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«International 17 Workshop th Nitrogen The was jointly organised by Teagasc and AFBI Printed by Print Depot Suggested citation Authors, 2012. Title ...»

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2. Materials & Methods A three-year field experiment (2008-2010) was conducted in a perennial ryegrass (Lolium perenne L.) sward on a sandy soil (38 g kg-1 organic matter, 1 g kg-1 Ntotal, 0.3 mg kg-1 Nmineral, carbon (C)/N ratio 22, and pH-KCl 5.3) just north of the city of Wageningen. Both fresh (FR) and composted (CO) SCM were surface-spread on grassland at once. This was done manually using pitchforks and three rates in the range from about 200 to 650 kg N ha-1 were used. Each experimental unit measured 5 m by 3 m. All treatments, including a non-fertilized control, were arranged in a randomized complete block design with three replicates. FR manure was taken directly from a litter-barn, whereas CO manure was obtained after storing and extensively mixing FR manure during a period of 8 months as described by Shah et al. (2010). During each growing season, the herbage was harvested three times (second half of June, first week of September and the last week of October). The herbage was cut to a stubble height of 4 cm using a motor mower. Fresh herbage yield was measured in the field and representative samples were oven-dried at 70°C for 48 hours, ground to pass a 1 mm sieve and analysed for total N content. Subsequently, apparent N recovery (ANR) in each year was calculated by means of the N difference method.

3. Results & Discussion The herbage N uptake in the non-fertilized control was on average 30 kg N ha-1 year-1. At the lowest N application rate, the herbage response in case of CO manure was not different (P 0.05) from the control. In all probability, this was caused by immobilization of the applied and released mineral N since the soil C/N ratio of the used field was above 20 and thus relatively high. The initial mineral N content of the CO manure compared to the FR manure was almost three-times lower (7 vs. 20 g 100g-1Ntotal) as a result of N losses during the composting process. Consequently, in the year of application herbage ANR was lower (P 0.01) from the CO manure (Table 1; Figure 1). In the two succeeding years this pattern did not change and herbage ANR was almost zero in the last year for the CO manure (Table 1; Figure 1). This can be ascribed to the presence of more stable organic N compounds since most of the readily degradable organic N compounds are lost during composting (Kirchmann, 1985). This is another drawback of composting next to the high losses (up to 50%) of the initial total N content (Shah et al., 2010; Shah and Lantinga, 2012).

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4. Conclusions During all three years, herbage N recovery from the fresh solid cattle manure was about twice as high compared to that from the composted treatment. The residual N fertilizing effect on this soil with a high C/N ratio was even almost zero in year 3 in the latter case. For use on grassland it is recommended not to compost solid cattle manure.

References Kirchmann, H. 1985. Losses, plant uptake and utilization of manure nitrogen during a production cycle. Acta Agriculturae Scandinavica Supplementum 24, pp. 77.

Schröder, J.J., Uenk, D. and Hilhorst, G.J. 2007. Long-term nitrogen fertilizer replacement value of cattle manures applied to cut grassland. Plant and Soil 299, 83-99.

Shah, G.M. and Lantinga, E.A. 2012. Effects of storage method on N disappearance and herbage N recovery from solid cattle manure. This workshop, pp. 2.

Shah, G.M., Shah, G.A. and Lantinga, E.A. 2010. Management strategies to reduce nitrogen losses from solid cattle manure. In: Cordovil C., Ferreira L. (Eds.), Proceedings of the 14th Ramiran International Conference, 13-15 Sept.

2010, Lisboa, Portugal, pp. 204-207.

Nitrogen Workshop 2012 Forage yield and nitrogen utilization of forage maize hybrids in Organic Farming Monteagudo, A.B.

Centro de Investigaciones Agrarias de Mabegondo (CIAM-INGACAL), A Coruña, Spain

1. Background & Objectives Chemical nitrogen (N) fertilizers are the most widely used to increase the maize yield but their use is forbidden in Organic Farming (OF). Only a controlled amount of organic N fertilizer is allowed in OF and the availability of N for plant uptake is limited. Moreover, the lower N availability reduces the risk of N loss by leaching so N utilization efficiency (NUtE) is interesting to consider for forage production at low N levels. In this context, the improvement of N uptake and utilization efficiency in forage production is required to prevent biomass yield reduction and nitrogen loss to the environment. The objective of this study was to evaluate forage maize yield and N utilization under OF conditions.

2. Materials & Methods Thirteen maize hybrids obtained at CIAM-INGACAL and 3 commercial hybrids (C) were evaluated under OF conditions in two field trials in Lugo (NW Spain): 1. Xía, without organic fertilizer (0N);

2. Arroxo, where organic cattle manure was applied at a rate of 170 kg N ha-1 (following the European Commission regulation No. 889/2008) in one application before planting (170N). Both soils came from a pasture rotation. Average rainfall and temperature during the growth cycle are presented in Figure 1. The experimental design was a randomized block with one plot of 8 m2 per hybrid and three replications with 90.000 plant ha-1 as the final plant density.

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At the silage stage, samples of 300g of entire plant, stalk and ears per plot were grinded and dry weights were measured after drying them at 80ºC for 16 hours. Forage yield was expressed as dry matter (DM) (Mg ha-1) based on the number of plants at harvest. Dried samples were ground in a Christy Norris mill to pass a 1mm sieve. Near Infrared Reflectance Spectroscopy (NIRS) was used to estimate crude protein content (CP) according to Campo et al. (2010) equations. Nitrogen uptake was estimated from CP and DM yield in each sample (kg N ha-1). NUtE was calculated as the ratio of DM yield to whole plant N uptake (kg kg-1) while the nitrogen harvest index was the ratio between ear N uptake and whole plant N uptake (kg kg-1). Harvest index was calculated as the ratio of grain yield to biomass yield (Mg Mg-1). The Duncan test to assess the differences between means and Pearson correlations between traits were calculated using the SAS statistical package v 9.2 (SAS Institute, 2008).





Nitrogen Workshop 2012

3. Results & Discussion The strong relationship found between N stress and maize yield has been reported by different authors (Cox et al., 1993; Bertin and Gallais, 2000; Améndola et al., 2010). This association could be observed in our study as one of the factor on the reduction in forage yield of 17% for the C treatment under the same trial conditions (Table 1), but this reduction was less than that found by other authors in forage maize (Cox et al., 1993). Nitrogen uptake was lower at 0N than 170N trial due to a positive correlation existed between this trait and rate of N applied to soil (r2 0.7, P0.001). This result is in disagreement with other studies (Dobermann, 2005).

Table 1. Forage yield, total nitrogen uptake (Nt), nitrogen uptake in stover (Nstover), nitrogen uptake in ear (Near), harvest index (HI), nitrogen utilization efficiency (NUtE) and nitrogen harvest index (NHI) of forage maize hybrids.

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In agreement with other studies negative correlations were found between Nt, Nstover and NUtE (r2

-0.88) and HI and NHI were positively correlated (r2=0.85). NUtE could have been affected by rainfall being low in August and high in October in the 0N trial. Its value was higher at low N supply so utilization efficiency was better at these trial conditions. Hybrids showed genetic variability with means statistically different for all traits studied within the CIAM group which had better performance than the commercial ones.

4. Conclusion Nitrogen uptake and utilization were variable amongst hybrids and so an improvement of N use efficiency could be possible by plant breeding programs. Evaluated hybrids were able to adapt to low N input with little reduction in forage yield and an increase in the nitrogen utilization efficiency.

References Améndola R., Cach I, Álvarez E., López I, Burgueño J., Martínez P. and Cristóbal D. 2011. Nitrogen balance in forage maize with different fertilization and phase of crop rotation with pastures. Agrociencia 45, 177-193.

Bertin P. and Gallais A. 2000. Genetic variation for nitrogen use efficiency is a set of recombinant maize inbred lines I.

Agrophysiological results. Maydica 45, 53-66.

Dobermann A. 2005. Nitrogen use efficiency - state of the art. IFA International Workshop on enhanced-efficiency Fertilizer. Germany, pp. 1-16.

Campo L., Castro P. and Moreno-González J. 2010. Ecuaciones de calibración preliminares para la evaluación de la

calidad de la biomasa en plantas de maíz por NIRS. In: Calleja A., García R., Ruiz A. and Peláez R. (eds.), Pastos:

Fuente natural de energía. Zamora, Spain, pp. 135-139.

Cox W.J., Kalonge S., Cherney D.J. and Reid W.S. 1993. Growth, yield and quality forage under maize different nitrogen management practices. Agronomy Journal 85, 341-347.

European Commission regulation Nº 889/2008. Implementation of Council Regulation (EC) No 834/2007 on organic production and labelling of organic products with regard to organic production, labelling and control.

SAS Institute. 2008. SAS version 9.2. SAS Institute Inc., Cary, NC.

Nitrogen Workshop 2012

Gap filling of missing data for calculating the cumulated ammonia emission in a fertilized bare soil: a case study in Lombardia region (Italy) R.M. Ferraraa,c, M. Carozzib, M. Acutisb, N. Martinellia, G. Ranaa a CRA - Research Unit for Agriculture in Dry Environments, Bari, Italy b University of Milan, Di.Pro.Ve, Milan, Italy c CRA - Research Centre for Agrobiology and Pedology, Florence, Italy

1. Background & Objectives The ammonia (NH3) concentration data necessary for estimating NH3 fluxes are often unavailable.

Reasons for this can be: (i) the detection range of detectors is outside the actual concentration values; (ii) the measuring equipment are upwind with respect to the fertilization spreading point;

and (iii) occasional gaps occur owing to instrumental failure. In such situations, to obtain a complete time series from which to calculate cumulative NH3 emissions, empirical estimates of missing fluxes are needed. The objective of the present study was to assess the reliability of the method developed by Spirig et al. (2010) for determining missing NH3 flux values using data from slurry application experiments in the Lombardia region of northern Italy.

2. Materials & Methods Applying the single layer model developed by Sutton et al. (1998), applied to bare soil, the NH3 flux is calculated as   z 0   z  ' F  [1] Ra  z   Rb where χ(z0’) is the NH3 concentration estimated at the surface, χ(z) is the concentration measured at height z, and Ra and Rb are the aerodynamic and the boundary layer resistances, respectively, calculated according to Flechard et al. (2010).

Firstly, for the NH3 fluxes measured in non problematic phases, values for χ(z0’) were derived using Equation 1. Secondly, an operational relationship was found between ln(Γs) and the time after slurry

application (in hours), where Γs is the [NH4+] to [H+] ratio (Dasgupta and Dong, 1986):

  z'0 109  s  4.12184507/T [2] where T is air temperature in K, and χ is given in ppb. This operational relationship was found to be linear and was used to derive χ (z0’) as a function of time after slurry spreading when the values of NH3 fluxes were not available. The value of χ(z) should always be available. The estimation of missing NH3 fluxes after slurry application is determined in a range, between a minimum and a maximum. The lower limit is obtained by log-linearly interpolation of Γs, while the upper limit is obtained using the initial surface concentrations calculated by repeating the Γs of slurry until the first experimental surface concentration was available.

The method described above was applied in an experimental trial in Landriano (Lombardia, Italy), where slurry was applied to bare soil (87 m3 ha-1 with 188 kg N ha-1, 95 kg N-NH4+ ha-1, 4.4% of dry matter and pH 8) on 27 March 2009, starting at 9:00 a.m. The NH3 fluxes were measured by the eddy covariance technique (Kaimal and Finnigan, 1994), using a Gill R2 (Gill Instruments Ltd, UK) sonic anemometer together with the QC-TILDAS developed by Aerodyne (USA) (Zahniser et al., 2005). The fluxes in the first 4 hours were not measured because the equipment was upwind with respect to the direction of the slurry spreading. NH3 concentrations in air were also measured by passive diffusion samplers (ALPHA samplers; Sutton et al., 2001) both upwind and downwind.

In order to evaluate the performances of the model, it was tested in another experimental campaign (Cornaredo, Lombardia region, Italy) where slurry was applied on 17 March 2010 starting at 9:00 a.m. and where all the values of NH3 fluxes were available. In this case, the fluxes were determined using the inverse dispersion model WindTrax (Flesch et al., 1995) with the NH3 concentrations measured by ALPHA samplers (every 2 hours during the spreading day) and the model input variables measured using a sonic anemometer.

Nitrogen Workshop 2012

3. Results & Discussion Figure 1 shows the good agreement obtained between estimated and measured NH3 fluxes in the first day of the trial in Cornaredo (MAE=2.63; RRMSE=37.22; EF=0.86; slope=0.99; r2=0.9): in this case only the lower limit was used (Eq. 1 & 2) because the slurry was homogeneously applied and we suppose that the emission started uniformly at t=0.

Figure 1. Comparison between estimated and measured NH3 fluxes in Cornaredo during and after slurry spreading.

The model was than applied to the Landriano trial (Figure 2), where the measurements of NH3 concentration were missed for the first 6 hours. In this case upper and lower limits of the estimated fluxes are shown with the measured fluxes in the last part of the period. Moreover, the relationship between ln(Γs) and the hours after slurry application is plotted, together with the linear relationship used to determine the estimated values of χ(z0’).

ln(Γs) 



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