# MONITORING RNA INDUCTION TO EVALUATE NITROGEN ABSORPTION AND ASSIMILATION FOLLOWING BIOSTIMULANT APPLICATION ON WHEAT (TRITICUM AESTIVUM L.)

KREMER, L.<fnref n="1" />, BELVAL, L.², BESSON, M.³, MEYER, L.<fnref n="1" />, HAAS, J.<fnref n="1" />, BENBRAHIM, M.<fnref n="1" />

## INTRODUCTION

Nitrogen use efficiency (NUE) is an important parameter for agriculture. Recently, new fertilizer additives called biostimulant were proposed by the industry and claimed to have different effects on growth and particularly a positive effect on NUE. The main objective of this study is the use of specific RNAs as indicators for NUE. The method, developed on wheat, is used to evaluate the effects of commercial products on nitrogen absorption and assimilation by measurements of gene expression changes. This includes seven genes in wheat.

## MATERIAL AND METHODS

### Plant material and growing conditions

Six days old emerged seedlings (20°C, darkness) of spring wheat (Triticum aestivum L. var. Lennox) were carefully clamped in individual neoprene foam floaters and maintained for 2 days in tap water (20°C with day/night cycles) before relocation to an hydroponic growth system. One unit of the hydroponic system consisted of a 5 liters plastic tank with a lid where 6 floaters (replicates) were inserted at the surface of the nutrient solution. Hoagland nutrition solution (Hoagland & Arnon, 1950) was used at ¼ dilution to apply sub-optimal nutrient conditions. A bubbling air pump ensured adequate root oxygenation in the solution (15 minutes / 1.5 hour). Hydroponic systems were positioned in a glasshouse and growth continued for 4 weeks (in semi-controlled conditions), renewal of nutrient solution occurred every 2 weeks.

### Modalities

4 modalities were compared (1 hydroponic system unit per modality): (1) negative control without any treatment, (2) positive control including a nitrate induction, (3) TL treated modality and (4) TT treated modality; TL and TT being two amino acid-based biostimulant products applied at 3.5 L/1000 L nutrient solution. For the positive control undergoing nitrate induction, the 6 plants were transferred in beakers containing a potassium nitrate solution (10 mM) during 4 hours prior the harvest.

### Roots sampling

At harvest, plants were removed from the floaters, dried on absorbent paper and the root tips were immediately collected and immersed in liquid nitrogen. Then, about 100 mg of root tips were grinded to a fine powder using liquid nitrogen, mortar and pestle and stored at -80°C until the next step.

### RNA extraction, reverse transcription and quantitative real-time PCR

Total RNAs samples were purified using RNeasy Plant Mini Kit (Bio-Rad), according to the manufacturer's instructions. Quantity and quality of the RNAs samples were checked measuring absorbance at 260 nm and 280 nm (Nanodrop One - Ozyme) and by electrophoresis in a 1% agarose gel. A concentration step using 3 M sodium acetate (pH 5.5) was sometimes necessary. **Reverse transcription was performed** with iScript™ Reverse Transcription SuperMix for RT-qPCR (Bio-Rad) in a MyCyler thermal cycler (Bio-Rad) using 1 µg of total RNA from each root sample, according the manufacturer's instructions. A reverse transcription negative control (without reverse transcriptase) and a non-template negative control (with reverse transcriptase) were included, and the absence of genomic DNA was verified through end-point PCR assays, and during qRT-PCR experiments.

<footnote n="1">¹ RITTMO agroenvironnement, France; ² Université de Haute Alsace, France; ³ Université de Perpignan Via Domitia, France</footnote>
Primer pairs have been designed (and tested for specificity and efficiency in parallel to published primers) to analyse the relative accumulation of transcripts of several genes involved in nitrogen assimilation: nitrate transporters (NRT1.1, NRT1.2, NRT2.1, NRT2.2) and nitrogen assimilation enzymes (nitrate reductase (NR), glutamine synthetase (GS) & glutamine oxoglutarate aminotransferase (GOGAT). Real-time PCR was performed using iQ SYBR Green Supermix (BIO-RAD) for each target and in triplicate for each RNA sample. Results obtained by the 2<sup>-ΔΔCt</sup> method (Livak & Schmittgen, 2001) provided the relative accumulation of transcripts as compared to housekeeping genes (GAPDH & EF1α were used for nitrate transporters amplification; EF1α and Ta.14126.1.S1_at (Long et al., 2010) were used for enzymatic genes amplification). Results were expressed relative to the negative control (untreated) modality.

## RESULTS AND DISCUSSION

The nitrate-induced modality constituted the positive control modality. The figure 1 clearly shows that nitrate induction increased RNA accumulation of NRT2.1 and NRT2.2 by a factor of 6, compared to the negative control. One can suppose that the induction of NRT2 (high affinity nitrate transporters) is linked to the delay between induction and harvest and that a subsequent raise could be observed in later enzymes like NR or GS/GOGAT.

<figure><img src="image_101.png" /><figcaption>Figure 1. Effect of induction on the relative accumulation of transcripts in positive control modality (average of 5 tests)</figcaption></figure>

Regarding nitrate transporters, the amino acid-based biostimulant products slightly modified NRT1.1 & 1.2, but had no effect on NRT2.1 indeed even a repression on gene NRT2.2 (see Table 1.).

<table><caption>Table 1. Profile of gene expression changes (values represent fold change (Log2) in transcript copy number relative to the negative control; bold indicate values that exceed a 3 fold difference in terms of RNA copies compared to negative control).</caption><thead><tr><th>Target gene</th><th>NRT 1.1</th><th>NRT 1.2</th><th>NRT 2.1</th><th>NRT 2.2</th></tr></thead><tbody><tr><td>Positive control</td><td><strong>0,3</strong></td><td><strong>-1,6</strong></td><td><strong>5,8</strong></td><td><strong>5,5</strong></td></tr><tr><td>TL biostimulant</td><td><strong>1,8</strong></td><td><strong>-0,6</strong></td><td><strong>-0,3</strong></td><td><strong>-1,7</strong></td></tr><tr><td>TT biostimulant</td><td><strong>2,1</strong></td><td><strong>1,5</strong></td><td><strong>-0,7</strong></td><td><strong>-1,9</strong></td></tr></tbody></table>

## CONCLUSION

The positive control results confirm that gene transcripts could be used to characterize the induced mechanisms of nitrogen assimilation. At the moment, the method allows to monitor 7 genes of wheat, but the compilation of data on other genes (including ammonium transport) is still ongoing, to achieve a complete overview of the different steps from the N cycle.

## REFERENCES

Hoagland D.R. and Arnon D.I. 1950. The Water-Culture Method for Growing Plants without Soil. California Agricultural
Experiment Station, Circular-347.

Livak K.J. and Schmittgen T.D. 2001. Analysis of Relative Gene Expression Data Using Real-Time Quantitative PCR and the 2^ΔΔCt^ Method. METHODS 25, 402–408

Long X.Y., Wang J.-R., Ouellet T., Rocheleau H., Wie Y.-M., Pu Z.-E., Jiang Q.-T., Lan X-J. and Zheng Y.-L. 2010. Genome-wide identification and evaluation of novel internal control genes for Q-PCR based transcript normalization in wheat. Plant Mol Biol 74:307-311
# EFFECTS OF A NATURAL NITROGEN-NUTRITIONAL AGENT ON WINTER WHEAT (TRITICUM AESTIVUM)

BRAS, P.Y., LEVIVIER, S. KLARZYNSKI, O.

1R&D Department, Bio3G, 7 rue du Bourg Neuf, 22 230 Merdrignac, FRANCE

## INTRODUCTION

Nitrogen (N) is an essential nutrient used in agricultural fields and, as a consequence, a large amounts of N fertilizers are used throughout the world. The efficiency of N fertilizers by crops in arable lands is relatively low, ranging from 25% to 50% of the applied N (Chien et al., 2016; Dobermann et al., 2003). Several methods are used to manage its efficiency in order to reduce nitrogen losses (Sharma et al., 2017). The majority of them are based on technical tools and agronomic knowledge (calculations and estimates) and only a few works target the use of natural substances and biostimulants to improve N fertilization. The R&D Bio3g team has developed a foliar biostimulant (seaweed-extracts and glutamic acid) in order to improve the nitrogen uptake and its efficiency, with a focus on cereals. Multiple experiments were conducted on various scales. The project was initiated under controlled conditions, in experimental greenhouse, with some trials under different fertilization regimes. Afterwards, transcriptomic analyses were carried out to understand the mode of action of the product. Lastly, in the field, the integration of this new solution into crop management techniques has been tested.

## MATERIAL AND METHODS

### Greenhouse trials

In 2012, a test was conducted under controlled conditions on soft winter wheat at the National Institute for Agricultural Research (INRA Rennes, France). 3 doses of the biostimulant (X; 5X; 10X) and a untreated control were compared. 3 sprays were carried out during nitrogen fertilization inputs (tillering [2-3]; pseudo-stem erection [4-5]; inflorescence emergence [10]). Nitrogen-limiting fertilization was tested (70% of the original needs). Statistical analysis details: Anova, $\alpha$ = 5%, post-hoc test = Newman-Keuls.

### Transcriptomic analyses

Seedlings of *A. thaliana* are grown in a climate chamber (day = 22 °C; night = 19 °C; photoperiod = 16 h). The product is sprayed with water (dose X; dilution factor = 100). 5 plants are used by modality (product and referent). Leaves are taken at 48 h after treatment and directly placed in RNAiater Stabilization Reagent. The tissues and total RNA are extracted with Tissue Lyser (Qiagen) and "RNeasy Protect Mini Kit + DNase 1 treatment" respectively. In vitro transcription with T7 polymerase precede retrotranscription step with dCTP-Cy3 or Cy5 and purification and quantification of the embedded fluorochromes. Hybridization (30 pmoles per sample/ AGILENT blade) was performed at 42 ° O/N in the presence of formamide.

### Field experiments

Between 2012 and 2013, 4 trials in real agricultural conditions were performed on winter wheat in western France (Bretagne and Nouvelle-Aquitaine). Experiments were carried out in microplots of 25 m². 3 stages of implementation in line with nitrogen fertilization inputs (tillering [2-3]; pseudo-stem erection [4-5]; inflorescence emergence [10]) have been studied. 3 conditions were explored (0.1X; X; referent). On each experimental site, each microplot received the same nitrogen fertilization, based on the objective of the crop yield and soil supplies (physicochemical analysis). Statistical analysis details: Anova, $\alpha$ = 5%, post-hoc test = Newman-Keuls.

## RESULTS AND DISCUSSION

### Greenhouse trials
In Nitrogen-limiting fertilization, grain yield has been improved with the 3 concentrations used (results statistically significant). However, the amount of straw was amplified solely at dose X (results not shown here, statistical significance). These results allowed us to identify the more efficient dose of the product.

<table><caption>Table 1. Average efficiency as a percentage of the Referent Datas on grey background show measured values whereas datas on white background are relative to the reference on a 100-basis.</caption><thead><tr><td>Mod</td><td>amount of straw (g/plant)</td><td>Dry grain yield (q ha-1)</td></tr></thead><tbody><tr><td>REF</td><td>18.4 b</td><td>9.5 b</td></tr><tr><td>X</td><td>122.3 a</td><td>114.8 a</td></tr><tr><td>5X</td><td>100.5 b</td><td>119.8 a</td></tr><tr><td>10X</td><td>93.4 b</td><td>115.4 a</td></tr></tbody></table>

## Transcriptomic analyses

The effect of the biostimulant on genes is large. 509 genes are induced and 234 genes are inhibited. Many genes of interest in nitrogen metabolism are overexpressed like ATNRT2.6 (Arabidopsis thaliana high affinity nitrate transporter 2.6: IF = 4.12) or ATGSTU10 (Arabidopsis thaliana Glutathione S-transferase (class tau) 10: IF = 2.82). As such, this innovative solution can be considered as a stimulator of nitrogen metabolism.

## Field experiments

These results obtained in the fields show that this biostimulant improves the yield of crops from 8% to 14%. The best gain is achieved with dose X (+11 q ha⁻¹). Differences are statistically significant in 3 out of 4 sites (Anova, α = 5%, post-hoc test = Newman-Keuls). This quantitative benefit also tends to enhance grain quality (protein and TKW), these results being statistically significant only in one trial.

<table><caption>Table 2. Average efficiency as a percentage of the Referent Datas on grey background show measured values whereas datas on white background are relative to the reference on a 100-basis. Results in bold were statistically significant in 3 out of 4 sites.</caption><thead><tr><th>Trial</th><th>Mod</th><th>Dry grain yield (q ha<sup>-1</sup>)</th><th>Protein (% dry)</th><th>1000-kernel-weight (g)</th><th>Specific weight (kg hL<sup>-1</sup>)</th></tr></thead><tbody><tr><td rowspan="3">4 trails average 2012-2013 (min - max)</td><td>REF</td><td>80.9 (69.4 - 86.4)</td><td>10.1 (8.9 - 11.6)</td><td>48.8 (44.8 - 56.4)</td><td>76.2 (73.9 - 80.0)</td></tr><tr><td>0.1X</td><td><strong>108</strong> (105 - 110)</td><td>102 (101 - 105)</td><td>102 (97 - 104)</td><td>102 (101 - 102)</td></tr><tr><td>X</td><td>114 (101 - 129)</td><td>102 (96 - 109)</td><td>102 (97 - 104)</td><td>100 (99 - 101)</td></tr></tbody></table>

## CONCLUSION

This serie of experiments clearly demonstrated the effect of this new solution. The dose X improves the nitrogen effect in wheat. The effect acts on the quantitative yield without diminishing the quality of the grain harvested. This biostimulant performs a positive role in the nutrient use efficiency (NUE) on winter wheat. In 2016, this biostimulant was registered in France an commercialized under the name ALTERNAZOTE.

## REFERENCES

Chien S.H., Teixeira L.A., Cantarella H., Rehm G.W., Grant C.A., Gearhart M.M., 2016. Agronomic effectiveness of
granular nitrogen/phosphorus fertilizers containing elemental sulfur with and without ammonium sulfate. A
Review. Agron. J. , 108, 1203.

Dobermann A., Ping J.L., Adamchuk V.I., Simbahan G.C., Ferguson R.B., 2003. Classification of Crop Yield Variability in Irrigated Production Fields. Agron. J. 95, 1105.

Sharma L.K., Bali S.K., 2017. A Review of Methods to Improve Nitrogen Use Efficiency in Agriculture. Mdpi journal. Sustainability, 10(1), 51.
# EFFECTS OF ORGANIC WASTE APPLICATION ON N₂O EMISSIONS AND N LEACHING IN SUGARCANE PLANTATION SOILS IN REUNION ISLAND

POULTNEY, D.M¹, VERSINI, A.¹, THURIES, L.¹

¹ CIRAD, UPR Recyclage et risque, 97743 Saint-Denis, La Réunion, France

## INTRODUCTION

Reunion Island is a densely populated Overseas Territory of France in the Indian Ocean. There is an increasing need for waste management, given the rising population density and the associated waste production increase. This waste can take the form of human waste (sewage sludge) and livestock waste (animal manure). The primary means of valorizing this waste would be as organic fertiliser in agroecosystems. Sugarcane is the most abundant crop on the island, spanning 58 % of the 43 000 hectares allocated as agricultural territory, across 9272 farms (Ageste DAAF, 2015).

N is an essential nutrient for crop growth and development, and is frequently a limiting factor in sugarcane agroecosystems. Despite the clear benefits of N fertilisers in contributing to adequate crop nutrition, excessive amounts accumulated in terrestrial and aquatic ecosystems can lead to a significant impact on environmental quality, ecosystems, biodiversity and human health (Dobermann, 2005). Environmental impacts linked to the N cycle include the loss of N to the atmosphere in the form of nitrous oxide (N₂O) during the process of denitrification. N₂O is a major greenhouse gas contributing to global warming, and agricultural soils are the most significant anthropogenic sources of N₂O (Allen et al., 2010). Excess N is also lost from soils via leaching mainly in the form of nitrates. Agricultural fertilisers are major contributors to increased concentrations of N in groundwater (Ghiberto et al., 2009). Eutrophication occurs when an excess of leached N reaches fresh water, which has negative effects on marine and freshwater ecosystems, and can render the water unsuitable for human consumption.

This study, which is the research project of a Doctor of Philosophy degree, is currently in its first year of implementation. It investigates the impact of recycling agricultural organic residue on the biogeochemical cycle of nitrogen in Reunion Island. The study is conducted on a SOERE-PRO site, which is a network of long-term field experimental sites, where the objective is to observe the effects of agricultural organic waste application on the different compartments of crops. The agricultural organic waste fertilisers are sewage sludge, pig manure and poultry manure. The mineral fertiliser used is urea, which is the standard fertiliser used on sugarcane farms in Reunion.

The primary objective of this study is to determine the environmental impact of organic fertiliser, as compared to mineral fertilisation. More specifically, N₂O emissions and NO₃⁻ leaching will be assessed.

## MATERIAL AND METHODS

The SOERE-PRO network in Reunion Island is closely situated to the island's capital, Saint-Denis (Lat 20°54'12.2"S, 55°31'46.6"E). The site is characterized by a tropical climate with an average annual temperature of 25°C and annual precipitation of 1650 mm. The trial was planted in March 2014 from viable buds of the R579 sugarcane variety placed with 1.5 m spacing between rows. The trial consists of 6 plots, each with a different fertiliser treatment, which is repeated in 5 blocks, with each plot made up of 6 sugarcane rows of 28 m, constituting a total plot area of 250 m².

N leaching in the soil is studied using a mixed system, consisting of porous cups under tension at depths of 10 and 40 cm; and lysimetric plates at a depth of 1 m. The vertical dynamic of DON, NH₄ and NO₃ in solution is studied in the different treatments. Finally, a mass balance of the loss of N by drainage flux at a depth of 1 m will be established with the aid of a computational model simulating hydric flux.
The annual flux of N₂O is estimated for the different treatments using 12 automatic chambers linked to a gas analyser. These semi-continuous measures allow the temporal variability of N₂O emissions to be studied, in the original context of organic waste application in tropical conditions.

## RESULTS AND DISCUSSION

The amount of N found at different soil depths (10 cm, 40 cm and 100 cm) are presented for the month of fertilizer application and the first three months following application (Figure 1). The proportion of N derived from fertiliser was also calculated for the three respective depths over the first three months. For the soil depths of 10 cm, 40 cm and 100 cm, the proportion of N derived from urea fertilisation was 5.2 %, 3.4 % and 0.5 %; the proportion of N derived from sewage sludge fertilisation was 11.7 %, 5.3 % and 0.8 %; and the proportion of N derived from pig manure fertilisation was 31.7 %, 14.4 % and 0.4 % respectively.

<figure><img src="image_102.png" /><figcaption>Figure 1. Nitrogen amount for the different fertiliser treatments (urea, sewage sludge, pig manure, no fertiliser) at sampling times t0, t1, t2, t3 at depths of 10 cm, 40 cm and 100 cm.</figcaption></figure>

There is a large increase in the quantity of N found in pig manure after the first month in the 10 cm and 40 cm soil depths, but this does not reach the 100 cm depth. The N amount in the other treatments remains relatively stable over the first month at depths of 10 cm and 40 cm. There is an overall decrease in N across treatments in the second month reaching a quantity of 0 g.m⁻² three months after fertilisation. N does not reach the 100 cm soil depth, showing that there is minimal loss of N by deep drainage during the first three months following fertilisation.

## REFERENCES

* Allen, D. E., Kingston, G., Rennenberg, H., Dalal, R. C., & Schmidt, S. (2010). Effect of nitrogen fertilizer management and waterlogging on nitrous oxide emission from subtropical sugarcane soils. Agriculture, Ecosystems & Environment, 136(3-4), 209-217.

* Agreste DAAF La Réunion, 2015. Enquête sur la structure des exploitations agricoles en 2013. Ministère de l'Agriculture, de l'Agroalimentaire et de la Forêt – Service de la Statistique et de la Prospective. Agreste Analyses n°95.

* Dobermann, A.R., 2005. Nitrogen Use Efficiency – State of the Art. IFA International Workshop on Enhanced-Efficiency Fertilisers, Frankfurt, Germany, 28-30.

* Ghiberto, P. J., Libardi, P. L., Brito, A. S., & Trivelin, P. C. O. (2009). Leaching of nutrients from a sugarcane crop growing on an Ultisol in Brazil. Agricultural Water Management, 96(10), 1443-1448.
N₂O MITIGATION POTENTIAL OF N-STABILIZERS APPLIED WITH UREA TO WINTER OILSEED RAPE

THIEL, E., SPOTT, O., KREUTER, T., LIETSCH, A., SCHUSTER, C.

SKW Stickstoffwerke Piesteritz GmbH, Department Research and Development, Möllensdorfer Strasse 13,
06886 Wittenberg, Germany

INTRODUCTION

Winter oilseed rape is the most important oil crop cultivated in Europe. Production related N₂O emissions are increasingly coming to the fore in the course of biofuel production and European emission reduction goals. Most recent estimates revealed a mean N₂O loss of 0.6% fertilizer-N (Ruser et al., 2017) and hence, below the current IPCC factor of 1.0% (De Klein et al., 2006). An application of a nitrification inhibitor (NI) along with urea and/or ammonium-based fertilizers was reported to additionally decrease N₂O emissions by ≈35% on average (Ruser et al., 2015). However, winter oilseed rape is in particular characterized by large amounts of N-rich crop residues und thus, relevant N₂O emissions not only occur soon after fertilization (directly based on applied mineral N), but also later on during maturity, harvest and afterwards based on their N-rich crop residues (Walter et al., 2015; Ruser et al., 2017). While the former N₂O loss can be mitigated by the application of a NI, the latter is far beyond the scale of NI effectiveness. The present study therefore aimed at evaluating the N₂O emission dynamic of winter oilseed rape after fertilization with urea under practice-related field conditions, particularly focusing on the NI effectiveness during different stages of plant development.

MATERIAL AND METHODS

**Experimental Site** – Field experiments have been conducted at the Agricultural Experimental Station Cunnersdorf in Central Germany (51°22'N, 12°33'E; 130 m a.s.l.; ∅ 9.1°C; ∅ 620 mm; Podzoluvisols; sandy loam, pH 6.5, Corg 1.1%, Nt 0.12%). Investigations occurred in the cropping period 2014/15 and 2015/16 using winter oilseed rape PX 104 (semi-dwarf).

**Experimental Design** – Field plots (each 1,6 x 8,5 m) were designed as a Latin square with the fertilizer treatments granular urea (U), granular urea + urease inhibitor 2-NPT (U+UI) and granular urea + urease & nitrification inhibitor MPA (U+UI+NI) as well as an unfertilized control (C), each with four replicates (in total 16 plots). According to common practice the total number of fertilizer applications can be reduced by one when a NI is added to a fertilizer. Therefore, fertilization occurred twice a year (beginning and end of March) without NI application (U & U+UI) and only once a year (end of February) in case of NI application (U+UI+NI). Total N input was 180 kg N ha⁻¹ independent of the number of fertilization events.

**N₂O Emission** – Emission measurements have been conducted (around noon) at least twice a week and additionally after rain events from February to September 2015 and February to August 2016, respectively, using a closed-chamber approach (Hutchinson & Mosier, 1981). One opaque chamber (volume ca. 350 L / area 0,56 m²) was placed at each field plot (n=16) by using a permanently installed chamber frame at the plot center. After closing four aliquot gas samples per chamber were taken by pre-evacuated glass vessels (100 ml after 0, 25, 50 and 75 min closure) and later on analyzed for N₂O (and CO₂) by gas chromatography. Calculation of emission was based on linear regression of at least three plausible concentration values per emissions measurement (2015 88% and 2016 95% of complete data set).

**Soil Nmin** – Soil mineral N (NH₄⁺, NO₃⁻) was analyzed (mainly) in parallel with emission measurements. Analysis was based on one composite soil sample (0-30 cm depth) per plot using CaCl₂ extraction (DIN 19746) and photometric detection afterwards.

**Soil water content** – Soil water content was analyzed in parallel with soil Nmin by determination of drying loss (105 °C for 2 h). Afterwards water filled pore space (=WFPS) was calculated based on mean dry bulk density of the
soil which was determined once a year by three parallel soil core samples (100 cm³, 5 cm depth) from one plot of each treatment (n=12).

## RESULTS AND DISCUSSION

Estimated total N₂O loss after urea fertilization ranged from 1.15 to 1.36 kg N ha⁻¹ in 2015 and 0.44 to 0.91 kg N ha⁻¹ in 2016. In total this corresponds to 0.10 to 0.44 % fertilizer-N. Regarding total investigation period (Feb to Aug/Sep) only in 2016 NI application did significantly reduce N₂O emissions. This was primarily caused by differences in the N₂O emission dynamic throughout the investigation period of both years.

<figure><img src="image_103.png" /><figcaption>Figure 1 Cumulative N₂O loss after urea fertilization to winter oilseed rape in (A) 2015 and (B) 2016 summarized according to plant development stages (2015: Phase I – Feb-Apr, Phase II – May-Jun, Phase III – Jul-Sep; 2016: Phase I – Feb-Apr, Phase II – May-Jun, Phase III – Jul-Aug)</figcaption></figure>

In 2015 >90 % of total N₂O loss (1.06-1.24 kg N ha⁻¹) occurred around harvest and afterwards (July to September, Fig. 1A) when fertilizer based mineral N was already completely depleted at that time. By contrast, N₂O loss was very low (max. 0.09 kg N ha⁻¹, ≈7 % of total N₂O loss) in the fertilization period (February to April) due to low soil moisture (29-66% WFPS). As a consequence, in 2015 total N₂O loss was not lowered by NI application, even if soil N₂O release was reduced at least within the fertilization period by 97%. By contrast, N₂O loss was significantly higher within the fertilization period of 2016 (up to 46% of total N₂O loss, ≈0.33 kg N ha⁻¹) due to markedly higher soil moisture (76-91% WFPS). Within this phase NI application reduced N₂O loss by 81%. Since afterwards (May to August 2016) significantly less N₂O was emitted (≈0.37-0.59 kg N ha⁻¹) total N₂O mitigation by NI application remained high at ultimately around 60%. Despite strong differences in total mitigation potential between both years as discussed above N₂O release during the fertilization period of 2015 and 2016 was equally reduced concerning a relative scale (i.e. 97% 2015 and 81% 2016).

## CONCLUSION

Determined N₂O loss after urea fertilization to winter oilseed rape was 1.36 kg N ha⁻¹ in maximum (0.44% fertilizer-N) and thus, remained below the current IPCC factor of 1.0% (De Klein et al., 2006). Similar results have been recently reported by Ruser et al. (2017). Regarding fertilization period from February till April (begin of flowering) NI application significantly reduced N₂O release (81-97%). Soil N₂O loss around harvest and also afterwards isn't fed directly by fertilizer based mineral N, but results from fresh biomass which is inherently increased in fertilized systems and irreducible by NI application along with fertilization. Consequentially, total N₂O mitigation potential gained by NI application largely depends on the N₂O emission strength within the period of NI effectiveness (until flowering) as well as during the harvest period and afterwards.

## REFERENCES

* De Klein C., Novoa R.S.A., Ogle S., Smith K.A., Rochette P., Wirth T.C., 2006. N₂O Emissions from managed soils, and CO₂ emissions from lime and urea application, in: Egglestone S., Buendia L., Miwa K., Ngara T., Tanabe K.
(Eds.), 2006 IPCC Guidelines for National Greenhouse Gas Inventories – Volume 4. IGES, Japan.

Hutchinson, G. L., Mosier, A. R., 1981. Improved soil cover method for field measurement of nitrous oxide fluxes. Soil Sci. Soc. Am. J., 45, 311-316.

Ruser R., Schulz R., 2015. The effect of nitrification inhibitors on the nitrous oxide (N₂O) release from agricultural soils - a review. Journal of Plant Nutrition and Soil Science, 178, 171-188.

Ruser R., Fuß R., Andres R., Hegewald R., Kesenheimer K., Köbke S., Räbiger T., Suarez Quinones T., Augustin J., Christen O., Dittert K., Kage H., Lewandowski I., Prochnow A., Stichnothe H., Flessa H. 2017. Nitrous oxide emissions from winter oilseed rape cultivation. Agriculture, Ecosystems and Environment, 249, 57-69.

Walter K., Don A., Fuß R., Kern J., Drewer J., Flessa H., 2015. Direct nitrous oxide emissions from oilseed rape cropping - a meta-analysis. Global Change Biology - Bioenergy, 7, 1260-1271.
# EFFECT OF DELAYED N APPLICATION ON SPRING BARLEY PRODUCTIVITY

HACKETT, R.

Teagasc, Crops Research Centre, Carlow, Ireland.

## INTRODUCTION

Spring barley is currently the main arable crop in Ireland with the majority being grown for animal feed but an increasing proportion being grown for use in malting. Fertiliser N is an important factor in determining crop yield and in the case of malting barley fertiliser N has a large influence on grain protein concentration. In Ireland the recommended fertiliser N dose for spring barley is based on the use of 'Look up tables' which determine the dose to be applied based on a limited number of parameters (previous crop and an estimate of expected yield which is calculated using historic yields). Fertiliser N is typically applied to spring barley in two doses, with a portion being applied at sowing and the remainder applied before the end of the tillering stage. In the current system no account is taken of actual crop growth and the system leaves little scope to adjust fertiliser N inputs based on actual growth or crop N status since all fertiliser is applied before the crop has produced a significant amount of biomass.

Delaying a portion of the fertiliser N until later in the growing season could allow actual crop growth and crop N status to be taken into account to adjust the total N dose. However, delaying a portion of N could subject the barley crop to periods of deficiency which could have a negative effect on grain yield. The objectives of this work were to determine the effect of delaying a portion of the fertiliser N dose until later than is normal in the growing season, on crops that had received sub-optimum levels of fertiliser N at the normal timing.

## MATERIAL AND METHODS

An experiment was carried out in 2015 at the Teagasc Crops Research Centre, Carlow, Ireland. The experiment was laid out as an alpha design with four replications. Plot size was 2.3 m x 12 m. Fertiliser N rates ranging from 0 to 240 kg N ha⁻¹ with 30 kg N ha⁻¹ increments were included in the trial where 30 kg N ha⁻¹ of the total was applied at sowing and the remainder applied during the tillering stage; this is referred to as the 'Standard N' treatment. No further fertiliser N was applied to these treatments. Additional 'Delayed N' treatments were established where two 'basal' N rates (90 and 120 kg N ha⁻¹), that were expected to be sub-optimal for grain yield, were applied as already described i.e. application completed before the end of the tillering stage. Additional N, as a third application, was applied to these treatments at either GS31/32 or GS37/39. For each 'basal' N rate a range of additional N rates, in 30 kg N ha⁻¹ increments up to a maximum total (basal + additional N) N application of 240 kg N ha⁻¹, was applied e.g. for the 90 kg N ha⁻¹ 'base' rate either 30, 60, 90, 120 or 150 kg N ha⁻¹ was applied at either GS31/32 or GS37/39 to give total N application rates ranging from 120 to 240 kg N ha⁻¹.

All fertiliser was applied as CAN (Calcium ammonium nitrate). Crops received all other inputs as per standard farm practice. Grain yield was determined at maturity using a combine harvester and grain protein was determined using an Infratec 1241 grain analyser (Foss, Hillerød, Denmark).

To compare the effect of the 'Delayed N' treatments to the 'Standard N' treatment the experiment was deemed to comprise of two overlapping factorial designs, one where the 'basal' rate was 90 kg N ha⁻¹ and one where the 'basal' rate was 120 kg N ha⁻¹. The factorial treatments were timing of the last application of N (before end of tillering, GS31/32 or GS37/39) and total N rate applied (120-240 for the 90 kg N ha⁻¹ basal rate and 150-240 for the 120 kg N ha⁻¹ basal rate). This allowed comparisons to be made where the same total amount of fertiliser N had been applied according to the either the 'Standard N' or 'Delayed N' protocol. Procedures described by Piepho et al. (2006) were used to analyse these factorial subsets of the data taking error variation for the whole experiment into account. The economic optimum N rate, for the 'Standard N' treatment, was calculated by
equating the first derivative of a quadratic response equation, fitted to grain yield data, to a fertilizer to-grain price ratio of 7:1. Analysis of variance was carried out using Proc Mixed of SAS 9.4

## RESULTS AND DISCUSSION

The economic optimum N rate, where all fertilizer N was applied before the end of tillering, was 169 kg N ha⁻¹. This confirms that the basal dose of N applied to both 'delayed N' treatments before the end of tillering was sub-optimal for yield. Effects of timing of the final N application on grain yield and grain protein concentration are presented in Table 1. There was no significant interaction between timing of the last N application and N rate for grain yield for either basal N application rate. Where additional N was applied to the 'delayed N' treatments at GS31/32 grain yield was either similar or significantly higher compared to where all N had been applied before the end of tillering. Where additional N was not applied until GS37/39 yield was significantly reduced where only 90 kg N ha⁻¹ had been applied previously; where 120 kg N ha⁻¹ had been applied before the end of tillering delaying the additional N until GS37/39 did not cause a significant yield reduction compared to where all N had been applied before the end of tillering. This suggests that negative effects on yield of delaying N until GS37 are only likely to occur where a relatively large deficiency has developed.

Delaying N application until GS37/39 caused a significant increase in grain protein concentration compared to where all N was applied before the end of tillering irrespective of whether a basal rate of 90 or 120 kg N ha⁻¹ had been applied. The effect was more pronounced where a base rate of 90 kg N ha⁻¹ was applied as a result of the lower grain yield obtained in that treatment where final N was delayed until GS37/39. Delaying final N application until GS 31/32 had no significant effect on grain protein concentration.

<table><caption>Table 1. Effect on grain yield and grain protein concentration of delaying a portion of fertilizer N dose until GS31/32 or GS 37/39 compared to where all N was applied before the end of tillering. Delayed N was applied where a base rate of either 90 kg N/ha or 120 kg N/ha had been applied before the end of tillering. Data are means of four (basal 120 treatment) or five (basal 90 treatment) N rates.</caption><thead><tr><th rowspan="2">Timing of final N</th><th colspan="2">Grain yield (t ha<sup>-1</sup>)</th><th colspan="2">Protein concentration (%)</th></tr><tr><th>Basal 90</th><th>Basal 120</th><th>Basal 90</th><th>Basal 120</th></tr></thead><tbody><tr><td>Tillering</td><td>7.39 a</td><td>7.32 b</td><td>9.6 a</td><td>10.1 a</td></tr><tr><td>GS 31/32</td><td>7.22 a</td><td>7.59 a</td><td>9.6 a</td><td>10.3 a</td></tr><tr><td>GS 37/39</td><td>6.67 b</td><td>7.28 b</td><td>10.3 b</td><td>10.7 b</td></tr></tbody></table>

Means within a column with the same letter are not significantly different (P<0.05)

## CONCLUSION

Delaying a portion of the N dose for spring barley until later in the season than would normally happen in commercial practice is unlikely to have a significant impact on grain yield provided a large, prolonged deficiency is not allowed to develop. This suggests that there is potential to delay the final decision as to the total dose of fertiliser N to apply to spring barley when monitoring of crop nitrogen status could be used to guide the decision.

## REFERENCES

* Piepho H.P., Williams E.R. and Fleck M., 2006. A note on the analysis of designed experiments with complex treatment structure. HortScience, 41,446-452.
N₂O SOIL EMISSIONS AFTER BIOCHAR AMENDMENT: CONTRASTING RESPONSES DEPENDING ON THE ORIGINAL FEEDSTOCK

SÁNCHEZ-GARCÍA, M.¹, SÁNCHEZ-MONEDERO, M.A¹, CAYUELA, M.L.¹

¹Department of Soil and Water Conservation and Waste Management, CEBAS-CSIC. Campus Universitario de Espinardo P.O. Box 164, 30100 Murcia (Spain)

INTRODUCTION

It has been demonstrated that biochar addition to soils reduces N₂O emissions in most cases (Cayuela et al., 2014). In this sense, molar O/C and H/C ratios are considered useful indicators to evaluate biochar recalcitrance and its potential in reducing GHG emissions (Spokas, 2010; Cayuela et al., 2015). Nevertheless, biochar properties depend on their feedstocks as well as on the pyrolysis conditions such as heating rate, highest pyrolysis temperature or residence time (Downie, 2011). Thus, generalizations about biochar GHG mitigation potential remain elusive due to the high heterogeneity of biochar properties and reactivity in soils.

In an effort to elucidate how biochars made from different feedstocks would affect N₂O release from agricultural soils, laboratory soil incubations in optimum conditions for denitrification were conducted. Eleven residues from the agricultural and agro-industrial sector widely available in the Mediterranean area were selected as feedstocks.

MATERIAL AND METHODS

Soil and biochar characterization

A fine texture silty clay agricultural soil (Calcic xerosol, USDA classification) was selected to perform the experiments. It was collected from a grapevine cultivated land located in Totana (Murcia, coordinates: 37° 47' N, 1° 34' W), air dried and sieved below 2 mm. The soil pH was 8.7 and EC 177 µS cm⁻¹ (water extract, 1:20 w:w 25°C). Biochars were obtained from pyrolysis of eleven different feedstocks at 600°C with a residence time of 2 h. Feedstocks were obtained from crop residues (primary feedstocks) and from agro-wastes derived from the subsequent agro-industrial processing (secondary feedstocks). Biochar main characteristics are shown in Table 1.

<table><caption>Table 1. Chemical characterization of the biochars</caption><thead><tr><th></th><th>AP</th><th>OlvP</th><th>CP</th><th>GP</th><th>OP</th><th>TPOMW</th><th>GS</th><th>GR</th><th>RS</th><th>TC</th><th>TC+S</th></tr></thead><tbody><tr><td>pH*</td><td>12.3</td><td>11.1</td><td>10.3</td><td>10.4</td><td>11.5</td><td>12.1</td><td>10.7</td><td>10.3</td><td>10.2</td><td>12.1</td><td>12.4</td></tr><tr><td>EC*<br>(mS cm<sup>-1</sup>)</td><td>3.32</td><td>754x10<sup>-3</sup></td><td>1.45</td><td>3.23</td><td>6.33</td><td>7.75</td><td>4.52</td><td>3.13</td><td>4.43</td><td>22.8</td><td>10.07</td></tr><tr><td>H/C**</td><td>0.24</td><td>0.23</td><td>0.28</td><td>0.44</td><td>0.26</td><td>0.32</td><td>0.28</td><td>0.29</td><td>0.29</td><td>0.37</td><td>0.30</td></tr><tr><td>O/C**</td><td>0.08</td><td>0.07</td><td>0.08</td><td>0.09</td><td>0.10</td><td>0.07</td><td>0.09</td><td>0.10</td><td>0.12</td><td>0.28</td><td>0.11</td></tr></tbody></table>

AP: Almond Tree Pruning; OlvP: Olive Tree Pruning; CP: Carob Tree Pruning; GP: Grapevine Pruning; OP: Orange Tree Pruning; TPOMW: Two Phase Olive Mill Waste; GS: Grape Stalks; GR: Giant Reed; RS: Rice straw; TC: Tomato Crop; TC+S: Tomato Crop with substrate (peat). * Water extract 1:20 w:w 25°C*. ** molar ratio

Soil incubations

Soil incubations were performed in 250 ml polypropylene jars at 25°C and 90% of the water filled pore space (WFPS) and lasted 28 days. The control treatment consisted of 100 g of dry soil and the treatments with biochar contained 98 g of dry soil and 2 g of dry biochar. Moisture content was adjusted adding a solution of KNO₃ in order to apply an equivalent rate of 200 kg N ha⁻¹ (corresponding to 66 mg N kg⁻¹ based on a plough layer of 25 cm). The jars were incubated aerobically, covered with a wet cloth which allowed gas exchange and minimized evaporation. N₂O samples were taken twice a day during the two first days decreasing subsequently to daily measurements
during the first two weeks, then every 3-4 days during the third week and a week after at the end of the incubation.
Four replicates of each treatment were stablished.

## RESULTS AND DISCUSSION

N₂O emissions were very low (average N₂O flux ratio from 1.74 to 30.83 µg h⁻¹ kg⁻¹, depending on the treatment) despite the NO₃⁻ input in all treatments. However, there was a contrasting response to biochar addition depending on its feedstock. All the pruning derived biochars (AP, OlvP, CP, GP and OP) had low H/C and O/C molar ratios and, as it was expected, N₂O release was lower when this type of biochar was added to the soil. However, this consistent result was not found with the rest of biochars derived from herbaceous and secondary wastes. In the latest, N₂O-N cumulative emissions ranged from a 46.61% decrease in TC treatment to a 702.63% increase in the case of RS addition.

<figure><img src="image_104.png" /></figure>

Figure 1. Soil cumulative N₂O-N emissions. Error bars indicate standard deviation (n=4). Letters indicate significant differences between treatments according to Tukey's method (α=0.05). AP: Almond Tree Pruning; OlvP: Olive Tree Pruning; CP: Carob Tree Pruning; GP: Grapevine Pruning; OP: Orange Tree Pruning; TPOMW: Two Phase Olive Mill Waste; GS: Grape Stalks; GR: Giant Reed; RS: Rice straw; TC: Tomato Crop; TC+S: Tomato Crop with substrate (peat).

## CONCLUSION

Consistently with previous results found in the scientific literature, biochars obtained from the pyrolysis of tree pruning at 600°C mitigated N₂O-N emissions from this soil. However, biochars obtained from other feedstocks had a contrasting impact on N₂O emissions being their H/C and O/C molar ratios of no value in predicting their mitigation potential. Our results indicate that adequate indicators of biochar capacity in reducing N₂O emissions remain hard to define when feedstock sources are different to those derived from tree pruning.

**Acknowledgements:** This study was funded by Funded by the Regional Agency of Science and Technology from Murcia (ref. 19281/PI/14).

## REFERENCES

Cayuela, M. L., Van Zwieten, L., Singh, B. P., Jeffery, S., Roig, A., Sánchez-Monedero, M. A., 2014. Biochar's role in mitigating soil nitrous oxide emissions: A review and meta-analysis. Agriculture, Ecosystems & Environment, 191, 5-16.

Cayuela, M. L., Jeffery, S., Van Zwieten, L., 2015. The molar H: Corg ratio of biochar is a key factor in mitigating N₂O emissions from soil. Agriculture, Ecosystems & Environment, 202, 135-138.

Downie, A., 2011. Biochar production and use: environmental risks and rewards. PhD Thesis, University of South
Wales.

Spokas, K. A.,2010. Review of the stability of biochar in soils: predictability of O: C molar ratios. Carbon Management, 1(2), 289-303.
N₂O EMISSION DURING SUGARCANE CULTIVATION WITH DIFFERENT LEVELS OF STRAW REMOVAL

GIACOMINI, S. J.¹, PINHEIRO, P. L.¹, DIETRICH, G.¹, RECOUS, S.², POLLET, C. S.¹, BICK, R. A.¹

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

INTRODUCTION

Brazil is the world's largest producer of sugarcane with a cultivated area of 8.74 million hectares in 2017. Currently about 90% of this area is managed in the green cane trash blanketing system (GCTB), in which straw (called trash) is left as mulch on the soil surface. The persistence of this residue (7.4 to 24.3 Mg ha⁻¹) on the soil can increase N₂O emissions by affecting the nitrification and denitrification processes due to the high C contribution and the maintenance of higher soil moisture values combined with the use of nitrogen fertilization (Butterbach-Bahl et al., 2013). With the advent of second generation ethanol produced from biomass, there is the possibility of partial or total removal of sugarcane straw for this purpose. However, little is known about the impact of straw removal on N₂O emissions from soil to the atmosphere. Therefore, the objective of our work was to determine soil N₂O emissions after mechanized harvest at different levels of straw removal before and after nitrogen fertilization.

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 (2015/16) during 365 days. The experimental design was of randomized blocks in a factorial scheme 4x2 with four replicates. The first factor was four straw levels: 0, 4, 8 and 12 Mg ha⁻¹ (100, 67, 33 and 0% removal). The second factor was two doses of urea-N: 0 and 100 kg ha⁻¹. The urea-N was applied in a single dose on the soil surface or on the straw 52 days after the harvest of plant cane. Soil-surface N₂O fluxes were measured between 09:00 and 11:00 hours from treatment application to harvest of sugarcane (365 days) using insulated, fan-mixed, non-flow-through and non-steady-state chambers (70 cm length, 40 cm width and 20 cm height). Measurements were made two to three times per week during the first month following straw and urea applications and less frequently thereafter. Prior to straw application, one galvanized steel base per plot was placed perpendicular to a cane row and inserted into the soil (5 cm). The bases were left in place for the duration of the measurement period. During chamber deployment, air samples were taken at 18-min intervals (t0, t18 and t36) using a 20-mL polypropylene syringe fitted with a three-way stopcock and immediately transferred to 12-mL pre-evacuated glass vials. Air samples were analyzed for N₂O concentration within 7d using a gas chromatograph (GC-2014, Shimadzu Corp.) equipped with an electron capture detector. The N₂O flux (µg N₂O m⁻² h⁻¹) and cumulative N₂O emission (g N-N₂O ha⁻¹) was calculated according to the equation described by Aita et al. (2014). The N₂O-N emission factors (EF) were calculated according IPCC (2006). 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 N₂O emission at the different levels of straw a linear regression was fitted.

RESULTS AND DISCUSSION

N₂O fluxes increased mainly at two periods and were associated with rainfall: after addition of straw on the soil surface and after N fertilization. In the treatments without N, N₂O fluxes were higher in the presence of straw (4S, 8S and 12S) than without straw (0S) until 65 days. After, N₂O fluxes returned to basal level (Figure 1b). In fertilizer N treatments, the highest N₂O fluxes occurred between 11 and 22 days after urea-N application in the 8S+N and 12S+N treatments (68.3 to 99.1 µg N₂O-N m⁻² h⁻¹). After 120 days N₂O fluxes returned to basal level (Figure 1b). The cumulative emission of N₂O did not differ between treatments in the period before N application. On average, the amount of N₂O emitted in that period represented 35.4 and 46.9% of the annual emission of the treatments with and without N, respectively. There was no interaction between straw levels and N. The difference in cumulative N₂O emitted between treatments with and without N at each level of straw was directly related to
the amount of straw at the soil surface, ranging from 519.3 (OS) to 759.1 (12S) g N2O-N ha-1 (y = 512.4+20.2* x, R2 = 0.99). EF for urea-N varied from 0.11 (OS) to 0.24% (12S) and increased with lower removal rate of the straw (y = 0.11+0.01* x, R2 = 0.97). On average for the four straw levels, N fertilization increased the N2O emission by 32.5% (712.6 vs 537.6 g N2O-N ha-1) compared to without N. The straw on soil surface influences soil moisture, temperature and availability of soluble C in the soil, which may favor the formation of anaerobic conditions and occurrence of the denitrification process, one of the main processes responsible for the emission of N2O in the soil (Butterbach- Bahl et al., 2013).

<figure><img src="image_105.png" /><figcaption>Figure 1. Mean daily air temperature and rainfall (a) and N₂O-N flux (b) in the first ratoon sugarcane after 100 kg urea-N ha⁻¹ (N) application over the different straw (S) rates (0, 4, 8 e 12 Mg ha⁻¹). Arrow indicates urea-N application.</figcaption></figure>

## CONCLUSION

Despite the various benefits that permanence of the straw generates to the soil and the plant, it is observed that the maintenance of the straw associated with N fertilization can provide favorable conditions for N₂O emission.

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

## REFERENCES

* Aita C., Gonzatto R., Miola E.C.C., Santos D. B. dos, Rochette P., Angers D. A., Chantigny M.H., Pujol S.B., Giacomini D.A., Giacomini S.J., 2014. Injection of dicyandiamide-treated pig slurry reduced ammonia volatilization without enhancing soil nitrous oxide emissions from no-till corn in southern Brazil. J Environ Qual. 789-800.

* Butterbach-Bahl K., Baggs E.M., Dannenmann M., Kiese R., Zechmeister-Boltenstern S., 2013. Nitrous oxide emissions from soils: how well do we understand the processes and their controls? Philos T Roy Soc B. 368.

* IPCC, 2006. Guidelines for National Greenhouse Gas Inventories. Vol. 4. Agriculture, Forestry and Other Land Use. Prepared by the National Greenhouse Gas Inventories Program (eds Eggleston HS, Buendia L, Miwa K, Ngara T, Tanabe K), pp. 5.1–5.50. IGES, Hayama, Kanagawa
# AMMONIA LOSS FROM UREA AND CALCIUM AMMONIUM NITRATE AFTER APPLICATION TO WINTER WHEAT AND WINTER OILSEED RAPE

SPOTT, O., KREUTER, T., SCHUSTER, C.

SKW Stickstoffwerke Piesteritz GmbH, Department Research and Development, Möllensdorfer Strasse 13, 06886 Wittenberg, Germany

## INTRODUCTION

Ammonia (NH₃) loss after fertilization of mineral nitrogen (N) is well known for its detrimental effect regarding N use efficiency and related ecological issues. The present study aimed at evaluating mean NH₃ loss after urea as well as calcium ammonium nitrate fertilization under practice-related field conditions and focused in particular on the NH₃ mitigation potential by the application of a urease inhibitor along with urea.

## MATERIAL AND METHODS

Since 2013, NH₃ emission measurements after N fertilization in winter wheat (WW / 2013 & 2014) and winter oilseed rape (WOR / 2015 & 2016) have been conducted over 4 years. Analyses of NH₃ fluxes as well as calculation of related cumulative N losses were based on the Calibrated Passive Sampling method (CPS) as described in detail by Pacholski (2016). The CPS approach was shown to deliver reliable results for broadcast application of mineral fertilizers in comparison to e.g. (i) passive flux sampling approaches with a backward Lagrangian stochastic dispersion flux model as well as (ii) the dynamic model Volt'Air' (Kang et al., 2015; Pacholski et al., 2017). Field experiments have been conducted at the Agricultural Experimental Station Cunnersdorf in Central Germany (51°22'N, 12°33'E; 130 m a.s.l.; ∅ 9.1°C; ∅ 620 mm; Podzoluvisols; sandy loam, pH 6.5, Corg 1.1%, Nt 0.12%). NH₃ emissions were measured in randomized field plots (size 9 x 9 m with 9 x 9 m interspace; n=4) including an unfertilized control. In total, five different N fertilizers were tested: calcium ammonium nitrate (CAN), granular urea (U), granular urea with a urease inhibitor (U+UI), granular urea with a nitrification inhibitor (U+NI), and granular urea with a urease- and nitrification inhibitor (U+UI+NI). Fertilizers were compared by their relative NH₃ loss (% of applied N). Here we present only U, U+UI+NI and CAN. In the case of WW, fertilizers were applied in three (CAN, U) and two (U+UI+NI) split applications per year, respectively. For WOR they were applied in two (CAN, U) split applications per year and only once a year (U+UI+NI), respectively. The total number of applications is reduced by one when a nitrification inhibitor is added to the fertilizer (i.e. U+UI+NI). Total N input was 220 kg N ha yr⁻¹ in WW and 180 kg N ha yr⁻¹ in WOR.

## RESULTS AND DISCUSSION

Over four years of practice-related fertilizer application to WW (2013 & 2014) and WOR (2015 & 2016) measured average total N loss via NH₃ was 7.0% for U, 2.6% for U+UI+NI and 0.6% for CAN, respectively (Fig. 1A). Consequently, the mean NH₃ loss for urea has been below the current European emission factor for Germany (close to 15%; Pacholski et al., 2017). It was additionally reduced by approx. 63% on average when a UI was applied concomitantly. As in principle expected, CAN was generally less susceptible to NH₃ loss (always < 1% of fertilized N), since no increase in soil pH takes place after its application to soil as is the case for urea during its hydrolysis (Sommer et al., 2004). Significant differences were found with respect to fertilized plant species and related NH₃ loss, in particular in the case of urea application (Fig. 1A). While in WW NH₃ loss of U was on average 12.3% (2013: 13.1% / 2014; 11.5%) of fertilized N, in WOR only 0.6% (2015: 0.6% / 2016: 0.6%) of applied urea-N was emitted as NH₃. A similar trend was also found for U+UI+NI, where in WW 4.6% (2013: 2.1% / 2014; 7.2%) and in WOR 0.2% (2015: 0.2% / 2016: 0.1%) was emitted on average. Even if less pronounced, CAN also revealed a weak trend for higher NH₃ emissions when applied to WW (2013: 0.9% / 2014; 1.0%) in comparison to WOR (2015: 0.0% / 2016: 0.3%). As reported by e.g. Rogers & Aneja (1980) plants are differently suited to take up NH₃ directly from the surrounding atmosphere and thus, the plant species currently fertilized may have an impact on total NH₃ loss after fertilization. It remains, however, rather questionable if large differences as found here can be explained by different NH₃ uptake capacities of cropped plants. Besides plant physiology effects as well as typical soil
characteristics such as pH and cation exchange capacity, the weather conditions during as well as after fertilization are also well known as a key driver of NH₃ loss (e.g. Sommer et al., 2004). This mainly relates to soil temperature and soil moisture conditions (i.e. precipitation and soil water dynamic). While the latter largely affects the distribution of a fertilizer within the soil, the former directly controls the equilibrium between NH₄⁺ and NH₃ within the soil solution. As a main consequence NH₃ loss potential is significantly decreased if a fertilizer is washed into the soil soon after its application. On the other hand, NH₃ loss potential is significantly increased by a rising soil temperature due to the resulting increase in NH₃ concentration in the soil solution (to the detriment of NH₄⁺) and thus, an increased NH₃ emission gradient towards the atmosphere.

<figure><img src="image_106.png" /><figcaption>Figure 1 (A) Average of total cumulative NH₃ loss after fertilization of U, U+UI+NI and CAN to winter wheat (WW 2013 & 2014) and winter oilseed rape (WOR 2015 & 2016), respectively, and (B) impact of seasonal weather conditions (visualized by the mean soil surface temperature of day 1 to 5 after fertilizer application) on NH₃ loss potential after a fertilization event (cumulative NH₃ loss after each single fertilization event of urea during the field campaign 2013 to 2016).</figcaption></figure>

Considering that the practice-related fertilization strategy of WW differs clearly from that of WOR, it appears rather likely that observed NH₃ loss related to WW and WOR was in fact provoked by the prevailing weather conditions during fertilization. While WOR is fertilized under largely cold and wet conditions (end of winter to early spring), WW is fertilized later on from spring to early summer under progressively warmer and dryer conditions. Consequently, NH₃ loss potential could be assumed to generally increase from end of winter to early summer (March to June) in the course of season-related changes of temperature and/or moisture conditions. There was a weak trend of an increasing NH₃ loss potential in relation to soil surface temperature after fertilization of urea (Fig. 1B). Even if it is currently not provable as statistically significant due to the multifactorial complexity of NH₃ soil release as well as the limited number of annual data sets, it underlines the fundamental impact of seasonal weather conditions during mineral fertilization of e.g. WOR on the one hand and WW on the other.

## CONCLUSION

Present results clearly demonstrate that a uniform NH₃ emission factor appears to be insufficient to represent NH₃ losses due to practice-related fertilization, in particular with respect to urea. Crop type and related fertilization strategy (i.e. season and number of application) have to be considered to optimize the estimation of soil NH₃ loss by mineral fertilizer application. The mean NH₃ loss of 7.0% fertilizer-N found for urea is lower than currently assumed and hence, challenges the latest European emission factor of approx. 15% as also recently reported by Pacholski et al. (2017). The application of a urease inhibitor significantly reduces NH₃ release after urea fertilization by more than 50% independent from crop type and related fertilization strategy.

## REFERENCES

Kang N., Köster J.R., Seidel A., Pacholski A., 2015. Field measurement of ammonia emissions after nitrogen
fertilization - A comparison between micrometeorological and chamber methods. European Journal of Agronomy, 71, 115-122.

Pacholski A., 2016. Calibrated Passive Sampling - Multi-plot field measurements of NH₃ emissions with a combination of dynamic tube method and passive samplers. Journal of Visualized Experiments 109, 1-15.

Pacholski A., Doehler J., Schmidthalter U., Kreuter T., 2017. Scenario modeling of ammonia emissions from surface applied urea under temperate conditions: application effects and model comparison. Nutrient Cycling in Agroecosystems, 110 (1), 177-193.

Rogers H.H., Aneja V.P., 1980. Uptake of atmosphere ammonia by selected plant species. Environmental and Experimental Botany, 20, 251-257.

Sommer S.G., Schjoerring J.K., Denmead O.T., 2004. Ammonia emission from mineral fertilizers and fertilized crops. Advances in Agronomy, 82, 557-622.
# A COMPARISON OF THE NITROGEN USE EFFICIENCY AND NITROGEN LOSSES ATTRIBUTED TO THREE FERTILISER TYPES APPLIED TO AN INTENSIVELY MANAGED SILAGE CROP

COWAN N¹, LEVY P¹, MORING A¹, LOUBET B², POLINA VOYLOKOV P², SKIBA U¹

¹ Centre for Ecology and Hydrology, UK; ² INRA, France

## INTRODUCTION

A constant supply of reactive nitrogen (Nr) is required to sustain high crop productivity in intensively managed agricultural soils; however, the nutrient use efficiency (NUE) of these crops is frequently low, with more than half of applied Nr typically being lost to the environment through biological pathways and chemical processes such as the emission of ammonia (NH₃) and nitrous oxide (N₂O). One method of reducing Nr losses from agriculture is the incorporation of microbial inhibitors with fertiliser application which directly target and slow a specific biological pathway. Synthetic fertilisers (typically urea) coated with chemical inhibitors that target urease hydrolysis and microbial nitrification have been shown to reduce Nr losses to some extent in lab conditions and several have been trialed at the field scale with varying results. Although there are many positive studies which promote the pollution reducing capabilities of these chemicals, some questions remain over the overall effectiveness of the inhibitors which face claims that reduction of one form of Nr pollution may contribute to another. The use of inhibitors in farming still remains uncommon, mostly due to a reluctance to change to an uncertain practice, compounded by the drawback that treated fertilisers are typically more expensive than traditionally used products, and that yields may be reduced. This study aims to specifically investigate the effect of the agrotain® urease inhibitor on a typical grassland silage crop in Scotland, comparing yield and Nr loses in the form of N₂O and NH₃ with the two most commonly used synthetic nitrogen fertilisers in the UK: ammonium nitrate (nitram) and urea.

## MATERIAL AND METHODS

A grassland field which had historically been used to graze sheep at Easter Bush Farm Estate (Scotland) was selected for the field trial. A grid of 16 plots, each measuring 20 m by 20 m, were marked out and randomly assigned one of four different treatments (Figure 1). Fertilisers in the form of nitram, urea and agrotain® coated urea were applied at a rate of 70 kg-N ha⁻¹ to the plots a total of five times over the space of two years (2016-2017).

<figure><img src="image_107.png" /><figcaption>Figure 1. Field site layout describing measurement locations of N₂O flux chambers and NH₃ sample badges.</figcaption></figure>
The plots were arranged in such a way to allow the use of the Flux Interpretation by Dispersion and Exchange over Short Range (FIDES) method; an inverse modelling approach which infers NH₃ emissions from multiple small areas using multiple passive (Alpha) samplers (Loubet et al., 2017). NH₃ fluxes were measured for three events only. Static chambers were used to measure N₂O fluxes over all five events. Cumulative fluxes of N₂O were calculated using a Bayesian approach which takes into account the log-normal nature of spatial and temporal variability of N₂O emissions (Levy et al., 2017). A 30 m² section of the silage grass (1.5 by 20 m) was harvested using a Haldrup harvester (Haldrup F-55) with on-board weighing capabilities for yield measurements.

## RESULTS AND DISCUSSION

The nitram fertilizer performed best in terms of yield across the five replications with the mean NUE approximately 40 % higher than that of the other urea based fertilisers, though large uncertainties were present due to spatial and seasonal variation. The negative environmental impact of nitram application was highlighted in the comparison of N₂O fluxes, for which nitram lost significantly more of the Nr applied than the urea fertilisers. Losses of applied Nr in the form of NH₃ were highest for the uncoated urea fertilizer, reaching into double figures while losses for nitram were negligible and emissions from the treated urea remained low (Table 1).

<table><caption>Table 1. Summary of the fate of applied Nr in terms of yield uptake, NH₃ and N₂O emissions for all Nr applications.</caption><thead><tr><th>N fertiliser type</th><th>Yield<br>% NUE</th><th>NH<sub>3</sub><br>% N Loss</th><th>N<sub>2</sub>O<br>% N Loss</th></tr></thead><tbody><tr><td>Nitram</td><td><strong>35.2 ± 21.6</strong></td><td>-0.3 ± 1.3</td><td><strong>1.9 ± 1.3</strong></td></tr><tr><td>Urea</td><td>20.5 ± 19.9</td><td><strong>13.6 ± 3.6</strong></td><td>0.6 ± 0.3</td></tr><tr><td>Urea & agrotain®</td><td>23.8 ± 23.3</td><td>1.4 ± 1.5</td><td>0.7 ± 0.4</td></tr></tbody></table>

## CONCLUSION

This experiment confirms past studies which have identified urea as a large source of NH₃ emission and ammonium nitrate as a large source of N₂O emissions. The Agrotain® treated urea emitted significantly less NH₃ when compared to urea and had a negligible effect on N₂O emissions; however, this decrease in Nr loss was not translated into a significant increase in crop yield. The results of this study suggest that urease inhibitors, such as Agrotain®, may play an important role in mitigating Nr pollution, however the agronomic benefits to the farmer appear to be negligible. Our experiments are short term only and there is a need for more long-term studies covering different climate zones, crop types and soil properties to investigate the economic and environmental benefits of switching from the preferred ammonium nitrate fertilisers in the UK.

**Acknowledgements:** We gratefully acknowledge funding of the BBSRC – Newton project ‘UK-China Virtual Joint Centre for Improved Nitrogen Agronomy (CINAG)’

## REFERENCES

Loubet, B., Carozzi, M., Voylokov, P., Cohan, J.P., Trochard, R., and Génermon, S., 2017, Evaluation of a new inference method for estimating ammonia volatilisation from multiple agronomic plots. Biogeosciences Discuss., https://doi.org/10.5194/bg-2017-424

Levy, P. E., Cowan, N., van Oijen, M., Famulari, D., Drewer, J. and Skiba, U., 2017, Estimation of cumulative fluxes of nitrous oxide: uncertainty in temporal upscaling and emission factors. Eur J Soil Sci, 68: 400–411. doi:10.1111/ejss.12432
# NITROGEN USE EFFICIENCY OF RAW AND ANAEROBICALLY DIGESTED SLURRIES: A FIELD STUDY WITH DIFFERENT ¹⁵N METHODS

HUTTER, M.¹,², KREBS, R.¹, MAYER, J.²

¹ Zurich University of Applied Sciences ZHAW, 8820 Wädenswil, Switzerland; ² Agroscope, Zürich, Switzerland

## INTRODUCTION

In agricultural biogas plants in Switzerland, in general 80 % or more of the digested organic matter is farmyard manure. Additional organic waste materials are used as co-substrates. Manure and slurry are valuable fertilisers, whereby a high nitrogen use efficiency (NUE) is important for agricultural productivity. Short-term nitrogen recovery by crops from slurries is influenced mainly by the NH₄-N content, the C:N ratio and the stability of the organic substance (Gutser et al., 2005). Compared to raw slurries, anaerobically digested (AD) slurries contain less easily available organic carbon, they have a smaller C:N ratio and a wider N<sub>NH4</sub>:total N ratio. In pot trials, NUE of AD was 10 to 25% higher compared to undigested slurries (Bosshard et al., 2010; de Boer, 2008). Under field conditions, results vary. Bosshard et al. (2010) found in wheat an apparent NUE of 37% when fertilised with raw and 56% with AD pig slurry. Möller et al. (2008) could find a significant effect of AD on N uptake compared to undigested slurry when slurry was incorporated into the soil shortly after application. The aim of this field study with silage maize was i) to prove whether the nitrogen use efficiency of AD slurries is higher than that of raw slurries in the year of application and ii) to compare a ¹⁵N direct method (¹⁵N labelling of the slurry NH₄-N fraction) with an indirect ¹⁵N isotope dilution method.

## MATERIAL AND METHODS

The field trial was carried out as a fully randomized block design with four replicates in 2015 with silage maize on a luvisol with sandy loam (Zurich, Switzerland). A raw cattle slurry (RawC) and a raw pig slurry (RawP) were compared with three AD slurries from agricultural biogas plants, each of it using one of the quantitatively most important co-substrates in Switzerland: residues from cereal production (ADCe), coffee ground (ADCo) or vegetable and fruit wastes (ADVeg). One control was fertilised with synthetic mineral nitrogen (CoMin) and a second control was unfertilised (CoNull). The apparent nitrogen use efficiency (NUE), based on above-ground biomass of silage maize, was studied with two ¹⁵N tracer methods. For the direct method, the slurry was labelled with (¹⁵NH₄)₂SO₄ (95 atm % ¹⁵N). NUE is related to the NH₄-N fraction of the slurry. For the indirect ¹⁵N isotope dilution method, ¹⁵N labelled clover-grass residues were ground and incorporated as a powder into the soil 32 days before sowing. In this case, slurry was not labelled. NUE calculation based on the dilution in the labelled soil pool compared to the unfertilised control and NUE refers to total-N. The plot size was 4 m², but tracers were applied on a microplot of 1 m² grown with 8 maize plants. Results of ¹⁵N methods were compared with a difference calculation, where the difference in the N uptake with and without slurry application is related to the amount of total N fertilised. From every microplot two maize plants were harvested in September, as well as two plants from the neighbouring row which was not ¹⁵N labelled. Differences were analysed by analysis of variance (ANOVA), following by Tukey's honestly significant difference (HSD) test using R, version 3.0.3 and RStudio open source edition. Significance was concluded in all tests if *P*<0.05.

## RESULTS AND DISCUSSION

In difference calculation, related to total N, both raw slurries had significantly lower NUE than AD slurry ADCe and a tendentially lower NUE than ADCo (Fig. 1A). A similar pattern between treatments could be found for the NUE of the NH₄-N fraction, determined with the ¹⁵N direct method (Fig. 1B): Raw slurries had significantly lower NUE than AD slurries ADCo and ADCe (significant difference between RawP and ADCo). NUE of ADVeg was between raw slurries and ADCo and ADCe, respectively. Using the ¹⁵N isotope dilution method, no differences between treatments could be found. Variation of the data was much larger compared with the two other methods and patterns between treatments were clearly differing (results not shown). One reason for a higher data variation in
the isotope dilution approach might be that the differences between isotopic signatures of maize in slurry fertilized plots compared to the control are smaller and thus cross contaminations and measurement errors have greater effects compared to the direct method. In addition, labelling of the soil 62 days before first fertiliser application appears to be too short to label soil organic nitrogen homogeneously.

Apparent NUE was relatively low in all treatments. The extraordinarily dry and hot weather in 2015 has probably lead to this low NUE. The two raw slurries had the lowest, the two AD slurries ADCe and ADCo the highest NUE. Bosshard et al. (2010) found comparable NUE in a field study with different calculation with 37% NUE in raw and 56% NUE in AD pig slurry, respectively. The lower NUE of ADVeg compared to ADCo and ADCe could neither be explained with the C:N ratio, nor with the NH₄-N proportion. However, ADVeg was fermented only for 14 days, which is relatively short. This could have lead to a higher amount of easily degradable C compounds and therefore to a greater slurry N immobilisation in soil.

<figure><img src="image_108.png" /></figure>

Figure 1. Nitrogen use efficiency (NUE) of raw and digested slurries calculated on the basis of above ground N uptake of mature silage maize by difference (A) and with the ¹⁵N direct method (B). NUE is related to total N (A) and NH₄-N (B), respectively. Different letters show significant differences between treatment means (Tuckey HSD; p≤ 0.05). RawC: raw cattle slurry, RawP: raw pig slurry, ADCe: anaerobically digested (AD) slurry with cereal residues, ADCo: AD slurry with coffee ground, ADVeg: AD slurry with vegetables, CoMin: mineraly fertilised control.

## CONCLUSION

Anaerobically digested slurry with co-substrates had a (tendentially) higher NUE compared to raw slurries in the year of application. The isotope dilution method would be a valuable method to estimate NUE of complex organic fertilisers, e.g. slurry, but the method requires a homogenous ¹⁵N labelling of the soil organic matter. The successful application of the isotope dilution method under field conditions requires further improvements.

## REFERENCES

* Bosshard, C., Flisch, R., Mayer, J., Basler, S., Hersener, J.-L., Meier, U., & Richner, W. (2010). Verbesserung der Stickstoffeffizienz von Gülle durch Aufbereitung. *Agrarforschung Schweiz, 1*(10), 378–383.

* de Boer, H. C. (2008). Co-digestion of Animal Slurry Can Increase Short-Term Nitrogen Recovery by Crops.
*Journal of Environment Quality*, 37(5), 1968–1973. https://doi.org/10.2134/jeq2007.0594

Gutser, R., Ebertseder, T., Weber, A., Schraml, M., & Schmidhalter, U. (2005). Short-term and residual availability of nitrogen after long-term application of organic fertilizers on arable land. *Journal of Plant Nutrition and Soil Science*, **168**(4), 439–446. https://doi.org/10.1002/jpln.200520510

Möller, K., Stinner, W., Deuker, A., & Leithold, G. (2008). Effects of different manuring systems with and without biogas digestion on nitrogen cycle and crop yield in mixed organic dairy farming systems. *Nutrient Cycling in Agroecosystems*, **82**(3), 209–232. https://doi.org/10.1007/s10705-008-9196-9
# INTERACTIVE EFFECTS OF THE FACTORS CONTROLLING URINE-N₂O EMISSIONS FROM AN UPLAND SOIL

CHARTERIS, A.F.<fnref n="1" />, MARSDEN, K.A.², CASTELLANO-HINOJOSA, A.³, LOICK, N.<fnref n="1" />, CHADWICK, D.R.², RAVELLA, S.R.⁴,
MEAD, A.<fnref n="1" />, FIELD, N.<fnref n="1" />, WHELAN, M.⁵, CÁRDENAS, L.M.<fnref n="1" />

## INTRODUCTION

Agriculture accounted for almost 70% of the UK's N₂O emissions in 2015 (Brown et al., 2017). The contribution of grasslands to these emissions has large uncertainty, partly due to their heterogeneous nature and the uneven distribution of animal excreta and treading. Emissions from upland pastures, important for sheep farming, are particularly understudied and uncertainty is increased by the lack of UK-specific emission factors (EFs) for grazing returns of sheep excreta (Brown et al., 2017). Urine patches represent important temporary point sources of pasture N₂O emissions in which labile urine-C and N stimulate soil N cycling (Cardenas et al., 2016). The main processes responsible for N₂O production are nitrification (aerobic) and denitrification (anaerobic). These processes are influenced by other soil conditions (e.g. pH), and any factors affecting them, including patch location (e.g. in relation to farmland features), pasture management and weather, as well as the concentration, composition and volume of the urine deposited (Dijkstra et al., 2013; Marsden et al., 2016). The interaction of these factors, varying in space and over time, make aggregated N₂O emission estimates uncertain. The laboratory experiments conducted in this study aim to investigate the interactive effects of factors affecting sheep urine-derived N₂O emissions from an upland soil. Data will be used in field-scale models of upland N₂O emissions which integrate the spatial and temporal variability of sheep diet and behaviour, urine deposition characteristics, topography and soil physico-chemical properties to generate better N₂O emission estimates.

## MATERIAL AND METHODS

### Site and sampling

Soil was sampled from an 11.5 ha semi-improved upland pasture (ca. 240-340 m above sea level) at Bangor University's Henfaes Research Centre (Abergwyngregyn, North Wales). The pasture is dominated by grasses (British NVC classifications U4 and MG6) and bracken (*Pteridium aquilinum*) on a podzolic soil, with spatial differences due to organic residues building up beneath bracken dominated areas. Representative bulked samples of 'grass' soil and of 'bracken' soil were generated by sampling 42 points identified across the site. Urine was sampled from six Welsh Mountain ewes (*Ovis aries*). It was stored filtered and frozen until required, upon which a homogenized sample was generated at 14 g N l⁻<fnref n="1" /> for use or appropriate dilution for the experimental treatments.

### Experimental design

Incubation experiments to determine N₂O fluxes were conducted in the denitrification incubation system (DENIS), a flow-through soil core incubation system which allows automated measurement of CO₂, N₂O, NO and N₂ emissions under an 80:20 He:O₂ atmosphere. A fractional factorial design was used to explore the interactive effects of five factors affecting urine-N₂O emissions: soil type (x2), soil water-filled pore space (% WFPS; x3), urine N concentration (x4), urine volume (x2) and temperature (x2). The design considered the constraints of the DENIS (12 vessels, one temperature per incubation) and prioritized information relating to two-factor interactions. Half of the 96 possible combinations were tested over four 14-day incubations in the DENIS. Parallel destructive incubation experiments with three time-points were also conducted. A subset of the treatments will also be analyzed using the multifactorial Taguchi methodology (Ravella et al., 2008). Soil cores consisted of sieved (< 9 mm) soil, repacked into two layers reflecting the organic-rich top layer overlying mineral soil to 0.5 and 0.8 g cm⁻³, respectively.

<footnote n="1">¹ Rothamsted Research, UK; ² School of Environment, Natural Resources and Geography, Bangor University, UK; ³ Department of Microbiology, University of Granada, Spain; ⁴ Institute of Biological and Environmental and Rural Sciences (IBERS), Aberystwyth University, UK; ⁵ Department of Geography, University of Leicester, UK</footnote>
## Gas and soil analyses

Out-flow gas concentrations were determined by gas chromatography-electron capture detection (CO₂ and N₂O), gas chromatography-helium ionization detection (N₂) and chemiluminescence (NO). Analysis of variance (ANOVA) was conducted on cumulative N₂O emissions to assess which factors are most important in driving emissions and whether any two-factor interactions are significant. Soil samples were analysed at t=0, 1, 3, 8 and 14 days. Soil moisture, pH and K₂SO₄-extractable NH₄⁺ and NO₃⁻ concentrations were determined.

## RESULTS AND DISCUSSION

CO₂ fluxes peaked quickly following urine application and showed a similar pattern of response across all urine treatments (max. ca. 90 kg ha⁻¹ hr⁻¹). NO fluxes peaked twice at low temperature, but only once in higher temperature experiments (max. ca. 3.5 g ha⁻¹ hr⁻¹). Production of N₂ was not observed during any incubation experiment. N₂O fluxes ranged from 0 to 0.23 kg ha⁻¹ hr⁻¹, with treatments with 0 g urine-N l⁻¹ and 50% WFPS giving lower fluxes than those with higher urine N inputs and 80% WFPS. Temperature affected the shape and timing of N₂O emission responses. Cumulative N₂O emissions ranged from ≈0 to 0.83 kg ha⁻¹. Increasing soil % WFPS and urine N concentration significantly increased cumulative N₂O emissions (F<sub>2,16</sub>=85, p<0.001 and F<sub>3,16</sub>=32, p<0.001, respectively). Although the effect of temperature was large (s²=3.37, 1 d.f. vs. residual=0.08, 16 d.f.), there is insufficient statistical power to conclude it is significant. Significant two-factor interactions were revealed for % WFPS and urine N concentration (F<sub>6,16</sub>=6.7, p=0.001), with a larger combined effect of increases in both factors on increasing N₂O emissions than each alone and for soil type and % WFPS (F<sub>2,16</sub>=4.2, p=0.034).

## CONCLUSION

N₂O emissions from upland soils, which are often assumed to be low due to N-limitation, are not negligible when urine patches are deposited under some conditions, (e.g. when concentrated (high N) urine is deposited on wet soils) and large, transient N₂O fluxes can result. These data will be used in developing a spatially and temporally explicit model of N₂O emissions from upland pastures to improve the agricultural inventory of N₂O. This will help in targeting mitigation efforts to highest impact areas. In addition, the results could be useful in developing simple rules for upland land owners to avoid higher N₂O emissions.

**Acknowledgements:** Thanks to J. Evans for statistical support; J. Holmberg and G. Sanfratello for urine collection and assistance with soil sampling. This work was funded by the UK NERC, under grant award NE/M015351/1/.

## REFERENCES

* Brown P., Broomfield M., Cardenas L., Choudrie S., Kilroy E., Jones L., Passant N., Thomson A., Wakeling D., 2017. UK Greenhouse Gas Inventory, 1990 to 2015: Annual Report for submission under the Framework Convention on Climate Change. Didcot, Ricardo-AEA.

* Cardenas L.M., Misselbrook T.M., Hodgson C., Donovan N., Gilhespy S., Smith K.A., Dhanoa M.S., Chadwick D., 2016. Effect of the application of cattle urine with or without the nitrification inhibitor DCD, and dung on greenhouse gas emissions from a UK grassland soil, Agr. Ecosyst. Environ., 235, 229-241.

* Dijkstra J., Oenema O., van Groenigen J.W., Spek J.W., van Vuuren A.M., Bannink A., 2013. Diet effects on urine composition of cattle and N₂O emissions, Animal, 7, 292-302.

* Marsden K.A., Jones D.L., Chadwick D.R., 2016. Disentangling the effect of sheep urine patch size and N loading rate on cumulative N₂O emissions, Anim. Prod. Sci., 56, 265-275.

* Ravella S.R., Kumar C.G., Prakasham R.S. and Hobbs P.J., 2008. The Taguchi methodology as a statistical tool for biotechnological applications: A critical appraisal, Biotechnol. J., 3, 510-523.
# OPTIMIZING NITROGEN RATE OF PEARL MILLET UNDER ARID AND SEMI-ARID ENVIRONMENTS

ULLAH, A.<fnref n="1" />,²*, AHMAD, A.<fnref n="1" />, KHALIQ, T.<fnref n="1" /> SAEED, U.<fnref n="3" /> AHMAD, I.<fnref n="1" /> HUSSAIN, J.<fnref n="1" /> MAHMOOD, A.²

## INTRODUCTION

The evidences for different response of pearl millet to fertilizer application have been reported in the literature with optimum rates ranging from 0 to >150 kg ha⁻<fnref n="1" /> (Ullah et al., 2017). The form of N (NO₃⁻ – N vs. NH₄⁻ – N), N mode and time of application also affect the nitrogen uptake and use efficiency. The authors concluded that absorption of ammonium over nitrate may have negative effect on growth and development of millet. Spitalnaik et al. (1995) examined the N uptake at various growth phases and concluded that pearl millet utilized high N uptake of 110 kg ha⁻<fnref n="1" /> at 4th stage (vegetative) and reached a maximum uptake of 153 kg ha⁻<fnref n="1" /> at physiological maturity. It is examined that for everyone kilogram N applied, the hybrids or improved varieties returned 10-15 kg of grain at 30-60 kg N ha⁻<fnref n="1" /> (Maman et al., 1999). However, 40 kg N ha⁻<fnref n="1" /> was found to be economical for most of the millet growing regions, but the higher nitrogen applications are recommended in soil with adequate moisture. The high yielding varieties and hybrids used N more efficiently than traditional cultivars (Ullah et al., 2017). There is clear need to understand N utilization in many cereals (Gascho et al., 1995). The overall optimum N utilization for grain pearl millet in not reported earlier for pearl millet farming areas in Pakistan.

## MATERIALS AND METHODS

Field experiments were conducted at two different locations, based on climatic conditions, the Layyah district is comprised of arid environment while Faisalabad have semi-arid conditions. Three plant spacings (10, 15 and 20 cm, main plots), and four N rates (0, 150, 200, 250 kg ha⁻<fnref n="1" />, subplots) were compared in split plot design with three replicates. The plot size of each sub plot was 3.6 m × 1.8 m with three replications.

Regression analysis was carried out to study the response of millet grain yield to different N levels for three intra row spacing. The quadratic equations were fitted to calculate optimum N for different plant spacing. The relationships were plotted between observed grain yield and N levels for each plant spacing to set equations. The amount of N for maximum grain yield (point of inflection) of millet was calculated for each intra row spacing using the following formula by considering x as optimum N. The response of millet grain yield to N rates (0, 150, 200, 250 kg ha⁻<fnref n="1" />) at different plant spacing (10, 15, 20 cm) was described with quadric response curve for each site, as in following equations (Saeed et al., 2017).

$$Y=a+bN+cN^2 \qquad (1), N_{(optimum)} = (-b) / 2(a) \qquad (2)$$

$$\text{Benefit Cost Ratio (BCR)} = (\text{Income}) / (\text{Input Cost}) \qquad (3)$$

$$\text{Excessive N (\%)} = [(N(\text{applied}) - N(\text{optimum})) / N(\text{applied})] \times 100 \qquad (4)$$

Where, Y is the pearl millet grain yield (kg ha⁻<fnref n="1" />), N is the amount of fertilizer applied (kg N ha⁻<fnref n="1" />), and a, b, c are estimated parameters. Linear regressions were used to establish relationships among variables.

## RESULTS AND DISCUSSION

The regression analysis showed significant strong relationship between millet grain yield and N application rate at Faisalabad and Layyah during both years of study (2015-2016). The requirement of N level was observed different for different intra row spacing at both locations. The results enumerated that continuous application of N may not be economical for millet farming community. Optimum N level of 176, 177 kg ha⁻<fnref n="1" /> was calculated for Faisalabad

<footnote n="1">¹ Department of Agronomy, University of Agriculture, Faisalabad, Pakistan; ² Ayub Agricultural Research Institute Faisalabad, Pakistan;</footnote>

<footnote n="3">³ Action on Climate Today Lahore, Pakistan</footnote>
location in year 2015 and 2016, respectively at 15 cm plant spacing. These optimum levels of N responded maximum yield of 3566 kg ha⁻¹ and 3695 kg ha⁻¹ in year 2015 and 2016, respectively. Economics of these optimum N did not allow to apply these high amounts of N and resulted to save 31% and 45% excessive N at 200 kg ha⁻¹, 250 kg ha⁻¹ N rate, respectively during year 2015 and 2016 at Faisalabad location. However, increasing or reducing plant spacing resulted in more N requirement for millet with reducing yield at Faisalabad in year 2015 and 2016. Similarly, in case of Layyah, maximum yield of millet (3674, 3644 kg ha⁻¹) were recorded at optimum N levels of 188 kg ha⁻¹, 174 kg ha⁻¹ during year 2015 and 2016, respectively at 15 cm plant spacing. The difference in yields and N rates during both years is non-significant. However, the economically optimum N levels were found 29%, 33% less over N₂₀₀ and 43, 47% less over N₂₅₀ in year 2015 and 2016, respectively. The amount of excessive N at N₂₀₀ and N₂₅₀ in district Layyah for both year is non-significant at 10cm and 20cm plant spacing. Saeed et al., 2017 determined N losses for wheat crop and optimize economic level of N.

<table><caption>Table 1: Optimum N rates for maximum millet grain yield, economical millet grain yield, and excessive N of millet at Layyah (arid) and semi-arid (Faisalabad) environments during 2015 and 2016</caption><thead><tr><th rowspan="2">Plant Spacing</th><th colspan="2">Optimum N<br>(kg ha<sup>-1</sup>)</th><th colspan="2">Maximum Yield<br>(kg ha<sup>-1</sup>)</th><th colspan="2">Economically Optimum<br>N<br>(kg ha<sup>-1</sup>)</th><th colspan="2">Excessive N at<br>N<sub>200</sub> (%)</th><th colspan="2">Excessive N at<br>N<sub>250</sub> (%)</th></tr><tr><th>2015</th><th>2016</th><th>2015</th><th>2016</th><th>2015</th><th>2016</th><th>2015</th><th>2016</th><th>2015</th><th>2016</th></tr></thead><tbody><tr><td colspan="11"><strong>(a) Faisalabad</strong></td></tr><tr><td>10 cm</td><td>195</td><td>194</td><td>3034</td><td>3153</td><td>145</td><td>145</td><td>27.5</td><td>27.5</td><td>42</td><td>42</td></tr><tr><td>15 cm</td><td>176</td><td>177</td><td>3566</td><td>3695</td><td>138</td><td>138</td><td>31</td><td>31</td><td>45</td><td>45</td></tr><tr><td>20 cm</td><td>198</td><td>174</td><td>3019</td><td>2761</td><td>157</td><td>139</td><td>21.5</td><td>30.5</td><td>37</td><td>44</td></tr><tr><td>Mean</td><td>190</td><td>182</td><td>3206</td><td>3203</td><td>147</td><td>141</td><td>27</td><td>30</td><td>41</td><td>44</td></tr><tr><td colspan="11"><strong>(b) Layyah</strong></td></tr><tr><td>10 cm</td><td>191</td><td>173</td><td>3227</td><td>3097</td><td>142</td><td>131</td><td>29</td><td>34.5</td><td>43</td><td>48</td></tr><tr><td>15 cm</td><td>188</td><td>174</td><td>3674</td><td>3644</td><td>141</td><td>133</td><td>29.5</td><td>33.5</td><td>44</td><td>47</td></tr><tr><td>20 cm</td><td>187</td><td>171</td><td>3001</td><td>2841</td><td>142</td><td>132</td><td>29</td><td>34</td><td>43</td><td>47</td></tr><tr><td>Mean</td><td>188</td><td>172</td><td>3300</td><td>3194</td><td>141</td><td>132</td><td>29</td><td>34</td><td>43</td><td>47</td></tr></tbody></table>

Assuming Prices: N = 0.79$ per kg and Millet grain = 0.23$ per kg

## CONCLUSION

It is concluded that empirical modeling through use of quadratic relationship and economic analysis is a good approach to economically optimize N application. Excessive use of N can be easily managed to a resource efficient use of inputs. So, this study concluded that optimum economic level of N should be sought out according to site specific environment for good production of hybrid pearl millet.

## REFERENCES

Ullah, A., A. Ahmad, T. Khaliq and J. Akhtar. 2017. Recognizing production options for pearl millet in Pakistan under changing climate scenarios. Journal of Integrative Agriculture. 16 (4): 762-773.

Spitalniak, J., D.L. Wright, I.D. Teare and N.R. Usherwood. 1995. Nutrient uptake (NPK) and growth stage for pearl millet, tropical and temperate com, p. 102-107. In First National Grain Pearl Millet Sym. Proc. Tifton, Georgia.

Saeed, U., S.A. Aftab, T. Khaliq and Z.A. Zahir. 2017. Optimizing irrigation and nitrogen for wheat through empirical modeling under semi-arid environment. Environ. Sci. Pollut. Res. DOI 10.1007/s11356-017-8733-y.

Maman, N., S.C. Mason, T. Galusha and M.D. Clegg. 1999. Hybrid and nitrogen influence on pearl millet in Nebraska: yield, growth, and nitrogen uptake and nitrogen use efficiency. Agron. J. 91:7 37-743.

Gascho, G.J., R.S.C. Menezes, WW. Hanna, R.K. Hubbard and J.P. Wilson. 1995. Nutrient requirements of pearl millet, p. 92-97. In First National Grain Pearl Millet Symposium Proceedings. Tifton, Georgia.
# EVALUATION OF THE EFFICIENCY OF A NEW ADDITIVE TO UAN 32 ON THE IMPROVEMENT OF THE NITROGEN ASSIMILATION BY WHEAT

MAIGNAN, VM.¹, GELIOT, PG.¹

¹ Via Végétale, France

## INTRODUCTION

The use of nitrogen fertilizers generates losses by volatilization and leaching. These losses have important environmental consequences but also economic impacts for the farmer. Currently, solutions such as nitrification inhibitors (DMPP) and urease inhibitors (NBPT) exist (Abalos D. et al., 2014). But there is no innovation on the market which improves the efficiency of nitrogen solution (UAN 32) applied on the soil. However, this is cheapest form of nitrogen, the easiest to use and its spreading quality is better, especially in terms of homogeneity.

The aim of this study was to evaluate the potential for improving the nitrogen assimilation by wheat by adding an additive to UAN 32.

## MATERIAL AND METHODS

### Hydroponics crop test

Hydroponics crop test was done to evaluate the efficiency of two products used in combination with a nitrogen solution (UAN32) in spring wheat cv. Specifik (Triticum aestivum L.). Plants were divided in three batches: (i) control (nitrogen solution UAN 32 + non-limiting mineral supplementation), (ii) VNT1 (nitrogen solution + formula VNT1 + supplementation) and (iii) VNT3 (nitrogen solution + formula VNT3 + supplementation). Five weeks after the onset of hydroponic growth, root dry weight (DW), shoot DW and root to shoot ratio were measured. The concentration of nitrates and total nitrogen amount were also analyzed.

### Field test in micro-plots

Field test in micro-plots was done to evaluate the efficiency of the best product resulting from hydroponics test in application with the UAN 32 in winter wheat cv. Anvergure. Plants were divided in four batches: (i) Ammonitrate X = 180 U Ha-1, (ii) Nitrogen Solution X-40, (iii) Nitrogen Solution X, (IVIII)VNT3 (Nitrogen Solution X + Formula VNT3). Yield, protein content and Nitrogen Use Efficiency (NUE = (yield x protein content) / 5.7) were measured.

### Statistical analysis

All parameters were analyzed by one-way ANOVA for each tissue (roots and shoots) separately. The Student test at p < 0.05 was employed for the estimation of statistically significant changes in response to the different treatments. All statistical analyses were performed by R software.

## RESULTS AND DISCUSSION

### Effects on biomass in hydroponics

VNT3 supply increased significantly the root dry weight compared to the control (UAN 32). Application of VNT3 led to an increase of the shoot dry weight compared to VNT1 supply. But there is no consistent change compared to the control. The root to shoot ratio showed a tendency to allocate more biomass to the roots when plants received VNT1 or VNT3.

### Effects on nitrogen in hydroponics
We observed that application of VNT1 or VNT3 reduced significantly the concentration of NO₃⁻ in roots compared to the control. In the same way, VNT3 supply slightly decreased NO₃⁻ concentration in shoots compared to the control and VNT1.

N amounts are very low in roots compared to the shoots. However, we demonstrated that N root amounts are significantly higher when we applied VNT1 or VNT3 compared to the control. In shoots, there was no consistent change. VNT3 application just slightly increased N total amount in shoots.

The results showed that VNT3 formulation increased roots biomass (+15% compared to the control) and N total uptake (+10% compared to the control). However, VNT1 formulation did not have a significant effect compared to the control (Figure 1).

<figure><img src="image_109.png" /><figcaption>Figure 1: Effect of VNT1 and VNT3 on nitrogen uptake and root development</figcaption></figure>

## CONCLUSION

This study showed a better nitrogen assimilation with VNT3 application in wheat plants in hydroponics conditions. The increase of root biomass and the low nitrate concentration in roots and shoots (suggesting an important activity for nitrate reductase), reveal that this additive stimulates nitrogen metabolism. The micro-plot trial confirms these results even if the pedoclimatic conditions could reduce the efficiency of the product. Others studies including different kinds of soil and measuring specifics parameters such as enzymes and genes have to be done for this product to better understand the mechanisms of stimulation and thus optimize the formulation. These studies could also be built from the genes expressions results (N-P-K transporters and abiotic stresses genes) recently obtained on tomatoes.

**Acknowledgements:** We acknowledge Jean-Christophe Avice for correction and kindly improving the English of the manuscript.

## REFERENCES

Abalos D. et al., 2014, Meta-analysis of the effect of urease and nitrification inhibitors on crop productivity and nitrogen use efficiency, Agriculture, Ecosystems & Environment, Volume 189, Pages 136-144
# INFLUENCE OF PEA, LENTIL AND FABA BEAN ON SOIL MICROBIAL ACTIVITIES IMPLICATED IN SULFUR AND NITROGEN MINERALIZATION

SLEZACK-DESCHAUMES, S.¹, GENESTIER J.¹, VOISIN, A.S.², PIUTTI, S.¹

¹UMR 1121 Agronomie et Environnement, Université de Lorraine-INRA, TSA 40602, 54518 Vandœuvre cedex, France ; ²UMR 1347 Agroécologie, Université de Bourgogne-INRA, 17 rue Sully, BP 86510, 21065 Dijon cedex, France

## INTRODUCTION

Integration of legumes in the crop rotation provides several benefits. These benefits are assumed to be partly due to an increase in soil nitrogen (N) availability. Legumes could also modulate the soil content in sulfur (S) since this element is essential for symbiotic N fixation. As a consequence, legumes could alter microbial communities involved in N and S mineralization. However, the influence of legumes on soil functioning may differ widely among species. In fact, legumes species can present distinct abilities to fix N and different characteristics in their root system that would influence nutrient acquisition (Wending et al., 2016) and the release of rhizodeposits. The aim of our study was to have a better understanding of the factors by which legume species influence microbial activities involved in N and S mineralization. The objectives were therefore: 1) to characterize the root traits of 3 legumes species i.e. pea, lentil and faba bean, 2) to analyze soil variables (microbial biomass C and N, organic extractable C and N) and microbial activities implicated in N (proteases, aminopeptidases) and S (arylsulfatase) mineralization and 3) to discuss the relationships between root traits of legumes and microbial activities. For that purpose, a field experiment was conducted.

## MATERIAL AND METHODS

### Field experiment

The field experiment was established at the Epoisses experimental farm (Bretenières, France, 47° 14′, 29″ N, 4°06′54″ E). Pea, faba bean and lentil were sown in October, 2015, with 3 repetitions per legume species. No fertilization was done. Soils were sampled under each plant cover using a hand auger (first 15 cm) at the beginning and at the end of vegetative stages and at mid-flowering of crops. The roots were manually separated from the soil using tweezers. The roots were gently cleaned under tap water, and root traits were immediately measured. The soil was stored at 4°C until processing.

### Root trait measurements

Roots were scanned at a resolution of 400 dpi using a flatbed Epson Expression 10000XL scanner. The scanned images were analyzed according to Romillac et al. (2015) in order to determine the total root length, the projected root surface area, the root mean diameter (mm) and the root length distribution per root diameter class. The fine root length percentage was calculated as the percentage of the total root length represented by roots with a diameter < 0.2 mm. The root fresh and dry weights (g) were determined.

### Soil C and N contents and soil microbial biomass C and N

Soil C and N were extracted with hot water and were measured using a TOC-V CSH (Shimadzu). Microbial biomass C and microbial biomass N were estimated using the fumigation extraction method (Vance et al., 1987). Extractable C and N concentrations were determined using a TOC-V CSH (Shimadzu).

### Arylsulfatase, aminopeptidase and protease activities

Potential arylsulfatase activity was determined according to Tabatabai and Bremner (1970). Potential protease activity was determined according to Romillac et al. (2015). Leucine and arginine aminopeptidases were measured according to Sinsabaugh et al. (2008).
## Statistical analyses

Analysis of variance and Principal Component Analysis (PCA) were conducted using R 3.0.0 software.

## RESULTS AND DISCUSSION

<figure><img src="image_110.png" /><figcaption>Figure 1. Evolution of soil functioning (A) and root traits (B) at the beginning (1) and the end (2) of vegetative phase and at mid-flowering (3) under pea (Pisum), lentil (Lens) and Faba bean (Faba) covers analyzed by Principal Component Analyses.</figcaption></figure>

### Evolution of soil functioning

PCA showed that soil functioning changed during legume development (Figure 1A). PCA revealed also that legume species differentially influenced soil functioning at the end of the vegetative phase. At this phase, the microbial biomass N was significantly lower under faba bean compared to pea and lentil whereas as the C/N ratio of the soil extractable C and N was higher under faba bean. Soil protease and soil arylsulfatase activities were significantly higher under faba bean at the end of vegetative phase. These findings could suggest that, under faba bean, N and S are more limiting for soil microorganisms. This would favor microbial activities implicated in N and S mineralization.

### Evolution of plant root traits

PCA showed that root traits varied throughout legume development, even if the magnitude of this evolution was less pronounced for pea and lentil than for faba bean (Figure 1B). Whereas pea and lentil root traits seemed to be quite similar, faba bean root traits were distinct from that of the other species, whatever developmental stage considered. Faba bean showed a higher root biomass. This was accompanied by a higher mean root diameter and a lower percentage of fine roots. These root traits would favor resource conservation in faba bean, as previously suggested by Wendling et al. (2016).

## CONCLUSION

This study revealed that faba bean had a differential influence on soil functioning compared to pea and lentil. In particular, faba bean stimulated microbial activities implicated in the mineralization of soil organic N and S at the end of the vegetative phase. This could be related to the contrasting root morphology between faba bean and the two other legume species. Notably, the lower percentage of fine roots, which have shorter longevity than coarse roots, could decrease the release of N and S resources for microorganisms into the soil. This would favor the mining of soil organic N and S by microorganisms in order to alleviate nutrient limitations.

## REFERENCES

* Romillac N., Piutti S., Amiaud B., Slezack-Deschaumes S., 2015. Influence of pea root traits modulating soil bioavailable C and N effects upon ammonification activity. Soil Biol. Biochem., 90, 148-151.

* Sinsabaugh R.L., Lauber C.L., Weintraub M.N., Ahmed B., Allison S.D., Crenshaw C., Contosta A.R., Cusack D., Frey S., Gallo M.E., Gartner T.B., Hobbie S.E., Holland K., Keeler B.L., Powers J.S., Stursova M., Takacs-Vesbach
C., Waldrop M.P., Wallenstein M.D., Zak D.R., Zeglin L.H., 2008. Stochiometry of soil enzyme activity at global scale. Ecology Lett., 11, 1252-1264.

Tabatabai M.A., Bremner J.M., 1970. Arylsulfatase activity of soils. Soil Sci. Soc. Am. J., 34, 225-229.

Vance E.D., Brookes P.C., Jenkinson D.S., 1987. An extraction method for measuring soil microbial biomass C. Soil Biol. Biochem., 19, 703-707.

Wending M., Büchi L., Amossé C., Sinaj S., Walter A., Charles R., 2016. Influence of root and leaf traits on the uptake of nutrients in cover crops. Plant Soil, 409, 419-434.
# SOIL NITROGEN DYNAMICS IN INTERCROPPED WHEAT (TRITICUM AESTIVUM) AND WHITE LUPIN (LUPINUS ALBUS)

DE OLIVEIRA, A. B.<fnref n="1" />,²,³; HINSINGER, P.²; YVIN, J. -C.<fnref n="1" />; ARKOUN, M.<fnref n="1" />; LE CADRE, E.³

## INTRODUCTION

Intercropping is a cropping system in which several species are growing in a field during a significant period of their life cycle. This cropping system becomes a promising alternative to intensive agriculture in many countries due to ecological regulations (Brooker et al., 2015). While benefits of mixed cropping in terms of yield gains are listed in a large body of literature, only scarce studies focused on the effects of such systems on soil quality, particularly soil chemical and microbiological properties involved in nitrogen (N) cycle. Plant species are known to shape microbial communities in their rhizosphere, by different amount and composition of root exudates (Song et al., 2007). However, little is known about the common microbial community existing in intercropping systems and the resulting changes in nutrient cycling. Since nitrification, and especially its first step (i.e. ammonia oxidation to nitrite), is essential to N-cycling regulation in agroecosystems, more studies are needed to examine changes of this key process under mixed crops conditions. Soil nitrification has been demonstrated to be positively related to the abundance of the two groups implicated in oxidation of ammonia to nitrite, the ammonia-oxidizing bacteria (AOB) and archaea (AOA) (Zhang et al., 2015). We assumed that intercropping lead to an increase in soil microbial biomass and AOB/AOA abundances due to a higher diversity of rhizodeposits through direct effects or indirect effects by modifying soil chemistry. Hence, the aim of this study was to investigate modifications in soil N dynamics under cereal-legume intercrops, especially in terms of changes in microbial and chemical-related N parameters compared to the respective sole crops.

## MATERIAL AND METHODS

A complete factorial pot experiment was conducted in a greenhouse from September to December 2017 on a calcareous Cambisol with wheat (*Triticum aestivum* var. Lennox) and white lupin (*Lupinus albus* var. Feodora) in both mixing (WL) and respective sole crops (W and L) at 3 soil nitrogen levels (N0 = 61 mg kg⁻<fnref n="1" /> soil; N1 = 92 mg kg⁻<fnref n="1" /> soil; N2 = 124 mg kg⁻<fnref n="1" /> soil) to influence plant interactions, with 7 replicates. Pots were filled with 2 kg of air-dried soil and 200 g of perlite beads (1:1 volume ratio). Plants densities were of 4 in W, 2 in L and 2/1 in WL treatments. Pots were maintained at 70% of the soil field capacity all over the experiment. At flowering, we measured the nitrogen content of plants (root and shoot), and soil chemical (nitrate [NO₃], ammonium [NH₄⁺] concentrations, and pH) and biological variables (total microbial biomass, abundance of ammonia-oxidizing bacteria [AOB] and archaea [AOA] and microbial carbon and nitrogen contents [MBC, MBN]) in two compartments (rhizosphere and bulk soil). Statistical analysis differences were performed with R software, version 3.3.2, by Tukey's multiple comparison tests at the 0.05 probability level.

## RESULTS AND DISCUSSION

Globally, intercropping (WL) has contrasted effects on microbial biomass relative to sole crops. We measured only a significant difference for MBC, with WL presenting higher values than L, but similar to those in W, at N1 treatment. MBC, MBN and NH₄⁺_N contents were significantly greater (*p* < 0.001 for MBC and MBN; *p* < 0.05 for NH₄⁺_N) in the rhizosphere relative to the bulk soil. The NO₃⁻_N concentration was significantly more important in the bulk treatments (*p* < 0.001) compared to other treatments, and for the L treatment whatever the soil compartment (Figure 1). Interestingly, NH₄⁺_N concentration in the L treatment was similar to intercropped crops in rhizosphere. We hypothesize that nitrification rate can be modified in rhizosphere of L compared to the other

<footnote n="1">¹Centre Mondial de l'Innovation Roullier - Agro Innovation International Society, France; ²Joint Unit Research SUPAGRO INRA IRD CIRAD Functional ecology and Biogeochemistry of Soils and Agroecosystems (UMR Eco&Sols), France; ³Joint Unit Research AGROCAMPUS OUEST INRA Soil, Agro- and Hydro-systems, Spatialization (UMR SAS), France</footnote>
treatments. Plant and molecular biology analyses planned will confirm this interpretation. If confirmed, it will be
interesting to investigate if this nitrification potential is maintained after several cycles of mixed cropping.

<figure><img src="image_111.png" /><figcaption>Figure 1. NO₃⁻_N contents in the rhizosphere and bulk soil of the different crop treatments (W – sole wheat; L – sole lupin; WL – wheat/lupin mixed crop) within each soil nitrogen treatment (N0, N1, N2 = 61, 92 and 124 mg N kg⁻¹ soil). Bars indicate standard errors. Different letters indicate significant differences at *p* < 0,05 between crop treatments within each N level.</figcaption></figure>

CONCLUSION

Preliminary results showed that intercropping did not present a significant effect (i.e. higher values) on microbial biomass as initially assumed. However, interesting results concerning soil NO₃⁻_N contents were found in particular when lupin is present. Other planned biological analyses (plant; soil AOA/AOB abundances and nitrification potential) will complete the present data for further interpretation of our results in order to confirm or reject our initial hypothesis.

Acknowledgements: We thank Agro Innovation International Society for its financial and technical staff support.
We also thank INRA and AGROCAMPUS OUEST for its technical staff support at experiment's harvest.

REFERENCES

Brooker, R. W., Bennett, A. E., Cong, W.-F., Daniell, T. J., George, T. S., Hallett, P. D., Hawes, C., Iannetta, P. P. M., Jones, H. G., Karley, A. J., Li, L., McKenzie, B. M., Pakeman, R. J., Paterson, E., Schöb, C., Shen, J., Squire, G., Watson, C. A., Zhang, C., Zhang, F., Zhang, J., and White, P. J. (2015). Improving intercropping: a synthesis of research in agronomy, plant physiology and ecology. *New Phytologist* **206**, 107-117.

Song, Y. N., Zhang, F. S., Marschner, P., Fan, F. L., Gao, H. M., Bao, X. G., Sun, J. H., and Li, L. (2007). Effect of intercropping on crop yield and chemical and microbiological properties in rhizosphere of wheat (Triticum aestivum L.), maize (Zea mays L.), and faba bean (Vicia faba L.). *Biology and Fertility of Soils* **43**, 565-574.

Zhang, N. N., Sun, Y. M., Wang, E. T., Yang, J. S., Yuan, H. L., and Scow, K. M. (2015). Effects of intercropping and Rhizobial inoculation on the ammonia-oxidizing microorganisms in rhizospheres of maize and faba bean plants. *Applied Soil Ecology* **85**, 76-85.
# QUANTIFICATION OF AMMONIA, NITROUS OXIDE AND METHANE EMISSIONS FOLLOWING BIOGAS DIGESTATE APPLICATION IN AN ORCHARD FIELD IN THE NORTH CHINA PLAIN

DEHARDE, A.¹, YUAN, Y.², GAO, Z.², MA, W.², ROELCKE, M.¹,³, NIEDER, R.¹

¹Technische Universität Braunschweig Institute of Geoecology Braunschweig | Germany, ²Hebei Agricultural University College of Resources and Environmental Science Baoding China, ³German-Chinese Agricultural Center (DCZ) Beijing | China

## INTRODUCTION

In China, excessive application of mineral and organic nitrogen (N) fertilizers such as urea, animal manure and to an increasing extent biogas digestate (BD) causes high N losses to the environment (e.g., Michalczyk et al., 2016). Pathways for N losses from soils include gaseous N emissions via denitrification and ammonia (NH₃) volatilization (e.g., Eickenscheidt et al., 2014). Emission of NH₃ is one of the most important N loss pathways in the North China Plain (NCP) (Michalczyk et al., 2016). Re-deposited NH₃ contributes to soil acidification and eutrophication. Ammonia also forms secondary particles, which may be transported over greater distances and can cause serious human health problems (Pacholski et al., 2006). Nitrous oxide (N₂O) and methane (CH₄) are potent greenhouse gases that contribute to global warming.

Up to now, almost no comparative investigations on the emissions of environmentally and climate-relevant gases following BD application in the NCP are available.

## MATERIAL AND METHODS

Emissions of NH₃, N₂O und CH₄ were quantified simultaneously in an apple orchard near Baoding (38°48′N 115°24′E), Hebei province, in the NCP in April 2017. The experimental soil was classified as an Eutric Cambisol. The soil pH (H₂O) in 0-20 cm was 8.2 and the texture a silty clay loam. The soil organic carbon content (0-20 cm) was less than 1% while the CaCO₃ content was around 4%. The climate of this region is subhumid with hot, humid summers and cold, dry winters. The annual precipitation is 535 mm and the mean annual temperature is 13 °C.

Biogas digestate from a pig farm (corresponding to 150 kg N ha⁻¹) was applied onto the soil surface (surface application: SA), into furrows parallel to tree rows and immediately re-covered with soil (furrow application: FA) and on soil surface with immediate uniform incorporation (IA). In addition, a control treatment (CT) without fertilization was designed. For each application method three replicate plots (1 m x 5 m) were established.

To determine the emissions of N₂O and CH₄, gas samples were taken from closed chambers (50 cm × 50 cm) and analyzed via gas chromatography within 24 hours. Sampling was carried out once a day for 12 days (288 hours). Table 1 shows cumulative emissions from only three sampling events (hours 4, 144 and 288) after start of the experiment. For the measurement of NH₃ the calibrated Dräger-Tube Method (DTM) (Pacholski et al., 2006) was used. The period of measurements included 4 days (96 hours), starting directly after fertilizer application, with about 30 measurements per plot. In parallel, the ambient wind speed was measured at two heights.

## RESULTS AND DISCUSSION

The cumulative N₂O emissions for 12 days after application were highest for FA (121.87 g N ha⁻¹, 0.08% of N applied), followed by IA (65.44 g N ha⁻¹, 0.044% of N applied) (Table 1). The results for SA were in an equal dimension like those of CT. The processes forming N₂O (denitrification and nitrification) are influenced by factors such as water, nitrogen and available C contents in soil (Bateman and Baggs, 2005), which varied significantly among the application methods. For FA, the BD and thus also the moisture and nitrogen were concentrated inside the furrows, while it was spread more or less uniformly over the plots for SA and IA. All application methods led to a slight decrease in CH₄ emissions (Table 1) which means that the soil generally acted as a sink for CH₄. The cumulative CH₄-C losses for the different application methods ranged from -7.47 g C ha⁻¹ to -14.32 g C ha⁻¹.
<table><caption>Table 2: Cumulative losses of N₂O [g N ha⁻¹] and CH₄ [g C ha⁻¹] 4, 144 and 288 hours after surface application (SA), furrow application (FA), uniform incorporation (IA) of biogas digestate and from a control treatment (CT) (mean values, n=3).</caption><thead><tr><th rowspan="2">Time after BD application [h]</th><th colspan="4">N₂O [g N ha⁻¹]</th><th colspan="4">CH₄ [g C ha⁻¹]</th></tr><tr><th>SA</th><th>FA</th><th>IA</th><th>CT</th><th>SA</th><th>FA</th><th>IA</th><th>CT</th></tr></thead><tbody><tr><td>4</td><td>0.17</td><td>0.15</td><td>0.20</td><td>0.16</td><td>-0.007</td><td>0.01</td><td>-0.03</td><td>-0.07</td></tr><tr><td>144</td><td>9.30</td><td>54.37</td><td>38.26</td><td>7.95</td><td>-5.28</td><td>-4.60</td><td>-3.32</td><td>-5.80</td></tr><tr><td>288</td><td>19.11</td><td>121.87</td><td>65.44</td><td>14.46</td><td>-14.32</td><td>-9.90</td><td>-7.47</td><td>-10.80</td></tr></tbody></table>

<figure><img src="image_112.png" /><figcaption>Figure 3: Cumulative NH₃ losses [kg N ha⁻¹] after surface application (SA), furrow application (FA) and uniform incorporation (IA) of biogas digestate during 96 hours after start of the experiment (mean values ± stand. dev., n=3).</figcaption></figure>

Comparing the application methods, SA led to the highest N losses in form of NH₃ (3.56% of applied N), while the NH₃ losses after IA and FA only accounted for 0.2% and 0.043% of the applied N, respectively (Fig. 1). The efficiency of fertilizer incorporation for reducing NH₃ emissions is widely known (e.g., Pacholski et al., 2006). In the SA treatment the NH₃ volatilization rate was highest with up to 30.82 mg N m⁻² h⁻¹ directly after fertilizer application. However, compared to other investigations with BD, the initial NH₃ fluxes of this study were comparably low. Probably, these low fluxes were a result of the untypically low pH (6.5) of the digestate (Eickenscheidt et al., 2014).

## CONCLUSION

Surface application of biogas digestate in the NCP leads to high N-losses in form of NH₃ while incorporation and furrow application results in higher N₂O emissions. Due to these antagonistic effects, loss-reducing measures have to be carefully balanced. For methane the detected fluxes were slightly negative, indicating that the soil acted as a sink for CH₄.

**Acknowledgement:** This study was supported by the DAAD-CSC (PPP project ID 57217922) and the NSFC (No. 41675151).

## REFERENCES

* Bateman E.J., Baggs E.M., 2005. Contributions of nitrification and denitrification to N₂O emissions from soils at different water-filled pore space. Biol Fertil Soils 41, 379–388.

* Eickenscheidt T., Freibauer A., Heinichen J., Augustin J., Drösler M., 2014. Short-term effects of biogas digestate and cattle slurry application on greenhouse gas emissions affected by N availability from grasslands on drained fen peatlands and associated organic soils. Biogeosciences, 11, 6187–6207.

* Michalczyk A., Kersebaum K.C., Heimann L., Roelcke M., Sun Q.P., Chen X.P., Zhang F.S., 2016. Simulating in situ ammonia volatilization losses in the North China Plain using a dynamic soil-crop model. J. Plant Nutr. Soil Sci., 179, 270–285.
Pacholski A., Cai G., Nieder R., Richter J., Fan X., Zhu Z., Roelcke M., 2006. Calibration of a simple method for determining ammonia volatilization in the field – comparative measurements in Henan Province, China. *Nutrient Cycling in Agroecosystems* 74, 259–273.
# EFFECTS OF THE NITRIFICATION INHIBITOR DMPSA ON NUTRIENT UPTAKE, NITRATE LEACHING AND CROP GROWTH IN BARLEY AND POTATO IN POT AND FIELD TRIALS

PACHOLSKI, A.<fnref n="1" />, GOEBEL, M.², MEYER, A.³, MANNHEIM, T.<fnref n="1" />

## INTRODUCTION

The application of nitrogen (N) fertilizers can be connected with N losses via nitrate leaching and resulting reduced N efficiency (Velthof et al. 2014). Conversely, low N efficiency due to limitations of N uptake by low availability of other nutrients (e.g. P) can result in nitrate leaching losses. Several measures are proposed to reduce aqueous N losses from managed soils: catch crops, reduced fertilization, buffer strips etc. The use of nitrification inhibitors (NI) as e.g. DCD or DMPP, which prolong the lifetime of the ammonium N form, have been validated in many trials as effective measures to reduce such losses after fertilizer application throughout the vegetation period (e.g. Yu et al. 2007). Fertilizers treated with NI usually have a higher price than untreated, but significant yield increases of about 5 % and 10% nitrogen use efficiency reported across published trials under various agro-ecological conditions (Abalos et al. 2014) pay for the environmental benefit and can provide additional income to the farmer. As one disadvantage in soils with low cation exchange capacity, treatment of urea and surface applied slurry with NI can result in higher ammonia emissions from these sources (Kim et al. 2012). One aspect often not considered in most studies is the positive effect of NI application on P and micronutrient availability to the crop due to sustained ammonium nutrition (Thomson et al. 1993). The NI DMPSA (2-(n-3,4-dimethylpyrazol)succinic acid) was developed to deliver these beneficial effects to N fertilizers to which established NI (DCD, DMPP) cannot be applied with stability, as e.g. calcium ammonium nitrate (CAN) or diammonium phosphate (DAP). DMPSA treated CAN, ASN and DAP were tested in Germany in greenhouse pot trials and in a field trial under simulated leaching water conditions for investigation of their leaching N retardation potential and related yield and nutrient (P, N) uptake effects compared to untreated fertilizers.

## MATERIAL AND METHODS

A pot trial was established in spring 2017 in an aerated greenhouse. Summer barley was seeded in early March in Kick-Brauckmann pots (10 kg of dry sandy loam soil) and supplied with DAP with and without DMPSA at two N levels (0.8 and 1.2 g DAP N/pot) and control without N supply in four replicates. At the beginning of April, four leaching events were initiated on a weekly basis by applying water at a volume corresponding total soil pore space while water was kept on the level of about field capacity in the meantime. After intensive irrigation event, leaching soil water was collected and mineral N concentrations were determined. Aboveground biomass was harvested at EC 40 of barley development and N and P uptake were measured. A second set of the same treatments was established without leaching stress and grown under optimum water supply until full ripeness. In a second trial, potatoes (planted early May) were grown in a field trial on a sandy loam soil in Northern Germany. Fertilizer treatments included CAN, CAN+DMPSA, ammonium sulfate nitrate (ASN)+DMPSA at 200 kg N/ha applied in two splits (4.05. and 15.06.2017) and control without N. The site is equipped with a linear irrigation system providing optimum water supply. At two events excess irrigation was scheduled to simulate high precipitation conditions followed by leaching. The summer was characterized by high rainfall and only one irrigation event was carried out (60 mm on two subsequent days). Leaching water was sampled using passive flux meters (Gee et al. 2009) until end of October 2017. Potato were harvested in September and marketable tuber yield was determined. Yield results were obtained from 4 replicate plots. Two of the 4 plots were each equipped with passive flux meters. Data of both trials were analyzed by ANOVA and Tukey HSD post-hoc test.

## RESULTS AND DISCUSSION

<footnote n="1">¹ Eurochem Agro GmbH, Reichskanzler-Mueller-Str. 23, 68165 Mann, Germany, Andreas.Pacholski@eurochemgroup.com,² Landesbetrieb Landwirtschaft Hessen, FG 33, Am Versuchsfeld 11-13, 34128 Kassel, Germany, Maria.Goebel@llh.hessen.de, ³ Landwirtschaftskammer Niedersachsen, Johannssenstr. 10, 30159 Hannover, Germany, andreas.meyer@lwk-niedersachsen.de</footnote>
In the pot trial, nitrate leaching was significantly reduced by 90% within a period of 2 month after fertilizer application compared to uninhibited DAP by addition of DMPSA, which roughly corresponds to the inhibited N fraction (100%) (data not shown). Biomass harvested at EC40 was increased by about 20%, while N uptake was 15% higher. In addition to higher N efficiency, P uptake was also strongly increased with addition of DMPSA to DAP by up to 100% (Fig. 1 A). Significantly higher yields and a higher harvest index were observed in the set of treatments without excess irrigation on the lower N level (0.8g N/pot)

<figure><img src="image_113.png" /><figcaption>Figure 1 A.) P-uptake by summer barley grown in Kick-Brauckmann pots, DAP applied with and without DMPSA with excess irrigation, no replicates: biomass had be pooled to obtain sufficient plant material; B.) Reduction of nitrate concentration in leaching water compared to untreated CAN by CAN and ASN treated with DMPSA, irrigated potato in Northern Germany.</figcaption></figure>

CAN treated with DMPSA showed an increase of potato marketable and starch yield by 5% and 7% (n.s.), respectively, while DMPSA treated ASN showed no yield effect. Across sampling intervals, nitrate concentrations in leaching water were significantly reduced by on average 50% compared to untreated CAN, with higher reductions in ASN+DMPSA corresponding to the fractions of ammonium N applied by the fertilizers (Fig. 1 B).

## CONCLUSION

Addition of the new inhibitor DMPSA to CAN, DAP and ASN reduced nitrate leaching within the vegetation period (2-6 months) compared to untreated fertilizer by 50%, up to 90% in the pot trial. This beneficial effect was accompanied by higher yields as well as higher N und P efficiencies. The use the nitrification inhibitor can be considered as a measure to reduce both, N leaching from excess water and from low N and P uptake efficiency.

## REFERENCES

* Abalos D, Jeffery S, Sanz-Cobena A, Guardia G, Vallejo A., 2014. Meta-analysis of the effect of urease and nitrification inhibitors on crop productivity and nitrogen use efficiency. Agric. Ecosyst. Environ. 189, 136–144.

* Gee G.W., Newman B.D., Green S.R., Meissner R., Rupp H., Zhang Z.F., Keller J.M., Waugh W.J., van der Velde M., Salazar J., 2009. Passive wick fluxmeters: Design consideration s and field applications. Water Res. Res. 45, 1-18.

* Kim D G, Saggar S, Roudier P, 2012. The effect of nitrification inhibitors on soil ammonia emissions in nitrogen managed soils: a meta-analysis. Nutr. Cycling Agroecosyst. 93, 51–64.

* Thomson C. J., Marschner H., & Roemheld V., 1993. Effect of nitrogen fertilizer form on pH of the bulk soil and rhizosphere. And on the growth, phosphorus, and micronutrient uptake of bean. J. Plant Nutrition, 16 83), 493-506

* Velthof GL, Lesschen J.P., Webb J., Pietrzak S., Miatkowski Z., Pinto M. et al., 2014. The impact of the nitrates directive on nitrogen emissions from agriculture in the EU-27 during 2000–2008. Sci Total Environ., 468, 1225–1233.

* Yu Q., Chen Y., Ye X., Zhang Q., Zhang Z., Tian P., 2007. Evaluation of nitrification inhibitor 3,4-dimethyl pyrazole phosphate on nitrogen leaching in undisturbed soil columns. Chemosphere, 67(5):872-8
# CALIBRATING AIRBORNE MULTISPECTRAL DATA TO AUTUMNAL FRESH MATTER AND N CONTENT OF WINTER OILSEED RAPE

BUKOWIECKI, J.<fnref n="1" />, PAHLMANN, I. <fnref n="1" />, KAGE, H.<fnref n="1" />

## INTRODUCTION

Winter oilseed rape (WOSR) is one of the major crops in Germany and it is proven to be a high contributor to N surpluses in cropping systems (Henke et al., 2007), hence optimizing its N fertilization is getting into focus. Henke et al. (2009) showed that autumnal canopy N uptake of WOSR is a sensible factor when calculating N fertilization rates in spring. Pahlmann et al. (2017) derived optimal site-specific N application rates from autumnal N uptake, measured by tractor-borne reflection data, and reduced N surpluses significantly.

Recently advancing unmanned aerial vehicle (UAV) technology enables a fast collection of high-resolution spectral data, at considerable low costs. In field trials it was tested if UAV-based multispectral data can be calibrated to fresh matter (FM) and shoot nitrogen of WOSR and whether this calibration is transferrable to predict FM on commercial farms in Northern Germany.

## MATERIAL AND METHODS

Data for calibration where collected from September to December 2017 on Hohenschulen Experimental Station of Kiel University. On the test site two different sowing dates and two levels of N fertilization were used to obtain variation in canopy size. At six dates four 1 m² areas per block were sampled, FM and N concentration of the plants were determined. Before the sampling an UAV-based camera (Sequoia camera by Parrot™) was utilized to receive multispectral data. The camera collects data in four bands: 530-570 nm (Green), 640-680 nm (Red), 730-740 nm (red edge) and 770-810 nm (near infrared, NIR) with a resolution of 8 *10⁻⁴ m². The reflectance data was processed in Pix4D Mapper Software (Pix4D SA, Switzerland) and extracted in QGIS v.2.18.6 (QGIS Development Team). The subsequent calculation of vegetation indices (VIs), the fit of linear models between VIs and FM and their evaluation was done with R, Version v.1.0143 (RStudio, 2016).

The same procedure of data sampling and extraction was applied to the validation data measured on six commercial farms (Field (F) 1-6). 10 to 20 sampling spots per field were picked to represent the whole spectrum of present WOSR development.

## RESULTS AND DISCUSSION

The simple ratio NIR/Red was the most sensitive VI to FM, providing an efficient way to calibrate the UAV-reflectance data to the collected data on all sites (Table 1). However it was not possible to transfer this calibration to the data from the commercial farms (Figure 1). Particularly in regard to F1 and F6 the relation between VI and FM was different, perhaps due to special radiation conditions during the reflectance data acquisition. Data from F2-5 correspond fairly well with the calibration although high FM values were underestimated. This could be associated by the low maximal FM achieved at the calibration site (Table 1).

<footnote n="1">¹ Institute for Crop Science and Plant Breeding, Christian-Albrechts-University, Germany</footnote>
<table><caption>Table 1. Number of observations (n), maximal and minimal sampled FM (FM<sub>Min</sub> and FM<sub>Max</sub> in kg m<sup>-2</sup>), root mean squared error (RMSE) of the linear model between NIR/Red and the measured FM and their coefficient of determination (R<sup>2</sup>).</caption><thead><tr><th>Data origin</th><th>n</th><th>FM<sub>Min</sub></th><th>FM<sub>Max</sub></th><th>RMSE</th><th>R<sup>2</sup></th></tr></thead><tbody><tr><td>Calibration Trial</td><td>72</td><td>0.01</td><td>0.89</td><td>0.06</td><td>0.94</td></tr><tr><td rowspan="6">Commercial farm</td><td>F1</td><td>16</td><td>0.32</td><td>1.59</td><td>0.10</td><td>0.92</td></tr><tr><td>F2</td><td>15</td><td>0.32</td><td>2.24</td><td>0.15</td><td>0.94</td></tr><tr><td>F3</td><td>14</td><td>0.41</td><td>1.55</td><td>0.12</td><td>0.96</td></tr><tr><td>F4</td><td>14</td><td>0.14</td><td>1.31</td><td>0.10</td><td>0.92</td></tr><tr><td>F5</td><td>15</td><td>0.15</td><td>1.55</td><td>0.08</td><td>0.96</td></tr><tr><td>F6</td><td>10</td><td>0.12</td><td>0.81</td><td>0.02</td><td>0.99</td></tr></tbody></table>

<figure><img src="image_114.png" /><figcaption>Figure 1. Relationship between the measured FM and the FM estimated by the NIR/Red calibration for the different commercial farms.</figcaption></figure>

## CONCLUSION

First results demonstrate that NIR/Red offers a valuable VI to estimate FM from UAV-based reflectance data. More sampling dates will be included into the calibration and possibly give a hint if it works out for high FM amounts as well. However, ground truth data seem to be necessary to consider for each area separately. Next, the reflection data will be calibrated to N content.

## REFERENCES

* Henke J., Breustedt G., Sieling K., Kage H., 2007. Impact of uncertainty on the optimum nitrogen fertilization rate and agronomic, ecological and economic factors in an oilseed rape based crop rotation. The Journal of Agricultural Science 145 (5), 455-468.

* Henke J., Sieling K., Sauermann, W., Kage H., 2009. Analysing soil and canopy factors affecting optimum nitrogen fertilization rates of oilseed rape (Brassica napus). The Journal of Agricultural Science, 147(1), 1-8.

* Pahlmann I., Böttcher U., Kage H., 2017. Developing and testing an algorithm for site-specific N fertilization of winter oilseed rape. Computers and Electronics in Agriculture 136, 228-237.

* R Development Core Team, 2016. R: A Language and Environment for Statistical Computing.
# IMPACT OF BAND APPLICATION AT 2-5 CM OF PELLETED MEAT BONE MEAL ON WINTER OILSEED RAPE YIELD

ENGSTRÖM, L., DELIN, S.

Swedish University of Agricultural Sciences (SLU), Department of Soil and Environment, Sweden;

## INTRODUCTION

In Sweden pelleted meat bone meal (MBM) is a common fertiliser in organic farming. The way in which organic fertilizers are placed in soil during application can affect the biological turnover of nitrogen (Sørensen & Jensen, 1995; Sørensen & Amato, 2002). Application in bands with a sowing machine achieves a deeper incorporation and also keeps the pellets more concentrated and less mixed with the soil. In this study we wanted to find out if band application of MBM to a certain depth between the rows in spring, compared with broadcasting, would increase yield and N-use efficiency in winter oilseed rape. We also wanted to examine the effect of band application under the row and between rows at sowing compared with broadcasting at sowing.

## MATERIAL AND METHODS

Three experiments were carried out in a hybrid winter oilseed rape (Brassica napus L.) seeded at 25 cm row spacing, on two loam soils and one clay soil in Sweden (58°N, 13°E) during the growing seasons of 2014/2015 and 2016/2017. Eight treatments were randomised into four blocks and involved band application of 80 kg total-N ha⁻¹ as MBM (Ekoväx 8-3-5-3) at 2 and 5 cm soil depths between the crop rows in spring and at sowing band application at 5 cm depth between and under the rows (Table 1). The treatments were compared to surface broadcasting in spring and at sowing, mineral N fertiliser (80 kg N ha⁻¹) in spring and an unfertilised control. Each plot was 0.7 m², sown and fertilized by hand. The two rows in the middle of the plot (0.25 m²) were harvested. The yields in all treatments were compared using General Linear Model one factor analysis in the statistical software Minitab16 (Minitab Inc. 2010).

## RESULTS AND DISCUSSION

On average for three experiments all fertilised treatments except broadcasting in spring gave increased yield compared to unfertilised control. MBM placed in bands at 2 and 5 cm in spring led to 380 kg ha⁻¹ (n.s) and 770 kg ha⁻¹ (p= 0.07) higher grain yield respectively compared with broadcasting, whereas band application at sowing between (p= 0.99) or under the rows (p=0.99) did not increase yield compared with broadcasting at sowing (Figure 1). Compared with the yield effect of mineral N fertilisation in spring, band application at 5 cm at sowing and in spring was 82 and 88 % respectively, band application at 2 cm in spring was 76 %, broadcasting at sowing was 77 % and in spring 67 %. Although mineral N fertiliser in spring had the highest yield, it was not significantly higher than band application at 5 cm (between rows) in spring or at sowing. There were no differences in yield for fertilisation of MBM at sowing compared with fertilisation in spring. The treatments had no impact on plants per m² or weed biomass. In a similar study also performed in small plots (0.7 m²), band application of pelleted MBM at 4-6 cm soil depth and 4 cm from crop row in spring oats, seeded at 25 cm row spacing, more than doubled the fertilisation effect on nitrogen uptake and grain yield compared with broadcasting (Delin & Engström, unpublished).
<figure><img src="image_115.png" /><figcaption>Figure 1. Yield effect in winter oilseed rape of pelleted meat bone meal applied in bands in spring (at 2 and 5 cm depth) and at sowing (at 5 cm depth) compared with broadcasting, no fertilisation and mineral N fertilisation, three experiments 2014/2015 and 2016/2017.</figcaption></figure>

<table><caption>Table 1. Eight treatments of mineral N fertiliser and pelleted meat bone meal (MBM) in winter oilseed rape with a row distance of 25 cm.</caption><thead><tr><th>Treatment</th><th>Application-time</th><th>Fertiliser</th><th>Method of application</th><th>N-rate<br>kg total-N/ha</th></tr></thead><tbody><tr><td>1</td><td></td><td>No N fertilisation</td><td>-</td><td>0</td></tr><tr><td>2</td><td>In spring</td><td>Mineral N fertilisation</td><td>Broadcast</td><td>80</td></tr><tr><td>3</td><td>In spring</td><td>MBM</td><td>Broadcast</td><td>80</td></tr><tr><td>4</td><td>In spring</td><td>MBM</td><td>2 cm soil depth between rows</td><td>80</td></tr><tr><td>5</td><td>In spring</td><td>MBM</td><td>5 cm soil depth between rows</td><td>80</td></tr><tr><td>6</td><td>At sowing</td><td>MBM</td><td>Broadcast</td><td>80</td></tr><tr><td>7</td><td>At sowing</td><td>MBM</td><td>5 cm soil depth between rows</td><td>80</td></tr><tr><td>8</td><td>At sowing</td><td>MBM</td><td>5 cm soil depth, under row</td><td>80</td></tr></tbody></table>

## CONCLUSION

In spring, incorporation of 80 kg total-N ha⁻¹ as pelleted MBM to 5 cm soil depth can have a significant yield effect of +29 % DM yield compared to broadcasting. At sowing, incorporation to 5 cm depth between or under rows had a similar effect on yield as broadcasting. Broadcasting at sowing tended to give a higher yield than broadcasting in spring in these three experiments and two years.

**Acknowledgements:** This study was financed by SLU Ekoforsk.

## REFERENCES

* Sørensen P., Amat M. 2002. Remineralization and residual effects of N after application of pig slurry to soil. European Journal of Agronomy, 16, 81-95.

* Sørensen P., Jensen E. S. 1995. Mineralization-immobilization and plant uptake of nitrogen as influenced by the spatial distribution of cattle slurry in soils of different texture. Plant & Soil, 173, 283-291.
# FIRST ANALYSIS OF THE NITRATE LEACHING RISK FOR DIFFERENT FERTILISERS IN THE PERSEPHONE PROJECT

DAIGNEUX, B.<fnref n="1" />, MOLITOR, N.², GENNEN, J.<fnref n="1" />, DEBBAUT, V.², TSACHIDOU, B.³

## INTRODUCTION

In the context of the Project «Perséphone: Intégration de la filière biogaz dans la nouvelle Bio-économie», financed by the European Regional Development Fund 2014-2020 INTERREG VA «Greater Region», our non-profit association is in charge of five organic and chemical fertilization field trials (2017-2019). This paper is based on the first data collected through 2017 and will present the analysis of the nitrate leaching risk for that year under permanent cut grassland. Koszela et al. (2015) demonstrated the fertilisation capacity of biogas residues, while Odlare et al. (2007) observed that biogas residues enhanced the proportion of metabolically active microorganisms, nitrogen mineralization capacity and had no negative effects on either chemical or microbiological properties of the soil. On the other hand, in a study performed by Wang et al. (2016), the application of biogas residues resulted into increased nitrogen volatilization. Therefore, to study the environmental impact, it is important to estimate soil nitrate leaching risk, especially during autumn, the focus point of this presentation. This study will also help to assess the value of biogas residues as an organic fertilizer and to evaluate its environmental benefits, to compare the impact of each tested fertilizer on the yield, microbial activity and evolution of soil physicochemical properties, and to assess the environmental risk induced by an organic based fertilisation scheme on a permanent mown meadow.

## MATERIALS AND METHODS

In this ongoing field trial, four different fertilisers are tested in three areas (Emmels (Be), Grendel (Be) and Laneuvelotte (Fr)). The fertilizers applied are i) local biogas residues at 350 units of total N/ha, ii) biogas residues of Faascht farm (Grendel, Be) at 230 U of N/ha, iii) local manure at 230 U of N/ha and iv) ammonium nitrate at 230 U of N/ha, which are compared to the unfertilized control (Te) and among each other. Nitrate leaching risk is indicated by mineral N measurement in soils which takes place in February, before fertilizer application, and in October, after the last forage harvest. This is the recommended strategy in Belgium. A high nitrate content in soil will increase the potential nitrate leaching risk. As Vandenberghe cited (2013), during the year, nitrogen measurements are taking place by GxBT of Uliège and UCL to provide reference for the farmers. Soil cores of 90 cm are collected and divided in layers of 0-30, 30-60 and 60-90 cm which subsequently are analysed for nitrate content. For our statistical analysis we used R studio software (R version 3.4.3 (2017-11-30)).

## RESULTS AND DISCUSSION

An ANOVA test performed shows that the risk for nitrate leaching differs in regard to the treatments (p<0.001). The post-hoc Tukey's analysis demonstrates significant differences between variants. This first assessment of nitrogen leaching risk reveals no significant differences between the 2 biogas residues treatments and the control (p<0.05). A similar conclusion has been drawn for the manure variant (p<0.05) though values are slightly higher. On the contrary, the ammonium nitrate variant (230 U of N/ha) shows a significant difference compared to the control (p< 0.001). In addition, the average value of the soil nitrate concentration under the application of ammonium nitrate is considerably higher compared to the rest of the variants, as demonstrated in the figure 1.

<footnote n="1">¹Agra-Ost, Belgium; ²Uliège – Sensing of Atmosphere and Monitoring, Belgium; ³Luxembourg Institute of Science and Technology, Luxembourg</footnote>
<figure><img src="image_116.png" /><figcaption>Figure 4: Box plot of soil nitrate content (kg N-NO₃/ha) after the application of four different fertilizers. Caption: Te = Control, DbF230 = Biogas residues of Fascht farm at 230 U of N/ha, Lbl230 = local manure at 230 U of N/ha, Db350 = local biogas residues at 350 U of N/ha, Na230 = ammonium nitrate at 230 U of N/ha</figcaption></figure>

## CONCLUSION

Our data show that the use of biogas residues and manure do not increase the values of nitrate leaching even at the maximum dose of 350 U of N/ha. In addition, it is important to note that part of the nitrogen present in biogas residues and manure is found in the organic matter. The release of this organic nitrogen depends on ammonification and nitrification. These processes are retroactive in regard of the fertilisation and highly depend on the weather conditions. Organic and mineral fertilisation will continue throughout the following years and the measurements obtained will indicate if the organic matter, present in biogas residues and manure, has the potential to increase or mitigate nitrate leaching risk.

**Acknowledgements:** The presented research was carried out as a part of the research project Interreg VA Grandrégion « Perséphone : Intégration de la filière biogaz dans la nouvelle Bio-économie ». This project is funded with the help of FEDER, German-speaking community of Belgium and Wallonia. Authors also thank all the partners of the project, especially Philippe Delfosse and Bella Tsachidou for their suggestions on the sampling scheme and the constructive discussions.

## REFERENCES

* Koszel, M., & Lorencowicz, E. (2015). Agricultural Use of Biogas Digestate as a Replacement Fertilizers. *Agriculture and Agricultural Science Procedia*, **7**, 119–124.

* Odlare, M., Pell, M., Svensson, K. (2008). Changes in soil chemical and microbiological properties during 4 years of application of various organic residues. *Waste Management*, **28**(7), 1246-1253.

* Wang, L. L., Li, W. Z., Wang, Z. J., Wang, Z. W., Sui, C., & Li, Y. (2016). Effects of digestate application depth on soil nitrogen volatilization and vertical distribution. *International Journal of Agricultural and Biological Engineering*, **9**(5), 101–107.

* Vandenberghe, Christophe; De Toffoli, Marc; Bachelart, Florent; Imbrecht, Olivier; Lambert, Richard, Marcoen Jean Marie;(2013). *Biotechnologie, Agronomie, Société et Environnement; Gembloux, Vol. 17, N° suppl 1, 231-236.*
BIODIVERSITY OF INDIGENOUS RHIZOBIA NODULATING PHASEOLUS VULGARIS IN CROATIA

RAJNOVIC, I.<fnref n="1" />, RAMÍREZ-BAHENA, M.H.²,³, SÁNCHEZ JUANES, F.⁴,⁵, GONZÁLEZ BUITRAGO, J.M.⁴,⁵, KAJIC, S.<fnref n="1" />, PEIX, A.³,⁶, VELÁZQUEZ, E.²,³, SIKORA, S.<fnref n="1" />

INTRODUCTION

Common bean (Phaseolus vulgaris L.) is very valuable and economically important grain legume. It is rich in proteins, fiber and B vitamin and recently, it has been discovered that common bean consumption can contribute to health improvement. However, common bean production in Croatia is limited to small-scale farmers and generally neglected despite favourable environmental conditions. Since it has been recognized that numerous rhizobial species can nodulate common bean, the main aim of this study was to assess genotypic diversity of indigenous rhizobia isolated from soils of Northwestern Croatia.

MATERIAL AND METHODS

Soil samples were collected from 27 different locations in Northwestern region of Croatia. Trapping host method was performed to obtain 45 isolates of indigenous common bean symbionts. The identification of isolates was first performed by Matrix-assisted Laser Desorption/Ionization Time-of-Flight Mass Spectrometry (MALDI-TOF MS) which is based on the characteristic protein profiles for each microorganism. Protein profiles obtained from isolates were compared to those contained in database created in Salamanca University, containing the type strains of all currently described species from the Family Rhizobiaceae (Ferreira et al., 2011). The results of identification by MALDI-TOF MS were further compared to those based on gene analysis. RAPD method was employed to assess rhizobial genetic diversity and to choose representative strains for further analyses of gene sequences. The sequence analysis of 16S rRNA (rrs) and two housekeeping genes, *recA* and *atpD*, was performed to classify isolates obtained from common bean nodules. Since *NodC* gene is the commonly used phylogenetic marker to define symbiovars within species of genus *Rhizobium*, its sequences were analysed to study simbiovars within species of indigenous rhizobia isolated from Croatian soils.

RESULTS AND DISCUSSION

Indigenous rhizobial strains nodulating common bean have been found in the soils of Northwestern Croatia. The results obtained with MALDI-TOF MS methodology showed that the strains from this study matched different species from the *Rhizobium leguminosarum* phylogenetic group with score values higher than 2.0. The results of the RAPD analysis revealed high diversity among indigenous rhizobial strains and the existence of 15 groups with similarity lower than 70 % from which representative strains were selected for core and symbiotic gene analyses. The *rrs* gene sequences analysis showed that all strains from this study belong to genus *Rhizobium* being their closest related species those of the phylogenetic group of *R. leguminosarum*. Similarity values of 100 % were found between 11 strains and *R. leguminosarum* and *R. hidalgonense* and between 1 strain and *R. pisi*. Three other strains, presented similarity values higher than 99 %, but lower than 100 % with *R. leguminosarum*, *R. pisi* and *R. etli*. Nine out of 11 strains that were closely related to the *R. leguminosarum* phylogenetic group were identified as this species after the analysis of the *atpD* and *recA* housekeeping genes. Other two strains were identified as *R. hidalgonense*, a species recently isolated in America from *P. vulgaris* nodules (Yan et al., 2017). One strain belongs to the species *R. pisi*. Two strains formed an independent branch, most closely related to *R. sophoriradicis*, but with similarity values lower than 98 %. One strain formed an independent lineage more closely related to the species *R. ecuadorense*, but the similarity values were lower than 97% indicating that it belongs to a new species. Further research is needed to determine taxonomic affiliation of this strain. The results of the *nodC* gene analysis

<footnote n="1">¹ University of Zagreb Faculty of Agriculture, Department of Microbiology, Croatia; ² Departmento de Microbiología y Genética and CIALE, Universidad de Salamanca, Spain; ³ Unidad Asociada Grupo de Interacción planta-microorganismo (Universidad de Salamanca-IRNASA-CSIC), Spain; ⁴ Instituto de Investigación Biomédica de Salamanca (IBSAL), Spain; ⁵ Departamento de Bioquímica y Biología Molecular, Universidad de Salamanca, Spain; ⁶ Instituto de Recursos Naturales y Agrobiología, IRNASA-CSIC, Salamanca, Spain</footnote>
showed that all indigenous common bean rhizobia from Croatian soils belong to symbiovar phaseoli. This is the first report about the existence of this symbiovar within the species *R. pisi*, which already contains strains from symbiovars viciae and trifolii (Marek-Kozaczuk et al., 2013).

## CONCLUSION

Given that the knowledge about the indigenous population of rhizobia that nodulate common bean in Croatia is very limited, the present study provided an insight into the composition of this group of microorganisms in different soil types of Northwestern Croatia. Further characterization of isolates is needed in order to select the most promising strains for common bean inoculation.

## REFERENCES

* Ferreira L., Sanchez-Juanes F., Garcia-Fraile P., Rivas R., Mateos P.F., Martinez-Molina E., 2011. MALDI-TOFmass spectrometry is a fast and reliable platform for identification and ecological studies of species from family Rhizobiaceae. PLoSONE 6: e20223.

* Yan J., Yan H., Liu L.X., Chen W.F., Zhang X.X., Verastegui-Valdes M.M., Wang E.T., Han X.Z., 2017. Rhizobium hidalgonense sp. nov., a nodule endophytic bacterium of Phaseolus vulgaris in acid soil. Archives of Microbiology 199: 97-104.

* Marek-Kozaczuk M., Leszcz A., Wielbo J., Wdowiak-Wrobel S., Skorupska A., 2013. Rhizobium pisi sv. trifolii K3.22 harboring nod genes of the Rhizobium leguminosarum sv. trifolii cluster. Systematic and Applied Microbiology 36: 252-258.
# SIMULATED NITROGEN DEPOSITION IN TWO ITALIAN BEECH FORESTS EXPOSED TO DIFFERENT CLIMATE CONDITIONS: EFFECT ON SOIL NITROGEN CYCLING

MARCOLINI, G.<fnref n="1" />, GIOACCHINI, P. <fnref n="1" />, MAZZENGA, F. ², D'ANDREA, E. ², RAVAIOLI, D. <fnref n="1" />, MUZZI, E. <fnref n="1" />, MEZZINI, E. <fnref n="1" />, MATTEUCCI, G. ³, MAGNANI, F.<fnref n="1" />.

## INTRODUCTION

Atmospheric deposition of reactive nitrogen can affect many forest ecosystem processes including nitrogen cycling, stand growth, nutrient cycling. The effects of N deposition on Northern and Central European forests have been the focus of a number of studies, both observational and manipulative, but only few data are available for southern areas. We established a manipulative N addition experiment in two Italian beech forests characterised by different levels of background N deposition and climate, with the aim to understand the effects of atmospheric N deposition on forest growth and health and on soil N cycling. Here we report the first results of the ongoing experiment on net N mineralization and net nitrification rates, as measured *in situ* by the resin core incubation technique.

## MATERIAL AND METHODS

The study sites are located (i) in the Cansiglio Forest, in the Veneto pre-alpine region, and (ii) at Collelongo in the Central Appenines, near two intensive monitoring plots of the Italian national long-term forest monitoring program CONECOFOR (Forest Ecosystem Monitoring; part of the Level II ICP Forest network). At both sites, three treatments are compared: (i) a control treatment (CK) without N addition; soil applications of (ii) 30 kg N ha⁻<fnref n="1" /> yr⁻<fnref n="1" /> (N30) and (iii) 60 kg N ha⁻<fnref n="1" /> yr⁻<fnref n="1" /> (N60); at the Cansiglio site a fourth treatment is included, consisting of 30 kg N ha⁻<fnref n="1" /> yr⁻<fnref n="1" /> sprayed above the canopy so as to better simulate atmospheric N deposition and account for canopy interception and uptake (N30canopy). At both sites, each treatment is replicated (N=3) in a complete randomized design. The N treatments started in 2015 and consist on three equal yearly applications of NH₄NO₃ solution during the growing season (July, August and September). Annual net N mineralization and net nitrification rates in the upper 20 cm forest soil and potential N leaching were determined *in situ* by the resin core incubation technique (DiStefano and Gholz, 1986; Vestgarden et al., 2003). Briefly, in each plot six undisturbed soil cores were incubated in open PVC-tubes with an ion exchange resin bag at the bottom so as to capture any ions leaching from the soil. Simultaneously six resin bags were placed on the soil surface, next to the cores, in order to estimate the amount of mineral N entering the tubes, either from fertilization or from atmospheric N deposition. Net N mineralization was calculated as the total mineral N present at the end of the incubation period (soil + bottom resin bag) corrected for N inputs (surface resin bag), minus the mineral N present at the beginning of the incubation. Stand growth was measured by stem circumference bands permanently installed on trees in the central area of plots. Treatment effects were statistically analyzed by analysis of variance (ANOVA). In particular, data from soil N treatments were analysed as in a completely randomized factorial experiment design with two factors: site (two levels: Cansiglio and Collelongo) and N applications (3 levels: 0, 30 and 60) with three replicates. All statistical analyses were performed with RStudio (RStudio Team 2014) using packages "easyanova" and "agricolae".

## RESULTS AND DISCUSSION

At both sites, no significant differences between treatments were observed for annual rates of net N mineralization, which resulted of about 95 and 120 kg N ha⁻<fnref n="1" /> yr⁻<fnref n="1" /> at Cansiglio and Collelongo, respectively. Also annual net nitrification rates did not differ among treatments, nor between sites. They reflected net N mineralization rates, indicating that all the N mineralized was nitrified. The amount of nitrogen collected in the

<footnote n="1">¹ Department of Agricultural and Food Sciences (DISTAL), University of Bologna, Italy; ² National Research Council, Institute of Agro-Environmental and Forest Biology (CNR-IBAF), Italy; ³ National Research Council, Institute for Agricultural and Forestry Systems in the Mediterranean (CNR-ISAFOM), Italy</footnote>
bottom resin trap, which can be viewed as a potential N leaching as it was measured in the absence of plant uptake, increased from approximately 75 to 130 kg N ha⁻¹ yr⁻¹ in response to N addition. At both sites, amounts of N collected in the surface resin traps reflected the N additions and were significantly higher in the N60 treatment compared to the others that, at Cansiglio, did not result significantly different as a result of the large spatial variability. Moreover, at Cansiglio, the amount of mineral N collected in the surface resin traps of the N30canopy treatment represented 54 % of the amount collected in the N30 treatment, suggesting that about half of N aerially applied was intercepted by the canopy. After two years of N addition, no significant differences in stand growth were found among treatments.

## CONCLUSION

These first results seem to indicate that both beech forests, despite the different levels of background N deposition, are not N limited, but rather close to N saturation, a result consistent with the negligible effect of N addition on stand growth. It will be important to continue the experiment, so as to explore the long-term effects on tree growth and N uptake, and assess the real N status of the two beech forests.

**Acknowledgements:** We thank the 'Reparto Biodiversità' of Vittorio Veneto and the 'Nucleo Carabinieri Tutela Biodiversità Pian Cansiglio' for their support in the field work. This work was supported by the MIUR-PRIN Grant 'Global change effects on the productivity and radiative forcing of Italian forests: a novel retrospective, experimental and prognostic analysis'.

## REFERENCES

* DiStefano J.F., Gholz H.L., 1986. A proposed use of ion exchange resins to measure nitrogen mineralization and nitrification in intact soil cores. Commun. in Soil Sci. Plant Anal. 17(9): 989-998.

* Vestgarden L.S., Selle L.T., Stuanes A.O., 2003. *In situ* soil nitrogen mineralisation in a Scots pine (*Pinus sylvestris* L.) stand: effects of increased nitrogen input. Forest Ecology and Management 176: 205-216.

* R Core Team (2014). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL http://www.R-project.org/.
# EFFECTS OF N FERTILIZER FORMS AND SOIL PH ON N₂O EMISSIONS DURING NITRIFICATION

TIERLING, J.¹, LEBENDER, U.¹, BRUECK, H.¹

¹ Research Centre Hanninghof, Yara GmbH & Co. KG, Germany

## INTRODUCTION

Microbial transformations of (mineral) fertilizers on intensively managed agricultural soils are a major source of the greenhouse gas nitrous oxide (N₂O). Besides denitrification of nitrate, nitrifying processes can significantly contribute to N₂O emissions. Lebender et al. (2014) reported differences between urea and ammonium salts, although both N fertilizer forms are subject to nitrification after application. Here we present two incubation experiments comparing effects of different N fertilizer forms under well-aerated, nitrifying soil conditions on N₂O emission rates and nitrogen transformations in the soil.

## MATERIAL AND METHODS

Columns of sandy loam soil (pH = 5.3) were adjusted to a water content of 40% WHC and subsequently fertilized with 82 kg N ha⁻¹ in the form of potassium nitrate (KN), ammonium sulphate (AS), or urea. Columns were incubated in a greenhouse at 20 °C for 21 days. N₂O emissions were measured daily with the closed chamber method. Four gas concentration measurements (gas chromatography (GC)) were taken at 0, 15, 30, 45 min closure time, and gas emission rates were estimated using linear regression analysis. Destructive soil samples were taken 0, 4, 7, 11, 14, and 21 days after fertilization. Soil samples were homogenized and analysed for ammonium and nitrate content with continuous-flow analysis. Nitrite content was determined spectrometrically at 543 nm after the addition if Griess reagent. Soil pH was determined in 0.01 M CaCl₂.

In a second experiment, sandy loam soil was sampled from two treatments of a long-term liming experiment in northern Germany, where pH values differed (5.3 and 6.3). Soil columns fertilized with AS or urea and incubated in a flow-through incubation system, where soil containers are closed during the experiment and continuously flushed with a N₂O-free gas mixture (21% O₂ in He). The gas stream from each container was directed to a GC. The N₂O emission rate was then estimated by multiplying the N₂O gas concentration with the gas mixture flow rate. Additional soil columns were incubated under similar conditions for destructive samplings and soil analysis as described above.

## RESULTS AND DISCUSSION

Both control and KN treatment emitted almost no N₂O, while AS and urea caused N₂O emissions over 21 days (Fig. 1, top). Total N₂O emissions from the urea treatment were almost 4-fold those of the AS treatment (20.8 and 5.4 mg N m⁻², respectively). While no nitrite was detected in the control and KN treatment and only very little in the AS treatment, nitrite was found in the urea treatment during the whole incubation period (Fig. 1, bottom). The addition of NaNO₂ solution to the soil induced N₂O emissions as well (data not shown), implying that the higher nitrite concentrations during nitrification of urea caused the higher N₂O emissions compared to AS (Venterea, 2015).

In the second incubation results for the soil with pH 5.3 were similar to those of the first experiment. Urea fertilization caused 3-fold N₂O emissions compared to AS. However, when the soil pH was raised to 6.3, N₂O emissions from AS and urea were comparable. Soil analysis showed that nitrite accumulated during nitrification of AS at pH 6.3, but not at pH 5.3 as it was also shown in the first experiment. This is in line with findings that nitrite accumulation tends to be promoted by higher soil pH values (Van Cleemput and Samater, 1996).
<table><caption>Table 03: Effect of soil bulk pH and N fertilizer form on N2O emissions and the emission factor (EF) from a loamy sand. The incubation period was 52 days under aerobic conditions. Values are means ± sd (n=3).</caption><thead><tr><th rowspan="2">Soil pH</th><th rowspan="2">N form</th><th>N<sub>2</sub>O</th><th>EF</th></tr><tr><th>mg N m<sup>-2</sup></th><th>%</th></tr></thead><tbody><tr><td rowspan="3">5.3</td><td>None</td><td>0.9</td><td>---</td></tr><tr><td>AS</td><td>16.9<sup>a</sup></td><td>0.22</td></tr><tr><td>Urea</td><td>46.1<sup>b</sup></td><td>0.62</td></tr><tr><td rowspan="3">6.3</td><td>None</td><td>0</td><td>---</td></tr><tr><td>AS</td><td>42.9<sup>b</sup></td><td>0.59</td></tr><tr><td>Urea</td><td>45.6<sup>b</sup></td><td>0.63</td></tr></tbody></table>

<figure><img src="image_117.png" /><figcaption>Figure 1: Nitrous oxide emission rates and soil nitrite concentrations of a loamy sand soil incubated under aerobic conditions after the application of 8.2 mg N m⁻² either as potassium nitrate (KN), ammonium sulphate (AS), or urea. Plots show mean values ± sd (n=6).</figcaption></figure>

## CONCLUSION

We conclude that under non-denitrifying conditions the nitrification of fertilizers can lead to nitrite accumulation, which subsequently significantly increased N₂O emissions, especially at higher soil pH. Compared to AS, urea was even more prone to nitrite accumulation, also at lower pH values, which can be attributed to the alkalising hydrolysis of urea taking place after fertilizer application.

## REFERENCES

* Lebender, U., Senbayram, M., Lammel, J., Kuhlmann, H., 2014. Effect of mineral nitrogen fertilizer forms on N2O emissions from ara ble soils in winter wheat production. J. Plant Nutr. Soil Sci. 177, 722–732.

* Van Cleemput, O., Samater, A. H., 1996. Nitrite in soils: accumulation and role in the formation of gaseous N compounds. Fert. Res. 45, 81–89.

* Venterea, R. T., Clough, T. J., Coulter, J. A., Breuillin-Sessoms, F., 2015. Ammonium sorption and ammonia inhibition of nitrite-oxidizing bacteria explain contrasting soil N2O production. Sci. Rep. 5, 12153.
ESTIMATING WHEAT GRAIN YIELD AND N UPTAKE BY MULTISPECTRAL IMAGING

CORTI, M.<fnref n="1" />, CABASSI, G.², CAVALLI, D.<fnref n="1" />, VIGONI, A.³, ORTUANI, B.<fnref n="1" />, DEGANO, L.², PRICCA, N.², MARINO GALLINA, P.<fnref n="1" />

INTRODUCTION

The innovative use of unmanned aerial vehicles (UAVs) in agriculture has opened new possibilities for crop monitoring. Flights of UAVs equipped with digital cameras can be easily scheduled in order to acquire crop spectral information in the visible and near-infrared regions at different times of crop development. Thereafter, vegetation indices (VIs) can be calculated and used to estimate the within-field variability of crop status (e.g. canopy N concentration). In a perspective of precision farming aimed at maximizing fertilizer-N use efficiency, integrating this information in a decision support system for crop fertilization, or directly estimating N supply rates based on spectral properties of the canopy, requires reliable predictions of spatial variability of crop yield and N uptake (Diacono et al., 2013). We present the results of a one-year field experiment designed to test the performances of two optical VIs for predicting winter-wheat yield and N uptake.

MATERIAL AND METHODS

The experiment was conducted in 2016 in a field of 11 ha located in Sant'Agnelo Lodigiano, Italy (45°13'31.4"N, 9°25'35.8"E). The field was sown in autumn 2015 with winter wheat (Triticum aestivum L., cultivar Basmati). On January 2016, the field surface was scanned using a multi-frequency EMI sensor Profiler-EMP400 (Geophysical Survey Systems Inc.), and three homogeneous areas (i.e. areas having low intra-variability and high inter- variability) were identified based on soil electric conductivity. Within each area, we measured wheat response to N fertilization using three increasing N rates: 0 (N0), 70 (N1) and 140 kg N ha⁻<fnref n="1" /> (N2). Treatments were replicated three times and arranged in a completely randomized block design. Fertilizer addition was split in two top-dressing events: 36% of total N was supplied as NH₄NO₃ on 13 February, and 64% as urea on 18 March. Fertilizers were surface-spread by hand on plots. The remainder of the field was fertilized at 140 kg N ha⁻<fnref n="1" />, according to farm practice. Plants were sampled (0.5 m² plot⁻<fnref n="1" />) on 17 March, 5 and 29 April, corresponding to BBCH growth stages 25, 31 and 45, respectively. Wheat was harvested at maturity (BBCH 99) using a Claas Lexion 570 harvester equipped with a Trimble yield monitoring sensor (Claas KGaA mbH) that provided a grain yield map (5 m × 5 m grid) of the whole field. The same days of plant sampling, we acquired multispectral images of the field using a MicaSense RedEdge™ camera (MicaSense Inc.) mounted on an unmanned coaxial octocopter. After radiometric calibration and image stitching (Pix4D software), the normalized difference vegetation indices based on the red (NDVI) and red-edge (NDRE) bands were calculated. Linear-plateau models were used to predict with the two VIs, wheat N uptake at the three sampling dates (using measurements taken in plots) and final grain yield (using estimates provided by the harvester for the whole field). One-way ANOVAs were performed, separately for each area and date, to test the statistical effect of N rate on N uptake.

RESULTS AND DISCUSSION

Wheat responded positively to N fertilization in all areas and in all sampling dates (Figure 1a). However, differences in N uptake were marked and significant (*P* < 0.05) only between N2 compared to N0. On average, N uptake was clearly lower in area 3 compared to others (not tested for significance with ANOVA), suggesting that factors other than N, further limited crop development in this area (likely a limited water availability as a consequence of a light texture and low organic matter content).

<footnote n="1">¹ Department of agricultural and environmental sciences – Università degli studi di Milano, Italy; ² Consiglio per la ricerca in agricoltura e l'analisi dell'economia agraria – CREA-ZA, Italy; ³ Sport turf consulting, Italy</footnote>
<figure><img src="image_118.png" /><figcaption>Figure 1. Relationship between VIs and plant N uptake measured in experimental plots (a) and grain yield measured in the whole field (b). Continuous black line: model fit using a linear-plateau model; symbol "x": plots belonging to area 3.</figcaption></figure>

Regressions between VIs and N uptake (Figure 1a) and grain yield (Figure 1b) were satisfactory modelled with linear-plateau functions, as confirmed by low Relative Root Mean Squared Errors in the range 4-12% for N uptake and 3-8% for grain yield. Plateaus of NDRE-based models occurred at higher N uptake or grain yield levels compared to those based on NDVI. The larger range of linearity in the response for NDRE suggests its use for N uptake estimation instead of NDVI. This consideration is further supported by considering that variability obtained in plots (VIs in Figure 1a) was higher than that observed at field level (VIs in Figure 1b in the range of those of N2 in Figure 1a), because the entire field was fertilized at the same N2 rate. Therefore, N uptake measured in N2 plots (Figure 1a) belonged to a linear-response range for NDRE, while for most of NDVI-based models it belonged to the flat response range, especially at earlier crop growth stages (BBCH 25 and 31).

## CONCLUSION

This experiment demonstrated that VIs could be satisfactory used to predict early-mid season wheat N uptake and final grain yield. However, regression models obtained in this study require additional validation in order to get more robust estimations of model parameters. Thereafter, model predictions of early-mid season wheat N uptake can be used to feed decision support systems for crop fertilization. Alternatively, robust statistical models can be directly used to predict final grain yield, and thus calculate the amount of fertilizer N required.

## REFERENCES

* Diacono M., Rubino P., Montemurro F., 2013. Precision nitrogen management of wheat. A review. Agron. Sustain. Dev., 33, 219-241.
# EFFECT OF MODIFYING ROOT DISTRIBUTION ON GROWTH OF WHEAT AND NET NITROGEN BUDGETS

BUCKINGHAM S, JONES S, CRAWFORD C, BINGHAM I J

SRUC, West Mains Road, Edinburgh, UK

## INTRODUCTION

Temporary net nitrogen (N) immobilisation by soil microbes, driven by carbon (C) deposition from crop roots, is considered to contribute to the poor recovery of applied fertilizer N in UK wheat production systems. Improved understanding of N transformations and their response to soil C additions will help optimise N use efficiencies. The objective was to determine the scope for modifying root distribution between topsoil and subsoil to reduce N immobilisation without reducing N uptake. A split-root technique was used to vary the number of seminal root axes in the topsoil and subsoil.

## MATERIALS AND METHODS

Topsoil and subsoil was collected following spring barley harvest at Boghall Farm (Edinburgh, Scotland). Soils were sieved (4mm) and packed into adjoining PVC conduits to a bulk density of 1.2 g cm³. Topsoil (30 x 7.2 x 4.0 cm) and subsoil (30 x 9.7 x 5.8 cm) conduit dimensions represented a realistic soil volume to plant ratio based on a typical density of 330 spring wheat plants/m² and a topsoil and subsoil depth of 30 and 60 cm respectively. Spring wheat (cv Tybalt) seedlings were planted into the subsoil compartment following germination (7 days prior to planting). Seminal roots were guided manually into the topsoil through a small hole (9mm in diameter and 1cm in length) between the subsoil and topsoil compartments to give treatments of 0, 1, 2, 3, 4 and 5 seminal roots in the top soil, with the remainder of roots in the subsoil compartment. Plants were grown in a controlled environment chamber set to 16 hours light (20°C, 80% relative humidity) and 8 hours dark (15°C, 60% humidity). Soil moisture was maintained at 20% and 18% field capacity for top- and sub-soil respectively. All topsoil compartments received 25kg SO₃/ha applied as K₂SO₄ and plants received two foliar applications of Mn. Nitrogen was applied as ammonium nitrate to the topsoil (no N added to the subsoil) at a rate equivalent to 130 kg N/ha with a third being applied at the 2-3 leaf stage (unlabelled N) and two thirds injected uniformly throughout the topsoil as ¹⁵NH₄¹⁵NO₃ at flag leaf emergence. Half of the replicated treatments were deconstructed 30 minutes after ¹⁵NH₄¹⁵NO₃ injection (T0) with the second half of replicates deconstructed 14 days after ¹⁵NH₄¹⁵NO₃ application at anthesis (T100).

## RESULTS AND DISCUSSION

Figure 1 shows little difference in shoot dry-weight at anthesis between treatments with one or more seminal roots in the topsoil demonstrating that providing there is at least one seminal root present the overall growth of spring wheat can be sustained. However, shoot growth was reduced by more than 50% when there were no roots in the topsoil (R0) and plants relied solely on subsoil conditions and nutrient supplies.

Root dry weight in the top soil at anthesis increased with increasing seminal root number up to treatment R0 (P<0.05 Figure 2a) but differences in root length across topsoil treatments were smaller (P>0.05 Figure 2b). Increases in lateral root branching led to increases in root length and, to a lesser extent, root DW per seminal root when numbers in the topsoil were low. Topsoil roots appeared to respond to nutrient deficiencies of the subsoil through compensatory adjustments in growth. The adjustments were largely established before the ¹⁵N fertilizer was applied. As a result, the initial variation in seminal root distribution had little effect on ¹⁵N uptake from the top soil or N immobilisation.
<figure><img src="image_119.png" /><figcaption>Figure 1. Spring wheat dry weight across treatments of 0 to 5 seminal roots in the topsoil</figcaption></figure>

<figure><img src="image_120.png" /><figcaption>Figure 2a and 2b. Topsoil root dry-weight (a) and root length (b) in relation to treatments (R0 to R5)</figcaption></figure>

## CONCLUSION

Preliminary results suggest that due to the plasticity of root systems, there may be relatively little scope for reducing root length density to any significant extent in the topsoil by modifying the distribution of seminal roots. There was no evidence of any significant immobilisation using soil mineral N and N uptake measurements. The N depletion from the nitrate pool between T0 and T100 was equivalent to the N uptake by plants in all treatments except the zero root treatment. Fertilizer uptake (¹⁵N) was less than total N uptake indicating that other sources of N were captured, which may be because the ¹⁵N fertilizer was diluted by the soil nitrate pool at the time of application. There was little difference in percent recovery at T0 and T100 which shows that further loss of ¹⁵N did not occur between T0 and T100. As a consequence opportunities for increasing fertilizer N recovery by reducing rhizodeposition of C and N immobilisation by this means may be limited.

**Acknowledgements:** This study was conducted as part of Work Package 2 activities in BBSRC funded project N-Circle.
# COMPOUND-SPECIFIC <sup>15</sup>N STABLE ISOTOPE PROBING TO PROVIDE NOVEL INSIGHTS INTO THE RESPONSE OF BACTERIAL AND FUNGAL COMMUNITIES IN SOIL TO FERTILISER

REAY, M.K.¹, JONES, D.L.², EVERSHED, R.P.¹

¹Organic Geochemistry Unit, University of Bristol, UK; ²Environment Centre Wales, University of Bangor, UK

## INTRODUCTION

Organic nitrogen (ON) concentrations tend to exceed the inorganic N pool in soils by an order of magnitude, yet nitrogen cycling in this complex pool is poorly understood. <sup>15</sup>N compound-specific stable isotope probing (SIP) techniques have been used to improve the understanding of N-cycling by tracing <sup>15</sup>N-additions through the active microbial community using amino acids (Charteris et al., 2016). This work has provided vital insights into the incorporation of inorganic fertiliser into ON in soil at the molecular level. However, amino acids are ubiquitous to all soil organisms therefore it is not possible to differentiate between bacterial and fungal assimilation of fertiliser using compound-specific stable isotope analysis (CSIA) of <sup>15</sup>N-enriched amino acids.

Amino sugars (AS) are the second largest defined pool of ON in soils (5 to 12 %). It is possible to separate the <sup>15</sup>N-immobilisation dynamics of fungal and bacterial pools due to the different origins of AS and elucidate their relative contributions in N utilisation (He et al., 2011). This offers an insight into the roles different soil microorganisms play in the soil N-cycle as they occupy different ecological niches. Therefore, the application of a novel GC-C-IRMS method for the analysis of <sup>15</sup>N-enriched amino sugars, as described here, provides the opportunity to differentiate between microbial responses of bacteria and fungi to inorganic fertiliser.

## MATERIAL AND METHODS

### Incubations

Laboratory incubations were carried out by Charteris et al. (2016). In short, soil, sampled from the Rowden Moor Experimental Site (Devon, UK), was homogenised and adjusted to 50 % water holding capacity (WHC). Soil microcosms (10 g soil) under aerobic conditions were treated with 10 atom % <sup>15</sup>N-ammonium chloride (<sup>15</sup>NH<sub>4</sub>Cl, 190 kg N ha<sup>-1</sup> yr<sup>-1</sup>), <sup>15</sup>N-potassium nitrate (K<sup>15</sup>NO<sub>3</sub>; 100 kg N ha<sup>-1</sup> yr<sup>-1</sup>) or DDW (for control samples). Incubations were carried out in triplicate and halted after incubation at 20°C over 32 days, frozen and freeze-dried.

### Extraction, isolation and derivatization of hydrolysable amino sugars

Freeze-dried incubation soil samples (400 mg) were acid hydrolysed under N<sub>2</sub> and *N*-methylglucamine added as an internal standard (IS). Soil hydrolysates were collected under centrifugation and amino sugars were isolated using cation-exchange chromatography. AS were then converted to their alditol acetate derivatives in a method adapted from Whiton et al. (1985).

### Instrumental Analyses

Bulk soil δ<sup>15</sup>N analyses were carried out at the Lancaster Node of the NERC LSMSF (Charteris et al., 2016). Quantification of individual amino sugars as their alditol acetate derivatives were carried out using gas chromatography, by comparison to the IS. The δ<sup>15</sup>N values of individual alditol acetate derivatives of AS were determined using GC-C-IRMS. δ<sup>15</sup>N values were determined relative to that of a monitoring gas of known isotopic composition and instrument performance was monitored using in-house AS standards which bracketed each sample.

## RESULTS AND DISCUSSION

Bulk soil δ<sup>15</sup>N values determined in Charteris *et al.* (2016) indicated an initial increase following <sup>15</sup>N-addition but subsequently remained relatively constant for the remainder of the incubation, with high percentage retention.
This demonstrates the limitations of bulk N determinations to detect the mechanisms and mediators of processing of ¹⁵N-addition in soil. Likewise, determinations of hydrolysable amino acid (HAA) concentrations showed no significant changes during incubation. However, compound-specific ¹⁵N-AA analyses allowed the assimilation of added fertilizer-N to be traced quantitatively into the newly synthesized protein pool. Here, for the first time, assimilation of different N fertilizer into the soil ON pool was quantitatively assessed.

In this new work we now consider the partitioning of substrate N between the bacterial and fungal pools. This has required the development of a new analytical approach to allow the determination of ¹⁵N individual amino sugars. The modified alditol acetate approach offers advantages over the existing methods (aldononitrile) by avoiding the use of a derivative that introduces exogenous N into the amino sugars during sample preparation. Using both CSIA of amino acids and amino sugars we will provide insights into both the biochemical routing of ¹⁵N following assimilation of inorganic fertilizer and differing ¹⁵N-immobilisation dynamics within the microbial pool. The hypothesis is that the bacterial community will initially outcompete fungi in the assimilation of applied ¹⁵N inorganic fertiliser; however, fungi will dominate assimilation of ¹⁵N later in the incubation period. This will be reflected by rapid ¹⁵N-incorporation into muramic acid (MurN found in peptidoglycan) as will bacterial derived glucosamine (GluN). The bacterial and fungal derived GluN can be separated using known ratios (He et al., 2011) and the fungal derived GluN will exhibit slower ¹⁵N-assimilation.

<figure><img src="image_121.png" /><figcaption>Figure 1</figcaption></figure>

Figure 1: Hypothetical δ¹⁵N values of amino acids (LHS) and amino sugars (RHS) relative to the bulk soil δ¹⁵N resulting from incubation with ¹⁵N-fertiliser.

## CONCLUSION

We will describe a new CSIA approach to investigate dynamics of ¹⁵N-assimilaiton within the microbial pool. The development of the CSIA ¹⁵N-SIP approach for amino sugars will provide insights into the different temporal response of bacteria and fungi to fertiliser application. Combined, this investigates the dynamics of the active microbial community at a molecular level for the two largest defined N pools present in soil.

**Acknowledgements:** Soil incubations were carried out during A.F. Charteris' UK NERC Open CASE PhD studentship (NE/J017523/1). We thank NERC for partial funding of the mass spectrometry facility at Bristol (Contract No. R8/H10/63) and the UK NERC LSMSF (Lancaster node; H. Grant) for bulk soil N isotopic analysis.

## REFERENCES

* Charteris, A. F., Knowles, T. D. J., Michaelides, K. and Evershed, R. P., 2016. RCM, 30, 1846–1856.

* He, H., Zhang, W., Zhang, X., Xie, H. and Zhuang, J., 2011. Soil Biol. Biochem., 43, 1155–1161.

* Whiton, R. S., Lau, P., Morgan, S. L., Gilbart, J. and Fox, A., 1985. J. Chromatogr. A., 347, 109–120.
# LONG TERM EFFECT OF NPK AND MANURE FERTILISATION AND CROP/GRASS ROTATIONS ON SOIL C AND N AND PLANT N CONCENTRATIONS

PALMBORG, C.<fnref n="1" />, CARLSSON, G. ², ALBERTSSON, J.² JENSEN, E.S.²

## INTRODUCTION

Cultivation of perennial crops such as grass-clover leys and use of animal manure have been suggested as general measures to enhance carbon sequestration in soil, which have many benefits for the cropping system and society such as greater yields, reduced need for fertilizers, mitigation of climate change and enhancing adaption to climate change. In Umeå, northern Sweden, a long-term experiment (LTE) where fertilization and crop rotation are separate factors has been conducted since 1965. This LTE makes it possible to determine both fertilization and crop rotation effects on soil C and N storage as well as plant N, unlike most Swedish long-term experiments where the use of animal manure is restricted to treatments with perennial ley in the crop rotation.

## MATERIAL AND METHODS

The Umeå site has silty soil. It is a former wetland and the C content at the start of the LTE was 5.3%. From 1965 to 2010, the six crops: grass/clover ley (GC), barley, fodder rape, potatoes, annual ryegrass and oats, were either grown in monocultures or in crop rotations. There were two six-years rotations: Mixed rotation (reference): barley undersown with two years GC ley- fodder rape- potatoes- annual ryegrass and Long ley rotation: barley undersown with five years GC ley. There was also one three years rotation: Short grain rotation: barley- barley- oats. There were two replicate plots of each treatment and six replicate plots of reference rotation where each crop was represented in one plot every year. The GC ley was harvested twice per year, annual ryegrass three times per year and the other crops once per year. There were also three different fertilization treatments as sub-plots in a split plot design: Low NPK, which replaced nutrient removal in the harvests, High NPK = twice the Low NPK dose and Solid cattle manure+NPK- 10 tonnes per ha of cattle manure+ complementary NPK to reach the total amounts of nutrients added in Low NPK. Soil tillage management was conventional plowing and harrowing. Results presented here focus on soil C and N changes (2010 vs 1965) and possible treatment effects on plant N content for short GC ley and annual ryegrass (2002-2003).

### Sampling and analysis

Top-soil samples (0-20 cm) from all treatments in 2010, that had been stored dry, were milled in rolling bottles with steel rods after removal of visible roots. Four randomly selected samples of top soil from 1965 were also analysed since another analysis method for soil C was used at that time. The homogenised samples were analysed for %C and %N with an elemental analyser (DeltaV, Thermo Fisher Scientific, Bremen, Germany). Dry stored plant samples from the first harvest 2001-2006 of grass/clover and annual ryegrass were ball milled to a fine powder and analysed for %N at the same mass spectrometer. All statistical analyses were made in NCSS 8 (Hintze 2012) and details are given in the results sections.

## RESULTS AND DISCUSSION

### Nitrogen and carbon concentration in soil

All treatments had lower top soil C and N concentrations in 2010 compared to 1965 (soil N content in figure 1). The soil data were analysed by General Linear Model ANOVA. Fertilization was considered a random factor, Crop rotation a fixed factor, and their interaction was included in the model. There were no significant differences between fertilization treatments in the final top soil C or N, thus the cattle manure addition had no effect on carbon sequestration. Thus, to avoid pseudo-replication, the means of the three fertilisation treatments were

<footnote n="1">¹ Department of Agricultural Research for Northern Sweden, Swedish University of Agricultural Sciences, Umeå Sweden; ² Department of Biosystems and Technology, Swedish University of Agricultural Sciences, Alnarp, Sweden</footnote>
calculated and used for further analysis with one way ANOVA. Long term ley had significantly higher soil %C (p=0.038) and %N (p=0.022) than all other crop rotations. It was noted that Monoculture barley and Short grain rotation had amongst the lowest treatment means of soil %N although they were not significantly different from the other rotations with annual crops (Figure 1).

<figure><img src="image_122.png" /><figcaption>Figure 1. Topsoil nitrogen and carbon after 45 years of monocultures or mixed crop rotations. Means of all fertilization treatments. The line at the top represents the mean %N in 1965 at the start of the experiment.</figcaption></figure>

## Effect of crop rotations and fertilisation on nitrogen content of grass-clover ley

The GC ley in the Long ley rotation was established in 2001, and thus directly comparable to the two year GC ley in the Mixed crop rotation in 2002 and 2003. Separate analysis was made for these years. There was a significant effect of fertilization (p=0.004) and year but no significant differences between crop rotations although there were differences in soil %C and %N between crop rotations. The High NPK treatment resulted in 2.08%N in the GC ley, higher than in the Low NPK treatment (1.74% N) but not significantly higher than the Manure+NPK treatment (1.79%N). There were no significant differences due to fertilization treatment in the annual ryegrass monoculture crop.

## CONCLUSION

At the Umeå site which had high soil C and N concentrations at the start of the experiment, a Long ley rotation with barley undersown with grass-clover ley renewed every six years prevented about half of the decrease of the soil C and N concentrations compared to pure grain crop rotations or annual ryegrass. However this did not affect plant N content that was more dependent on the NPK-fertilization.

**Acknowledgements:** This study was made possible by the SITES Research station Röbäcksdalen that is partly financed by the Swedish Research Council. The study was financed by Formas within the ERA-net project Climate CAFE (Formas project number 155-2014-1744).

## REFERENCES

Hintze, J. (2012). NCSS 8, NCSS, LLC, Kaysville, Utah USA.
# CLIMATE AND MANAGEMENT EFFECTS ON N₂O EMISSIONS FROM TWO CROP SITES IN THE SOUTHWESTERN FRANCE

BIGAIGNON, L.¹, LE DANTEC, V.¹, ZAWILSKI, B.¹, GRANOUILLAC, F.¹, CLAVERIE, N.¹, BRUT, A.¹, CESCHIA, E.¹, MORDELET, P.¹, TALLEC, T.¹

¹ Centre d'Etudes Spatiales de la BIOsphère (CESBIO), France

## INTRODUCTION

Nitrous oxide (N₂O) is an important greenhouse gas (GHG) with a high global warming potential, around 300-fold higher than CO₂ for an approximate residence time of 120 years in the atmosphere (IPCC, 2013). Agricultural soils represent the highest anthropogenic source of N₂O emissions due to bacterial degradation of nitrogen fertilizers. In France, 51% of agricultural GHG emissions are related to N₂O emissions. In the context of global change, the objective is twofold: to satisfy food production to meet the growing demography needs and to reduce the environmental footprint of agricultural practice for a sustainable agriculture. N₂O emissions are related to physico-chemical parameters which depend on climate (temperature, rain...), soil texture (Robertson et al., 1989) and farming practices (irrigation, tillage, fertilizer type and quantity...) (Tellez-Rio et al., 2015). Given this context, it is essential to evaluate climatic variability and management interaction effects on N₂O fluxes in using long time series of flux measurements to highlight practices producing low N₂O emissions. In this on-going project we propose to analyze the effects of climate and contrasted management on N₂O fluxes monitored for five years over two crop sites in the south-west of France.

## MATERIAL AND METHODS

### Sites description

N₂O flux measurement were carried out between 2012 and 2016 on two crop sites near Toulouse in the South-West of France, Lamasquère (FR-Lam) and Auradé (FR-Aur). Both sites are part of the European research infrastructure consortium ICOS (Integrated Carbon Observation System) and of the Regional Spatial Observatory (OSR). The mean annual rain and air temperature are 680 mm and 12,6°C respectively. Both sites experience similar meteorological conditions but have different management, soil properties and topography. FR-Lam site is flat with a high water table depth. At FR-Aur site, there is a gentle slope (2%) with a very low water table depth. The FR-Aur plot belongs to a cereal production farm (only grain is exported), whereas the FR-Lam plot belongs to a dairy farm (all aboveground biomass is exported). Only mineral fertilization is applied at FR-Aur, whereas at FR-Lam both mineral and organic fertilizers are applied. Crop rotations on both sites are representative of the main regional crop rotations: winter wheat – irrigated maize at FR-Lam; wheat – rapeseed – sunflower – winter wheat at FR-Aur. The soil is classified as clayey at FR-Lam site and as clay-loam at FR-Aur site.

### Chamber methodology for N₂O flux measurement

On each site, flux measurements were performed using a set of 6 closed automated chambers (70cm x 23cm x 10cm) coupled to an infrared gas analyzer, the Thermofisher Scientific 46i (relative accuracy of ± 20 ppb). The set up allowed measuring the potential N₂O accumulation during 17.5 minutes four times a day every 6 hours (00:00, 06:00, 12:00, 18:00 UTC) inside each chamber alternatively. N₂O fluxes (gN.ha⁻¹.day⁻¹) were then calculated following Tallec et al. (submitted). The data were fitted with an exponential rise regression model.

### Soil variable measurement

Soil water content and temperature were measured at 0-7 cm depth at hourly step using a probe (ThetaProbe, ML2x, Delta-T Devices Ltd., UK) and T107 captors (Campbell Scientific Ltd., UK) respectively.

## RESULTS AND DISCUSSION
The preliminary results highlighted that N₂O fluxes followed a clear seasonal dynamic related to WFPS, soil temperature and potential mineral nitrogen availability dynamics (data not shown). In the year 2012, a large peak of N₂O emissions (higher than 150 g N-N₂O ha⁻¹ day⁻¹) appeared consecutively to a heavy rain event (87 mm in 4 days) between 19 and 22 May 2012 (Figure 1), which increased WFPS from 46 ± 8 % to more than 65 ± 11 % (data not shown). At the same time, high amount of nitrate was available following spring mineralization (data not shown). N₂O fluxes remained high from 22 May to 2 June, with mean emissions of 114 g N-N₂O ha⁻¹ day⁻¹. Slurry application on 7 September led to an immediate peak of N₂O emission, reaching a maximum of about 220 g N-N₂O ha⁻¹ day⁻¹ that lasted no more than six days. Despite the positive effect of irrigation on the WFPS between mid-July and mid-August, N₂O fluxes remained mostly low, probably because of reduced mineral nitrogen availability combined with lower soil temperature than in May (data not shown). Background emissions observed and calculated from 10 to 21 May and from 4 to 7 July achieved a mean value of 13.3 ± 1.6 g N₂O-N ha⁻¹ day⁻¹ (Figure 1). The study is still in process and the future work on other years would allow analysing in details respective effect of climate and management on N₂O fluxes. At this stage, we would expect less N₂O emissions at FR-Aur than at FR-Lam site partly due to split application of nitrogen fertilizer and the water table depth difference.

<figure><img src="image_123.png" /><figcaption>Figure 5. Daily dynamic of N₂O emissions from a maize crop at FR-Lam site during the year 2012: sowing on 27 April, harvest on 23 August, fertilizer: 110 kg N.ha⁻¹ on 30 May and 120 kg N.ha⁻¹ as manure on 4 September.</figcaption></figure>

## CONCLUSION

The long time series of N₂O fluxes measured for five years on two contrasted cropping system offer the unique opportunity to better understand and determine impact of environmental variables, themselves modulated by climate variability, soil properties, topography and agricultural practices, on soil GHG emissions in the southwestern France. This ongoing project is expected to highlight the agricultural practices which could reduce N₂O emissions.

## REFERENCES

* IPCC, 2013. Climate Change 2013: The Physical Science Basis. Cambridge University Press, Cambridge.

* Robertson et al., 1989. Aerobic denitrification in various heterotrophic nitrifiers. Antonie van Leeuwenhock., 56, 289-299.

* Tallec et al., N₂O flux measurements over an irrigated maize crop: a comparison of three methods. Submitted to Agr. Forest Meteorol.

* Tellez-Rio et al., 2015. N₂O and CH₄ Emissions from a Fallow-wheat Rotation with Low N Input in Conservation and Conventional Tillage under a Mediterranean Agroecosystem. Sci. Total Environ., 508, 85-94.
# ANALYZING AND MODELING THE VARIABILITY OF SOIL ORGANIC NITROGEN MINERALIZATION FROM FIVE YEARS OF FIELD MEASUREMENTS

BEFF, L.<fnref n="1" />, LAMBERT, Y.², GERMAIN, P.<fnref n="1" />, LOUIS, B.³, MARY, B.⁴, BEAUDOIN, N.⁴, MORVAN, T.<fnref n="1" />

## INTRODUCTION

Optimizing nitrogen (N) fertilization requires correctly predicting the amount of N resulting from soil organic N mineralization, crop usable, which can vary greatly depending on climatic conditions, soil properties and cropping system. While many studies were realized to evaluate the impact of soil properties, soil temperature or water content, few studies integrated the cropping system. We therefore conducted field experiments during five years in Brittany to study the effect of this three factors and especially the cropping system on soil N mineralization, and propose a predictive model.

## MATERIAL AND METHODS

Experiments were performed for five years (2010-2014) on 67 maize cultivated fields located throughout Brittany, France. The fields were chosen to cover a wide range of soil types under different management systems (crop rotation and manure supply) and climatic conditions. Soil net N mineralization (Mn) was calculated from mineral N mass-balance: $Mn = Nf - Ni + N_{uptake} + N_{leached}$, with: (i) $Nf - Ni$ corresponding to the difference in soil mineral (0-90 cm) N content at the end, $Nf$, (October) and at the beginning, $Ni$, (March) of the mass-balance period (kg N ha⁻<fnref n="1" />); (ii) $N_{uptake}$ corresponding to N uptake by the plant (kg N ha⁻<fnref n="1" />); (iii) $N_{leached}$ corresponding to nitrate leaching that occurs in spring, after $Ni$ measurement (kg N ha⁻<fnref n="1" />) and was estimated using the STICS model (Brisson et al., 2008). We extracted the effect of climate on mineralization by converting calendar time into normalized time (tn). We used the functions described by Brisson et al. (2008) to model effects of temperature and soil water content on N mineralization. Mn was normalized by dividing it by tn for each year and field, which gives a daily 'normalized' rate of mineralization, Vn (kg N ha⁻<fnref n="1" /> tn⁻<fnref n="1" />). Because fields were unfertilized, without input of fresh organic matter and bare soil during winter, we assumed that Mn corresponds to mineralization of stable organic N for the three last years of experiment, i.e. after stabilization of the system. With this assumption, we are allowed to suppose that Vn was similar for the three last measurement years, for a given field, and therefore equaled the potential N mineralization rate of the soil.

The soil of the upper layer (0-30 cm) was sampled in March 2013 to estimate some soil properties (e.g. texture, C and N content, CEC, pH), microbial biomass and an indicator of mineralization with a phosphate-borate buffer, EON (Gianello and Bremner, 1988). An indicator of the cropping system ($I_Sys$) was calculated to estimate effects of field management (crop rotation and manure application) on N mineralization for the 15 years before the beginning of the experiment. $I_Sys$ was calculated by summing (i) N return to the soil by plants and (ii) effects of repeated manure applications in the middle term. To assess impacts of $I_Sys$ on N mass balance and soil N mineralization, we classified its values into three levels using the K-means method: low (≤ 67 kg N ha⁻<fnref n="1" />), moderate (67-104 kg N ha⁻<fnref n="1" />) and high (> 104 kg N ha⁻<fnref n="1" />).

## RESULTS AND DISCUSSION

Mean Mn from March to October equaled 162, 146 and 154 kg N ha⁻<fnref n="1" /> in 2012, 2013 and 2014, respectively. Mn was thus relatively similar in all three years. The level of $I_Sys$ had a significant effect on the **3 years averaged values** of $N_{uptake}$, Mn and Vn (P<0.01). We also observed a significant effect of $I_Sys$ on the **annual average values** of Vn (P < 0.05) (Figure 1a).

Vn allows for comparison of soil N mineralization between years and fields and therefore highlights effects of the

<footnote n="1">¹ UMR SAS, AGROCAMPUS OUEST, INRA 35000 Rennes, France ; ² Chambre d'agriculture de Bretagne, Rennes, France ; ³ Statisticien indépendant, Beaumont, France ; ⁴ INRA, UR1158 Agro-Impact, Laon, France</footnote>
cropping history and soil properties on soil N mineralization. The averaged Vn values for the 3 years (Vn<sub>mean</sub>) was highly correlated with EON (r=0.48, P<0.001), microbial biomass (r=0.45, P<0.001) and I_Sys (r=0.39, P<0.001). The significant and positive correlation between Vn<sub>mean</sub> and I_Sys confirms and highlights the need to take into account effects of cropping system at a middle-term scale (15 years in the current study). However, individual correlations are not sufficiently high to satisfactorily explain the variability in Vn for this dataset.

We then applied Kruskal-Wallis test to identify the fields for which we could accept the hypothesis of equal values of Vn, for the 3 years. This hypothesis was accepted for 43 fields (P< 0.05), allowing us to consider that tn explained well the N mineralization variability between the 3 years, for these fields. We then considered that Vn<sub>mean</sub> corresponded to the best estimate of the mineralization of the field, and the modeling approach was developed on this subset of 43 fields. The variable and their form (linear, quadratic or polynomial of degree 2 or 3) were selected by the minimization of the MSEP for a GAM model (Wood 2006). The selected variables were EON, microbial biomass, I_Sys, clay, coarse sand, coarse silt. Because EON and microbial biomass were the two variables that correlated best with Vn<sub>mean</sub> and were poorly correlated between them, they gave complementary information. The predictive quality of the model (r<sup>2</sup>=0.71) was quite comparable to the performance of the best models found in the literature (Figure 1b).

<figure><img src="image_124.png" /><figcaption>Figure 1: (a) Effect of the level of I_Sys on Vn. The data were averaged for the fields belonging to the same crop level by year and for all the 3 years (mean). Significance of the level of crop system obtain with Kruskal-Wallis test is given at the bottom of each subplot with "*" for p.value < 0.05, "**" for p.value < 0.01. (b) Comparison of Vn<sub>mean</sub> and that predicted by the model for the 43 fields. The dashed line indicates the 1:1 line.</figcaption></figure>

CONCLUSION

With five years field measurements, we evaluated the variability of soil N mineralization and highlight the importance of the cropping system on this variability. For that, we developed an indicator of the cropping system. This indicator combined with an EON indicator, microbial biomass and soil texture allowed an accurate prediction of the normalized soil N mineralization rate (Vn) for the Brittany region.

**Acknowledgements:** This work was financially supported by AELB, CRB, DRAAF, CG 22, CG 29 and CG 56.

REFERENCES

Brisson, N., Launay, M., Mary, B., Beaudoin, N., 2008. Conceptual Basis, Formalisations and Parameterization of the STICS Crop Model. INRA, Rd 10, 78026 Versailles Cedex, France, Editions Quae.

Gianello, C., Bremner, J. M., 1988. A rapid steam distillation method of assessing potentially available organic nitrogen in soil. Communications in Soil Science and Plant Analysis, 19(14): 1551-1568.

Wood, S. N., 2006. Generalized additive models: an introduction with R. Boca Raton, Florida, U. S. A., Chapman.