European Journal of Agronomy 10 (1999) 129–144
Azodyn: a simple model simulating the date of nitrogen deficiency for decision support in wheat fertilization M.-H. Jeuffroy a,*, S. Recous b a Unite´ d’Agronomie, INRA-INA PG, BP 01, 78 850 Thiverval-Grignon, France b INRA Unite´ d’Agronomie, rue Fernand Christ, 02 007 Laon, Cedex, France Accepted 9 December 1998
Abstract A dynamic soil–crop model was developed to predict the date on which N deficiency occurs for winter wheat crops in the temperate climate of Northwest Europe. It is based on the daily simulation of soil N supply and crop N requirement for the period during which N-fertilizer is usually applied to wheat crops, the end of winter until flowering. The soil sub-model was derived from the ‘balance-sheet method’ used in France for nitrogen fertilization recommendations. It describes the net mineralization of various sources of organic matter (soil humus, crop residues, organic products). The crop sub-model simulates crop biomass production and its nitrogen content using a radiation use efficiency model and a critical dilution curve for nitrogen content. Both soil and crop sub-models require few parameters and inputs, most of which are readily available on commercial farms, together with daily climatic data. The model tested with various rates and timings of N application in three experiments accurately simulated the date on which nitrogen deficiency began in wheat crops. The interest in using the model for tactical and strategic approaches is discussed. © 1999 Elsevier Science B.V. All rights reserved. Keywords: Azodyn; Fertilization; Model; N balance method; Nitrogen; Plant N requirement; Soil N supply
1. Introduction Environmental constraints are forcing farmers in Western Europe to be increasingly precise in determining the rate and date of nitrogen fertilizer application to crops. It has been clearly demonstrated for various crops and soil conditions in temperate climates that optimal rates of N application minimize the residual levels of N in the soil when the crop is harvested and reduce potential fertilizer losses to the environment (MacDonald * Corresponding author. Tel.: +33 1-30-81-55-36; fax: +33 1-30-81-55-64; e-mail
[email protected]
et al., 1989). Moreover, the crop uses nitrogen fertilizer more efficiently if the dates of N application match the crop N requirements (Powlson et al., 1992; Strong, 1995; Recous et al., 1997). Consequently, several methods have been developed to improve fertilization practices and to minimize excess N application (e.g. Piekielek et al., 1995; Justes et al., 1997). They generally involve the application of a small amount of nitrogen fertilizer during tillering of wheat and measurement of the N status of the crop during the crop cycle. If the crop is found to be deficient in nitrogen, additional N fertilizer is applied. Several indicators have been suggested for determining the
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N status of the crop, including the nitrate content of the stem base extracts (Papastylianou et al., 1982; Scaife and Stevens, 1983; Justes et al., 1997), leaf reflectance or transmittance (Benedict and Swilder, 1961; de Rosny et al., 1995) and the chlorophyll content of leaves ( Yadava, 1986). However, these methods require several crop measurements to be taken. This is time-consuming for the farmer and may limit their use, particularly at a time when the agricultural labour force is decreasing. Numerous mechanistic crop models, simulating the dynamics of crop nitrogen requirements and nitrogen supply in the soil, have been developed in recent years (e.g. de Willigen, 1991). Such models should be able to determine accurately the periods of N stress for the crop. Simplified software derived from models should help farmers determine the critical periods and the optimum timing of nitrogen fertilizer application, as was the case for pesticide application (e.g. Thornton and Dent, 1984; Zadoks, 1989). However, mechanistic models include numerous parameters for both soil (water and N transformations) and crop submodels. These parameters may vary with environmental conditions and are often difficult to estimate. Moreover, they often require numerous input data that are rarely available on commercial farms. Simulation models for wheat crops describe crop growth and N uptake well, but most poorly describe soil mineral N content, mostly overestimating soil N content (de Willigen, 1991). Fixation of fertilizer N in clay-lattices, microbial immobilization and gaseous losses have been blamed for the losses of soil mineral N and the differences between the observed and simulated data, depending on the model and the dataset considered (Addiscott et al., 1991a; Groot and de Willigen, 1991; Hansen et al., 1991; Kerserbaum and Richter, 1991; Otter-Nacke and Kuhlmann, 1991; Whitmore et al., 1991). It has often been concluded that the models should include additional functions to simulate more accurately the soil processes occurring after fertilizer-N application. Alternatively, further model development, for decisionmaking in fertilizer application, should focus on developing or improving simple models, as
suggested by Addiscott et al. (1991a) and Angus (1995). The balance-sheet method, a simple static model, was developed in France for calculating N rates for application to cereal and other crops (Re´my and He´bert, 1977). It involves evaluating the total N requirements for a given crop with a particular target yield, and the total soil N supply during the crop cycle. The difference between the requirement and soil supply is the amount of N that must be supplied by fertilizer application to obtain the target yield. Soil N supply includes the residual mineral N still in the soil after winter and the soil organic N mineralized between the end of winter and harvest (Laurent and Mary, 1992). The target yield is usually defined as the maximum yield obtainable on the field concerned ( Viaux, 1980; Meynard and Limaux, 1987; Machet et al., 1990). This method has already been evaluated in a wide range of environmental conditions and is widely used for fertilization management in France because it is robust (Meynard et al., 1981, 1997; Re´my and Viaux, 1982; Meynard, 1995). Our aim was to develop a dynamic version of the balance-sheet method, Azodyn, with no substantial increase in the number of input data and parameters involved, in order to benefit from the predictive ability, the simplicity of use and the robustness of the static method. This new dynamic balance-sheet must be able to simulate the date on which N deficiency will occur in a wheat crop, for various dates and rates of N-fertilizer application. As the static version of the model has already been validated (Meynard et al., 1981; Re´my, 1981; Taureau, 1987), evaluation of Azodyn will focus on its specificity, that is its ability to predict the beginning of N deficiency for a large range of N-fertilizer application dates.
2. Materials and methods 2.1. Description of the model 2.1.1. Soil sub-model The soil sub-model [Fig. 1(a)] is based on the balance-sheet method, developed in France in the 1980s (Re´my and He´bert, 1977; Re´my and Viaux,
M.-H. Jeuffroy, S. Recous / European Journal of Agronomy 10 (1999) 129–144
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Fig. 1. Flow charts of the simulation model of daily plant nitrogen requirements (a) and daily soil nitrogen availability (b). M =net mineralization of humus; M =net mineralization of crop residues; M =net mineralization of organic wastes; e =fraction h r a i of incident radiation intercepted by the crop; e =radiation use efficiency; e and k=maximum e and extinction coefficient; b imax i LA/BM=ratio of leaf area over total aerial biomass; boxes in grey=sub-model input.
1982), and used to calculate fertilizer N recommendations for the whole period from the end of winter (initial date) until harvest (final date). This method has been further developed in the Azobil software (Machet et al., 1990, 1991; Meynard et al., 1997). The balance-sheet method involves calculating the rate of fertilizer-N application (X ) based on crop N requirements and the changes in soil mineral N content between the initial and the
final dates of the balance-sheet, with the equation: X=(P −P )−(R −R +M +M +M −L), f i i f h r a (1) where P and P are the amounts of N accumulated i f in the crop at the initial and the final dates, respectively. (R −R +M +M +M −L) desi f h r a cribes the net availability of soil mineral N. R i
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and R are the initial and final amounts of residual f inorganic N in the soil, respectively, at the end of winter and at harvest. M is the net mineralization h of soil humus, M the net contribution of crop r residues, M the net contribution of organic wastes a and L the amount of nitrate leaching, estimated for the whole period. This equation assumes that: (1) deposition of N from the atmosphere (nonsymbiotic fixation, wet and dry deposition) is equal to gaseous emissions (volatilization, denitrification), which explains why these two terms do not appear in the equation; and (2) the net contributions of the various sources to mineralization (humus, crop residues, organic wastes) are evaluated separately before they are accumulated, which means that there is no interaction between the various processes (e.g. date of measurement of R and M ). i r The amount of N mineralized (kg ha−1 day−1) is calculated as (Meynard et al., 1997): M =k SW [N ]b, (2) h 2 where SW is the soil weight in the ploughed layer (kg ha−1), [N ] the total N content (‰ soil weight), and b is a coefficient accounting for the fact that additional N is mineralized from soil below the ploughed layer. In this model, b=1.3 (Meynard et al., 1997). The coefficient k (unitless), which affects the 2 total N content of the ploughed layer, depends on clay and carbonate content and is set at a mean annual air temperature of 10°C (Mary and Gue´rif, 1994): 3.287f s exp[(a(T−10)], k = 2 (Clay+200) (0.3 CaCO +200) 3 (3) with a the temperature coefficient equal to 0.115 (Recous, 1995), T the mean daily air temperature, and the clay and CaCO contents are soil inputs 3 expressed in ‰ of soil weight. The parameter f , s which also affects k , takes into account the history 2 of the plot, such as the long-term effect of crop residue management, organic wastes application and set-aside periods (Meynard et al., 1997). The values given for M and M terms cover the r a
net contribution of crop residues and organic product application during the period from mid winter to harvest time. All parameters of the soil sub-model have been previously set locally in a large range of situations (Machet et al., 1990, 1991). The daily net mineralization of crop residues and organic waste applications (M and M ) r a are estimated from the values of total net mineralization during spring given in Azobil (Machet et al., 1991) and distributed throughout the period of the simulation, according to the mean daily temperature. The value for R (residual N in soil at i the beginning of the simulation) is input into the model from soil measurements at the end of winter. Soil mineral N content increases each day due to the net mineralization of humus, crop residues and organic wastes, and to any inorganic N-fertilizer applied on this day. It decreases due to the plant taking up its N requirement, as calculated from the plant sub-model. The model assumes that all N-fertilizer is available to the crop. There is no mineralization when the daily air temperature is at or below 0°C. The leaching of nitrate is considered to be negligible during the spring under cereal crops, as demonstrated by numerous 15N experiments under cropping systems and climate similar to ours (Addiscott et al., 1991b). Thus, N leaching is not included in the model. The model assumes that a constant amount of soil mineral N is not available to the roots (20 kg N ha−1 over the whole soil profile) and is subtracted from total soil mineral N, as observed in previous studies (Recous et al., 1988, 1992) and in other models such as Sundial (Bradbury et al., 1993). The soil model starts on the date on which soil residual mineral N is measured. 2.1.2. Plant sub-model The plant sub-model [Fig. 1(b)] simulates the daily N requirements of the crop, by estimating dry matter biomass production, according to Monteith’s analysis (Monteith, 1972, 1977), and from the changes in the critical nitrogen content of the aerial parts of the crop (Justes et al., 1994). Biomass production is calculated cumulatively for each day starting from the initial crop aerial biomass (input) measured on the date of measurement of residual mineral N in the soil after winter.
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Biomass is based on the radiation intercepted by the crop, and the radiation use efficiency (e , b defined as the ratio of cumulative aerial biomass to intercepted radiation, and expressed in g BM MJ−1), with the formula (Gosse et al., 1986): BM =BM +(e e PAR , (4) d d−1 b id id where BM and BM =cumulative aerial biod d−1 mass from the initial date until day d and day d−1, respectively (kg ha−1), e =ratio of id intercepted to incident radiation on day d (unitless), and PAR =incident photosynthetically id active radiation on day d (MJ m−2). The radiation use efficiency, e , is essentially b constant for the vegetative part of the cycle (Gosse et al., 1986) if there is no water stress, nitrogen deficiency, pests or diseases. For wheat, several values of e between 1.09 and 3.8 have been b reported, differing according to the method by which intercepted radiation was measured (Gosse et al., 1986), the cultivar (Siddique et al., 1989; Yunusa et al., 1993), or by the introduction of the effect of temperature on e into the model (Brisson b et al., 1998). We used e =2.8, based on previous b measurements on several crops, for the cultivar Soissons (data not published). PAR is readily calculated from daily global id incident radiation (Rg ), with Rg measured at the d d nearest climatic station: PAR =0.48Rg (5) id d ( Varlet-Grancher et al., 1982). As shown for a large number of species, variations of e with time are closely linked to the id changes in the daily leaf area index (LAI ) of the d crop ( Varlet-Grancher, 1987): e =e (1−exp−kLAId ), (6) id imax with e and k, parameters varying according to imax species (Gosse et al., 1986), and possibly to cultivar, because they depend on the leaf angle distribution ( Varlet-Grancher, 1987). We estimated e imax to be 0.96 and k to be 0.72 for the wheat cultivar Soissons (Girard and Jeuffroy, 1994). LAI was calculated every day from the total aerial biomass, taking the ratio of leaf area to plant biomass (LA/BM ) as a constant of
6.10−3 m2 g−1, until LAI reached 4. Above this threshold, we assumed that e was at its maximum id and did not change further until anthesis. The ratio of leaf area to plant biomass was found constant only for the beginning of the growth cycle, its variability later in the cycle being due to senescence, leaf drop and diseases (Aase, 1978). This ratio must vary with crop density but, as we evaluated the model only for high crop densities, we used only one value for this ratio. We calculated the initial LAI based on the initial crop aerial biomass measured at the end of winter. Daily calculations were then made [Fig. 1(a)], resulting in the simulation of daily biomass accumulation. Crop N requirement can be expressed as the minimum amount of N accumulated in the crop that yields maximum biomass ( Ulrich, 1952). The minimum amount of N accumulated in the aerial parts of the crop (N ) is then calculated as the a product of maximum biomass (BM, simulated as described previously) and the critical N concentration (N ) of the aerial parts, as described by ct Justes et al. (1994): N =10BMN , (7) a ct where N =N if BM
