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Modelling N mineralization of vegetable crop residues during laboratory incubations
PII:
Soil Eiol. Biochem. Vol. 28, No. 10/l I, pp. 1451-1457, 1996 Copyright 0 1996 Elsevier Science Ltd Printed in Great Britain. All rights reserved 0038-0717/96 $15.00 + 0.00 soo38-0717(%)00154-x
MODELLING N MINERALIZATION OF VEGETABLE CROP RESIDUES DURING LABORATORY INCUBATIONS S. DE NEVE* and G. HOFMAN University of Ghent, Department of Soil Management and Soil Care, Division of Soil Fertility and Soil Data Processing, Coupure Links 653, 9000 Gent, Belgium (Accepted
24 May 1996)
S~IMI~~~--A range of vegetable crop residues were subjected to a modified Stevenson chemical fractionation. N mineralization parameters were determined for the fractionated crop residue components from aerobic laboratory incubations. Fresh chopped crop residues were incubated with soil at fixed temperature and soil moisture content. N mineralization (both NH&N and NOT-N) was measured over a 3-4 month period (depending on degradability) at regular intervals. The first order kinetic model N(t) = NA (1 - e-“) was fitted to the mineralization data of total N (parameters NA and k) and of organic N (parameters NAeorsand korg). Both the amount of mineralizable N (NA) and the rate constant k differed widely between the residues. The amount of mineralizable organic N (N.+& was better correlated to chemical composition than the amount of mineralizable total N (NA). The parameter N ,~rs was best related to the C-to-N ratio of the lignin (78% of the total variance of NA,org explained). Good correlations were also observed with lignin content (r = 0.863) and with the water soluble fraction (r = 0.861). The rate constant kors was much less predictable. It was related negatively to the relative amount of organic N (relative to total N) contained in the residues. The mode1 presented can be used to calculate the amount of N mineralized at any specified time after incorporation of the residues under the experimental conditions used. Prediction of N mineralization improves with time of incubation of the residues because the influence of the rate constant diminishes. The critical C-to-N ratio, i.e. the break point between net N mineralization and net N immobilization (NA = 0), was calculated to be at a C-to-N ratio of 44. Copyright 0 1996 Elsevier Science Ltd
INTRODUCI’ION Knowledge of nitrogen (N) mineralization from different organic sources (soil organic matter, crop residues, manures, slurry) is a key factor in developing efficient predictions of the need for N fertiliza-
tion. Much research has been conducted on the relationship between N mineralization and chemical characteristics (or quality) of crop residues. Significant correlations are reported between percentage N mineralization of crop residues and N-content (Vigil and Kissel, 1991; Constantinides and Fownes, 1994), C-to-N ratio (Frankenberger and Abdelmagid, 1985; Vigil and Kissel, 1991), lignin content or lignin-C (Frankenberger and Abdelmagid, 1985; Kirchmann and Bergqvist, 1989; Honeycutt et al., 1993), polyphenol content (Palm and Sanchez, 1991) or combinations of these factors such as lignin-to-N (Vigil and Kissel, 1991; Constantinides and Fownes, 1994), polyphenol-to-N (Palm and Sanchez, 1991) or (lignin + polyphenol)to-N ratio (Fox et al., 1990; Constantinides and Fownes, 1994). However, Fox et al. (1990) did not observe significant relationships between N mineralization and N-content, lignin, polyphenol or lignin*Author for correspondence. Tel.: 0032 9 264 60 61 Fax.: 0032 9 264 62 47 E-mail: [email protected].
to-N ratio. Palm and Sanchez (1991) found no relationship with N-content or lignin. These conflicting results are partly due to differences in ranges of the chemical variables considered in these studies, the range of residues studied, but also to differences in methodology used. Mostly this research was limited to a static relationship between mineralization and chemical composition, i.e. a relationship which is established between chemical composition and mineralization after a fixed time. Therefore differences in incubation time will affect the amount of N mineralized and thus the relationships with chemical composition. This is a serious limitation if such mineralization models are to be used to predict the whole N mineralization process. Frankenberger and Abdelmagid (1985) calculated mineralization potentials and rate constants of leguminous crops, but did not attempt to predict these mineralization parameters from chemical composition. Moreover most of this research deals with the major agricultural crops and green manures. Less is known about N mineralization from vegetable crop residues. However, vegetable crop residues often contain high amounts of N as compared to other crop residues and thus can potentially release large amounts of mineralized N. Previous experiments by De Neve et al. (1994) have shown that it is difficult to derive
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S. De Neve and G. Hofman
mineralization parameters from field experiments because of high spatial variability and problems in accurately measuring leaching and denitrification. We have used a chemical fractionation method to predict N mineralization parameters for some important vegetable crop residues during laboratory incubations. The model derived can be used to predict the amount of N mineralized at any specified time after residue incorporation, under the experimental conditions specified.
MATERIALS AND METHODS
Plant chemical analysis and fractionation The crop residues used in the trials are given in Table 1. They represent a wide range of important field grown vegetable crops. For several crop residues plant parts such as leaf-blades, leaf-stalks, upper and lower parts of stems and roots were differentiated. Because of differences in chemical composition it was expected that the different parts of a crop would mineralize differently as well. The crop residues were analysed for dry matter, total N by the Kjeldahl method, mineral N by extraction with 1 N KC1 followed by calorimetric analysis with a continuous flow auto-analyzer, and ash content. The chemical fractionation method of Stevenson (1965) was modified to be used for fractionation of dried and ground crop residues. The fractionation procedure yields six fractions: lipids (ether extraction for 24 h), resins (alcohol extraction, reflux for 2 h), water soluble fraction (water extraction, reflux for 2 h), hemicellulose (hydrolysis with 2% HCI, reflux for 5 h), cellulose (hydrolysis with 80% HzS04 for 2.5 h, followed by dilution with distilled water to 1.42 M and reflux for 5 h) and lignin (the final residue). Each extraction was performed on the residue of the previous treatment. For each fraction ash content and total N content were determined.
This fractionation differed from that used by De Neve et al. (1994) in that all fractions were now determined gravimetrically (including fractions 4 and 5). Incubations The soil used in the incubations is a loamy sand soil from Pittem (West-Flanders) on which chicory has been grown for several years. The soil has a pHkcr of 5.75, a C content of 1.14% and a total N content of 0.097%. The soil was sampled at a moisture content above field capacity (gravimetric moisture content at FC was 17%) and was allowed to dry to a moisture content of 80% of FC. The soil was not air dried and not sieved in order to minimize disturbance of microbial activity. The fresh crop residues were chopped into small pieces of approximately 0.5 cm*. For the incubation trials plastic tubes with an inner dia. of 46.3 mm were used. The tubes were filled with 317 g of moist (80% of FC) soil mixed thoroughly with 6 g of the fresh chopped crop residues. The soil-crop residue mixture was then compacted to obtain a bulk density of 1.4 g cmp3, which was also the density of the upper layer of this soil in situ. The water filled pore space (WFPS) of the samples was 40% (bulk density is 1.4 and assuming a soil particle density of 2.65). The tubes were covered with a single layer of gas permeable parafilm (in order to minimize water loss) and weighed. The tubes were stored at a temperature of 17°C. This temperature was chosen because it is approximately the soil temperature in late summer or early autumn (when most of the vegetable crop residues are incorporated). A series of blanks (i.e. tubes with soil but without crop residues) was included as a control. The moisture content was checked monthly by reweighing the tubes but no water additions were required. Sampling took place by removing intact tubes. Samples were removed in three replicates
Table I. Chemical composition of the vegetable crop residues studied Crop residue
Dry matter (%)
Ash (% of DM)
Beans leaves Beans stems
22. I 20.7 14.7 9.5 18.6 16.5 12.9 7.4 II.6 13.4 8.3 6.5 13.2 13.7 14.1 15.2
22.8 12.4 23.7 19.0 12.1 29.4 22. I 49.0 20.6 21.3 45.9 23.9 25.8 22.5 17.0 17.9
Broccoli leaf-blades Broccoli stem upper part Broccoli stem lower part Celery leaves Turnip leaf-blades Endive leaves Endive roots Red cabbage leaves Lettuce leaves Lettuce stems Savoy cabbage leaves Fennel leaves Cauliflower leaf-blades Cauliflower stems
“N,,, is the total N content of the residues. blV,,n is the initial mineral N content of the residues
39.5 17.6 45.5 26.4 14.7 24.2 39.2 23.7 23.7 24.0 29.9 30. I 33.9 38.5 35. I 28.2
N”,,. (mg g&I
C-to-N ratio
I.11 I .97 I .20 7.44 2.1 I I .62 0.34 7.51 6.61 I .55 6.63 13.2 3.48 4.59 I .05 5.42
9.8 24.9 8.4 IS.3 30.0 14.6 10.0 10.8 16.8 16.4 9.1 12.6 10.9 IO.1 II.8 14.6
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N mineralization of vegetable crop residues tubes per crop residue), extracted with KC1 and analyzed for NOT-N and NH&N with a continuous flow auto-analyzer.
(three
Data analyses
The net N mineralization from the crop residues was calculated by subtracting total extractable N in the blank soil from that in the residue-amended soil. At each sampling time means and standard errors of the means (as percentage of total added residue N) were calculated. Fitting of the first order model to the net mineralization of total and organic N and calculation of a Pearson correlation matrix and linear regression equations between chemical plant parameters and the parameters of the first order model were performed using SYSTAT (Wilkinson, 1990). Fig. 2. Net N mineralization from the crop residues. RESULTS AND DISCUSSION Incubation experiments
Fractionations
The initial mineral N content of the soil was sufficiently low to adequately detect net N mineralization from the residues (Figs l-3). There was a wide variety in mineralization behaviour between the various crop residues and residue parts. The large differences in mineralization pattern between the different parts of one crop residue show that it was useful to incorporate these parts separately. This was particularly true for stems and leaves of beans and the upper and lower part of stems of broccoli. For most crop residues there was a small peak in NH: formation (relative to the unamended soil) after 2 weeks of incubation, but after 1 month the amounts of NH; measured were negligible. The fast disappearance of NH: from the residue-treated soils indicates that there were no anaerobic conditions during the trial. No net immobilization was observed with any of the crop residues.
The structural composition of the vegetable crop residues was very different (Table 2), except the hemicellulose fraction, which was relatively constant, varying mainly between 30 and 40% of organic matter. Stems of beans and cauliflower, the lower part of stems of broccoli and roots of endive had high or very high lignin contents and a low water-soluble fraction. No significant amounts of N were recovered in lipid and resin fractions. The bulk of the N was contained in the water-soluble and hemicellulose fraction.
0
3
6
&eob)
12
15
10
Time
N mineralization kinetics model A N mineralization model was fitted to the measured data of residue mineralization. The shape of the mineralization curves is similar to the typical shape described by the single first order kinetics model N(t) = NA (1-emk’), in which NA is the
00 0
3
B
12
15
Time (kkr)
Fig. 1. Net N mineralization from the crop residues. Bars represent standard errors.
Fig. 3. Net N mineralization from the crop residues.
I
1454 Table 2. Results
S. De Neve and G. Hofman of the modified
Crop residue Beans leaves Beans stems Broccoli leaf-blades Broccoli stem upper part Broccoli stem lower part Celery leaves Turnip leaf-blades Endive leaves Endive roots Red cabbage leaves Lettuce leaves Lettuce stems Savoy cabbage leaves Fennel leaves Cauliflower leaf-blades Cauliflower stems
Stevenson
fractionation (bracketed values are N contents total N in the crop residues).
of the different
Fractions (%
of fractions
Lipids
Resins
3.5 1.4 6.8 1.2 0.9 3.8 6.1 3.3 2.2 4.7 4.3 2.9 4.0 3.6 4.2 0.7
4.4 2.2 4.9 3.8 I.6 12.4 6.1 3.8 3.2 12.9 10.5 6.2 7.1 5.5 II 4 3.0
of organic matter) and N content Water-soluble fraction 29.1 (43) 13.6 (54) 24.4 (28) 18.6 (57) 9.2 (43) 30.4 (23) 27.6 (26) 23.0 (31) 15.9 (46) 30.4 (34) 30.2 (44) 27.0 (50) 28.7 (37) 28.4 (23) 28.1 (23) 11.4 (49)
amount of mineralizable N (expressed as percentage of total residue N), k is the rate constant and t is the time from the start of the incubation. The simple first order model has several advantages over more complicated models. There is no need to input initial estimates of the parameters and a limited number of mineralization data, even with high variability, will let the model converge. The results of the curve fitting are given in Table 3. The parameters NA and k in Table 3 are based on the mineralization data of total N, i.e. both organic and inorganic N contained in the residues. Because some of the residues contain relatively high amounts of mineral N (Table l), also the net mineralization ~ensu strict0 (i.e. mineralization of organic N from the residues) was calculated. From the measurements at all sampling times O-3 amount of mineral N in the residues was subtracted in order to obtain the amounts of organic N mineralized. This assumes that all mineral N contained in the crop
Table
Hemi-cellulose fraction 38.4 32.4 41.8 33.5 34.6 30.7 38.0 35.5 33.6 30.1 32.1 30.5 36.2 37.3 38.7 35.9
expressed
in % of
(% of total N)
Cellulose
(40) (32) (58) (34) (27) (58) (61) (50) ;36j (55) (40) (38) (51) (63) (63) (39)
fractmns,
fraction
10.7 (IO) 21.3 (3) 7.9 (5) 24.1 (4) 23.2 (19) 5.9 (4) 5.0 (4) 22.6 (6) 21.5 (5) 9.0 (2) 13.3 (8) 20.8 (5) 9.6 (5) 9.6 (4) 7.2 (3) 17.0 (4)
Lignin fraction 13.9 (7) 29.2 (I I) 14.3 (8) 18.2 (5) 30.5 (II) 16.8 (15) 17.5 (9) II.8 (13) 23.6 (13) 13.0 (9) 9.7 (8) 12.6 (7) 14.4 (7) 15.6 (IO) 9.8 (I I) 26.0 (8)
residues was released or at least measured from the first sampling time and that further release of mineral N was entirely due to mineralization of organic N. Because the crop residues were cut into small pieces this seemed a reasonable assumption. The first order model was then also fitted to the mineralization data of organic N. The parameters NA,org (the amount of mineralizable organic N expressed in percentage of organic N) and korg (the rate constant for mineralization of organic N) are also given in Table 3. For the crop residues which contain important amounts of mineral N, the model parameters for mineralization of total and organic N differed significantly. Relationship between N mineralization and chemical composition The chemical composition and N mineralization of the residues were used to establish a quantitative relationship for predicting net N mineralization
3. Parameters of the first order model fitted to the mineralization data (k (k,,,) = rafe constant for mineralization of total (orgamc) N; NA (N~.ors ) = mineralizable N as percentage of total (organic) N; bracketed values represent standard deviation)
Crop residue Beans leaves Beans stems Broccoli leaf-blades Broccoli stem upper part Broccoli stem lower part Celery leaves Turnip leaf-blades Endive leaves Endive roots Red cabbage leaves Lettuce leaves Lettuce stems Savoy cabbage leaves Fennel leaves Cauliflower leaf-blades Cauliflower stems
k (week-‘) 0.293 (0.014) 0.313 (0.035) 0.635 (0.033) 1.687 (I ,069) 0.872 (10.978) 0.272 (0.038) 0.525 (0.022) 1.092 (0.232) I.306 (0.168) 0. I87 (0.065) 1.305 (0.880) 1.256 (0.226) 0.325 (0.017) 0.635 (0.070) 0.410 (0.093) I. 108 (0.369)
NA (% of total N) 56.0 25.0 59.6 55.0 34.7 65.5 61.7 76.9 60.4 62.3 67.2 86.3 78.0 76.4 73.2 42.2
(0.5) (0.7) (I .3) (0.8) (4.3) (1.3) (1.8) (3.0) (3.2) (3.6) (9.6) (1.7) (5.5) (1.1) (5.5) i2.5j
korg(week-‘)
N ~.org(% of N,,)
0.269 (0.0 15) 0.122 (0.004) 0.607 (0.037) 1.002 (0.951) 0.506 (10.844) 0.234 (0.037) 0.516 (0.022) 0.678 (0.141) 0.838 (0.183) 0.163 (0.073) 1.020 (0.840) 0.752 (0.269) 0.266 (0.01 I) 0.520 (0.061) 0.414 fO.090) 0.296 (0.396j
55.2 (0.4) 17.7 (1.5) 58.5 (1.5) 36.2 (1.5) 23.9 (5.2) 64.0 (1.8) 61.4 (8.9) 66.8 (4.5) 43.4 (5.2) 60.8 (6.6) 57.3 (12.7) 75.5 (2.0) 76.8 (6.3) 73.7 (1.3) 72.3 (5.3) 30.9 (4.2)
N mineralization of vegetable crop residues
from the residues at any specified time after incorporation. A Pearson correlation matrix (Wilkinson, 1990) and linear regression equations were calculated between selected parameters or combinations of parameters reflecting plant chemical composition and the parameters of the first order model (Table 4). For mineralization of total N the best correlation to N,.+ was with lignin content; an equally good correlation was obtained with the Cto-N ratio of the lignin. Good correlation to NA was observed with a factor defined by Herman et al. (1977) to describe C mineralization from grass species, namely lignin times C-to-N ratio over the root square of the water soluble fraction (r = - 0.773, P < 0.001). Correlation with C-to-N ratio was rather good but correlation with total N content was not significant (Table 4) and much weaker than for data obtained 4 weeks after field incorporation of vegetable crop residues (De Neve et al., 1994). The weak correlation between N mineralization and N content is probably due to the relatively small range in N contents of the crop residues considered here (total N content varying mainly between 25 and 35 mg g-’ dry matter). Regressions between mineralizable organic N and chemical parameters were more significant than for mineralization of total N for all chemical parameters studied (Table 4). The best relationship was between N~,~rs and the C-to-N ratio of the lignin. Other good correlations to N..~,rs were observed with lignin content and with the water soluble fraction. Correlation with C-to-N ratio was good but correlation with total N content was again much weaker. Addition of more chemical parameters to the regression did not result in a significant decrease of the residual variance. There were no obvious curvilinear relationships between chemical composition and NA or NA,org.
1455
The rate constants k and k,, were more difficult to predict from chemical parameters. The best linear relationship was with the percentage of organic N in the residues (Table 4). The following model is proposed to predict net mineralization of organic N from incorporated vegetable crop residues: Norg(t) = (76.6 - 0.653 C - to - N,ir”i”) -(1.73-0.0144N,&r)
x(1-e
In this equation N,,,(r) is the percentage of organic N mineralized at time f, C-tO-N1isnin is the Cto-N ratio of the lignin fraction and Nors is the amount of organic N in the crop residues (expressed in percentage of total N). Assuming that all mineral N contained in the residues is released in the period before the first measurement, the total amount of N released is then given by: + N O’K (t)
N(r) = Nml”
N 100
.2%
In this equation N(t) is the percentage of total residue N released at time t, Nmin is the initial amount of mineral N in the crop residues (expressed in percentage of total N), and N&t) and Nors are as defined in equation (1). In Figs 4 and 5 the percentages of organic N mineralized after 2 and 16 weeks as given by the experimentally determined values of N~,~rs and korg (Table 3) and as calculated by the proposed mode1 (equation (1)) are compared. The correlation between predicted (model) and measured values improves from 0.821 after 2 weeks to 0.882 at the end of the incubation (16 weeks). This is due to the fact that the importance of the rate constant decreases with time of incubation, and it is the rate constant that has the highest prediction error.
Table 4. Linear regression equations between mineralization parameters and selected chemical properties of the residues (FR3 = water-soluble fraction, FR6 = lignin content, N,,, = total N content in % of dry matter, C-toN = global C-to-N ratio, C-to-N,is,,i, = C-to-N ratio of lignin fraction, Nors = organic N content in % of N,,,) Mineralization parameters
Regression equations and correlation coefficients
NA
17.8 + 1.81.FR3 91.3 - 2.09.FR6 33.9 + 9.15.N,,, 89.7 - 2.03.(C-to-N) 79.3 - 0.542.(C-to-N,is,i,)
r = 0.746”’ r = - 0.833”’ r = o.470”‘s. I = - 0.723” r = - 0.833”’
NAorg
-1.99 + 2.37.FR3 91.2 - 2.46.FR6 15.9 + 13.1.N,,, 88.6 - 2.41.(C-to-N) 76.6 - 0.653.(C-to-N,,,i.)
, r r r r
= 0.861”’ = - 0.861”’ = 0.591’ = - 0.757”’ = - 0.882”’
k
4.37 - 0.041 I.N,,
I = - 0.626”
k ore
1.73 - 0.0144.N,,,
r = -0.631”
‘P c 0.05, l*p < 0.01, ***p < 0.001.
(1)
1456
z
S. De Neve and G. Hofman
20
.o i
G 0
. I ’
r = 0.821
l
.
.
,
0
I
I
I
20
40
60
80
% organic N mineralized after 2 weeks: model calculations
Fig. 4. Comparison between percentages of organic residue N mineralized after 2 weeks of incubation as calculated from the mineralization parameters in Table 3 and from the model (equation (1)). The line is the bisector.
Several researchers have attempted to give critical C-to-N ratios for N mineralization, i.e. the C-to-N ratio at the break point between net N mineralization and net N immobilization. Values in literature range from C-to-N = 20 for 4 week incubations (Iritani and Arnold, 1960), to C-to-N = 30 (Fox et al., 1990) or C-to-N = 40 for long term incubations of 11 to 44 weeks (Vigil and Kissel, 1991). Critical C-to-N ratios depend on the duration of the incubation considered. Das et al. (1993) observed a critical C-to-N ratio of 46 after 30 days at FC. This value increased to 95 after 120 days of incubation. Janzen and Kucey (1988) found the critical C-to-N ratio to increase from 24 to 41 after 14 and 84 days of incubation, respectively. In our study the C-to-N 00
,
I
.
l
.Y
*I
. l
**
l
,
m-
l
)/
,j
, . 20 -
r = 0.882
.
0
I 0
20
% organic N mineralized
I
I
40
60
80
after 16 weeks: model calculations
Fig. 5. Comparison between percentages of organic residue N mineralized after 16 weeks of incubation as calculated from the mineralization parameters in Table 3 and from the model (equation (1)). The line is the bisector.
ratio can be used to predict values of NA or NA,org (which are independent of time of incubation, within certain limits). The (critical) C-to-N ratio that would give neither mineralization nor immobilization (NA = 0) here is 44 (Table 4). This is a relatively high value but it corresponds to those found by Vigil and Kissel (1991) and Janzen and Kucey (1988) for prolonged incubations. The strength of the N mineralization model presented here is that the relationship between chemical parameters and net N mineralization is independent of the duration of the incubation because they are linked to the parameters from the first order model. In this way net N mineralization can be predicted at any given time after residue incorporation. It should be stressed that the model proposed here was developed for predicting the mineralization of vegetable crop residues. Further research including residues with completely different characteristics such as straw or composts should be undertaken to see whether their mineralization pattern fits the model as well. The mineralization process will of course be influenced by important factors such as temperature, soil moisture content, soil bulk density and possibly others, which will have to be taken into account when they differ from the conditions specified here. Acknowledgements-Financial support by the EC is gratefully acknowledged (EC project No. 800l-CT91-0115).
REFERENCES
Constantinides M. and Fownes J. H. (1994) Nitrogen mineralization from leaves and litter of tropical plants: relationships to nitrogen, lignin and soluble polyphenol Soil Biology and Biochemistry 26, 49-55. concentrations. Das S. K., Subba Reddy G., Sharma K. L., Vittal K. P. R., Venkateswarlu B., Narayana Reddy M. and Reddy Y. V. R. (1993) Prediction of nitrogen availability in soil after crop residue incorporation. Fertilizer Research 34, 209-215. De Neve S., Pannier J. and Hofman G. (1994) Fractionation of vegetable crop residues in relation to in situ N mineralization. European Journal of Agronomy 3, 261-272. Fox R. H., Myers R. J. K. and Vallis I. (1990) The nitrogen mineralization rate of legume residues in soil as influenced by their polyphenol, lignin and nitrogen contents. Plant and Soil 129, 251-259. Frankenberger W. T. and Abdelmagid H. M. (1985) Kinetic parameters of nitrogen mineralization rates of leguminous crops incorporated into soil. Plant and Soil 87, 257-271.
Herman W. A., McGill W. B. and Dormaar J. F. (1977) Effects of initial chemical composition on decomposition of three grass species. Canadian Journal qf Soil Science 57, 205-2 15. Honeycutt C. W., Potaro L. J., Avila K. L. and Halteman W. A. (1993) Residue quality, loading rate and soil temperature relations with hairy vetch (Vicia villosa Roth) residue carbon nitrogen and phosphorus mineralization. Biological Agriculture and Horticulture 9, 18 I-199.
N mineralization of vegetable crop residues Iritani W. M. and Arnold C. J. (1960) Nitrogen release of vegetable crop residues during incubation as related to their chemical composition. Soil Science 89, 74-82. Janzen H. H. and Kucey R. M. N. (1988) C, N, and S mineralization of crop residues as influenced by crop species and nutrient regime. Plant and Soil 106, 35-41. Kirchmann H. and Bergqvist R. (1989) Carbon and nitrogen mineralization of white clover plants (Trifolium repens) of different age during aerobic incubation with soil. Zeitschrift ftir Pjanzenerntihrung und Bodenkunde 152, 283-288.
Palm C. A. and Sanchez P. A. (1991) Nitrogen release from the leaves of some tropical legumes as affected by
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their lignin and polyphenolic contents. Soil Biology and Biochemistry 23, 83-88.
Stevenson F. J. (1965). Gross chemical fractionation of organic matter. In Methodr of Soil Analysis, Part 2 (C. A. Black, Ed.), pp. 1409-1421. American Society of Agronomy, Madison. Vigil M. F. and Kissel D. E. (1991) Equations for estimating the amount of nitrogen mineralized from crop residues. Soil Science Society of America Journal 55, 757761.
Wilkinson, L. (1990) SYSTAT: the system for statistics. Systat Inc., Evanston, IL.
Soil Eiol. Biochem. Vol. 28, No. 10/l I, pp. 1451-1457, 1996 Copyright 0 1996 Elsevier Science Ltd Printed in Great Britain. All rights reserved 0038-0717/96 $15.00 + 0.00 soo38-0717(%)00154-x
MODELLING N MINERALIZATION OF VEGETABLE CROP RESIDUES DURING LABORATORY INCUBATIONS S. DE NEVE* and G. HOFMAN University of Ghent, Department of Soil Management and Soil Care, Division of Soil Fertility and Soil Data Processing, Coupure Links 653, 9000 Gent, Belgium (Accepted
24 May 1996)
S~IMI~~~--A range of vegetable crop residues were subjected to a modified Stevenson chemical fractionation. N mineralization parameters were determined for the fractionated crop residue components from aerobic laboratory incubations. Fresh chopped crop residues were incubated with soil at fixed temperature and soil moisture content. N mineralization (both NH&N and NOT-N) was measured over a 3-4 month period (depending on degradability) at regular intervals. The first order kinetic model N(t) = NA (1 - e-“) was fitted to the mineralization data of total N (parameters NA and k) and of organic N (parameters NAeorsand korg). Both the amount of mineralizable N (NA) and the rate constant k differed widely between the residues. The amount of mineralizable organic N (N.+& was better correlated to chemical composition than the amount of mineralizable total N (NA). The parameter N ,~rs was best related to the C-to-N ratio of the lignin (78% of the total variance of NA,org explained). Good correlations were also observed with lignin content (r = 0.863) and with the water soluble fraction (r = 0.861). The rate constant kors was much less predictable. It was related negatively to the relative amount of organic N (relative to total N) contained in the residues. The mode1 presented can be used to calculate the amount of N mineralized at any specified time after incorporation of the residues under the experimental conditions used. Prediction of N mineralization improves with time of incubation of the residues because the influence of the rate constant diminishes. The critical C-to-N ratio, i.e. the break point between net N mineralization and net N immobilization (NA = 0), was calculated to be at a C-to-N ratio of 44. Copyright 0 1996 Elsevier Science Ltd
INTRODUCI’ION Knowledge of nitrogen (N) mineralization from different organic sources (soil organic matter, crop residues, manures, slurry) is a key factor in developing efficient predictions of the need for N fertiliza-
tion. Much research has been conducted on the relationship between N mineralization and chemical characteristics (or quality) of crop residues. Significant correlations are reported between percentage N mineralization of crop residues and N-content (Vigil and Kissel, 1991; Constantinides and Fownes, 1994), C-to-N ratio (Frankenberger and Abdelmagid, 1985; Vigil and Kissel, 1991), lignin content or lignin-C (Frankenberger and Abdelmagid, 1985; Kirchmann and Bergqvist, 1989; Honeycutt et al., 1993), polyphenol content (Palm and Sanchez, 1991) or combinations of these factors such as lignin-to-N (Vigil and Kissel, 1991; Constantinides and Fownes, 1994), polyphenol-to-N (Palm and Sanchez, 1991) or (lignin + polyphenol)to-N ratio (Fox et al., 1990; Constantinides and Fownes, 1994). However, Fox et al. (1990) did not observe significant relationships between N mineralization and N-content, lignin, polyphenol or lignin*Author for correspondence. Tel.: 0032 9 264 60 61 Fax.: 0032 9 264 62 47 E-mail: [email protected].
to-N ratio. Palm and Sanchez (1991) found no relationship with N-content or lignin. These conflicting results are partly due to differences in ranges of the chemical variables considered in these studies, the range of residues studied, but also to differences in methodology used. Mostly this research was limited to a static relationship between mineralization and chemical composition, i.e. a relationship which is established between chemical composition and mineralization after a fixed time. Therefore differences in incubation time will affect the amount of N mineralized and thus the relationships with chemical composition. This is a serious limitation if such mineralization models are to be used to predict the whole N mineralization process. Frankenberger and Abdelmagid (1985) calculated mineralization potentials and rate constants of leguminous crops, but did not attempt to predict these mineralization parameters from chemical composition. Moreover most of this research deals with the major agricultural crops and green manures. Less is known about N mineralization from vegetable crop residues. However, vegetable crop residues often contain high amounts of N as compared to other crop residues and thus can potentially release large amounts of mineralized N. Previous experiments by De Neve et al. (1994) have shown that it is difficult to derive
1451
1452
S. De Neve and G. Hofman
mineralization parameters from field experiments because of high spatial variability and problems in accurately measuring leaching and denitrification. We have used a chemical fractionation method to predict N mineralization parameters for some important vegetable crop residues during laboratory incubations. The model derived can be used to predict the amount of N mineralized at any specified time after residue incorporation, under the experimental conditions specified.
MATERIALS AND METHODS
Plant chemical analysis and fractionation The crop residues used in the trials are given in Table 1. They represent a wide range of important field grown vegetable crops. For several crop residues plant parts such as leaf-blades, leaf-stalks, upper and lower parts of stems and roots were differentiated. Because of differences in chemical composition it was expected that the different parts of a crop would mineralize differently as well. The crop residues were analysed for dry matter, total N by the Kjeldahl method, mineral N by extraction with 1 N KC1 followed by calorimetric analysis with a continuous flow auto-analyzer, and ash content. The chemical fractionation method of Stevenson (1965) was modified to be used for fractionation of dried and ground crop residues. The fractionation procedure yields six fractions: lipids (ether extraction for 24 h), resins (alcohol extraction, reflux for 2 h), water soluble fraction (water extraction, reflux for 2 h), hemicellulose (hydrolysis with 2% HCI, reflux for 5 h), cellulose (hydrolysis with 80% HzS04 for 2.5 h, followed by dilution with distilled water to 1.42 M and reflux for 5 h) and lignin (the final residue). Each extraction was performed on the residue of the previous treatment. For each fraction ash content and total N content were determined.
This fractionation differed from that used by De Neve et al. (1994) in that all fractions were now determined gravimetrically (including fractions 4 and 5). Incubations The soil used in the incubations is a loamy sand soil from Pittem (West-Flanders) on which chicory has been grown for several years. The soil has a pHkcr of 5.75, a C content of 1.14% and a total N content of 0.097%. The soil was sampled at a moisture content above field capacity (gravimetric moisture content at FC was 17%) and was allowed to dry to a moisture content of 80% of FC. The soil was not air dried and not sieved in order to minimize disturbance of microbial activity. The fresh crop residues were chopped into small pieces of approximately 0.5 cm*. For the incubation trials plastic tubes with an inner dia. of 46.3 mm were used. The tubes were filled with 317 g of moist (80% of FC) soil mixed thoroughly with 6 g of the fresh chopped crop residues. The soil-crop residue mixture was then compacted to obtain a bulk density of 1.4 g cmp3, which was also the density of the upper layer of this soil in situ. The water filled pore space (WFPS) of the samples was 40% (bulk density is 1.4 and assuming a soil particle density of 2.65). The tubes were covered with a single layer of gas permeable parafilm (in order to minimize water loss) and weighed. The tubes were stored at a temperature of 17°C. This temperature was chosen because it is approximately the soil temperature in late summer or early autumn (when most of the vegetable crop residues are incorporated). A series of blanks (i.e. tubes with soil but without crop residues) was included as a control. The moisture content was checked monthly by reweighing the tubes but no water additions were required. Sampling took place by removing intact tubes. Samples were removed in three replicates
Table I. Chemical composition of the vegetable crop residues studied Crop residue
Dry matter (%)
Ash (% of DM)
Beans leaves Beans stems
22. I 20.7 14.7 9.5 18.6 16.5 12.9 7.4 II.6 13.4 8.3 6.5 13.2 13.7 14.1 15.2
22.8 12.4 23.7 19.0 12.1 29.4 22. I 49.0 20.6 21.3 45.9 23.9 25.8 22.5 17.0 17.9
Broccoli leaf-blades Broccoli stem upper part Broccoli stem lower part Celery leaves Turnip leaf-blades Endive leaves Endive roots Red cabbage leaves Lettuce leaves Lettuce stems Savoy cabbage leaves Fennel leaves Cauliflower leaf-blades Cauliflower stems
“N,,, is the total N content of the residues. blV,,n is the initial mineral N content of the residues
39.5 17.6 45.5 26.4 14.7 24.2 39.2 23.7 23.7 24.0 29.9 30. I 33.9 38.5 35. I 28.2
N”,,. (mg g&I
C-to-N ratio
I.11 I .97 I .20 7.44 2.1 I I .62 0.34 7.51 6.61 I .55 6.63 13.2 3.48 4.59 I .05 5.42
9.8 24.9 8.4 IS.3 30.0 14.6 10.0 10.8 16.8 16.4 9.1 12.6 10.9 IO.1 II.8 14.6
1453
N mineralization of vegetable crop residues tubes per crop residue), extracted with KC1 and analyzed for NOT-N and NH&N with a continuous flow auto-analyzer.
(three
Data analyses
The net N mineralization from the crop residues was calculated by subtracting total extractable N in the blank soil from that in the residue-amended soil. At each sampling time means and standard errors of the means (as percentage of total added residue N) were calculated. Fitting of the first order model to the net mineralization of total and organic N and calculation of a Pearson correlation matrix and linear regression equations between chemical plant parameters and the parameters of the first order model were performed using SYSTAT (Wilkinson, 1990). Fig. 2. Net N mineralization from the crop residues. RESULTS AND DISCUSSION Incubation experiments
Fractionations
The initial mineral N content of the soil was sufficiently low to adequately detect net N mineralization from the residues (Figs l-3). There was a wide variety in mineralization behaviour between the various crop residues and residue parts. The large differences in mineralization pattern between the different parts of one crop residue show that it was useful to incorporate these parts separately. This was particularly true for stems and leaves of beans and the upper and lower part of stems of broccoli. For most crop residues there was a small peak in NH: formation (relative to the unamended soil) after 2 weeks of incubation, but after 1 month the amounts of NH; measured were negligible. The fast disappearance of NH: from the residue-treated soils indicates that there were no anaerobic conditions during the trial. No net immobilization was observed with any of the crop residues.
The structural composition of the vegetable crop residues was very different (Table 2), except the hemicellulose fraction, which was relatively constant, varying mainly between 30 and 40% of organic matter. Stems of beans and cauliflower, the lower part of stems of broccoli and roots of endive had high or very high lignin contents and a low water-soluble fraction. No significant amounts of N were recovered in lipid and resin fractions. The bulk of the N was contained in the water-soluble and hemicellulose fraction.
0
3
6
&eob)
12
15
10
Time
N mineralization kinetics model A N mineralization model was fitted to the measured data of residue mineralization. The shape of the mineralization curves is similar to the typical shape described by the single first order kinetics model N(t) = NA (1-emk’), in which NA is the
00 0
3
B
12
15
Time (kkr)
Fig. 1. Net N mineralization from the crop residues. Bars represent standard errors.
Fig. 3. Net N mineralization from the crop residues.
I
1454 Table 2. Results
S. De Neve and G. Hofman of the modified
Crop residue Beans leaves Beans stems Broccoli leaf-blades Broccoli stem upper part Broccoli stem lower part Celery leaves Turnip leaf-blades Endive leaves Endive roots Red cabbage leaves Lettuce leaves Lettuce stems Savoy cabbage leaves Fennel leaves Cauliflower leaf-blades Cauliflower stems
Stevenson
fractionation (bracketed values are N contents total N in the crop residues).
of the different
Fractions (%
of fractions
Lipids
Resins
3.5 1.4 6.8 1.2 0.9 3.8 6.1 3.3 2.2 4.7 4.3 2.9 4.0 3.6 4.2 0.7
4.4 2.2 4.9 3.8 I.6 12.4 6.1 3.8 3.2 12.9 10.5 6.2 7.1 5.5 II 4 3.0
of organic matter) and N content Water-soluble fraction 29.1 (43) 13.6 (54) 24.4 (28) 18.6 (57) 9.2 (43) 30.4 (23) 27.6 (26) 23.0 (31) 15.9 (46) 30.4 (34) 30.2 (44) 27.0 (50) 28.7 (37) 28.4 (23) 28.1 (23) 11.4 (49)
amount of mineralizable N (expressed as percentage of total residue N), k is the rate constant and t is the time from the start of the incubation. The simple first order model has several advantages over more complicated models. There is no need to input initial estimates of the parameters and a limited number of mineralization data, even with high variability, will let the model converge. The results of the curve fitting are given in Table 3. The parameters NA and k in Table 3 are based on the mineralization data of total N, i.e. both organic and inorganic N contained in the residues. Because some of the residues contain relatively high amounts of mineral N (Table l), also the net mineralization ~ensu strict0 (i.e. mineralization of organic N from the residues) was calculated. From the measurements at all sampling times O-3 amount of mineral N in the residues was subtracted in order to obtain the amounts of organic N mineralized. This assumes that all mineral N contained in the crop
Table
Hemi-cellulose fraction 38.4 32.4 41.8 33.5 34.6 30.7 38.0 35.5 33.6 30.1 32.1 30.5 36.2 37.3 38.7 35.9
expressed
in % of
(% of total N)
Cellulose
(40) (32) (58) (34) (27) (58) (61) (50) ;36j (55) (40) (38) (51) (63) (63) (39)
fractmns,
fraction
10.7 (IO) 21.3 (3) 7.9 (5) 24.1 (4) 23.2 (19) 5.9 (4) 5.0 (4) 22.6 (6) 21.5 (5) 9.0 (2) 13.3 (8) 20.8 (5) 9.6 (5) 9.6 (4) 7.2 (3) 17.0 (4)
Lignin fraction 13.9 (7) 29.2 (I I) 14.3 (8) 18.2 (5) 30.5 (II) 16.8 (15) 17.5 (9) II.8 (13) 23.6 (13) 13.0 (9) 9.7 (8) 12.6 (7) 14.4 (7) 15.6 (IO) 9.8 (I I) 26.0 (8)
residues was released or at least measured from the first sampling time and that further release of mineral N was entirely due to mineralization of organic N. Because the crop residues were cut into small pieces this seemed a reasonable assumption. The first order model was then also fitted to the mineralization data of organic N. The parameters NA,org (the amount of mineralizable organic N expressed in percentage of organic N) and korg (the rate constant for mineralization of organic N) are also given in Table 3. For the crop residues which contain important amounts of mineral N, the model parameters for mineralization of total and organic N differed significantly. Relationship between N mineralization and chemical composition The chemical composition and N mineralization of the residues were used to establish a quantitative relationship for predicting net N mineralization
3. Parameters of the first order model fitted to the mineralization data (k (k,,,) = rafe constant for mineralization of total (orgamc) N; NA (N~.ors ) = mineralizable N as percentage of total (organic) N; bracketed values represent standard deviation)
Crop residue Beans leaves Beans stems Broccoli leaf-blades Broccoli stem upper part Broccoli stem lower part Celery leaves Turnip leaf-blades Endive leaves Endive roots Red cabbage leaves Lettuce leaves Lettuce stems Savoy cabbage leaves Fennel leaves Cauliflower leaf-blades Cauliflower stems
k (week-‘) 0.293 (0.014) 0.313 (0.035) 0.635 (0.033) 1.687 (I ,069) 0.872 (10.978) 0.272 (0.038) 0.525 (0.022) 1.092 (0.232) I.306 (0.168) 0. I87 (0.065) 1.305 (0.880) 1.256 (0.226) 0.325 (0.017) 0.635 (0.070) 0.410 (0.093) I. 108 (0.369)
NA (% of total N) 56.0 25.0 59.6 55.0 34.7 65.5 61.7 76.9 60.4 62.3 67.2 86.3 78.0 76.4 73.2 42.2
(0.5) (0.7) (I .3) (0.8) (4.3) (1.3) (1.8) (3.0) (3.2) (3.6) (9.6) (1.7) (5.5) (1.1) (5.5) i2.5j
korg(week-‘)
N ~.org(% of N,,)
0.269 (0.0 15) 0.122 (0.004) 0.607 (0.037) 1.002 (0.951) 0.506 (10.844) 0.234 (0.037) 0.516 (0.022) 0.678 (0.141) 0.838 (0.183) 0.163 (0.073) 1.020 (0.840) 0.752 (0.269) 0.266 (0.01 I) 0.520 (0.061) 0.414 fO.090) 0.296 (0.396j
55.2 (0.4) 17.7 (1.5) 58.5 (1.5) 36.2 (1.5) 23.9 (5.2) 64.0 (1.8) 61.4 (8.9) 66.8 (4.5) 43.4 (5.2) 60.8 (6.6) 57.3 (12.7) 75.5 (2.0) 76.8 (6.3) 73.7 (1.3) 72.3 (5.3) 30.9 (4.2)
N mineralization of vegetable crop residues
from the residues at any specified time after incorporation. A Pearson correlation matrix (Wilkinson, 1990) and linear regression equations were calculated between selected parameters or combinations of parameters reflecting plant chemical composition and the parameters of the first order model (Table 4). For mineralization of total N the best correlation to N,.+ was with lignin content; an equally good correlation was obtained with the Cto-N ratio of the lignin. Good correlation to NA was observed with a factor defined by Herman et al. (1977) to describe C mineralization from grass species, namely lignin times C-to-N ratio over the root square of the water soluble fraction (r = - 0.773, P < 0.001). Correlation with C-to-N ratio was rather good but correlation with total N content was not significant (Table 4) and much weaker than for data obtained 4 weeks after field incorporation of vegetable crop residues (De Neve et al., 1994). The weak correlation between N mineralization and N content is probably due to the relatively small range in N contents of the crop residues considered here (total N content varying mainly between 25 and 35 mg g-’ dry matter). Regressions between mineralizable organic N and chemical parameters were more significant than for mineralization of total N for all chemical parameters studied (Table 4). The best relationship was between N~,~rs and the C-to-N ratio of the lignin. Other good correlations to N..~,rs were observed with lignin content and with the water soluble fraction. Correlation with C-to-N ratio was good but correlation with total N content was again much weaker. Addition of more chemical parameters to the regression did not result in a significant decrease of the residual variance. There were no obvious curvilinear relationships between chemical composition and NA or NA,org.
1455
The rate constants k and k,, were more difficult to predict from chemical parameters. The best linear relationship was with the percentage of organic N in the residues (Table 4). The following model is proposed to predict net mineralization of organic N from incorporated vegetable crop residues: Norg(t) = (76.6 - 0.653 C - to - N,ir”i”) -(1.73-0.0144N,&r)
x(1-e
In this equation N,,,(r) is the percentage of organic N mineralized at time f, C-tO-N1isnin is the Cto-N ratio of the lignin fraction and Nors is the amount of organic N in the crop residues (expressed in percentage of total N). Assuming that all mineral N contained in the residues is released in the period before the first measurement, the total amount of N released is then given by: + N O’K (t)
N(r) = Nml”
N 100
.2%
In this equation N(t) is the percentage of total residue N released at time t, Nmin is the initial amount of mineral N in the crop residues (expressed in percentage of total N), and N&t) and Nors are as defined in equation (1). In Figs 4 and 5 the percentages of organic N mineralized after 2 and 16 weeks as given by the experimentally determined values of N~,~rs and korg (Table 3) and as calculated by the proposed mode1 (equation (1)) are compared. The correlation between predicted (model) and measured values improves from 0.821 after 2 weeks to 0.882 at the end of the incubation (16 weeks). This is due to the fact that the importance of the rate constant decreases with time of incubation, and it is the rate constant that has the highest prediction error.
Table 4. Linear regression equations between mineralization parameters and selected chemical properties of the residues (FR3 = water-soluble fraction, FR6 = lignin content, N,,, = total N content in % of dry matter, C-toN = global C-to-N ratio, C-to-N,is,,i, = C-to-N ratio of lignin fraction, Nors = organic N content in % of N,,,) Mineralization parameters
Regression equations and correlation coefficients
NA
17.8 + 1.81.FR3 91.3 - 2.09.FR6 33.9 + 9.15.N,,, 89.7 - 2.03.(C-to-N) 79.3 - 0.542.(C-to-N,is,i,)
r = 0.746”’ r = - 0.833”’ r = o.470”‘s. I = - 0.723” r = - 0.833”’
NAorg
-1.99 + 2.37.FR3 91.2 - 2.46.FR6 15.9 + 13.1.N,,, 88.6 - 2.41.(C-to-N) 76.6 - 0.653.(C-to-N,,,i.)
, r r r r
= 0.861”’ = - 0.861”’ = 0.591’ = - 0.757”’ = - 0.882”’
k
4.37 - 0.041 I.N,,
I = - 0.626”
k ore
1.73 - 0.0144.N,,,
r = -0.631”
‘P c 0.05, l*p < 0.01, ***p < 0.001.
(1)
1456
z
S. De Neve and G. Hofman
20
.o i
G 0
. I ’
r = 0.821
l
.
.
,
0
I
I
I
20
40
60
80
% organic N mineralized after 2 weeks: model calculations
Fig. 4. Comparison between percentages of organic residue N mineralized after 2 weeks of incubation as calculated from the mineralization parameters in Table 3 and from the model (equation (1)). The line is the bisector.
Several researchers have attempted to give critical C-to-N ratios for N mineralization, i.e. the C-to-N ratio at the break point between net N mineralization and net N immobilization. Values in literature range from C-to-N = 20 for 4 week incubations (Iritani and Arnold, 1960), to C-to-N = 30 (Fox et al., 1990) or C-to-N = 40 for long term incubations of 11 to 44 weeks (Vigil and Kissel, 1991). Critical C-to-N ratios depend on the duration of the incubation considered. Das et al. (1993) observed a critical C-to-N ratio of 46 after 30 days at FC. This value increased to 95 after 120 days of incubation. Janzen and Kucey (1988) found the critical C-to-N ratio to increase from 24 to 41 after 14 and 84 days of incubation, respectively. In our study the C-to-N 00
,
I
.
l
.Y
*I
. l
**
l
,
m-
l
)/
,j
, . 20 -
r = 0.882
.
0
I 0
20
% organic N mineralized
I
I
40
60
80
after 16 weeks: model calculations
Fig. 5. Comparison between percentages of organic residue N mineralized after 16 weeks of incubation as calculated from the mineralization parameters in Table 3 and from the model (equation (1)). The line is the bisector.
ratio can be used to predict values of NA or NA,org (which are independent of time of incubation, within certain limits). The (critical) C-to-N ratio that would give neither mineralization nor immobilization (NA = 0) here is 44 (Table 4). This is a relatively high value but it corresponds to those found by Vigil and Kissel (1991) and Janzen and Kucey (1988) for prolonged incubations. The strength of the N mineralization model presented here is that the relationship between chemical parameters and net N mineralization is independent of the duration of the incubation because they are linked to the parameters from the first order model. In this way net N mineralization can be predicted at any given time after residue incorporation. It should be stressed that the model proposed here was developed for predicting the mineralization of vegetable crop residues. Further research including residues with completely different characteristics such as straw or composts should be undertaken to see whether their mineralization pattern fits the model as well. The mineralization process will of course be influenced by important factors such as temperature, soil moisture content, soil bulk density and possibly others, which will have to be taken into account when they differ from the conditions specified here. Acknowledgements-Financial support by the EC is gratefully acknowledged (EC project No. 800l-CT91-0115).
REFERENCES
Constantinides M. and Fownes J. H. (1994) Nitrogen mineralization from leaves and litter of tropical plants: relationships to nitrogen, lignin and soluble polyphenol Soil Biology and Biochemistry 26, 49-55. concentrations. Das S. K., Subba Reddy G., Sharma K. L., Vittal K. P. R., Venkateswarlu B., Narayana Reddy M. and Reddy Y. V. R. (1993) Prediction of nitrogen availability in soil after crop residue incorporation. Fertilizer Research 34, 209-215. De Neve S., Pannier J. and Hofman G. (1994) Fractionation of vegetable crop residues in relation to in situ N mineralization. European Journal of Agronomy 3, 261-272. Fox R. H., Myers R. J. K. and Vallis I. (1990) The nitrogen mineralization rate of legume residues in soil as influenced by their polyphenol, lignin and nitrogen contents. Plant and Soil 129, 251-259. Frankenberger W. T. and Abdelmagid H. M. (1985) Kinetic parameters of nitrogen mineralization rates of leguminous crops incorporated into soil. Plant and Soil 87, 257-271.
Herman W. A., McGill W. B. and Dormaar J. F. (1977) Effects of initial chemical composition on decomposition of three grass species. Canadian Journal qf Soil Science 57, 205-2 15. Honeycutt C. W., Potaro L. J., Avila K. L. and Halteman W. A. (1993) Residue quality, loading rate and soil temperature relations with hairy vetch (Vicia villosa Roth) residue carbon nitrogen and phosphorus mineralization. Biological Agriculture and Horticulture 9, 18 I-199.
N mineralization of vegetable crop residues Iritani W. M. and Arnold C. J. (1960) Nitrogen release of vegetable crop residues during incubation as related to their chemical composition. Soil Science 89, 74-82. Janzen H. H. and Kucey R. M. N. (1988) C, N, and S mineralization of crop residues as influenced by crop species and nutrient regime. Plant and Soil 106, 35-41. Kirchmann H. and Bergqvist R. (1989) Carbon and nitrogen mineralization of white clover plants (Trifolium repens) of different age during aerobic incubation with soil. Zeitschrift ftir Pjanzenerntihrung und Bodenkunde 152, 283-288.
Palm C. A. and Sanchez P. A. (1991) Nitrogen release from the leaves of some tropical legumes as affected by
1457
their lignin and polyphenolic contents. Soil Biology and Biochemistry 23, 83-88.
Stevenson F. J. (1965). Gross chemical fractionation of organic matter. In Methodr of Soil Analysis, Part 2 (C. A. Black, Ed.), pp. 1409-1421. American Society of Agronomy, Madison. Vigil M. F. and Kissel D. E. (1991) Equations for estimating the amount of nitrogen mineralized from crop residues. Soil Science Society of America Journal 55, 757761.
Wilkinson, L. (1990) SYSTAT: the system for statistics. Systat Inc., Evanston, IL.