During the last years, an increasing number of stockless farms in Europe converted to organic farming practice without re-establishing a livestock. Due to the lack of animal manure as a nutrient input, the relocation and the external input of nutrients is limited in those organic cropping systems. The introduction of a one-year green manure fallow in a 4-year crop rotation, including clover-grass mixtures as a green manure crop is the classical strategy to solve at least some of the problems related to the missing livestock. The development of new crop rotations, including an extended use of catch crops and annual green manure (legumes) may be another possibility avoiding the economical loss during the fallow year. 

Modelling of the C and N turnover in the soil-plant-atmosphere system using the soil-plant-atmosphere model DAISY is one of the tools used for the development of new organic crop rotations. In this paper, we will present simulations based on a field experiment with incorporation of different catch crops. 

An important factor for the development of new crop rotations for stockless organic farming systems is the expected N mineralisation and immobilisation after incorporation of the plant materials. Therefore, special emphasise will be put on the simulation of N-mineralisation/-immobilisation and of soil microbial biomass N. Furthermore, particulate organic matter C and N as an indicator of remaining plant material under decomposition will be investigated

Hansen, S.

Magid, J.

Müller, T.

Nielsen, N. E.

Stoumann Jensen, L.

Thorup-Kristensen, K.

English

Müller, Dr. Torsten

Magid, Dr. Jakob

Jensen, Dr. Lars Stoumann

Nielsen, Dr. Niels Erik

Thorup-Kristensen, Dr. Kristian

Organic Eprints

Symposium no. 14 Paper no. 830 Presentation: oral830-1Catch crops in organic farming systems withoutlivestock husbandry-model simulationsMÜLLER Torsten (1), JENSEN Lars Stoumann (2), MAGID Jakob (2), NIELSENNiels Erik (2), HANSEN Søren (3) and THORUP-KRISTENSEN Kristian (4)(1) Dep. of Soil Biology and Plant Nutrition, Faculty 11, University of Kassel,Nordbahnhofstr. 1a, D-37213 Witzenhausen, Germany(2) The Royal Veterinary and Agricultural University, Dep. of Agricultural Sciences,Plant Nutrition and Soil Fertility Lab., Frederiksberg, Denmark(3) The Royal Veterinary and Agricultural University, Dep. of Agricultural Sciences,Agrohydrology and Bioclimatology Lab., Høje Tåstrup, Denmark(4) Danish Institute of Agricultural Science, Dep. of Horticulture, Research CentreAarslev, DenmarkAbstractThis paper presents simulations of the soil-plant-atmosphere model DAISY basedon an organic crop rotation with incorporation of different catch crops following pea asa leguminous cash crop. Special emphasise was put on the simulation of N-mineralisation/-immobilisation and of soil microbial biomass N. The DAISY model wasable to simulate soil mineral N and soil microbial biomass N after soil incorporation ofcatch crop plant residues to some extend. Several processes need further attention andmay be integrated into the DAISY model: (1) soil tillage induced mobilisation oforganic material including considerable amounts of organic N, (2) winter killing ofsensitive plant species and varieties, (3) decomposition of plant residues at the soilsurface as occurring after winter killing, (4) decomposition of easily decomposableplant residues at low temperatures, (5) soil microbial residues as an organic pooltemporarily protected against turnover. Furthermore, reliable criteria for the subdivisionof green plant residues into an easily decomposable pool and a more recalcitrant poolhave to be developed.Keywords: organic farming, catch crop, DAISY, modelling, mineral N, soil microbialbiomassIntroductionModelling of the C and N turnover in agro-ecosystems is one of the tools used forthe development of new organic crop rotations. Point of departure for our investigationwas the following hypothesis: The soil-plant-atmosphere model DAISY is able tosimulate organic crop rotations including an extended use of catch crops and greenmanure.This paper presents model simulations based on a field experiment withincorporation of different catch crops following pea as a leguminous cash crop.An important factor for the development of new crop rotations for stockless organicfarming systems is the expected N mineralisation and immobilisation after soilMÜLLER ET AL. 17th WCSS, 14-21 August 2002, Thailand830-2incorporation of the plant materials. Therefore, special emphasis was put on thesimulation of N-mineralisation/-immobilisation and of soil microbial biomass N.Materials and MethodsField ExperimentThe field experiment with 3 replicates was placed at the Agricultural ResearchCentre Aarslev (10°27' E, 55°18' N) located at the isle of Funen (Denmark) in wettemperate climate (Throrup-Kristensen, 2001). Mean yearly temperature andprecipitation were 8.1°C and 719 mm respectively during the period 1986 to 1998.Data from the first year of the experiment reported by Throrup-Kristensen (2001)were chosen for this investigation. The soil in the first year was a Typic Luvisol. Thetopsoil was a sandy loam with 14.6% clay, pH(CaCl2) 7, 2.0% C and 0.15% N.Pea was sown 22 April 1996. In stead of harvesting pea, the above ground plantmaterial was ploughed into the soil completely 25 July 1996. 2 August 1996 differentcatch crops were sown. For the model simulations we chose four catch crops differingin chemical properties (Table 1) and growth patterns. Oil radish (Raphanus sativus cv.oleiformis) and winter rape (Brassica napus cv. napus) died completely during winter.Italian ryegrass (Lolium multiflorum) and rye (Secale cereale) were partly killed duringwinter time. The remaining plant material was incorporated into the soil by rotavation 2April 1997. Thereafter, the soil remained as bare fallow. After rotavation, soil microbialbiomass N (Nmic) and mineral N (Nmin) were measured 5 times until 1 July 1997 to adepth of 25 cm. Soil microbial biomass was estimated by chloroform fumigationextraction (Brookes et al., 1985). Total N in the extracts was measured afterpersulphate-oxidation at 120°C for 30 minutes, according to Cabrera and Beare (1993).Nmic was calculated as the difference between fumigated and non-fumigated samplesmultiplied by an fEN-factor of 1.85 (Brookes et al., 1985; Joergensen and Mueller,1996). Soil mineral N (NH4+and NO3-) was measured in the non-fumigated 0.5 K2SO4-extracts by colorimetric methods using flow-injection analysis (Keeney and Nelson,1982).Table 1 Properties of the above ground catch crop plant materials before soilincorporation. afdm = ash free dry matter.total water insoluble water solubleCt Nt cellulose lignin C Nplant[% afdm]C/N[% afdm]lignin/N[%Ct][% Nt]C/N C[% Ct]N[% Nt]C/Nrye 49.0 4.3 11.3 19.8 2.9 0.7 60.9 49.3 14.9 39.1 50.7 9.0Italianryegrass48.9 4.2 11.7 22.8 3.9 0.9 74.3 61.0 14.3 25.7 39.0 7.7winterrape47.9 3.9 12.5 30.7 7.0 1.8 72.6 56.3 16.1 27.4 43.7 9.9oil radish 48.5 3.4 14.3 33.5 8.1 2.39 77.7 67.7 16.4 22.3 32.3 7.7The DAISY modelDAISY is a deterministic model which simulates water-, energy-, C- and N-fluxesin a one-dimensional soil-plant-atmosphere system (Hansen et al., 1990; Hansen et al.,1991). In this study, an open DAISY version (Abrahamsen and Hansen, 2000) wasused.MÜLLER ET AL. 17th WCSS, 14-21 August 2002, Thailand830-3Three discrete soil organic pools (added organic matter (AOM), soil microbialbiomass (SMB) and native nonliving soil organic matter (SOM)), soil mineral N (Nmin)and soil respiration (CO2) are simulated by the soil-organic-matter submodel (Figure 1).Figure 1 C and N fluxes between the various pools and subpools of organic matter,mineral N and evolved CO2 in the DAISY submodel for Soil Organic Matter(Hansen et al., 1990, 1991). AOM = Added Organic Matter, SMB = SoilMicrobial Biomass, SOM = native dead Soil Organic Matter. fX = partitioncoefficient.MÜLLER ET AL. 17th WCSS, 14-21 August 2002, Thailand830-4Plant residues are simulated as AOM. The organic pools (AOM, SMB, SOM) areeach considered being a continuum having a certain range of turnover rates. In theoriginal development of the model, it was found that these continuums could besimulated satisfactorily if each pool is subdivided into two subpools, one with a slowerturnover (i.e. SOM1) and one with a faster turnover (i.e. SOM2). Furthermore, it wasassumed that the turnover of the pools follows first order kinetics.Turnover rate coefficients under standard conditions (10°C, -10 kPa, 0% clay) aredefined for each carbon pool. For SMB1 and SMB2, death rate coefficient andmaintenance respiration rate coefficient have to be defined separately. In order todetermine actual rate coefficients, the rate coefficients under standard conditions aremultiplied by modifiers that are functions of the actual soil temperature and of the actualsoil water potential. Additionally, modifiers depending on the soil clay content areadded for the pools SOM1, SOM2 and SMB1.Carbon fluxes into microbial biomass are multiplied by substrate utilisationefficiencies which define the fraction of substrate C, that can be used for microbialgrowth. The remaining substrate C is respired as CO2.After each time step, the N pools are calculated from the actual amount of the C-pool by multiplication with the reciprocal value of a fixed C/N ratio for each pool. NetN-mineralisation or N-immobilisation is then derived from the N-balance.If immobilisation occurs during growth of SMB1 and SMB2, this growth may belimited by the lack of mineral N in the soil. The basic time step of the soil-organic-matter submodel is 1 hour. A more detailed description of the soil-organic-mattersubmodel is given by Mueller et al. (1997).For the comparisons with the measured values, total simulated soil microbialbiomass N (Nmic) was calculated as the sum of SMB1-N and SMB2-N.Detailed descriptions of the whole DAISY model are given by Hansen et al. (1990and 1991) and by Abrahamsen and Hansen (2000).Soil physical and chemical properties were parameterised using measured data. Thesoil organic matter module was parameterised using a setup calibrated on a fieldexperiment with incorporation of rape straw (Mueller et al., 1997).For the simulation of pea, a plant module including symbiontic N2-fixation wasused. For the simulation of Italian ryegrass and rye, default plant modules were used.Oil radish was simulated using a plant module calibrated in an earlier investigation(Thorup-Kristensen et al., 1997). Winter rape was simulated using a modification of thesame plant module. Plant residues (AOM) were subdivided by simply allocating thewaters-insoluble C and N to AOM1 and the water-soluble C and N to AOM2 accordingto Table 1 (Muller et al., 1997).The modelling scenariosIn a first step, dry matter production of the modelled pea was fitted to the amountsof plant dry matter and plant N measured in the field before soil incorporation byrotavation. Simultaneously, the initial amount of Nmic was adjusted with respect to thecorrect simulation of Nmic during spring 1997 in the fallow treatment (Figure 3).In a second step, the plant modules for grass, rye, oil radish and winter rape werefitted to the amounts of plant dry matter and plant N before and after winter (Figure 2).Due to missing algorithms for winter killing, this process had to be simulated bymanually increasing leaf and root death rates during periods of very low temperature.MÜLLER ET AL. 17th WCSS, 14-21 August 2002, Thailand830-5Oil radish and winter rape died completely during winter. This was simulated by ashallow soil incorporation at the end of December 1996.No further adjustments have been done on the parameterisation of the soil organicmatter turnover.Figure 2 Amount of dry matter and N in the different catch crops before (shoot androot) and after winter (shoot only). Measured and model simulated values.Bars show standard errors.0.01.02.03.04.05.06.07.0Grass Oil Radish Rye W-Rapet dm ha-1Nov 1996, measuredNov 1996, simulatedMar 1997, measuredMar 1997, simulated020406080100120140160180Grass Oil Radish Rye W-Rapekg N ha-1Nov 1996, measuredNov 1996, simulatedMar 1997, measuredMar 1997, simulatedMÜLLER ET AL. 17th WCSS, 14-21 August 2002, Thailand830-6Figure 3 Mineral N (Nmin) and soil microbial biomass N (Nmic). Measured (diamonds)and model simulated values (lines). Bars show standard errors.oil radish020406080100120140Aug-96 Nov-96 Feb-97 May-97kg Nmin ha-1winter rape020406080100120140Aug-96 Nov-96 Feb-97 May-97kg Nmin ha-1oil radish100120140160180200220240Aug-96 Nov-96 Feb-97 May-97kg Nmic ha-1winter rape100120140160180200220240Aug-96 Nov-96 Feb-97 May-97kg Nmic ha-1mineral N (0 - 25 cm) soil microbial biomass N (0 - 25 cm)fallow020406080100120140Aug-96 Nov-96 Feb-97 May-97kg Nmin ha-1rye020406080100120140Aug-96 Nov-96 Feb-97 May-97kg Nmin ha-1ryegrass020406080100120140Aug-96 Nov-96 Feb-97 May-97kg Nmin ha-1fallow110130150170190210230250Aug-96 Nov-96 Feb-97 May-97kg Nmic ha-1rye110130150170190210230250Aug-96 Nov-96 Feb-97 May-97kg Nmic ha-1ryegrass100120140160180200220240Aug-96 Nov-96 Feb-97 May-97kg Nmic ha-1MÜLLER ET AL. 17th WCSS, 14-21 August 2002, Thailand830-7Results and DiscussionFallow treatmentIt was possible to simulate dry matter and N in the above ground plant material ofpea (data not shown). This was an important prerequisite for the model simulation of thefollowing period in the different modelling scenarios.In the fallow treatment, simulated soil microbial biomass N was in the correct orderof magnitude during spring 1997 (Figure 3). However, it was not possible to simulatethe doubling of Nmic and Nmin within the first three sampling dates after rotavation(Figure 3). This may be due to the fact, that DAISY does not include algorithms for thesimulation of organic matter mobilisation by soil tillage.Catch crop treatmentsAs shown in Figure 2, simulated dry matter and N in the catch crops was in thecorrect order of magnitude both before and after winter. It was decided to accept slightover or underestimations without further modifications of the plant modules.The DAISY model underestimated Nmin in April and May 1997 in the rye andryegrass treatments. In addition, the model was not able to simulate the early increase ofNmic correctly. Simulated Nmic-peaks appeared too late (rye and ryegrass) and were tolow (all treatments except ryegrass). The observations indicate, that the turnover ofwinter killed plant material began earlier and happened faster in the field than predictedby the model.Winter killed plant material remained at the soil surface. It was visible in the field,that decomposition of these plant residues began during late winter and early spring. Inthe DAISY model however, plant material is decomposing only after incorporation intothe soil, which means after rotavation 2 April 1997. As a result, the turnover of rye andryegrass residues was initiated too late. Bio-incorporation of plant residues as simulatedby the DAISY model could not compensate for this shortcoming.In the winter rape and oil radish treatments, the early increase of Nmin wassimulated satisfactorily. Here, the complete dying of the plants during winter wassimulated by shallow soil incorporation at the end of December 1996. This enabled theDAISY model to initiate the turnover of the plant residues earlier.Another aspect may explain late simulated decomposition: The current DAISYtemperature modifier reduces the turnover rates of the organic matter pools at 5ºC toonly 25% of the rates at 20ºC. Below 0ºC, turnover rates are zero. This is in contrast toMagid et al. (2001) who showed that disproportionately high N-mineralisation ratesfrom green manures can occur at low temperatures which may have implications formodeling in cool temperate agro-ecosystems.A further explanation may be the simple subdivision of the plant residues (AOM) inwaters-insoluble C and N (AOM1) and water-soluble C and N (AOM2). Mueller et al.(1998) suggested that a considerable part of the water-insoluble C and N deriving fromgreen plant materials may be easily decomposable and should be allocated to AOM2.Except for the ryegrass treatment, the measured Nmic-peaks in early spring weremore pronounced than the simulated peaks. This indicates a preliminary microbialincorporation of AOM-N followed by a fast release of N from the Nmic-pool. Ifassuming, that this release leads to net N mineralisation, model predictions of Nminshould have failed in the same order of magnitude as release of N from Nmic occurred.MÜLLER ET AL. 17th WCSS, 14-21 August 2002, Thailand830-8However, the difference between measured and model simulated values was bigger forNmic than for Nmin. Hence, a part of the N released from microbial biomass must haveremained as microbial residues protected against mineralisation (Mueller et al., 1998).Denitrification as a possible sink for N was not measured in the field and it is thereforean uncertainty in our considerations. This point needs further attention in laterinvestigations.At the last sampling date in the oil radish treatment, the decay of simulated Nmic ledto an ongoing simulated N-mineralisation in the model simulations. During this periodmeasured Nmin and Nmic remained fairly constant. Simulated Nmin clearly exceedsmeasured Nmin. To some extend, this is also visible in the other treatments. Obviously,soil microbial biomass returns to a steady state earlier in the field than simulated by themodel.The differences between the four catch crop treatments can not be explained by theproperties of the plant materials measured before soil incorporation (Table 1). Asmentioned above, considerable parts of the plant residues decomposed before samplingin April 1997. Hence, the data shown in Table 1 may not reflect the properties of theoriginal plant residues. This may also have led to a partly wrong subdivision of AOM.ConclusionThe DAISY model was able to simulate mineral N after incorporation of catch cropplant residues to some extend only. The following processes need further attention andmay be integrated into the DAISY model:•  Soil tillage induced mobilisation of organic matter which can mobilise considerableamounts of organic N•  Winter killing of sensitive plant species and varieties•  Decomposition of plant residues at the soil surface as occurring after winter killing•  Decomposition of easily decomposable plant residues at low temperatures•  Soil microbial residues as an organic pool temporarily protected against turnover•  Furthermore, reliable criteria for the subdivision of green plant residues (AOM)into AOM1 and AOM2 have to be developed.AcknowledgementsThis study has been financed by the Danish Agricultural Research Centre forOrganic Farming under the NICLEOS project and by the Danish University Consortiumon Sustainable Land Use and Natural Resource Management (DUCED-SLUSE).ReferencesAbrahamsen, P. and S. Hansen. 2000. Daisy: an open soil-crop-atmosphere systemmodel. Env. Modelling Softw. 15:313-330.Brookes, P.C., A. Landman, G. Pruden and D.S. Jenkinson. 1985. Chloroformfumigation and the release of soil nitrogen: a rapid direct extraction method tomeasure microbial biomass nitrogen in soil. Soil Biol. Biochem. 17:837-842.Cabrera, M.L. and M.H. Beare. 1993. Alkaline persulfate oxidation for determiningtotal nitrogen in microbial biomass extracts. Soil Sc. Soci. Am. J. 57:1007-1012.Hansen, S., H.E. Jensen, N.E. Nielsen and H. Svendsen. 1990. DAISY-Soil PlantAtmosphere System Model. NPo-forskning fra Miljøstyrelsen, Vol. A10. Miljøstyrelsen, Copenhagen. 272 p.MÜLLER ET AL. 17th WCSS, 14-21 August 2002, Thailand830-9Hansen, S., H.E. Jensen, N.E. Nielsen and H. Svendsen. 1991. Simulation of nitrogendynamics and biomass production in winter wheat using the Danish simulationmodel DAISY. Fert. Res. 27:245-259.Joergensen, R.G. and T. Mueller. 1996. The fumigation-extraction method to estimatesoil microbial biomass: calibration of the kEN value. Soil Biol. Biochem. 28:33-37.Keeney, D.R. and D.W. Nelson. 1982. Nitrogen-inorganic forms, pp. 643-698. In A.L.Page (ed.). Methods of Soil Analysis. ASA, Madison.Magid, J., O. Henriksen, K. Thorup-Kristensen and T. Mueller. 2001.Disproportionately high N-mineralisation rates from green manures at lowtemperatures-implications for modeling and management in cool temperate agro-ecosystems. Plant and Soil 228:73-82.Mueller, T., L.S. Jensen, J. Magid and N.E. Nielsen. 1997. Temporal variation of C andN turnover in soil after oilseed rape straw incorporation in the field: simulationswith the soil-plant-atmosphere model DAISY. Ecol. Modelling. 99:247-262.Mueller, T., J. Magid, L.S. Jensen and N.E. Nielsen. 1998. Soil C and N turnover afterincorporation of chopped maize barley straw and blue grass in the field: evaluationof the DAISY soil-organic-matter submodel. Ecol. Modelling 111:1-15.Thorup-Kristensen, K. 2001. Are differences in root growth of nitrogen catch cropsimportant for their ability to reduce soil nitrate-N content, and how can this bemeasured? Plant and Soil 230:185-195.Thorup-Kristensen, K., T. Müller and J. Magid. 1997. Cover crops and nitrogenmanagement-exploring limitations and the applicability of the DAISY model. InJ.J. Schröder (ed.). Long Term Reduction of Nitrate Leaching by Cover Crops.Second Progress Report of the EU Concerted Action (AIR3) 2108, Wageningen,NL.

Alkaline persulfate oxidation for determining total nitrogen in microbial biomass extracts.

Are differences in root growth of nitrogen catch crops important for their ability to reduce soil nitrate-N content, and how can this be measured? Plant and Soil

Chloroform fumigation and the release of soil nitrogen: a rapid direct extraction method to measure microbial biomass nitrogen in soil.

Cover crops and nitrogen management-exploring limitations and the applicability of the DAISY model.

DAISY-Soil Plant Atmosphere System Model. NPo-forskning fra Miljøstyrelsen, Vol.

Daisy: an open soil-crop-atmosphere system model.

Disproportionately high N-mineralisation rates from green manures at low temperatures-implications for modeling and management in cool temperate agroecosystems.

Nitrogen-inorganic forms,

Report of the EU Concerted Action (AIR3) 2108,

Soil C and N turnover after incorporation of chopped maize barley straw and blue grass in the field: evaluation of the DAISY soil-organic-matter submodel.

Temporal variation of C and N turnover in soil after oilseed rape straw incorporation in the field: simulations with the soil-plant-atmosphere model DAISY.

The fumigation-extraction method to estimate soil microbial biomass: calibration of the kEN value.

Catch Crops in Organic Farming Systems without Livestock Husbandry - Model Simulations

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Catch crops in organic farming systems without livestock husbandry-model simulations

Catch Crops in Organic Farming Systems without Livestock Husbandry - Model Simulations

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