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Pyrolysates of tetraborate extracts
The tetraborate extract of MSWi (TEi, Figure 2.3) released high proportions of N-containing and polysaccharide-derived compounds during pyrolysis (respectively 51% and 19% of the total areas of identified peaks, Table 2.3). The two principal peaks were acetamide (N25, 8.8% of the total area of identified peaks) and phenol (U15, 6.8% of the total area of identified peaks). Phenol is an ubiquitous pyrolysis product, which may originate from tyrosine-containing peptides and proteins (Tsuge and Matsubara, 1985), as well as from lignins (Saiz-Jimenez and De Leeuw, 1986), tannins (Galletti and Reeves, 1992) or polysaccharides (Pouwels et al., 1987). In the pyrolysate of the MSWm tetraborate extract (TEm, Figure 2.4), the principal peaks were 2-hydroxy-pyridine (N34, 11.7% of the total area of identified peaks) probably deriving from alanine-containing proteins and peptides (Chiavari and Galletti, 1992) and phenol (U15, 8.2% of the total area of identified peaks). The pyrolysate of TEm was dominated by N-containing products (64% of the total area of identified peaks) and displayed only a few polysaccharide-derived compounds (3% of the total area of identified peaks, Table 2.3). Large and unresolved peaks of lipid-derived carboxylic acids were detected at the end of the pyrogram for TEi (Figure 2.3) but not that for TEm (Figure 2.4). A few lignin-derived compounds (LIG1, LIG2, LIG5 and LIG6) were identified in the pyrograms of TEi and TEm, although lignins were not expected to be solubilized in tetraborate. Pyrrole (N14), an ubiquitous compound derived from proteins and peptides, microbial cells (Ceccanti et al., 1986) or pigments like chlorophyll was present at high proportions in the pyrolysates of both TEi and TEm. A small quantity of styrene (U9) was detected in these pyrolysates (3% and 1% of the identified peak areas for TEi and TEm, respectively).
Pyrolysates of extraction residues
In MSWi compost, polysaccharide-derived products dominated the pyrolysates of both residues after neutral detergent extraction or alternative procedure (NDFi and ARi, respectively, Figure 2.3 and Table 2.3). They accounted for 25% and 43% of total areas of identified peaks in the pyrolysates of NDFi and ARi, respectively, large proportion as observed in the pyrolysate of bulk immature compost (36%). The carboxylic acid peaks observed at the end of the pyrogram for bulk MSWi compost were not present in the pyrolysate of the NDFi residue but was observed in the pyrolysate of ARi although some were extracted using tetraborate.
In MSWm compost, both residues (ARm and NDFm) presented similar characteristics of their pyrolysates with fewer polysaccharide-derived compounds and higher proportions of unspecified compounds, and particularly more styrene (45% and 50% of the total area of identified peaks respectively, Table 2.3) when compared to the pyrolysates of extraction residues of the immature compost (ARi and NDFi, respectively). Fewer lignin-derived, nitrogenous compounds and more ubiquitous compounds were present in the pyrolysates of ARm and NDFm compared with the pyrolysate of the bulk MSWm compost.
FTIR spectroscopy
The FTIR spectra of bulk composts (MSWi and MSWm) and of the hot water (WEi and WEm) and tetraborate (TEi and TEm) extracts are presented in Figure 2.5. Interpretation of these spectra was based on data in the literature (Ouatmane et al., 2000; Francou et al., 2008, Smidt and Meissl, 2007).
We focused our interpretation on the height of several bands of interest: absorption bands at 2925 and 2850 cm-1 (aliphatic C-H stretch), the band at 1600-1650 cm-1 (aromatic C=C, in addition to quinines, conjugated carboxyls and ketones and the C=O stretch of primary amide), a narrow peak at 1384 cm-1 (N-O stretch of nitrates) and the band at 1040 cm-1 (C-O stretch of polysaccharides and aromatic ether). The aliphatic bands at 2925 cm-1 and 2850 cm-1 were higher for MSWi than for MSWm. Regarding the intensity of the aliphatic bands in the FTIR spectra, alkanes and alkenes peaks should be observed in the pyrolysates although they were not detected. This was probably due to the GC polar column used, non-polar column being more suitable for the characterization of aliphatic structures producing alkanes and alkenes upon pyrolysis (Dignac et al., 2006).
The FTIR spectra of WEi displayed more intense aliphatic bands (2925 and 2850 cm-1) than those seen for WEm. The nitrate band at 1384 cm-1 was very intense in WEm spectra but not visible in WEi spectra which was consistent with its presence in MSWm spectrum and not in MSWi one. By contrast, the band at 1040 cm-1 was present in the spectra of WEi but not in that of WEm, reflecting the higher levels of polysaccharides in the WEi extract which was consistent with the results found in pyrolysis.
Aliphatic bands (2925 and 2850 cm-1) were visible in TEi spectra although they were less intense than in WEi spectra and very weak in TEm spectra. The band at 1040 cm-1 was present in TEi but not in TEm spectra.
Principal Component Analysis (PCA)
The data used for PCA were the relative surface areas of pyrolysis products originating from the different biochemical families: polysaccharide-derived products (PS), N-containing products (N), ligninderived products (LIG) and products of unspecified origin (U) as a percentage of the total area of identified peaks, the C/N ratio of the residues and WE and TE extracts. The proportion of organic C mineralized after 21 days of incubation (C21) was used as illustrative variable because data were not available for TE extracts. The plane defined by the two first principal components accounted for 88% of total inertia (Figure 2.6). The first principal component was significantly and positively correlated with the proportion of N-containing compounds released during pyrolysis (N, r = 0.98, p<0.01), significantly and negatively correlated with the proportion of compounds of unspecified origin (U, r = – 0.87, p<0.01), the proportion of lignin-derived compounds (LIG, r = -0.80, p<0.01) and the C/N ratio (r = -0.75, p<0.05). The second principal component was significantly and negatively correlated with polysaccharide-derived compounds (PS, r = -0.88, p<0.01). The C21 variable was strongly, negatively correlated to the second principal component (r = -0.93, p<0.01). The second component thus represented the degree of biodegradability of the samples.
Table of contents :
Partie I. Amélioration d’outils et de méthode de caractérisation des matières organiques exogènes et d’estimation de leur devenir dans les sols
Chapitre 2. Change of the chemical composition and biodegradability of the Van Soest soluble fraction during composting: A study using a novel extraction method
2.1. Abstract:
2.2. Introduction
2.3. Materials and Methods
2.3.1. Composts
2.3.2. Extraction of the Van Soest soluble fraction
2.3.3. A novel alternative fractionation procedure
2.3.4. Elemental composition
2.3.5. Laboratory incubations
2.3.6. Curie-point pyrolysis-gas chromatography-mass spectrometry (Pyrolysis-GC/MS)
2.3.7. Fourier-Transform Infra-Red (FTIR) spectroscopy
2.3.8. Statistical analysis
2.4. Results
2.4.1. Quantification of organic matter fractions obtained using the Van Soest and alternative procedures
2.4.2. Mineralization of organic C in the fractions
2.4.3. Characterization of composts, fractions and residues using pyrolysis-GC/MS
2.4.4. FTIR spectroscopy
2.4.5. Principal Component Analysis (PCA)
2.5. Discussion
2.5.1. Evaluation of the alternative fractionation procedure
2.5.2. Evolution during composting of the chemical nature and biodegradability of extracted organic fractions
2.5.3. Change of the chemical nature and biodegradability of the fractions extracted using the alternative method indicative of changes to the biodegradability of the “soluble” Van Soest fraction during composting
2.6. Conclusions
2.7. References
Chapitre 3. Near infrared reflectance spectroscopy: a tool to characterize the composition of different types of exogenous organic matter and their behaviour in soil
3.1. Abstract
3.2. Introduction
3.3. Materials and Methods
3.3.1. EOM dataset
3.3.2. Chemical and biochemical characterisation of EOM
3.3.3. Stable organic C in EOM
3.3.4. NIRS analysis
3.4. Results and Discussion
3.4.1. Analytical characteristics of EOM
3.4.2. NIRS prediction of the elemental composition of EOM
3.4.3. NIRS prediction of Van Soest biochemical fractions of EOMs
3.4.4. NIRS prediction of EOM-C mineralized during laboratory incubations
3.4.5. NIRS prediction of the stable organic C in EOM
3.5. Conclusions
3.6. References
Partie II. Accumulation de C dans le sol suite à des apports répétés de MOEs: Paramétrage du modèle RothC en vue de simuler le devenir de MOEs dans les sols
Chapitre 4. Carbon accumulation in soil following repeated applications of different organic amendments: distribution within particle size and density fractions and simulation with the RothC model.
4.1. Abstract
4.2. Introduction
4.3. Materials and methods
4.3.1. Qualiagro field experiment
4.3.2. Chemical and biochemical characterisation of EOMs
4.3.3. Soil sampling and C stocks
4.3.4. C inputs from crop residues
4.3.5. Yields of C accumulation
4.3.6. Size and density fractionation of soil organic matter
4.3.7. Simulation of C accumulation in soil with RothC
4.3.8. Simulation of potential sequestration of C through EOM applications
4.3.9. Statistical analysis
4.4. Results and Discussion
4.4.1. Characteristics of the EOMs applied
4.4.2. Evolution of field C stocks after EOM application
4.4.3. Distribution of SOC in size and density fractions following EOM application
4.4.4. Simulation of C stock evolutions using RothC
4.4.5. Extrapolation of RothC simulation
4.4.6. Comparison of particle size fractions and model pools
4.5. Conclusions
4.6. References
4.7. Supporting Information
Chapitre 5. Carbon accumulation in soil after repeated applications of different organic amendments evaluated by applying the RothC model to four long-term field experiments.
5.1. Abstract
5.2. Introduction
5.3. Materials and methods
5.3.1. Field experiments
5.3.2. C stocks
5.3.3. C inputs from crop residues
5.3.4. RothC model
5.3.5. Yields of C accumulation in soil
5.3.6. Laboratory characterization of EOMs
5.3.7. Calculation of linear regressions
5.4. Results and Discussion
5.4.1. Characteristics of the EOMs applied
5.4.2. Simulation of C accumulation in soil with RothC
5.4.3. Proportion of the cumulated C inputs remaining in soil
5.4.4. Relationship between the analytical characteristics of EOMs and C accumulation in the soil
5.4.5. Simulation of C accumulation using partition coefficients predicted from laboratory characterizations of EOMs
5.5. Conclusions
5.6. References
Partie III. Composition chimique de la MO du sol après des apports répétés de matières organiques exogènes
Chapitre 6. Modifications to the chemical composition of organic matter in particle size and density fractions after 8 years of compost and manure applications in a loamy soil
6.1. Abstract
6.2. Introduction
6.3. Material and methods
6.3.1. Field experiment and soil sampling
6.3.2. Chemical and biochemical characterization of EOMs
6.3.3. Size and density fractionation of soil organic matter
6.3.4. Hydrofluoric acid (HF) treatment
6.3.5. Pyrolysis-gas chromatography-mass spectrometry (pyrolysis-GC/MS)
6.3.6. Diffuse reflectance infrared Fourier transform (DRIFT) spectroscopy
6.3.7. Statistical analysis
6.4. Results
6.4.1. Characteristics of the EOMs applied
6.4.2. Total organic C and N in bulk soil and separated fractions
6.4.3. Characterization using pyrolysis-GC/MS of the bulk EOMs applied and of the soil fractions
6.4.4. Characterization using DRIFT spectroscopy of the bulk EOMs applied and the size and density fractions of soil
6.4.5. Relationships between analytical variables
6.5. Discussion
6.5.1. Comparison of the chemical composition of OM in soil fractions
6.5.2. Effects of EOM applications on the chemical composition of POM
6.5.3. Effects of EOM applications on the chemical composition of the 0-50 μm fraction
6.6. Conclusions
6.7. References
Conclusion générale et perspectives
