CERES-BEET, A MODEL A MODEL FOR THE PRODUCTION AND ENVIRONMENTAL IMPACT OF SUGAR-BEET
/ CERES-
BETTERAVE, UN MODÈLE DE PRÉDICTION DE LA PRODUCTION ET DES IMPACTS ENVIRONNEMENTAUX DE LA BETTERAVE B. LEVIEL1, C. CRIVINEANU 2, B. G ABRIELLE1,* 1: Institut National de la Recherche Agronomique, Unité Mixte de Recherche Environnement et Grandes Cultures, Thiverval-Grignon, France. 2 : Université des Sciences Agronomiques et de Médecine Vétérinaire, Bucarest, Roumanie * corresponding author (E-mail :
[email protected])
ABRÉGÉ Dans le cadre d’un projet Européen concernant l’environnement dans l’agriculture de la plaine du Danube, un modèle de type CERES a été élaboré pour la betterave à sucre. CERES est une famille de modèles déterministes de fonctionnement du système sol-plante- atmosphère, disponibles pour un grand nombre de cultures. La version utilisée dans ce travail a été adaptée plus spécifiquement à la prédiction des impacts environnementaux liés à l’utilisation d’engrais azotés. L’une des premières étapes dans l’adaptation a consisté à développer un modèle d’indice foliaire, dont l’originalité est d’être basé sur une modélisation du développement des feuilles individuelles. Le modèle a été développé et testé sur des jeux de données expérimentales obtenues sur plusieurs années, et en deux endroits (Grignon et Bucarest). Une fois calé sur les données d’une année à Grignon, le modèle a donné de bons résultats en ce qui concerne les dynamiques d’indice foliaire et d’accumulation de matière sèche totale. Ainsi intégré à la famille CERES, le modèle développé pour la betterave peut ensuite être appliqué à un certain nombre d’analyse : prédiction des pertes en nitrates et des émissions gazeuses associées (ammoniac, oxydes Proceedings of the joint colloquium on Sugar Beet Growing and Modelling, September 12th, 2003, Lille (F)
d’azote, gaz à effet de serre), intégration dans une démarche d’analyse de cycle de vie, analyse des risques de pollution liés à différentes pratiques agricoles (rotations, fertilisation azotée, irrigation, choix des dates de semis ou des variétés, etc…) Nous montrons ici quelques résultats généraux sur ce type d’études, et un cas particulier obtenu sur les risques de pertes en nitrate dans la plaine du Danube. Cette étude par simulation montre l’effet de l’introduction de la betterave dans les rotations céréalières, et permet de donner des recommandations pour la conduite de la fertilisation azotée.
SUMMARY
IIRB translation
Proceedings of the joint colloquium on Sugar Beet Growing and Modelling, September 12th, 2003, Lille (F)
INTRODUCTION Mechanistic soil-crop models are a powerful and sometimes exclusive tool to investigate the effect of management practices on the productivity or environmental impacts of arable crops. Because they simulate the major physical and biological processes occurring in these systems, they may in principle be extrapolated to climatic conditions, soil types or cropping systems other than those on which they have been developed and tested. As a consequence, they may be used to approach the effects of climate variability, when run on long sequences of past or generated weather data, or to provide recommendations as regards fertiliser use or irrigation. The CERES models (e.g., Jones and Kiniry, 1986) provide a simple and coherent framework for the simulation of the water, carbon and nitrogen cycles in soil-plant systems. Over the past twenty years, they have been widely used and tested in applications ranging from decision-aid in irrigation to global assessment of crop productivity (Rosenzweig and Parry, 1994). Although they now exist for a number of crops (including for instance wheat, barley, oilseed rape, maize, sorghum and sunflower), no version for sugar- beet have been reported to date. In the context of a research project dedicated to the environmental impacts of agriculture in the Romanian Danubian plain (Gosse et al., 1999), we developed a CERES-type model for sugar- beet. Compared to other sugarbeet models such as SUCROS (Guérif & Duke, 1998) or the Jaggard & Werker (1999) model, the resulting model has several original features (Gabrielle et al., 2002). It can simulate the succession of crops on a given field, and thus account for crop rotation effects. It is environmentallyoriented, and predicts the field emissions of relevant compounds, whether gaseous or leaching (including ammonia, nitrous oxide, nitrate, and soilcrop carbon balance). Lastly, its approach to the development of leaf area is based on the simulation of individual leaves. In this paper we thus present the development and testing of the CERESBeet model, which involved two data sets: one from France, and the other from Romania.
1.- MATERIAL AND METHODS
Proceedings of the joint colloquium on Sugar Beet Growing and Modelling, September 12th, 2003, Lille (F)
1.1.- Field trials Experiments were carried out in two locations: Grignon (Northern France) for model development and calibration, and Bucharest (Romania) for independent testing. The Bucharest experiments took place in 1997 and 1998 at the University of Agronomic Sciences, on a reddish- brown forest soil whose main characteristics are a silt-clay texture (38 % clay), and a pH of 6.8. The wilting point and the field capacity moisture contents were estimated at 13 % and 25 % (v/v), respectively. In this region, the climate is continental, with average temperatures are -1.2°C in winter, 10.4°C in spring and autumn and 21.3°C in summer. The average rainfall is 550 mm in the year with a maximum of 78 mm / m onth in May and June. Sugar- beet (cultivar Emma) was sown on 29 April, 1997 and 4 April, 1998. The experiment included three nitrogen treatments (0, 150 and 300 kg N / ha) with and without irrigation in order to obtain data sets under limiting and non- limiting conditions. The treatments are referred to as N0irr, N0dry, N150irr, N150dry, N300irr and N300dry. Each treatment involved a five 42 m² replicate plots comprising 14 rows of crop, with an inter-row distance of 50 cm. Crops were sampled every other week, over an area of 1 m 2 in each replicate plot. Plants were analysed for fresh and dry weight, in their various organs (tap root, leaves), along with their N content (Dumas method). Leaf area was estimated every 10-12 days, with the following relation: S = K (L*l) where S is the blade surface of an individual leaf (cm²), L its length (cm), l its maximum width (cm), and K the Kvêt (1966) coefficient depending on the crop. It was calibrated from direct measurements using planimetry at 0.77 (R2=0.965; Leviel, 2000). Upon harvest in October, quality analyses were performed on root sugar content. The Grignon experiment was similar to that of Bucharest, and took place in 1998 on a silty clay loam. Treatments included rainfed and irrigation variants, combined with two levels of fertilisation (0 and 150 kg N / ha). The soil in Grignon is a brown earth, with a silty clay loam texture. The same variety 'Emma' was used, as well as the same depth and density of sowing, on April 1, 1998. Harvest occurred on November 15, 1998.
1.2.- Modelling concepts The model is detailed in Leviel (2000). Briefly, the phenology module considers four events: sowing, germination, emergence, and harvest. Proceedings of the joint colloquium on Sugar Beet Growing and Modelling, September 12th, 2003, Lille (F)
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Germination is a function of soil moisture content, and emegence occurs after 40 Growing Degree Days, with a base temperature of 3°C (noted GDD 3). Harvest date is set manually by the user.
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Figure 1. Expansion kinetics of leaf number i. Si is the maximum area reached by the full-grown leaf, and the x-axis is termal time in growing degree days (base temperature: 3°C). The simulation of crop leaf area is based on the growth of individual leaves, whose expansion is driven by thermal time, with a leaf appearance rate of 39 GDD 3. Figure 1 shows the various phases of leaf growth, under non- limiting conditions. Stress factors apply should water or nirogen deficit occur (see end of paragraph). Net photosynthesis is computed from intercepted photosynthetically active radiation (PARi) by means of a radiation use efficiency set to 2.8 g Dry Matter /MJ PARi. PARi is computed from leaf area index using the classical Beer-Lambert law of radiation transmission in turbid media. The extinction coefficient it set to 0.65. Throuhout the growing season, photosynthates are primarily partitioned to the leaves. The latter are made up of sheaths and blades compartments, with blades DM demand calculated from potential leaf area growth assuming a specific leaf area of 50 g DM / m 2. Leaf sheaths DM demand represent 80% of leaf blades demand. After partiotioning to the leaves, 85% of the remaining dry matter is allocated to the roots (including the tap root), while the last 15% are allocated to the crown. In practice, leaf area ceases growing after 1500 GDD 3, so that the tap root becomes the main DM sink thereafter. Final marketable sugar yield is calculated from total root dry matter assuming that 95% of root DM is harvested, and that roots have a 82% moisture content, and a sugar content of 14% on a fresh weight basis.
Proceedings of the joint colloquium on Sugar Beet Growing and Modelling, September 12th, 2003, Lille (F)
Lastly, crop N uptake is computed through a supply / demand scheme, with soil supply depending on soil nitrate and ammonium concentrations and root length density. Crop demand is a function of the distance between actual and critical nitrogen content in the aerial and below- ground tissues. Critical nitrogen is defined as the optimum concentration for biomass production, as evidenced from field studies for various crops. It a decreasing power function of crop dry matter. Here we used the Greenwood et al. (1990) general parameterization for C 3 crops, as presented in Figure 2. Water and nitrogen stress affect both leaf area growth and, to a lesser extent, net photosynthesis. They are expressed as unitless 0 to 1 coefficients which are combined to reduce potential growth rates. N stress coefficients are based on the Nitrogen Nutrition Index, which is the ratio of actual N concentration in aerial biomass to a critical N content which is optimal for biomass growth. Water stress coefficients are calculated from the ratio of actual to potential plant transpiration.
Figure 2. Critical N curve (solid line) used in the N uptake and stress modules of CERES-Beet, from Greenwood et al. (1990). The symbols refer to the experimental data from the various treatments of the Bucharest 1998 experiment.
2.-
RESULTS AND DISCUSSION
Figures 3 to 5 present the simulation of crop leaf area index, total dry matter and its partitioning under potential conditins for the two years of Proceedings of the joint colloquium on Sugar Beet Growing and Modelling, September 12th, 2003, Lille (F)
experiment in Bucharest. They show reasonable model performance whether in 1997 or 1998. Whereas the total number of leaves was well predicted in both years, leaf senescence was slightly anticipated in 1997, and more strongly in 1998. Total dry matter is over-estimtated in both years in the first half of the growing season, which points to a bias in the calculation of intercepted radiation for low values of LAI. As a consequence, partitioning to the roots was over-estimated until harvest when final root dry matter was correctly predicted (Figure 5). Accordingly, simulated sugar yields were also correct in both years. Unfortunately, the full test of CERES under water- or nitrogen- limiting conditions has not been carried out to this date, althouth the experiments were designed for it. The only results obtained regarding these treatments involve the simulation of total extractable soil water over the root zone in the rainfed treatments(Figure 6). They show good predictions of soil water dynamics under these dry conditions. CERES was subsequently applied to analyse various agronomical scenarios, to produce recommendations to mitigate the environmental impacts of agriculture in the Danubian plaine (Gosse et al., 1999). Table 1 compares the introduction of sugar- beet or maize in a wheat /s unflower based rotation. It shows that whereas wheat yields are similar in both rotations, sunflower yields improve in the rotation including sugar- beet. However, the latter induces extra nitrate leaching, occurring during the period between the harvest of the proceeding wheat and the sowing of sugar- beet. Better management of this period (eg through the use of catch crops) may mitigate this drawback, and CERES would be helpful in such an analysis.
CONCLUSION Although further tests appear indispensable under more stringent growing conditions, and in other pedo- climatic conditions, the CERES model presented may be used to simulate the growth and development of sugarbeet, as well as the dynamics of water and nitrogen in the soil profile. Some improvements should also be sought in the simulation of total dry matter in early growth, and in the N uptake and partitioning routine. Once the model will have been further verified along these lines, it may be used in combination with the other CERES crop models, whereby it will Proceedings of the joint colloquium on Sugar Beet Growing and Modelling, September 12th, 2003, Lille (F)
benefit from the support from the international community of CERES users and developers. As formalized in the International Consortium on Agricultural System Applications network (www.icasa.net), it provides worldwide soil and climate data bases, standardized experimental data sets, improvement of existing modules and addition of new capacities.
Proceedings of the joint colloquium on Sugar Beet Growing and Modelling, September 12th, 2003, Lille (F)
Figure 3. Simulated (lines) and observed (symbols) time course of leaf area index (left) and leaf number (right) in the Bucharest 1997 and 1998 trials (N300irr treatment with irrigation and ample N supply).
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Figure 4. Simulated (lines) and observed (symbols) time course of total crop dry matter in the Bucharest 1997 and 1998 trials (N300irr treatment with irrigation and ample N supply). Proceedings of the joint colloquium on Sugar Beet Growing and Modelling, September 12th, 2003, Lille (F)
Figure 5. Simulated (lines) and observed (symbols) dry matter partitioning in the Bucharest 1998 trial (N300irr treatment with irrigation and ample N supply).
Figure 6. Simulated (lines) and observed (symbols) time course of plant extractable water in the 1997 Bucharest trial (N300dry treatment, rainfed with ample N supply).
Proceedings of the joint colloquium on Sugar Beet Growing and Modelling, September 12th, 2003, Lille (F)
Table 1. Crop yields, water drainage and nitrate leaching simulated by CERES over two different crop rotations: a sunflower-wheat-sugar beet-wheat rotation (top), and a sunflower-wheat-wheat- maize rotation (bottom table), in Fundulea (N Romania). The same climatic year was repeated throughout the simulation, which starts in year 0, and ends in year 5 or 6. The various fluxes reported are cumulated over either the cropping period considered, or from the onset of the rotation.
REFERENCES 1.
GABRIELLE B., ROCHE R., ANGAS P., CANTERO-MARTINEZ C., COSENTINO L., MANTINEO M., LANGENSIEPEN M., HÉNAULT C., LAVILLE P., NICOULLAUD B. & GOSSE G.: A priori parameterisation of the CERES soil-crop models and tests against several European data sets, Agronomie, 22, 119-132, 2002. Proceedings of the joint colloquium on Sugar Beet Growing and Modelling, September 12th, 2003, Lille (F)
2.
GOSSE, G., et al. (13 authors), Evaluation of risks and monitoring of nitrogen and pesticides fluxes at the crop level on the Romanian and Bulgarian plain, Final report, EU COPERNICUS Project IC15CT960101, 1999.
3.
GREENWOOD, D.J., LEMAIRE, G., GOSSE, G., CRUZ, P., DRAYCOTT, A. & NEETESON, J.J.: Decline in the percentage N of C3 and C4 crops with increasing plant mass, Annals of Botany, 66, 425436, 1990.
4.
GUERIF, M. & DUKE, C.: Calibration of the SUCROS emergence and early growth module for sugar-beet using optical remote sensing data assimilation, Eur. J. Agronomy, 9, 127-136, 1998.
5.
JAGGARD, K.W. & WERKER, A.R.: An evaluation of the potential benefits and costs of autumn sown sugar-beet in NW Europe, J. Agric. Sci. (Cambridge), 132, 91-102, 1999.
6.
JONES, C.A. & KINIRY, J.R.: CERES-N Maize: a simulation model of maize growth and development, Texas A&M University Press, College Station, Temple, TX, 1986.
7.
KVÊT, J., NECAS, J. & KUBÍN, Š.: Measurement of leaf area. Method of Studying Photosynthetic Production of Plants, Academia, Pragha, 315331, 1966.
8.
LEVIEL, B.: Evaluation of risks and monitoring of nitrogen fluxes at the crop level on the Romanian and Bulgarian plain. Application to maize, wheat, rapeseed and sugar-beet. Ph. D. dissertation, Institut National Polytechnique de Toulouse, 2000.
9.
ROSENZWEIG, C. & PARRY, M. L.: Potential impact of climate change on world food supply. Nature, 367, 133-138, 1994.
Proceedings of the joint colloquium on Sugar Beet Growing and Modelling, September 12th, 2003, Lille (F)