Identifying NEMO: a model-based methodology to identify strategic N application rates for rainfed crop

Transcription

1 Identifying NEMO: a model-based methodology to identify strategic N application rates for rainfed crop Elizabeth Pattey, Morteza Mesbah, Guillaume Jégo Nitrogen Workshop Rennes, France, 26 June 2018

2 N fertilization Issues Identifying the right amount of nitrogen (N) fertilizer for increased crop productivity and limited N loss to the environment is highly important particularly for rainfed corn with high N demand. However, this is challenging because the optimum amount of N rate (N opt ) not only is affected by soil properties, it is also dependent on short-term and seasonal climate variations, which modulate the N uptake. The N opt identification method should include climate variations for given soil properties and cultivars.

3 Yield A model-based methodology to derive optimum N rate for rainfed crops in variable climate Economical N opt,$ is an N rate beyond which adding more N is not economically justified. At this N rate: N-use efficiency (NUE) = ΔY = $N ΔN $ Yield This does not account for any environmental impact caused by application of N fertilizer. NUE=? Yield function NUE= $N $ Yield To better account for the environmental sustainability of crop production, a higher NUE & a lower N opt should be selected. The question is which NUE corresponds to the ecophysiological NUE & N opt? This is the objective of the proposed methodology: Ecophysiological N opt Economical N opt,$ N rate Identifying NEMO A methodology, compatible with reactive N assessment, is developed to identify an ecophysiological optimum N rate using a process-based crop model, daily climate data, and a yield function.

4 Components of the proposed methodology To identify the ecophysiological N opt, a methodology was proposed using a crop model, long time series of climatic data, soil datasets, and a new proposed yield function. The methodology is generic: it can be done for other crops (e.g., wheat, canola, potato), any region insofar the selected crop model is adapted and tested for yield to N response, and is compatible with most crop models able to simulate the effect of the climate-soil-n availability interaction on crop growth and N uptake, such as DSSAT, APSIM, STICS, etc.

5 Components of the proposed methodology Modeling allows 1) the yield response to be tested with fine resolution N increments and 2) the use of consistent cultivar over a long time period (~50 yrs). LO-L N Parameterization of corn cultivars adapted for this ecozone in Jégo et al. (2011). Two cultivars were used: CanMaïsNE was calibrated for the crop heat units (CHU) region and the CanMaïsSE for the CHU region. Yield predicted by STICS (t ha 1 ) London region - loam N rate (kg ha 1 )

6 Testing the proposed methodology in the Mixedwood Plains Ecozone of Eastern Canada More than 90% of Canada s corn production Climatic years per region : 59 yrs Quebec 51 yrs Saint-Hubert 61 yrs Ottawa 48 yrs London 54 yrs Windsor # Model simulations: 819 soil-region-year N rate-soilregion-year Region Most dominant soil texture 2 nd most dominant soil texture 3 rd most dominant soil texture Windsor Silty clay loam Sandy loam Silty clay London Loam Silty clay loam Sandy loam Ottawa Sandy loam Clay loam Loam Saint-Hubert Clay Sandy loam Clay loam Quebec Sandy loam Silty clay loam Loam

7 Yield (t ha -1 ) Yield (t ha -1 Yield Fitting yield functions to model outputs Yield predicted by STICS (t ha 1 ) Common yield functions: Linear-plateau (L-P) Mitscherlish Baule (MB) Proposed yield function: MB-plateau LO-L N (MB-P) London-loam N rate (kg ha 1 ) N plateau N plateau MB-P function led to lower RMSE and predicted the slopes better. N rate N N rate (kg (kg ha ha -1 ) -1 ) STICS L-P L-P MB MB-P Mesbah, M., Pattey, E., Jégo, G A model-based methodology to derive optimum nitrogen rates for rainfed crops a case study for corn using STICS in Canada. Computers and Electronics in Agriculture, 142(Part B):

8 How do we select the N-use efficiency (NUE)? We used the following range: Dry Yield (t ha -1 ) Yield function NUE = NUE $ = t dry Yield/ kg N rate N opt N opt,$ N rate (kg ha -1 ) NUE $ = Nyiraneza, J., N Dayegamiye, A., Gasser, M.O., Giroux, M., Grenier, M., Landry, C., Guertin, S., Soil and crop parameters related to corn nitrogen response in eastern Canada. Agron. J. 102,

9 N-use efficiency (NUE) selection criteria Sandy loam (SL) soils For higher NUE values, the linearity in Y Nopt vs N opt data increases. However, more yield is lost compared to the maximum achievable yield.

10 Trade-off between economic and environmental objectives Sandy loam soils For a given NUE, the yield-nopt linear relationship is used to derive an N application rate at a given expected yield (Yexp), which is referred to as recommended N (Nrec). Expected yield Recommended N

11 Expected dry yield occurrence over 50+ yrs for sandy loam soil Y exp Occurrence of Y exp <Y (%) Windsor London Ottawa Saint-Hubert Quebec Mesbah, M., Pattey, E., Jégo, G A model-based methodology to derive optimum nitrogen rates for rainfed crops a case study for corn using STICS in Canada. Computers and Electronics in Agriculture, 142(Part B):

12 Expected dry yield, Nrec, yield loss, N excess or deficit for same soil texture in different regions Mesbah, M., Pattey, E., Jego, G., Didier, A., Geng, X., Tremblay, N., Zhang, F New model-based insights for strategic nitrogen recommendations adapted to given soil and climate. Agron. Sustain. Dev. 38:36. Reduction in yield: 1 ΔY = n N excess/deficit: Excess>0 Deficit<0 n i = 1 n 1 ΔN = n i = 1 Ymax,i Y i N rec Nrec N opt i

13 Case study for corn in the Mixedwood Plains ecozone Low optimum NUE High optimum NUE

14 Case study in the Mixedwood Plains ecozone Optimum NUE (kg dry yield kg -1 N) Clay Clay loam Silty clay Silty clay loam Loam Sandy loam Windsor London Ottawa Saint-Hubert Quebec Volumetric available water capacity (AWC) in % Clay Clay loam Silty clay Silty clay loam Loam Sandy loam Windsor London Ottawa Saint-Hubert Quebec 7 t ha AWC<12 12<AWC<15 15<AWC

15 Integrated modeling for environmental benefit assessment of improved N management Mesbah, M., Pattey, E., Jégo, G A model-based methodology to derive optimum nitrogen rates for rainfed crops a case study for corn using STICS in Canada. Computers and Electronics in Agriculture, 142(Part B):

16 Mesbah, M., Pattey, E., Jego, G., Didier, A., Geng, X., Tremblay, N., Zhang, F New model-based insights for strategic nitrogen recommendations adapted to given soil and climate. Agron. Sustain. Dev. 38:36. Conclusions The ecophysiological optimum N rates varied by soil texture and along the range of climate of the ecozone. Thus, N recommendation must be region and soil specific. The model outputs showed that the interannual climate variations had a strong influence on the optimum N rates of each corn growing season The NUEopt ranged from 10 to 17 kg dry yield kg -1 N, and was often higher for loamy soils, and lower for clayey soils. NUEopt was also higher for soils with lower available water capacity. These recommendations could reduce the use of N fertilizer as they are kg ha -1 less than recommended values in Ontario and Quebec. The proposed methodology is compatible with quantifying nitrous oxide and ammonia emissions as well as nitrate leaching.

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