure management. Biogeosciences Discussions 9, 2307-2341.
20th Nitrogen Workshop

Coupling C-N-P-S cycles

June 25-27, 2018

Le Couvent des Jacobins, Rennes – France

**Session III: Local process studies – Highlighted posters**
# PROTEIN AND AMINO ACID BREAKDOWN IN SOIL ALONG A PLANT FERTILITY GRADIENT

GREENFIELD, L.M.<fnref n="1" />, HILL, P.W.1, PATERSON, E.², BAGGS, E.M.³, SEATON, F.M.⁴, JONES, D.L.<fnref n="1" />

## INTRODUCTION

Soil organic compounds (including proteins and amino acids) are important sources of carbon (C) and nitrogen (N) for microorganisms. Therefore, the breakdown of proteins and amino acids in soil represent key controls on both the soil C and N cycles. Protease enzymes break down proteins to peptides and amino acids in the rate limiting step of organic N mineralisation whereas free amino acids can be taken up directly by microorganisms. Soil organic compound quantity is determined by plant production and decomposition of plant-derived material (Jobbagy and Jackson 2000). Consequently, the relationship between plant fertility and protein and amino acid breakdown is important in understanding the controls on soil C and N cycling.

## MATERIAL AND METHODS

We investigated how soil properties affect protein and amino acid breakdown along a fertility gradient. Soil was collected at two depths at ten points along a UK catena sequence. The catena sequence is a series from sea level to 410 m elevation characterised by different soil types and grassland communities. Background soil and plant parameters were measured at each site including soil protease activity following the method by Vepsäläinen et al., (2001). Rates of protein and amino acid mineralisation were measured by adding ¹⁴C-labelled plant protein and a ¹⁴C-labelled amino acid mixture respectively. Then ¹⁴CO₂ evolution was measured over a two-month period. A conceptual framework of protein and amino acid mineralisation along a plant C:N gradient was created to determine the key soil parameters that influence mineralisation.

All statistical analyses were performed in R studio 1.1.0.153 (R Core Team 2017). A random effects model was created to test the conceptual framework of protein and amino acid mineralisation along a plant C:N gradient. A model was fitted for ¹⁴CO₂ production after 6 hours and 60 days from ¹⁴C-labelled protein and amino acid at each depth with site as a random effect using the lme function in the package nlme (Pinheiro and al. 2017).

## RESULTS AND DISCUSSION

Overall, ¹⁴CO₂ production from ¹⁴C-labelled protein occurred at higher rates in the topsoil compared to the subsoil but no difference was observed between depths for amino acids (Fig. 1). Input of soil organic compounds are expected to be higher in the topsoil compared to the subsoil due to a higher density of roots that release organic compounds. This leads to a high abundance of microorganisms resulting in increased soil organic C mineralisation rates (Loeppmann et al. 2016). Therefore, it is unexpected that amino acid mineralisation does not differ between depths. ¹⁴CO₂ production from ¹⁴C-labelled amino acid was higher in the first six hours compared to ¹⁴C-labelled protein (Fig. 1) indicating that amino acids were utilised more quickly because they can be taken up intact by microorganisms.

According to our model, soil C and N, and microbial biomass C were found to have the most effect on ¹⁴CO₂ production. As above, these results show that soil organic compound inputs and microbial hotspots around the roots are important drivers on mineralisation rates. Plant C:N ratio was also an important control on protein and amino acid mineralisation rates indicating that breakdown is correlated with the plant fertility gradient. Protease activity did not have a strong influence on C mineralisation likely because proteases were not a limiting factor.

<footnote n="1">¹ Bangor University, UK; ² James Hutton Institute, UK; ³ University of Edinburgh, UK; ⁴ Centre for Ecology & Hydrology, UK</footnote>
<figure><img src="image_68.png" /><figcaption>Figure 1. Cumulative ¹⁴CO₂ production (% of total ¹⁴C-substrate added) (n = 3; mean ± SEM) for each site from low plant C:N ratio (site 1) to high plant C:N ratio (site 10) over a 60 day period. A) ¹⁴C-labelled protein added to topsoil, B) ¹⁴C-labelled protein added to subsoil, C) ¹⁴C-labelled amino acids added to topsoil and D) ¹⁴C-labelled amino acids added to subsoil.</figcaption></figure>

## CONCLUSION

Our study indicates that soil C and N inputs and microbial biomass are stronger drivers on soil organic C mineralisation over the plant fertility gradient rather than soil protease activity.

**Acknowledgements:** This work was supported by the Biotechnology and Biological Sciences Research Council; and the Natural Environment Research Council [Grant number NE/M009106/1], by a Soils Training and Research Studentships (STARS) grant to LMG. STARS is a consortium consisting of Bangor University, British Geological Survey, Centre for Ecology and Hydrology, Cranfield University, James Hutton Institute, Lancaster University, Rothamsted Research and the University of Nottingham.

## REFERENCES

- Jobbágy EG, Jackson RB (2000) The vertical distribution of soil organic carbon and its relation to climate and vegetation. Ecol Appl 10:423–436

- Loeppmann S, Blagodatskaya E, Pausch J, Kuzyakov Y (2016) Enzyme properties down the soil profile - A matter of substrate quality in rhizosphere and detritusphere. Soil Biol Biochem 103:274–283

- Pinheiro J, Bates D, DebRoy S, et al (2017) nlme: Linear and Nonlinear Mixed Effects Models. (R package version 3.1-131)

- R Core Team (2017) R: A language and environment for statistical computing

- Vepsäläinen M, Kukkonen S, Vestberg M, et al (2001) Application of soil enzyme activity test kit in a field experiment. Soil Biol Biochem 33:1665–167
# HOW DO SOIL AND FERTILISER TYPE AFFECT N₂O AND N₂ FLUXES? A SHORT-TERM HELIUM OXYGEN INCUBATION EXPERIMENT

BUCHEN, C.¹, HAGEMANN, U.¹, AUGUSTIN J.¹

¹ Leibniz Centre for Agricultural Landscape Research (ZALF), Germany

## INTRODUCTION

The greenhouse gas nitrous oxide (N₂O) is mainly derived from agricultural soils, whereby high fertiliser inputs are directly related to N₂O production. Understanding the factors controlling N₂O production processes in soils is still challenging and has to be improved to implement more advanced mitigation strategies to reduce undesirable side effects of fertiliser use. During the last years, a large share of mineral fertiliser was substituted by biogas residues (BD) from biogas production. However, BD have a higher potential to increase N₂O fluxes due to increasing ammonium (NH₄⁺-N) concentrations and total nitrogen (Nt) contents, as well as the labile carbon (C) pool in soil, compared to mineral fertilisers (MIN) (e.g. ammonium sulphate) (Senbayram et al., 2009; Charles et al., 2017). Apart from N₂O fluxes, the question have to be raised, how much of the applied fertiliser N is lost via dinitrogen (N₂) fluxes, which is of agronomic interest. Up to now, there are only a few data about N₂ fluxes following BD application. That's most likely, because determination of N₂ fluxes from soils is still a delicate matter due to high atmospheric background concentrations. In addition, environmental controls, such as nutrient and oxygen availability, soil conditions and climate have a known impact on N₂O and N₂ fluxes. Therefore it is required to improve our understanding of the combined effects of the factors mentioned on the resulting N₂O/(N₂O+N₂) ratio of denitrification. Thus, two fertiliser types (BD vs. MIN) and five different soil types (ranging from slightly loamy sand to very clayey silt) were investigated in a short-term laboratory experiment under N₂ free helium-oxygen (He-O₂) incubation atmosphere.

## MATERIAL AND METHODS

### Field sampling

Five undisturbed soil cores (250 cm³) were randomly taken immediately after fertiliser application in spring from five different study sites, covering various soil characteristics along a broad range of weather conditions in Germany. On all sites, two types of fertiliser were previously applied using drag hose and injection techniques: organic fertiliser, i.e. BD from biogas plants and MIN fertiliser, i.e. calcium ammonium nitrate.

### Laboratory incubation

Soil cores were incubated in special gas-tight incubation vessels in a He-O₂ incubation system (Butterbach-Bahl et al., 2002), classified as a flow-through steady-state system. Incubation atmosphere was replaced with He gas mixture containing <21 % O₂ and trace gases to remove atmospheric N₂. An incubation temperature of 10°C was established, similar to prevailing field conditions during sampling. Simultaneous measurements of the gases: N₂O and N₂ were conducted, lasting for two to four days until fluxes were constant. Following incubation, soil samples were analysed on relevant soil parameters (e.g. WFPS, NO₃⁻, NH₄⁺, pH, C org, Nt).

### Data analysis

Differences in soil properties and gas fluxes between treatments within site were analysed using the Mann-Whitney U-Test; differences among sites within treatments using the Kruskal-Wallis *H*-Test combined with *post-hoc* Student-Newman-Keuls test. Pairwise associations between either N₂, N₂O, N₂O/(N₂O+N₂) ratio of denitrification, soil and fertilisation parameters were characterised using the distribution-independent coefficient Spearman's rho. The influence of all variables on N₂ and N₂O fluxes was determined using generalised linear model (GLM) analysis with stepwise elimination.
# RESULTS AND DISCUSSION

## Site characteristics

Organic BD applications increased differences and variability among sites due to higher pH values, higher soil moisture (WFPS: 31 to 75%), higher organic C concentrations, higher $NH_4^+$ and lower $NO_3^-$ concentrations in BD samples compared to MIN samples.

## N₂O and N₂ fluxes

Measured absolute N₂O fluxes ranged from 37 to 1221 µg N₂O-N m⁻² h⁻¹ and from 23 to 140 µg N₂O-N m⁻² h⁻¹ for BD and MIN soil samples. Across sites, BD samples showed both significantly higher absolute and relative (to fertiliser N input) N₂O fluxes compared to MIN samples, even though this effect was dominated by samples from clayey Dornburg site. The same applies for the N₂ fluxes, were all measured fluxes were higher from BD samples than MIN samples. This means that the calculated average N₂O/(N₂O+N₂) ratio of denitrification was lower for BD compared to MIN samples, even though N₂ fluxes dominated both fertiliser treatments.

## Environmental controls

GLM analysis showed $NH_4^+$-N concentration, study site, bulk density, soil moisture and their interactions to be the most important factor for N₂O fluxes, followed by application type and fertilisation treatment. However, N₂ fluxes were driven by fertilisation treatment, $NH_4^+$-N concentrations and their interactions, followed by soil moisture and application type.

# CONCLUSION

The present study provided valuable insights into short-term N₂O and N₂ fluxes following the initial phase of fertiliser application. In particular high N losses from soil were obtained for the BD treatment, which were lost as a valuable plant nutrient source. Overall, N₂O and N₂ fluxes were strongly influenced by the interactions between soil and fertiliser type along five different field sites across Germany.

**Acknowledgements:** The study was funded by the German Federal Ministry of Food and Agriculture and managed by the Agency for Renewable Resources under grants 22021008 (08NR210). We thank all our partners from the Christian-Albrechts-University Kiel, University of Rostock, University of Applied Sciences Weihenstephan-Triesdorf, Thünen Institute and the Leibniz Centre for Agricultural Landscape Research.

# REFERENCES

* Butterbach-Bahl, K., Willibald, G., Papen, H., 2002. Soil core method for direct simultaneous determination of N₂ and N₂O emissions from forest soils. Plant and Soil 240, 105-116.

* Charles, A., Rochette, P., Whalen, J., Angers, D., Chantigny, M., Bertrand, N., 2017. Global nitrous oxide emission factors from agricultural soils after addition of organic amendments: A meta-analysis. Agriculture, Ecosystems & Environment 236, 88-98.

* Senbayram, M., Chen, R., Mühling, K., Dittert, K., 2009. Contribution of nitrification and denitrification to nitrous oxide emissions from soils after application of biogas waste and other fertilizers. Rapid Communications in Mass Spectrometry 23, 2489-2498.
# INTERACTIVE PLANT AND SOIL EFFECTS ON DENITRIFICATION POTENTIAL IN AGRICULTURAL SOILS

MALIQUE F.<fnref n="1" />, KE P.², MAURER D.³, DANNENMANN M.<fnref n="1" />, BUTTERBACH-BAHL K.<fnref n="1" />

## INTRODUCTION

During microbial denitrification, nitrate ($NO_3^-$) is reduced to nitrite ($NO_2^-$), nitric oxide (NO), nitrous oxide ($N_2O$) and finally to the terminal end product dinitrogen ($N_2$). The main ecological importance of denitrification is the removal of reactive nitrogen (N) from the biosphere. Moreover, denitrification is a key process for the production and consumption of the potent greenhouse gas $N_2O$. Main controls of denitrification are carbon and nitrate availability as well as oxygen levels as denitrification is a predominantly anaerobic process. All major controls of denitrification are directly or indirectly affected by plants. However, the effects of plants on denitrification as well as plant-soil interactions in dependence of soil parameters (texture, SOC) have rarely been studied.

Here we investigated the effect of three common agricultural crops (wheat, barley and ryegrass) on the denitrification potential in two different agricultural soils.

## MATERIAL AND METHODS

Two different soils were collected in Germany during the summer 2016: a) the Rotthalmünster soil was taken from arable land at the long-term experimental field in Höhere Landbauschule Rottalmünster (latitude N48°21', longitude E13°11', elevation 360m above sea level (a.s.l.); b) the Gießen soil, was taken at the grassland research station (latitude N50°32', longitude E8°41.3', elevation 172m a.s.l) near Gießen in the floodplain of the stream Lückenbach. The soils were sieved (10mm), air-dried and finally stored at 4°C before use. Experiments were done with three crops: wheat (Triticum aestivum), barley (Hordeum vulgare), and ryegrass (Lolium multiflorum).

Plants were pre-germinated on a 1% agar-agar solution. Following germination, plants were transplanted in planting pots (1L volume) with soils either originating from Gießen or Rotthalmünster. Soils were either fertilized (all plant treatments (3 crop types + 1 unplanted control)) with 100 mg N/kg dry soil of NPK fertilizer or left unfertilized (barley crops and unplanted control). Throughout the experiments soil moisture content was kept constant at a) 50 % Water Filled Pore Space (WFPS) (Rotthalmünster and Giessen) or b) at 34% (Rotthalmünster) or c) 40% WFPS (Giessen).

Besides planted soil we also investigated unplanted soils as controls. Soil denitrification potentials were measured before plant transplanting (day 0) and 10, 30 and 50 days after plant transplanting. The multifactorial experiment (2 soils * 4 plant treatments * 2 water levels * 2 fertilizer levels (unfertilized/ fertilized)) was replicated 5 times for the four sampling dates (day 0, 10, 30 and 50 following transplanting), resulting in a total of 480 planted/unplanted pots.

At sampling dates soil and plants were carefully separated, with soils being separated, as far as possible, in bulk and rhizosphere soil. Root and shoot biomasses were measured. Soils samples were analyzed for nitrate and ammonium contents, and soil denitrification potential.

The soil denitrification potential of bulk and rhizosphere soil was measured according to the protocol given by Groffman et al. (1999) using the acetylene blockage technique. Gas samples were analysed for $N_2O$ with a SRI 8610C Gas Chromatograph equipped with an electron capture detector. Potential denitrification rates were calculated from the mass of $N_2O$ produced during 1-hour anaerobic incubation (ng N/g/h). The results were

<footnote n="1">¹ Institute for Meteorology and Climate Research, Atmospheric Environmental Research (IMK-IFU), Karlsruhe Institute of Technology (KIT), Garmisch-Partenkirchen 82467, Germany, ² State Key Laboratory of Environmental Simulation and Pollution Control, Tsinghua University, Beijing 100084, China, ³ Institute of Forest Botany and Tree Physiology, Albert-Ludwig University, 79085 Freiburg</footnote>
statistically compared by using either the one-way ANOVA and Tukey's-b post hoc test method for the samples
which meet the requirements, or the non-parametric Welch and Games-Howell post hoc test method.

RESULTS AND DISCUSSION

At none of the sampling dates significant differences in potential denitrification rates could be demonstrated for treatments with and without fertilizer. Increased rates of potential denitrification in rhizosphere soils were found for soil samples taken at day 10 following transplanting, while for 30 and 50 no distinction could be made between bulk and rhizosphere soils as the entire planting pot was densely rooted. The following results are therefore only for fertilized pots and rhizosphere soil samples.

Rates of potential denitrification were significantly and up to 7 times higher in early plant growth stages (0 and 10 days) –as compared to soils sampled at days 30 and 50. Denitrification potentials significantly differed between the two soil types only for samples taken at days 0 and 10. (Figure 1). Across the entire observation period and all sampling dates significant differences in potential denitrification between unplanted and planted soils were not found.

<figure><img src="image_69.png" /><figcaption>Figure 1. Comparison of denitrification potential of fertilized soils taken either from Gießen (grassland soil) or Rotthalmünster (arable soil) with soils being incubated at 50% WFPS. Figure a) shows results for unplanted pots, while figure b) shows results for pots planted with wheat. Different letters indicate a significant difference at p <0.05</figcaption></figure>

However, interactive effects of plants and soils on denitrification potential were found for individual sampling
dates. These effects were either of additive, synergistic or antagonistic nature.

CONCLUSION

In sum, our results underline the decisive but so far hardly quantified importance of plants for the denitrification activity in soils. In order to provide a holistic understanding of plant control on denitrification, future studies should focus on disentangling plant-soil-microbe effects on actual denitrification rates and N gas product ratios. However, this remains a methodological challenge. Further analyses of soil properties and plant traits might be critical to better understand the mechanisms of how plants do effect soil denitrification.

REFERENCES

Groffman P. M., Gold A. J., Addy K., 1999. Nitrous oxide production in riparian zones and its importance to national emission inventories. Chemosphere – Global Change Science 2, 291-299
# NITROGEN LEACHING AND NITROUS OXIDE EMISSIONS FROM MAIZE: MITIGATION POTENTIAL OF VIZURA®, A NOVEL FORMULATION OF 3,4-DIMETHYLPYRAZOLE PHOSPHATE (DMPP)

NAIR, D.<fnref n="1" />, SANZ-GOMEZ, J.², BRENDSTRUP, I.³, PETERSEN, S.O.<fnref n="1" />

## INTRODUCTION

Denmark is an intensively farmed country, with 61% of its total land under cultivation. In the year 2015, agriculture contributed to 21.5% of the total greenhouse gas emissions in Denmark (Nielsen et al., 2017). Since Denmark has a 39% emission reduction target for 2030 as per the European Union's climate and energy framework for non-ETS sectors (Denmark's Energy and Climate Outlook, 2017), significant mitigation needs to be achieved also by the agriculture sector.

Silage maize for dairy cattle feed has become an important crop in Denmark, and the area under silage maize cultivation has increased from 61,000 to 190,000 ha during the past 20 years, often in rotations with grass-clover as the preceding crop. It is well established that mineral N accumulating in the soil after harvest of maize represents a risk of NO₃⁻ leaching during winter (Hansen & Eriksen, 2016). However, grass-clover incorporated before planting of maize can return large quantities of organic N to the soil (Eriksen, 2001) and net N mineralisation during spring, before planting of maize, therefore also involves a risk of nitrate leaching depending on soil properties and rainfall patterns.

Nitrification inhibitors have the potential to reduce N₂O emissions, as well as nitrate leaching from manure and fertilizer amended croplands (Qiao et al., 2015) by suppressing the activity of nitrifying bacteria and possibly archaea, thereby delaying the conversion of NH₄⁺ to NO₃⁻. This reduces the potential for N₂O emissions from nitrification, and from denitrification, by reducing substrate availability for denitrifying microbes. Use of NI's can thus help retain N in the form of less mobile NH₄⁺ and potentially improve plant N use efficiency. BASF has developed Vizura®, a novel formulation of the nitrification inhibitor DMPP for liquid manure and biogas digestate. In this study, Vizura® was assessed for its potential to mitigate N₂O emissions and nitrate leaching from a coarse sandy soil during spring within a grass-clover and maize rotation receiving cattle manure.

## MATERIALS AND METHODS

The experiment was carried out in a lysimeter facility located at AU Campus Foulum in western Denmark. A total of 36 lysimeters (1 m x 1 m, depth 1.4 m) with coarse sandy soil had been seeded with grass-clover (GC) in June 2016. A total of 12 treatments with three replicates were planned in a factorial design with three factors (figure 1), including: 1) ± application of Vizura® to GC prior to incorporation; 2) application of cattle manure ± Vizura® or no fertilization; and 3) ± simulated rain events to represent wet spring conditions; the pattern of extra rainfall (in total 90 mm) was determined based on precipitation in previous years. The treatments were randomized within each of three blocks.

<figure><img src="image_70.png" /><figcaption>Figure 1: Treatment combinations</figcaption></figure>

<footnote n="1">¹ Department of Agroecology, Aarhus University, Denmark; ² BASF SE, Germany; ³ BASF A/S, Denmark</footnote>
During April 2017, GC was cut and returned in equal amounts to all lysimeters, half of the portions after treatment with Vizura®, and then spring tillage was simulated. Manure or manure + Vizura® was applied to and incorporated in the respective plots, followed the next day by sowing of silage maize in all plots, in two rows with five plants each.

Monitoring of N leaching and N₂O emissions began in April 2017, immediately after GC tillage. Leachate was collected from all lysimeters for analysis of NO₃⁻ concentrations and volumes of leachate. Nitrous oxide emissions were determined by a closed static chamber method from an area between the two rows of maize plants. As supporting data, soil air was sampled from diffusion probes inserted at 5, 10, 20 and 50 cm depth in connection with flux measurements. Weather data were obtained from a nearby weather station. Crop yield was determined at harvest.

## RESULTS AND DISCUSSION

Monitoring of N₂O emissions and nitrate leaching covered a 12-month period, and therefore final cumulative values were not available at the time of writing. The preliminary estimates of N₂O emissions, including measurements from April to September, showed a consistent reduction in treatments where manure was amended with Vizura® in comparison to control treatments. An effect of treating GC with Vizura® before tillage was only seen under high rainfall conditions.

With respect to leaching, elevated nitrate concentrations in leachates (collected at 1.4 m depth) were not observed until August. The delay would be consistent with matrix flow of pore water in the coarse sandy soil. Based on the preliminary data representing April to September, there was no effect of Vizura® on nitrate leaching under normal rainfall conditions. The simulated high rainfall significantly increased leaching losses from treatments with un-amended manure, but this increase in nitrate leaching was partly prevented in manure + Vizura® treatments, showing a potential to conserve plant available N under wet spring conditions.

Harvest yield data were not available at the time of writing. Based on fresh weights only, the harvested biomass was substantially reduced under high rainfall conditions, but the yield reduction was less pronounced in treatments with Vizura®.

The preliminary results from this study thus indicate that nitrification inhibitors such as Vizura®, applied along with manure, could be a viable option for farmers to reduce N₂O emissions, as well as nitrate leaching on sandy soils. For Denmark, it could help in achieving the emission reduction target for agriculture of 39%.

## REFERENCES

* Denmarks Energy and Climate Outlook (2017) Denmark's Energy and Climate Outlook 2017. Denmark.

* Eriksen J (2001) Nitrate leaching and growth of cereal crops following cultivation of contrasting temporary grasslands. Journal of Agricultural Science, 136, 271–281.

* Hansen EM, Eriksen J (2016) Nitrate leaching in maize after cultivation of differently managed grass-clover leys on coarse sand in Denmark. Agriculture, Ecosystems and Environment, 216, 309–313.

* Nielsen, O.-K., Plejdrup, M.S., Winther, M., Nielsen, M., Gyldenkærne, S., Mikkelsen, M.H., Albrektsen, R., Thomsen, M., Hjelgaard, K., Fauser, P., Bruun, H.G., Johannsen, V.K., Nord-Larsen, T., Vesterdal, L., Callesen, I., Caspersen, O.H., Rasmussen, E., MG (2013) Denmark'S National Inventory Report. Aarhus.

* Qiao C, Liu L, Hu S, Compton JE, Greaver TL, Li Q (2015) How inhibiting nitrification affects nitrogen cycle and reduces environmental impacts of anthropogenic nitrogen input. Global Change Biology, 21, 1249–1257.
# COMPARATIVE EFFECT OF INORGANIC N ON PLANT GROWTH AND N₂ FIXATION OF TEN LEGUME CROPS

GUINET, M., NICOLARDOT, B., DUREY, V., REVELLIN, C., LOMBARD, F., PIMET, E., BIZOUARD, F., VOISIN, A.S.

UMR Agroécologie, AgroSup Dijon, CNRS, INRA, Université Bourgogne Franche Comté, France

## INTRODUCTION

Legumes are able to establish a symbiosis with *Rhizobium* bacteria and to fix atmospheric nitrogen (N₂). Thus, N nutrition of legumes can rely on both symbiotic nitrogen fixation (SNF) and on soil inorganic N uptake. Despite potential complementarity between these two N sources, N deficiency can be observed (Voisin and Gastal., 2015), especially when plant nutrition mostly relies on SNF (Moreau et al., 2008). Moreover, the proportion of N derived from SNF relative to total N uptake (% Ndfa) is known to be negatively affected by inorganic N available in the soil (Voisin et al., 2002). In view of this particular characteristic, the reintroduction of legume crops should play a key role in cropping system sustainability by allowing a reduction of nitrogen (N) inputs. A diversity of legume crops adapted to various pedoclimatic conditions exist and could meet these challenges. However, there is a lack of references on a wide range of legume crops. Furthermore, the few studies on legume species other than pea make comparison among species relatively difficult due to different experimental conditions. The main objectives of our study were to i) compare ten grain legumes for their response to inorganic N in terms of N accumulation, for comparable field experimental conditions, ii) understand the differences among the 10 species for SNF inhibition by inorganic N. For this, we also examined plant ability to uptake soil inorganic N and plant growth, which may explain variations among species in the level of SNF inhibition by inorganic N.

## MATERIALS AND METHODS

A field experiment was carried out in 2014 at the INRA experimental site of Bretenière (Eastern France). Ten legume crops were sown either in March (faba bean, common vetch, lentil, lupin, pea) or in May (fenugreek, chickpea, common bean, soybean, Narbonne vetch) depending on the physiology of each species. All seeds were inoculated at sowing with species-specific strains of N₂-fixing bacteria. Non-fixing reference crops were also sown: barley in March and sorghum in May. At sowing, inorganic N content in the first 60 cm of the soil were 69 and 84 kg N ha⁻¹ in March and May, respectively. Different levels of N fertiliser (0, 50, 150 and 300 kg N ha⁻¹) were applied at both sowing dates, in the form of NH₄NO₃. To estimate SNF, the ¹⁵N isotope dilution technique was used, with barley or sorghum as reference crops. 5 kg N ha⁻¹ of NH₄NO₃ labelled with ¹⁵N (1 % ¹⁵N enrichment) was additionally spread on all crops at each sowing date. Shoots were harvested at physiological maturity and dry matter (DM), N concentration (% N), ¹⁵N enrichment were measured for each crop and % Ndfa was calculated.

## RESULTS AND DISCUSSION

The amount of shoot N accumulated over the whole growth cycle greatly varied among species. When no N fertilizer was applied (ON treatment), shoot N ranged from 94 to 360 kg N ha⁻¹. For common vetch, lentil, lupin, fenugreek, Narbonne vetch, and soybean the level of N fertilizer did not significantly affect the shoot N amount. For common bean, faba bean, pea, and chickpea, the 300N treatment differed from the ON treatment, with the amount of shoot N compared to the ON treatment being increased by 11, 17, 33, and 57 %, respectively. For both sowing dates, a negative relationship between % Ndfa and the amount of inorganic N available at sowing was observed for all species but with great differences in the response intensity among species. As an indicator of this response intensity, the amount of inorganic N available at sowing, for which % Ndfa was equal to 50 %, was calculated. It ranged from 82 to 251 kg N ha⁻¹ for common bean to faba bean, respectively the most and least responsive to soil N (Figure 1). This indicator was positively related to mean shoot N amounts at maturity, as averaged for the four levels of N fertilization. However, great differences were observed among species according to their ability to uptake soil inorganic N. As an indicator of plant ability to uptake soil N, theoretical N uptake efficiency of inorganic N available at sowing (NUEt) was calculated. This is the ratio between the amount of total inorganic N uptake by the legumes when SNF was equal to 50 % (corresponding to half of the total amount of
shoot N at maturity), and the amount of inorganic N available at sowing required to inhibit SNF by 50 % of total
shoot N (Figure 1). Faba bean, lupin, fenugreek and Narbonne vetch had a NUE value lower than 0.5, indicating
that the amount of inorganic N they retrieved was twice less than the amount available at sowing. In contrast,
chickpea, common bean, common vetch, lentil, pea, soybean had NUE equal or higher than 0.5. Common bean
was the most efficient to uptake inorganic N (NUE = 0.94), meaning that almost all the inorganic N available at
sowing was retrieved by the plant.

<figure><img src="image_71.png" /></figure>

Figure 1. Relationships between (i) the mean shoot N amounts measured at maturity and (ii) inorganic N available at sowing for which % Ndfa was equal to 50 % (calculated using four level of N fertilization), measured for ten legumes species sown in a single field experiment, either in March 2014 (▲) and May 2014 (●). Cb : common bean, Ch : Chickpea, Cv : Common vetch, Fa : Fababean, Fe : Fenugreek, Le : Lentil, Lu : Lupin, Nv : Narbonne vetch, Pe : Pea, So : Soybean. The curves represent iso-efficiency uptake of inorganic N available at sowing.

CONCLUSION

While N fertilization had little effect on the amount of shoot N, SNF decreased with the level of inorganic N available at sowing with great differences among the ten legume species. Our field experiment allowed us to classify ten legume species according to their inorganic N uptake efficiency. We suggest that this ability to retrieve inorganic N might be a key element to understand the differences of SNF apparent inhibition by soil inorganic N. A better understanding of plant traits leading to a better NUE of inorganic N is crucial to avoid N losses, leaching being often observed in legume based rotations (Plazza-Bonilla., 2015). To go further, comparison of root architecture of the ten legume species is currently studied.

**Acknowledgements:** M. Guinet PhD work was granted by INRA and the Ministry in charge of Agriculture. This experimental work was supported by the ANR LEGITIMES and Bourgogne-Franche-Comté Region (France).

REFERENCES

Moreau, D., Voisin, A. S., Salon, C., Munier-Jolain, N. 2008. The model symbiotic association between *Medicago truncatula* cv. *Jemalong* and *Rhizobium meliloti* strain 2011 leads to N-stressed plants when symbiotic N₂ fixation is the main N source for plant growth. Journal of exp botany, 59, 3509-3522.

Plaza-Bonilla, D., Nolot, J.-M., Raffaillac, D., and Justes, E. (2015). Cover crops mitigate nitrate leaching in cropping systems including grain legumes: field evidence and model simulations. *Agriculture, Ecosystems & Environment* **212**, 1-12.

Voisin, A.-S., Gastal, F. 2015. Nutrition azotée et fonctionnement agrophysologique spécifique des légumineuses. *In* "Les légumineuses pour des systèmes agricoles et alimentaires durables" (A. Schneider and C. Huyghe, eds.), 79-137. editions Quae.

Voisin, A. S., Salon, C., Munier-Jolain, N. G., Ney, B. 2002. Quantitative effects of soil nitrate, growth potential and phenology on symbiotic nitrogen fixation of pea (*Pisum sativum* L.). Plant and Soil, 243, 31-42.
# THE EFFECT OF SEPARATING PIG SLURRY ON NITROGEN USE EFFICIENCY AND NITROGEN LOSS PATHWAYS FROM WINTER WHEAT ON CONTRASTING SOIL TYPES

THORMAN, R.E.¹, MUNRO, D.G¹, BENNETT, G.², EDWARDS, D.J¹, KINGSTON, H.L¹, WILLIAMS, J.R.¹

¹ ADAS Boxworth, Battlegate Road, Boxworth, Cambridge, CB23 4NH, UK; ² ADAS Gleadthorpe, Meden Vale, Mansfield, NG20 9PD, UK

## INTRODUCTION

Agriculture is fundamental in feeding a growing global population, but at the same time faces the challenge of minimising climate change and other environmental impacts. The use of new and modified manure management technologies has the potential to improve nitrogen (N) use efficiency (NUE) and minimise the loss of N to air (ammonia and nitrous oxide) and water (nitrate). Slurry separation on farms is a practical method to improve slurry management and has the potential to increase NUE by producing a high dry matter (DM), low readily available N, easily transported solid fraction, and a low DM, high readily available N liquid fraction (Fangueiro et al., 2015). The relatively low DM content of the liquid fraction compared to whole slurry can increase slurry infiltration into the soil reducing ammonia (NH₃) loss & hence indirect nitrous oxide (N₂O) emissions, as well as increasing grain yield and N uptake by the crop. However, the reduced NH₃ loss conserves N in the soil, which may result in an increase in direct N₂O emissions and nitrate (NO₃) leaching losses. The use of nitrification inhibitors (NIs) has been shown to reduce direct N₂O emissions, but NIs may also influence crop yields and N recovery, as well as NH₃ and NO₃ losses with consequential effects on indirect N₂O emissions. In the UK the use of slurry separation is increasing, therefore there is a need to investigate the effect that slurry separation (& combined with NIs) has on N loss pathways and crop available N supply following application to contrasting soil types.

## MATERIAL AND METHODS

Field experiments were carried out on two commercial arable farms in England with contrasting soil types. Site 1 was located near Cambridge, eastern England (average annual rainfall 565 mm) on a clay soil (c.40% clay). Site 2 was located near Mansfield, central England (average annual rainfall 650 mm) on a sandy loam soil (c.12% clay). At both sites treatments were applied to replicated (x3) plots (5 x 15 m) on cereal stubble in autumn 2016 and to separate plots with a growing winter wheat crop in spring 2017. Whole pig slurry and separated pig slurry - liquid fraction was applied by trailing hose using a custom-made small plot applicator. Separated pig slurry - solid fraction was applied by hand. Application rates were based on manure N analysis to give a target N loading for all the manures of 100-150 kg total N ha⁻¹. In a separate treatment, the commercially available NI, dicyandiamide (DCD) was tested; prior to application, DCD (1% solution) was mixed with separated pig slurry - liquid fraction to give a DCD application rate of 10 kg ha⁻¹. The N supplied by the DCD was accounted for in the total N application value. Additionally, for comparison with the manure treatments, ammonium nitrate and urea fertiliser were also applied at a rate of 150 kg N ha⁻¹ to separate plots. A control treatment was included where no nitrogen was applied.

Following N application, measurements of direct N₂O were made over 6 months, using 5 static chambers (0.8 m² total surface area) per plot and based on the method described by Chadwick et al., (2014). The sampling strategy was weighted with more intensive sampling in the first 6 weeks after application. Gas headspace samples were analysed by gas chromatography. The N₂O flux was calculated based on the linear increase in N₂O concentration inside the chamber. The assumed linear relationship was checked on each sampling occasion. Cumulative fluxes following land spreading were calculated using the trapezoidal rule. Nitrous oxide emission factors were calculated by subtracting the fluxes from the control plots and expressed as the percentage of total-N applied.

Ammonia emissions were measured using a wind tunnel technique (Nicholson et al., 2017) for 1 week following applications of whole pig slurry and the separated fractions, and for 2 weeks following application of the manufactured N fertilisers. One wind tunnel per plot was set up immediately after application with each wind tunnel being moved on a daily basis. Nitrate leaching losses were measured following the autumn application at
site 2 only. Porous ceramic cups (5 per plot) were installed at a depth of 90 cm during the period of over-winter drainage (Webster et al., 1993). Samples were taken every 2 weeks or after 25 mm of rain, whichever was soonest. Drainage volumes were estimated using IRRIGUIDE (Bailey and Spackman, 1986) and were combined with NO₃ concentrations to quantify the amounts of NO₃-N leached.

Soil temperature was logged continuously, along with measurements of air temperature and daily rainfall recorded at a nearby meteorological station. On every N₂O measurement occasion, representative soil samples were taken (0-10 cm) from each plot for the determination of gravimetric moisture and soil mineral N (ammonium-N and nitrate-N) content.

The fertiliser N replacement value of the organic manure treatments was calculated by comparing yields and crop N offtakes from plots receiving applications of manufactured N fertiliser; ammonium nitrate was applied in spring 2017 to replicated (x3) plots (3 x 15 m), at 6 rates ranging from 0-300 kg N ha⁻¹.

Grain yields and total crop N offtake were measured from all plots (including the N response) at harvest in 2017. ANOVA was conducted to determine experiment and treatment differences.

## RESULTS AND DISCUSSION

Results will be presented and discussed in terms of the potential that slurry separation has on improving winter wheat NUE and the effect that separation has on N loss pathways. We will examine the possible impact of using a NI combined with separation on the mitigation of gaseous emissions and NO₃ leaching losses, as well as any benefits to crop production. Additionally, the replacement of manufactured N fertilisers with the organic manures tested in these experiments will be discussed in relation to possible agronomic and environmental damage or indeed benefits.

**Acknowledgements:** This experiment forms part of the UK-China Virtual Joint Centre for Closed-Loop Cycling of Nitrogen in Chinese Agriculture (N-CIRCLE), funded from the Newton Fund via The Biotechnology and Biological Sciences Research Council (BBSRC).

## REFERENCES

- Bailey R.J., Spackman E., 1996. A model for estimating soil moisture changes as an aid to irrigation scheduling and crop water-use studies: I. Operational details and description. Soil Use Manage., 12, 122-129.

- Chadwick D.R., Cardenas L., Misselbrook T.H., Smith K.A., Rees R.M., Watson C.J., McGeough K.L., Williams J.R., Cloy J.M., Thorman R.E., Dhanoa M.S., 2014. Optimizing chamber methods for measuring nitrous oxide emissions from plot-based agricultural experiments. Eur. J. Soil Sci., 65, 295-307.

- Fangueiro D., Surgery S., Fraga I., Cabral F., Coutinho J., 2015. Band application of treated cattle slurry as an alternative to slurry injection: implications for gaseous emissions, soil quality and plant growth. Agric. Ecosyst. Environ., 211, 102-111.

- Nicholson F., Bhogal A., Cardenas L., Chadwick D., Misselbrook T., Rollett A., Taylor M., Thorman R., Williams J., 2017. Nitrogen losses to the environment following food-based digestate and compost applications to agricultural land. Environ. Pollut., 228, 204-516.

- Webster C.P., Shepherd M.A., Goulding K.W.T., Lord E.I., 1993. Comparisons of methods for measuring the leaching of mineral nitrogen from arable land. J. Soil Sci., 44, 49-62.
# WHAT LIMITS SHEEP URINE-N₂O EMISSIONS IN THE UPLANDS: NITRIFICATION OR C AVAILABILITY?

MARSDEN, K.A.<fnref n="1" />, HOLMBERG, J.A.<fnref n="1" />, JONES, D.L.<fnref n="1" />, CHARTERIS, A. F.², CÁRDENAS, L.M.² AND CHADWICK, D.R.<fnref n="1" />

## INTRODUCTION

There are > 33 million sheep in the UK (DEFRA, 2017), many of which graze land classed as ‘Less Favourable Areas’ (LFA), which are typically situated on mountainous terrain with poor production conditions (e.g. acidic soils, sloping land, high rainfall, cool climate and short growing season). According to Armstrong (2016), 88%, 80%, 69% and 16% of the agricultural land area in Scotland, Wales, England and Northern Ireland, respectively, falls within the LFA classification. The large numbers of livestock grazing on upland pastures (enclosed hill land and mountain areas) both in the UK, and globally, is a potentially large source of the greenhouse gas (GHG) nitrous oxide (N₂O), via excretal deposition of nitrogen (N) to soil. Data to quantify N₂O emissions from such areas, with urine as the N source, are particularly scarce. We aim to provide accurate and representative (in terms of urine chemical composition, patch size and volume) sheep urine patch N₂O emission factors (EF₃), for two contrasting grazing seasons (spring/summer (SP) and autumn (AT)), on unimproved common land. Due to slow rates of nitrification, we hypothesise that the N₂O EF from urine patches will be lower than would be measured from lowland mineral soils, indicating that national emissions from such areas are currently over-estimated.

## MATERIAL AND METHODS

### Study site, experimental design and treatments

The study took place within the Carneddau mountains (556 m a.s.l), in the Snowdonia National Park (53°22'N, 3°95'W). The vegetation is comprised of NVC classification H12 (*Calluna vulgaris* - *Vaccinium myrtillus* heath; Elkington et al., 2001), overlaying a Histosol soil type. The site was excluded of stock (Welsh Mountain ewes; *Ovis aries*) from 15th May 2017, and study sites contained 12 plots (1.5×1.5 m; treatments in a randomised block design), for both SP and AT. Sheep urine was collected *in-situ*, from penned ewes. Treatments (n=4) for SP included: i) control, ii) artificial sheep urine (860 kg N ha⁻<fnref n="1" />) and iii) real sheep urine (930 kg N ha⁻<fnref n="1" />). Urine patches were applied in triplicate within the GHG chambers. Based on SP application results, and limited quantities of real urine, treatments for AT were: i) control, ii) artificial urine (1125 kg N ha⁻<fnref n="1" />), and iii) NO₃⁻ and glucose (100 kg N ha⁻<fnref n="1" /> and 200 kg C ha⁻<fnref n="1" />). Treatment iii) was applied to determine the capacity for denitrification-related N₂O emissions without substrate limitation (soil moistures were high and assumed not to limit denitrification).

### Soil and GHG sampling and analysis

GHG emissions were monitored using a mobile, automated GHG monitoring system, with 12 static chambers (Scheer et al., 2014). The system captured N₂O, CO₂ and CH₄ data at a resolution of 8 flux measurements day⁻<fnref n="1" />. Within-chamber soil solution was collected via Rhizon soil solution samplers (Rhizosphere Research Products, Wageningen, Netherlands) and soil cores were taken using an auger from replicated treatments outside the chambers. Soil solution and K₂SO₄-extracts were analysed for NO₃⁻, NH₄⁺, dissolved organic C and total dissolved N over the study period. Cumulative N₂O fluxes were determined via integration and EF values were expressed as a % of the total N applied.

## RESULTS AND DISCUSSION

The magnitude of mean N₂O fluxes from real (in SP) and artificial sheep urine (in SP and AT) were low and did not peak above 40 µg N₂O-N m⁻² h⁻<fnref n="1" />. In contrast, the magnitude of mean fluxes from the NO₃⁻ and glucose treatment were much higher, peaking at just under 800 µg N₂O-N m⁻² h⁻<fnref n="1" />. Cumulative emissions and EF values for the treatments are shown in Table 1. The EF values for all urine treatments (real or artificial) were lower than

<footnote n="1">¹ School of Environment, Natural Resources and Geography, Bangor University, Bangor, Gwynedd, LL57 2UW, UK; ² Rothamsted Research, North Wyke, Okehampton, EX20 2SB</footnote>
comparable values from lowland mineral soils. We suggest EF values for urine deposition to UK soils could be disaggregated based on productivity gradients. In SP, evidence for nitrification (i.e. increasing $NO_3^-$ within soil solution), was only observed in one replicate of the real urine treatment and artificial urine treatments, where a corresponding $N_2O$ peak occurred (resulting in a high error term in the EF values). This suggests generally low rates of nitrification (potentially due to the low soil pH of 4.38) were limiting $N_2O$ production via both nitrification and denitrification. High $N_2O$ emissions from the $NO_3^-$ and glucose treatment demonstrated a high capacity for denitrification in these soils. Microbial C-limitation seems unlikely in these organic soils, but is possible if C is bound in non-available forms. Through further laboratory incubation experiments, a mechanistic understanding of what limits $N_2O$ emissions from these soils will be gained.

<table><caption>Table 1. Season of treatment application, measurement period (days), treatment type, cumulative $N_2O$ emissions over the measurement period (mg $N_2O$-N) and EF values for treatment application (% of total N applied).</caption><thead><tr><th>Season</th><th>Measurement period (days)</th><th>Treatment</th><th>Cumulative emissions (mg N<sub>2</sub>O-N)</th><th>EF (%)</th></tr></thead><tbody><tr><td rowspan="3">Spring (SP)</td><td rowspan="3">80</td><td>Control</td><td>1.30 ± 0.53</td><td>-</td></tr><tr><td>Artificial sheep urine</td><td>4.20 ± 2.92</td><td>0.14 ± 0.11</td></tr><tr><td>Real sheep urine</td><td>10.2 ± 9.28</td><td>0.34 ± 0.32</td></tr><tr><td rowspan="3">Autumn (AT)</td><td rowspan="3">45</td><td>Control</td><td>0.68 ± 0.34</td><td>-</td></tr><tr><td>Artificial sheep urine</td><td>2.07 ± 1.04</td><td>0.05 ± 0.01</td></tr><tr><td>$NO_3^-$ + glucose</td><td>246 ± 56</td><td>14.5 ± 3.3</td></tr></tbody></table>

## CONCLUSIONS

Our study provides novel high-frequency $N_2O$ flux data for sheep urine applied to UK upland peat soil. Extremely low emissions were observed from the urine patch in both SP and AT, in addition to low rates of nitrification. Results of the study provide EF values for sheep urine deposited to upland soils which provide evidence to refine the UK agricultural GHG inventory and can further be used to calculate more accurate sustainability metrics for upland lamb (e.g. life cycle analysis and C footprint) and will contribute towards evidence-based decision making for the future of UK upland land management.

**Acknowledgements:** Thanks to the Uplands-N2O project team, Emily Charlotte Cooledge, Danielle Hunt, Rob Brown, Mark Hughes, Llinos Hughes & Andrew Packwood for assistance with the study. Thanks to Snowdonia National Park, Natural Resources Wales, the National Trust and Aber & Llanfairfechan Graziers Association for allowing the site to be used. This work was funded under NERC under grant award (NE/M015351/1).

## REFERENCES

* Armstrong E., 2016. Research Briefing The Farming Sector in Wales, National Assembly for Wales.

* DEFRA, 2017. Agriculture in the United Kingdom 2016.

* Elkington T., Dayton N., Jackson D.L, Strachan I.M., 2001. National Vegetation Classification: Field Guide to Mires and Heaths, JNCCC, Peterborough, UK, pp 98-99.

* Scheer C., Rowlings D.W., Firrel M., Deuter P., Morris S., Grace P.R., 2014. Impact of nitrification inhibitor (DMPP) on soil nitrous oxide emissions from an intensive broccoli production system in sub-tropical Australia. Soil Biol. Biochem., 77, 243-251.
# GASEOUS EMISSIONS OF 3 TREATMENTS (CONTROL, COVERED, COVERED+COMPACTED) SOLID MANURE HEAP AT STORAGE

LORINQUER, E.<fnref n="1" />, CHARPIOT, A.<fnref n="1" />, FOUGERE, M.³, LECOMTE, M.², ROBIN, P.²

## INTRODUCTION

From the environmental point of view, ammonia emissions are partly responsible for acidification and eutrophication. In France, agriculture contributes 97% to national ammonia emissions which 46% comes from bovine farms (CITEPA, 2010). Different regulations at international, european and national levels have been established to limit particulate emissions, including ammonia, and sign up for part in the National Health and Environment Plan (NESP). As part of the proposed measures to reduce gas emissions in agriculture, it is necessary to pay attention to their feasibility from the point of view of their environmental efficiency and of their relevance at the farmer scale. Emissions from storage, which represent nearly 13% of nitrogen losses (as ammonia) from the bovine livestock operation, has however been little studied in France. This is particularly the case of cattle solid manure whose emissions are ignored while 68.7 million tons of cattle manure are produced each year in France, representing 80% of the total mass of cattle manure. EMAFUM project, funded by ADEME, had three main objectives: (i) development of a simplified method for the measurement of cattle manure storage (modeling and intermittent measurements), (ii) acquisition of reference values on emission kinetics deep litter heap (DLH) in representative conditions of livestock, (iii) evaluating the effect on gas emissions of three manure management modes (control heap, heap covered by a geotextile covering, covered + compacted heap) of deep litter during storage. This study focused on point (iii) that is based on the most dry and compact category of manure ('FTC') that represented in 2010, 25% of the solid manure produced by dairy farms and 65% of the solid manure produced by meat farms.

## MATERIAL AND METHODS

### Farm and manure characteristics

The solid manure studied comes from a Pays de la Loire dairy farm. During accumulation period, there were 69 Holstein dairy cows in 400 m² straw based loose housing (10 kg of straw/cow/day). Dairy cows were fed with maize silage, grass silage and concentrates (respectively 38kg, 17kg, 7kg of raw matter per cow), and they produced 28 kg milk.day-1.cow-1 during the accumulated period with an average of 6 months lactation stage. After removal from the barn, 5 tons of solid manure per heap have been stored on a platform from 13/02/2013 to 22/04/2013. Three storage modalities of this solid manure have been tested at the experimental farm of Derval: (i) Control (Cont.) manure stored in a heap, (ii) Covered (Cov.) with a polypropylene cover (Gangloff® Toptex) and (iii) Covered + compacted (Cov. + Comp.) with tractor at storage.

### Gaseous emissions

Temperatures have been followed at different heights (30, 60 and 90cm) with thermocouples linked with a CR3000 (Campbell Scientific). Gaseous emissions were followed during 2 days (48 hours) every week for 11 weeks with dynamic chamber systems (Greenhouse structure covered by a plastic cover usually used to cover maize silage). Gas concentration were measured at entry and exit of dynamic chamber with an infrared photoacoustic analyser (INNOVA 1412). Ventilation rate was controlled with Fancom mechanical fan, and punctually controlled anemometer (TSI 8470, TH-industrie, Paris). During 1 week, from 27/02 to 6/03/13, heaps have been covered and SF6 tracer gas has been introduced at entry to estimate and validate the ventilation rate of the fan. All along the

<footnote n="1">¹ Institut de l'Elevage, Monvoisin BP 85225, 35652 LE RHEU Cedex, France; 2 INRA UMR-SAS, 65 Rue de Saint Brieuc, 35042 Rennes, France; 3 La Touche, 44590 Derval, France</footnote>
trial, air entry size and ventilation rate have been adapted in order to keep a sufficient difference between entry and exit air concentrations to calculate the gradient concentration ([Gasoutlet]-[Gasinlet]). Leachates were collected, weighted and analysed regarding rainfall during all the storage period. Gas emissions were calculated by multiplying concentration gradients and ventilation rates. Emissions between, two measurements points have been estimated with a linear interpolation.

## RESULTS AND DISCUSSION

Ammonia emissions range from 4 to 12% total nitrogen originally present in the heap, probably related to the low ammonia nitrogen content of this type of effluent (11-34% of TAN – “total ammonium nitrogen” – TAN representing 35% of initial nitrogen). N₂O emissions ranged between 0.08 and 0.2% of total nitrogen initially present. Liquid losses of nitrogen (nitrate, ammonia) were less than 1% of the initial total nitrogen. The decrease in nitrogen of deep litter cattle manure occurs mostly in the form of dinitrogen (N₂-N; 24-28% of the initial total nitrogen for the control and the covered pile, and 4% for the compacted treatment). This study shows that NH₃-N, N₂O-N and CH₄-C emissions occur predominantly during the first month of storage for deep litter heap (FTC), respectively in the range of 97 to 100%, 41 to 56% and 82 to 90% depending on the treatment. The treatments studied in this project confirmed the hypothesis of ammonia emission reductions by covering or compacting (Petersen & Sommer, 2011). The uncertainty on emission reduction (in % of initial total nitrogen) was less than 6%, but remained high considering the uncertainty about the initial composition of manure (above 20%) and the repeatability of pile setting up (complex geometrical shape, lack of turning equipment). Covering the pile induced a decrease in biological activity by limiting the wetting from rain. This result should be confirmed with further measurements covering the variability of pile setting and climates (rainfall). Regarding GHG emissions, covering the pile did not reduce emissions. On the contrary, the compaction has a significant impact: nearly 10 times increase the amount of methane emitted. This is unacceptable to consider recommending compaction heap at storage. Staying at the scale of single storage is a bit simplistic, particularly at the level of ammonia that can be emitted after spreading, particularly when the manure is entered in the soil after 48h. Indeed, the control heap contains no more ammonia nitrogen at the end of storage, which suggests a limited volatilization during spreading. The covered heap had little bit less volatilization during storage, but it still contains 3 kg of NH₃ at the end of the period, which could be more easily volatilized during spreading.

## CONCLUSION

Ammonia losses were less than 12% of initial nitrogen for all treatments. This study confirmed that solid manure (FTC) is a very heterogeneous product and sampling and characterization is hard. Moreover in France there is a very high diversity of solid manure types linked to farm practices (feed ration, type and amount of litter, type of housing, grazing, animal productivity,...), so further investigation are required to have an overview of diversity at national scale on the whole manure management chain.

**Acknowledgements:** Acknowledgements, to the partners: IRSTEA Rennes, INRA UMR SAS, Derval experimental farm and the funder ADEME.

## REFERENCES

CITEPA, 2010. Inventaire des émissions de polluants atmosphériques en France – Séries sectorielles et analyses étendues – Format SECTEN, 247p.

Petersen S. O., S. G. Sommer, 2011. Ammonia and nitrous oxide interactions: Roles of manure organic matter management. Animal Feed Sci. and Technol. 166–167, 503–513.
# RECOVERY OF NITROGEN FROM DEPTH BY GRASSLAND SPECIES IN NORWAY

BYERS, E., RAUT, P., DÖRSCH, P., EICH-GREATOREX, S., BLEKEN, M.A.

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

## INTRODUCTION

In grassland systems, perennial ryegrass is often included for its good forage nutritional value and high yields. In Norway it has also been suggested as a catch crop to reduced leached mineralized nitrogen ($N_{min}$). However, it has poor winter survival and persistence in Norway (Sturite et al., 2007). There are contradictory reports about the rooting depth and relative ability to recover $N_{min}$ which has been leached to deeper soil layers (Hoekstra et al., 2015, Malcolm et al., 2015).

The purpose of this study was to compare recovery of $N_{min}$ from depth throughout one season by perennial ryegrass (*Lolium perenne* L.) with other grassland species commonly grown in Norway. Fast-growing perennial ryegrass was expected to uptake $N_{min}$ quickly, but not from depth. Three other tall grasses – tall fescue (*Festuca arundinacea* L.), meadow fescue (*Festuca pratensis* Huds.), and timothy (*Phleum pratense* L.) were included, with deepest-rooting tall fescue expected to recover the greatest amount of $N_{min}$ from depth. Kentucky bluegrass (*Poa pratensis* L.), included for its suitability to grazing conditions, has shallower rooting activity and was expected to take up the least $N_{min}$ from depth among the grasses. Red clover (*Trifolium pratense* L.) and white clover (*Trifolium repens* L.) were included because they are nitrogen-fixing, and were expected to take up less $N_{min}$ than the grasses, though deeper-rooting red clover was expected to recover more from depth than white clover.

## MATERIAL AND METHODS

A ¹⁵N-labeling study was performed in an established grassland trial in its second production year. Four replicate plots of each species in pure stands were labeled with ¹⁵NH₄Cl adsorbed to zeolite. The zeolite was buried at 43 cm in a 4x4 array of 16 holes, for an effective loading of 0.07 g ¹⁵N m⁻² within each experimental harvest area of approximately 0.5 m². Biomass from each of three harvests in 2016, plus the first harvest of 2017, was analyzed for dry matter yield, N content and ¹⁵N.

To account for different yields and nitrogen contents between species, the cumulative recovery of ¹⁵N (1st harvest, 1st + 2nd harvest, 1st + 2nd + 3rd harvest, all harvests) was plotted versus the cumulative total N content. Differences between species ¹⁵N uptake were tested in a general linear model with total N, species, and their interaction as regressors. Species were introduced into the model as dummy variables. A natural log transformation of total N was found to give the best model. ANOVA of ¹⁵N recovery by species was also performed for each harvest. The analysis was performed in R.

## RESULTS AND DISCUSSION

Contrary to the expectation that tall fescue would recover the most $N_{min}$ from depth, it recovered the same amount of ¹⁵N as meadow fescue and timothy, both in terms of absolute ¹⁵N amount and relative to total N. Ryegrass in fact had the highest ¹⁵N recovery in the 2nd harvest of 2016 (growth period 1 June – 13 July), and the highest cumulative ¹⁵N per total N. This may indicate an advantage of using ryegrass as a catch crop for leached $N_{min}$ mid-season. As expected, these four tall grasses had higher cumulative ¹⁵N recovery than shallower-rooting bluegrass.

Nitrogen-fixing red clover and white clover recovered less ¹⁵N and had higher total N concentrations, thus having lower ¹⁵N uptake per total N than all the grasses. Their ¹⁵N uptake was not different to that of the grasses in the
3rd harvest of 2016 (growth period 13 July – 2 September), perhaps because the original ¹⁵N loadings in the grass plots were more depleted by that time. White clover was not harvested in the first cut of 2016 due to poor early spring growth; this explains its lower ¹⁵N uptake compared to red clover. Despite the deeper rooting of red clover, there was no significant difference in ¹⁵N uptake between red and white clover in the 2nd or 3rd harvest of 2016. Red clover did however recover more ¹⁵N than white clover in early spring 2017.

<figure><img src="image_72.png" /><figcaption>Figure 1. Cumulative ¹⁵N uptake in four consecutive harvests, plotted versus cumulative total N content of harvested herbage. Symbols mark replicate values (4 per treatment X harvest combination). Logarithmic least square trend lines for tall fescue, meadow fescue and timothy were not significantly different from each other, whereas those for all other species were significantly higher or lower than this group (p<0.05).</figcaption></figure>

## CONCLUSION

Ryegrass may perform well in recovering deep-leached $n_{min}$ mid-season in sub-boreal climates. Tall fescue was not better at $n_{min}$ uptake from depth than the other tall grasses. Clovers and bluegrass may recover $n_{min}$ from depth later in the season, with red clover recovering more than white clover in the early spring due to better growth. The ability to recover and retain $n_{min}$ also depends on the persistence and overwinter survival into following years. Therefore in 2017, the 2016 study was followed up with continued harvests of the original plots, and the experiment was also repeated with newly-labeled plots (results forthcoming).

## REFERENCES

* Sturite, I., Henriksen, T.M., Breland, T.A., 2007. Winter losses of nitrogen and phosphorus from Italian ryegrass, meadow fescue and white clover in a northern temperate climate. Agriculture, Ecosystems & Environment 120, 280–290.

* Hoekstra, N.J., Suter, M., Finn, J.A., Husse, S., Lüscher, A., 2015. Do belowground vertical niche differences between deep- and shallow-rooted species enhance resource uptake and drought resistance in grassland mixtures? Plant and Soil 394, 21–34.

* Malcolm, B.J., Moir, J.L., Cameron, K.C., Di, H.J., Edwards, G.R., 2015. Influence of plant growth and root architecture of Italian ryegrass (Lolium multiflorum) and tall fescue (Festuca arundinacea) on N recovery during winter. Grass and Forage Science 70, 600–610.
# IS THE SPATIAL DEPENDENCE OF NITROGEN AND SULPHUR COMBINABLE FOR SITE SPECIFIC MANAGEMENT?

CORDOVA, C.

Departamento de Suelos y Recursos Naturales, Facultad de Agronomía, Universidad de Concepción, Chile

## INTRODUCTION

Crop yield and quality are key aspects to achieve global food security, and nitrogen (N) is essential to meet the production target to feed the increasing world population. However, the natural N supply from the soil is restrictive for crop growth, and mineral or organic application of N is often necessary. The interaction between N and sulfur (S) (Maynard et al., 1983), due to the similarities in their soil cycles, might help to increase the efficiency of N uptake and therefore decrease the rate of N applied. Moreover, the quality of crop production in terms of protein, essential amine acids or fatty acids might be improved by the S application.

Site specific fertilization within a field needs to identify areas with differential nutrient supply, i.e., the mineralization process. The classification of the differential zones is made according to the analysis of the spatial dependence and variability of a soil property/process. A nested analysis of variance allows the investigation of multiple intervals of distance in a single analysis (Lark, 2011), and provides a good approximation to the variogram for spatial interpolation (Webster et al., 2007) to map differential areas.

Therefore, the objective of this study is to analyse the spatial dependence of N and S mineralization at the field scale, which might lead to a combined fertilizer recommendation and management if they are spatially correlated.

## MATERIAL AND METHODS

### Soil sampling

This research was carried out in a site at the fringes of the Andes Mountains (36°59'S 71°55'W) with rainfall around 1500 mm year⁻¹ and the slope between 3-8%. The crop rotation was oat-wheat, established on a Andisol soil (11.09 % soil organic matter, 8.79 cmol kg⁻¹ soil exchange capacity, 14.30 mg kg⁻¹ available N, 14.60 mg kg⁻¹ available P, 324.50 mg kg⁻¹ available K, 30.0 mg kg⁻¹ available S).

Soil samples were collected in Autumn season, at 0-10 cm depth, considered relevant for the active mineralization process. A number of 96 soil samples were obtained, instead of 486, from an efficient nested sampling design (Webster and Lark, 2013) over a 4 ha field, where sampling intervals of 121.5 m were organized as a triangle (replicated twice within the field) and from each node other sampling intervals were hierarchically marked away at 40 m, 13.5 m, 4.5 m and 1.5 m, and then sampled. From each sample mineralization indicators for N and S were measured.

### Nitrogen and sulfur supply assessment

Potentially available nitrogen (PAN) was measured to estimate the natural soil contribution to N supply. Ammonium was measured on air-dry soil samples by colorimetric analyses, and after seven days of anaerobic soil incubation at 40°C. The ammonium was extracted from the soil using 2M KCl solution (1:5), and the color development was obtained using 3M NaOH and Nessler reactive solutions. The color intensity was measured at 490 nm. The PAN was calculated as the difference of the mineralized N at the end of the incubation and the initial amount in the soil. Sulphur mineralization was measured by open soil incubation held on Buchner funnel for seven days at 22°C. The sulfate in the soil was extracted using a 10mM CaCl₂ solution (1:5) and the sulfate concentration was measured by ion-chromatography.
## Data analysis

The statistical summary of the data sets was calculated to analyze the central and dispersion parameters of N and S variables. The N and S mineralization results were analyzed by maximum residual likelihood (REML) to obtain the components of variance from each scale studied and determine the spatial dependence, using Genstat package 16th Ed. (VSNI international, 2014).

## RESULTS AND DISCUSSION

The mean value for the index of N supply was 32.92 ± 17.36 N-NH₄⁺ kg⁻¹ and the S-SO₄²⁻ mineralized was 6.45 ± 4.83 mg kg⁻¹. The range, 90.04 mg N-NH₄⁺ kg⁻¹ and 26.23 mg S-SO₄²⁻ kg soil⁻¹, and variance of N and S values of mineralization measured were large, showing the spatial variation of the soil supply of these two elements for crop nutrition, i.e., some locations within the field are deficient whilst others show a surplus. This could be associated to the soil clay content stabilizing organic matter, and regulated by soil moisture.

The data set of N and S mineralized were skewed and so a log-transformation was applied for the REML analysis. The partial components of variance were accumulated from the shortest distance interval to the largest one (Table 1) and the resulting limit of spatial dependence of PAN was detected at 40.5 m, where 59% of the variance was obtained. S mineralization reached the spatial dependence at 40.5 m, encompassing 53% of the variance (Table 1). Although N and S mineralization showed the same limit of spatial dependence, the partial components of variance showed a different approach to the variogram (figures not shown) which needs to be further analyzed by spatial correlation, particularly for the 4.5 m scale.

<table><caption>Table 1. Components of variance and the spatial dependence for an index of soil nitrogen supply and sulfur mineralization from an Andisol under cereal crop rotation.</caption><thead><tr><th rowspan="2">Interval distance</th><th colspan="3">Potentially available nitrogen</th><th colspan="3">Sulfur mineralization</th></tr><tr><th>Component of variance</th><th>Accumulated variance</th><th>% of total variance</th><th>Component of variance</th><th>Accumulated variance</th><th>% of total variance</th></tr></thead><tbody><tr><td>121.5 m</td><td>0.313</td><td>0.763</td><td>100</td><td>0.028</td><td>0.060</td><td>100</td></tr><tr><td>40.5 m</td><td>0.000</td><td>0.450</td><td>59</td><td>0.000</td><td>0.032</td><td>53</td></tr><tr><td>13.5 m</td><td>0.250</td><td>0.450</td><td>59</td><td>0.000</td><td>0.032</td><td>53</td></tr><tr><td>4.5 m</td><td>0.200</td><td>0.200</td><td>26</td><td>0.032</td><td>0.032</td><td>53</td></tr><tr><td>1.5 m</td><td>0.000</td><td>0.000</td><td>0</td><td>0.000</td><td>0.000</td><td>0</td></tr></tbody></table>

## CONCLUSION

Preliminary results show that a plausible sampling distance to simultaneously account for the spatial variability of N and S supply is 20 m, half of the limit of spatial dependence. However, spatial correlation analysis will define the exact relationship between N and S.

**Acknowledgements:** This research was funded by Conicyt-Fondecyt 11130447.

## REFERENCES

* Lark, R.M., 2011. Spatially nested sampling schemes for spatial variance components: scope for optimization. Comput. Geosci., 37: 1633-1641.

* Maynard, D.G., J.W.B, Steward, and J.R, Bettany, 1983. Sulfur and nitrogen mineralization in soils compared using two incubation techniques. Soil Biol. Bioch., 15: 251-256.

* Webster, R., Oliver, M. 2007. Geostatistics for environmental scientists. John Wiley & Sons, Ltd. Chichester, UK.

* Webster, R. and R.M. Lark., 2013. Field sampling for environmental science and management. Routledge. Milton Park, UK.

* VSN International, 2014. GenStat for Windows 16th Edition. VSN International, Hemel Hempstead, UK.
# NITROGEN TURNOVER FROM CONTRASTING COMPLEX ORGANIC MATRIXES - EXAMPLES FROM ¹⁵N STABLE ISOTOPE STUDIES WITH COMPOST AND DIGESTED SLURRIES

MAYER, J.<fnref n="1" />, KOEPPE, P.<fnref n="1" />, DUBOIS, A.<fnref n="1" />, HUTTER, M.<fnref n="1" />,²

## INTRODUCTION

Organic waste composts, manure or digested slurries with or without co-fermentation are complex organic matrixes containing organic substrates from various origins and quality. Process studies on nitrogen (N) flows, source specific losses and N use efficiency (NUE) in a plant soil system require the use of ¹⁵N tracers. One option is the direct labelling of the whole matrix of the organic fertiliser, containing organic and inorganic N forms. However, this option is coupled with very high efforts and costs, e.g. feeding animals with labelled feed. Another option is to label only inorganic N-forms for fertilizers containing high proportions of those. This restricts observations on inorganic forms. A third option is an indirect approach by ¹⁵N enrichment of the soil and determination of N flows by dilution of previously labelled functional soil / plant pools, e.g. plant N or soil mineral N, etc., by an unlabelled fertiliser source. However, this option requires a more or less homogenous enrichment of the soil organic matter to avoid misinterpretations of isotope data. Those are caused by e.g. pool substitution of an unlabelled by a labelled source and thus results in an overestimation of e.g. N crop uptake from the applied fertiliser.

## MATERIAL AND METHODS

Here we compare the results from two ¹⁵N tracer studies with compost (Mayer et al. 2011), slurries and digested slurries (Hutter et al. 2017). i) In a four year pot experiment we examined the N uptake of crops and N flows through soil pools like microbial biomass and mineral N fractions. We used ¹⁵N labelled compost and compared it with isotope dilution of previously, over a one year period, ¹⁵N labelled soil; ii) In a one year field experiment we compared N uptake by maize from slurries and digested slurries. We labelled the NH₄-N fraction of the slurries with (¹⁵NH₄)₂SO₄ and compared the uptake from the NH₄-N fraction with the N-uptake determined by isotope dilution where we have labelled the field soil with ¹⁵N enriched clover-grass powder two months before slurry application (details see contribution of Hutter, M. et al. at this conference).

## RESULTS AND DISCUSSION

Homogeneous ¹⁵N labelling of a municipal waste compost worked very well by co-composting of ¹⁵N labelled ryegrass (data not shown). Both methods directly ¹⁵N labelled compost and isotope dilution showed similar results for N uptake from compost (Fig. 1), compost N immobilization in microbial biomass and compost N in the mineral N fraction during the whole 4 years period. However, the N recovery from compost determined by isotope dilution in soybean as third crop in the crop rotation caused negative compost N recoveries. N2-fixation by the legume as a second unlabelled N source lead to an apparent dilution of the labelled N pool and thus to misinterpretation of N uptake from compost (Fig. 1). In the field study the NUE of the NH4-N fraction in maize determined by ¹⁵N labelling was 34% for slurries and 45% for digested slurries. A simple difference calculation, using an unfertilised plot as control, revealed a NUE of 24% for slurries and 38% for digested slurries related to total N. Both methods showed the same pattern. However, the isotope dilution approach failed here. We got a complete different pattern and in single field plots NUE above 100%. We attributed this to an inadequate homogeneous labelling of the soil organic matter two months before slurry application (details and figures see contribution of Hutter, M. et al. at this conference).

<footnote n="1">¹ Department of Agroecology and Environment, Agroscope, Switzerland; ² School of Life Sciences and Facility Management, ZHAW, Switzerland;</footnote>
<figure><img src="image_73.png" /><figcaption>Figure 1. Recovery of applied compost N by crops with directly ¹⁵N labelled compost by ¹⁵N-ryegrass or (¹⁵NH₄)₂SO₄ or by ¹⁵N isotope dilution in a four years model crop rotation (pot experiment). Different letters indicate significant differences (*p*<0.05).</figcaption></figure>

## CONCLUSION

The comparison of the two studies at pot and field scale shows clearly the advantages of direct ¹⁵N labelled organic matrices compared to an isotope dilution approach. Direct ¹⁵N labelling by co-composting of labelled organic substrates worked well and can be done with low efforts. However, the production of homogeneously labelled organic fractions in manures is coupled with high efforts and costs, and it is almost impossible for mixed substrates e.g. manure digested with different co-substrates. So isotope dilution might be an option for those organic substrates, but requires further methodological development.

## REFERENCES

* Hutter M., Krebs R., Mayer J., 2017: Nitrogen use efficiency of raw and digested slurries: A study using different ¹⁵N methods. In: Wolfrum S. et al. (Eds.). Beiträge zur 14. Wissenschaftstagung Ökologischer Landbau. Freising-Weihenstephan. Verlag Dr. Köster, Berlin, pp. 314-317.

* Mayer, J.; Koeppe, P., Dubois, A., 2011: Turnover of compost nitrogen in an organic model crop rotation. A comparison of direct and indirect labelling ¹⁵N tracer methods. In: Leithold et al. (Eds.). 11. Wissenschaftstagung Ökologischer Landbau. Verlag Dr. Köster, Berlin, pp. 181-182.
# MODELLING C-N-P-K SOIL DYNAMICS IN A CONTEXT OF REPEATED COMPOSTS APPLICATIONS

REVALLIER, A.¹, ORVAIN, M.¹, BISINELLA DE FARIA, A. B.¹, NAVES-MASCHIETTO, G.¹, ALBUQUERQUE, M.¹, HOUOT, S.², HARTMAN, M.³, PARTON, B.³

¹ Veolia Recherche & Innovation, France; ² INRA Ecosys, France; ³ Colorado State University, United States of America

## INTRODUCTION

In a context of high environmental impact of fertilizer use and soil organic matter (OM) degradation, recycling nutrients and stabilizing soil OM through organic residues applications such as composts has become an essential objective of sustainable farming. However, efficient use of compost is still a challenge, due to high variability of OM mineralization that depends on its quality and on various soil and climate characteristics. Modelling and simulation of OM mineralization and its impacts on N, P and K dynamics play an important role when understanding nutrient interactions and optimizing compost spreading.

The Century model (Parton et al., 1987) describes the different OM pools dynamics in agricultural soils at monthly scale and considers pedo-climatic context and farming practices including residual organic matter additions. This study describes the modifications to Century and the validation of the results with a long-term field experiment in France.

The aim of this study is to modify, calibrate and validate Century model in order to correctly predict C, N, P and K in soil and differentiate between different compost spreading strategies for a French pedo-climatic context.

## MATERIAL AND METHODS

### Integration of ISMO index to Century model

Century describes the dynamics of soil organic matter and nutrient cycling between 3 different pools: active, slow and passive soil organic matter (SOM). These SOM pools are supplied by structural and metabolic C, N, P and S pools. In the first study (data not published), it was noted that the effects of different composts additions on soil organic matter mineralization was not precisely predicted. To be able to differentiate between the types of amendment used, the Organic Matter Stability Index (ISMO) (Lashermes et al., 2009) of composts was integrated to Century. Century uses the ISMO to divide organic matter into the structural carbon and the slow organic carbon pools. Between ISMO of 36% to 90%, the OM going into the slow organic carbon pool is linearly proportional to the value of ISMO. Consequently, the flow going into the structural pool decreases with the increase of ISMO. In addition, it is important to predict K due to its fertilization effect and its presence in organic amendments. Therefore, the dynamics of S, initially simulated by Century, have been adapted to describe K dynamics in soil, based on the SOM mineralization and C/K ratios to describe the fluxes between different pools.

### Model validation

To validate the modifications in the model, an experimental dataset provided by the long-term field experiment QualiAgro (INRA-Veolia partnership, http://www6.inra.fr/qualiagro) dedicated to compost application, was used. In the QualiAgro experiment, three types of composts and farm manure were applied every two years on a loamy soil cropped with corn and winter wheat from 1998 to 2013. Control plots (TEM) were cropped without organic amendments and half of the experimental sites were fertilized (EXPERIMENT_N) while the other part received no mineral fertilizer, leading to 10 different treatments which are replicated 4 times. Also, the ISMO value of organic amendments was measured along with soil characteristics including C, N, P and K stocks. Statistical analyses using linear regression were conducted to compare model predictions and measurements. Three different organic amendments (including municipal solid waste compost - OMR) and the control treatments were used to calibrate the model while a last treatment (compost of sludge and green waste - DVB) was used to validate the calibration.
## RESULTS AND DISCUSSION

The model predictions showed strong correlations with experimental soil total organic carbon (r²=0.91) and soil total organic nitrogen stock (r²=0.90) as shown in Figure 1 for TEM_N, OMR_N and DVB_N. Also, the modified version of Century distinguished precisely the scenarios with and without amendments as well as the type of compost regarding its stabilization level.

<figure><img src="image_74.png" /><figcaption>Figure 1. Total Soil Organic Matter Carbon (A) and Nitrogen (B). Comparison among Century results and QualiAgro data for TEM_N (control plot with mineral N fertilization), OMR_N (municipal solid waste compost with mineral N fertilization) and DVB_N (sludge and green waste compost with mineral N fertilization).</figcaption></figure>

Predictions of exchangeable P and K stocks in soil (data not shown) were also in accordance with the measurement values. However, more experimental data concerning total P and K are needed to improve the whole P and K dynamics in soil.

## CONCLUSION

The calibration and validation of the modified Century model implemented with ISMO and K showed encouraging results for the French organic amendment scenarios. As a next step, a sensitivity analysis and more powerful calibration tools will be used to decrease the uncertainty of Century prediction. Also, the use of different calibration and validation datasets will enhance the capability of the model to predict C, N, P and K soil dynamics in various French pedo-climatic and organic amendment contexts.

**Acknowledgements:** The authors acknowledge INRA Ecosys for providing QualiAgro experimental data.

## REFERENCES

* Parton, W. J., Schimel, D. S., Cole, C. V., & Ojima, D. S. (1987). Analysis of factors controlling soil organic matter levels in Great Plains grasslands. Soil Science Society of America Journal, 51(5), 1173-1179.

* Lashermes, G., Nicolardot, B., Parnaudeau, V., Thuriès, L., Chaussod, R., Guillotin, M. L., ... & Tricaud, A. (2009). Indicator of potential residual carbon in soils after exogenous organic matter application. European Journal of Soil Science, 60(2), 297-310.
# IMPACT OF THE UREASE INHIBITOR LIMUS® ON AGRONOMIC AND ENVIRONMENTAL PARAMETERS IN TEMPERATE GRASSLAND.

KROL, D.J.<fnref n="1" />, FORRESTAL, P.J.<fnref n="1" />, WALL, D.<fnref n="1" />, LANIGAN, G.J.<fnref n="1" />, SANZ-GOMEZ, J.², KNAUER, M.², FORD, I.³, KELLY, G.⁴, RICHARDS, K.G.<fnref n="1" />

## INTRODUCTION

Nitrogen (N) fertilisation is the cornerstone of agricultural production however it can also lead to losses of a potent greenhouse gas nitrous oxide (N₂O), air pollutant ammonia (NH₃), and nitrate (NO₃⁻) leaching to the environment. Novel urea-based fertilisers that incorporate urease inhibitors in their formulations aim to abate these losses while maintaining and enhancing yields. One example of urease inhibitor is Limus® developed by the BASF (Sanz-Gomez et al. 2017), which is a combination of the active ingredients N-(n-butyl)-thiophosphoric-triamide (NBPT) and N-(n-propyl)-thiophosphoric-triamide (NPPT). The aim of this work was to test the feasibility of urea treated with Limus® for reducing N₂O and NH₃ in a temperate grassland while maintaining or improving productivity.

## MATERIAL AND METHODS

Experimental work was conducted on a permanent grassland site in Johnstown Castle in Co. Wexford. Fertiliser treatments were: control, calcium ammonium nitrate (CAN), urea (U) and urea treated with Limus® (UL). The trial was a fully randomized block design with five blocks incorporating agronomy plots (10 m x 2 m), N₂O plots (0.4 m x 0.4 m) and ammonia plots (2.5 m x 2 m) (three blocks). Treatments were applied to agronomic and N₂O plots on the same days at a standard agronomic rate of 200 kg N ha⁻<fnref n="1" /> yr⁻<fnref n="1" /> in six split applications. Ammonia plots received fertiliser in July at a rate of 40 kg N ha⁻<fnref n="1" />. Dry matter yield was measured at every harvest, N₂O was measured regularly throughout the growing period using the static chamber technique (de Klein and Harvey, 2012) and NH₃ was measured for two weeks post-fertilisation using the wind tunnel technique (Lockyer, 1984). Gaseous loses (N₂O and NH₃) are presented as emission factors (EFs) which is a ratio of N loss to N fertilisation rate (%). Statistical analysis was performed using the proc MIXED procedure of SAS followed by the F-protected Least Significant Difference test to check the effect of fertiliser treatment on cumulative N₂O, NH₃ and grassland productivity.

## RESULTS AND DISCUSSION

### Nitrous oxide

Fertilisation led to large increases in N₂O emissions. The highest loss was observed from the CAN treatment representing EF of 0.74%. Emissions from urea-based fertilisers were not different from the control, whereas CAN emission was significantly higher (P<0.05) than the control and other fertilisers. Results indicate that urea treated with Limus® mitigated N₂O to levels not significantly different to that of control.

### Ammonia

Fertilisation resulted in large NH₃ losses with EF of up to 43.1%. There was a significant difference in NH₃ losses between different fertiliser formulations. Losses were largest from urea, however addition of the urease inhibitor with Limus® mitigated losses by 68% to levels not significantly different to these from CAN.

### Herbage production

There were differences between individual harvests, with first and second harvest returning low grass yields from all the treatments, while substantially larger yields were achieved during the third and fourth harvest. All fertilized

<footnote n="1">¹ Teagasc, Crops, Land Use and Environment, Johnstown Castle, Co. Wexford, Ireland; ² BASF SE, Agricultural Solutions, Functional Crop Care, Limburgerhof, Germany; ³ BASF plc, Crop Protection, Business Development, Cheadle, United Kingdom, ⁴ BASF Ireland Ltd., Crop Protection, Business Development, Cork, Ireland</footnote>
plots achieved significantly higher yields (P<0.05) compared with control unfertilized grassland, however there
was no statistically significant difference between all the urea-based fertilisers.

<figure><img src="image_75.png" /><figcaption>Figure 1 a-c. Losses of a) N₂O, b) NH₃ and c) dry matter yield in temperate grassland following N fertilisation with various fertiliser formulations. Different letters indicate statistical significant differences using Tukey-Kramer grouping for Least Square Means P<0.05.</figcaption></figure>

CONCLUSION

Outputs of this work clearly support the hypothesis that urea-based fertilisers with added urease inhibitors such as Limus® can help reconciling environmental and production targets of Irish agriculture by providing a win-win solution that not only lower environmental losses but simultaneously maintain production.

Acknowledgements: This research was financially supported by the Irish Research Council Enterprise Partnership Scheme Postdoctoral Fellowship (grant number EPSPD/2016/54) and BASF as industry partner.

REFERENCES

de Klein C.A.M., Harvey M., 2012. Nitrous oxide chamber methodology guidelines.
[https://globalresearchalliance.org/wp-content/uploads/2015/11/Chamber_Methodology_Guidelines_Final-V1.1-2015.pdf](https://globalresearchalliance.org/wp-content/uploads/2015/11/Chamber_Methodology_Guidelines_Final-V1.1-2015.pdf) (Retrieved 30.04.2018)

Lockyer D.R., 1984. A System for the Measurement in the Field of Losses of Ammonia through Volatilization.
Journal of the Science of Food and Agriculture, 35, 837-848.

Sanz-Gomez J., Knauer M., Pasda G., Wissemeier A., Staal M., Schneider K.H., Zerulla W., Schmid M., Meger H., Tarlazzi S., Munoz-Guerra L.M., Chiodini, M. E., Acutis M., Villar-Mir J.M., Muskolus A., 2017. Limus®: a novel combination of urease inhibitors reducing ammonia emissions from urea containing fertilizers and its performance concerning environmental and agronomic parameters, handling, transport and storage properties.
Poster presented at the conference Sustainable Solutions for Sustainable Management of Nitrogen, Aarhus, Denmark.
# GAS EMISSIONS DURING SOLID MANURE MANAGEMENT AT HOUSING AND STORAGE STAGES FROM DAIRY CATTLE IN CONTRASTED FEEDING AND CLIMATIC SITUATIONS

EDOUARD, N.<fnref n="1" />, ROBIN, P.², ALMEIDA, J.G.R.<fnref n="1" />,³, ALVES, T.P. <fnref n="1" />,³, LAMBERTON, P.<fnref n="1" />, LORINQUER, E.⁴

## INTRODUCTION

French dairy systems are characterized by a large proportion of deep litter systems. However, gas emission measurements from solid manure are very scarce in the literature and also very variable in relation with contrasted litter management (fresh straw addition frequency and amount, accumulation time, animal type and feeding...). In deep-litter systems, manure is mixed with bedding material and accumulated for a few weeks in a thick layer where the oxygen level decreases with depth. This can result in several processes such as aerobic degradation of organic matter, urea hydrolysis, nitrification-denitrification, nitrogen immobilization and anaerobic degradation of organic matter (Jeppsson, 1999). These complex interactions among microbial, biochemical and physical processes lead to highly variable emissions of ammonia as well as greenhouse gases (Webb et al., 2012). The objective of this study was to acquire new knowledge about N₂O and NH₃ emissions during accumulation of a straw-based deep litter at the dairy barn level and throughout the storage of the resulting solid manure. To consider different management practices, the experiment offered contrasting diets to the dairy cows (a grass-based GD and a maize silage-based diet MD) and was conducted at two seasons (autumn and spring) leading to variable grass quality and different climatic effects during storage. This lead to 4 treatments to be compared: GDaut, MDaut, GDspr and MDspr.

## MATERIAL AND METHODS

### Housing

At each season, two groups of three Holstein dairy cows in late (in autumn) or mid (in spring) lactation were housed in two closed and controlled mechanically ventilated rooms, and kept on a straw-based deep litter accumulated under the animals during four weeks. The MD diet consisted in an 80-20% mixture of maize silage and concentrate while GD was 100% grass. Individual milk yields and dry matter (DM) intake were recorded daily. NH₃ and N₂O concentrations were measured continuously with an infrared photo-acoustic gas analyzer (Innova model 1412). Ventilation rate was punctually assessed with the tracer ratio method (SF₆).

### Storage

After 4 weeks of accumulation in the barn, solid manure was put in pile under dynamic chamber systems and stored during 14 weeks. The MDaut and GDaut heaps were therefore monitored during winter while the MDspr and GDspr heaps were monitored during spring and summer. NH₃ and N₂O concentrations were measured with an infrared photo-acoustic gas analyzer (Innova model 1412) during the whole week following stacking and then 2 days a week (dynamic chambers uncovered the rest of the time). Ventilation rates were obtained from the fans. Leachates from manure heaps were continuously collected and analyzed for their composition.

## RESULTS AND DISCUSSION

### Housing

Ammonia emissions were slightly greater on GD compared to MD in autumn and were lower and quite close from each other in spring (Table 1). GDaut ammonia emissions were also observed to increase gradually over the course of manure accumulation. It appeared that NH₃ emissions were more related to variation of milk urea content than

<footnote n="1">¹ PEGASE, INRA, Agrocampus-Ouest, Rennes, France; ² SAS, Agrocampus-Ouest, INRA, Rennes, France; ³ Universidade do estado de Santa Catarina, UDESC Centro de Ciências Agroveterinárias, 88520-000 Lages SC, Brazil; ⁴ Institut de l'élevage, 149 rue de Bercy, Paris, France</footnote>
to CP content (15% for MD and 18% for GD at both season) or N intake itself (that was systematically higher in MD, because of higher DM intake). Milk urea content, good indicator of urinary urea N excretion (Burgos et al., 2007), is indeed the direct reflection of the unbalance degradable and metabolisable protein supplies of the grass, particularly important in the autumn grass. N₂O emissions were classically low at the house level and were higher on GD than on MD whatever the season. The solid manure was indeed more humid and compacted with GD, probably stimulating denitrification processes causing N₂O emissions.

## Storage

The peak of ammonia emission was reached the day after manure stacking; emissions then decreased down to zero 3 weeks after. As for housing, ammonia emissions were higher (even doubled) on GDaut than on MDaut in relation with a higher NH₄-N content of the manure at the beginning of the storage period. On the contrary, NH₃ emissions were higher on MD than on GD in spring-summer. We observed that the MDspr manure heap was warmer (up to 85°C in the core of the heap) than the GDspr pile (65°C) and probably also more porous (less humid) stimulating ammonia volatilization. The GDspr heap lost consequently more N in the form of N₂O.

<table><caption>Table 1. Cumulated nitrogen gas emissions over the solid manure accumulation in the house and during consecutive storage. MD: maize silage diet; GD: grass-based diet; aut: autumn-winter period; spr: spring-summer period</caption><thead><tr><th colspan="2">Cumulated gas emissions over the period</th><th>MDaut</th><th>GDaut</th><th>MDspr</th><th>GDspr</th></tr></thead><tbody><tr><td rowspan="2">Housing<br>(4weeks)</td><td>NH<sub>3</sub>-N, g/cow</td><td>406</td><td>468</td><td>354</td><td>321</td></tr><tr><td>N<sub>2</sub>O-N, g/cow</td><td>2.6</td><td>7.6</td><td>2.3</td><td>6.3</td></tr><tr><td rowspan="2">Storage<br>(14weeks)</td><td>NH<sub>3</sub>-N, g/cow</td><td>500</td><td>967</td><td>870</td><td>615</td></tr><tr><td>N<sub>2</sub>O-N, g/cow</td><td>32</td><td>34</td><td>33</td><td>53</td></tr></tbody></table>

## CONCLUSION

Considering housing and storage, nitrogen gas losses represented 6, 11, 8 and 7% of the system N input (N intake + N from the straw) for MDaut, GDaut, MDspr and GDspr respectively. Feeding animals with fresh grass in the house does not seem to be relevant in term of environmental impacts with straw-based deep litter systems, especially in the autumn when grass degradable N content is high. Storage of solid manure during warm season should also be avoided because of the temperature effect stimulating ammonia volatilization. To go further, it would be interesting to compare these results with emission during grazing, to find the best way to combine grass valorization and maize yields to preserve milk production and environment.

**Acknowledgements:** This work was supported by Ademe. We are also grateful to the INRA staff both at the dairy experimental farm and at the laboratory.

## REFERENCES

* Burgos, S.A., Fadel, J.G., DePeters, E.J., 2007. Prediction of ammonia emission from dairy cattle manure based on milk urea nitrogen: Relation of milk urea nitrogen to urine urea nitrogen excretion. J. Dairy Sci., 90, 5499-5508.

* Jeppsson, K.H., 1999. Volatilization of Ammonia in Deep-litter Systems with Different Bedding Materials for Young Cattle. J. Agri. Eng. Res. 73, 49-57.

* Webb, J., Sommer, S., Kupper, T., Groenestein, K., Hutchings, N.J., Eurich-Menden, B., Rodhe, L., Misselbrook, T.H., Amon, B., 2012. Emissions of ammonia, nitrous oxide and methane during the management of solid manures, in: Lichtfouse, E. (Ed.), Agroecology and strategies for climate change. Springer, pp. 67-107.
# PREDICTING C AND N FATE FROM MIXTURE OF SUGARCANE STRAW AND ORGANIC FERTILIZERS.
## MECHANISTIC APPROACH BY MODELING

KYULAVSKI, V. <fnref n="1" />, ⁴, ⁵, THURIÈS, L.<fnref n="1" />, RECOUS, S. ³, PAILLAT, J.-M.², GARNIER, P.⁴

## INTRODUCTION

Carbon (C) budget and nitrogen (N) mineralization in mulch cropping systems depend on both residue and fertilizer inputs. Mixing organic fertilizer – N and straw - C seems to lead to interactive relations, controlled by mineral N contents for OF (Aita et al. 2012, Giacomini et al. 2015) and N diffusion between microbial biomass and C sources (Garnier et al. 2008). However, predicting C and N fate when mixing different C and N sources is challenging, because it is necessary to better describe the mechanisms that drive the potential mineralization rates. The objective of our work was to study C and N mineralization from mixtures of plant residues and OF in soil, and to compare them with the mineralization of these OF applied alone.

## MATERIAL AND METHODS

### Acquisition of experimental data

An incubation experiment of soil samples (Nitisol from La Reunion) was conducted during 182 days at 28°C in a dark room (AFNOR, 2016). The C-CO₂ was measured at 14 dates and mineral N was measured at 9 dates. The treatments included organic materials with different physicochemical characteristics either incubated alone as pig slurry (PS), digested solid sewage sludge (DS) and sugarcane straw (S), or incubated as mixtures, namely pig slurry with sugarcane straw (PS-S) and digested solid sewage sludge with sugarcane straw (DS-S). The doses of organic or mineral inputs were calculated to provide non-limiting organic N for the mixtures, and non-limiting mineral N (KNO₃) for S treatment.

### Modelling strategy

CANTIS is a mechanistic model simulating C and N transformations in soils (Garnier et al. 2003). CANTIS-simulated curves were fitted with a single set of parameters to the experimental data obtained with S, PS and DS treatments. The same set of parameters was used to predict the C-CO₂, N-NO₃⁻ and N-NH₄⁺ kinetics from the mixtures (PS-S and DS-S). The difference between predicted and measured dynamics for the mixtures was considered as interactions. In CANTIS, the contact factor (K*MZ) is an empirical function that accounts for modifications of the rate of microbial colonization of C source and/or N source. Since N limitation was previously attributed to the contact area between soil and residues (Garnier et al. 2008, Iqbal et al. 2014), we calibrated K*MZ to account for the interactions. The predictions were evaluated using Nash-Sutcliffe model efficiency index (Ef).

## RESULTS AND DISCUSSION

Calibrating CANTIS model enabled a good prediction of all measured variables (CO₂, NO₃⁻ and NH₄⁺) for the treatments S, PS and DS and for the control soil, as all the Nash-Sutcliffe model efficiency indexes were positive. However, CANTIS model overestimated the CO₂ measured in both mixture treatments, PS-S and DS-S. This suggests a N limitation occurring when mixing different C and N sources, that CANTIS model does not consider using the parameters calibrated for a single organic source. Considerable improvement of the prediction of C and N kinetics was obtained by fixing K*MZ to 60 and 130, for PS-Scorr and DS-Scorr respectively, compared to PS-S and DS-S, respectively (fig. 1). The higher value of K*MZ for DS-S treatment, indicates that the N uptake was less efficient, compared to PS-S. This was probably due to the lower N diffusion and consequently, the lower N accessibility from

<footnote n="1">¹ CIRAD, UPR Recyclage et Risque, Saint-Denis de La Réunion, France, ² CIRAD, UPR Recyclage et Risque, Montpellier, France, ³ FARE laboratory, INRA, Université de Reims Champagne-Ardenne, Reims, France, ⁴ INRA-AgroParisTech, UMR1402 EcoSys, F-78850 Thiverval-Grignon, France, ⁵ ADEME, Angers, France.</footnote>
the sewage sludge. We hypothesized that the distance between N and C was responsible for the antagonistic interaction, that reduces C colonization by decomposers and leads to a lower CO₂ release, than in case of pure additivity ($K_{MZ} = 0$).

<figure><img src="image_76.png" /><figcaption>Figure 1: CANTIS-simulated (lines) and observed (dots, standard deviation) data for C and N mineralization kinetics during incubation of mixtures of organic materials in control soil with (PS-S) pig slurry and sugarcane straw (a, b), (PS-Scorr) pig slurry and sugarcane straw with modified contact factor $K_{MZ}$ (c, d), (DS-S) sewage sludge and straw (e, f) and (DS-Scorr) sewage sludge and straw with modified contact factor $K_{MZ}$ (g, h), and their corresponding Nash-Sutcliffe efficiency indices (Ef).</figcaption></figure>

## CONCLUSION

The transformations of C and N from different organic sources in mixture have been accurately simulated with CANTIS model, by including and optimizing a function that reflects the accessibility of N. Thus, it is necessary to better describe and integrate the chemical and physical variability that characterizes the organic fertilizers, which determines the rate of their accessibility.

## REFERENCES

* AFNOR, 2016. FD U 44-163 - Amendements organiques et supports de culture — Caractérisation de la matière organique par minéralisation potentielle du carbone et de l'azote. Soil improvers and growing media - Characterization of organic matter by potential mineralization.

* Aita, C., S. Recous, R. H. O. Cargnin, L. P. da Luz, and S. J. Giacomini. 2012. Impact on C and N dynamics of simultaneous application of pig slurry and wheat straw, as affected by their initial locations in soil. Biol. Fertil. Soils 48:633-642.

* Garnier, P., C. Cambier, M. Bousso, D. Masse, C. Chenu, and S. Recous. 2008. Modeling the influence of soil-plant residue contact on carbon mineralization: Comparison of a compartmental approach and a 3D spatial approach. Soil Biol. Biochem. 40:2754-2761.

* Giacomini, S. J., V. L. G. Simon, C. Aita, L. M. Bastos, D. A. Weiler, and M. Redin. 2015. Carbon and Nitrogen Mineralization in Soil Combining Sewage Sludge and Straw. Rev. Bras. Ciênc. Solo 39:1428-1435.

* Iqbal, A., P. Garnier, G. Lashermes, and S. Recous. 2014. A new equation to simulate the contact between soil and maize residues of different sizes during their decomposition. Biol. Fertil. Soils 50:645-655.
# QUALITY OF CARBON COMPOUNDS OF MAIZE ROOT AND SHOOT LITTER CONTROLS SHORT-TERM CO₂ AND N₂O EMISSIONS FROM AGRICULTURAL SOILS

RUMMEL, P.S.<fnref n="1" />, PFEIFFER, B.<fnref n="1" />,<fnref n="2" />, PAUSCH, J.<fnref n="3" />, DITTERT, K.<fnref n="1" />

## INTRODUCTION

Availability of easily biodegradable carbon (C) compounds is one of the main drivers of denitrification events in agricultural soils. Potential C sources are rhizodeposits, especially root exudates, and decaying plant and root biomass. Incorporation of plant residues into agricultural soils and its subsequent degradation increases microbial respiration and creates plant litter associated microsites with low O₂ concentrations. Together with the availability of nitrate (NO₃⁻) from residual fertilizers or mineralization, these microsites are becoming hotspots for denitrification. Studies investigating the effect of plant litter on nitrous oxide (N₂O) emissions mainly considered C/N ratio and total C input as key variables (Chen et al., 2013), which control decomposition of plant litter in long-term studies. For short-term responses, however, the quality of C and N compounds is an important driver of denitrification. Water-soluble and low-molecular weight compounds can be directly used in the microbial metabolism, leading to an immediate increase of CO₂ and N₂O fluxes. The composition of structural components further influences the microbial community in soil, with fungi being generally regarded as the main decomposers of plant materials rich in cellulose and lignin (Kögel-Knabner, 2002). In general, fungi are seen as major contributors to denitrification under aerobic and weakly anaerobic conditions, while bacterial denitrification predominates under strongly anaerobic conditions (Hayatsu et al., 2010). Thus, we hypothesize that quality of C compounds (i) is an important predictor for short-term N₂O emissions and (ii) affects microbial denitrifier community structures.

## MATERIAL AND METHODS

In our study, maize plants (Zea mays L.) were grown in a greenhouse for eight weeks, harvested and all roots were removed from soil by sieving and handpicking. Soil, fresh plant shoot and root biomass were used in a 22-day two-factorial laboratory incubation experiment with two N levels (N1 and N2) and three litter addition treatments (Control = no litter input, Root = 100 g root FM kg⁻<fnref n="1" /> dry soil, Root+Shoot = 100 g root FM + 100 g shoot FM kg⁻<fnref n="1" /> dry soil). The closed chamber technique was used to measure daily CO₂ and N₂O fluxes and, soil nitrate and water-soluble C org concentrations were analyzed in regular intervals. A subsample of maize shoot and root litter was analyzed for total and water extractable carbon and nitrogen content, and structural components. Characteristics of maize biomass are shown in table 1. Microbial communities were analyzed using large-scale metabarcoding.

## RESULTS AND DISCUSSION

Maize shoot litter has a higher relative hemicellulose content, lower lignin/N ratio, slightly higher C/N ratio, and higher water soluble C org concentration compared to maize root litter (table 1). Addition of maize litter increased daily CO₂ and N₂O emissions, cumulative emissions and the N₂O/CO₂ ratio compared to Control (figure 1). The effect was much higher with incorporation of Root+Shoot litter, even when higher C inputs were taken into account. Differences in soil NO₃⁻ concentration between N1 and N2 were very small, but significantly influenced N₂O emissions when water-soluble C org concentrations were high.

We anticipate that higher litter input with higher biodegradability led to stronger anaerobicity in the Root+Shoot treatment compared to Root and Control. Additionally, shrinking of soil incorporated shoot litter created larger soil pores and facilitated rapid escape of generated N₂O. Potentially, a higher share of N₂O was further reduced

<footnote n="1">¹ Section of Plant Nutrition and Crop Physiology, Department of Crop Science, Georg-August-Universität Göttingen, Göttingen, Germany;</footnote>

<footnote n="2">² Institute of Microbiology and Genetics, Dept. of Genomic and Applied Microbiology, Georg-August-Universität Göttingen, Göttingen, Germany;</footnote>

<footnote n="3">³ Institute of Agroecology, Faculty for Biology, Chemistry, and Earth Sciences, University of Bayreuth, Germany</footnote>
to N₂ in the Root treatment. Analyses of microbial community structures will give further insights. We expect
differences in bacterial and fungal species richness and diversity between the different litter treatments.

<figure><img src="image_77.png" /><figcaption>Figure 1. Daily N₂O fluxes in relation to daily CO₂ fluxes from soils during a 22-day incubation experiment with two N levels (N1, N2) after incorporation of maize root biomass (R), maize root + shoot biomass (R+S) and control (C) without biomass. Regressions calculated with combined N levels (n=184).</figcaption></figure>

<table><caption>Table 1. Chemical characteristics of maize root and shoot biomass used in the incubation experiment. Hemicellulose, cellulose and lignin are expressed relative to lignin content.</caption><thead><tr><th></th><th>Maize root</th><th>Maize shoot</th></tr></thead><tbody><tr><td>C/N ratio</td><td>17.01</td><td>23.22</td></tr><tr><td>Lignin/N ratio</td><td>2.82</td><td>1.44</td></tr><tr><td>Water extractable C<sub>org</sub> (% of total C)</td><td>11.6</td><td>23.39</td></tr><tr><td>Hemicellulose (relative content)</td><td>3.36</td><td>9.08</td></tr><tr><td>Cellulose (relative content)</td><td>3.18</td><td>11.5</td></tr><tr><td>Lignin (relative content)</td><td>1</td><td>1</td></tr></tbody></table>

CONCLUSION

Quality parameters, in particular the concentration of water-soluble C<sub>org</sub> and lignification, as well as total C input
were the main factors influencing N₂O losses from soil in this study.

Acknowledgements: This study was funded by the Deutsche Forschungsgemeinschaft through the research unit DFG-FOR 2337: Denitrification in Agricultural Soils: Integrated Control and Modelling at Various Scales (DASIM).

REFERENCES

Chen H., Li, X., Hu, F., Shi W., 2013. Soil nitrous oxide emissions following crop residue addition: a meta-analysis. Global Change Biol., 19, 2956-2964.

Hayatsu M., Tago K., Saito M., 2010. Various players in the nitrogen cycle: Diversity and functions of the microorganisms involved in nitrification and denitrification. J. Soil Sci. Plant Nutr., 54, 33-45.

Kögel-Knabner I., 2002. The macromolecular organic composition of plant and microbial residues as inputs to soil organic matter. Soil Biol. Biochem., 34, 139-162.
# NITRIFICATION INHIBITOR N-LOCK™ WITH OPTINYTE™ TECHNOLOGY – RESEARCH ON ENVIRONMENTAL AND AGRICULTURAL BENEFITS IN GRAIN CORN AND OILSEED RAPE

DZIKOWSKI, M.¹, PETERSON, M.², LOURDET, Y.³

¹ Dow AgroSciences, Germany; ² Dow AgroSciences, USA; ³ Dow AgroSciences, France

## INTRODUCTION

Nitrification inhibitors such as nitrapyrin improve retention of nitrogen in the root-zone, prevent nitrate leaching to the groundwater, and reduce greenhouse gas emissions (Wolt 2004). Nitrogen transformation processes are slowed enabling more nitrogen is available for the crops for longer period of time (www.ipni.net). This enables more nitrogen to be available later in the corn and oilseed rape growing season when options to fertilize are limited (www.nitrogenmaximizers.com). Dow AgroSciences tested N-Lock™ nitrogen stabilizer in corn and oilseed rape to determine the impact of inhibiting nitrification with N-Lock on the soil, environment and crop growth and yield.

## MATERIAL AND METHODS

Dow AgroSciences established a series of field trials between 2013 and 2017 across Europe to evaluate the impact of N-Lock on crop growth and yield. Trials were located in: France, Spain, Germany, Poland, Hungary and Italy. N-Lock was incorporated into the soil either mechanically or using precipitation/irrigation: 15mm within 10 days after N-Lock application. In oilseed rape N-Lock was applied in spring on established crop before vegetation regrowth and in corn N-Lock was applied before planting.

### Trial design

Plot-trials with randomized complete block design with 3 to 4 replicates to ensure reliable yield determination, independent on soil variation. The untreated reference (nitrogen applied without N-Lock) was compared with treated plots (nitrogen with N-Lock).

### Nitrogen Source

Depending on the location nitrogen was delivered either in the form of mineral or organic fertilizer. Dose rate of nitrogen varied depending on local practices and supplemented nitrogen already available in the soil and was in range from 100 to 200 kg N/Ha.

### Product formulation

N-Lock was used as a encapsulated formulation containing 200 g ai/L of nitrapyrin applied at 2,5 L/ha of formulated product which translate to a nitrapyrin rate of 500 g ai/ha. N-Lock was either mixed with liquid fertilizer such as UAN or applied separately from granular fertilizer with field sprayer.

### Crop

A total of 68 and 42 were conducted in corn and winter oilseed rape, respectively. Both crops require nitrogen throughout the growing season, especially during late season growth stages when fertilizing is not possible due to the crop size. In corn, N-Lock™ nitrogen stabilizer and fertilizers were applied in spring before planting and in oilseed rape N-Lock and fertilizer were applied in spring on established crop.

### Application and incorporation practice

Depending on the local practice and situation N-Lock was applied either with field sprayer or tank mixed with organic fertilizer. N-Lock application was made within 10 days before or after nitrogen application. N-Lock was
incorporated into the soil either mechanically or through precipitation/irrigation (15 mm water within 10 days after application).

## Measured factors

Depending on the location the following values were collected: chlorophyll-index in leaves; Nmin values in the soil during vegetation and after harvest; crop performance and yield; nitrogen losses through leaching and greenhouse gases emissions. The gases were collected in chambers and then concentration measured using gas-chromatograph equipment.

## RESULTS AND DISCUSSION

Data collected from trials across Europe showed that N-Lock influenced chlorophyll index in leaves, crop grain yield (Table 1), nitrogen retention in root zone and nitrate leaching to the groundwater.

<table><caption>Table 1. Impact of N-Lock application on yield increase in corn and winter oilseed rape grain with number of observations (n)</caption><thead><tr><th>Crop</th><th>n</th><th>Yield untreated (t/ha)</th><th>Yield treated with N-Lock (t/ha)</th><th>Yield increase (%)</th></tr></thead><tbody><tr><td>Grain corn</td><td>68</td><td>10,27</td><td>10.83</td><td>7,1</td></tr><tr><td>Winter oilseed rape</td><td>42</td><td>3.92</td><td>4.05</td><td>4.2</td></tr></tbody></table>

## CONCLUSION

Based on large number of trials it can be concluded that the application of N-Lock at 2,5 l/ha (nitrapyrin at 500 gai/ha) impacts following factors: (1) increases chlorophyll index in leaves, (2) increase yield of grain corn and winter oilseed rape, (3) nitrogen stays longer in the root zone available for the crops, (4) N-min values in the soil are higher and more stable, (5) nitrate leaching to the groundwater is decreased and (6) greenhouse gases emissions were reduced.

™ Trademark of The Dow Chemical Company (“Dow”) or an affiliated company of Dow.

## REFERENCES

* Wolt J., 2004. A meta-evaluation of nitrapyrin agronomic and environmental effectiveness with emphasis on corn production in the Midwestern USA, Nutrient Cycling in Agroecosystems 69: 23-41.

* International Plant Nutrition Institute: Nutrient Source Specific No. 26:

http://www.ipni.net/publication/nss.nsf/0/21B8084A341C98E085257E3C0077595B/$FILE/NSS-26%20Nitrification%20Inhibitors.pdf

https://www.nitrogenmaximizers.com/maximizemanure/?utm_source=maximize_manure&utm_medium=redir-ect&utm_campaign=Vanity%20URL
# MAINTAINING SOIL NITROGEN AND CARBON STOCKS IN LONG-TERM GRASSLAND EXPERIMENTS IN NORWAY

STURITE I., OPSTAD S.

Norwegian Institute of Bioeconomy, Norway

## INTRODUCTION

More than 90 % of crops grown on Norwegian soils are turned into food through animal production systems, making perennial forage production one of the main pillars of Norwegian food production. To maintain high productivity, grasslands are subjected to different management practises such as frequently renovation by ploughing and reseeding together with the addition of inorganic or organic fertiliser. However, in Norway, a significant amount of swards are more than 10 years old. The choice of management practice can influence soils' ability to store and cycle carbon (C) and nitrogen (N) (Bellamy et al. 2005; Heyburn et al. 2017). The objective of presented study was to assess whether age of grassland and fertilisation practises affect C and N content in soil.

## MATERIAL AND METHODS

In Norway, one experimental site has been maintained since 1968 (Særheim Research Station in southwest (SW) Norway (58°47′N 5°41′E) and the second experimental site since 1974 (SW Norway at Fureneset Research Station (61°18′N 5°4′E)). These are the oldest, ongoing fertilisation experiments on grassland in Norway that include long-term/permanent (no-tillage almost 20 and 40 years) next to short-term leys reseeded every 3rd and 6th year. Both sites have a costal climate with mild winters and rainy summers. Soil at both sites is a sandy loam of moraine origin. The grass seed mixture (timothy, meadow fescue and smooth grass) was used when establishing both the permanent and reseeded 6- years swards while pure perennial ryegrass is used in 3-years sward. Since 1992 two levels of N have been applied during the growing season either in form of mineral N or as the cattle slurry (OF) in combination with mineral fertiliser (MF). Annually, permanent and 6-years old swards received 185 or 260 kg ha⁻¹ of N at Fureneset and 190 or 270 kg ha⁻¹ of N at Særheim. Corresponding values of N inputs in 3-years old swards were 245 and 295 kg ha⁻¹ at Fureneset and 250 and 330 kg ha⁻¹ at Særheim. The plant biomass of long-term and 6-years old swards were harvested two times per year and the biomass of 3-years old swards were harvested three times during the growing season. Herbage yields were determined on each cut. The experiments were arranged in a strip-split-block design. Soil samples were collected from all treatments in the end of the growing season in 2009 using a 2.5 cm soil corer to a depth of 0-5 cm, 5-20 cm and 20-40 cm. The samples were analysed for total C and N (g/100g dry matter) content. The relation between C and N content in soil horizons of different age grasslands and fertilisation practises was tested statistically by linear regression.

## RESULTS AND DISCUSSION

The total soil N content measured in different soil depth was a highly linearly correlated with the total soil C content at the corresponding soil depth regardless of sward age and fertilisation practise (Table 1 and Fig.1 A, B). Heyburn et al (2017) also found significantly positively relation between soil C stocks and soil N content in 22-years old grasslands. At both experimental locations, the content of soil N and C was significantly higher at the depth of 0-5 cm than at the depth of 20-40 cm (P< 0.0001). Only at Fureneset (Fig.1 A) the both long-term grassland treatments had significantly larger soil N and C content in upper soil horizon than frequently ploughed and reseeded grasslands. Despite the same soil type, plant botanical composition and management practices at both sites, the N and C content in soil tended to be higher at Fureneset (Fg.1 A) than at Særheim (Fig.1 B). Application method of nutrients and fertiliser level had no influence on N and C stocks over the entire 17 years period.
<table><caption>Table 1. Mean total soil carbon and nitrogen content (g 100 g DM⁻¹) in the different soil depths of long-term and short-term grasslands at Særheim and Fureneset in 2009.</caption><thead><tr><th rowspan="3">TREATMENT</th><th colspan="6">SÆRHEIM</th><th colspan="6">FURENESET</th></tr><tr><th colspan="3">TOT C</th><th colspan="3">TOT N</th><th colspan="3">TOT C</th><th colspan="3">TOT N</th></tr><tr><th>0-5</th><th>5-20</th><th>20-40</th><th>0-5</th><th>5-20</th><th>20-40</th><th>0-5</th><th>5-20</th><th>20-40</th><th>0-5</th><th>5-20</th><th>20-40</th></tr></thead><tbody><tr><td>SOIL DEPTH, CM</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>40-YEARS SWARD</td><td>6.6</td><td>4.8</td><td>2.6</td><td>0.46</td><td>0.27</td><td>0.14</td><td>11.7</td><td>9.6</td><td>5.2</td><td>0.64</td><td>0.54</td><td>0.29</td></tr><tr><td>20-YEARS SWARD</td><td>5.8</td><td>4.3</td><td>2.5</td><td>0.30</td><td>0.25</td><td>0.15</td><td>10.5</td><td>8.5</td><td>5.5</td><td>0.59</td><td>0.45</td><td>0.26</td></tr><tr><td>6-YEARS SWARD</td><td>5.1</td><td>4.9</td><td>3.0</td><td>0.30</td><td>0.28</td><td>0.17</td><td>8.6</td><td>7.8</td><td>4.1</td><td>0.47</td><td>0.40</td><td>0.21</td></tr><tr><td>3-YEARS SWARD</td><td>5.2</td><td>4.6</td><td>3.1</td><td>0.29</td><td>0.27</td><td>0.16</td><td>8.4</td><td>7.8</td><td>4.7</td><td>0.45</td><td>0.42</td><td>0.23</td></tr></tbody></table>

<figure><img src="image_78.png" /></figure>

<figure><img src="image_79.png" /><figcaption>Figure 1. Relationship between total soil N and total soil C in long- and short-term grasslands at Fureneset (A) and at Særheim (B). Mean of each fertiliser type and each fertiliser level.</figcaption></figure>

## CONCLUSION

A highly significantly linear relationship was found between N and C content in soils of long- and short-term grasslands, suggesting that C and N biogeochemical cycles are influenced from each other. In one of the two experimental sites almost 20 and 40 years old grasslands stored significantly more N and C in upper soil horizon (0-5 cm) than reseeded grasslands every 3rd and 6th year. Regardless of grassland age, no differences were found between the nutrient application levels and the methods used on the N content in any of soil horizons.

## REFERENCES

* Bellamy P.H., Loveland P.J., Bradley R.I., Lark R.M., Kirk G.J., 2005. Carbon losses from all soils across England and Wales 1978-2003. Nature, 437: 245-248.

* Heyburn J., McKenzie P., Crawley M.J., Fornara D.A., 2017. Effects of grassland management on plant C:N:P stoichiometry: implications for soil element cycling and storage. Ecosphere, 8 (10): 1-14.