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a INRA - Unité d'agronomie de Châlons-Reims, Centre de Recherche Agronomique, 2 esplanade Roland Garros, BP 224, 51686 Reims cedex 2, France
b INRA - Unité d'agronomie de Laon-Péronne, rue Fernand Christ, 02007 Laon cedex, France
c INRA - Station d'agronomie, 71 avenue Edouard Bourlaux, BP 81, 33883 Villenave d'Ornon cedex, France
d INRA - CMSE Laboratoire de Microbiologie des Sols, 17 rue Sully, BP 1540, 21034 Dijon cedex, France
bernard.nicolardot{at}reims.inra.fr
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ABSTRACT |
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 TOP ABSTRACT INTRODUCTIONMaterials and methodsResultsDiscussionREFERENCES |
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Abbreviations: CEL, cellulose fraction • d.m., dry matter • HEM, hemicellulose fraction • LIG, lignin fraction • POL, soluble polyphenols • S20, soluble C fraction • SOL, soluble fraction
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INTRODUCTION |
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TOPABSTRACTINTRODUCTIONMaterials and methodsResultsDiscussionREFERENCES |
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The objective of our work was to establish, under conditions of nonlimiting N, the relationships between the kinetics of C and N decomposition and the biochemical characteristics of the residues produced by the main arable crops of temperate regions: oilseed rape (Brassica napus L.), barley (Hordeum vulgare L.), wheat (Triticum aestivum L.), maize (Zea mays L.), soybean [Glycine max (L.) Merr.], pea (Pisum sativum L.), and alfalfa (Medicago sativa L.). The kinetics of decomposition of C and N of these different materials were studied in the laboratory in the absence of limiting factors and were related to some of their biochemical characteristics (e.g., concentrations of N, polyphenols, and different forms of C present in the plant tissues). Any such relationships should confirm the relevance of expressions representing quality in existing decomposition models or permit their modification where necessary to provide a new approach to plant residue quality.
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Materials and methods |
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TOPABSTRACTINTRODUCTIONMaterials and methodsResultsDiscussionREFERENCES |
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The mineral N and soluble C (S20) in the residues were obtained by extraction in water for 30 min at 20°C (2:1000 material/extractant ratio). The mineral N was measured by continuous-flow colorimetry (see below). The concentration of soluble C (S20) was determined with an auto-analyzer (1010, O.I. Analytical, College Station, TX) by oxidation at 100°C in a persulfate medium, followed by infrared detection of the CO2 evolved (Barcelona, 1984).
The soluble fraction (SOL) of the different materials was determined by hot water extraction (100°C) for 30 min, followed by extraction with neutral detergent (100°C) for 60 min (Linères and Djakovitch, 1993). The hemicellulose (HEM), cellulose (CEL), and lignin (LIG) fractions were then determined (Van Soest, 1963). The C and N concentrations of the solid fractions, HEM, CEL, and LIG, obtained by Van Soest's method were determined by elemental analysis (NA 1500, Carlo Erba).
The soluble polyphenols (POL) present in the crop residues were extracted at 80°C with an aqueous methanol solution (1:1 water/methanol ratio) (Tian et al., 1995) and measured by colorimetry in the presence of Folin-Denis reagent (King and Heath, 1967).
The CO2 produced by the soil and trapped by the NaOH was determined by continuous flow colorimetry (Chaussod et al., 1986) using an auto-analyzer (TRAACS 2000, Bran & Luebbe, Norderstedt, Germany). The mineral N (NO-2, NO-3, and NH+4) in the soil and the residue extracts were measured by continuous flow colorimetry (TRAACS 2000, Bran & Luebbe). The NO-3 and NO-2 were measured using an adaptation of the method proposed by Kamphake et al. (1967) and the NH+4 by a method derived from that of Krom (1980).
Expression of Results
Nitrogen, POL, SOL, HEM, CEL, and LIG contents were expressed as a proportion of the residue dry matter and the S20 content as a proportion of the residue C content. In order to compare incubations carried out at 15 and 12°C, the time length at 12°C was converted into the time length at 15°C by using a temperature factor as proposed by Aita et al. (1997) with a Q10 value of 3.15.
The apparent mineralization of C from the residues was calculated from the difference between the CO2–C produced by the soil–residue mixture and that produced in the same period by the control soil (without residue addition). It was thus assumed that the priming effects due to the addition of plant residues to native soil organic matter were comparable for the different experimental treatments. The results were then expressed as grams C per kilogram of the C added.
The kinetics of C mineralization from the residues were simulated using a two-compartment model:
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The effect of adding residues on the dynamics of soil mineral N (net mineralization or immobilization) was calculated from the difference between the mineral N present in the soil and residue mixture and that present in the control soil. This was then expressed in grams N per kilogram C added by the various residues to allow their comparison.
Statistical Calculations
SAS software (SAS Institute, 1987) was used to analyze the data obtained 7, 28, 84, and 168 d after incorporating the residues into the soil. NLIN was used to calculate the parameters of the two-compartment model. CORR provided the simple correlation between the different variables: organic N, C/N, S20, SOL, HEM, CEL, LIG, POL, and the following ratios: LIG/N, POL/N, and (LIG+POL)/N. Finally, REG was used to calculate the best multiple regression models incorporating all these variables with the STEPWISE option. In this case, the method starts with no variables in the model and adds them one by one. Not all of the variables introduced into the model will necessarily remain. The significance level for adding or retaining variables in the multiple regression model was 0.15.
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Results |
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TOPABSTRACTINTRODUCTIONMaterials and methodsResultsDiscussionREFERENCES |
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Mineralized Carbon and Kinetic Parameters of the Model
Figure 2
shows the range of variation covered by the kinetics of apparent C mineralization of the 47 crop residues and underlines some typical cases. In general, the amounts of C mineralized by the end of incubation, expressed as a proportion of residue C, varied between 330 g C mineralized kg-1 residue C (rape leaves, Residue 34) and 670 g C mineralized kg-1 residue C (pod walls, Residue 32, and rape stems, Residue 31).
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The initial decomposition rate of the residues was strongly related to the presence of soluble compounds. Thus, C mineralized at the start of incubation (7 d) and the rate constant for decomposition of the labile fraction (k1) were strongly correlated with the various forms of soluble C in the residue (Table 3 , Fig. 3) . As decomposition proceeded, the relationship between the C mineralized and the soluble fractions weakened. The equations developed through multiple linear regression (Table 4) show that, after 28 d of incubation, the mineralization of residue C resulted from the effects of other C forms (LIG, CEL, and HEM). The labile fraction A, defined in the two-compartment model, was largely correlated with the lignin content (Table 3), whereas the equation obtained by multiple linear regression (Table 4) accounted for most of the C forms.
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Dynamics of Soil Mineral Nitrogen
The incorporation of the various residues into the soil strongly modified both the dynamics of the soil mineral N and the amount of inorganic N involved during the decomposition, as shown by the highly variable pictures presented on Fig. 4
. Some of the residues (bold lines on Fig. 4) typically represent the main situations: the highest net N mineralization (+50 g N kg-1 C) was obtained for alfalfa shoots (Residue 37), and the lowest (-28 g N kg-1 C) for maize straw (Residue 47) at the end of the incubation period. A net N mineralization was observed throughout the entire incubation period only in alfalfa shoots (Residue 37) and rape leaves (Residue 21). The incorporation into the soil of all the other residues initially caused net N immobilization, although the date of maximal immobilization and amounts of N immobilized varied with the residue, up to 33 g N kg-1 C being immobilized for maize straw (Residue 47), and only 1 g N kg-1 C for rape leaves (Residue 12). Net N immobilization was then followed by a phase of net N mineralization, the amount (Residue 27 vs. 10) and rate (Residue 10 vs. 47) of which varied greatly between residues. The amounts of N mineralized from the date of maximum immobilization to the end of incubation varied from a maximum of 33 g N kg-1 C for rape leaves (Residue 13) to a minimum of 2 g N kg-1 C for wheat straw (Residue 46).
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The net effect of crop residue application on soil mineral N dynamics was positively related to the organic N concentration of the residues or their C/N ratio at Days 7, 28, 84 and 168 (Table 3, Fig. 5) , better R2 value being obtained with the organic N concentration (Table 3). The POL concentrations of the residues influenced the soil N dynamics, particularly during the early stages of decomposition (Table 4). In fact, the inclusion of POL concentration in the multiple regression model led to a better description at 7 and 28 d. Thus, the overall coefficients of determination (R2) of the model were 0.70 (Day 7) and 0.86 (Day 28) when only the organic N concentration of the residues was included, and 0.84 (Day 7) and 0.94 (Day 28) when both organic N and POL concentrations were included. Later on, the effect of POL concentration was smaller. At 84 d, the overall coefficient of determination was 0.91 when only organic N was included, and 0.93 when POL was added. This influence of POL concentration on the dynamics of mineral N after incorporation of residues was particularly clear in the case of rape leaves, that have both low C/N ratios (9.3–30.0) and the highest POL concentrations. These residues mostly caused N immobilization at the start of decomposition, followed by net N mineralization the rate of which remained much lower than that of alfalfa shoots, for example.
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Discussion |
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TOPABSTRACTINTRODUCTIONMaterials and methodsResultsDiscussionREFERENCES |
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After 7 d of decomposition, the C mineralization of residues was related mainly to the amount of C present initially in soluble form. These results confirm the work of several authors (Reinertsen et al., 1984; Cogle et al., 1989; Herman et al., 1977; Collins et al., 1990). As decomposition proceeded, the proportion of soluble compounds had less influence on the rate of C mineralization because this fraction had been largely degraded. At this point, the proportion of variation in mineralization rates accounted for by multiple regression analysis decreases. Also, the decomposition rate constant of the resistant fraction is explained rather poorly by a multiple regression model. These results do not agree with the data obtained by Linères et al. (1993) who showed that the nondecomposed C of organic residues incorporated in soil could be explained by multiple regression models that took into account the different plant polymers. This could be because such relationships were established for a wider range of organic residues (including plant residues, refuse compost, sawdust, wood, manures, barks, and peat) the characteristics of which are relatively unlike those of annual crop residues. In reality, the C mineralization kinetics are deduced from the difference between the amounts of CO2 released from the soil with and without addition of residues. It results from (i) primary decomposition of the C of the residue, (ii) renewal of the C of the microbial biomass newly created from the residue, and (iii) secondary decomposition of the organic matter fractions into which the C of the residue has been incorporated (e.g., microbial metabolites). Consequently the relative weight of the C coming from the residue by primary decomposition falls during the course of decomposition. This is mainly why only the initial rates of decomposition can be explained by the biochemical characteristics of the residues. In a similar way, it is difficult to associate the labile and resistant fractions of the model directly with the fractions measured in the plant as these two fractions implicitly include the C of the residue that has been incorporated into the different soil organic matter fractions and is once again subjected to decomposition by the soil microflora.
Finally, the decomposition of the residues was only weakly related to the organic N concentration or the C/N ratio of the residues. The significant relationship found at 7 d between C mineralization and organic N content was actually due to the high correlation between the concentrations of soluble forms of C and organic N. Thus, organic N was not taken into account into the multiple regression model at this date, which conflicts with results of Cotrufo et al. (1994) and Vanlauwe et al. (1996). It has been shown that the decomposition of crop residues can be affected by the availability of N since the N/C ratio of the decomposers is far higher than the N/C ratio of many crop residues. Thus, very often, the availability of soil inorganic N will, at least in the short term, control the kinetics of C decomposition, as has been shown with cereal residues (e.g., Recous et al., 1995; Henriksen and Breland, 1999; Corbeels et al., 2000). In our studies, the possibility of N limitation was eliminated by the initial addition to soil of a sufficient amount of mineral N, so as not to obtain confounding effects of N availability and nature of residue polymers on decomposition rate. This explains why the residue N contents probably did not significantly affect their decomposition. Conversely, in the reported experiments (e.g., Cotrufo et al., 1994; Vanlauwe et al., 1996), the amount of N added by the residues constituted most of the N available for decomposition, so it is therefore not surprising that the authors found a significant relationship between decomposition rates and the N concentration or the C/N ratios of the residues.
In the longer term, N could have a negative effect on decomposition. A high N availability is also known to inhibit the synthesis of ligninolytic enzyme systems (Keyser et al., 1978). Fog (1988) and Berg and Matzner (1997) showed a negative effect of high soil N availability on decomposition. However these results were obtained for forestry residues with very high lignin concentrations and biochemical characteristics that are very different from those of crop residues. Lastly, despite the significant correlation established with the polyphenol concentration of the residues, decomposition can only slightly be explained by the presence of these compounds in the plant tissues except shortly after the start of decomposition (Table 4). These observations may be due to the low polyphenol concentrations in the residues studied compared with those in the relationships published earlier (Kachaka et al., 1993; Vanlauwe et al., 1996).
So, the concentrations of the different polymers in the plant tissues are the most important factors that influence the C decomposition of crop residues in soils, when decomposition is not controlled by the overall availability of N. Models that describe the fate of residues or quantify gross fluxes of C and N during residue decomposition (Paustian et al., 1997) must therefore account for the biochemical quality of the residues, or use indices that reflect that quality (Whitmore and Handayanto, 1997). In addition, it appears crucial that parameters depending on the residue characteristics should be calibrated from data obtained under conditions of nonlimiting N, therefore avoiding the confounding effects of biochemical characteristics of the residues and of N availability, the latter factor including both residue N content and soil residual N or N mineralized. The inclusion in these models of a function describing the effect of N availability on C decomposition and N dynamics should then allow the possibility of limitation by mineral N availability to be assessed (Hadas et al., 1998). Lastly, our study dealt with the effect of biochemical quality of the residues under conditions where the residue had been ground and mixed thoroughly with the soil. It is certain that morphological properties of the residues and their contact with the soil also affects decomposition and interacts with biochemical composition to influence decomposition rates (Angers and Recous, 1997; Bremer et al., 1991; Jensen, 1994a).
The net effect of applying crop residues on the dynamics of soil mineral N and the maximum quantities of N immobilized were related mainly to the organic N concentrations and C/N ratios of the residues. These results confirm the work of Quemada and Cabrera (1995) and Constantidines and Fownes (1994). Iritani and Arnold (1960) and Frankenberger and Abdelmagid (1985) suggested that the initial N concentration is a better index than the C/N ratio, perhaps because the C/N ratio can be distorted by the presence of appreciable quantities of mineral N (mainly NO-3) in the plant tissues, which are thus immediately available.
In our study, all residues with a C/N ratio between 10 and 150 (with the exception of alfalfa shoots, Residue 37, and rape leaves, Residue 21) caused net N immobilization in the early stages of decomposition. Most authors (e.g., Paul and Clark, 1989) have suggested that net N mineralization occurs when C/N ratios of residues are <25. Nevertheless, some (Jensen, 1994b) have shown that residues with a low C/N ratio can cause net immobilization of the soil mineral N. In fact, most studies referring to a C/N ratio threshold value were carried out in the field and did not monitor precisely the changes occurring in soil mineral N with time. Most of the time, they evaluated the net effect of residue incorporation on the soil mineral N after a certain period of time (a season or cropping year). Looked at in this way, the results of our study are in agreement with the literature. In fact, considering the net effect of the residues after 168 d of incubation, all residues with a C/N ratio below 24 induced net N mineralization, whereas those with a C/N ratio above 24 caused net immobilization of soil mineral N. Finally, it seems much more important to consider the kinetics of decomposition rather than just the amounts mineralized by the end of decomposition, as the relationships between C mineralization and N and the intrinsic characteristics of the residues are temporally dynamic (Vanlauwe et al., 1996; Quemada and Cabrera, 1995).
Our study has shown an effect of polyphenol concentration on N mineralization mainly during the first stages of decomposition. These effects have been observed previously during the decomposition of leguminous crop residues, for which the polyphenol concentrations are high (Seneviratne et al., 1998; Oglesby and Fownes, 1992). In general, these studies showed that soluble polyphenols slow the mineralization of residue N by forming complexes with proteins, thus making them inaccessible to the microorganisms (Mafongoya et al., 1998). These latter authors have also suggested that the capacity of the polyphenols to complex with proteins is a more suitable index than the total polyphenol concentration of the residues. The interactions of the polyphenols with the N compounds described by the POL/N or (LIG+POL/N) ratios (Fox et al., 1990; Palm and Sanchez, 1991; Vanlauwe et al., 1996) and included in the multiple regression model brought about little or no improvement in fit, despite the existence of significant correlations between the net effect of residues on the dynamics of soil mineral N and the value of the POL/N ratio.
Lastly, except for the soluble compound content, which appeared to have an influence on the dynamics of soil N, especially at the beginning of incubation, the inclusion of other forms of residue C (HEM, CEL, LIG) or ratios such as LIG/N did not improve the models proposed, which contrasts with the work of Taylor et al. (1989) and Kachaka et al. (1993), who found correlations between the N mineralization of the residues and the LIG/N ratio.
Considering the net effect of incorporated residues on the dynamics of soil mineral N, our work confirms that the N concentration of the residue is the most important influencing factor. This result suggest that the description of residue quality should be simplified for the determination of mineral N dynamics and will be important for the development of simple models that predict crop N fertilizer requirements, and for testing agronomic scenarios (e.g., STICS model by Brisson et al., 1998; APSIM model by Probert et al., 1998).
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ACKNOWLEDGMENTS |
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Received for publication March 23, 1999.
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REFERENCES |
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TOPABSTRACTINTRODUCTIONMaterials and methodsResultsDiscussionREFERENCES |
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