The Critical Nitrogen Curve for winter oilseed rape : determination and use as a diagnostic tool for crop nitrogen status
1 Institut Supérieur d’Agriculture de Lille, F59046 Lille cedex Colnenne@isa.fupl.asso.fr
2 Institut National de la Recherche Agronomique, F78850 Thiverval-Grignon, Meynard@jouy.inra.fr
Lemaire and Salette (1984) developed the concept of the critical N concentration in aerial biomass which corresponds, at any moment of vegetative growth, to the minimum concentration of N necessary to achieve maximum above ground biomass. This concentration is represented by a power equation : N = aW-b, where W is the total shoot biomass expressed in t/ha, N the total N concentration in shoot biomass expressed as a percentage of the shoot dry matter, and a and b positive constants. According to the different histological and morphological plant characteristics compartments (Lemaire and Gastal, 1987), it seems necessary to define the specific values of the critical N curve coefficients for each species. This has been done for grassland (Lemaire and Salette, 1984), wheat (Justes et al., 1994), maize and sorghum (Plenet and Cruz, 1997) ect… This critical N curve could be used to determine the plants’N requirements and to calculate the Nitrogen Nutrition Index (N.N.I.) which quantifies the nitrogen status of the plants (Lemaire et al., 1989).
Our objective is to present the methodology to obtain the specific critical N curve for winter oilseed rape and some utilizations of this diagnostic tool in agronomic data explanations.
1 Determination of the critical nitrogen curve specific for winter oilseed rape
1.1. Materials and methods
Three types of experiment were required to cover the development stages from emergence to flowering : the first one, in the early development stages, was carried out in controlled environment conditions, two other types of experiment, combining rosette growth and stem elongation, were conducted in the field during Autumn, and Spring respectively. In each experiment, several N fertilization treatments were spread, some supposed to be insufficient and others assumed to be non limiting for growth. The data collected regularly were the biomass and the total nitrogen concentration of the shoot parts.
1.2. Statistic determination of the critical N curve coefficients.
1.2.1. Methodology. This methodology, developed by Justes et al. (1994), consists of calculating theoretical critical points as presented in Figure 1. In one experiment and at one measurement date, a theoretical point is characterized by the maximum shoot biomass (mean of the higher shoot dry matter measured in non N limiting growth conditions : i.e. T4, T5, T6), and the total N concentration is obtained as the ordinate of the maximum shoot biomass in the simple linear regression defined with the data measured in the N limiting growth conditions (i.e.T1,T2,T3).
Following this computation method, 15 groups of field experimental data allowed us to calculate theoretical critical points. The critical N curve coefficients result from a bivariate regression (Dagnelie, 1975) to take into account both the variability of the shoot dry matter and the total N concentration. These curve coefficients are defined between 1.43 t/ha and 6.47 t/ha of shoot dry matter (cf. Figure 2). For low biomasses, i.e. in absence of light competition, the critical N value is a constant and it has been defined with the same methodology as presented before, with the controlled environment experiments measurements. This critical N value is 4.63 from 0.03 to 0.88 t/ha of shoot biomass.
Figure 1 : Determination of the thearetical critical point
1.2.2. Experimental validation of the critical N curve. We have validated this critical N curve in several pedoclimatic conditions with all the data not used to define the theoretical critical points. 142 situations characterized either as N limiting or non N limiting growth conditions were selected in the range of 0.1 to 6.9 t/ha, corresponding to stage 2 green leaves open (B2) to the beginning of flowering (F1). These two populations of points were well discriminated by the critical N dilution curve (cf. Figure 3).
Figure 3 : Validation of the nitrogen critical curve
Figure 2 : Nitrogen critical curve for winter oilseed rapee
2. Utilization of the critical N curve in agronomic data
2.1. N.N.I. : diagnostic tool of nitrogen status of crops.
To characterize the N status of crops, Lemaire et al. (1989) calculated the nitrogen nutrition index as : N.N.I. = Nt/Nc , where Nt is the total N concentration measured in the aerial parts and Nc the critical N concentration for the same biomass. For a N.N.I. equal to 1 the nutrition is considered as optimum, with higher values indicating N excess, and lower values N deficiency.
Three types of N.N.I. could be calculated : instantaneous N.N.I. characterizes punctual N status of crops, integrated N.N.I. characterize both its duration and its intensity. This second approach is more revelant than the first one because its expresses the kinetic of the N status of crops which is necessary to define the N requirement of plants.
2.2. Characterization of the N supply absorption by crops in agronomic experiments.
To study the consequences of the nitrogen, many experiments have been carried out with different quantities of N supply. The growth, development and yield elaboration were analysed according to the N supply levels and the conclusions were various because in no case the N status of crops, which ensures the N supply absorption, has been taken into account. For exemple, the conclusions were different about the effects of Autumn N supply. A complementary analysis of the N status of crops allowed us to understand the variability of these results, according to the mineral N absorption which depends on the temperature, the rain or the soil conditions. In Figure 4, we present the evolution of the shoot biomass in different pedoclimatic conditions, for two different Autumn N supplies. The data explanation is different when we analyse the growth according to the N supply, or according to the N status of crops. In the first situation, a same N supply has different effects on growth. On the contrary, in the second analysis (cf. Figure 4), the responses are homogeneous when we analyse the nitrogen status of crops (i.e. N.N.I.).
2.3. Analysis of the consequences of N deficiencies on growth.
2.3.1. Effects of nitrogen deficiencies on growth : ex L.A.I. Three experiments have been carried out in different pedoclimatic conditions with different N alimentation conditions. Regular shoot biomass, total nitrogen concentration in aerial parts, and L.A.I. measurements have been collected during the Autumn. We have defined a relation between the N.N.I. and the relative L.A.I. (cf. Figure 5 : r²=0.60) which describes the effects of N deficiencies on L.A.I.
The comparison with the fescue results, (cf. Figure 5) shows a higher L.A.I. decrease for the winter oilseed rape than for the fescue in N stress conditions. The same work have been conducted on shoot biomass and R.U.E.. These approaches allow to describe the effects of nitrogen deficiencies, precisely identified, on the different growth components. These studies explain the variability of the growth evolution between species. On the other hand, this knowledge could be used in different models such as CERES CECOL or AZODYN.
2.3.2. Optimising the management agricultural practices The evolution of the agricultural context has some consequences on the management of different cultural practices, and the N supply for winter oilseed rape competes specifically in Autumn with the potatoharvesting or maize ensilage, or in Spring with the protection or fertilization of cereals. The N.N.I. determination, in association with the measurement of the nitrate concentration in sap (like Jubil methodology on wheat : Justes et al., 1997) could define the best moment of a N supply for winter oilseed rape, with no or very small consequences on yield.
The critical N curve and the N.N.I. are revelant diagnostic tools of the N status of crops. They can be used in various pedoclimatic conditions, and allow to distinguish the effects of N deficiencies from the limiting N absorption climatic conditions. On the other hand, the knowledge about the effects of different N deficiencies on growth components could be used in different models (CERES CECOL…) to test various N supply management on rape.
We thank the members of CETIOM for theirs participations in data collecting, advice, and the CETIOM which finances the experiments.
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Figure 4 : Evolution of the relative shoot weight with nitrogen deficiencies
Figure 5 : Evolution of the relative L.A.I. with nitrogen deficiencies. Comparison with fescue model.