winter rape, respectively. However, none of these authors quantified the actual N nutritional state
of the crop. The N status of a crop may be assessed by using the N nutrition index NNI
proposed by Lemaire and Gastal 1997. Be´langer et al. 1992 used the NNI successfully to take
account of the effect of N on the RUEa of forage grasses. In the same way, Lemaire et al. 1997
shown that for maize RUEa was strongly reduced by N deficiency: the relationship between RUEa
and NNI was linear for values of NNI between 0.5 and 1. This high sensitivity of RUEi to N
deficiency was also observed by Muchow and Davis 1988 and Sinclair and Horie 1989 for
maize, sorghum, rice and soybean. Until now there have been no studies on the variation of
oilseed rape RUEa as a function of its N nutri- tion. Recently, Gabrielle et al. 1998a proposed a
CERES-Rape model including N stress on LAI and obtained significant over-estimation of DM
for unfertilised crops; they hypothesised that RUEa decreased in response of N deficiency.
Now, RUEa is a widely used parameter in crop simulation models; it seems then necessary to
assess the magnitude of the N effect on it.
The objective of this work was to investigate the effect of N on the RUEa of winter oilseed
rape canopies which had received different doses of N fertiliser, using the NNI. After having ac-
counted for the influence of N status on RUEa, the effect of temperature for all development
stages of the crop was also investigated, which enabled one to avoid confounding interactions
between N and temperature. Moreover, to limit the influence of experimental artefacts, the RUEa
was calculated on the basis of the radiation ab- sorbed by the crop which yielded RUEa, and by
taking account the total biomass of the crop, including the measured dry matter of the leaves
which fell onto the soil during growth generated total dry matter.
2. Materials and methods
2
.
1
. Field location, general design and treatments Data were collected from September 1994 to
July 1995 in a field in the Champagne area North-eastern France, 48°50 N, 2°15 E. The
soil is a very calcareous rendosol consisting of a rendzina 0 – 28 cm layer overlying chalky and
loamy ‘cryoturbated’ material 28 – 120 cm layer; the chalk substratum is found below 120 cm. The
main soil characteristics were described previously by Leviel et al. 1998.
A winter oilseed rape crop Brassica napus c6 oleifera Metzg., cv Goe´land was sown on 9 Sep-
tember, 1994 and harvested on 11 July, 1995; the plant density was 60 plants m
− 2
. Three N treat- ments were applied: nil treatment N0, subopti-
mal split applications made in spring totalling 135 kg N ha
− 1
treatment N135, and a high applica- tion of 272 kg N ha
− 1
applied in four doses treatment N270 Table 1. The experiment was
laid out as a split plot design, with N treatments as main plots and sampling dates as sub-plots.
This arrangement was replicated in three blocks. Other fertilisation P, K, Mg, S was carried out
at rates which ensured that there would be no deficiency. Phytosanitary protection was complete
and effective. Meteorological data were continu-
Table 1 Dates and amounts of fertiliser applied to the three oilseed rape crops in kg N ha
− 1
Date and development stage Total
Treatment 150395
290395 120994
200295 inflorescence formation
16 leaves stem elongation
sowing N0
78 N135
135 57
272 38
107 78
N270 49
ously recorded on site: incoming radiation R, air temperature, potential evapotranspiration, rain.
Linear and non-linear regression fittings were done using the REG and the NLIN procedures of
the SAS software, respectively SAS Institute Inc., 1987.
2
.
2
. Plant measurements At 17 dates throughout the growth of the crop
emergence to harvest three plots of 0.435 m
2
were sampled per block two contiguous rows of 0.75 m length. Sampling frequency varied from 2
to 4 weeks, depending on growing conditions. Depending on which organs were present, each
sample was separated into several fractions: roots mainly taproots, stems, branches, green leaves,
senescent leaves, dead leaves, inflorescences, and pods. Leaves were considered senescent when they
were more than half discoloured, and dead when they were very easily detached from the axis. The
ADM consisted of all the green and senescent aerial parts present on the plant. The mass of
dead leaves falling on the soil was estimated by collecting the dry matter of the leaves which had
fallen on the soil DDM = dead DM, on previ- ously
installed plastic
mesh, twice
a week
throughout the growth period for all three treatments.
Also, by using core sampling of the soil, and washing
out and
weighing the
root mass
RDM = root dry matter was measured twice in early spring and at flowering: the dry weight of
fine roots was very small B 10 by comparison with the taproot, and thus negligible. Hence the
TDM was calculated by adding ADM + RDM, and the generated total dry matter gTDM was
obtained by summing TDM with DDM for each sampling date.
The developmental stages of the crop were recorded using the INRA-CETIOM phenological
scale INRA-CETIOM, 1988. Each of the plant fractions was dried at 80°C in
a forced-draught oven to constant weight and then weighed. After grinding, the total N content
was measured Dumas method for each fraction and the weighted average N content of the aerial
parts was calculated.
2
.
3
. Measurements of area indices The areas of the leaves and pods were measured
by planimetry Li-Cor, Delta-T devices, or Ayashi Denko optical planimeter, with the lamina and
petiole together. The green leaf area index green LAI was calculated as the ratio of measured leaf
area to the area of soil sampled; the same was done for the pods PAI for pod area index. The
flower area index FAI was estimated as the product of the mean flower size and the number
of flowers present per unit area of soil. The num- ber of flowers was calculated from day to day
after counting the number of flowering axes main stems and branches and measuring the dynamics
of flower generation and the mean lifespan of a flower. It was confirmed that the area of a single
flower area of four petals is stable whatever the position of the flower in the canopy, and for all
treatments, as already established by Yates and Steven 1987 and Habekotte´ 1997b; the value
found for the cultivar Goe´land was 1.99 cm
2
flower
− 1
. The rate of flower production on the main stem was measured at 17.2 flowers 100°C
day
− 1
base 0°C and 24 flowers 100°C day
− 1
for N135 and N270, respectively; it was however less
on the side branches: 12.8, 14.7 and 16.2 flowers 100°C day
− 1
for N0, N135 and 270 respectively.
2
.
4
. Calculation of PAR absorbed by the canopy As one wanted to estimate the efficiency of
conversion of radiation absorbed by the green parts of the plant which were photosynthetically
active leaves and pods, the absorbed PAR PARa was calculated day by day for each layer
of the green canopy green LAI, PAI and FAI following the three layers radiation balance
scheme proposed by Chartier et al. 1983 Fig. 1. The absorbed radiation PARa
X
of each homo- geneous layer X was calculated using a form of
Beer’s Law, as follows: PARa
X
= PAR
X
× 1 − r
X
× [1 − e
− K
X
× XAI
] 1
Where PAR
X
is the radiation incident on the layer X, r
X
is the reflection coefficient of the layer X considered, K
X
is the radiation extinction coeffi-
Fig. 1. Crop radiation balance using a 3-layer model adapted from Chartier et al., 1983.
below or the soil. During flowering, this calcula- tion involves the calculation of the radiation
reflected and transmitted by flowers; the calcula- tion was made using the method proposed by
Habekotte´ 1997b, taking account of two spectral bands: a 400 – 525 nm and b 525 – 700 nm. Only
first-order reflections are considered. The calcula- tion was made for each day, from daily incoming
radiation for the day and canopy LAI, with the latter linearly interpolated between sampling
dates. The values of the various parameters in- volved are shown in Table 2. The photosyntheti-
cally active radiation PAR was estimated as 50 of the total incoming radiation R measured on
the site Varlet-Grancher et al., 1989.
The cumulative PARa for the three layers PARa was calculated on a daily basis for the
time interval between two sampling dates, which required to interpolate LAI and PAI between
these two dates. In view of the quite frequent samplings, linear interpolation was used, based on
degree-days with a base of 4.5°C Gabrielle et al., 1998b.
Given that the row arrangement of the crop influences radiation interception at the beginning
of growth LAI 5 1.5, the ground cover ratio was cient, and XAI is the index for the layer AI =
area index, m
2
m
− 2
. The subscript X corresponds to: L for green LAI, P for PAI and F for FAI.
The incident radiation PAR
X
is the sum of the radiation transmitted by the layer above or the
atmosphere and that reflected from the layer
Table 2 Value and references of parameters used in the calculation of the radiative balance for each layer of the oilseed rape crop
a
References Parameter
Layer Value of parameter
0.772 Kf
a
Kf FAI
Habekotte´ 1997b Kf
b
0.506 Andersen et al. 1996
PAI Kp
0.5 Mean of references values from:
LAI Kl
0.75 Mendham and Salisbury 1995
0.5–0.6 Morrison and Stewart 1995
0.65 0.71
Child and Butler 1987 cited by Hough 1990 Chartier et al. 1983
0.85 0.903
Habekotte´ 1997b r
l or r
p 0.05
LAI and PAI canopy level Mean of references values from:
0.047 Yates and Steven 1987
0.03–0.06 Leach et al. 1989
r f
r f
a
FAI organ level 0.035
Habekotte´ 1997b r
f
b
for PAR spectral band a or b 0.45
t f
a
t f
0.035 t
f
b
0.15 r
s Cellier et al. 1996
Soil 0.2
a
Significance of parameters: K = extinction coefficient, r = reflection coefficient or albedo; t = transmission coefficient. See text for more details.
taken into account Chartier et al., 1983. Thus, to account for the variation in ground cover until
the stem elongation phase, an effective index of ground cover was introduced to estimate the in-
tercepted radiation Jones, 1992, and Eq. 1 was applied within the row. The LAI, measured over
the whole plot, was thus related to the fraction occupied by the row within the plot, according to
a formula derived from Eq. 1:
PARa
L
= GCR × PAR
L
× 1 − r
L
× {1 − e
[ − K
L
× LAIGCR]
} 2
where GCR is the ground cover ratio unitless. The ground cover ratio was estimated for the
eight first sampling dates, from numerical treat- ment of digitised picture taken at a 1.5 m height
above the ground. Between measurements, the GCR was interpolated using a regression of LAI
on GCR obtained from the sampling dates.
2
.
5
. Calculation of RUEa In principle, RUEa may be calculated between
two successive sampling dates as the ratio of crop dry matter production to total absorbed PAR
over the corresponding time period. Here, dry matter
production was
calculated from
the changes in generated dry matter gTDM, as de-
scribed in the ‘plant measurements’ section. Al- though the measurements of gTDM were quite
precise CVs B 15, the RUEa values thus ob- tained were affected by a significant random vari-
ation, with a saw-tooth pattern. This may be explained by errors propagating from one time
interval to the next. For instance, if gTDM was under-estimated on one sampling date, then
RUEa was accordingly under-estimated on the time interval preceding this sampling, and over-es-
timated on the following time interval. In order to smooth this variability, one chose to estimate
RUEa over longer time periods spanning two to three sampling dates, and corresponding to differ-
ent development stages. Here, RUEa was taken as the slope of the linear regression unconstrained
between cumulative gTDM production and ab- sorbed PAR, over these time intervals.
2
.
6
. Calculation of NNI The N nutritional status for each treatment was
quantified using the NNI Lemaire and Gastal, 1997 which is calculated as follows:
NNI = NmNc 3
where Nm is the measured total N concentration for all the aerial parts and Nc is the critical total
N concentration calculated for the value of ADM measured in situ; Nm and Nc are expressed as
of ADM. Nc is the minimum N concentration needed to obtain the maximum dry matter pro-
duction by the crop. Nc is regarded as constant for low biomasses, and subsequently drops as
ADM increases, according to a relationship known as ‘N dilution’. It can be used for a large
number of herbaceous species: wheat, maize, for- age grasses, lucerne, peas, barley, durum wheat,
sorghum etc. Although N dilution is a general phenomenon, parameters of the critical N dilution
curve must be determined for each crop species Lemaire and Gastal, 1997. Nc has been estab-
lished for oilseed rape by Colnenne et al. 1998 from juvenile stages up to flowering, correspond-
ing to values of ADM from 0.2 to 6.3 t ha
− 1
: Nc = 4.63
if ADM 5 0.88 t ha
− 1
4a Nc = 4.48 × ADM
− 0.25
otherwise 4b
NNI was calculated for each sampling date and was then averaged for the period of two to three
measurement dates corresponding to the calcula- tion of RUEa as a function of development stage.
A value of NNI ] 1 indicates a crop with ample N supply N non-limiting; NNI = 1 represents
optimal N nutrition. The more NNI falls below 1, the more deficient is the crop in N.
3. Results
