$N_{\text{ammoniacal}}$: 1.99 kg/m³, dry matter: 3.23% and volatile solids: 59.5%.

## *Uncovered lagoon*

Average $NH_3$ emission ranged between 0.33 and 0.50 mg/m²/min and didn't vary during the three days of measurements (P>0.05).

Emission level was below the values previously reported in scientific literature. It might be related to the low ventilation rate applied in this study (2.5 l/min).

The coefficient of variation of the average emission rates varied between 42 and 47%, due to the spatial and temporal heterogeneity of the emissions.

Concentrations up to 132 mg $NH_3$/m³ were measured at fresh digestate discharge area (hot-spot) being 2-3 times higher than the average emission rate of the lagoon.

Ammonium concentration in digestate showed no differences between the closest and the furthest area of the lagoon to the discharge point. Thus, differences in the emission rate were not significant (P>0.05).

$N_2O$ emission was negligible at uncovered lagoon, although some low positive concentrations were detected after digestate discharge (1.2 mg/m³) associated to the aeration of digestate.

Daily average $CH_4$ and $CO_2$ emission rates (biogas) ranged between 64.7 and 125.0 mg/m²/min, and 215.1 and 336.9 mg/m²/min, respectively. Biogas losses were within the ranges reported in the scientific literature for raw slurry, although $CH_4:CO_2$ ratio (25:75) was lower. Biogas emission differed between two zones of the uncovered lagoon, being higher in those areas where dry matter and volatile solids content of digestate analyzed were higher. Additionally, this zone was stirred through a pump, which could also contribute to enhance the emission level.

## *Covered lagoon*

The average exit speed of gas at safety valves was low (0.030-0.127 m/s), which was close to the detection limit of the hot-wire anemometer (± 0.03 m/s). Moreover, the speed of the circulating atmospheric air could have increased the uncertainty of the measurements and the estimation of the exhaust gas flow. Ammonia (4.2, 5.7 and 9.8 mg/m³) and $CH_4$ (16.8, 15.9 and 79.0 mg/m³) daily average concentrations within the valve system were slightly higher than those measured in the ambient air. Emission losses in the covered lagoon, ($NH_3$: 4.4 to 7.1 mg/min and $CH_4$: 11.6 to 64.0 mg/min) estimated for the whole lagoon were reduced nearly 100% in relation to the uncovered lagoon ($NH_3$: 313-477 mg/min; $CH_4$: 484-937 g/min). $N_2O$ emissions were also negligible.

## Conclusions

In the uncovered lagoon, the dynamic chamber methodology used let notice the heterogeneity of the gas emission in the lagoon surface (VC > 30% in all the cases). $NH_3$ average emission rates (0.33 to 0.50 mg/m²/min) were lower than the data found in scientific papers. It may be influenced by the use of lower air flow in the measurements (closer to real conditions). No $N_2O$ emissions were detected and biogas emissions ($CH_4$: 64.7 to 125 mg/m²/min and $CO_2$: 215-336 mg/m²/min) were similar to scientific bibliography data, although emissions varied significantly on the lagoon surface, showing higher values in those areas where the dry matter and volatile solids content of digestate were higher.

In the covered lagoon the emission concentration of $NH_3$ (3.2 to 20.3 mg/m³) and $CH_4$ (8.5 to 151 mg/m³) in the valves were slightly higher than in atmospheric air and the emission rates ($NH_3$: 4.4 to 7.1 mg/min and $CH_4$: 11.6 to 64.0 mg/min) were reduced almost 100% compared to the uncovered lagoon ($NH_3$: 313-477 mg/min; $CH_4$: 484-937 g/min). No $N_2O$ emissions were detected. Thus the cover is a useful measure in mitigating emissions of $NH_3$ and $CH_4$.

## Acknowledgements

This work was funded by the European Union under the Project Life MANEV (LIFE09 ENV/ES000453): Evaluation of manure management and treatment technologies for environmental protection and sustainable livestock farming in Europe.
References

[1] Peu, P., Beline, F., Martinez, J. 1999. Journal of Agricultural Engineering Research 73, 101-104
# WINTER COVER CROPS IMPACT ON PLANT NUTRIENTS IN AN ORGANIC CROP ROTATION

Liina Talgre¹, Viacheslav Eremeev¹, Berit Tein¹, Helena Madsen¹, Anne Luik²

¹Institute of Agricultural and Environmental Sciences, Department of Field Crop and Grassland Husbandry, Estonian University of Life Sciences, Tartu, Estonia, ²Institute of Agricultural and Environmental Sciences, Department of Plant Protection, Estonian University of Life Sciences, Tartu, Estonia, Tartu, Estonia

## Objectives

In crop rotations winter cover crops (WCC) can play a certain role in organic matter and plant nutrient formation. Under Nordic conditions the selection of crops for winter cover crops is quite limited. The aim of the present research was to explain the biomass and nutrients (N, P and K) formation by certain winter cover crops in an organic crop rotation. The effects of WCC on the following main crop yields were monitored.

## Method

The field experiment was situated at the experimental station of the Estonian University of Life Sciences in Eerika, Tartu, Estonia (58°22'N, 26°40'E). The soil type of the experiment area was sandy loam *Stagnic Luvisol* according to the World Reference Base classification (FAO 2014). The experiment was set up in four replications with each plot (60 m²) in a systematic block design. In a five-field crop rotation, barley under sown with red clover, red clover, winter wheat, pea and potato were grown in succession in three organic systems. System Org 0 followed only the rotation. In system Org I, green manures as winter cover crops (WCC) were used: after winter wheat – mixture of winter oilseed rape and winter rye, after pea – winter oilseed rape and after potato – winter rye were grown. In System Org II, green manures as WCC were used with the application of fully composted cattle manure with the amounts of 20 t ha⁻¹ for potato and 10 t ha⁻¹ for both cereals. Seeding rate for winter oilseed-rape was 6 kg ha⁻¹, for winter rye 220 kg ha⁻¹, for mixture of rye and oilseed-rape 180 and 6 kg ha⁻¹, respectively. In Org I and II systems all plots had green plant cover in winter. After the previous main crops were harvested the soil was immediately cultivated and WCC were sown with a Kongskilde sowing machine (row line width 12.5 cm). In all systems, the red clover was cut and then ploughed into the soil. The aboveground biomass of WCC were measured before their incorporation into soil by ploughing at end of April (2013, 2014, 2015). Total nitrogen and carbon contents of oven-dried samples were determined by dry combustion method on a varioMAX CNS elemental analyzer (Elementar, Germany).

## Results

One way to reduce nitrogen/nutrient leaching and increase the soil organic matter/nutrient content is to use WCC. Our results showed that WCC biomass production depended on a crop species grown and growing year. On average, the winter rye produced the largest amount of biomass 893 kg ha⁻¹ compared to rye and oilseed rape mixture 717 kg ha⁻¹ and oilseed rape 577 kg ha⁻¹. However there were big differences between the years. The average biomass of WCC was lowest in 2013 and highest in 2015 (p<0.05). In autumn of 2012 there were problems with excessive wetness and the following winter was very long which suppressed the development of WCC. Also, the different WCC showed large differences in biomass production and in above-ground plant parts N binding. In system with green manures (Org I) the total biomass of WCC varied from 39 kg dry matter ha⁻¹ of winter oilseed rape (in 2013) to 2174 kg dry matter ha⁻¹ of winter rye (in 2015). Winter rye had also the best N binding ability: 15 kg ha⁻¹ in 2013 and 99 kg ha⁻¹ in 2015, whereas the winter oilseed rape fixed only 1 kg ha⁻¹ in 2013 and 36 kg ha⁻¹ in 2015. The low biomass of winter oilseed rape in 2013 can be explained by the extremely long winter in 2012/2013 which damaged the crop. The co-influence of cattle manure (Org II system) increased the amount of biomasses as well as N, P and K contents in all WCC but differences between Org I and II systems were not significant. Winter rye was also the most effective binder of phosphorus (p<0.05). There were no significant (p<0.05) differences between WCC in terms of potassium binding.

The winter cover crops within crop rotation supply N for the subsequent crop. After the WCC are incorpo-
rated into the soil the N mineralization process starts, thus part of the mineralized N becomes available for
the following main crop. The main crop yields in Org 0 system was lower compared to other two systems
where WCC probably helped to increase the yields. WCC and their combination with cattle manure applica-
tion increased significantly grain yields of barley and, pea, as well as potato tuber yield (in 2013). Our re-
sults showed that lower crop yields and nutrient uptake under Org 0 system resulted with somewhat lower
surpluses of N but the N use efficiencies were higher.

Conclusions

Winter rye, winter oilseed rape and their mixture as winter cover crops enrich crop rotation with organic matter, N, P and K whereas the winter rye was the most effective. A tendency occurred that the use of cattle manure increased the organic matter and nutrient formation in all WCC. Winter cover crops and their combination with cattle manure increased the yields in all rotation crops compared to a system in which no WCC were grown.

Acknowledgements

This research was supported by the ERA-NET CORE ORGANIC project FertilCrop, by Estonian University of Life Sciences project 8-2/P13001PKTM and by institutional research funding IUT36-2 of the Estonian Ministry of Education and Research.
# MONITORING FERTILIZATION EFFECTS ON GROUNDWATER NITRATE POLLUTION

Hayriye IBRIKCI¹, Mahmut CETIN², Hande SAGIR¹, Mert UCAN², Ebru KARNEZ³, Said GOLPINAR²

¹Cukurova University, Soil Sci. and Plant Nutr. Dept., Adana, 01330, Turkey, ²Cukurova University, Agricultural Structures and Irrigation Dept., Adana, 01330, Turkey, ³Cukurova University, Karaisali Vocational School, Karaisali/Adana, Turkey

## Objectives

Nitrogen fertilization and irrigation both are playing an increasingly major role in crop production of the Mediterranean countries. Excess nitrogen fertilizer use is one of the phenomena as result of cropping factors and increased irrigation. However, fertilization induces nitrate losses to groundwater bodies especially during the rainy winter months and irrigation season in summer. Winter and early spring crops such as wheat and corn, receiving a large amount of N fertilizers (up to 380 kg N ha⁻¹), contribute to NO₃ losses to shallow groundwater by intensified seasonal rainfall. Therefore, the objectives of this research in a 9,495 ha irrigated land was 1) to determine temporal losses of NO₃ concentrations to shallow groundwater wells, 2) to evaluate the affects of nitrogen fertilizers on concentration levels from 2010 to 2014.

## Method

The research area Akarsu Irrigation District (9,495 ha) is located in the Mediterranean coastal region comprising the most intensively cropped and irrigated area of southern Turkey. The average annual rainfall in the experimental area was 640 mm on average. The soils of the study area are mostly alluvial, deep and high in clay, calcium carbonate and pH, but low in organic matter, and have wide cracks during the dry summer months.

The major crops of the District were wheat (Triticumaestivum), corn (Zea mays L.), citrus (Citrus sinensis L.), cotton (Gossypiumhirsutum L.) and various vegetables during the study years. Digitalized cropping-pattern maps showed that over 70% of the total irrigated land was covered by citrus and fruit trees, wheat and corn in the years under study. The most common irrigation practice in the location is gravity (surface) irrigation except irrigation of citrus and the other fruit trees.

The N fertilizer application rates for the crops varied between 60 to 380 kg N ha⁻¹, with an average of 250 kg N in the 5 years. Information on fertilizer rates and fertilization practices was recorded through farmers’ interviews by using questionnaires. Based on the cropping pattern, N fertilizer application continues year-around except a few months in early fall when no crops are fertilized in the field. Wheat and first-crop corn exist in winter and rainy spring are determined as excessively N receiving crops. The hydrological year (HY) in the District was considered to start on the 1st of October and finish at the end of September in the following year. The irrigation season (IS) covers the period from April the 1st to September the 30th, and the rest of the year was considered as the non-irrigation season (NIS).

The water samples were taken from 108 observation wells in January, April, July and September of each year to assess the NO3 concentrations. All water samples were analyzed for NO3 concentrations for each sampling period, and were mapped at GIS media. Soil mineral nitrogen (Nmin) was also determined in three depths to determine plant available N in a rooting depth (0-90 cm).

## Results

Based on the cropping pattern done twice a year during the 5 years, the main crops of the District were mainly field crops as wheat, corn, cotton and citrus and fruit trees which were consisted of over 70% of the total crop coverage. Wheat and corn planted in late fall and early spring were excessively fertilized with nitrogen fertilizers without detailed soil analysis and expert recommendation. Local survey study showed that N fertilizer rates applied to the common crops increased 10to 35% in the last 5 years resulting in excessive mineral N build-ups in soil profiles and thus in the groundwater and irrigation return flows. Even though based on the expert recommendations wheat and the first crop corn need to be fertilized with total amount of
180 and 240 kg N ha-1, these crops recently receive 265 and 380 kg N ha-1, respectively, as combination of basal and surface applications. Therefore, these regular inorganic N fertilizers quickly dissolve in the soil by heavy winter and spring rains plus irrigation practices, and possibly leach to shallow groundwater. Since the both crops (wheat and corn) were in their dormant-to-early growth stages, most of the nitrate-N form sub- jected to leaching to groundwater and drainage. In addition, total of 70 to 130 kg N min ha-1 were measured in a rooting depth.

Average nitrate concentrations in groundwater samples collected in January and March/April were higher than that of the other sampling periods and exceeded the critical threshold level (>50 mg L-1) in substantial area of the district. The groundwater nitrate values between 30-50 mg L-1 were potentially in the pollution risks (up to 41%) because of excessive N fertilization of wheat and corn. The lower NO3 concentrations up to 20 mg L-1 were also common in the 60 to 90% of the total area throughout the hydrological years (Octo- ber 1st to Sept. 30th of the following year) except in mid winter to early spring. It is also a regional reality that these two crops will remain as the major field crops of the region because of their economical value and adaptability to the Mediterranean climatic conditions. Especially wheat will also be preferred as a rotational crop for many years allowing the growth of soybean, second crop corn and sesame after its harvest. In addi- tion, citrus as a perennial tree significantly contributes to NO3 leaching to shallow groundwater and drainage in the study area.

Conclusions

Since there are considerable amounts of pre-plant soil mineral nitrogen in the rooting depth, and also
groundwater nitrate concentrations are high in some locations, regional N fertilizer recommendations need
to be considered and closely applied at the farmers’ level.

Acknowledgements

Authors gratefully acknowledge that this work was funded by:1) Through the project of FP6 - QUALIWA-
TER: Diagnosis and Control of Salinity and Nitrate Pollution in Mediterranean Irrigated Agriculture (Project
No: INCO-CT-2005-015031), 2) TUBITAK:IRAFLUT (Monitoring and multi-scale modelling of irrigation
return flow and its nutrient load in an agricultural area of Turkey) and 3) Cukurova Univ. BAP-664-ZF-
2013BAP23.
# EFFECT OF COVER CROP BIOMASS APPLICATION AS A GREEN MANURE ON REDUCING NITROUS OXIDE EMISSION

Hyun Young Hwang, Gil Won Kim, Jeong Gu Lee

Gyeongsang National University, Jin Ju, Republic of Korea

## Objectives

The cultivation of a winter cover crop as green manure is strongly recommended to improve soil quality and reduce the dependence of chemical fertilizers in temperate cropping systems. However, its biomass application as green manure promotes greenhouse gas (GHG) emissions by providing a readily available C and N substrates. It is likely that improved crop production strategies will conflict with mitigation of GHG emission. However, little is known about the effect of cover crop biomass application on the emission of N₂O, which is a main GHG emitted from upland conditions and has 310 higher global warming potential (GWP) than CO₂ on mole base, in temperate cropping lands.

## Method

In this field study, the mixture of barley (Hordeum vulgare R.) and hairy vetch (Vicia villosa R.) seeds with 75 % recommended dose (RD 140 kg ha⁻¹) and 25 % RD (90 kg ha⁻¹), respectively, were seeded in early November, 2011 and 2012, and harvested in early June 2012 and 2013, respectively. Total aboveground biomass was 36 Mg ha⁻¹ (fresh weight basis with 43-69 % moisture content). In order to determine the effect of cover crop biomass application on N₂O emission, different recycling ratios of 0, 25, 50, 75, and 100 % of the total harvested biomass were incorporated as green manure one week before corn transplanting in a typical temperate upland soil. For comparison, chemical N fertilizer was applied with different levels from 0 to 200% of standard amount of N fertilizer (190 kg N ha⁻¹).

## Results

Daily mean N₂O emission rates and total N₂O fluxes were significantly (p<0.05) increased with increasing application rates of cover crop biomass and chemical N fertilizer (urea). There was no difference on N₂O emission factor between chemical fertilization and cover crop biomass application with around 0.03 kg N₂O-N kg⁻¹ N, but cover crop biomass application as green manure significantly reduced seasonal N₂O fluxes by 76% under same levels of N addition. Corn productivity also significantly (p<0.05) increased with biomass application, but the highest grain yield (14% increase over the control) was observed for 75% recycling.

## Conclusions

Conclusively, cover crop biomass application as green manure might be suitable to sustain crop productivity with suppressing N₂O emission impact in temperate cropping system.
# DIAGNOSIS OF N LOSSES IN CROPPING SYSTEMS IN WATER PROTECTION AREAS

Raymond Reau¹, Marine Bedu², Jean-Baptiste Gratecap¹, Fabien Pucel², Virginie Parnaudeau²

¹INRA, Rennes, France, ²INRA, Grignon, France

## Objectives

Addressing the issue of agricultural pollution in water protection areas (WPA) requires assessing the impact of agricultural activities at regional scale. The main objective of this work was the diagnosis of the nitrogen losses of cropping systems in 7 contrasting water protection areas (WPA), in order to improve water quality and favor environmental-friendly systems. We aimed at involving stakeholders of each WPA, considered as local experts, to avoid results disconnected of the reality of farmers of the region. We used, adapted and developed, the framework described in Dupas et al. (1), consisting in describing the diversity of cropping systems and soils at the territory levels using local expert knowledge, and in assessing the nitrate losses in the territory with the modelling tool Syst'N (2). In this presentation, we will detail 3 contrasting WPA.

## Method

The first step of this work was the selection of 7 contrasting territories in terms of size, production, pedoclimatic characteristics and issues. The second step consisted in developing a typology of cropping systems and soils in each WPA, taking account of the local diversity, as the WPA were too large to enable an exhaustive description of the territory. We built the cropping system typology in collaboration with extension services or farmers so as to mix their local knowledge and data provided by local databases or regional statistics. The method was based on farmer logics considering nitrogen management. Soil types were defined with local pedologists and by using regional databases. The allocation of cropping systems in the WPA was also provided by the local experts or by making assumptions. Those descriptions were then translated in inputs for the DSS Syst'N; Syst'N includes a dynamic model simulating N fluxes in air-soil-plant system at a daily time step, and enables to view nitrogen losses results at different time scales. A third step was the Syst'N simulations in each WPA, including stages in which parameter optimization was required to fit field measurements (mineral N stocks in soil, N uptake by crops). The last step was the shaping of results that could be adapted to the specific issue of each WPA. However for all the WPA the results were expressed at the rotation scale or for two successive crops.

Three WPA will be presented here (called H, B and L), varying in terms of size (90 to 1300 ha), level of involvement of stakeholders, type of agriculture (crops vs livestock).

## Results

A general result is that despite of the successive steps of the approach, interactions between local experts and researchers were regular and useful during the whole study, strengthened in the WPA where the stakeholders were deeply involved in the process and where a dynamic had already been created at the local scale.

As a result of the development of the typologies, tables combining agricultural practices linked with nitrogen management and soils were produced to report the diversity of cropping system in the WPA, regarding the functions affecting nitrogen losses.

The DSS Syst'N required in nearly all the WPA expert knowledge or measurements to parameter situations and provides more correct results, which asks the question of the reliability of some results. In cases where crops where not parameterized in the DSS, we used other crops having the same behavior regarding N dynamics. We could not perform the assessment in one of the WPA for which the DSS was not adapted, because of the high stocks of ammonium in soil.

We will illustrate the results of 3 WPA in the presentation.

WPA H: This small WPA is characterized by i) a strong involvement of the local extension services and ii)
extensive livestock production (presence of permanent grasslands). As expected, the N losses are more sig-
nificant under short crop rotations (cereals-maize) than under grassland. Soil characteristics and efficiency
of cover crops in winter may affect significantly the nitrate losses. Simulation results could be used by the
extension services as a way to make farmer and other stakeholders discuss.

WPA B: This WPA is characterized by i) an existing dynamic at the territory level and collaboration with ag-
ricultural scientists, and ii) crop production dominated by oilseed rape and cereals. The results confirmed the
efficiency of the actions set up in the initial program, consisting in the generalization of cover crop for short
and long period between two commercial crops. The results emphase the high risk due to application of ag-
ricultural manure during summer before winter cereals. And tomorrow, these results will permit to assess the
nitrate losses under the whole agricultural fields of the area.

WPA L: This WPA is characterized by i) an existing program to improve water quality and ii) two contrast-
ing soil zones including a vulnerable alluvial zone. The results confirmed the efficiency of the actions set up
in the existing program, consisted mainly in allocating permanent grasslands in the alluvial zone.

Conclusions

This study enabled the development of N loss diagnosis in contrasting WPA, by building typologies describ-
ing the territory with local experts. We were able to get the nitrogen management issue further, even if we
can't already know how or if the stakeholders will use this work! The next stages are parallel: 1) improving
the DSS Syst'N, considered as user-friendly, to make the simulations more reliable by taking into account
available field measurements, 2) developing the interactive and dynamic N diagnosis as a tool to help stake-
holders to lead agricultural evolutions in the WPA.

Acknowledgements

This work was funded by the French ONEMA Agency. The authors would like to thanks the environmental
and agricultural extension services and more generally the stakeholders that participated in this study.

References

[1] Dupas R, Parnaudeau V, Reau R, Jeuffroy MH, Durand P, Gascuel-Odoux C. 2015. Integrating local knowledge and biophysical modeling to assess nitrate losses from cropping. Environmental modeling and software, 69, 101-110.

[2] Parnaudeau V., Reau R., Dubrulle P. 2012. Un outil d'évaluation des fuites d'azote vers l'environnement à l'échelle du système de culture : le logiciel Syst'N. Innovations Agronomiques 21, 59-70. http://www6.inra.fr/ciag/Revue/Volume-21-Septembre-2012.
# MANAGEMENT PRACTICES OF MISCANTHUS × GIGANTEUS STRONGLY INFLUENCE SOIL PROPERTIES AND N₂O EMISSIONS

Céline Peyrard, Fabien Ferchaud, Bruno Mary, Joël Léonard

INRA AgroImpact, Laon, France

## Objectives

Miscanthus × giganteus, a perennial C4 crop, is presented as a promising energy crop. Main variations in management practices concern harvest time and N input rate. These practices strongly modify the N and C cycles in the soil, influencing N₂O emission and the crop GHG balance which has to be beneficial. Whereas the effect of N input on N₂O emissions was often investigated, the effect of fertilizer form and harvest time in miscanthus remains poorly documented. The purpose of this study was to investigate the effect of an early or late harvest on soil parameters and N₂O emissions and the effect of fertilizer form (NH₄ or NO₃) on N₂O emissions.

## Method

The study was carried out on the Biomass & Environment long term experiment located in Estrées-Mons (80) in the north of France (49.872 N, 3.013 E). This experiment was set up in 2006 and compares the production and the environmental impacts of different bioenergy crops including Miscanthus × giganteus [1]. In our study, we focused on fertilized miscanthus (120 kg N ha⁻¹ yr⁻¹) and the two harvest-time treatments: early harvest (EH) in October and late harvest (LH) in February. In 2014 and 2015, these treatments were combined with two N fertilizer forms. We applied to each harvest-time treatment either 120 kg N ha⁻¹ of potassium nitrate (EH-NO₃ and LH-NO₃) or 120 kg N ha⁻¹ of ammonium sulphate (EH-NH₄ and LH-NH₄). N₂O and CO₂ fluxes were measured after fertilization, from April to August, on each of the 4 treatments and at a daily time step using automatic dynamic chambers (3 replicates). Soil samplings (0-5, 5-15 and 15-30 cm) were carried out every 10 days to determine pH, water content, NH₄⁺ and NO₃⁻ contents in each layer. Soil temperature (0-10 cm) and volumetric water content (0-30 cm) were also measured continuously using T107 and CS616 probes (Campbell Scientific). Total soil carbon was measured in 2015 before the fertilization while dissolved organic carbon (DOC) was measured at three dates in 2014. The effect of the 4 treatments on soil parameters and N₂O emissions was tested using variance analysis. Multiple regression analysis was also realized on log transformed fluxes to analyse how soil parameters influence N₂O emissions.

## Results

The cumulative N₂O emissions during five months were strongly higher (P < 0.0001) in LH than EH (4207 vs 893 g N₂O-N ha⁻¹ respectively), with no main effect of fertilizer form or year, although climatic conditions differed between the two years (precipitation = 364 and 73 mm in 2014 and 2015, respectively). A significant interaction between form of fertilizer and year was however observed.

The LH treatment is characterized by an important accumulation of leaves falling during winter resulting in a thick mulch which maintained significantly higher soil water content even during the dry period in 2015. The average WFPS was 80% during both years in LH treatment versus 65% in 2014 and 46% in 2015 in the EH treatment. Such a difference can explain a large part of the variance in N₂O fluxes. Indeed the daily N₂O fluxes (log transformed) were found to be strongly correlated with WFPS (R² = 0.55). Emissions may also have been stimulated in LH by the higher amount of NO₃⁻ in the soil, especially in the 15-30 cm layer, probably due to a delayed crop N uptake in this treatment as shown previously at the same site [2]. The LH treatment had a greater soil carbon content (16.3 g C kg⁻¹) than LH (13.1 g C kg⁻¹) which could further stimulate N₂O emissions by denitrification. However no difference was detected for DOC between treatments and CO₂ fluxes were higher in EH than LH, which suggests a greater microbial activity in EH.

By varying the fertilizer form we expected changes in emissions associated to a different stimulation of nitrification and denitrification with NH₄ or NO₃ input. We often observed higher N₂O fluxes in the NH₄ treatments but no clear effect of fertilizer form could be detected on cumulative emissions (P = 0.18). However,
we observed a significant decrease in pH after NH₄ fertilizer applications. The average NH₄ contents in each plot were strongly correlated with soil pH (R²=0.65). The multiple regression analysis carried out on physico-chemical soil parameters (0-30 cm) showed that pH was the second factor driving N₂O emissions after WFPS. pH is known to have a strong effect on N₂O reduction to N₂, modifying the denitrification contribution. Both factors explained 65.7% of the variance of N₂O emissions showing that crop management strongly influences N₂O emissions on miscanthus.

## Conclusions

The use of Miscanthus × giganteus as a bioenergy crop increases both in Europe and in France, but few studies have measured the environmental impact of these new systems and the influence of management practices. We have shown that harvest time strongly influenced N₂O emissions, with an average 4.7 times more emissions with a late harvest than an early harvest for a common N rate of 120 kg N ha⁻¹ yr⁻¹. This difference is mainly due to the higher soil water content induced by the presence of mulch with a late harvest. The fertilizer form did not affect directly N₂O emissions. However NH₄ fertilizer induced a decrease in pH that stimulated N₂O emissions most probably through less efficient reduction of N₂O to N₂. Management practices should then be chosen carefully to maximize the benefits of bioenergy crops.

## References

[1] Cadoux S, Ferchaud F, Demay C et al. 2014. GCB Bioenergy, 6, 425-438.

[2] Strullu L, Cadoux S, Preudhomme M, Jeuffroy M-H, Beaudoin N. 2011. Field Crops Research, 121, 381-391.
IMPLEMENTATION OF NITROGEN DYNAMICS IN THE DECISION SUPPORT SYSTEM ÖKO-SIMPHYT TO IMPROVE MANAGEMENT PROCESSES IN ORGANIC POTATOES

Hannes Schulz¹, Paolo Racca², Claudia Tebbe², Benno Kleinhenz², Christian Bruns¹

¹University of Kassel, Witzenhausen, Germany, ²Central Institute for Decision Support Systems in Crop Protection (ZEPP), Bad Kreuznach, Germany

Objectives

Organic potatoes have high profit margins. Recently ongoing specialization among organic potato farmers as well as fluctuating market prices increase cropping risks and jeopardize farmers’ income. Hence, key factors of yield development need to be considerably optimized such as nitrogen-supply and the control of late blight epidemics [1], [2].

For german organic potato farmers the decision support system (DSS) ‘ÖKO-SIMPHYT’ (Isip.de) was developed to control late blight epidemics based on copper applications. However, this DSS is only based on weather data and epidemiological models. Recently, it was shown that besides late blight the nitrogen uptake of the crop has a higher impact on yield in organic potatoes than expected. Therefore, in an EC project research was performed to implement a nitrogen vegetation model of potatoes in the DSS in order to improve copper spraying (and termination) strategies based on potential yield and thus offer means to reduce copper in organic potatoes.

Method

The presented study based on four year field trials (2012-1015) at the experimental sites Neu Eichenberg (51.37 N, 9.91 E, 220 m a.s.l.) and Frankenhausen (51.24 N, 9.26 E, 200 m a.s.l.). Long term (1970-2000) weather conditions are characterized with an annual precipitation of 650 mm and a mean temperature of 8.5°C for Frankenhausen and 620 mm / 7.9°C for Neu Eichenberg. Soil is classified as a silty loess luvisol on both experimental sites. For Frankenhausen carbon and nitrogen content was 1.02% and 0.11%, the content of phosphorus, potassium and magnesium was 83, 97 and 82 mg*kg⁻¹ dry soil, respectively. At Neu Eichenberg nutrient status in carbon and nitrogen was 1.02% and 0.11%. Phosphorus, potassium and magnesium was 59-140, 92-100 and 92-110mg*kg⁻¹ in dry soil, respectively.

Experimental design considers four basic Treatments (pest management, maturity type, N-fertilization and time) which changed over time. Pest management was realized up to three treatments corresponding to organic or conventional management (control [non Cu], conventional, 2 times ÖKO-SIMPHYT). The maturity type, which reflects development differences and yield potential risks in potato varieties, differed in very early, early, and mid early varieties. N-fertilization (BIOILSA® 11) was applied in 3 levels (low (field status), mid (40 kg*ha⁻¹ N) and high (70 -100 kg*ha⁻¹ N)). Yield development was determined with up to 10 sequential harvests in the field trials by collecting data on canopy biomass and tuber yield.

Soil NO₃-N dynamics were determined in 2 soil layers (0-30; 30-60) up to 10 times during vegetation period. N-content of the above ground biomass and tubers was analyzed. Late blight was regularly assessed according to James et al. (1971).

The results of the field trials were used to model the basic Nitrogen dynamics in the potatoes and in the soil. For soil, above ground biomass and tuber development mathematical time based functions were developed (e.g. Richards 'curve for tuber-N development') to complete the existing ontogenetic model. As second step, a high correlating intervention point (BBCH 60) was implemented in the model to setup N-dynamics during vegetation period and to adapt the operational procedure (e.g. the termination of copper spraying).
## Results

As expected weather conditions were one of the main drivers which influenced results of the field trials. Two main phenomena were observed which influenced results in the shown experiments in these years. In dry years (2013 and 2015) water was the yield limiting factor: The yield was below average and reached 30t*ha⁻¹ in both years. N-content in above ground biomass was not affected (results were between 3 and 4 % in dry matter). A rapid phonological development in above ground biomass was observed which affected tuber growth potential and the tuber vegetation period. Yield potential was reached at an earlier date compared to wet years and dry matter content was high. More rain in July (2015) nearly doubled the yield of the mid-early variety (50 t*ha⁻¹ at the end of vegetation period 2015). The very early variety wasn't affected that much. Under humid conditions, essentially in 2012, late blight development became the yield limiting factor. Copper spraying resulted in a plus in yield of 10 t*ha⁻¹. The effects of fertilization corresponded to water availability, too. NO₃-N-dynamic showed a maximum in mineralization (between 50 and 100 kg*ha⁻¹) at 10 to 25 days after plant emergence. Already at the first sequential harvests (mostly 50 – 60 days after planting) plants went into a N-limited situations, according to the theories of Duchenne et al. ([3]).

Modelling these results, time based functions were selected for NO₃-N-dynamic, for above ground biomass-N and tuber N-development and implemented in the existing web application of ÖKO-SIMPHYT. For NO₃-N-dynamic and above ground biomass-N a Gaussian function was chosen. Tuber-N development is modelled with a Richard's curve. Additionally a first Intervention point (phonological development stage 60, begin of flowering) was implemented to adjust the predicted growth situation to the actual growth stage. A threshold for predicted yield potential was integrated, which is linked to the recommended plant disease management strategy given by the ÖKO-SIMPHYT model.

## Conclusions

The results of this study improved the decision support tool ÖKO-SIMPHYT. The basic ontogenetic model was complemented by a nitrogen dynamic model for the vegetation period in organic potatoes. This tool will allow farmers to get a more transparent overview about growth and development of their potatoes. Supporting points in the web application offers the possibility to correct the estimated model during vegetation period. Spraying decision and management opportunities will become more comprehensive for farmers. Furthermore, it will be necessary to improve the web application by additional interventional points which are easy to estimate and which correlate to the actual growth development.

## References

[1] Finckh, M. R., Schulte-Geldermann, E., Bruns, C. 2006. Potato Research 49, 27–42.

[2] Palmer, M. W., Cooper, J., Tétard-Jones, C., Średnicka-Tober, D., Barański, M., Eyre, M., Shotton, P.N., Volakaki, N., Cakmak, I., Ozturk, L., Leifert, C., Wilcockson, S.J., Bilsborrow, P.E. 2013. European Journal of Agronomy, 49, 83-92.

[3] Duchenne, T., Machet, J.M., Martin, M. 1997. In: Lemaire D.J. (ed.) Diagnosis of the Nitrogen Status in crops p. 119-130.

[4] James, C. 1971. A manual of assessment keys for plant diseases. American Phytopathological Society, ASP Press, St. Paul.
# AMMONIA EMISSION FROM TWO LAYING HEN FACILITIES DIFFERING ON MANURE AND VENTILATION MANAGEMENT.

Oier Alberdi¹, Haritz Arriaga¹, Salva Calvet², Fernando Estellés², Pilar Merino¹

¹NEIKER-Tecnalia, Derio, Basque Country, Spain, ²Universitat Politècnica de Valencia, Valencia, Valencia, Spain

## Objectives

Ammonia ($NH_3$) is one of the main pollutant gases associated with poultry operations [1]. Laying farms with more than 40,000 hens are obliged to implement best available techniques according to Directive 2010/75/ EU (IED) adopted to mitigate pollutant emission. According to existing literature, strategies to reduce $NH_3$ emission from laying hen sector are most effective if they are applied at facilities or during manure land spreading. In EU, intensive laying hen farms had to adopt Directive 1999/74/EC on animal welfare in Europe in 2012, changing from conventional to an enriched cage (EC) system. In this sense, there is still scarce information on $NH_3$ emission from EC laying facilities. Improving the knowledge on such losses will allow identifying practices to mitigate $NH_3$ pollution. The objective was to assess $NH_3$ losses at two EC laying hen facilities located in different climatic zones, in which ventilation systems and manure management were also different.

## Method

The study was performed at 2 laying hen farms from the Basque Country (northern Spain), which were located in Oceanic (OF farm) and Mediterranean (MF farm) climatic conditions, respectively. 52,000 Lohmann-Brown hens were allocated at OF whereas 39,000 hens were reared in MF facility. OF was ventilated through 18 fans within a tunnel ventilation system. On the contrary, side ventilation system was installed at MF by using 15 fans. Manure management at OF consisted of full manure removal every 3 days whereas one third of accumulated manure was daily removed at MF. MF facility was equipped with an outdoor manure drying tunnel. This drying tunnel used warm air sent flushed by the fans from the facility to dry manure.

Ammonia ($NH_3$) concentrations were continuously monitored from June to December 2012 at OF and during year 2015 at MF. Ammonia was measured by using a calibrated INNOVA 1412 Photoacoustic multi gas analyser coupled with an INNOVA 1309 multipoint sampler (LumaSense, Denmark). Twelve sampling tubes were distributed into 8 exhaust fans (outlet) and 4 windows (inlet). Five sensors (Onset, HOBO U12-013, USA) were used to record air temperature at both facilities. An automated system regulated indoor temperature through a window opening and fan activation system. Air cooling was activated at both facilities in summer conditions. Mean percentage of operation of each fan was recorded every 5 minutes through an electronic datalogger system (Binary Devices S.L., Spain). Total airflow rate was calculated by integrating the number of operating fans every hour and the individual airflow rate of the fans (Estimated values: 38000 $m^3 h^{-1}$ for OF; 32000 $m^3 h^{-1}$ for MF).

Ammonia emission was calculated according to the following equation:

$$E = (C_{\text{outlet}} - C_{\text{inlet}}) * V$$

Where E is the emission (mg $h^{-1}$), $C_{\text{outlet}}$ and $C_{\text{inlet}}$ is the outlet and inlet $NH_3$ concentration (mg $m^{-3}$) and V is the ventilation rate in the building ($m^3 h^{-1}$).

## Results

Mean $NH_3$ emission rates during both experimental periods were 117.6 mg $d^{-1}$ hen$^{-1}$ and 142.4 mg $d^{-1}$ hen$^{-1}$ at OF and MF, respectively. Emission rates ranged from 73.3 to 175.4 mg $d^{-1}$ hen$^{-1}$ at OF and from 76.4 to 198.3 mg $d^{-1}$ hen$^{-1}$ from at MF. These values were within the emission range previously reported (54.0 to 169.9 mg $d^{-1}$ hen$^{-1}$) by other authors at EC facilities [2],[3]. Ammonia emission rate was monthly higher at MF facility except in June, when hens were still in a pre-laying stage. The difference observed at OF and MF farms were not attributed to nutritional factors as crude protein (CP) content of the concentrates supplied averaged 17.5%. We suggest that the different ventilation rates (VR) recorded in OF and MF considerably affected on the performance of $NH_3$ losses. A regression model conducted at MF showed the strong positive
relationship existing between VR and NH₃ emission rate (r² = 0.92; P < 0.05) when the amount of manure accumulated on belts is constant. Ventilation rates averaged 4.1 and 6.8 m³ hen⁻¹ h⁻¹ at OF and MF, respectively. Mean temperatures were 19.0°C in both summer seasons whereas temperature tended to be higher in OF conditions (14.6°C) than in MF (10.7°C) during autumn period. Despite the atmospheric temperature was slightly colder at MF, VR was higher to ensure air through the outdoor manure drying tunnel. In addition to ventilation practices, NH₃ emission rates from OF also highlighted the importance of manure management in the volatilisation process. Despite VR at OF was 60% of value reported at MF, mean NH₃ rate accounted for 82.5% of the emission at MF farm. As manure accumulation period was occasionally longer than the average 3 days (up to 5 days accumulated on belts), it would have contributed to enhance partially NH₃ losses at OF.

## Conclusions

The present study concluded that either ventilation or manure management are the main factors affecting on NH₃ volatilisation at EC laying hen facilities. Increasing VR at facilities is directly related to higher NH₃ losses, especially when manure management is constant. However, under variable manure removal frequency, accumulation period should be reduced as much as possible to reduce NH₃ emitted from the animal house.

## Acknowledgements

Oier Alberdi holds a grant from the Ph.D. student's research program of the Department of Economic Development and Competitiveness of the Basque Government.

## References

[1] Alberdi, O., Arriaga, H., Calvet, S., Estellés, F., & Merino, P. (2016). Biosystems Engineering, 144, 1–12.

[2] Shepherd, T.A., Zhao, Y., Li, H., Stinn, J.P., Hayes, M.D., & Xin, H. (2015). Poultry Science, 94, 534–543.

[3] Fabbri, C., Valli, L., Guarino, M., Costa, A., & Mazzotta, V. (2007). Biosystems Engineering, 97, 441–455.
COMPARISON OF NITROUS OXIDE EMISSION FACTORS FROM COVER CROP BIOMASS
AMENDED UPLAND AND PADDY SOILS DURING CROPPING PERIODS

Hyun Young hwang, mozammel Haque, Pill Joo Kim, Gil won Kim

Gyeongsang National University, Jin Ju, Republic of Korea

Objectives

Nitrous oxide (N₂O) is an important globe warming gas and a destructive agent of ozone in the stratosphere. A major concern is the increasing contribution of chemical fertilizers to atmospheric N₂O buildup. There is only a limited understanding of the contributions from crop residues. Nitrous oxide is produced from the biological nitrification and denitrification process in soils. It is well known that much higher N₂O is emitted from upland than paddy soil, generally due to higher N fertilization and favorable aerobic condition for biological nitrification. Therefore, most N₂O emission studies were conducted in upland soils, but very rare in rice paddy soils. In particular, this N₂O emission factors were developed on centering chemical fertilizer-induced factor, but its emission factors induced from organic matters were not developed systematically well.

Method

In this two year field studies, in order to determine N₂O emission factors induced from organic amendments, the mixture of barley and hairy vetch was cultivated in upland and paddy soils during the fallow season, and its biomasses were harvested in the next early June before main cash crop cultivation. Total aboveground biomass productivities were 35-36 Mg ha⁻¹ (fresh weight basis). The harvested biomass was finely chopped (size 5-10 cm), and applied with different recycling ratios (0-100% of the aboveground biomass) in upland for corn cultivation and in paddy soil for rice cultivation. Nitrous oxide emission rates were monitored using the closed chamber method once a week interval.

Results

Seasonal N₂O fluxes significantly increased with increasing cover crop biomass application, but N₂O emis-
sion factor which was determined using N₂O-N flux changes to total N input changes was significantly
higher with 0.032 kg N₂O-N kg⁻¹ N in upland soil during corn cultivation than 0.005 kg N₂O-N kg⁻¹ N in
paddy soil during rice cultivation. The N₂O emission factor induced from organic residues of upland soil was
approximately three times higher than the IPCC default 1% value. In contrast, N₂O emission factor in paddy
soil was one second times lower than the IPCC default values.

Conclusions

In Korea, IPCC Tier 1 methodology, assuming that 1% of N input as fertilizer is directly emitted, could be
developed considering agricultural land use under crop residues applied condition.
# NITROUS OXIDE AND NITRATE LOSSES - INFLUENCING FACTORS IN WILLOW CROPPING INVESTIGATED BY MODELLING

Hongxing He, Per-Erik Jansson, Anna Hedenrud, Sophie Rychlik, Per Weslien, Leif Klemedtsson, Åsa Kasmir

Earth Sciences, University of Gothenburg, Göteborg, Sweden

## Objectives

Bioenergy crops are expected to play an important role in securing the energy supply and mitigating greenhouse gas emissions. However, to increase the yield, mineral N fertilizer and sewage sludge fertilizer are normally applied which might in turn increase the risk of soil N2O emissions and also nitrate leaching. This paper thus focuses on the N2O emissions and soil nitrate leaching and their influencing factors for a conventional Swedish willow bio-energy plantation.

The following research questions were addressed:

1. What influencing factors are found for N2O emissions and nitrate leaching, respectively?

2. What is the optimum fertilization amount rate to minimize N2O emissions in relation to gain in biomass?

3. What is the possible impact of drainage on the willow biomass growth and also N losses?

## Method

We calibrated a detailed process-oriented model, CoupModel with a number of measured high resolution data obtained from the Skrehalla field experiment site in Grästorp, Sweden (N58016' E12046'), having willow (Salix viminalis). The site has heavy clay soil with pH 5.8 (±0.1). Soil C/N ratio was 12 (± 0.4) for the first 0-50 cm soil layers. The site was drained by a tile pipe drainage system, depth of ~ 1 m and 10 m spacing.

The field experiments started in 2012, the year before the fifth harvest. NH4NO3 was added in June 2012, 100 kg N ha-1. Harvesting was performed 29th of March and sewage sludge from a local waste water treatment plant was then added in May, in total 270 (80-460) kg N ha-1.

The current general model structure setups and basic parameterizations were based on previous usage of CoupModel on similar ecosystems. The calibration and uncertainty analysis method used in this study is the Generalized Likelihood Uncertainty Estimation (GLUE). For the GLUE calibration, a number of high resolution data including biotic and abiotic variables were used together with eddy covariance measurements of CO2 and N2O fluxes. The application of mineral fertilizer was assumed to directly add ammonia and nitrate to the soil surface N content pool. Sewage sludge was analogously treated as “Faeces” in the model, adding to both soil mineral and organic pools, and assumed to be mixed into the soil surface. The initial conditions of the willow plants are defined by measured plant growth biomass data. Soil physical structure was defined by soil water retention curves derived from pedo-functions from measured soil texture fractions. Where measured data show large variations, coefficients with high uncertainties were included into calibration. Since initial values for total soil organic matter content was unknown, this was subject for calibration. Meteorological data, hourly resolution, was used as model forcing.

## Results

A detailed investigation of the period, June to July 2012 and May to October 2013 shows an emission peak in June 2012 to be closely connected to the soil surface water content variation induced by rainfall soon after mineral fertilizer application. Despite some discrepancies in capturing the measured peaks, the simulated emissions after commercial fertilizer addition were 0.05 (0.02 to 0.15) g N2O-N m-2, similar to what was measured in the year of 2012, 0.035 g N m-2. The simulated emissions after adding sewage sludge in 2013 were estimated to be 0.2 (0.1 to 0.37) g N2O-N m-2 which was slightly higher than measured, 0.17 g N m-2. After the mineral fertilizer addition leaching was estimated to 0.66 (0.34 to 1.08) g NO3--N m-2 yr-1, where high leaching was found connected to intense rainfall, also being a period with high N2O emissions. Sewage sludge application resulted in lower nitrate leaching, 0.2 (0.05 to 0.35) g N m-2 yr-1. Our modeling also describes the leaching of dissolved organic N (DON), which is simulated to be 0.14 (0.13 to 0.15) g DON-N m-2 for the first year but only 0.02 (0.01 to 0.03) g N m-2 for the second year. The simulated leaching dy-
namics was linked to precipitation patterns, where the total precipitation in 2012 was 919 mm yr-1, much higher than the 30 years mean 683 mm yr-1 (data from a nearby SMHI station), while 2013 was dry with only 524 mm yr-1, which explains the small soil nitrate leaching in 2013 despite sludge application. The relatively low N2O emissions and soil nitrate leaching can also be explained by large plant N uptake, simulated to be 108 (83 to 133) kg N ha-1 in 2012, and 147 (108 to 186) kg N ha-1 in 2013. Therefore the plant nitrogen uptake is the dominating controlling factor in the soil N cycle, leaving relative small amount of available N for N2O production and nitrate leaching.

## Conclusions

Our modeling indicates that N2O emissions are mainly produced by the nitrification process, most influenced by soil water content and the amount of fertilizer added. The modelled soil nitrate leaching was negatively influenced by the denitrification and positively by water drainage flow. Model sensitivities indicate that to minimize the N2O emissions in relation to biomass gain, the application rate of mineral fertilizer should be within the range of 50 to 100 kg N ha-1, sewage sludge within 150 to 300 kg N ha-1. The high sensitivity to drainage suggests that an optimum drainage is of need both to achieve high plant yield and minimize N losses.

## Acknowledgement

We want to acknowledge funding from Swedish Energy Agency (project number32652-1) and research area BECC (Biodiversity and Ecosystem services in a Changing Climate).

## References

[1] He, H., Jansson, P. E., Svensson, M., Meyer, A., Klemedtsson, L., and Kasimir, Å. 2015 Ecological Modelling, 10.1016/j.ecolmodel.2015.10.030
# A NETWORK TO MEASURE AND ANALYZE VARIABILITY IN SOIL NITROGEN MINERALIZATION AT THE FIELD SCALE IN BRITTANY (FRANCE)

Laure Beff¹, Yvon Lambert², Philippe Germain¹, Benjamin Louis¹, Bruno Mary³, Nicolas Beaudoin³, Thierry Morvan¹

¹INRA-Agrocampus, UMR 1069, Rennes, France, ²Chambre d'agriculture de Bretagne, Rennes, France,

³INRA, UR1158, Agro-Impact, Laon, France

## Objectives

Increasing efficiency of nitrogen (N) fertilizer use and decreasing losses to the environment (e.g. NO3 leaching) requires accurate predictions of soil N mineralization under field conditions. Predicting soil N mineralization is challenging given its high variability and the factors that influence it, such as soil properties, field management and climate. Experimental measurements have shown that models developed in France (e.g. the Comifer model [1]) are not suitable for predicting soil N mineralization in the Brittany region of France. The lack of references for this region prohibits calibration and parametrization of these models. In this context, INRA and the Brittany Chamber of Agriculture created a network of agricultural fields to create a reference dataset for soil N mineralization. The aim of this network is to improve knowledge about factors influencing soil N mineralization and to develop a predictive model adapted to this region.

## Method

The experiments were performed on 65 silage maize fields (bare soil during winter) managed without any N fertilization during the experiment and located throughout Brittany (France). The fields were chosen to represent a range of soil parent materials under different management systems (crop rotation and manure supply). For each field, three experimental plots, for measurement replicates, were established in 2010 (28 fields) or 2011 (37 fields) and then monitored for 4 or 5 years. Soil properties (pH, Metson cation exchange capacity (CEC), total and exchangeable elements, organic matter, particulate organic matter, bulk density, soil water content at field capacity and wilting point), microbial biomass and soil-chemical N indices to estimate soil N mineralization (N extraction with hot water, hot KCl and phosphate-borate buffer) were determined. Soil N mineralization was calculated by mineral N mass-balance: amount of mineral N in soil in spring (March) and in autumn (October), maize N uptake, and nitrate leaching (predicted with the STICS model [2]).

The daily effect of soil water content and soil temperature was normalized using functions allowing the conversion of calendar days in normalized days, Jn, [3]. Soil water content and temperature were predicted with STICS [2] from field weather. The normalized N mass balance (BN) was the N mass balance divided by Jn.

One indicator ($I_Sys$) was calculated to evaluate the effect of field management (crop rotation and manure application) on N mineralization. This indicator was calculated by summing the average nitrogen mass balance of crops and the effect of manure application (estimated with DSM model [4]) for the 15 years before the beginning of the experiment.

All statistical analyses were performed with R, v. 3.2.1. Pearson correlations were used to assess relations between variables. Generalized Additive Models (GAMs) were used to develop a predictive model of the potential of soils to mineralize N [5]. Variables were chosen to obtain models with the smallest Mean Square Error of Prediction (MSEP). This criterion was calculated by applying a “leave-one-out” strategy, which represented an internal validation approach of the model and avoided over-fitting the model to data.

## Results

Normalized N mineral mass balance (BN) varied from 0.28-2.53 kgN.ha⁻¹.Jn⁻¹, illustrating the variability in soil potential to mineralize N. Mean BN was higher in 2012 and 2013 than in 2014. These differences in BN between years showed that additional yearly processes besides climate normalization should be considered to properly understand and estimate soil N mineralization.
In laboratory studies, some authors observed a flush of mineralization due to cycles of dry/wet soil water content [6, 7] Moreover, Lado-Monserrat, et al. [8] showed an impact of pre-wetting soil moisture on N mineralization flush.

In the field, dry/wet soil-moisture cycles are not as well defined as in the lab and depend on rainfall and soil properties, such as texture and water content at field capacity and wilting point. Alternation, intensity and duration of soil water content cycles can increase N mineralization, which can be difficult to estimate, especially since other environmental factors can impact it. Weather conditions in 2012 and 2013 were characterized by drought during summer. Therefore, we consider that soil N mineralization is the combination of a basal component and an extra-mineralization (Em) component. The basal component is composed of the potential N mineralization rate (Vp) multiplied by Jn. We determined years in which Em occurred by performing t-tests between the BN of the years, which allowed us to calculate the basal component and Em.

Em can partly be explained by climate variables and soil properties. Em occurred mainly in 2012 and 2013 in fields where we observed summer water deficit followed by a long rewetting time. In these cases, Em can be considered as an autumnal flush and is usually associated with a high amount of mineral N in soil in autumn. Because Em occurred occasionally and cannot be predicted, we developed a model to predict the basal component of soil N mineralization: Vp × Jn.

Vp was significantly correlated with I_Sys, representing the field-management effect (r = 0.43, P < 0.01), with different soil properties (texture, N stock, C stock), with microbial biomass (P<0.01) and with the soil-chemical N indices (P < 0.01). However, no correlation was sufficient to predict Vp accurately, and the model to predict Vp combined multiple variables: I_Sys, soil properties (texture, CEC, particulate organic matter), microbial biomass and the N mineral extracted by phosphate-borate buffer. Given the number of variables influencing soil N mineralization and Vp, this model predicts Vp well (R² = 0.67).

## Conclusions

In this study, we measured a network of fields in Brittany to create a reference dataset of soil N mineralization for this region and improve our understanding of environmental factors influencing it. We showed that soil N mineralization is the combination of a basal component and an extra-mineralization (Em) component. Em occurred occasionally; is influenced by weather conditions, soil moisture and soil properties; and cannot be predicted. We developed a model to predict the basal component (Vp × Jn) of soil N mineralization. This model predicts soil N mineralization well from three factors known to influence it: soil properties, crop management and climate (via Jn).

## Acknowledgements

This work was financially supported by AELB; Regional Council of Brittany; Departmental Councils of Côtes d'Amor, Finistère and Morbihan; and DRAAF. This work was supported by partnerships with the SEMSE, AUREA and Galys laboratories.

## References

[1] Comifer. 2013. Groupe Azote Comifer, 159.

[2] N. Brisson, M. Launay, B. Mary and N. Beaudoin. 2008. INRA, Rd 10, 78026 Versailles Cedex, France, Editions Quae.

[3] A. Rodrigo, S. Recous, C. Neel and B. Mary. 1997. Ecological Modelling 102(2-3), 325-339.

[4] R. Trochard, A. Bouthier, T. Morvan and J. Grall. 2012. Innovations Agronomiques 25, 55-69.

[5] S. N. Wood. 2006. Boca Raton, Florida, U. S. A., Chapman Hall/CRC.

[6] H. F. Birch. 1958. Plant and Soil 10(1), 9-31.

[7] W. Borken and E. Matzner. 2009. Global Change Biology 15(4), 808-824.

[8] L. Lado-Monserrat, C. Lull, I. Bautista, A. Lidon and R. Herrera. 2014. Plant and Soil 379(1-2), 21-34.
# SOIL NITROGEN MINERALIZATION: RELIABILITY OF A MULTI-COMPONENT APPROACH

Thierry Morvan¹, Laure Beff¹, Philippe Germain¹, Rémi Chaussod³, Mathieu Valé⁴, Benjamin Louis¹, Yvon Lambert²

¹INRA-Agrocampus, UMR 1069, Rennes, France, ²Chambre d'agriculture de Bretagne, Rennes, France,

³SEMSE, Vievigne, France, ⁴AUREA, Ardon, France

## Objectives

Accurately estimating mineralizable nitrogen (N) in soil organic matter (OM) is essential to improve fertilizer management and reduce nitrogen leaching in cultivated soils. Many soil-chemical N indices were developed before the 1980s to improve predictions of soil N mineralization [1]. A meta-analysis by Ros, et al. [2] confirmed the utility of some of these tests (5 of the 18 evaluated) but concluded that (i) one single indicator cannot sufficiently predict mineralization and (ii) it is necessary to adapt a multi-component approach based on simultaneously considering several indicators, soil properties, and land use. The objective of this study is to examine this conclusion by studying relations among soil N mineralization, three soil tests, soil microbial biomass, soil physical and chemical properties, and land use.

## Method

### Soil sampling and analysis

Soil samples were collected in March 2013 from a network of 130 fields in Brittany (France) chosen to represent a range of parent materials under different management systems (annual crops, prairie/crop rotations). We used a 7-day anaerobic incubation to measure soil N mineralization (Ana_Nmin), using a procedure adapted from Keeney and Bremner [3]. Soil microbial biomass was determined by the chloroform fumigation extraction method (AFNOR NF FD ISO 14.240-2, 1997).

Three soil tests, providing five chemical indices, were determined for dried soils sieved at 2 mm: (i) hot-water extractable C (HW_C) and N (HW_N), according a modified method by Leinweber, et al. [4]; (ii) hot extractable NH4-N (Hot_KCINH4) and hydrolysable NH4 (Hyd_KCINH4), the latter obtained by subtracting the NH4 content of the cold KCl extract from the Hot_KCINH4, were determined following the procedure of Gianello and Bremner [1]; and (iii) phosphate-borate distillable nitrogen (PBD_N), analyzed according to Gianello and Bremner [5].

Routine soil analyses (i.e., pH, Metson cation exchange capacity (CEC), total and exchangeable elements) were performed according to AFNOR procedures. Total C and N were analyzed by dry combustion. OM was physically fractionated into OM associated with sand (50-2000 µ), corresponding to particulate OM (POM_C and POM_N), and with silt and clay particles (0-50 µ), following the procedure of Balesdent, et al. [6]. One indicator (I_Sys) was calculated to include the effect of crop rotation and manure application on N mineralization.

### Statistical analyses

All statistical analyses were performed with R, v. 3.2.1. Pearson correlations were used to assess relations between variables. Generalized Additive Models (GAMs) [7] were used to determine the best combination of variables for predicting 7-d anaerobic soil mineralization. Variables were chosen to obtain models with the smallest Mean Square Error of Prediction (MSEP). This criterion was calculated by applying a “leave-one-out” strategy, which represented an internal validation approach of the model and avoided over-fitting the model to data.

## Results

### Ranges of soil characteristics, N mineralization and chemical indices

Soil physical and chemical properties were representative of soils in Brittany. Most of the soils were loams: clay loam, sandy loam and sandy clay loam. Soils had pH from 4.8-7.9 (mean = 6.1) and low CEC (mean = 9.8 meq/100 g). Total N varied widely (0.87-3.10 g N kg-1 dried soil (d.s.)), as did total C (8.8-37.9 g C kg-1 d.s.), corresponding to high OM content in most of the 130 cultivated soils, except the loamy soils. Mean soil microbial biomass (Biom) was relatively low (179 mg C kg-1 d.s.) given the C content of the
soils. The Biom/Total C ratio differed significantly among parent materials (P<0.001). The highest percentage of biomass C was observed in loamy soils (mean = 1.10%), while the lowest was observed in micaschist soils (mean = 0.63%).

Chemical extractable N indices also varied widely. Mean values for HW_C, HW_N, Hot_KCINH4, Hyd_KCINH4 and PBD_N were 752.3 mg C kg-1 d.s and 73.5, 22.4, 14.9, 26.3 mg N kg-1 d.s., respectively. The hot-water extraction method was the strongest, extracting a mean of 4.5 times as much C as those based on microbial biomass and 2.8-4.9 times as much N as the other soil-chemical N indices.

Ana_Nmin varied from 8.7-39.2 mg N kg-1 d.s. (mean = 21.8 mg N kg-1 d.s.). The range of Ana_Nmin was similar to those of Hot_KCINH4 and PBD_N.

## Correlations and N mineralization modeling

Most of the correlation coefficients among Ana_Nmin, chemical N indices, total N, total C, POM_C and POM_N were highly significant (P<0.001 or <0.01). However, correlation coefficients >0.7 were observed only between total N and C (r=0.93), Hot_KCINH4 and Hyd_KCINH4 (r = 0.90), Hot_KCINH4 and Total N (r = 0.85), and Hyd_KCINH4 and Total N (r = 0.84).

The correlation coefficients between Ana_Nmin and chemical indices ranged from 0.40-0.56 (P<0.001), and was similar to those between Ana_Nmin and total N or POM_gN (r=0.50 and 0.48 respectively). The strongest correlation was observed between Ana_Nmin and Biom (r = 0.59).

The modeling approach based on the use of GAMs led to development of a model that integrated soil properties (pH, clay content, CEC), soil microbial biomass (Biom), two mineralization indicators (HW_N and Hyd_KCINH4) and the land-use indicator (I_Sys). This model correctly predicted Ana_Nmin (R² = 0.63).

## Conclusions

Mineralizable N was positively related to soil microbial biomass, total N, land use and all soil chemical indices. But none of these variables was accurate enough to predict mineralizable N on its own, in agreement with the conclusions of Ros et al (2011). A “multi-component” modeling approach allowed selection of soil properties and soil chemical indices and showed the utility of integrating a land-use indicator.

## Acknowledgements

This work was financially supported by the Agence de l'Eau Loire Bretagne; the Regional Council of Brittany; the Departmental Councils of Côtes d'Amor, Finistère and Morbihan; and the DRAAF. This work was also supported by partnerships with the SEMSE, AUREA and Galys laboratories.

## References

[1] C. Gianello and J. M. Bremner. 1986. Communications in Soil Science and Plant Analysis 17(2): 195-214.

[2] G. H. Ros, E. J. M. Temminghoff and E. Hoffland. 2011. European Journal of Soil Science 62(1): 162-173.

[3] D. R. Keeney and J. M. Bremner (1966). Nature 211. 5051: 892-893.

[4] P. Leinweber, H. R. Schulten and M. Korschens. 1995. Biology and Fertility of Soils 20(1): 17-23.

[5] C. Gianello and J. M. Bremner. 1988. Communications in Soil Science and Plant Analysis 19(14): 1551-1568.

[6] J. Balesdent, E. Besnard, D. Arrouays and C. Chenu. 1998. Plant and Soil 201(1): 49-57.

[7] S. N. Wood. 2006. Boca Raton, Florida, U. S. A., Chapman Hall/CRC.
# CROPPING SEQUENCE AFFECTS NITRATE LEACHING DIFFERENTLY ON SANDY SOILS IN THE NETHERLANDS

Martine Hoogsteen¹, Arno Hooijboer¹, Ton van Leeuwen², Eke Buis¹

¹National Institute for Public Health and the Environment, Bilthoven, The Netherlands, ²Agricultural Economics Research Institute, Wageningen UR, The Hague, The Netherlands

## Objectives

Nitrate leaching to groundwater is still a major environmental concern associated with dairy farming on the sandy regions of the Netherlands. Manure application has been restricted throughout the last decades and a national monitoring program is in place to evaluate the on-farm quality of groundwater. It is well known that nitrate leaching from agricultural soils is influenced by naturogenic factors such as precipitation rates and groundwater level. Moreover, farm management such as the crop choice, type and amount of applied manure and the application time are of major importance¹,². However, the effects of cropping sequence on nitrate levels are less known. The objective of this study was to assess the effect of different sequences of grass/ maize rotations on nitrate leaching on the sandy soils of the Netherlands by using on-farm measurements of a large-scale national monitoring program.

## Method

The Dutch Minerals Policy Monitoring Program³ consists of around 450 farms of which about 235 are located in the Sand region. All farms are sampled annually between June and September. On each farm 16 sub-samples are taken of the upper groundwater. The nitrate concentration is measured in the field using a Nitra-chek reflectometer. Furthermore, the groundwater depth is recorded at the moment of sampling. A ground-water table score is allocated based on the Dutch national groundwater classification system using overlay maps. The wetness index, a measure of the precipitation surplus, is calculated using daily weather data⁴.

At farm level, detailed management data is gathered through the national Farm Information Network⁵. Live-stock numbers, crop information and nitrogen flows are recorded on an annual basis. Manure application rates are recorded at crop level distinguishing grassland and arable land.

In this study we selected data points based on the following criteria: soil type (sand), crop type (grass or maize) for a period of two and three consecutive years prior to the year of sampling. This resulted in a total number of 5912 and 3632 data points, respectively. Those points were located on 103 farms, which were sampled between 2006 and 2013. Farms were selected based on the criteria: crop (only grass/ maize). Fur-thermore, the amount and type of fertilization were reported on a crop scale. It was not possible to combine information on the cropping sequence at point level with the data on agricultural practices. However, nitrate concentrations at point level could be aggregated to crop level on farms. This resulted in one dataset at point level and one at farm/crop level.

Statistical tests were performed at point level. Analysis of variance was conducted with cropping sequence and wetness index, including their interaction as explanatory variables and nitrate as dependent variable. The 2-year cropping sequences were: grass-grass, grass-maize, maize-grass and maize-maize. Post-hoc tests were conducted according to LSD. All possible combinations of grass and maize for a three-year cropping sequences were also distinguished except for maize-grass-maize, because this group contained only 16 mea-surement points.

## Results

The analysis of variance revealed that wetness index, cropping sequence and their interaction had a highly significant effect (P<0.000) on nitrate concentrations. This was observed for both two and three year crop-ping sequences. For the two year crop sequences, greatest NO₃ concentrations were found for fields under grass with maize as the preceding crop (95 mg NO3 l⁻¹) and no significant differences were found between grass-maize and maize-maize (90 mg NO3 l⁻¹). Lowest NO₃ concentrations were found for two years of
grass (44 mg NO₃ l⁻¹). This was also the case for the three year grass cropping sequences where concentrations were on average 39 mg NO3 l⁻¹ for a three year period of grass. Greatest NO₃ concentrations were found for maize-maize-grass (109 mg NO₃ l⁻¹) and grass-maize-grass (101 mg NO₃ l⁻¹). A three year period of maize resulted in an intermediate level of nitrate of 78 mg NO₃ l⁻¹.

## Discussion

Largest NO₃ concentrations were found for maize-maize-grass and grass-maize-grass. Fertilization levels of grassland are generally greater than on maize⁶. However the root mass of maize is much smaller resulting in a reduced recovery of the applied fertilizers. Moreover, soil organic matter (SOM) levels of maize land are generally lower, leading to a reduced denitrification capacity of the soil. Large NO₃ concentrations observed for maize-maize-grass are possibly the result of both increased decomposition of SOM due to the annual ploughing and a reduced denitrification capacity due to the lower SOM levels.

The fact that the cropping sequence grass-maize showed greater NO₃ concentrations might be a consequence of the timing of manure application. During a large part of the monitoring period, it was common practice that the process of maize harvesting was followed by animal manure application. Grassland was seeded after ploughing the fields and thus incorporating the manure. In spring manure was again applied before the first cut. During the winter and spring period, newly seeded grasslands are however not fully established while manure is already applied. Consequently, a great part of the applied N will directly leach to the groundwater leading to amplified NO₃ concentrations in young grassland soils.

## Conclusions

Based on these preliminary results we conclude for the sandy regions of the Netherlands that multiple years of maize do not lead to greater NO₃ losses as compared to grass with maize in rotation. Further research should contemplate integrating data of the Dutch Minerals Policy Monitoring Program with data on fertilization at farm level and data of the Dutch National Registration of Cropping areas⁷, an annual registration program of crop type at field level. In this way, the crop rotation at field level can be retrieved for a period of 6 years and linked to measured NO₃ concentrations and farm management.

## References

[1] Schröder et al. 2009. Grass and Forage Science, 49-57.

[2] Hooijboer et al. 2015. Nitrate leaching from dairy farms in the sandy regions in the Netherlands: Causes for higher nitrate leaching from maize land than from grassland, LUWQ2015, Vienna, Austria.

[3] Dutch Minerals Policy Monitoring Program. 2016. At: http://www.rivm.nl/Onderwerpen/L/Landelijk_Meetnet_effecten_Mestbeleid, Accessed: 30/1/2016.

[4] Fraters et al. 2015. Acta Agriculturae Scandinavica, Section B - Plant & Soil Science, 144-154.

[5] Farm Information Network. 2016. At: http://www.wageningenur.nl/nl/Expertises-Dienstverlening/Onderzoeksinstituten/LEI/Data-1/Bedrijveninformatienet.htm, Accessed: 30/1/2016.

[6] Hooijboer et al. 2014. Agricultural practice and water quality at grassland farms registered forderogation in 2012. p 33.

[7] Dutch National Registration of Cropping areas. 2016. At: https://data.overheid.nl/data/dataset/brp-gewaspercelen, Accessed: 3/2/2016
# A NOVEL COMBINATION OF UREASE INHIBITORS AND ITS FORMULATION WITH BETTER PERFORMANCE CONCERNING BIOLOGY, HANDLING TRANSPORT AND STORAGE COMPARED TO EXISTING PRODUCTS

Gregor Pasda¹, Alexander Wissemeier¹, Laura Vance², Marcela Muller³, Alexander Ungru¹, Matthias Lex¹, Karl-Heinrich Schneider¹, Maarten Staal¹, Wolfram Zerulla¹, Markus Schmid¹

¹BASF SE, Limburgerhof, Germany, ²BASF Corp., Raleigh, USA, ³BASF S.A., Sao Paulo, Brazil

## Objectives

The main disadvantage of urea-containing fertilizers, which are the dominant nitrogen fertilizers worldwide, is nitrogen (N) volatilization losses in form of ammonia ($NH_3$). Depending on weather and on soil conditions the extent of such N losses can be up to 70% of applied N [1]. One approach to reduce these losses is the application of urease inhibitors (UI), which may substantially reduce $NH_3$-losses by up to 80% [2].

BASF SE developed a novel combination of urease inhibitors (brand name Limus®), which is a mixture of three parts NBPT (N-(n-butyl)thiophosphoric-triamide) and one part NPPT (N-(n-propyl)thiophosphoric-triamide). The new developed formulation of these two active ingredients (AI) is based on polymers.

The objective of several studies was to compare this novel product with the market standard regarding $NH_3$ emissions, yield impact, handling, transport and storage properties.

## Method

Limus® or the corresponding treated urea-containing fertilizers (urea, urea ammonium nitrate solution (UAN)) was compared with the market standard (MS, Agrotain® or Agrotain Ultra®, Koch Agronomic Services LLC) and the treated urea-containing fertilizers, resp.. The active ingredient (AI) of the MS is NBPT (N-(n-butyl)thiophosphoric-triamide) only. AI concentrations of Limus and MS were between 0.04 and 0.09% based on urea fertilizer. UI-treated urea were produced in small concrete mixer, seed treater or tumbler mixer.

Experiments were conducted under fully controlled conditions in the lab and under field conditions in Argentina, Brazil, Denmark, France, Germany, Italy, Spain and United States. Test crops in the small plot and fully randomised field experiments with minimum three replicates were mainly corn, wheat and rice.

$NH_3$ emissions were measured in the lab (measuring period up to 35 days) using ventilated chambers and under field conditions (measuring period in most cases 10-15 days) with a closed chamber method. Crops were harvested with small plot combine harvesters or by hand.

Parameters to compare handling, transport and storage properties were drying time after treatment, AI abrasion during transport and AI stability in the formulation (AI degradation after 14 days at 54°C) and crystallization at low temperature (down to -10°C without and with crystal seeding) as well as AI stability on urea during storage (at 20°C and storage time up to 6 months). Applied methods were in-house methods based on AI transfer from fresh treated to untreated urea (drying time), AI analysis [3] [4] in abrasion dust after movement in a rotating metal barrel for 3 minutes (AI abrasion), AI analysis and crystallization rating (AI stability in formulation and on urea).

## Results

With the same AI concentration Limus reduced $NH_3$ emissions significantly compared to the MS (no UI: 13.1%, MS: 4.8%, Limus: 3.9% $NH_3$-N losses of applied N, basis: 80 experiments (2013-2015), SNK test 5%). To reach the same performance as the MS the AI concentration of Limus could be reduced between 30 and 40%. On average of 74 field experiments between 2012 and 2015 the yield increase by Limus was 2.1% compared to MS (no UI: 7.57 c, MS: 7.72 b, Limus: 7.88 t/ha a, SNK test 5%). Due to this higher N efficiency the N amount of Limus-treated urea can be reduced to reach same yield level of MS. The reason
for this higher efficiency of Limus is a synergistic action of the two AI which could be demonstrated by lab experiments. Due to its new formulation, Limus dried faster than on urea than MS (3 hours after treatment of urea 2.4% of MS AI and just 1% of Limus AI could still transfer to untreated urea). The faster drying time of Limus reduces risk of equipment blocking due to fertilizer aggregation. Also abrasion of AI from the surface of urea granules after mechanical stress was lower for Limus (AI concentration in the abrasion dust remaining in the testing equipment after treatment was 0.7% for Limus and was 2.0% for MS). Lower amounts of abrasion result in less AI loss as well as in less build-up in the blender equipment and so reducing cleaning effort and down-time of the blending system.

Positive effects of the new formulation were also found for AI storage stability in the formulation. At high temperatures (54°C for 14 days) AI loss was lower for Limus (0.2% in the Limus formulation and 1.2% in the MS formulation) and at low temperature (-10°C for 14 days) Limus formulation didn't crystalize out in contrast to the MS formulation. In such cases the MS formulation must be heated to redissolve the crystals before treating urea at low temperature e.g. during winter time. This is an additional effort which reduces flexibility of the fertilizer blenders. Biggest difference between Limus and MS is AI stability on urea during fertilizer storage. After 6 months storage time at 20°C and 70% relative humidity in open bags AI loss from MS-treated urea was 72% and for Limus-treated urea only 14%. Such high AI losses from MS-treated urea reduces possible storage time, biological performance and represent an economical loss for the farmer.
To compensate for these AI losses during storage, AI concentration in MS-treated urea must be clearly increased to be able to guarantee the stated biological performance after long-term storage and to stay above minimum AI concentration on urea according to EU/national fertilizer legislations.

## Conclusions

Thanks to the synergistic interaction of the two active ingredients NBPT and NPPT and a tailor made polymer-stabilized formulation the novel product Limus® shows better performance concerning reduction of NH₃ emissions, yield, handling, transport and storage in comparison to the NBPT based market standard.
Due to the higher efficiency of Limus the performance level of the market standard could be reached with a lower Limus concentration. The new formulation Limus also provides a shorter drying time, lower abrasion and especially longer AI storage stability on urea compared to market standard. These properties represent advantages for the farmer as well as for the fertilizer producer/distributors. This makes Limus an optimal solution to fulfill international and national efforts to reduce NH₃ emissions from urea-containing fertilizers.

[1] Kiss, S., Simihăian, M. 2002. Improving efficiency of urea fertilizers by inhibition of soil urease activity, Kluwer Academic Publishers, Dordrecht, Boston, London.

[2] Trenkel, M. 2010. Slow- and controlled-release and stabilized fertilizers: An option for enhancing nutrient use efficiency in agriculture, 2nd edition, International Fertilizer Industry Association, Paris.

[3] DIN EN 2008. Fertilizers - Determination of urease inhibitor N-(n-butyl)thiophosphoric triamide (NBPT) using high-performance liquid chromatography (HPLC), DIN EN 15668.

[4] DIN EN 2015. Fertilizers - Determination of urease inhibitor N-(n-butyl)thiophosphoric triamide (NBPT) and N-(n-propyl)thiophosphoric triamide using high-performance liquid chromatography (HPLC), DIN EN 16651
# COUPLING OF DAYCENT AND HYDRUS FOR STUDING THE WATER AND NITROGEN CYCLES IN SOILS WITH SHALLOW GROUNDWATER – A CASE STUDY IN NORTH ITALY

Elisa Cocco¹, Yao Zhang³, Barbara Lazzaro², Antonio Berti¹, Keith Paustian³, Francesco Morari¹

¹Department of Agronomy, Food, Natural resources, Animals and Environment, University of Padova, Padova, Italy, ²Veneto Region, Department of Agriculture and Rural Development, Sector Agri-environmental Policies, Mestre, Italy, ³Department of Soil and Crop Sciences, Colorado State University, Colorado, USA

## Objectives

DAYCENT model was selected as a tool to evaluate the effectiveness of agri-environmental measures in Veneto Region (northern Italy). Because the site is characterized by both free drainage and shallow ground-water conditions, particular attention must be paid to simulate water dynamic. Indeed, DAYCENT adequately represents the water movement in well-drained soil using the tipping bucket method for water infiltration and redistribution. However, the representation of water movement in shallow groundwater conditions is not exhaustive. In this work we replaced the native water sub-model of DAYCENT with the HYDRUS sub-routines which solve the Richard's equation for saturated-unsaturated water flow. A first evaluation of the efficiency of the coupled model to simulate water and nitrogen cycles is following reported.

## Method

Incorporation of HYDRUS 1-D water module into DAYCENT to create a coupled model (DAYCENT&HYDRUS).

Part of the code for integration was adapted from Yuan et al. (2011). During simulation a daily communication occurred between DAYCENT and HYDRUS module. DAYCENT calculates 1) the potential water flux from rain after interception of biomass or the amount of melted water, 2) the potential soil evaporation rate, 3) the potential transpiration rate, 4) root depth. The variables from HYDRUS that are returned to DAYCENT are 1) actual evaporation, 2) actual transpiration, 3) drainage (or capillary rise), 4) total net water flux for each node. Actual evapotranspiration (ETa) and soil water content were used from DAYCENT to growth plants and for C e N biogeochemical processes.

### Model testing

DAYCENT and DAYCENT&HYDRUS were tested using data measured in a lysimeter experiment in northern Italy. A three-year experiment (2011-2013) on continuous maize (Zea mays L.) was conducted in 12 loamy-soil lysimeters (1 x 1 m² width x 1.5 m depth). The factorial combination of three water table levels (free drainage - FD, water table at 60 cm - WT60 and water table at 120 cm - WT120 depths) with two N input levels ("Low" and "High") were evaluated. N input was a sum of organic+mineral nitrogen ("Low" =170+80 and "High" =250+118 kg N ha⁻¹ y⁻¹).

The experimental design was completely randomised with two replicates. Soil hydraulic parameters of the 120 cm profile were estimated by laboratory methods (e.g. Wind's method). Water balance was monitored considering the precipitation, irrigation, groundwater recharge and upflux and the soil water content. Moreover the nitrogen balance was calculated in terms of N-uptake and N leaching. Lysimeters were also equipped by an automatically chamber system to monitor N₂O emission from the soil.

## Results

DAYCENT was sensitive to N input simulating an higher biomass and crop yield according to the N input. In free drainage conditions, simulated yield and N uptake were close to the real ones, 251 vs 264 g C m⁻² y⁻¹ and 10.2 vs 11 g N m⁻² y⁻¹. Also, actual evapotranspiration (ETa) and percolation well fitted with the measured data. On the contrary, total biomass and yield were underpredicted when watertable boundary condition were simulated (WT60 and WT120), because the model was not able to describe the capillary rise (e.g. in WT120, simulated grain was 290 g C m⁻² y⁻¹ vs observed 504 g C m⁻² y⁻¹). Moreover, DAYCENT could not differentiate WT120 from WT60. In terms of water balance, percolation tended to zero, an obvious underestimate with respect to real values of about 220 mm, while simulated ETa was about the 63% and 61%
of the real ETa in WT120 and WT60, respectively.

DAYCENT &HYDRUS allowed to better represent the higher water availability in correspondence of shallow groundwater conditions. The simulated yield was more realistic than in DAYCENT e.g. in WT120 grain was 290, 600 and 503 g C m⁻² y⁻¹ for DAYCENT, DAYCENT &HYDRUS and lysimeters, respectively. In some cases, the crop production in the coupled model exceeded the real one, due to the transient water flow imposed by HYDRUS sub-routines.

Regarding the N₂O emissions, during crop growing season all nitrogen emitted was due to nitrification pathway in both the models. In FD condition, real emission was of 1.36 kg N-N₂O ha⁻¹ y⁻¹ vs 2.61 kg N-N₂O ha⁻¹ y⁻¹ and 1.65 kg N-N₂O ha⁻¹ y⁻¹ simulated by DAYCENT and coupled model, respectively. In WT120 emissions were 1.23 (real) vs 1.22 kg N-N₂O ha⁻¹ y⁻¹ and 2.45 kg N-N₂O ha⁻¹ y⁻¹ simulated by DAYCENT and DAYCENT&HYDRUS. During the winter period N₂O fluxes simulated by the coupled model in the shallow groundwater conditions were on average 8.9 kg N-N₂O ha⁻¹ y⁻¹, due to the denitrification pathway triggered by the water saturation in the deeper layers.

## Conclusions

The application of the DAYCENT &HYDRUS in free drainage conditions did not improve the results with respect to the original model. On the contrary, the coupled model favored a more dynamic representation of soil water content and in turn actual evapotranspiration, water distribution within the profile, crop productivities and N leaching. A problem persists in simulating the N₂O emissions that are higher than the measured ones. Such differences probably depend on the sensitivity of the denitrification module to the saturated soil water content. Indeed, soil water content influences soil-gas diffusion coefficient, and also the prediction of total denitrification flux (N₂+N₂O) and the repartition of N in N₂ and N₂O. A specific calibration of the algorithm for nitrogen emissions could improve the description of the N gaseous losses in shallow groundwater conditions.

## Acknowledgements

This research was co-financed by the Rural Development Programme for the Veneto 2007-2013.

## References

[1] Yuan, F., Meixner, T., Fenn, M. E., Simunek, J. (2011). Impact of transient soil water simulation to estimated nitrogen leaching and emission at high- and low-deposition forest sites in Southern California. Journal of Geophysical Research: Biogeosciences, 116, 1–15.
# THE APPORTIONING OF N₂O EMISSIONS TO NITRIFICATION OR DENITRIFICATION FROM DIFFERENT NITRATE SOURCES AT DIFFERENT WATER-FILLED-PORESPACES (WFPS)

Nadine Loick¹, Liz Dixon¹, Miguel Angel-Repullo¹, Veronica Ciganda¹, Maria Lopez-Aizpun¹, G. Peter Mat-thews², Christoph Müller³, Laura Cardenas¹

¹Rothamsted Research, Okehampton, UK, ²University of Plymouth, Plymouth, UK, ³IFZ Institut für Pflanzenökologie, Giessen, Germany

## Objectives

A series of laboratory incubation experiments suggested the existence of different pools of NO₃⁻ in soils. For the assessment of the utilisation of applied NO₃⁻ vs nitrified NO₃⁻ from applied NH₄⁺, the model developed by Müller et al. [1,2] can be used to calculate the immobilisation of added NO₃⁻ and NH₄⁺, nitrification of added NH₄⁺, mineralisation of organic N and subsequent nitrification by the analysis of the ¹⁵N in the soil as well as the ¹⁵N enrichment of the emitted N₂O.

Using our denitrification incubation system (DENIS, [3]) further developed to include real time measurements of ¹⁵N-N₂O, three experiments will be performed, each using twelve re-packed soil cores incubated within the DENIS and amended using the triple labelled N technique (¹⁵NH₄NO₃, NH₄¹⁵NO₃ and ¹⁵NH₄¹⁵NO₃) [1,2].

The WFPS will be set at a high, medium and low level to favour nitrification, a mixture of nitrification and denitrification, and denitrification.

## Method

Soil samples were taken from a typical grassland soil from SW England. The soil was air dried to ~20% H₂O, sieved to <2 mm and stored at 4°C until the start of the experiment. The soil was acclimatised to room temperature (RT) for 1 week before the moisture content was adjusted to correspond to the final WFPS (taking the later addition of 50 ml amendment solution into account). The soil was left loosely covered at RT for another week before soil cores were packed. Experiments were performed at 55% and 70% WFPS (with a further experiment at 85% WFPS to be done), each containing 4 different treatments with three replicates each. ¹⁵NH₄NO₃, NH₄¹⁵NO₃, ¹⁵NH₄¹⁵NO₃ and a control of KNO₃ serving as a treatment indicating total denitrification potential of the soil. This treatment was adjusted to 85% WFPS just before cores were placed into the incubation chamber. For each experiment 12 soil cores (140 mm diameter x 75 mm height) were packed to a bulk density of 0.8 g cm⁻³. Cores were left over night and after final moisture adjustment placed into the DENIS, where they were kept at 20°C. To remove native N2 from the soil, cores were flushed from the bottom with a mixture of He/O₂ (80:20) at 30 ml min⁻¹ for 4 days. Flow rates were then decreased to 12 ml min⁻¹ and the flow re-directed to flow over the surface of the soil core. For all treatments N was added at 75 kg N ha⁻¹ in 50 ml water via a sealed, He-flushed amendment chamber fixed to each vessel lid. Measurements were taken “continuously” for 15 days with one sample being analysed every 20 minutes resulting in four-hourly values for each vessel. Emissions of N₂O and CO₂ were measured by GC with an electron capture detector and N₂ with a helium ionisation detector, while NO concentrations were determined by chemiluminescence. ¹⁵N enrichment of the emitted N₂O was measured by mass spectrometry. All gas concentrations were corrected by the flow rate through the vessel and fluxes were calculated on a kg N or C ha⁻¹ basis.

## Results

The emitted N₂O was analysed for its ¹⁵N enrichment. At 55% WFPS the highest enrichment was found in the dual labelled treatment (¹⁵NH₄¹⁵NO₃, increasing to 9 atom% by day 13) indicating that both nitrification (NH₄-oxidation) as well as denitrification (NO₃-reduction) contributed to N₂O production at this moisture level. This was confirmed by the enrichment of N₂O in the two single labelled treatments. No significant difference was found between those two treatments in the ¹⁵N-enrichment of the produced N₂O and in both treatments the enrichment increased over the course of the experiment to around 6.5 atom%.

At 70% WFPS the highest enrichment was again found for the dual labelled treatment (¹⁵NH₄¹⁵NO₃). At this
higher soil moisture enrichment levels increase more rapidly and to a higher level (16.5 atom% by day 13). In contrast to the lower WFPS, enrichment levels of the single labelled treatments revealed that most of the N₂O derived from NH₄⁺. While the ¹⁵N-enrichment from the labelled ¹⁵NO₃⁻ increased similarly to the same treatment at 55% WFPS, the enrichment of N₂O from the labelled ¹⁵NH₄⁺ treatment increased more rapidly and to a higher level (13.5 atom%)

The model by Müller allows determination of N₂O emissions from added NO₃⁻ or from the added NH₄⁺ that has been nitrified. In addition, immobilisation of added NO₃⁻ and NH₄⁺, nitrification of added NH₄⁺, mineralisation of organic N and subsequent nitrification will be determined by the analysis of the ¹⁵N in the soil. We will add the data for nitrification/denitrification from this study.

A KNO₃ treatment was used in each experimental run to determine the denitrification potential of the soil under the given conditions. At 85% WFPS denitrification is promoted. The KNO₃ treatments in both experiments showed the typical appearance of the different gases as has been found in previous experiments [2]

## Conclusions

N₂O can be produced during nitrification as well as denitrification. Nitrification and denitrification may occur simultaneously in different microsites of the same soil but there is often uncertainty associated with which process dominates in a particular soil under specific conditions. Low WFPS is thought to promote nitrification, due to better aeration of the soil, while high WFPS is thought to promote denitrification during induced anaerobicity. 55% WFPS was considered to be favourable for nitrification, while WFPS above 80% would promote denitrification. At the chosen WFPS of 70% a combination of nitrification and denitrification is expected. The performed experiments give insight into the origin of the emitted N₂O and the major processes contributing to its emission and not only show the influence of the immediate WFPS on GHG emissions and the processes leading to them, but also highlight the effect of previous moisture conditions on GHG emissions and the denitrification potential of the soil under the given conditions.

## Acknowledgement

The authors are grateful to the BBSRC for financial support.

## References

[1] Müller, C., Rütting, T., Kattge, J., Laughlin, R. J., Stevens, R. J. 2007. Soil Biology & Biochemistry 39, 715-726

[2] Müller, C., Stevens, R. J., Laughlin, R. J. 2004. Soil Biology & Biochemistry 36, 619-632

[3] Cárdenas, L.M., Hawkins, J.M.B., Chadwick, D., Scholefield, D. 2003. Soil Biology & Biochemistry 35, 867-870

[4] Loick, N., Dixon, E.R., Abalos, D., Vallejo, A., Matthews, G.P., McGeough, K.L., Well, R., Watson, C.J., Laughlin, R.J., Cárdenas, L.M. 2016. Soil Biology & Biochemistry 95, 1-7
# FOCUS ON NUTRIENTS - A SWEDISH EXTENSION SERVICES PROGRAM

Stina Olofsson¹, Hans Nilsson², Maria Stenberg³, Katarina Börling⁴, Maria Fermvik¹, Anna Hagerberg¹, Per-nilla Kvarmo⁵, Cecilia Linge¹, Ulrika Listh⁴, Sofie Logardt¹, Johan Malgeryd⁵

¹Swedish Board of Agriculture, Alnarp, Sweden, ²Länsstyrelsen, Skåne, Sweden, ³Swedish Board of Agriculture, Skara, Sweden, ⁴Swedish Board of Agriculture, Uppsala, Sweden, ⁵Swedish Board of Agriculture, Linköping, Sweden

## Objectives

Focus on Nutrients (Greppa Näringen in Swedish) offers advice that benefits both the environment and the farm finances free of charge for the farmer. Focus on Nutrients started in 2001 and is a joint venture between The Swedish Board of Agriculture, The County Administration Boards and the Federation of Swedish Farmers. Focus on nutrients is funded by the EU Rural Development Program for Sweden.

The purpose of the project is to:

* reduce losses of greenhouse gases from agriculture; nitrous oxide, methane and carbon dioxide

* reduce losses of nitrate and phosphorus from farmland

* reduce ammonia emissions from animal production and manure handling

* avoid or reduce losses of pesticides into surface and groundwater

* increase energy efficiency on farms.

## Method

In order to fulfil the objectives the project focuses on increasing nutrient management efficiency by increasing the farmer's awareness and knowledge. The farmer is in focus and therefore the core of the project is education and individual on-farm advisory visits. Generally, a farmer needs to farm more than 50 hectares of arable land and/or have more than 25 livestock units in order to qualify for the individual counselling visits. When a farmer signs up to become a member the first step is a start-up visit, which includes calculating the farm's nutrient balance. A plan for future advisory visits is also made during the start-up visit. The advisory plan is based on the specific challenges that each farmer faces, which in turn vary depending on the type of production and environmental impact that the farm has. There are over 30 different types of advisory visits (consulting modules) to choose from. After approximately 3 years or 4-6 visits there is a follow-up visit where the farmer and advisor go through the changes made on the farm and which environmental and economic benefits these changes have resulted in. Farm nutrient balances, nitrogen leaching, ammonia and greenhouse gas emissions from the farm are calculated by the advisory tool VERA (VERA, 2016). VERA can also be used to make up fertilisation plans and calculate the nutrient content and amounts of manure produced. VERA was released in August 2015 and replaced an earlier tool, STANK in MIND.

## Results

Focus on Nutrients has a systematic approach to ensure the quality of the advice given by the extension services as well as to ensure the environmental benefits of the program. About 50 000 farm visits have been carried out since the beginning of the project. The on-farm visits are carried out by almost 300 advisors who employed by 70 different consultancy companies across Sweden. In 2011, Focus on Nutrients introduced advisory services on climate and energy efficiency, as well as advisory services aimed at meeting the objectives in the EU water framework directive.

Farm surpluses of nitrogen and phosphorus have decreased significantly since the start of the program mainly due to more efficient production on the farms (Nilsson & Olofsson, 2015). To achieve any long-term changes on the farm it is important to make repeated visits. The results from the program are regularly evaluated and the farmers and advisors have been very satisfied throughout the years (Focus on Nutrients, 2011).
Conclusions

Farm surpluses in nutrient balances were decreased by a program offering advices free of charge. Long-term changes in farm nutrient efficiency was improved by repeated visits by advisors at the farms.
# DIFFERENT NITROGEN SEASONAL DYNAMIC UNDER CONVENTIONAL AND CONSERVATION TILLAGE

Primož Žigon, Marjetka Suhaldoc, Rok Mihelič

University of Ljubljana, Biotechnical Faculty, Agronomy, Ljubljana, Slovenia

## Objectives

Interest on conservation tillage practices is growing because of its beneficial effects on soil quality and positive environmental impact. Conservation tillage, in comparison to conventional moldboard ploughing, minimizes soil disturbance and augment crop residue near the soil surfaces, which results in accumulation of soil organic carbon in the top soil and may also affect N transformation processes leading to changes in N dynamic and distribution in the soil profile. However these tillage effects are environmentally dependent and related to different types of soil and climate [1; 2]. The objectives of this study were (i) to determine influences of two different tillage intensities on temporal soil nitrogen dynamic and its distribution in soil profile of a shallow Cambisol in NE Slovenia and (ii) to potentially adapt fertilizer requirements regarding to the changes in plant available nitrogen contents.

## Method

Field experiment was carried out on a long term field trial in Moškanjci in Sub-Pannonia basin, Slovenia (46° 3', 15° 4'; 225 m a.s.l.) where two different soil cultivation systems including convectional tillage (CT) by moldboard plough (20 - 25 cm deep) and minimum tillage (MT) by vario-disc harrow (10 cm deep) have been compared side by side since 1999. Location is characterized by a continental climate (annual mean temperature 10.6°C and mean precipitation 913 mm), with shallow soil (40-60 cm) classified as a Cambisol formed over sand and gravel (loamy texture: 30-40 % sand, 42-48 % silt, 17-26 % clay) and pH of 6.0-6.5. During the period of investigation (April to October 2012) main crop, sunflower, was fertilized on 6th June by 40 kg N/ha (as CAN). Soil samples were taken from four randomly chosen plots sized 12 x 8 m each. The soil in both tillage treatments was sampled four times: after maize harvest in November 2011, 10 days after tillage in April 2012, during the vegetative growth of sunflower in July 2012, and after tillage and seeding of rye in October 2012. The soil samples were taken at depths of 0-10, 10-20 and 20-30 cm. Samples were dried at 40° C, ground to pass a 2 mm sieve and extracted by 0.01 M CaCl2 [3]. Ntot and Nmin (NO3-N and NH4-N) in the extracts were measured with autoanalyser (Bran Luebbe-Technicon), dissolved organic nitrogen (DON) was calculated from the difference between Ntot and Nmin.

## Results

13 years of continuous minimum tillage (MT) changed several chemical and physical soil properties in the upper 10 cm: higher OM content, water-stable 2-4 mm sized aggregates, and water-holding capacity [4]. The variations of the Nmin content in the 0-30 cm depth were higher in CT than in MT. Nmin was quite stable under MT during the year. CT resulted in significantly higher Nmin in April 2012, indicating the increased mineralization. The opposite situation was in hot and dry period of mid-July: Nmin was almost twice higher by MT in the upper soil layer. Year later at the same experimental site Kaurin et al. [4] reported about significantly higher microbial biomass in 0-10 cm depth by MT, which seems to provide better living conditions for the microbes and better resilience of microbial population to drought stress. The yield of sunflower was nearly the same (1.6 t dry seeds/ha) for the both tillage treatments, which indicates onset of increased mineralization in the spring by CT was not beneficial for the yield. In October 2012 after sunflower harvest and subsequent tillage and rye seeding CT again led to significant increase in Nmin content compared to MT, which could lead the NO3-N leaching during winter. Contents of Nmin progressively increased with depth (0-30 cm) by CT (leaching), whereas by MT there were no significant Nmin differences between the soil depths.

Temporal distribution of DON was more homogenous, differences between the tillage treatments were significant only in the summer with the highest contents of DON by MT. Soil profile distribution of DON showed the same trend as Nmin distribution in the same time. Significantly higher contents of DON in top (0-10 cm) of MT soil were also reported by Kaurin et al. [4].
Conclusions

13 years of practicing different tillage treatment resulted in changed dynamic of Nmin. By CT temporal dy-
namic is more intensive and related to greater disturbance of soil profile. Higher Nmin contents in summer
by MT may indicate on better soil condition for microbial activity even in more dry conditions. In autumn
advantage of minimal soil disturbance regarding to plowing has been shown in decreased mineralization of
soil nitrogen and reduced potential for nitrate leaching during the winter. Delayed beginning of mineraliza-
tion processes in spring time may cause nitrogen deficiency for winter crops in early season, but not very
likely for the summer crops in conditions of gravelly Cambisol in NE Slovenia.

[1] Gomez-Rey M. X., Couto-Vazquez A., Gonzalez-Prieto S. J. 2012. Nitrogen transformation rates and nu-
trient availability under conventional plough and conservation tillage. Soil & Tillage Research, 124: 144-152

[2] Wright L. A., Hons M. F., Lemon G. R., McFarland L. M., Nichols L. R. 2007. Stratification of nutrients in soil for different tillage regimes and cotton rotations. Soil & Tillage Research, 96: 19-27

[3] Houba V. J. G., Temminghoff E. J. M., Gaikhorst G. A., van Wark W. 1999. Soil analysis procedures, ex-
tractions with 0.01 M CaCl2. Wageningen, Agricultural University: 95 p.

[4] Kaurin A., Mihelič R., Kastelec D., Schloter M., Suhadolc M., Grčman H. 2015. Consequences of mini-
mum soil tillage on abiotic soil properties and composition of microbial communities in a shallow Cambisol
originated from fluvioglacial deposits. Biology and fertility of soils 2015 v.51 no.8 pp. 923-933.
# TOP DRESSING NITROGEN RECOMMENDATION IN WHEAT AFTER APPLYING ORGANIC MANURES. USE OF FIELD DIAGNOSTIC TOOLS

Marta Aranguren, Ander Castellón, Ana Aizpurua

NEIKER Institute of Agriculturlal Research and Development, Derio (Bizkaia), Spain

## Objectives

Evaluate the usefulness of the proxy tools N-tester and RapidScan for diagnosis of nitrogen nutritional status in the field when farmyard manures are applied.

## Method

A field trial was established in Arkaute (Basque Country, Spain) in the 2014-2015 winter wheat growing season and 16 N fertilization treatments tested. Three kinds of initial fertilization were applied: dairy slurry (40 t/ha), sheep farmyard manure (40 t/ha) and conventional (not organic fertilizer on basal dressing and 40 kg N/ha at tillering). These three types of fertilization were combined with five N dose at top dressing applied at stem elongation (0, 40, 80, 120 and 160 kg N/ha). The experimental design was a factorial randomized block with four replicates. Dairy slurry dry matter (DM) content was 8.99%; N-NH₄⁺ (2.6%); total N (4.8 kg/t); P₂O₅ (1.8 kg/t); and K₂O (3.4 kg/t); and sheep manure DM was 38.02%; total N (8.4 kg/t); P₂O₅ (6.2 kg/t); and K₂O (15.3 kg/t). Soil texture was sandy clay loam, soil P and K content were high and pH was 8.55. The proxy tools for the diagnosis of the N nutritional status tested (©Hydro-N-tester of Yara and RapidScan CS-45 (Holland Scientific)) were used at stem elongation. ©Hydro-N-tester measures the light transmittance in red and near infrared and calculates a numeric value that estimates chlorophyll content. RapidScan CS-45 measures the reflectance of crop canopy, provides the NDVI Index and estimates the photosynthetically active biomass. Normalized values were calculated to avoid the noise encountered by variables other than N fertilization and were calculated as a percentage by assigning the 100% value to an overfertilized control plot, which received 280 kg N/ha. Three rows of wheat one meter long were cut before applying the top dressing at stem elongation. Biomass was estimated and N concentration determined from these samples in order to calculate ‘Nitrogen nutrition index (NNI)’ [1]. Grain and straw yield, and yield components of each treatment were measured at harvest.

## Results

There were not significant differences among NNI values before applying N at stem elongation for the three initial fertilization treatments, ranging from 0.29 for sheep manure and 0.37 for dairy slurry. This values were low (NNI<1), so N was limiting for wheat [1], even at the conventional treatment, where 40 kg N/ha had been applied at tillering. Accordingly, at tillering, just before the first N application, soil mineral N at 0-60 cm depth was lower than 30 kg N/ha in all treatments. ©Hydro-N-tester and RapidScan CS-45 gave the same results and showed higher values at the conventional treatment without manure application and 40 kg N/ha at tillering (87%), than dairy slurry and sheep manure treatments (65%). Crop yield response was adjusted to a Quadratic-Plateau Model, being the N optimum rate at stem elongation 98 kg N/ha at conventional treatment (total dose 138 kg N mineral/ha) and 118 kg N mineral/ha at dairy slurry and sheep manure treatments. Maximum yields were about 8.500 kg/ha. The number of spikes/m² when N was not applied at stem elongation was greater for the conventional treatment, due to the effect of the 40 kg N/ha applied at tillering. However, when N was provided at stem elongation these differences in the number of spikes/m² disappeared. These results confirm findings of other authors [2] who observed that even suffering early N stress it is possible to achieve maximum yields when N is applied later. To obtain the maximum protein value in grain (around 11%) the highest dose of N, 160 kg N/ha, was necessary at stem elongation for any of the initial fertilizations tested. Differences obtained in the optimum dose of N applied at stem elongation, evidenced that the proxy tools correctly diagnosed different nutritional situations that NNI was not able to predict. Thus, treatments with organic basal dressing needed 20 kg N mineral/ha less than the conventional treatment. Tools tested are not invasive and measurements can be repeated several times along the growth period, so information obtained on crop N status dynamics can be used for decision making in N fertilizer management [3].
**Conclusions**

These preliminary results look promising in order to modulate N application rate at stem elongation, but more studies are needed to further evaluate these field devices under different conditions and make specific N recommendations.

**Acknowledgments**

This work has been financially supported by INIA from the Spanish Government (Project nº RTA2013-00057-C05) and the Department of Economic Development and Competitiveness from the Basque Government, which also supported this work with a grant.

**References**

[1] Justes, E., Mary, B., Meynard, J.M., Machet J.M. & Thelier-Huche L. 1994. Annals of Botany 74, 397-407.

[2] Morris, K.B., K.L. Martin, K.W. Freeman, R.K. Teal, K. Girma, D.B. Arnall, P.J. Hodgen, J. Mosali, W.R. Raun & J.B. Solie. 2006. J. Plant Nutr. 29, 727-745.

[3] Lemaire, G., Jeuffroy, M.H. & Gastal, F. 2008. European Journal of Agronomy 28, 614-624.
# CROPPING SYSTEMS FOR TRANSFER OF SOIL MINERAL N IN ORGANIC GREEN MANURE LEYS TO SUBSEQUENT SPRING WHEAT

Ann-Charlotte Wallenhammar, Eva Stoltz

HS Konsult AB, Örebro, Sweden

## Objectives

There is a shortage of organic quality spring wheat with protein content greater than 12 % demanded by the milling industry in Sweden. The organic fertilizers commonly used in stockless organic wheat production are generally not sufficient to achieve high enough nitrogen availability during the growing season of wheat. Therefore, the protein concentration in organically produced spring wheat grains is often too low to qualify for premium price. Rotational grass/clover leys are sometimes used as green manure crops in organic farming, but the transfer of N from the green manure to subsequent spring wheat are generally not efficient due to losses [1].

The objective of this study was to quantify the nitrogen effect of using annual crops established after incorporation of grass/clover to carry nitrogen to subsequent spring wheat.

## Method

The investigations were carried out 1997-2001 in twenty field experiments located at ten farms in organic production in central Sweden. The ley was established in spring cereals and allowed to grow during two seasons. The experiment starts with the incorporation of the grass/clover during the third autumn after sowing. The grass/clover ley consisted of red clover (*Trifolium pratense*) with timothy (*Phleum pratense*) and meadow fescue (*Festuca pratense*) as companion grasses. The tillage was performed with a mouldboard plough. The treatments were, a) Incorporation (IC) of ley in early August, catch crop: frost sensitive winter oilseed rape (*Brassice napus* L,) (IC Aug + WOSR), b) Incorporation of ley in early August, catch crop: 1997-1998 spring turnip rape (*B. campestris* L), 1999-2000 white mustard (*Sinapsis alba* L) (IC Aug + SOTR or WM), c) Incorporation of ley in early October, no catch crop (IC Oct), d) Incorporation of ley in early November, no catch crop (IC Nov), e) Incorporation of ley in April before sowing (IC April). The duration of catch crops lasted until the following spring, and was incorporated with a harrow into the soil right before seedbed preparation. The catch crop in treatment b (IC Aug + SOTR or WM) was changed from spring turnip rape to white mustard in 1999, since the growth potential of SOTR was low. The treatment (IC April) was added to the experiments in 1998 as a control treatment to demonstrate the effects of a late onset of mineralization. Spring wheat, were sown in all field trials. Grain yield was determined at harvest. Dry matter (DM) and Kjeldahl N content of grain was analyzed. Soil samples were collected on two occasions; at sowing and after harvest at 0-30 cm, 30-60 and 60-90 cm and were analysed for soil mineral N (SMN) (NH₄-N and NO₃-N). The systems were evaluated on the variables time point of incorporating the ley and on the choice of catch crop.

## Results

The investigations were carried out 1997-2001 in twenty field experiments located at ten farms in organic production in central Sweden. The ley was established in spring cereals and allowed to grow during two seasons. The experiment starts with the incorporation of the grass/clover during the third autumn after sowing. The grass/clover ley consisted of red clover (*Trifolium pratense*) with timothy (*Phleum pratense*) and meadow fescue (*Festuca pratense*) as companion grasses. The tillage was performed with a mouldboard plough. The treatments were, a) Incorporation (IC) of ley in early August, catch crop: frost sensitive winter oilseed rape (*Brassice napus* L,) (IC Aug + WOSR), b) Incorporation of ley in early August, catch crop: 1997-1998 spring turnip rape (*B. campestris* L), 1999-2000 white mustard (*Sinapsis alba* L) (IC Aug + SOTR or WM), c) Incorporation of ley in early October, no catch crop (IC Oct), d) Incorporation of ley in early November, no catch crop (IC Nov), e) Incorporation of ley in April before sowing (IC April). The duration of catch crops lasted until the following spring, and was incorporated with a harrow into the soil right before seedbed preparation. The catch crop in treatment b (IC Aug + SOTR or WM) was changed from spring turnip rape
to white mustard in 1999, since the growth potential of SOTR was low. The treatment (IC April) was added
to the experiments in 1998 as a control treatment to demonstrate the effects of a late onset of mineralization.
Spring wheat, were sown in all field trials. Grain yield was determined at harvest. Dry matter (DM) and
Kjeldahl N content of grain was analyzed. Soil samples were collected on two occasions; at sowing and after
harvest at 0-30 cm, 30-60 and 60-90 cm and were analysed for soil mineral N (SMN) (NH₄-N and NO₃-N).
The systems were evaluated on the variables time point of incorporating the ley and on the choice of catch
crop.

Conclusions

In conclusion, an early turn under of ley followed by an easily decomposed catch crop, e.g. white mustard, compared with a later turn under of ley, will result in a higher yield of spring wheat and a in protein content >12 % of the grain. Our results show that production of organic spring wheat with baking quality is possible with an N source relying on a green manure ley in combination with a catch crop.

Our results show that the content of soil mineral N is detrimental for organic spring wheat production of premium quality. Green manure crops incorporated in early August, followed by an easily decomposed catch drop e.g. white mustard provide a transfer of soil mineral N superior to incorporating the ley in early October, early November or in April the following year.

Acknowledgements

This study was financially supported by the Swedish Board of Agriculture.

References

[1] Thorup-Kristensen, K., Magid, J., Stoumann Jensen, L. 2003. Catch crops and green manures as biologi-cal tools in nitrogen management in temperate zones. Advances in Agronomy,79, 227-302.

[2] Andersen, M.K., Jensen, L.S. 2001. Low soil temperatures on short-term gross N mineralisaitio0n- im-mobilization turnover after incorporating a green manure. Soil Biology & Biochemistry, 33, 511-521.
# EFFECT OF VARYING DOSES OF SOIL APPLIED UREA ON GROWTH AND PRODUCTION POTENTIAL OF QUINOA (Chenopodium quinoa Willd.)

Muhammad Bilal Chattha¹, Muhammad Umer Chattha², Hassan Munir², Muhammad Usman Aslam², Muhammad Usman Chattha³, Muhammad Nasir Subhani¹

¹University of the Punjab, Lahore, Lahore, Punjab, Pakistan, ²University of Agriculture, Faisalabad, Faisalabad, Punjab, Pakistan, ³Bahauddin Zakarya University, Multan, Multan, Punjab, Pakistan

## Objectives

Quinoa (Chenopodium quinoa Willd.), a lesser-known food and feed crop is gaining acceptance in Pakistan. It is being cultivated to develop its production technology under local conditions. A balanced fertilization ensures the maximum economic return. Therefore, a field experiment was proposed to optimize the dose of nitrogenous fertilizer on the phenology and production potential of quinoa.

## Method

Quinoa seeds of three accessions collected from the department of Crop Physiology, University of Agriculture Faisalabad Pakistan were sown on sandy loam soil of pH 7.9 and EC of 1.74 dS m⁻¹ at Agronomy students' farm during 2nd week of November 2012 with 15 cm and 75 cm as distances between plants and rows, respectively. Study was performed in randomized complete block design (RCBD) with split plot arrangement in three replications. Three genotype viz. HBM-3, HMB-4, HMB-5 were assigned in main plot and four nitrogen levels (80, 100, 120 and 140 kg ha⁻¹) were kept in subplots. All the other Agronomic practices were carried out using standard procedure for quinoa crop. Growth and yield data were recorded by adopting standard procedure and quality analysis were made from the samples.
Leaf area index, leaf area duration, crop growth rate and net assimilation rate were derived adopting formulae as described by Hunt (1978) at various crop stages. Data was analyzed using MSTAT C Program (MSTAT Development Team, 1989). Least Significant difference (LSD) test at 5% level of probability was used to compute the mean values (Steel et al., 1997).

## Results

Results revealed that all the growth and yield related traits such as leaf area index, leaf area duration, crop growth rate, net assimilation rate, plant height, stem diameter, number of panicles per plant, main panicle length, and thousand grain weight were maximum for genotype HMB4 and minimum for genotype HMB5 among three genotypes. While in case of nitrogen levels an increasing trend, in growth and yield components was recorded with in nitrogen levels from 80 to 140 kg N ha⁻¹ except thousand grain weight which were maximum at 100 kg N ha⁻¹. However interaction was non-significant except biological yield, economic yield and harvest index which were maximum for genotype HMB-4 at nitrogen level of 100 kg ha⁻¹. Nitrogen application also increased leaf chlorophyll content (40.124 mg g⁻¹Fresh wt.) and total phenolics (9.2976 mg g⁻¹fresh wt.) when soil was fertilized with 140 kg N ha⁻¹ and 80 kg N ha⁻¹ respectively.

## Discussion

Nitrogen is most important determinant of growth and yield of crops among all major plant nutrients. Deficiency of nitrogen in crops plants causes stunted growth and chlorosis (yellowing) of leaves due to decreased level of chlorophyll content. Nitrogen fertilization significantly increased the growth related traits like leaf area, leaf area index, leaf area duration, crop growth rate, net assimilation rate and total dry matter up to maximum nitrogen level i.e. 140 kg ha⁻¹. Increase in chlorophyll content not only increase the leaf area but also the nitrogen assimilation resulting in better growth and development of crop. Nitrogen supply also increases rates of cell division and expansion, photosynthesis and leaf production. The source sink relationship is due to the development and maintenance of leaf area which is influenced by nitrogen as a result photosynthetic efficiency as well as dry matter partitioning to reproductive organs improved under optimum nitrogen availability and translocation of photo assimilates from source (leaves) to sink (grain) during grain development. Significant increase in yield contributing traits by soil supplementation with nitrogen (100 kg ha⁻¹) resulted in substantial increase in grain yield. Increase in biological yield by nitrogen application might
be due to improved leaf area development and photosynthetic efficiency due to fact that N is a part of Ru-
bisco which resulted in improved plant height, leaf area index and crop growth rate which increased the bio-
logical yield. Varying levels of nitrogen fertilization resulted in increased harvest index of quinoa genotypes.
Higher the harvest index, greater will be the physiological potential for converting dry matter into economic
part. It might also be due to nitrogen ability to enhance the translocation of photo assimilates from vegeta-
tive to reproductive parts, which may increase the grain yield and consequently the harvest index in quinoa.

Conclusions

Nitrogen application increased all growth related traits like leaf area index, leaf area duration and crop growth rate, net assimilation rate with increasing nitrogen rates. Nitrogen dose of 100 kg ha⁻¹ contributing to substantial increase in economic yield, biomass production and harvest index in quinoa genotypes under semi-arid conditions.

References

[1] FAO. 2003. The State of Food Insecurity in the World. Published by the Food and Agriculture Organiza-
tion of the United Nations Viale delle Terme di Caracalla, 00100 Rome, Italy.

[2] Jacobsen, S.E., A. Mujica and R. Ortiz. 2003. The global potential for quinoa and other Andean crops. Food Rev. Inter., 19: 139-148.

[3] Ogungbenle, H.N. 2003. Nutritional evaluation and functional properties of quinoa (*Chenopodium quinoa* Willd.) flour. International Journal of Food Sciences and Nutrition 54: 153-158.

[4] Repo-Carrasco R, C. Espinoza and S.E. Jacobsen. 2003. Nutritional value and use of the Andean crops quinoa (*Chenopodium quinoa*) and kañiwa (*Chenopodium pallidicaule*). Food Rev. Int., 19:179-189.

[5] Shams, A.S. 2010. Combat degradation in rainfed areas by introducing new drought tolerant crops in Egypt. 4th International Conference on Water Resources and Arid Environments, Riyadh, Saudi Arabia, 5-8 December, 575-582.

[6] Shams, A.S. 2012. Response of quinoa to nitrogen fertilizer rates under sandy soil conditions. 13th international Conf. Agron faculty of Agric., Benha Univ., Egypt, 9-10 September, 195-205.

[7] Vega-Gálvez, A., M. Miranda, J. Vergara, E. Uribe, L. Puente and E.A. Martínez. 2010. Nutrition facts and functional potential of quinoa (*Chenopodium quinoa* Willd.), an ancient Andean grain: a review. J. Sci. Food Agric. 90: 2541-2547.
# NITROGEN LEACHING RISK FROM PREFERENTIAL FLOW IN A STONY SOIL IRRIGATED BY CENTRE PIVOT

Rogerio Cichota³, Francis Kelliher³, Steve Thomas¹, Patricia Fraser¹, Sam Carrick², Gina Clemens¹

¹Plant and Food Research, Christchurch, New Zealand, ²Landcare Research, Christchurch, New Zealand,

³AgResearch, Christchurch, New Zealand

## Objectives

The area of irrigated land in New Zealand is increasing and it is expanding fast in the South Island on areas with stony soils. Such soils are considered vulnerable to nutrient leaching losses and likely to exhibit preferential flow. Nitrogen (N) losses from irrigated dairy farms are a major concern in many regions. This study aimed to investigate whether irrigation intensity has an effect on preferential solute transport in a typical New Zealand stony soil. Data was gathered from an experiment performed in large lysimeters under different irrigation regimes where a non-reactive tracer was applied on the soil surface. The Burns' equation was fitted to the measured data to infer the fraction of soil water that takes part in the solute transport. An exponential function was proposed to extrapolate these results. This approach was then used to describe the potential risk of nitrogen leaching under a centre-pivot irrigation system.

## Method

The experiment was conducted under rain shelter in December 2014 at the lysimeter facility of Plant and Food Research at Lincoln, NZ. 12 lysimeters, with 500 mm diameter and 700 mm length, were collected from a dairy farm following the procedure described by Cameron et al. [1]. The soil was a Lismore Stony Silt Loam (Typic Dystrustept), with total porosity of 57% (fine earth fraction) and stone content varying between 17% in the surface to 64% at the base of the lysimeters. Two irrigation treatments were used, with application intensities of 5 mm/h and 20 mm/h, kept constant during the experiment. The irrigation lasted until the equivalent of approximately three pore volumes of leachate were collected. All lysimeters received an application of chloride (as KCl, at a rate equivalent to 400 kg/ha) after approximately one pore volume had been leached. The leachate was collected at regular intervals, stored at 4°C, and subsequently analysed using ion exchange chromatography. The Burns' equation, following the approach presented by Scotter et al. [1], was used to describe the leaching series of the non-reactive tracer in each irrigation treatment. In this approach, the proportion, X, of a solute leached below a given depth, z (mm), is a function of cumulative drainage, I (mm):

$$X = \exp(-z\theta_{FC}f_t/I)$$

where $\theta_{FC}$ (m³/m³) is the soil water content at field capacity, and $f_t$ represents the fraction of water that effectively takes part in the solute transport. An exponential function was then used to describe the relationship between $f_t$ and the irrigation intensity, J (mm/h):

$$f_t = 1 + m[\exp(-bJ) - 1]$$

where m and b are fitting parameters. It was assumed that $f_t$ should be equal to one when irrigation intensity approaches zero, that is, the whole soil water takes part in the solute transport. The two functions above were then used to infer the value of $f_t$ as function of the irrigation intensity, as it varies across the length of a centre-pivot, and subsequently to estimate the potential risk of nitrogen leaching losses as function of the length of this irrigation system. The leaching risk was defined as the proportion of solute leached below the depth of 0.5m after 100mm of drainage.

## Results

The results from chloride leaching provided strong evidence of preferential solute transport in the Lismore stony soil, and corroborated other studies with stony soils in New Zealand [2, 3]. The Burns' equation was able to describe the experimental data well and thus, following the interpretation of Scotter et al. [1], it was
used to characterise the extent of preferential flow in this soil. This approach is simpler than most standard
models, it requires only basic soil properties and has only one fitting parameter ($f_t$). Based on the estimat-
ed values of $f_t$, irrigation intensity was found to have a significant effect on preferential solute transport.
The mean value of $f_t$ was reduced from 0.85 for 5 mm/h to 0.58 for 20 mm/h. Such values are in general
agreement with estimates for other similarly stony New Zealand soils [2, 3]. A smaller value of $f_t$ means
faster movement of solute and therefore a higher risk of leaching losses, as it can be inferred from Burn's
equation.

With the assumption that the fraction of soil water that takes part on solute transport is equal to one as in-
tensity approaches zero, an exponential function was found reasonable to describe the relationship between
irrigation intensity and $f_t$. This function suggests that $f_t$ decreases as the irrigation intensity increases, and it
reaches a plateau as irrigation increases beyond approximately 50 mm/h, with asymptote value of 0.35. This
relationship can then be employed to estimate the likely values of $f_t$ for varying irrigation intensities.

Centre pivots have variable application intensities along their length in order to compensate for the fast-
er speed of nozzles away from the centre. Considering the results of our study, lower values of $f_t$ can
be expected along the length of the pivot and thus higher risk of leaching losses. Moreover, the area
irrigated by each nozzle is much larger away from the centre. The potential risk for N leaching, i.e. the
fraction of solute leached below a given depth, as function of centre pivot length can thus be estimated by
combining the results from Burn's equation and the area irrigated. It can be shown that, for a soil exhibiting
preferential flow, the risk of leaching is considerably higher under the variable intensity of a centre pivot
than it would be expected if the intensity was constant. This results should be tested further for different
soils, but raise concerns over the estimation of the impact of irrigation systems on the environment. The in-
crease in irrigation systems in New Zealand is linked to the expansion of dairy farming, such intensive land
use has been linked to N leaching from effluent and especially urine depositions. The design and manage-
ment of irrigated systems should thus take in consideration the potential leaching risk due to high intensity
irrigation.

Conclusions

The experimental data was successfully described using the Burns' equation, which was used to quantify the
fraction of the soil pore space (') involved in solute transport. The results were sufficient to confirm a sig-
nificant effect of irrigation intensity on preferential solute flow in the stony soil of this study. The presence
of preferential flow is a concern as it suggests that the risk of leaching losses should increase as irrigation
intensity increases. An exponential function was used to relate the values of and irrigation intensity and
employed to assess the risk of N leaching under irrigation by a centre pivot. More studies are needed to
better understand this relationship. This approach can then be used to aid on the design and management of
irrigation systems.

Acknowledgements

This work was conducted through the Land Use Change and Intensification programme of Plant and Food
Research

References

[1] Scotter, D.R.; White, R.E.; & Dyson, J.S. 1993. The Burns leaching equation. *Journal of Soil Science*, 44(1):25-33.

[2] Pang, L.; McLeod, M.; Aislabie, J.; Šimůnek, J.; Close, M.; & Hector, R. 2008. Modeling transport of microbes in ten undisturbed soils under effluent irrigation. *Vadose Zone Journal*, 7(1):97-111.

[3] Carrick, S.; Cavanagh, J.; Scott, J.; & McLeod, M. 2014. Understanding phosphorus, nitrogen, and cadmium transfer through a young stony soil. *Nutrient management for the farm, catchment and community*. Palmerston North, New Zealand: Fertiliser and Lime Research Centre. pp. 1-11.
# REYGRASS OVERSOWING IN SOYBEAN AS AN ALTERNATIVE TO REDUCE NITROUS OXIDE EMISSIONS IN INTEGRATED CROP-LIVESTOCK SYSTEM

Sandro José Giacomini¹, Getúlio Elias Pilecco¹, Sylvie Recous², Majid Mahmood Tahir³, Raquel Schmatz¹,
Carolina Schultz Pollet¹, Adriane Schu¹, Celso Aita¹

¹Department of Soil Science, Federal University of Santa Maria, 97105-900 Santa Maria, RS, Brazil, ²INRA, UMR614 Fractionnement des Agroressources et Environnement, F-51000 Reims, France, ³Department of Soil and Environmental Sciences, Faculty of Agriculture, The University of Poonch, Rawalakot, 12350, Azad Jammu and Kashmir, Pakistan

## Objectives

Integrated crop-livestock system (ICLS) is defined as a rotation of annual summer crops with winter pastures, which helps in practicing agricultural and livestock activities within the same area. In southern Brazil, ICLS is mainly characterized by the use of soybeans for grain production in the summer and ryegrass for forage production in winter. The most common strategy of ryegrass use is its sowing after soybean harvest. However, sowing of ryegrass when soybean is in R6-R7 stage i.e. at the time of senescence of leaves, appeared as a strategy to anticipate the supply of forage to animals. The aim of this study was i) to compare two options of ryegrass sowing, i.e. oversowing of ryegrass or sowing after the soybean harvest, on N₂O emissions and ii) to compare the N₂O emissions of between ICLS and systems exclusively devoted for grains production.

## Method

The experiment was conducted from November 2011 to October 2013 on a Typic Hapludalf (60% sand, 30% silt, 10% clay, total C 7.5 g kg⁻¹) at the Department of Soil, Federal University of Santa Maria (29°41′S, 53°48′W), Brazil. The treatments were three crop rotations (summer/winter): CR1- soybean/ryegrass (*Lo lium multiflorum*) in post harvest (late sowing); CR2- soybean (*Glycine max*)/ryegrass in oversowing; and CR3- soybean/oilseed rape (*Brassica napus*) in 2011/12 and soybean/wheat (*Triticum aestivum*) in 2012/13. CR1 and CR2 are characteristic of ICLS and CR3 of grain production systems. All crop rotations have been managed under no-till. During the two years and in all rotations, soybean was sown in November, while ryegrass in the CR1 and CR2 was sown 15 days after soybean harvest (May) and 30 days before soybean harvest at the stage R6-R7 of soybean (March), respectively. The oversowing of ryegrass in CR2 was held manually. In CR3, oilseed and wheat were sown on 30 (May 2012) and 45 (June 2013) days after soybean harvest, respectively. The treatments were organized in a randomized complete block design with four replications. The size of the plot was 25m². Phosphorus and potassium were applied to soybean, wheat and oilseed rape before sowing. However, urea-N (60 kg ha⁻¹) was applied only in wheat and oilseed rape. Soil N₂O fluxes were measured periodically by the closed static chamber technique. The N₂O concentrations in the samples were analyzed by gas chromatography (Shimadzu GC-2014 Greenhouse). Daily N₂O fluxes (µg N m⁻² h⁻¹) were calculated by linear interpolation and the cumulative fluxes (g N ha⁻¹) were calculated by the integration of the daily N₂O emissions. Gravimetric soil moisture (105°C for 24 h), soil inorganic N (NH₄ and NO₃) and water-filled pore space (WFPS) were determined in the 0-10 cm soil layer on each gas sampling date.

## Results

The N₂O-N fluxes ranged from -22.9 to 173.6 µg m⁻² h⁻¹ in the first year and from -5.0 to 252.2 µg m⁻² h⁻¹ during the second year of the study. In both years, the largest fluxes of N₂O-N occurred in the period between the start of senescence of soybean leaves (74 days after sowing) and two weeks after soybean harvest (157 days after sowing). Likely, this has occurred due to increased availability of C and N in the soil, mainly by the decomposition of soybean senescing leaves. This condition, combined with periods of low O₂ availability in the soil, increased N₂O production by denitrification process. During this period, oversowing of ryegrass (CR2) reduced the mean N₂O-N flux by 11% in the first year compared to CR1 and CR3 and by 16% and 24% in the second year in relation to CR1 and CR3, respectively. Two weeks after soybean harvest
N₂O-N fluxes were reduced in all rotations with CR2 presenting the lowest flows. Annual N₂O-N emissions did not vary greatly between two years (938 and 1,064 g ha⁻¹), being higher in CR3 (1,176 g ha⁻¹) than in CR1 (1,006 g ha⁻¹) and CR2 (821 g ha⁻¹). The largest emissions of N₂O-N in CR3 were due to the use of N fertilizer (60 kg N ha⁻¹) in grain crops (oilseed and wheat) after soybean. The oversowing of ryegrass in CR2 reduced cumulative emissions of N₂O-N by 30% and 18% in comparison to the late sowing of ryegrass in CR1 and grain crops in CR3, respectively. Although the oversowing of ryegrass has reduced N₂O emissions from its sowing to soybean harvest, the main effect of this practice was seen from soybean harvest and by the end of ryegrass, oilseed and wheat cultivation. On an average of two years, the cumulative emission of N₂O-N in this period decreased in the following order CR3 (340 g ha⁻¹)> CR1 (186 g ha⁻¹)> CR2 (83 g ha⁻¹). The oversowing of ryegrass anticipated the establishment of grass that used the N mineralized from senescent leaves and crop residues of soybean, thereby reducing mineral N content in the soil and consequently its possible loss in the form of N₂O, with agronomic and environmental benefits.

## Conclusions

The results of this study indicate that the ICLS with soybean in summer and ryegrass in winter (soybean/ reygrass) have lower N₂O emissions compared to grain production systems (soybean/oilseed and soybean/ wheat). The oversowing of ryegrass reduced N₂O emissions in relation to its sowing after soybean harvest and therefore can be considered as a mitigating practice of N₂O emissions in the ICLS under no-till conditions.

## Acknowledgments

This work was supported by the Brazilian government through the Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) and Fundação de Amparo à Pesquisa do Estado do Rio Grande do Sul (FAPERGS).
EFFECT OF N SOURCE ON GROWTH, YIELD, YIELD COMPONENTS AND YIELD OF BUCKWHEAT IN THE FENUGREEK/BUCKWHEAT INTERCROPPING

Aliyeh Salehi, Seyfollah Fallah

Shahrekord university, shahrekord, Iran

**Objectives**

To meet the requirements of sustainable development for feeding the increasing population in the world, farmers and scientists have developed many valuable eco-agricultural techniques. These include integrate systems and applying organic fertilizers [1, 2]. Also improving productivity and soil fertility is important to increasing production on medicinal plant. The present study investigated effect of fertilizer sources on growth, yield and yield components of buckwheat in intercropped with fenugreek.

**Method**

A field factorial experiment was conducted in randomized complete block design at research farm of Shahrekord University, Iran in 2014. Sole cropping of fenugreek (F), sole cropping of buckwheat (B) and three intercropping ratios (F:B; 2:1 (two rows of fenugreek + one row of buckwheat), 1:1 (one row of fenugreek + one row of buckwheat) and 1:2 (one row of fenugreek + two rows of buckwheat)), were evaluated as the first factor and three sources of fertilizer consist of chemical fertilizer (CF), broiler litter (BL) and integrated fertilizer (IF); (50% CF+ 50% BL) and as the second factor. The measured traits were plant height, No. branch plant⁻¹, No. nod plant⁻¹, 1000-seed weight, seed yield, biological yield and harvest index for buckwheat and fenugreek, No. spike plant⁻¹, No. seed spike⁻¹ for buckwheat and also No. pod plant⁻¹ and No. seed pod⁻¹ for fenugreek. Analysis of variance (ANOVA) was performed by SAS software and fisher's least significant difference (LSD) was used for comparison of means

**Results**

The results showed that N source, intercropping ratio and interaction of N source and intercropping ratio had a significant effect (p < 0.01) on the most of studied characters of buckwheat and fenugreek.

The results indicated that intercropping ratios significantly increased the most of studied characters in comparison with sole crop. The F:B (2:1) increased No. spike plant⁻¹ (41.53 %) and 1000-seed weight (18.32 %) of buckwheat over sole crop. No. spike plant⁻¹ and 1000-seed weight of buckwheat were higher in the integrated fertilizer than CF and BL. The highest No. seed spike⁻¹ of buckwheat was recorded for F:B (2:1), also in this treatment the lowest No. seed spike⁻¹ of 6.09 and the highest of 8.69 were achieved for CF and BL, respectively, but there was no significant difference between CF and IF.

In sole buckwheat, the lowest seed yield, biological yield and harvest index of 3125, 7764 kg ha⁻¹ and 40.39 % were recorded for the chemical fertilizer, respectively. Also the highest seed yield, biological yield, harvest index of 4758, 10455 kg ha⁻¹ and 49.1 % for buckwheat were observed for integrated fertilizer treatment, respectively. Buckwheat yield (3050 kg ha⁻¹) and biological yield (7535 kg ha⁻¹) was highest in F:B (2:1), but harvest index of 44.28 % was highest in the F:B (1:2) treatments. The highest and the lowest buckwheat yield were observed for IF and CF in the F:B (2:1) intercropped.

The results showed seed yield (2329 kg ha⁻¹) and biological yield (7234 kg ha⁻¹) of fenugreek were recorded for IF in the F:B (2:1) and harvest index of 32.49 % was highest for BL in the F:B (1:2). The application integrated fertilizer and broiler litter has been shown to influence nutrient cycling [3] and increasing yield of intercropping [4]. Similar results in other studies were found for higher yield in intercropping than sole crop [5,6]). In general it can be concluded that use of intercropping under integrated fertilizer conditions by the potential availability of nutrients in the soil cause to increase the yield of buckwheat.

**Conclusions**

In overall, the most of studied characters were higher in intercropping and organic manure compared with sole crop and inorganic manure respectively. So that this increasing was higher in intercropping (specially
F:B (2;1)) than sole crop and organic manure (specially, integrated fertilizer) than inorganic manure. So, seed yield and other characters studied of both plant was increased in the F:B (2:1) under fertilization (IF and BL) and this system can be efficient for manufactures of medicinal plants.

## Acknowledgements

We are so grateful to Shahrekord University for financial support.

## References

[1] Gomiero, T., Pimentel, D., Paoletti, M.G. 2011. Is there a need for a more sustainable agriculture? Crit. Rev. Plant. Sci. 30, 6-23.

[2] Branca, G., Lipper, L., McCarthy, N., Jolejole, M.C. 2013. Food security, climate change, and sustainable land management. A review. Agron. Sustain. Dev. 27, 1-16.

[3] Bastida, F., Moreno, J.L., Hernandez, T., Garcia, C. 2006. Microbiological degradation index of soils in a semiarid climate. Soil Biol. Biochem. 38, 3463-3473.

[4] Rostaei, M., Fallah, S., Abbasi Sorki, A. 2014. Effect of fertilizer sources on growth, yield and yield components of fenugreek intercropped with black cumin. Crop production. 7 (4): 197-222

[5] Saban, Y., Mehmt, A., Mustafa, E. 2007. Identification of advantage of maize-legume intercropping over solitary cropping through competition indices in the East Mediterean region. Turk J. Agric., 32: 111-119

[6] Sheri, M., Strydhorst, J., King, R., Lopetinsky, K.J., Neil Harker, K. 2008. Froge potential of intercoping barly with faba bean, lupin, or field pea. Agron. J., 100: 182-190.
# CONSIDERING THE FINE SCALE OF VARIATION FOR NITROGEN MANAGEMENT

Carolin Córdova

Universidad de Concepcion, Chillan, Chile

## Objectives

The world population diet relies largely on the cereal crop production, which in turn demands significant quantities of N (nitrogen) to grow, particularly under the current climatic change scenario and the improved new plant varieties. However, the N supply through the mineralization process seems to be a site-specific soil property, as it has been shown to be spatially variable and scale dependent, limiting the precision of the N application to match the crop demand at all scales, and raising environmental uncertainties. Geostatistics resolves the analysis of the soil spatial variability, but an a-priori figure of the spatial dependence of a soil property is recommended to make the analysis straightforward. Therefore, the focus of this research is to assess the spatial dependence of the N supply in a volcanic soil under cereal crop production in order to better understand and further model the spatial N application, using an appropriated sampling scheme.

## Method

The study was carried out over a 6-ha field of an Andisol under wheat crop, at the beginning of the Autumn season. The site is located in the Andes pre-mountains in the South of Chile (36° 59' S, 71° 55' W, 937 m.a.s.l.) and the crop rotation is based on oat-wheat.

The spatial dependence of N supply was assessed by applying an optimized hierarchical nested design [1, 2], where main stations (n=6) were separated 121.5m away forming an equilateral triangle from where groups of interval distances of 40.5m, 13.5m, 4.5m, and 1.5m, were randomly allocated, respectively. Thus, 96 soil samples were obtained at 23 cm depth, air dried for 48 hours and sieved at 2mm to measure an index of N supply.

The potentially available N represents the amount of N mineralized during a crop season, and it is measured as the ammonium content released after 7 days of anaerobic soil incubation at 40°C. The ammonium concentration was measured at the beginning and at the end of the incubation on soil extracts of 2M KCl (ratio 1:5) shaked for 60 min, settle for 30 min, then centrifuged for 8 min at 6000 rpm and filtered. Nessler and NaOH (3M) solutions were added to 2 mL of the extracts from the soil samples as well as to 2mL of the standard ammonium concentration solutions. Samples were left to stand for 20 min for colour development and the absorption (490 nm) of the samples was measured by molecular absorption spectroscopy. A regression model between the standard ammonium concentrations and the absorbance was used to interpolate the ammonium content in the soil extracts.

Summary statistics were computed for all data set, and components of variance were calculated by residual maximum likelihood (REML) for each stage and accumulated from the smallest spacing of 1.5m up to the largest 121.5m. The difference between the stages are equivalent to the range of distances to the semivariances of the regionalized variable theory, from where the spatial dependence of the N supply index can be estimated.

## Results

The N supply measured as the potentially N mineralized under controlled conditions was between 1.2 and 188.2 mg NH₄⁺ kg suelo⁻¹, with a mean value of 80 mg NH₄⁺ kg suelo⁻¹ (standard deviation of 47.92), which is large compared to other type of soils. A large initial ammonium content was also observed in soil samples before incubation. However, this might be explained by the large soil organic matter measured in the field (11%), and the effect of residual N application. This wide range of values shows the spatial variability of nitrogen under traditional agronomic management at the field scale.

The estimated components of variance calculated by REML were constrained to positive values, as negative components were found at the stages 40.5m and 13.5m, respectively. Negative components are associated to a repetition of the values, which might signify, for example, a repetitive pattern from the stage 13.5m, thought to represent the width of machinery used for fertilizer/pesticides applications in the field. After the
positive constraint, the main contribution to the total variance was observed from the stages 1.5m, 4.5m, and 121.5m, respectively. Nevertheless, up to 60% of the variance was found at the short interval distance of 4.5m, showing the fine spatial variation of the N. This is similar to other unpublished result in a natural forest on a volcanic soil, where 80% of the total variance of available NO₃⁻ was accounted for at 5m interval. Under the light of these results, it seems that the biological process of mineralization and/or its physico-chemical conditions might be defining the fine spatial dependence of the N supply at the field scale. Although other authors have previously discussed the influence of the scale of variation, there are not many studies reporting this information, which can lead not only to a more efficient spatial analysis concerning N management, but can also provide a guide to design the plot size under specific conditions in experimental studies of N transformation.

## Conclusions

The N supply measured as potentially available N showed to be different according the interval distance of sampling, and although this variability has been described before, it is not usually reported for cereal crops growing on volcanic soils.

Under the conditions of this study, the shortest interval distances showed to have a larger influence in the total variance than the stages 13.5m, 40.5m explored, making it relevant to consider 4.5m as an optimum sampling interval to analyze the spatial structure of N variability.

## Acknowledgements

This research was funded by Fondecyt 11130447 (Conicyt-Chile) and VRDI-Universidad de Concepcion, Chile.

## References

[1] Lark, R.M., 2011. Spatially nested sampling schemes for spatial variance components: scope for their optimization. Computers and Geosciences, 37: 1633-1641.

[2] Webster R., Lark, M., 2013. Field sampling for environmental science and management. Routledge Eds.. Milton Park, Abingdon, Oxon. United Kingdom.
# QUANTIFICATION OF LABILE NITROGEN IN SOIL UNDER DIFFERENT FERTILIZATION REGIMES

Zenon Hamkalo¹, Tymur Bedernichek², Tetyana Partyka³

¹Ivan Franko National University of Lviv, Lviv, Ukraine, ²M.M. Gryshko National Botanical Garden, Kyiv, Ukraine, ³Institute of Agriculture of Carpathian Region, Obroshyno, Lviv region, Ukraine

## Objectives

More than half a century ago Jansson [1] developed a theory of the internal cycle of nitrogen in soil and defined active and passive N phases (pools). This approach is still popular and two-pool models of soil organic matter are widely used. However, there is always one big problem - how to quantify labile soil organic matter and in particular labile N. Stevenson [2] considered it to be formed from many substances of different origin and composition, but similar biokinetic properties. Jansson [1] concluded that only 10-15 % of total nitrogen (TN) content can be defined as active or labile. Kudeyarov [3] found this pool to be much bigger - 26-65 % of TN. Commonly these values vary in wide ranges (10-70%) [4]. The purpose of our research was to "shrink" this range and to develop a new method to evaluate the content of really labile N in arable soil.

## Method

The experiments were carried out on the long-term agricultural research sites in Obroshyno (Ukraine). They were established in 1965 and then in 1975 conversed into intensively managed hayfields with 5 cuttings per vegetation period (imitation of grazing). Soils of the research sites were *Gleyic Phaeozems*. Basic soil agro-chemical properties of the topsoil (0-20 cm) were studied before conversion in 1974. TOC content was 20.7 mg g⁻¹, TN - 3.31 mg g⁻¹, available P (0.2 M HCl) - 37.2 mg kg⁻¹, labile K (1 M CH₃COONH₄) - 45.1 mg kg⁻¹, pHₖCl - 5.42, cation-exchange capacity - 35.2 cmol⁺/kg, exchangeable acidity (in CH₃COONa) - 6.7 cmol⁺/kg. Content of clay was 12.0 %, silt - 71.5 % and sand - 16.5 %.

We studied soil under four fertilization regimes (in 3 replicates): control (no fertilization); P<sub>90</sub>K<sub>120</sub>; P<sub>90</sub>K<sub>120</sub>N<sub>240</sub> (60+60+60+60) and P<sub>90</sub>K<sub>120</sub>N<sub>240</sub> (0+30+90+120). Granulated superphosphate, potash and ammonium nitrate were used in this study. Soil samples were taken from 0-20 cm depth in 3 replicates 4 times during vegetation period: 04.01, 05.13, 06.30 and 09.17.

For the evaluation of labile N pool the method of Cornfield [5] in modification of Shcherbakov and Kislykh [6] was used. We further developed this method of multistep alkali hydrolysis. After preliminary studies on the effect of different alkali concentrations (0.25 - 17 M) and exposure times (6 - 192 hours) it was found that the most informative fractions can be extracted in the range: 0.25 - 8 M NaOH and 6 - 144 hours [4]. For this purpose 11 different concentrations of NaOH (0.25, 0.5, 1.0, 1.5, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 M) and 12 different exposure times (6, 12, 18, 24, 30, 36, 42, 48, 54, 90, 120 i 144 hours) were used. This fractionating scheme provides 132 fractions of labile nitrogen. For visual interpretation of the results we used a 3D (XYZ) model (N content; alkali concentration, exposure time). Content of labile nitrogen in the obtained extracts was determined by Cornfield method [5]. Total nitrogen was determined in soil samples by Kjeldahl method.

## Results

We found that a traditional method of Cornfield [5] (1 M NaOH, 40-42 hours), which is widely used as an indicator of labile nitrogen content in soil, was not informative enough. Content of this fraction changed insignificantly during the period of vegetation and did not respond to nitrogen fertilizer application. It was found that alkali hydrolyses with 8 M NaOH during 144 hours was the most informative. Content of this fraction changed dramatically during vegetation period and was a reliable indicator of N-mineralization and N-immobilization processes in soil. In this study we define content of this fraction as hardly hydrolyzable labile nitrogen (HHLN).
**Control (no fertilization).** Long exposure time (144 hours) caused a significant increase of labile N content in comparison to traditional (42 hours) method, especially when high concentrations of NaOH (4-8 M) were used. It was found that in spring content of HHLN was 920 mg kg⁻¹ (18% of TN). During the vegetation period content of HHLN decreased and reached 402 mg kg⁻¹ (14% of TN). Multistep hydrolysis gives one more important opportunity. With this method it is possible to evaluate the homogeneity of labile N pool. In control, this pool was formed by three main fractions with ratio 230:200:490 mg kg⁻¹ in spring and 270:70:60 mg kg⁻¹ in autumn. Hence, homogeneity of labile N pool in soil increased during the vegetation process. Content of the most hardly hydrolyzable fraction was the most informative one and decreased in 8.2 times.

**P<sub>90</sub>K<sub>120</sub>**. Application of P and K fertilizers slightly changed the content of HHLN in soil. As in control, its highest content was observed in spring (04.01) - 850 mg kg⁻¹. During the vegetation period content of this fraction gradually decreased down to 440-460 mg kg⁻¹ in summer (06.30) and autumn (09.17).

**P<sub>90</sub>K<sub>120</sub>N<sub>240(60+60+60+60)</sub>**. Application of N fertilizers in spring (04.01) caused a significant accumulation of labile N in soil. 40 days after fertilization content of HHLN increased by 150 mg kg⁻¹. In summer (06.30) the lowest content of HHLN (445 mg kg⁻¹) was observed. This fact was caused by mineralization of soil organic matter and was followed by intensive nitrification and ammonification. Application of N fertilizers significantly changed lability and probably availability of nitrogen in soil during vegetation period (04.01, 05.13, 06.30 and 09.17). Percentage of HHLN (% of TN) was 18.0:19.5:15.4:14.0 in control and 17.3:22.7:14.1:29.2 when P<sub>90</sub>K<sub>120</sub>N<sub>240(60+60+60+60)</sub> applied.

**P<sub>90</sub>K<sub>120</sub>N<sub>240(0+30+90+120)</sub>**. Gradual increase of N doses during vegetation period caused a significant decrease of HHLN content in soil - at least by 50-60 mg kg⁻¹ in comparison to the previous fertilization regime. These results further support the idea of Kudeyarov [3], who assumed that application of nitrogen fertilizers may increase total but significantly decrease labile N contents.

## Conclusions

This study has shown that multistep alkali hydrolyses is a reliable and informative method for SOM evaluation and quantification of labile nitrogen in soil. In our 4-year field experiments we found that content of hardly hydrolyzable labile nitrogen (HHLN) was between 18 and 32 % of total nitrogen.

This method is suitable not only for quantification of different N fractions in soil, but also shows the heterogeneity of labile N pool. Such approach is suitable for the differential evaluation of mineralization and immobilization processes in soil, especially when N fertilizers applied.

It was found that alkali hydrolyses with 8 M NaOH during 144 hours was the most sensitive in comparison to other concentrations and exposure times. The described method is an informative and cheap alternative to expensive stable isotope techniques in quantifying labile nitrogen in soil and priming effect evaluation.

## References

[1] Jansson, S.L. 1958. Tracer studies on nitrogen transformations in soil with special attention to mineralization-immobilization relationships. Lantbrukhogsk. Ann. 24, 101-361.

[2] Stevenson, F. J., Cole M. A. Cycles of Soils: Carbon, Nitrogen, Phosphorus, Sulfur, Micronutrients, 2nd ed. 448 p.

[3] Kudeyarov, V.N. 1989. Nitrogen cycle in soil and effectiveness of fertilizers. Moscow. 216 p.

[4] Hamkalo Z. 2009. Soil ecological quality, Lviv, 412 p.

[5] Cornfield, A.H. 1960. Ammonia released on treating soils with N sodium hydroxide as a possible means of predicting the nitrogen-supplying power of soils. Nature 187, 260-261.

[6] Shcherbakov, A.P., Kislykh Y.Y. 1990. Effective Soil Fertility: Methodological Aspects, Moscow, 70 p.
# NITROGEN FERTILIZATION REDUCTION OF CORN IN A NITRATE VULNERABLE ZONE

Jose Soler-Rovira, Ruben Flores-Manso, Juan Manuel Arroyo-Sanz

Technical University of Madrid, Madrid, Spain

## Objectives

The aim of this work is to study the response of different corn hybrids to nitrogen fertilization reduction in a nitrate vulnerable zone in central Spain. Yield, yield components and radiation use efficiency were analyzed and crop gross margin was evaluated.

## Method

In 2013, a trial was carried out in Jadraque that is included in the "Alcarria-Guadalajara" Nitrate Vulnerable zone in Castilla-La Mancha region in Spain. This is a semiarid zone, where maize is commonly cultivated with irrigation during summer months. Two nitrogen fertilization rates were studied: farmers rate (FR: 372 kg N/ha) and the maximum rate established in the Action Programme of that Vulnerable zone (APMR: 211 kg N/ha). Three corn hybrids (one FAO 500 cycle and two FAO 600 cycle) were sown in each N level on 5th of May, with a final plant density of 96,000 plants/ha. Four replications were done, so 24 elemental plots were defined of 162 m² per plot (12 rows x 18 m). The experimental area was surrounded by a commercial corn crop, so border effects were avoided. 165 kg N/ha were applied before sowing in all the plots and other 207 kg N/ha were applied on 15th June in top dressing FR fertilization, but only 46 kg N/ha in APMR level. Crop was irrigated from June to September with 570 mm of water. The other crop practices were the usual done in that farming area. Harvest was done on 5th December with a commercial harvester. Grain of each elemental plot was weighted in a portable bascule and grain moisture content was measured with an automatic device. Prior to harvest, the number of plants and number of cobs were measured in two crop rows of each plot. Later, the number of rows per cob and number of grains per row were counted in six cobs of each plot at the laboratory. The weight of 100 grains was also measured. So, crop yield and yield components were estimated. During crop growth cycle, leaf chlorophyll content was measured with an SPAD device and Photosynthetically Active Radiation (PAR) was measured with a quantum sensor. Intercepted PAR was assessed as incident solar PAR in the top of the crop canopy minus incident PAR at the ground level below crop canopy. Crop economic gross margin was calculated with crop yield and corn price and nitrogen and seed prices and rates.

## Results

Leaf chlorophyll content was affected by N fertilization, but this effect was strongest in one hybrid, where decline in SPAD values began in July. These SPAD values were correlated with final corn yield, but the parabolic relationship between those variables indicates that there is a threshold level of chlorophyll (42-43 SPAD values in mid-June and 49-53 in mid-July) beyond that yield does not increase. Nitrogen fertilization reduction did not affect PAR radiation interception except in one hybrid, but it had a clear effect on radiation use efficiency (mass of grain per MJ of intercepted PAR) in the three hybrids, and this variable was highly correlated with corn yield. So, nitrogen reduction in this trial should affect some physiological plant processes other than leaf growth and radiation interception.

Nitrogen reduction also affected the weight of grain per cob, which was the component that showed the best correlation with final corn yield. The second component was the number of cobs per ha.

Nitrogen fertilization reduction significantly decreased corn yield in two hybrids but not in the third, so interaction arose between the two studied factors (N rate and corn hybrid). Choosing the latter hybrid in the Vulnerable zone may thus prevent yield reductions due to reduced N fertilizer application. With this hybrid the maximum economic gross margin was also achieved.
Conclusions

Nitrogen fertilization reduction in corn cultivated in a Nitrate Vulnerable zone reduced leaf chlorophyll content and radiation use efficiency of the crop. The effect of N rate on yield depended on the sown hybrid, so, choosing the adequate one, yield should not be reduced using less N fertilizer; neither gross economic margin should be reduced, compared with other highly fertilized hybrids commonly sown in that zone. However, the high yielding hybrid showed the highest yield and profit using an N rate higher than the maximum rate established in the Action Programme of the Nitrate Vulnerable zone.
# OPTIMIZATION TESTING AND SPLITTING OF THE CONTRIBUTION PERIOD OF NITROGEN FOR GROWING DURUM WHEAT IN IRRIGATED SEMI-ARID ZONE

Anouar Benamar SEBAIBI

Ph.D. Student, Department of Agronomy, Faculty of Natural Sciences and Life, Abdelhamid Ibn Badis University, Mostaganem, 27000, Algeria

## Objectives

When one is interested in growing techniques, we should mention the key element for developing wheat yields, such as nitrogen fertilization who requires strict management, based on the strategy to adapt the inputs crop requirements during its various stages of development (Fair, 1993).

In this context, we seek to compare several nitrogen fractionation procedures. The Selected fertilization methods allow to know the response of a variety of durum wheat (Chen's), widespread in our region (Ain Temouchent, Northwest Algeria) to the action of unfractionated nitrogen fertilization, on one hand, and the effect of requirements divided into two and three equal or unequal fractions, other hand. The effectiveness of different modalities is aprecied at the level of yields support, that is the biomass and yield components, without neglecting a very important element that is the nitrogen content of the biomass formed, and therefore the protein content of the grain produced.

## Method

The parameters measured during this study are :

1/ Air dry biomass : The production of dry matter produced by a plot of 0.6 m² at heading stage is evaluated after passage of the sample in an oven set at 80 °C for 48 hours (ICARDA 1996).

2/ The nitrogen content : the Nitrogen levels in aboveground biomass and grain are measured by the Kjeldahl method.

3/ The grain protein content : The protein content of the harvested grain is calculated by the formula: Protein (%) = N content of grain x5,7 (JEUFFROY 2001).

4/ Other parameters are taken into account in particular :

- Number of ears / m² per plant;

- Number of grains / m² per spike;

- 1000 kernel weight;

- Grain yield and straw / m².

## Results

The study broadly confirms the equivalent nitrogen needs of the crop improves grain yield components, including the ear fertility. To be most effective, nitrogen fertilization should be divided into several fractions. Moreover, a good combination between fractions and fertilizer contributed stages adds value more nitrogen fertilizer.

Under our experimental conditions, the best results were obtained with the modality in 3 fractions in general and its G2 and G3 variants in particular. The advantage of this method lies in the fact that its application covers 3 vegetative stages criticism of wheat with a view to the nitrogen.

The number of grains is the second component that reflects the nitrogen nutrition (Jeuffroy and Bouchard, 1999). In this study, this component responds positively to nitrogen fertilization. The plot driving with a nitrogen supply produces a grain significantly heavier. By cons, splitting fertilization overall still no significant
effect on this component.

Moreover, as for the production parameters, the grain protein content and nitrogen content of its support heavily dependent on user input of nitrogen fertilizer needs. It improves if more nitrogen fertilizer is distributed between the different stages. The fractionation related increase is on average 55.75% for the nitrogen content of the biomass heading and 13.68% for the rate of grain protein.

Better yet, the division in 3 contributions from all variants is more rewarding than 2 fractions. Its grain and its biomass heading contain respectively 40.30 and 86.14 % more than the control, and 47.65% against 6.31 for option 2 contributions; In other words, the effectiveness of the fumure fractions is 6.4 to 3 times that of the mode 2 inputs to the grain protein, and 1.8 times for the nitrogen content of the heading biomass.

## Conclusions

The study focuses on the optimization of the fractionation and the contribution period of the nitrogen requirements of the winter cereals. The test was conducted on a local variety (Chen's) driving in the field of semi-arid zone. A total of 22 combinations of intake of 115 units of ammonium nitrate 33.5% / ha was tested. The airline biomass, straw, grain yield and its components, as well as the nitrogen content in certain organs proteins were determined.

The results obtained showed that the nitrogen fertilization encourages all the parameters considered, but its effectiveness varies greatly with the input modality. The number of fractions, the proportion of the contributions and the stage of fertilized culture are very influential.

The results confirm that nitrogen fertilizer applied in a single intake is less efficient than fractionated. The Splitting improves straw yield of 20.6%, 24% in grain and grain protein content of 11%.

The most effective of the 19 fractionated modalities studied is that fractioned in 3 inputs, divided between early tillering, ear in 1cm 2 knots. The best results were obtained with the contributions of 25% of needs in early tillering, 50% to the ear 1cm and 25% in stage 2 knots. This allocation improves the yield of 86.7% of grains by 112.1% straw and rich in grain protein by 59% (+ 6%).
# NITROGEN BALANCES AND FLOWS IN CENTRAL SPAIN DAIRY FARMS

Jose Soler-Rovira, Diego Jimenez-Jimenez, Francisco Alonso-Peralta, Juan Manuel Arroyo-Sanz

Technical University of Madrid, Madrid, Spain

## Objectives

The aim of this work is to study the nitrogen use efficiency and eco-efficiency in dairy farms of Castilla y Leon region in Spain, considering different farm size, livestock density, milk production, feeding type, agricultural land and fodder production. This region has important differences with typical dairy zones in the North and the Northwest of Spain, because farms in Castilla have more agricultural land for cultivating fodder (silage of rye or corn; hay of wheat or vetch with oats) and feeding crops (barley and wheat). Nitrogen flows and balances were estimated at different levels: cow, dairy and farm.

## Method

Six dairy farms from Ambles Valley (Avila, Spain) were studied. In 2013, data about livestock (milking cows, dry cows and calves), feeding, milk production (quantity and composition) and agricultural land (fodder, cereal, pastures, etc.) were recorded in each farm.

The amount and types of feeds and fodders used in livestock feeding were also consigned and a sample of each raw material was taken. Oven dry matter and nitrogen (Kjeldahl method) content of each feeding product were analyzed in the laboratory. Milk production and protein content were also consigned. N excreted by each animal was estimated as the difference between N intake and N in milk (only in milking cows) minus N retention in body mass. N dietary intake was estimated for each group of animals with the data of feeding intake, dry matter content and protein content. N in milk was estimated with the data of milk production and protein content of the milk. N retention in body mass was taken from literature: 15% of N intake in cows and 11% in calves. Nitrogen use efficiency of milking cows was calculated as the ratio of N in milk and N intake. Nitrogen use efficiency of dairies was calculated as the ratio of N in milk and N intake of all types of animals.

A nitrogen balance was carried out at farm scale considering farm gate inputs and outputs. N inputs were: fertilizers (quantity and N content were consigned), fodder and feeds (quantity and N content were consigned). N outputs were: milk (quantity and N content were consigned), cereals not used in the farm (quantity sold and N content were consigned) and live animals (old cows, male calves and part of female calves: number and average weight of animals were consigned and 2.2% N was considered from literature).

Some indicators were computed as follows: Nitrogen surplus as the difference of N inputs and outputs, N efficiency as the ratio of N outputs and inputs; eco-efficiency as the ratio of N surplus and N outputs.

## Results

Studied farms had between 20 and 100 milking cows, with a milk quota of 150-1,200 L, 20-34 kg FCM per cow and day (fat corrected milk) and 40-200 ha of agricultural land. The livestock density was between 0.3 and 1.6 LU/ha, less than the maximum required of 2.5 LU/ha.

N excretion of milking cows was between 90 and 143 kg N/cow year, according to literature values. Thus, animals excreted between 48-65% of N dietary intake, so nitrogen use efficiency was between 20-37%. Four farms showed an average N efficiency of milking cows (25-30%), one showed an excellent one (37%) and the last should improved its efficiency (20%). The N efficiency of the dairy (considering all N intakes of all types of cows) decreased to 20-25%, although in the worst farm this value was only 17%, but the best recovered 31% of N intake in the milk. In this farm, 16 kg N were used to produce 1 ton of FCM, but more than 20 kg N were needed in the other less efficient farms. Dairy cows accounted for 86% of N dietary intake in the farm, but only for 80% of N excretion.
N excretion per ha in all studied farms was lower than 170 kg N/ha, the limit of Nitrates Directive, because none of them had a high livestock density and the amount of agricultural land was appreciable.

The most important nitrogen flows in the farms were those related to feeding and excretion. In four farms all N flows were lower than 100 kg N/ha, but in the two other there were nitrogen flows higher than 100 kg N/ha.

Nitrogen inputs in the farms depended on N in purchased concentrates, but total N inputs per ha were lower in this zone than in farms from the North of Spain. The proportion of purchased N to total N in feeds increased with livestock density in the studied farms. N in milk was the main nitrogen output. Farm N surplus varied between 42 and 187 kg N/ha, and it was lower than data showed in the literature about farms in the North of Spain. This farm surplus was correlated with N excretion per ha, so when livestock density increased, the nitrogen surplus to the environment was higher.

N use efficiency in dairy farms varied between 22 and 36%, and the most efficient ones were also the most eco-efficient, because they lost less nitrogen to the environment. Thus, the two most efficient farms lost less than 2 kg N per kg N that went out the farm gate in form of milk, crop products or animals, but the less efficient farms lost more than 3 kg N to the environment.

## Conclusions

The purchased N in concentrates was higher in farms with more livestock density, and internal production of fodders and cereals was lower. Nitrogen excretion and surplus to the environment were also higher in farms with more animals per ha, so they were less efficient and eco-efficient. Thus, more N was lost to the environment per unit of N produced in the farm. However, the studied farms showed lower N surplus and better environmental performance than other located in the North and Northwest of Spain, because they had more surface of agricultural land.
# NITROUS OXIDE EMISSIONS FROM A SUGARCANE CROP UNDER DIFFERENT NITROGEN FERTILIZER RATES

Raquel Schmatz¹, Vagner João Moro¹, Majid Mahmood Tahir², Sylvie Recous³, Carolina Schultz Pollet¹,
Bruno Chaves¹, Celso Aita¹, Sandro José Giacomini¹

¹¹Department of Soil Science, Federal University of Santa Maria 97105-900, Santa Maria -RS, Brazil, ²Department of Soil and Environmental Sciences, Faculty of Agriculture, The University of Poonch, Rawalakot, 12350, Azad Jammu and Kashmir, Pakistan, ³³INRA, UMR614 Fractionnement des Agroressources et Environnement F-51000, Reims, France

## Objectives

Nitrogen (N) fertilization generally increases nitrous oxide (N₂O) emissions in soil [1]. The application of N fertilizer greater than the demand of the plants has shown greater proportion of N₂O emissions per unit of fertilizer applied [1]. Therefore, the knowledge of N₂O emissions on a local level is necessary to identify N rates and management practices that reduces N₂O emissions. In this perspective, our objective was to estimate N₂O emissions, under different N rates applied to the sugarcane crop in southern Brazil.

## Method

The experiment was conducted from September 2010 to July 2012 on a Typic Haplustalf (60% sand, 30% silt, 10% clay, total C 7.5 g kg⁻¹) at the Department of Soils, Federal University of Santa Maria (29°41′S, 53°48′W), Brazil.

The planting of sugarcane (RB956911 genotype) was done on 20 September 2010 in furrows, approximately 0.3 m deep, 1.4 m row spacing with a plant density of 18 gems per meter. The treatments were four rates of urea-N: 0 (N0), 40 (N40), 80 (N80) and 120 kg N ha⁻¹ (N120). The experiment was organized in randomized complete block design (RCBD) with four replications. The treatments were evaluated in plant cane (2010/11) and first-ratoon cane (2011/12) cycles. In the plant cane cycle, N rates were splitted in three doses, i.e, 20 kg N ha⁻¹ at planting, and sidedressing at 65 and 92 days after planting (50% of the remaining N at each time). In the first-ratoon cane cycle, N rates were splitted into two equal doses, sidedressing at 34 and 99 days after cane plant harvest. In sidedressing, N was applied on the soil surface near the planting row. Sugarcane was harvested without fire in July 2011 and June 2012 in plant cane and first-ratoon cane cycles, respectively. The average amount of straw on soil surface after plant cane harvesting in all treatments (N0, N40, N80 and N120) was 15.8 Mg ha⁻¹.

Soil N₂O fluxes were measured periodically by the closed static chamber technique. The N₂O concentrations in the samples were analyzed by gas chromatography (Shimadzu GC-2014 Greenhouse). Daily N₂O fluxes (µg N m⁻² h⁻¹) were calculated by linear interpolation and the cumulative fluxes (g N ha⁻¹) were calculated by the integration of the daily N₂O emissions. Gravimetric soil moisture (105°C for 24 h), soil inorganic N (NH₄and NO₃) and water-filled pore space (WFPS) were determined in the 0-10 cm soil layer at each sampling date.

## Results

The mean flux of N₂O in N0 treatment was 17.8 µg m⁻² h⁻¹ in the plant cane and 13.2 µg m⁻² h⁻¹ in first-ratoon cane. The N₂O flux increased after N application and in both crop cycles the effect of first N application on N₂O emission was greater than second application. In the plant cane cycle during first 30 days after N application, the observed average N₂O fluxes in N80 and N120 treatments were 80 and 116 µg of N₂O-N m⁻² h⁻¹, respectively. After second N application, the values were low and reduced to 36 and 52 µg of N₂O-N m⁻² h⁻¹. A similar trend was observed in first-ratoon cane cycle. During these periods, highest N₂O fluxes were related to the occurrence of rainfall that raised WFPS in soil. After 30 days of N application, the N₂O fluxes reduced in all treatments, without any emission peaks even after rainfall events. This was possibly due to the reduced mineral N availability in the soil during this period.

N application in both sugarcane crop cycles increased the amount of N₂O emission until the crop harvest. In the plant cane cycle, only N80 and N120 treatments emitted more N₂O than N0 treatment while in first-ra-
toon cane, all the three treatments emitted more N₂O compared to the control treatment (N0). The amount of N emitted as N₂O in the first cycle ranged from 0.67 kg ha⁻¹ in N0 to 1.78 kg ha⁻¹ in the N120 whereas in the second cycle it ranged from 1.09 kg ha⁻¹ in N0 to 2.67 kg ha⁻¹ in N120. During the two years of sugarcane crop, the N₂O emission factor (proportion of N applied at each dose lost as N₂O) was significantly lower in the N40 treatment (mean 0.71% N applied) and did not differ between N80 (mean 1.21%) and N120 (mean 1.22%) treatments. The productivity of stalks in cane plant and first-ratoon cane also increased with increasing N rates. Nevertheless, on an average of the two cycles, the increase in sugarcane yield decreased with increasing N application above 40 kg N ha⁻¹ (22.0, 9.0 and 2.6 Mg ha⁻¹, respectively, to N40, N80 and N120). When considering the ratio of N₂O-N per unit stalk produced (yield-scaled emissions), the observed values were close to this relationship between the N0 and N40 (9.0 e 9.2 g Mg⁻¹, respectively). However in N80 (13.5 g Mg⁻¹) and N120 (17.0 g Mg⁻¹) treatments N₂O emissions per unit stalk produced increased significantly (nonlinear response).

## Conclusions

N₂O emissions increased linearly with applied N rates in sugarcane crop. On an average of plant cane and first-ratoon cane cycles, 0.56 kg N₂O-N ha⁻¹ was emitted per 40 kg N ha⁻¹ applied. The N₂O emission factor (calculated by using IPCC methodology for the conditions of this study) was below the standard value of 1% for N rates lower than 40 kg N ha⁻¹. Emissions factors based on the relationship between N₂O emission and sugarcane yield indicated that increased stalk yields obtained with rate up to 40 kg N ha⁻¹ resulted in higher amount of N₂O-N emitted per Mg of stalk/sugarcane produced.

## Acknowledgments

This work was supported by the Brazilian government through the Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) and Fundação de Amparo à Pesquisa do Estado do Rio Grande do Sul (FAPERGS).

## References

[1] McSwiney, C.P., Robertson, G.P. 2005. Global Change Biology 11, 1712-1719.

[2] Zebarth, B. J., Rochette, P., Burton, D. L. 2008. Can. J. Soil Sci. 88, 197-205.
## APPARENT LONG-TERM FERTILIZER REPLACEMENT VALUE OF ORGANIC AMENDMENTS DEPENDS ON MINERAL FERTILIZER N RANGE ITSELF

Hein ten Berge¹, Renske Hijbeek², Martin van Ittersum², Gerrit Gort³, Andy Whitmore⁴

¹Wageningen UR - PSG, Wageningen, The Netherlands, ²Wageningen UR - PPS, Wageningen, The Netherlands, ³Wageningen UR - Biometris, Wageningen, The Netherlands, ⁴Rothamsted Research - SSGS, Harpenden, UK

### Objectives

Efficient use of nitrogen (N) requires careful matching of N supply to crop demand. Where mineral fertilizers are combined with organic amendments - such as farmyard manure (FYM), slurries, and crop residues - the N supplied by organic amendments must be estimated to assess the remaining mineral N fertilizer requirement. For this purpose, organic amendments are characterized by their 'apparent N fertilizer replacement value' (NFRV), which can be based on either equal yield or equal N uptake [1]. We used NFRV at equal yield, thus following the original definition by Herron and Erhart [2]. Factors known to affect NFRV (at given dose of the amendment) include the content and form of N in the amendment, and the method and time of application which may govern losses. Here we inspect the effect on NFRV of an additional factor: the N fertilizer rate itself at which NFRV is evaluated.

### Method

We screened two databases on long term experiments (LTEs): EuroSOMNET (www.ufz.de/somnet/) and CATCH-C (www catches-c.eu), and collected data from trials where crop yield response to mineral N fertilizer rates (F) was determined both in absence (Y⁰) and in presence (Yª) of annual organic amendments A of constant dose across all F levels. This allows for comparison between two response curves Y⁰(F) and Yª(F) that constitute a pair. Data per trial included at least four rates F each with and without amendment, and covered at least five years of yield data. Phosphorus and potassium were applied in all treatments. Where possible, yield data from the last 10 years of each crop per experiment were averaged. Alternatively, average yields over the last five years were used. Data from 20 LTEs resulted in 78 pairs of curves (one LTE often providing data on several crops or amendments). The LTEs were situated in Austria, Czech Republic, Germany, Estonia, Italy, Poland, Romania, Serbia, and Spain. To the yield data Y⁰(F) and Yª(F) we fitted response curves of the form

$$Y = a + b*0.99^{F} + c*F \quad (1)$$

where Y is crop yield (t/ha), F is the mineral N fertilizer rate (kg N/ha) [3]. NFRV at low mineral N fertilizer rate (NFRVLo) was defined as the amount of mineral N fertilizer (F) needed in absence of amendment A to match the yield obtained with amendment A but without mineral fertilizer (F₀):

$$Y^{0}(F) = Y^{A}(F_{0}) \quad (2)$$

$$NFRV^{Lo} = F \quad (3)$$

NFRV at high mineral N fertilizer rate (NFRVHi) was defined as the amount of mineral N fertilizer that can be saved in the presence of amendment A, while still matching the maximum yield found with mineral fertilizer alone:

$$Y^{A}(F) = Y^{0}(F_{max}) = \quad (4)$$

$$NFRV^{Hi} = F_{max} - F \quad (5)$$

where Fmax is the mineral N fertilizer rate where the smoothed Y⁰(F) curve reaches its highest value Y⁰(Fmax) within the range of rates F applied. (We used this definition rather than the economic optimum to avoid the
use of price ratios which vary across years and countries.)

## Results

The 78 suitable data sets (curve pairs, see above) found refer to wheat (n=24), barley (18), rye (2), sugar beet (13), maize (13), potatoes (8). The organic amendment varied between trials, and included FYM (n=37), slurry (7), straw (18), and straw mixed with other N sources (green manures, beet leaves, slurry; n=16).
Based on the full data set, $NFRV^{Hi}$ (mean 43.3 kg N/ha) was significantly higher than $NFRV^{Lo}$ (30.4 kg N/ha) (p=0.035 based on paired test), the two differing by a factor 1.43. The full set included 33 curve pairs where the maximum yield with organic amendment was lower than that without ($Y^0(F_{max})$). Excluding these, we repeated the analysis for the remaining 'narrow set' (n=45) and found a stronger contrast between the two $NFRV$ values. Again, $NFRV^{Hi}$ and $NFRV^{Lo}$ differed significantly (p<0.001), now with means of 86.3 kg N/ha and 44.4 kg N/ha, respectively, differing by a factor 1.94. At the level of individual crops, using the full data set, the difference was significant only in potatoes (p=0.003) and almost in maize (p=0.081), with $NFRV^{Hi}$ larger by a factor of 2.29 and 1.55, respectively, than $NFRV^{Lo}$. For the individual amendments (using all data), the difference was significant only for FYM (with n=37 the dominant amendment in the set; p=0.025), where the ratio between $NFRV^{Hi}$ and $NFRV^{Lo}$ was 1.61. Based on the 'narrow set', $NFRV^{Hi}$ was significantly higher than $NFRV^{Lo}$ (p<0.002) in all crops with n>1, their ratio ranging from 1.77 (maize, n=11) to 2.24 (sugar beet, n=7). Similarly, all amendments with n>1 showed significantly larger $NFRV^{Hi}$ than $NFRV^{Lo}$ (p<0.04) in the 'narrow set', with ratios of 1.98 (FYM, n=23), 1.73 (slurry, n=6) and 2.24 (straw, n=6).

We did not investigate causes of the above differences in *NFRV*. For a start, two types of impact by an organic amendment on a reference response curve (to mineral N fertilizer) could be distinguished. The first (a) is an upward shift of the entire curve (same yield increment over the entire N range; no change of curve shape). Alternatively (b) the curve is shifted 'laterally' without changing shape, such that the same yield is achieved at lower *F*. In case (a), the typical shape of response curves (levelling off with increasing *F*) dictates that *NFRV*<sup>Hi</sup> is larger than *NFRV*<sup>Lo</sup>. In case (b), *NFRV* is by definition independent of the N range, for any curve shape. Our findings suggest that most of our data resemble more case (a) than (b), implying that the amendment brings some other benefit than just N. This may relate to other nutrients, soil quality properties, or patterns of N release. Our *NFRV* must therefore be referred to as an 'apparent' replacement value.

## Conclusions

This meta-analysis over 20 LTEs on different crops and organic amendments showed that the apparent N fertilizer replacement value (*NFRV*) of organic amendments was roughly up to two times larger at high than at low rate of mineral N fertilizer. While *NFRV* is commonly assessed using data at the 'lower end' of the N response curve (to reduce random error impact), farmers normally operate at high N availability and using *NFRV*<sup>Lo</sup> here may introduce systematic error. If our findings can be further generalized, the observed contrast between *NFRV* in the respective N ranges may have practical implications that extend to fertilizer recommendations, and possibly to fertilizer equivalency coefficients used by some EU member states in their Action Programmes under the Nitrates Directive (e.g., Denmark, The Netherlands) to regulate the use of manures.

## Acknowledgements

This publication received funding under the CATCH-C project (Grant Agreement N° 289782) within the 7th Framework Programme for Research, Technological Development and Demonstration. Its content does not represent the official position of the European Commission and is entirely under the responsibility of the authors.

## References

[1] Schröder, J.J. 2005. Manure as a suitable component of precise nitrogen nutrition. Proceedings 574, 32
pp. International Fertiliser Society, Colchester, UK.

[2] Herron, G.M., Erhart, A.B. 1965. Value of manure on an irrigated calcareous soil1. Soil Science Society of America Journal, 29: 278-281.

[3] George, B.J. 1984. Design and interpretation of nitrogen response experiments. In: *The nitrogen requirement of cereals*, MAFF Reference Book 385, pp. 133-150.
# ESTIMATION OF THE QUANTITY OF N2 FIXED BY CLOVER GROWN IN THE MIXTURE WITH GRASS IN LONG TERM FIELD EXPERIMENT

Dorota Pikula, Agnieszka Rutkowska

Institute of Soil Science and Plant Cultivation-State Research Institute, Puławy, Poland

## Objectives

In sustainable agriculture, one of the most important characteristics of legumes is their symbiosis with Rhizobium to fix nitrogen for growth. For proper management and a full realization of the benefits of legumes, it is necessary to estimate the quantity of nitrogen fixed under different field conditions. A suitable method for accurately measuring the amount of N crops derived from the atmosphere is therefore, an actual and important requirement. The most appropriate and widely accepted method is so called 15N isotope dilution, but it is usually limited to pot experiments. In the paper, the quantity of nitrogen fixed by clover in long-term field experiment was calculated. The amount of N2 reduced was calculated as the difference between tested (clover grown in the mixture with grass) and reference crops (maize), grown under the same field and weather conditions and disposed to a parallel pool of nitrogen from manure applied for forecrop.

## Method

The long-term field experiment was carried on in 1979 at Experimental Station Grabów of the Institute of Soil Science and Plant Cultivation in Puławy, in the split-block layout, in two crop rotations - including legume and non-legume crop (first factor), and in four replications. After clover-grass mixture (rotation 1) and maize (rotation 2), the following crops were grown in succeeding years: potato, winter wheat and spring barley. In the both crop rotation, five rates of manure (M) were applied under potato (second factor), which corresponds to: M0, M1-188, M2-376, M3-564 and M4-752 kg N/ha. Each crop was supplied with four rates of mineral fertilizers (third factor). The following rates of ammonium nitrate (N): N0, N1-45, N2-90, N3-135 kg N/ha were applied under clover with grass, and N0, N1-40, N2-80, N3-120 kg N/ha under maize.

The amount of nitrogen fixed by clover was calculated as the difference between total N uptake by clover-grass and the reference crop - maize. The paper presents the results of five rotations: III (years 1988-1991), IV (years 1992-1995), V (years 1996-1999), VI (2000-2003) and VII (2004-2007). Statistical processing of the results was performed using the Statgraphic 5 Plus package (Statgraphics Plus, Rockville, USA). The Tukey's test has been applied to evaluate the significance of differences between the treatments.

The expression levels nitrogenase (*nifH*), ammonia monooxygenase (*amoA*), nitrite reductase (*nirK* and *nirS*), and nitrous oxide reductase (*nosZ*) were determined by real-time quantitative PCR, using specific primers and microbial reporter genes (from *Nitrosomonas europaea*, *Azospirillum irakense*, *Azospirillum brasiliense*, *Pseudomonas stutzeri* and *Pseudomonas fluorescens*). Total soil RNA extraction was carried out by RNA PowerSoilTM Total RNA Isolation Kit Sample (Mobio) followed by a DNase treatment. Retrotranscripts were purified by using the Wizard SV Gel and PCR Clean-Up System (Promega).
## Results

On the basis of the assumption that the both - fixing and non - fixing crops take up N from soil in the same ratio, the difference corresponds to the quantity of nitrogen biologically fixed by clover. The total N uptake of maize increased with manure rates, and N uptake by clover did not respond to organic fertilization. The effect of mineral fertilization on total N uptake by the both crops was proven. In the treatment M0, maize took up from 80 to 147 kg N/ha, in M1 - from 93 to 171 kg N/ha, in M2 - from 101-158 kg N/ha, in M3 - from 101 to 157 kg N/ha, and in M4 - from 114 to 169 kg N/ha. Total N uptake by clover with grass was as follows: M0 234-292, M1 245-320, M2 238-328, M3 238-327, and M4 234-321 kg N/ha.

The average nitrogen uptake by the crops calculated for the total rate of N applied in form of manure and mineral fertilizers reached 131 kg N/ha for maize and 275 kg N/ha for clover. The difference in the uptake corresponds to the quantity of nitrogen fixed by clover. Thus, the contribution of di-nitrogen in the total quantity of N accumulated by green biomass of clover-grass mixture varies between 49% and 59% depending on N supply. The quantity differed statistically between the fifth rotations of the experiment. There was not found the effect of manure application, and mineral fertilization on N biologically fixed by clover. In the treatment without organic fertilization (M0), the estimated amount of N-fixed was as follows: at the rate N0 - 158 kg, at N1 - 148 kg, at N2 - 127, and at N3 - 144 kg per hectare. To compare, at the highest manure rate (M5) the quantities was: at N0 - 124 kg N/ha, N1 - 127, N2 - 143, N4 - 152 respectively. In the experiment, the mean value of the quantity of N fixed by clover accounted for 144 kg N per hectare, on the average. It is in accordance with results obtained by other authors on the base of the Hopkins - Peters coefficient of nitrogen fixation, which is widely used to access nitrogen fixation. This coefficient is related to biomass yield and is equal to 0,66 for clover grass mixture. In Polish conditions, the quantity of N fixed in investigations using the coefficient amounted to 120-130 kg N/ha.

The method proposed in the paper is based partly on N difference and 15N isotope method. In spite of strict isotopic dilution method, the experiment has been carried out in long term field experiment. It can include both the weather and climatic conditions.

## Conclusions

The quantity of N fixed biologically by clover was calculated using the difference between N uptake by legume- and non-legume crop (maize).

The quantity of N biologically fixed by clover calculated using the difference method accounted to 144 kg/ha.

The amount of N2 fixed by clover was not affected by both, manure and mineral fertilization.
# NITRIFICATION INHIBITION BY PEAT ENRICHED WITH NANOPARTICLES OF SILICATE MINERALS

Natalia Zaimenko¹, Olexandr Slyusarenko², Tymur Bedernichek¹

¹M.M. Gryshko National Botanical Garden, Kyiv, Ukraine, ²Odessa Botanical Garden, Odessa, Ukraine

## Objectives

Usually nitrification inhibitors are chemical compounds which slow down nitrification rates of different N fertilizers. These chemicals are widely used in intensive agricultural systems to reduce losses of N - both for keeping plant-available nitrogen as long as possible in soil and to reduce N losses from the soil-plant system because migration of NO₃⁻ into hydrosphere and of N₂O and NO into atmosphere cause severe environmental problems on different scales - from eutrophication of local waterbodies up to greenhouse effect and ozone layer depletion [1]. However there are many limitations of the application of chemical nitrification inhibitors - for example in organic farming or wastewater management. Thus, developing new methods of nitrification inhibition is a matter of high importance. The objective of this study was to develop an effective and cheap method to reduce nitrification rates in soil without using traditional chemical nitrification inhibitors, but only with safe natural products.

## Method

Application of nanoparticles of silicate minerals in the forms of suspensions or aerosols without peat did not cause any significant changes of soil properties or crop productivity, as well as application of peat itself. In this study a mixture of nanoparticles of silicate minerals (50%) with milled and 1-mm sieved peat (50%) was used as a potential nitrification inhibitor (1 mg g⁻¹ in laboratory experiments and 100 kg ha⁻¹ in field experiments). A mixture (1:1) of analcime and rotten stone (SiO₂ 78-83%, Al₂O₃ 5-7%, Fe₂O₃ 2-3%, CaO 4-7%, MgO 2-3%), both mined from local deposits, was used in this study. Simultaneously we tested the impacts of a mixture of 90% ATC (4-amino-1,2,4-triazole hydrochloride) with 10% of hydrophilic silica nanoparticles (1 mg g⁻¹) on nitrification rates. After preliminary research, where different nitrification inhibitors were studied, effectiveness of ATC was found to be almost identical to nitrapyrin (ClC₅H₃NCCl₃). Because of this fact and while ATC is still one of the most popular nitrification inhibitors in post-soviet countries it was chosen for future research.

*Laboratory microcosm experiments.* Twelve microcosms in 3 replicates were used in this study: soil+wheat, sand+wheat, soil+corn and sand+corn (without any treatment; ATC+hydrophilic silica nanoparticles, dispersed peat+nanoparticles of silicate minerals). Each microcosm contained 200 g of substrate. Samples of calcinated sand and *Gleyic Phaeozems* were used. We chose wheat and corn because they have different types of photosynthesis and nitrogen requirements. Content of NO₃⁻ in substrate was studied after 15, 30 and 45 days of incubation. Urea was used as N fertilizer.

*Field experiments.* Soil of the experimental plots was *Gleyic Phaeozem* under continuous monoculture of winter wheat. Basic agrochemical properties of the topsoil (0 - 20 cm) were: TOC content 18.1 mg g⁻¹, TN 2.5 mg g⁻¹, available P (0.2 M HCl) 150 mg kg⁻¹, water-extractable K 40 mg kg⁻¹, pHₐ₅₀ 7.2. Content of clay was 9.5 %, silt - 65.0% and sand - 25.5%. Urea was used as N fertilizer, superphosphate and potash - as P and K fertilizers. The fertilization regime was N₁₂₀P₆₀K₆₀, 10 kg of each studied nitrification inhibitor was applied per experimental plot.

## Results

*Laboratory microcosm experiments.* Under wheat in the control treatment, concentration of N-NO₃⁻ after 15 days of incubation was 115.7 in sand and 146.9 mg kg⁻¹ in soil. After 30 days of incubation these values were 193.6 and 235.8 mg kg⁻¹; after 45 days - 298.1 and 334.2 mg kg⁻¹ respectively. Application of ATC+hydrophilic silica nanoparticles significantly slowed down nitrification rates. In sand, content of N-NO₃⁻ after 15, 30 and 45 days of incubations were 97.5, 83.9 and 92.4 mg kg⁻¹ and in soil - 101.7, 88.3 and 95.6 mg kg⁻¹