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Estimates at farm level provide an integral account and tend to be lower than the summed costs at field and/or farm compartment levels, due to compensation effects. Estimates at sector level include the indirect economic effects for suppliers and processing industries, which can be significant when N management activities at the farm significantly change farm inputs and/or outputs. Finally, cost-benefit analyses at national or society level basically integrate all effects, the cost of the N management activities as well as the benefits to society of lower N surpluses and higher NUE (e.g. Brink et al., 2011). Estimating costs of N management activities at farm level can be done through longitudinal comparisons of one or few similar farms over time or through comparisons of different farms with and without improved N management. Effects of N management activities are monitored over time in the first case, while differences between farms in N management activities are analyzed statistically in the second case. The cost of improving N management highly depends on the reference situation; on farms with poor nutrient management Nitrogen Workshop 2012 it is often highly beneficial to lower N surpluses (Ondersteijn et al., 2003). On the other hand, efficiently managed farms generally have good economic and environmental performances, and may not easily decrease N surplus and increase NUE further.
4. Economic costs of N management activities on arable and vegetable farms Nitrogen management activities on arable farms relate to maximizing the N output (i.e., yield) and maximizing the utilization of available N sources, using the right method, time and amount of application. Maximizing yield involves using the proper genetic crops and optimal crop husbandry. The economic cost of selecting the appropriate timing, method and rate are relatively small, but the implementation of these best management practices is still modest. Sheriff (2005) examined why farmer perceptions of agronomic advice, input substitutability, hidden opportunity costs, uncertainty, and risk aversion can make it economically rational to “waste” fertilizer by applying it above agronomically recommended rates. The costs of N fertilizer in proportion to the total production costs may range from 20-30% on large cereals farms to 1-5% on farms specialized in growing seed potatoes, vegetables and flowers (Pederson et al., 2005;
Van Dijk et al., 2007; Jensen et al., 2011). The relatively low cost of N use for high-value crops is one of the reasons for its liberal use in these crops, and for the relatively high N surpluses and low NUE (Jensen et al., 2011). Costs and benefits of improved N management relate to (i) decreasing over-fertilization, (ii) increasing the effectiveness of N applied via fertilizers, manures, composts, i.e., use the right method and time of application, and (iii) increasing crop yield through selection of high-yielding crop varieties and optimal crop husbandry. The net costs are highly depending on crop type, but are usually in the range of -0.5 to +2 euro per kg N saved, which translates to -5 to 25 euro per ha (Van Dijk et al., 2007; Mikkelsen et al., 2010).
5. Economic costs of N management activities on dairy farms Empirical information on the relationship between farm management, N surplus and financial consequences on dairy farms has been collected by Rougaar et al. (1997), Ondersteijn et al.
(2003), Doornewaard et al. (2007) and Daatselaar et al. (2010). A major conclusion of these studies is that improved management leads to improved efficiency and to improved financial results, though within certain boundaries. Similar conclusions have been reached by Powell et al., (2009; 2010) and Rotz (2003) for dairy farms in the USA. Improving the utilization of nutrients from manure while decreasing the use of synthetic fertilizers is cost-effective measure to decrease N surplus and increase NUE.
6. Economic costs of N management activities on specialized pig and poultry farms Landless pig and poultry farms basically import all animal feed and export animal products and manure. Activities related to improving N management on these farms include (i) low protein, phase-feeding, (ii) herd management (genetic selection, reproduction and disease management), (iii) low-emission housing system and (iv) low-emission manure storage, treatment and export.
Economic cost of these activities can be very high, up to 10% of total running costs and more.
To cover, these costs, farms have to excel in productive performances and in scale.
7. Conclusions Empirical information on economic cost of improving N management is scarce. Benefits seem largest for mixed farms, while costs are highest for landless pig and poultry farms. There is need for further studies, collecting and analyzing empirical information on economic cost of improving N management, both through longitudinal comparisons and through comparisons of farms with and without improved N management.
References Available on request to authors (firstname.lastname@example.org).
Nitrogen Workshop 2012 Beer, bread and other opportunities for innovation in nitrogen use Sylvester-Bradley, R.a a ADAS UK Ltd., Battlegate Road, Boxworth, Cambridge, CB23 4NN, UK
1. Proposition The paradox is frequently cited between improving crop productivity and reducing inputs of nitrogen (N), thereby reducing N emissions (Berry et al., 2011). However, despite the evident urgency, commercially viable resolutions are hard to envisage.
N requirements of high yielding crops (e.g. cereals yielding 9 t ha-1) are primarily due to the N in their harvested products, but also to the N fertility of soils and the inefficiencies of fertilisers or manures used in their production. The pace of innovation in crop N management, crop N requirements or in N fertiliser efficiency has been poor thus far. Key factors governing fertiliser N requirements were recognised at least 75 years ago; yet little of the known wide variation in requirements is predicted by current decision-support systems, commercial cultivars have yet to be bred for reduced N requirements, and most N is still sprinkled onto soils as simple salts with no conditioning and poor targeting. In consequence, crop recovery of fertiliser N is always partial, whilst most of the N sold to end users is subsequently wasted or excreted. By considering the path of N through to end use (Figure 1), and the recycling of N, points with potential for innovation become apparent, the most telling and crucial being in end-use.
Figure 1. Anthropogenic cycling of nitrogen with ‘thought bubbles’ indicating opportunities for innovations to reduce inputs, hence waste and environmental pollution.
0 1.5 2 1.8 Figure 2. Grain yields (circles) and grain N contents (%DM; triangles) of wheat and barley in the UK since the 1970s (Survey data from Defra and HGCA websites). Axes for wheat and barley are scaled identically. Significant trends (linear or quadratic) are shown; there is no significant trend for wheat grain N.
3. Summary Reducing end-use requirements for N could have significant repercussions for the way that crops are bred, grown and fertilised. Whilst protein (or N) content is not included within specifications for most crop products, opportunities exist for their introduction. Strategies to enhance sustainable crop productivity should seek to introduce and improve specifications for N in foods and feeds, as well as addressing the use of fertiliser N more directly through crop and fertiliser improvement.
References Berry, P.M., Sylvester-Bradley, R. and Weightman, R. 2011. Yield potential of combinable crops in the UK.
Proceedings of the International Fertiliser Society 697, 1-17.
HGCA. 2011. Milling wheat – quality criteria and tests. Sourced at www.hgca.com/publications/documents/varieties/milling_wheat.pdf magb (The malsters association of Great Britain). 2011. Controlling the intake of malting barley to UK maltings.
Sourced at: www.ukmalt.com/maltingbarley/controlintake.asp Smith, T.C., Kindred, D.R., Brosnan, J.M., Weightman, R.M., Shepherd, M. and Sylvester-Bradley, R. 2006). Wheat as a feedstock for alcohol production. HGCA Research Review No. 61, 88 pp.
Sylvester-Bradley, R. and Kindred, D.R. 2009. Analysing nitrogen responses of cereals to prioritize routes to the improvement of nitrogen use efficiency. Journal of Experimental Botany 60, 1939-1951.
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Using NDVI to define optimal N rate: an application on durum wheat Loddo, S.a, Morari, F.a, Sartori, L.b, Berti, A. a and Mosca, G.a a Dept of Agronomy Food Natural resources Animal and Environment, University of Padua;
b Dept of Land Environment Agriculture and Forestry, University of Padua, Italy.
1. Background & Objectives In the past decade, identification of optimal N rate has become a crucial issue in wheat cultivation, since the breeders’ goal to increase protein content has contrasted with the effort to limit N input (Sylvester-Bradley and Kindred, 2009). Use of uniform N rates at field scale generally leads to exceed actual crop requirements (Lobell et al., 2004) thus soil spatial variability should be accounted to enhance nitrogen use efficiency. Spectral indexes are useful tools to assess N status of crops and optimize fertilization, in particular for small grain cereals (Raun et al, 2001; Zilmann et al., 2006). In this experiment a normalized difference vegetation index (NDVI) was used to set up a reference scale for nitrogen application in durum wheat. An algorithm for N input correction was implemented and its results were compared to the actual fertilisation applied in field.
2. Materials & Methods In 2010-2011, a 13.6 ha field was cropped with durum wheat in Northern Italy (Mira, 45°22’N, 12°08’E). Soil properties were strongly variable (e.g.higher sand content and poor organic matter in South-Eastern corner (Figure 1-a)). In the field, 3 management zones were identified and subjected to 6 site-specific nitrogen treatments: 130, 160 and 200 kg N ha-1 (at tillering and stem elongation) or the same N rates with additional 15 kg N ha-1 by late foliar treatment. To set a reference scale, NDVI (Greenseeker, Ntech Industries, CA-USA), biomass production and N uptake were measured from tillering to flowering in 1 m2 plots (in total 18 areas across the field). In 4 dates during spring season, Greenseeker associated to a DGPS was also used to measured NDVI along 15-m wide transects (in total ~6000 points). Grain yield and protein content sensors were installed on a combine harvester to acquire data across the field (3000 points in 13.6 ha). Spatial information was extended to the field with Kriging technique. A recommendation map for N application was produced from NDVI map and compared to N rates actually applied in the management zones.
3. Results & Discussion NDVI sampled in 1 m2 plots was highly correlated with N uptake (R2 = 0.8821; n = 75; P0.001). A single exponential equation  described this relationship from tillering to flowering. Senescent plots were excluded from model to avoid to underestimate N content. RMSE was low enough (22.1 kg ha-1) to encourage the use of spectral index to forecast N uptake. Optimal NDVI curve was estimated by calculating the 90th percentile for each sampling date. Values were plotted against thermal-based time scale (base temperature 0°C) and an inverse exponential model  identified optimal NDVI across all durum wheat growth cycle. Highest value was found at the booting stage.
A recommendation N fertilisation map was calculated from NDVI map of 7th April (onset of stem elongation, Figure. 1-b) as follow: a) the difference between the optimal NDVI and the real NDVI was converted in N uptake deficit using equation ; b) the N uptake deficit was added to the base fertilisation (105 kg ha-1) which was estimated to be needed to maximise N uptake at the end of
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growth cycle in normal conditions. NDVI-based recommendation (NDVI-rec) was compared to actual fertilisation (Figure 1-c). Highest grain yield (7.9 t ha-1) and N uptake (Figure 1-d) were observed in plot 160+15, where accordance between NDVI-rec and real N rate was high. In plot 130+0 actual N rate was lower than NDVI-rec, highlighting N deficiency conditions. These were also confirmed by the poorer crop performances obtained in a management zone characterised by higher soil quality (e.g. lower sand content, higher SOM). Very low yield (4.8 t ha-1) and thus N offtake (Figure 1-d) were observed in 200+15 management zone: water stress, worsened by the lower water retention capacity (i.e. sandy soil), limited crop yield. Apparent N balance was therefore in dramatic excess (Figure 1-e). In the sandy area, NDVI measurements were ineffective to optimise N applications since they were carried out before the unforeseeable water stress events.
Figure 1. Maps of soil sand content (a), NDVI at the beginning of stem elongation (b), difference between NDVI-based and actual N rate (c), N offtake of grains (d) and apparent N balance (e).
4. Conclusion As observed in a previous study (Zillman et al., 2006), if no other stresses than N availability occur, NDVI-based N recommendation matches crop requirements. These results evidence the possibility to apply on durum wheat sensor-based input correction, extending it to a wide area in Southern Europe. Difficulties are still encountered to outline optimum N rate in sandy soils which are more sensitive to meteorological variability.
References Lobel,l D.B., Ortiz-Monasterio, J.I.O and Asner, G.P. 2004. Relative importance of soil and climate variability for nitrogen management in irrigated wheat. Field Crops Res. 87, 155-165.
Raun, W.R., Solie, J.B., Johnson, G.V., Stone, M.L., Mullen, R.W., Freeman, K.W., Thomason, W.E. and Lukina, E.V.
2002. Improving nitrogen use efficiency in cereal grain production with optical sensing and variable rate application.
Agron. J. 94, 815-820.
Sylvester-Bradley, R. and Kindred, D.R. 2009. Analysing nitrogen responses of cereals to prioritize routes to the improvement of nitrogen use efficiency. J. Exp. Bot. 60, 1939-1951.