Effects of nitrogen deficiencies on autumnal growth of oilseed rape

European Journal of Agronomy 17 (2002) 11 – 28 www.elsevier.com/locate/eja

Effects of nitrogen deficiencies on autumnal growth of oilseed rape C. Colnenne a,*, J.M. Meynard b, R. Roche c, R. Reau d a G.E.V.E.S. Domaine de La Minie`re-F78285 Guyancourt Cedex, France INRA, Unite´ Mixte de Recherche INRA-INAPG-BP01 -F78850 Thi6er6al-Grignon, France c INRA, Unite´ Mixte de Recherche En6ironnement et grandes cultures-BP01 -F78850 Thi6er6al-Grignon, France d CETIOM, BP04 -F78850 Thi6er6al-Grignon, France b

Received 25 April 2001; received in revised form 14 September 2001; accepted 1 October 2001

Abstract Several field experiments were carried out to define the effects of temporary N deficiency in autumn on the growth and yield of winter oilseed rape. N deficiencies are described in terms of nitrogen nutrition index (NNI) i.e. methodologies of Lemaire et al. (Proceedings of the XVI International Grassland Congress, Nice, France, 1989, p. 179) and Lemaire and Gastal (In: G. Lemaire (Ed.), Springer, Berlin, Diagnosis of the Nitrogen Status in Crops, 1997, p. 3). The growth components analysed were shoot and tap root biomass, leaf area index (LAI) and radiation use efficiency (RUE). In all the experimental conditions, N deficiencies were severe (NNI near 0.60) and had significant effects on all growth components. These growth variables and NNI were fitted by various functions. The effects of N stress on winter oilseed rape are discussed and compared to another crop. Despite severe autumn N deficiencies, no difference in yield was apparent because these deficiencies probably allow all the time enough growth in autumn to ensure sufficient regrowth in spring. © 2002 Elsevier Science B.V. All rights reserved. Keywords: Rapeseed; Nitrogen; NNI; Temporary deficiencies; Shoot and tap root biomass; LAI; RUE; Models

1. Introduction In autumn, winter oilseed rape has a particularly high potential for growth and nitrogen (N) absorption (up to 6 t ha − 1 and 350 kg N ha − 1, respectively; Dejoux, 1998, 1999). In many situa-

* Corresponding author. Tel.: + 33-1-3083-3273. E-mail addresses: [email protected] (C. Colnenne), [email protected] (J.M. Meynard), roche@bcgn. grignon.inra.fr (R. Roche), [email protected] (R. Reau).

tions, insufficient quantities of N in the soil lead to various intensities of N deficiency (Colnenne, 1999). However, the apparent fertiliser recovery rate is somewhat low (maximum equal to 0.5; Merrien et al., 1997; Reau and Wagner, 1998) to compare with spring applications. That part of autumn fertiliser not absorbed by the crop can increase N leaching and denitrification in winter (Dejoux, 2002). Authors who have measured the effects of different autumn N supplies on autumn growth —aerial biomass, leaf area index (LAI), photosynthetic activity (Mendham, 1995; Triboı¨-

1161-0301/02/$ - see front matter © 2002 Elsevier Science B.V. All rights reserved. PII: S 1 1 6 1 - 0 3 0 1 ( 0 1 ) 0 0 1 4 0 - X

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Blondel, 1988; Ogunlela et al., 1989; Tittonel, 1990)—have shown, in low autumn N supply conditions, that tap root biomass at the end of winter is important for aerial growth rate in early spring (Quille´ re and Triboı¨-Blondel, 1988; Ogunlela et al., 1990; Gabrielle et al., 1998c). However, results on yield are not so conclusive: Delhaye (1980), Mendham et al. (1981), Merrien et al. (1991) and Leto et al. (1994) did not show any significant consequence of autumn N supplies on yield components; Holmes and Ainsley (1978), Ogilvy (1985), Chalmers (1989), Palleau and Tittonel (1991) and Pouzet (1995) observed significant production increases in some cases. On the other hand, for a production potential higher than 4 t ha − 1, Colnenne (1999) has shown that there is a significant yield decrease when, due to autumn N deficiency, aerial growth and N content are below 120 g m − 2 and 40 kg N ha − 1, respectively, at the end of winter. According to these studies, the autumn period of the winter rape cycle is significant for spring growth, yield elaboration and, indirectly, winter nitrate leaching from the soil. The purpose of our work was to evaluate the effects of autumn N deficiency on autumn growth components (LAI: leaf area index, RUE: radiation use efficiency, ratio between shoot and tap root biomass, etc.), which can be used to predict growth, N requirements and yield. Table 1 Characteristics of the soils in S94, S95 and SF95 Experimental situations

S94/S95

SF95

Longitude Latitude Depth of soil (cm) Type of soil

0°.70%W 46°.12%N 25–30 Rendosol

Clay (g g−1) Silt (g g−1) Sand (g g−1) Organic matter (g g−1) Calcareous total (g g−1) PH H2O (%) Stones in the first 30 cm (%)

0.28 0.33 0.10 0.04 0.26 8.1 30

2°.33%E 47°.00%N 18–20 Superficial rendosol 0.20 0.47 0.22 0.02 0.04 6.9 30

2. Materials and methods

2.1. Field experiments Three field experiments were carried out during two growing seasons (1994, 1995) under different pedoclimatic conditions in France. The trials at Surgeres (latitude: 46°.12%N; longitude: 0°.70%W) in 1994 and 1995, and at Saint Florent sur Cher (latitude: 47°.00%N; longitude: 2°.33%E) in 1995 are named S94, S95 and SF95, respectively. To obtain different autumn N deficiencies, the crops were sown early, following a poorly fertilised cereal crop and on shallow soils (Table 1). Each experiment included six N fertiliser (urea) levels applied at emergence (0, 20, 40, 60, 80 and 100 kg N ha − 1), named T0, T20, T40, T60, T80 and T100, respectively. In all field trials, the experimental design took the form of randomised complete blocks with four replicates. Plant density was 45 m − 2 with 0.4 m between rows. The cultivar used was Goeland. Soil P and K contents were high enough to be not limited for the crops. Plants were irrigated at sowing to allow an immediate and homogeneous emergence. Crops were fully weed- and pest-protected so that associated stresses were negligible. In S94 mean temperatures were near 0 °C between 21.11 and 30.11, and in S95 they regularly decreased from 7.7 to 1.7 °C between 24.11 and 13.12. To avoid confusion of the effects of frost and N deficiencies (Gabrielle et al., 1998b; Dejoux, 1999; Justes et al., 2000), we excluded 14.12.93 data and 06.12.94 data in S94 and S95, respectively.

2.2. Data processing The development stages were classed by Jung’s scale (1992) which is based on both foliar and reproductive stages. In autumn, aerial biomass and total N concentration in shoot (Dumas method) were regularly measured every 10 or 15 days, from emergence (B2 stage; two green leaves) until the spring regrowth in January (C1– C2; beginning of stem growth), on three 0.8 m2 samples from each plot. No LAI measurement was performed in 1994. In the autumn of 1995, to

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calculate LAI, we measured on each plot (i) leaf blade area on 50 leaves, which amounts to a surface area of over 300 cm2, (ii) leaf blade biomass on one sample of 0.8 m2. LAI was calculated as follows: LAI = W/0.8Ws

(1)

where W is the leaf blade biomass and Ws the leaf blade area. RUE was calculated according to the model developed by Monteith (1972), which describes shoot growth as follows: W= Ei*RUE*PAR

(2)

where Ei is the radiation interception efficiency and PAR the photosynthetically active radiation. PAR was calculated as follows: PAR = 0.48RG

(3)

where RG is the global incoming radiation (MJ m2), measured in each experiment. Ei was calculated according to Beer’s law, as follows: Ei = Eimax(1− exp.( − k*LAI))

(4)

where Eimax is the maximum fraction of the incoming radiation that can be intercepted by the crop (set to 0.95; Varlet-Grancher et al., 1982), and k is the canopy extinction coefficient (set to 0.75 for rapeseed; Gosse et al., 1983). Biomass and N concentration in tap roots were measured in S95 and SF95 at two periods (post emergence and beginning of winter), on one sample of 0.8 m2. No replication was done in S95. The samples were taken to a depth of 25 cm, which corresponds to about 85% of total root biomass (Kjellstro¨ m, 1991). Yield components, i.e. number of branches m − 2, main stem flowers m − 2, main stem pods m − 2, flowers m − 2 and pods m − 2, were measured at the G4 development stage (Jung, 1992), and number of seeds m − 2, P1G (mean seed weight) and yield at harvest were measured on a subsample of 0.7 m2 per plot. Statistical analyses (ANOVA and non-linear regressions) were performed with STATGRAPHICS software (Manugistics, USA; 1993) and SIGMAPLOT 4.0 software (SPSS Inc., USA; 1997).

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2.3. Determination of N deficiencies 2.3.1. Instantaneous NNI (NNI) To characterise the N status of the plants, the Nitrogen Nutrition Index (NNI) defined by Lemaire et al. (1989) was calculated as follows: NNI = Nt/Nc

(5)

where Nt is the total N concentration measured in aerial parts and Nc the critical N concentration for the same shoot biomass calculated with the critical N curve specific to winter oilseed rape (Colnenne et al., 1998). If NNI is equal to 1, N nutrition is considered to be optimum, while higher values indicate excess N. Lower values indicate a deficiency; the lower the NNI, the more deficient the nutrition (Lemaire and Gastal, 1997).

2.3.2. Integrated NNI (NNIINTE) Integrated NNI describes both the intensity and the duration of N deficiencies and appears more accurate for characterising N deficiencies when they fluctuate considerably (Lemaire and Gastal, 1997). NNIINTE corresponds to the integrated value of NNI during the period of deficiency (i.e. NNI B1), calculated during the period analysed (Lemaire and Gastal, 1997).

3. Results

3.1. E6olution of N deficiency in autumn N nutrition conditions differed widely between experimental situations (Fig. 1a–c). The lower the autumn N supplies, the higher the intensity and duration of N deficiency. In 1995, the earliest N deficiencies (NNI inferior to 1) appeared with T0 at the B3 stage, 427 and 482 degree-days (base 0 °C) after emergence (base 0) in S95 and SF95, respectively. These deficiencies were 854 and 584 degree-days earlier than those with T100. In S94, the first measurement was taken at the B7–B8 stages, when N deficiencies were also well established with T0, T20 and T40. In all the conditions, N deficiencies increased steadily in autumn until the C1–C2 stages (January), and the lowest NNI values were systemati-

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Fig. 1. (a) Evolution of NNI in autumn for different N treatments in S94. (b) Evolution of NNI in autumn for different N treatments in S95. (c) Evolution of NNI in autumn for different N treatments in SF95.

cally measured for the T0 control treatments (0.58, 0.53 and 0.61 in S94, S95 and S95, respectively).

3.2. Effects of temporary N deficiency on shoot biomass and LAI The evolutions of both shoot biomass and LAI were consistent with NNI values i.e. with N supply levels (2a–c and 3a and b). The earlier and more severe the N deficiency, the slighter the increase in each growth variable.

Significant differences appeared quickly between N treatments: for shoot biomass, from 14.10.1993, 26.09.1994 and 24.11.1994 in S94, S95 and SF95, respectively, and for LAI, from 26.09.1994 and 24.11.1994 in S95 and SF95. In autumn, the widest differences between T0 and T100 were for shoot weight: 226.1, 251.4 and 124.9 g m − 2 in S94 (14.12.1993), S95 (06.12.1994) and SF95 (13.12.1994), respectively, and for LAI: 1.32 and 1.96 in S95 (06.12.1994) and SF95 (13.12.1994). In winter, both shoot biomass and

C. Colnenne et al. / Europ. J. Agronomy 17 (2002) 11–28

LAI decreased systematically from 14.12.1993, 06.12.1994 and 13.12.1994 in S94, S95 and SF95, respectively. At the end of winter, there was less difference in shoot biomass and LAI between the various N supply treatments; this can be explained by leaf loss.

3.3. Ability of different criteria to integrate the effects of temporary N deficiency on shoot biomass, LAI and RUE To cancel out the pedoclimatic conditions specific to each experiment, we analysed the effects of the N deficiencies on growth components expressed in relative values. W/Wmax corresponds to the ratio between the shoot biomass of each treatment (W) and the maximum shoot biomass value measured at the same moment in time (Wmax). Wmax is the mean of W for the group of treatments giving the highest W value, not significantly different by the test of Newman and Keuls, at 5% level. LAI/LAImax ratios were calculated using the same methodology. RUE/RUEmax is the ratio between the RUE calculated for each treatment and the RUE calculated for the treatment with the highest N supply. Using the methodology developed by Be´ langer et al. (1992) on tall fescue, the evolutions of the

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different relative growth variables were linked with NNI, calculated at the measurement date (Fig. 2a–c). All the relative growth components correlate well with the N status of the crop. The relationships between these three variables and NNI are described by first-order monomolecular equations (see models and r 2 in Fig. 2a–c). NNI explains 74, 71 and 51% of the variability associated with W/Wmax, RUE/RUEmax and LAI/ LAImax, respectively. The earlier and more severe the N deficiency, the lower the level of each growth variable. Where NNI is equal to 0.70, the ratio W/Wmax decreases by 30%, LAI/LAImax by 38% and RUE/RUEmax by 30%. However, the description of N deficiencies in terms of NNIINTE seems more accurate (Lemaire and Gastal, 1997; Ple´ net and Cruz, 1997). In Fig. 3a–c, each relative growth variable is linked with NNIINTE. All the data have been well fitted by simple linear regressions (see models and r 2 in Fig. 3a–c). NNIINTE explains more than 80% of the variability associated with any of these three variables. For an NNIINTE equal to 0.70, 34% of shoot biomass reduction is explained by the decrease in either LAI (− 62%) or RUE ( − 24%). The high precision of these correlations can be explained by the self-correlation between data which have been successively cumulated. We then

Fig. 1. (Continued)

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Table 2 Evolution of shoot biomass (g m−2) in autumn for different N treatments in S94, S95 and SF95 (a) S94 Dates of data Sum of temperatures from emergence (DD*, base 0 °C) T0 T20 T40 T60 T80 T100 WMAX (b) S95 Dates of data Sum of temperatures from emergence (DD*, base 0 °C) T0 T20 T40 T60 T80 T100 WMAX (c) SF95 Dates of data Sum of temperatures from emergence (DD*, base 0 °C) T0 T20 T40 T60 T80 T100 WMAX

14-10-93 620.8

02-11-93 812.5

17-11-93 972.3

14-12-93 1130.2

20-01-94 1434.7

115.6 b 136.6 ab 134.4 ab 140.8 ab 154.2 a 146.9 a 142.58

142.3 e 211.2 d 236.6 cd 253.2 bc 269.3 ab 291.2 a 280.25

182.8 d 246.9 c 312.7 b 360.2 a 393.7 a 385.3 a 379.73

165.1 236.6 261.8 307.1 378.6 391.2 384.9

c b b b a a

164.7 b 167.2 b 202.1 b 309.1 a 264.0 a 303.6 a 292.23

26-09-94 441.8

06-10-94 600.3

26-10-94 900.9

06-12-94 1416.3

23-01-95 1783.8

178.3 214.0 263.4 319.9 294.4 326.2 313.5

201.6 c 278.4 b 318.0 b 412.8 a 439.7 a 453.0 a 435.17

204.7 238.5 393.0 401.7 405.7 369.2 392.4

24-11-94 1015.1

13-12-94 1194.9

07-02-95 1514

24-02-95 1653.5

75.0 122.9 110.3 121.6 134.2 155.8 145.0

78.8 139.0 148.6 150.1 174.6 203.7 189.2

84.7 109.0 117.0 138.0 160.2 183.2 171.7

106.5 155.7 173.7 177.2 180.2 237.0 237.0

44.0 54.8 61.1 61.1 61.1 61.1 61.1

c b a a a a

05-10-94 413.9 7.5 7.8 7.9 7.2 8.4 8.0 –

83.6 117.6 139.9 139.9 139.9 139.9 139.9

c b a a a a

25-10-94 864.1 34.7 40.9 41.3 42.2 42.8 53.0 –

c c b ab ab a

c b b b a a

c b b b a a

b b a a a a

c b b b a a

c b b b b a

Values of WMAX. DD*, Degree-day; abc, statistic groups defined by Newman and Keuls test (*PB0.05) at each date.

analysed the variations of a non-cumulative variable, the shoot growth rate index (dW/dWmax), which corresponds to the ratio between aerial growth rate as measured between two successive sampling days on one treatment and the same variable measured on the non-N-limiting treatment. The leaf area variation index (d(LAI)/ d(LAImax)) was calculated using the same methodology. The RUE index (RUEi) is the following ratio: RUE calculated between two successive sampling dates/RUE calculated on the non-N-limited treatment between the same two dates. These variables are related to NNIM, which is the mean of the NNIs of the two successive

sampling dates. The results are shown in Fig. 4a–c. The relationships between NNIM and NNIM variables dW/dWmax, d(LAI)/d(LAImax), RUEi were described by polynomial equations (see models and r 2 in Fig. 4a–c). NNIM explained 74, 66 and 88% of the variability in these three variables, respectively. Where NNIM is equal to 0.70, the decreases were 78, 88 and 42% for dW/dWmax, d(LAI)/d(LAImax) and RUEi, respectively.

3.4. Effects of N deficiency on tap root growth At the B2 and B10 stages, there was no significant difference in tap root growth (biomass, N

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quantity) between N treatments in SF95. The mean values of tap root biomass were 2 and 42.37 g m − 2 and the mean values of tap root N quantity were 0.2 and 0.72 g N m − 2 at B2 and B10, respectively. No statistical analysis was possible with S95, but the results of the different treatments were very close. The partitioning of biomass and N quantity between shoot and tap root was compared with NNI; RW corresponds to the ratio between tap root and shoot biomass, RN to the ratio between tap root and shoot N quantity. The relationships between these variables (RW, RN) and NNI were described by power equations (models and r 2 appear in Fig. 5a and b). In non-N-limiting conditions (i.e. NNI \1), RW and RN were the lowest (i.e. near 10%) for each variable, and increased with N stress. Where NNI was equal to 0.5, tap root biomass and N quantity represented 63 and 32% of shoot biomass and N quantity, respectively, showing that the tap root is less sensitive to N stress conditions than the aerial parts.

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3.5. Effects of N deficiency on yield components In these three experimental conditions, no significant differences appear between treatments (F test, *PB 0.05) either for the yield components defined early in autumn (numbers of branches m − 2, main stem flowers m − 2, main stem pods m − 2) or those developing later, in spring (numbers of flowers m − 2, pods m − 2, seeds m − 2 and P1G). The low precision of the numbers of pods m − 2 and yield results in S94 is due to lodging in N60, N80 and N100 (Table 4a–c).

4. Discussion

4.1. Relationships between NNI and growth 6ariables Consistent with the work of Be´ langer et al. (1992), the high precision of all the relationships linking NNI with growth variables (Fig. 2a– c) confirms that NNI is a relevant diagnostic tool for

Table 3 Evolution of LAI in autumn for different N treatments in S95 and SF95 (a) S95 Dates of data Sum of temperatures from emergence (DD*, base 0 °C) T0 T20 T40 T60 T80 T100 LAIMAX (b) SF95 Dates of data Sum of temperatures from emergence (DD*, base 0 °C) T0 T20 T40 T60 T80 T100 LAIMAX

26-09-94 441.8

06-10-94 600.3

1.01 1.33 1.59 1.59 1.59 1.59 1.59

1.11 1.54 1.93 2.00 2.00 2.00 1.99

c b a a a a

c b a a a a

05-10-94 413.9

25-10-94 864.1

0.35 0.34 0.35 0.38 0.40 0.37 –

0.51 0.74 0.67 0.71 0.75 0.88 0.75

b a a a a a

26-10-94 900.9 1.44 1.69 2.13 3.04 2.86 3.51 3.51

d d c b b a

24-11-94 1015.1 1.18 1.91 1.76 2.10 2.46 2.62 2.27

c ab b ab a a

06-12-94 1416.3 1.25 1.50 1.59 2.25 2.35 2.57 2.39

b b b a a a

13-12-94 1194.9 0.92 1.91 1.70 1.60 2.23 2.88 2.56

c b bc bc ab a

23-01-95 1783.8 1.17 1.31 1.42 1.52 1.65 1.55 1.54

c bc abc ab a ab

07-02-95 1514 0.64 0.91 1.32 1.44 1.41 2.21 2.21

c bc b b b a

24-02-95 1653.5 1.79 2.42 2.23 2.49 2.68 3.15 2.92

Values of LAIMAX. DD*, Degree-day; abc, statistic groups defined by Newman and Keuls test (*PB0.05) at each date.

c b bc b ab a

b

a

1740 1816 1851 1902 2246 1702

2082 2080 2013 2177 2120 2047

Number of pods on the main stem m−2

12 252 11 214 13 284 11 216 12 479 10 859

Number pods m−2

13 483 12 311 12 493 13 627 13 696 11 465

15 617 13 922 15 508 14 777 13 890 16 146

Number of flowers m−2

86 636 83 348 81 005 76 475 80 554 77 512

Number seeds m−2

Mean seed weight. Lodging notes have been done at harvest according to Jung’s scale (1992).

2505 2554 2683 2637 3017 2380

235 247 244 273 250 229

Number of flowers on the main stem m−2

2677 2720 2852 3033 2917 2838

Number of branches m−2

Experimental treatments

2586 2550 2544 2385 2445 2523

Number of pods on the main stem m−2

270 266 249 236 240 233

301 284 330 312 341 296

(a) S94 T0 T20 T40 T60 T80 T100

(b) S95 T0 T20 T40 T60 T80 T100 (c) SF95 T0 T20 T40 T60 T80 T100

Number of branch m−2

Experimental treatments

Table 4 Components of yield for different N treatments in S94, S95 and SF95

0.53 0.58 0.55 0.55 0.51 0.54

53.65 51.45 42.47 43.73 48.82 43.87

Fecondation index

4.28 4.42 4.28 4.34 4.33 4.26

P1G×1000 (g)a

7136 7140 6834 7511 7044 6157

8379 7162 6586 6462 6781 7083

Number of pods m−2

3.61 3.68 3.47 3.32 3.49 3.30

Yield (t ha−1)

91 957 91 512 90 212 90 811 89 315 91 247

82 056 78 783 73 538 81 950 79 881 80 108

Number of seeds m−2

0 0 0 100 100 100

Beating down notes at harvestb

3.73 3.77 3.78 3.70 3.65 3.77

4.28 4.34 4.52 4.17 4.27 4.16

P1G×1000 (g)a

3.43 3.45 3.41 3.36 3.26 3.44

3.51 3.42 3.32 3.42 3.41 3.33

Yields (t ha−1)

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Fig. 2. (a) Relationship between W/WMAX and NNI. Rapeseed model: W/WMAX =1.1431 − 2.7095 exp.( − 2.5912NNI); r 2 =0.75; n= 57 and its confidence interval. Comparison with the tall fescue model (Be´ langer et al., 1992). (b) Relationship between LAI/LAIMAX and NNI. Rapeseed model: LAI/LAIMAX = 1.1335 − 2.3004 exp.( − 2.3052NNI); r 2 =0.53; n = 33 and its confidence interval. Comparison with the tall fescue model (Be´ langer et al., 1992). (c) Relationship between RUE/RUEMAX and NNI. Rapeseed model: RUE/RUEMAX =1.0393− 1.6908 exp.( − 2.9170NNI); r 2 = 0.71; n = 31 and its confidence interval. Comparison with the tall fescue model (Be´ langer et al., 1992).

crop N nutrition. However, this index can only be used where N stress develops uniformly. When N supply is irregular over time, i.e. when N supply is instantaneously increased by fertiliser input or mineralisation flushes, N deficiency has to be characterised by integrated NNI. Using the methodol-

ogy developed by Lemaire and Gastal (1997) on tall fescue swards, the linear relationships between integrated NNI and growth variables (Fig. 3a–c) appear more accurate and show a wider range of validity. On the other hand, integrated relationships are not appropriate for use in dynamic crop

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models such as Ceres Rape (Gabrielle et al., 1998a,b) or Azodyn (Jeuffroy and Recous, 1999). The relationships linking biomass growth rate, LAI increase rate or RUE index and NNI measured at the same period (Fig. 4a– c), characterise the instantaneous N stress effects and can be used in these dynamics crop models. Both LAI and RUE show greater sensitivity to severe N deficiencies than in the previous relationships.

4.2. Effects of temporary N deficiencies on biomass, LAI and RUE Consistent with the general structure of the dynamic crop models (Ceres Rape: Gabrielle et al., 1998a,b, or Azodyn: Jeuffroy and Recous, 1999), the consequences of N deficiency on shoot biomass were broken down into their effects on LAI and RUE, using the energy model developed by Monteith (1972).

4.2.1. Reduction of LAI under N stress conditions The decrease in LAI can be explained by (i) changes in the phyllochron, i.e. the rate of leaf emergence expressed in degree-days, (ii) a reduction in leaf blade size or (iii) higher rate of loss of senescent leaves (Mendham, 1995). The phyllochron varies from 60 to 120 degreedays (Triboı¨-Blondel, 1988; Tittonel, 1990; Dejoux, 2002), depending on such factors as water

supply, nutrition and plant spacing (Mendham, 1995). The loss of leaves, which depends on genotype characteristics (Mendham, 1995), is directly influenced by such climatic factors as winter freezing (Gabrielle et al., 1998b), and more accurately, temperatures below 8 °C (Justes et al., 2000), self-shading senescence occurring when LAI rises above 3– 3.5 in winter oilseed rape (Gabrielle et al., 1998b; Justes et al., 2000), or N supply (Ogunlela et al., 1989). At S95, N deficiency did not significantly alter either phyllochron (values were 57–89 degree-days after emergence in order of leaf emergence; this is the effect of increasing self-shading and the autumn decline in day length), or leaf loss (reaching 600 and 790 degreedays after emergence in order of leaf emergence as a result of autumn temperature decrease: Triboı¨Blondel, 1988). These conclusions are in agreement with the findings of Dejoux (1999), who has worked in a wide range of N stress conditions. In Fig. 4a–c, models have been fitted without measurements of leaf fall occurring (i) after periods of frost and (ii) when LAI is higher than 3.5, i.e. in light competition conditions. These phenomena also appear in N deficiency conditions (Mendham, 1995; Ogunlela et al., 1989), and have been taken into account in oilseed rape crop models such as Ceres Rape (Gabrielle et al., 1998a,b) and Daisy (Petersen et al., 1995).

Fig. 2. (Continued)

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Fig. 3. (a) Relationship between W/WMAX and NNIINTE. Rapeseed model: W/WMAX =1.1347NNIINTE −0.1367; r 2 =0.86; n =55. (b) Relationship between LAI/LAIMAX and NNIINTE. Rapeseed model: LAI/LAIMAX =2.1660NNIINTE −1.1366; r 2 =0.84; n = 29. (c) Relationship between RUE/RUEMAX and NNIINTE. Rapeseed model: RUE/RUEMAX =0.7449NNIINTE +0.2366; r 2 =0.80; n= 28.

In the relationships shown in Figs. 2a– c and 3a–c, the data collected in freezing conditions or for higher LAI did not stand apart from the others because these growth variables are expressed in cumulative values.

4.2.2. Decrease in RUE under N stress conditions Be´ langer et al. (1992) and Lemaire and Gastal (1997) have shown that N stress has a significant

effect on RUE in tall fescue and maize, respectively. For winter oilseed rape, the results have been disputed depending on the expression of N deficiencies. Anderson et al. (1996) did not reveal any impact of different N fertilisation treatments on RUE, but Justes et al. (2000) measured significant negative effects of N deficiency. On the other hand, RUE varied according to (i) development stage (changes after post-flowering when lipid

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compounds are forming: Habekotte´ , 1997), (ii) falling temperatures (strong reductions below a temperature threshold of 6– 7 °C: Justes et al., 2000), (iii) limiting nutritional conditions such as water or N supplies (Mendham, 1995). In our autumn experiments, the winter oilseed rape was at the rosette stage and data gathered in frost conditions with mean temperatures below 8 °C were removed. In these conditions N stresses appear to be the main parameter inducing a decrease in RUE/RUEMAX. These findings are confirmed by Justes et al. (2000) (see Fig. 6). A RUE decrease in N-limiting conditions could be linked to changes either in photosynthetic pigment concentrations or photosynthesis activity (Ogunlela et al., 1989). Gammelvind et al. (1996) have linked potential photosynthetic capacity to tissue N contents, and demonstrated a significant decrease for a threshold below 2 g N m − 2. In maize, the evolution of RUE/RUEMAX in N-deficient conditions looks similar to that in winter oilseed rape (Ple´ net and Cruz, 1997). However, the RUE decrease could arise from (i) the calculation methodology, in which tap root biomass is not taken into account, or (ii) the specific characteristics of oilseed rape during autumn N deficiency. With lucerne in spring, Khaiti

and Lemaire (1992) have shown a smaller RUE variability when tap root biomass was included than when it was excluded. Winter oilseed rape in autumn, on the other hand, stores a part of the assimilates in the tap root and we have observed less tap root growth sensitivity to N stress conditions as found by Quille´ re and Triboı¨Blondel (1988) or Merrien et al. (1997). For these reasons RUE values could be under-estimated and we have calculated RUE with both shoot and tap root biomass for S95 and SF95. The relationship between this new variable and NNI was fitted to a polynomial function (Fig. 7). The low correlation (r 2 = 0.508) could be explained by the absence of replication for tap root measurements at S95 and also by the weak general trend between the two variables. N deficiency had less effect on RUE when tap root biomass was taken into account. For NNI equal to 0.90, the decreases were 0% when tap root was taken into account, and 3% when it was not. For NNI equal to 0.70, they were 12 and 30%, respectively, with and without tap root. For NNI values higher than 0.70, N stresses had a stronger effect on the partitioning of assimilates between root and shoot than on RUE values. For NNI below 0.70, RUE decreased whatever the calculation methodology.

Fig. 3. (Continued)

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23

Fig. 4. (a) Relationship between d(W)/d(WMAX) (W 1) and NNIM. Rapeseed model: W 1 = −1.9548NNIM2 +4.7998NNIM − 1.9848; r 2 =0.74; n =42. (b) Relationship between d(LAI)/d(LAIMAX) (LAI1) and NNIM. Rapeseed model: LAI1 = − 1.5913NNIM2 + 4.5020NNIM − 2.2563; r 2 = 0.66; n= 18. (c) Relationship between d(RUE)/d(RUEMAX) (RUE1) and NNIM. Rapeseed model: RUE1 = 3.4205NNIM3 − 11.8250NNIM2 + 13.7600NNIM −4.4311; r 2 =0.82; n =25.

4.3. Effects of N deficiency on yield An explanation of the effects of autumn N stresses on yield must take into account both the growth status of the plants at the end of winter, i.e. biomass and N quantities in shoot parts, and the production potential of the pedoclimatic conditions (Colnenne, 1999). In our field experiments,

shoot biomass was more than 120 g m − 2 (except for T0 and T20 in SF94), shoot N quantities more than 40 kg N ha − 1 (except for T0, T20 and T40 in SF94), and in all cases the production potential was below 4 t ha − 1. On the criteria defined above, no significant yield decrease was expected. These results show that even with intense and long-lasting N deficiencies in autumn (the strongest NNI

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was 0.53 and the longest N stress was 1356.8 degree-days for T0 in S95), neither yield nor any of the yield components were modified. We performed some simulations with the CERES-rape model (Gabrielle et al., 1998a,b) to study what happens in low shoot biomass situations. Simulated responses of yield to total biomass at regrowth (January 30th in this example) and under three different climatic environments are shown in Fig. 8. Yield was very responsive to conditions during the flowering period, which is the period when pods are mainly formed. But, for a given climatic potential, biomass at regrowth had only a small effect on yield: in all cases, above a threshold of about 200 g m − 2, yields levelled out at their potential value. These results are in good agreement with those of Colnenne (1999) mentioned above, since at regrowth, the shoot usually represents 60– 80% of total biomass (the exact value depends on the N status of the plant as seen above in 2.4, and also on the intensity of frost damage). It is therefore not surprising that, in our conditions, N deficiency in autumn proved to have no effect on yield. Enough N was released by natural mineralisation in our soils to allow sufficient growth in autumn, even though no fertiliser was applied. We conclude that very intense temporary N deficien-

cies in autumn are not a problem for achieving good yields in winter oilseed rape: this is due to the great recovery abilities of this crop during spring. Bouchard and Jeuffroy (1998) and Jeuffroy and Bouchard (1999) drew similar conclusions from their experiments with temporary N deficiencies in wheat: treatments with minor N deficiencies (e.g. with only weak effects on total growth) did not significantly differ from the control for final yield. The main point seems to be achieve sufficiently high LAI values at flowering to allow the fastest growth possible during the reproductive phase.

4.4. Comparison of N deficiency effects on winter oilseed rape and fescue The consequences of N deficiency on growth for winter oilseed rape and tall fescue (Be´ langer et al., 1992) were compared, to analyse the sensitivity to N of the two species. In Be´ langer’s experimental conditions, as in ours, N stresses increased steadily without any fluctuation. In N-limiting conditions, the decrease in shoot biomass is considerable in both species. For NNI equal to 0.50, W decreases were 60 and 50% in rapeseed and fescue, respectively. Despite the discrepancy between the two species, these reduc-

Fig. 4. (Continued)

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25

Fig. 5. (a) Partitioning of biomass between shoot and tap root with NNI. Rapeseed model: RW =0.196NNI −1.689; r 2 =0.88; n= 13. (b) Partitioning of N quantity between shoot and tap root with NNI. Rapeseed model: RN =0.101NNI −1.684; r 2 =0.92; n= 13.

tions were not significantly different (Fig. 2a). Changes in LAI are compared in Fig. 2b. The LAI decrease was greater in winter oilseed rape than in tall fescue— 60 and 53%, respectively, for NNI equal to 0.50— but the wide variability of the rapeseed’s responses did not result in a significant gap. This heterogeneity of the data could be explained by leaf loss, which is considerable in Cruciferae. In both species, N deficiencies have little effects on RUE i.e. on photosynthesis. For NNI equal to

0.50, the reduction in RUE is 36% for oilseed rape and 43% for fescue (Fig. 2c). These responses can been explained by the RUE calculation methodology, which takes only shoot biomasses into account and the weak effect of NNI on RUE. In autumn, in winter oilseed rape, tap root growth is less sensitive to N stresses. In tall fescue, on the other hand, root biomass contributes to the increase in aerial growth in spring. According to the specific growth management for each species during the two periods analysed, a complementary

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study taking account of root biomass seems to be necessary to make the comparison more accurate.

5. Conclusion We have shown that NNI is a good diagnostic tool of N deficiency damage on crop growth in

winter oilseed rape, as in other species such as tall fescue and maize. However, even intense (NNI equal to 0.53 for T0 in S95) and lasting autumn N stresses did not necessarily have a negative impact on yield. In this article, we have validated the determination method for N deficiency (NNI, integrated NNI) and quantified its impact on both LAI and

Fig. 6. Comparison of RUE/RUEMAX results and Justes et al.’s data (2000).

Fig. 7. Comparison of RUE/RUEMAX results when shoot biomass or shoot biomass + tap root biomass have been taken into account in RUE calculate. Model with shoot biomass and tap root biomass: RUE/RUEMAX =1.0142 − 6.3936 exp.( − 7.0485NNI); r 2 =0.51; n =12.

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Fig. 8. Simulated responses of yield under three contrasting climatic environments.

RUE. On the basis of this work, the effects of autumn N deficiency on yield elaboration in spring can be studied more accurately.

Acknowledgements Our thanks to CETIOM which financed this study, and to F. Caceres, L. Champolivier, P. Fauvin, G. Sauzet (C.E.T.I.O.M.) for their participation in data collecting and for their advice.

References Anderson, M., Heidman, T., Plauborg, F., 1996. The effects of drought and N on light interception, growth and yield of winter oilseed rape. Acta Agric. Scand., Sect. B, Soil Plant Sci. 46, 55 – 67. Be´ langer, G., Gastal, F., Lemaire, G., 1992. Growth analysis of a tall fescue sward fertilized with different rates of nitrogen. Crop Sci. 32, 1371 – 1376. Bouchard, C., Jeuffroy, M.H., 1998. Fertilisation du ble´ tendre d’hiver:quels sont les effets de carences azote´ es sur le nombre de grains par m2. Perspect. Agric. 237, 69 –76. Chalmers, A.G., 1989. Autumn and spring fertiliser nitrogen requirements for winter oilseed rape. Aspects Appl. Biol. 23, 125– 133. Colnenne, C., 1999. The`se de doctorat INA-PG (Fance).

Colnenne, C., Meynard, J.M., Reau, R., Justes, E., Merrien, A., 1998. Determination of a critical dilution curve for winter oilseed rape. Ann. Bot. 81, 311 – 317. Dejoux, J.F., 1998. Inte´ reˆ t environnemental des semis tre`s pre´ coces. Ole´ oscope 46, 22 – 24. Dejoux, J.F., 1999. The`se de doctorat INA-PG (France). Dejoux, J.F., 2002. Evaluation of environment friendly crop management systems for winter rapeseed based on very early sowing dates, Agronomie, p. 31, in press. Delhaye, R., 1980. Fractionnement de la fumure azote´ e dans des cultures de colza d’hiver en Hesbaye. Rev. Agric. 1, 69 – 77. Gabrielle, B., Denoroy, P., Gosse, G., Justes, E., Andersen, M.N., 1998a. Development, calibration and test of CEREStype model for winter oilseed rape. Field Crops Res. 57, 95 – 111. Gabrielle, B., Denoroy, P., Gosse, G., Justes, E., Andersen, M.N., 1998b. A model of leaf area development and senescence for winter oilseed rape. Field Crops Res. 57, 209 – 222. Gabrielle, B., Justes, E., Denoroy, P., 1998c. Modelling of temperature and nitrogen on the rooting dynamics of winter oilseed rape. Proceedings 16e`me Congre`s Mondial de Science du sol, Montpellier, Symposium, vol. 14, pp. 110 – 117. Gammelvind, L.H., Schjoerring, J.K., Mogensen, V.O., Jensen, C.R., Bock, J.G.H., 1996. Photosynthesis in leaves and siliques of winter oilseed rape (Brassica napus L.). Plant Soil 186, 227 – 236. Gosse, G., Rollier, M., Rode, J., Chartier, M., 1983. Vers une mode´ lisation de la production chez le colza de printemps, Proceedings of the Sixth International Rapeseed Congress, Paris, pp. 116 – 126.

28

C. Colnenne et al. / Europ. J. Agronomy 17 (2001) 11–28

Habekotte´ , B., 1997. A model of the phenological development of winter oilseed rape (Brassica napus L.). Field Crops Res. 54, 127 – 136. Holmes, M.R.J., Ainsley, A.M., 1978. Seedbed fertiliser requirements of winter oilseed rape. J. Sci. Food Agric. 29, 657 – 666. Jeuffroy, M.H., Bouchard, C., 1999. Nitrogen deficiency and wheat grain number. Crop Sci. 39, 1385 –1393. Jeuffroy, M.H., Recous, S., 1999. Azodyn: a simple model simulating the date of nitrogen deficiency for decision support in wheat fertilisation. Eur. J. Agric. 10, 121 –144. Jung, L., 1992. Bien repe´ rer les stades du colza. Ole´ oscope 7, 18– 19. Justes, E., Denoroy, P., Gabrielle, B., Gosse, G., 2000. Effect of crop nitrogen status and temperature on the radiation use efficiency of winter oilseed rape. Eur. J. Agric. 13, 165 – 177. Khaiti, M., Lemaire, G., 1992. Dynamics of shoot and root growth of lucerne after seeding and after cutting. Eur. J. Agron. 1 (4), 241 –247. Kjellstro¨ m, C., 1991. Growth and distribution of the root system in Brassica napus. Proceedings of the Eighth International Rapeseed Congress, Saskatoon, vol. C(08), pp. 722 – 726. Lemaire, G., Gastal, F., 1997. N uptake and distribution in plant canopies. In: Lemaire, G. (Ed.), Diagnosis of the Nitrogen Status in crops. Springer, Berlin, pp. 3 –45. Lemaire, G., Gastal, F., Salette, J., 1989. Analysis of the effect of N nutrition on dry matter yield of a sward by reference to potential yield and optimum N content. Proceedings of the XVI International Grassland Congress, Nice, France, pp. 179– 180. Leto, C., Carruba, A., Cibella, R., Trapani, P., 1994. Effetti della concimazione azotata su caratteri bioagronomici e qualitativi del colza (Brassica napus var. oleifera D.C.) in ambiente semi-arido. Riv. Agron. 28, 199 – 205. Mendham, N.J., 1995. Physiological basis of seed yield and quality in oilseed rape, Proceedings of the Ninth International Rapeseed Congress, Cambridge, vol. 2, pp. 485 – 490. Mendham, N.J., Shipway, P.A., Scott, R.K., 1981. The effects of seed size, autumn nitrogen and plant population density on the response to delayed sowing in winter oil-seed rape (Brassica napus). J. Agric. Sci. Camb. 96, 417 – 428. Merrien, A., Champolivier, L., Devineau, J., Estragnat, A., Jung, L., 1991. Valorisation de l’azote par une culture de

colza d’hiver. Proceedings of the Eighth International Rapeseed Congress, Saskatoon, vol. C(04), pp. 1186 – 1192. Merrien, A., Jung, L., Maisonneuve, C., 1997. Valorisation re´ elle de l’azote apporte´ e a` l’automne. Ole´ oscope 20, 9 – 16. Monteith, J.L., 1972. Solar radiation and productivity in tropical ecosystems. J. Appl. Ecol. 9, 747 – 766. Ogilvy, S., 1985. Nitrogen for winter oilseed rape. High Mowthorpe E.H.F. Ann. Rev., 28 – 33. Ogunlela, V.B., Kullmann, A., Geisler, G., 1989. Leaf growth and chlorophyll content of oilseed rape (Brassica napus L.) as influenced by nitrogen supply. J. Agron. Crop Sci. 163, 73 – 89. Ogunlela, V.B., Kullmann, A., Geisler, G., 1990. Nitrogen distribution and dry matter accumulation in oilseed rape (Brassica napus L.) as influenced by nitrogen supply. J. Agron. Crop Sci. 164, 321 – 333. Palleau, J.P., Tittonel, E., 1991. Effet d’un apport d’azote a` un stade repe`re de la fleur. Re´ percussions sur les composantes du rendement. Proceedings of the Eighth International Rapeseed Congress, Saskatoon, pp. 125 – 128. Petersen, C., Jorgensen, U., Svendsen, H., Hansen, S., Jensen, H., Nielsen, N., 1995. Parameter assessment for simulation of biomass production and N uptake in water rapeseed. Eur. J. Agron. 4, 77 – 89. Ple´ net, D., Cruz, P., 1997. The nitrogen requirement of major agricultural crops: maize and sorghum. In: Lemaire, G. (Ed.), Diagnosis of the Nitrogen Status in Crops. Springer, Berlin, pp. 93 – 107. Pouzet, A., 1995. Agronomy. Production and Utilization of Brassica Oilseed. Cab International. Ed. Kimber and Mac Gregor Oxford, pp. 11 – 64. Quille´ re, I., Triboı¨-Blondel, A.M., 1988. Dynamique des re´ serves carbone´ es chez le colza d’hiver. Impacts sur la croissance. Proceedings of the Seventh International Rapeseed Congress, Poznan, pp. 745 – 750. Reau, R., Wagner, D., 1998. Apport d’azote sur colza inutile a` l’automne. Ole´ oscope 46, 18 – 19. Tittonel, E., 1990. The`se de doctorat de l’Universite´ Paris. Triboı¨-Blondel, A.M., 1988. Mise en place et fonctionnement des feuilles de colza d’hiver:relation azote carbone et senescence. Agronomie 9, 37 – 44. Varlet-Grancher, C., Bonhomme, R, Chartier, M., Artis, P., 1982. Efficience de la conversion de l’e´ nergie solaire par un couvert ve´ ge´ tal. Oecol. Plant. 3 (17-1), 3 – 26.