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PhD Thesis presentation : Chemical composition and biofuel potential

• f plant biomasses

Thesis · February 2013

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1 Presented by : Ir Bruno GODIN Promoters : Prof. Patrick GERIN (UCL-ELI) Dr Jérôme DELCARTE (CRA-W) 13/02/2013

PhD presentation

Chemical composition and biofuel potential of plant biomasses

2

• 1. Context
• Production of plant biomasses
• Conversion into biofuels
• Chemical composition and suitabilities to be converted

into biofuel

• Fibrous plant biomasses
• 1. Context
• 2. Objectives
• 3. Results and discussion
• 4. Conclusions and prospects

3

• High production of greenhouse gas  Climate change
• High dependence on fossil fuels  Volatile prices and uncertain availability

Fossil energy

Adapted of Vanholme, 2012

• 1. Context
• 2. Objectives
• 3. Results and discussion
• 4. Conclusions and prospects

4 Biofuel production from biomasses requires an accurate knowledge of the characteristics of the used resource

Renewable energy from biomasses

Adapted of Vanholme, 2012

• 1. Context
• 2. Objectives
• 3. Results and discussion
• 4. Conclusions and prospects

5

Biomass conversion to bioenergy

• Biomass
• Annual crop / Perennial crop / Algae / Wood/ Residues / Waste
• Bioenergy
• Thermal / Electric / Mechanical
• Conversion pathways
• Thermochemical  Combustion
• Biological  Anaerobic digestion / Ethanolic fermentation
• 1. Context
• 2. Objectives
• 3. Results and discussion
• 4. Conclusions and prospects

6

Adapted of ENERBIOM, 2012

Miscanthus Switchgrass Tall fescue

Perennial

Hemp

Annual

Spelt straw

Residues

Fibrous plant biomasses

• Non-food
• Acceptable biomass yield par hectare
• In less favorable soil and climatic conditions
• Need less input
• 1. Context
• 2. Objectives
• 3. Results and discussion
• 4. Conclusions and prospects

7

Lignin (5-15%) Hemicelluloses (10-30%) Cellulose (20-40%)

Adapted of Gnansounou, 2006

 Cellulose  Homogeneous and linear polysaccharide made of glucose units  Hemicelluloses  Heterogeneous and ramified polysaccharides mainly made

• f xylose units

 Lignin  Phenylpropan polymer  Other compounds  Pectins, proteins

Chemical composition of plant cell walls

Plant cell wall polymers

• 1. Context
• 2. Objectives
• 3. Results and discussion
• 4. Conclusions and prospects

8

Chemical composition of plant cell walls

Commelinids species differ in the composition of their wall

• 1. Context
• 2. Objectives
• 3. Results and discussion
• 4. Conclusions and prospects

9

• 1. Context
• 2. Objectives
• 3. Results and discussion
• 4. Conclusions and prospects

Outline

10

 Gross energy productivity per hectare

 Relative chemical characteristics of the biomass  Unknown impact  Dry matter yield per hectare  Dry matter content

What are the key parameters to classify fibrous plant species in order to maximize the gross energy productivity?

• 1. What are the key parameters to be used to

assess the gross energy productivity?

• 1. Context
• 2. Objectives
• 3. Results and discussion
• 4. Conclusions and prospects

11

 Suitabilities to be converted into biofuel

 Identification of joint relevant parameters of the chemical composition  Optimization of the analytical investment

What are the relevant parameters of the chemical composition of plant biomasses to be used to assess their suitabilities to be converted into biofuel?

• 2. What are the relevant parameters to be used to

assess the suitabilities to be converted into biofuel?

• 1. Context
• 2. Objectives
• 3. Results and discussion
• 4. Conclusions and prospects

12

 Optimizing biomass conversion requires a good knowledge of

the chemical characteristics

 Chemical composition  Hemicelluloses composition  Suitabilities to be converted into biofuel

What is the chemical composition of the considered biomasses?

• Sort these biomasses into groups with similar characteristics?
• 3. What are the chemical characteristics of

plant biomasses?

• 1. Context
• 2. Objectives
• 3. Results and discussion
• 4. Conclusions and prospects

13

• Abundance of the cellulose and hemicelluloses
• Assess available resources for biofuel production
• Van Soest method
• Reference
• Bias ?

What is the appropriate method for the quantification of cellulose and hemicelluloses in the context of biofuel production?

• 4. How to quantify correctly

cellulose and hemicelluloses?

• 1. Context
• 2. Objectives
• 3. Results and discussion
• 4. Conclusions and prospects

14

• 1. Context
• 2. Objectives
• 3. Results and discussion
• 4. Conclusions and prospects

Outline

15

 Relative chemical characteristics of the biomass  Dry matter yield per hectare  Dry matter content

3.1. Key parameters to assess the gross energy productivity

• 3. Results and discussion

3.1. Most important parameters to assess the productivity

16

 Dry matter yield per hectare

 Plant maturity  Autumn / (example of fiber sorghum)

Key parameters to assess the gross energy productivity

Dry matter yield per hectare Indicator for the anaerobic digestion Indicator for the combustion Bioethanol potential

Tons of dry matter /(hectare x year) Tons of enzymatically digestible

• rgnic matter/(hectare x year)

Higher heating value /(hectare x year) Liters of bioethanol /(hectare x year)

17

Key parameters to assess the gross energy productivity

 Dry matter yield per hectare

 Plant species  Soil and climate conditions

 Example of Gembloux (favorable) vs Libramont (less favorable)

Tons of dry matter /(hectare x year)

• 3. Results and discussion

3.1. Most important parameters to assess the productivity

18

 Dry matter content

 Combustion  Bioethanol

Key parameters to assess the gross energy productivity

• 3. Results and discussion

3.1. Most important parameters to assess the productivity

19

 Chemical characteristics of the biomass  Unimportant / (example of fiber sorghum)

 Not unimportant for the biofuel conversion process

Key parameters to assess the gross energy productivity

Chemical composition Indicator for the anaerobic digestion Indicator for the combustion Bioethanol potential

Chemical components kg/kg of dry matter Tons of enzymatically digestible

• rgnic matter /(hectare x year)

GJ of higher heating value /(hectare x year) Liters of bioethanol /(hectare x year)

20

3.2. Chemical composition and suitabilities to be converted into biofuel

• 3. Results and discussion

3.2. Chemical composition and biofuel potential

21

 Plant species diversity structured into groups with similar chemical

characteristics

Godin B., Lamaudière S., Agneessens R., , Schmit T., Goffart J.-P., Stilmant D., Gerin P. & Delcarte J., 2013. Energy and Fuels, 27, 2588-2598.

Chemical composition and suitabilities to be converted into biofuel

CO : Commelinid s NC : Non-commelinid magnoliophyta PI : Pinophyta

• 3. Results and discussion

3.2. Chemical composition and biofuel potential

NC-LF CO-LF PI-FI

NC-WO

22

0,0 0,2 0,4 0,6 0,8 1,0 CO-FI (n=382) CO-MF (n=348) CO-AM (n=146) NC-LI (n=8) NC-FI (n=123) NC-MF (n=21) NC-SU (n=8) GY-FI (n=3) Chemical components kg/kg of dry matter

Commelinids

Non-commelinid magnoliophyta

Pinophyta

Fibrous Fibrous Fibrous Less fibrous Less fibrous Rich in starch Rich in total soluble sugars Woody

 Chemical composition of the groups with similar chemical characteristics

Phylogenetic cleavage Hemicelluloses and Lignin Fiber cleavage

• 3. Results and discussion

3.2. Chemical composition and biofuel potential

Chemical composition and suitabilities to be converted into biofuel

23

Godin B., Lamaudière S., Agneessens R., , Schmit T., Goffart J.-P., Stilmant D., Gerin P. & Delcarte J., 2013. Energy and Fuels, 27, 2588-2598.

• 3. Results and discussion

3.2. Chemical composition and biofuel potential

Chemical composition and suitabilities to be converted into biofuel

CO : Commelinid s NC : Non-commelinid magnoliophyta PI : Pinophyta

NC-LF PI-FI NC-WO

 Plant species diversity structured into groups with similar chemical

characteristics

24

0,0 0,2 0,4 0,6 0,8 1,0 CO-FI (n=120) CO-MF (n=56) CO-AM (n=37) NC-LI (n=8) NC-FI (n=47) NC-MF (n=21) NC-SU (n=8) GY-FI (n=3) Hemicellulosic components kg/kg of hemicelluloses

Commelinids

Non-commelinid magnoliophyta

Pinophyta

Fibrous Fibrous Fibrous Less fibrous Less fibrous Rich in starch Rich in total soluble sugars Woody

 Hemicelluloses composition of the groups with similar chemical

characteristics

Phylogenetic cleavage  Xylan+Arabinan and Mannan

• 3. Results and discussion

3.2. Chemical composition and biofuel potential

Chemical composition and suitabilities to be converted into biofuel

25

 Indicator for the anaerobic digestion potential without

pretreatment of the biomass  Enzymatically digestible organic matter

 Indicator for the combustion potential after drying of the biomass

 Higher heating value

 Bioethanol potential

 Theoretical model

Godin B., Lamaudière S., Agneessens R., , Schmit T., Goffart J.-P., Stilmant D., Gerin P. & Delcarte J., 2013. Energy and Fuels, 27, 2588-2598.

Link between chemical composition and suitabilities to be converted into biofuel

• 3. Results and discussion

3.2. Chemical composition and biofuel potential

26

0,225 0,635 0,742 0,159 0,450 0,791 0,973 0,096 0,0 0,2 0,4 0,6 0,8 1,0 CO-FI (n=382) CO-MF (n=348) CO-AM (n=146) NC-LI (n=8) NC-FI (n=123) NC-MF (n=21) NC-SU (n=8) GY-FI (n=3) Enzymatically digestible orgnic matter kg/kg of dry organic matter

Link between chemical composition and suitabilities to be converted into biofuel

Commelinids

Pinophyta

Fibrous Fibrous Fibrous Rich in starch Rich in total soluble sugars Woody Less fibrous Less fibrous

 Indicator for the anaerobic digestion potential

 Favorable for biomasses with cytoplasm-rich metabolically active cell

• 3. Results and discussion

3.2. Chemical composition and biofuel potential

Non-commelinid magnoliophyta

27

19,1 18,8 18,3 19,5 18,2 16,8 17,1 20,3 5 10 15 20 CO-FI (n=382) CO-MF (n=348) CO-AM (n=146) NC-LI (n=8) NC-FI (n=123) NC-MF (n=21) NC-SU (n=8) GY-FI (n=3) Higher heating value MJ/kg of dry matter

Link between chemical composition and suitabilities to be converted into biofuel

Commelinids

Pinophyta

Fibrous Fibrous Fibrous Rich in starch Rich in total soluble sugars

 Indicator for the combustion potential

 Favorable for biomasses with a high organic matter content

Woody Less fibrous Less fibrous

• 3. Results and discussion

3.2. Chemical composition and biofuel potential

Non-commelinid magnoliophyta

28

0,0 0,1 0,2 0,3 0,4 0,5 CO-FI (n=382) CO-MF (n=348) CO-AM (n=146) NC-LI (n=8) NC-FI (n=123) NC-MF (n=21) NC-SU (n=8) GY-FI (n=3) Liter of bioethanol per kg of dry matter

Link between chemical composition and suitabilities to be converted into biofuel

 Bioethanol potential

 Favorable for all the biomass groups

 Except for non-commelinid less fibrous magnoliophyta biomasses

Commelinids

Pinophyta

Fibrous Fibrous Rich in starch Rich in total soluble sugars Woody Less fibrous Less fibrous

• 3. Results and discussion

3.2. Chemical composition and biofuel potential

Non-commelinid magnoliophyta

Fibrous

29

 Impact of the plant maturity  Impact of other crop husbandry factors

 Location, Year, Cultivar and Level of nitrogen fertilization

Impact of the crop husbandry on the chemical composition and the suitabilities to be converted into biofuel

Godin B., Lamaudière S., Agneessens R., , Schmit T., Goffart J.-P., Stilmant D., Gerin P. & Delcarte J., 2013. J. of the Sci. of Food and Agri., Accepted.

• 3. Results and discussion

3.2. Chemical composition and biofuel potential

30

 Chemical characteristics  Dependent on the plant maturity

 Example of fiber sorghum

Impact of the crop husbandry on the chemical composition and the suitabilities to be converted into biofuel

Godin B., Lamaudière S., Agneessens R., , Schmit T., Goffart J.-P., Stilmant D., Gerin P. & Delcarte J., 2013. J. of the Sci. of Food and Agri., Accepted.

Chemical composition Indicator for the anaerobic digestion Indicator for the combustion Bioethanol potential Hemicelluloses composition

Chemical components kg/kg of dry matter Hemicellulosic components kg/kg of hemicelluloses Higher heating value MJ/kg of dry matter Enzymatically digestible orgnic matter Kg/kg of dry organic matter Liters of bioethanol per kg of dry matter

31

Impact of the crop husbandry on the chemical composition and the suitabilities to be converted into biofuel

Chemical components kg/kg of dry matter

• 3. Results and discussion

3.2. Chemical composition and biofuel potential

Godin B., Lamaudière S., Agneessens R., , Schmit T., Goffart J.-P., Stilmant D., Gerin P. & Delcarte J., 2013. Industrial Crops and Products, 48, 1-12.

 Chemical characteristics  Do not dependent on the other crop

husbandry factors

 Location, Year, Cultivar and Level of nitrogen fertilization

32

3.3. Relevant parameters to assess the suitabilities to be converted into biofuel

 Identification of joint relevant parameters of the chemical

composition

• 3. Results and discussion

3.3. Relevant parameters to assess the biofuel potentials

33

Relevant parameters to assess the suitabilities to be converted into biofuel

 Cellulose, hemicelluloses and mineral compounds content

 Indicator for the anaerobic digestion (Enzymatically digestible organic

matter)

 Indicator for the combustion (Higher heating value)  Bioethanol potential

 Decision tools  Classification key of plant biomasses

• 3. Results and discussion

3.3. Relevant parameters to assess the biofuel potentials

34

 Decision tool

35

Non-commelinid high total soluble sugars magnoliophyta biomasses Non-commelinid less fibrous magnoliophyta biomasses Commelinid high starch biomasses Commelinid fibrous biomasses Non-commelinid fibrous magnoliophyta biomasses

Non-commelinid fibrous magnoliophyta biomasses Commelinid less fibrous biomasses Commelinid fibrous biomasses Pinophyta fibrous biomasses

Non-commelinid woody magnoliophyta biomasses

 Classification key of plant biomasses

• 3. Results and discussion

3.3. Relevant parameters to assess the biofuel potentials

36

• The Van Soest method
• Fiber fractionation by successive chemical extractions and gravimetric

quantification

• Contamination of the fractions by non-cellulosic and non-hemicellulosic

components

• Bias

3.4. Van Soest method : reference to quantify cellulose and hemicelluloses

• 3. Results and discussion

3.4. NDE-SAH-LC-CAD and Van Soest method

37

 The NDE-SAH-LC-CAD method

1. Extraction with a pH 7 phosphate buffer containing α-amylase and with Van Soest neutral detergent (NDE) 2. Solubilization and hydrolysis of cellulose and hemicelluloses with sulfuric acid (SAH) 3. Separation of the monosaccharides released by the acid hydrolysis by a classic chromatographic system (LC) 4. Quantification of the monosaccharides released by the acid hydrolysis by the charged aerosol detector (CAD)

NDE-SAH-LC-CAD method : appropriate to quantify cellulose et hemicelluloses

• 3. Results and discussion

3.4. NDE-SAH-LC-CAD and Van Soest method

38

 Extraction of non-lignocellulosic components with a phosphate buffer

containing α-amylase and with Van Soest neutral detergent (NDE)

 Eliminating interference

Godin B., Agneessens R., Gerin P., Delcarte J., 2011. Talanta, 85, 2014-2026.

NDE-SAH-LC-CAD method : appropriate to quantify cellulose et hemicelluloses

• 3. Results and discussion

3.4. NDE-SAH-LC-CAD and Van Soest method

39

 The NDE-SAH-LC-CAD method

1. Extraction with a pH 7 phosphate buffer containing α-amylase and with Van Soest neutral detergent (NDE) 2. Solubilization and hydrolysis of cellulose and hemicelluloses with sulfuric acid (SAH) 3. Separation of the monosaccharides released by the acid hydrolysis with a classic chromatographic system (LC) 4. Quantification of the monosaccharides released by the acid hydrolysis with the charged aerosol detector (CAD)

NDE-SAH-LC-CAD method : appropriate to quantify cellulose et hemicelluloses

• 3. Results and discussion

3.4. NDE-SAH-LC-CAD and Van Soest method

40

 Solubilization and hydrolysis of cellulose and hemicelluloses to

monosaccharides with sulfuric acid (SAH)

Design of experiments (Box-Behnken)  Step 2 : Hydrolysis time (120 min)  Most significant

Godin B., Agneessens R., Gerin P., Delcarte J., 2011. Talanta, 85, 2014-2026.

NDE-SAH-LC-CAD method : appropriate to quantify cellulose et hemicelluloses

• 3. Results and discussion

3.4. NDE-SAH-LC-CAD and Van Soest method

41

 The NDE-SAH-LC-CAD method

1. Extraction with a pH 7 phosphate buffer containing α-amylase and with Van Soest neutral detergent (NDE) 2. Solubilization and hydrolysis of cellulose and hemicelluloses with sulfuric acid (SAH) 3. Separation of the monosaccharides released by the acid hydrolysis with a classic chromatographic system (LC) 4. Quantification of the monosaccharides released by the acid hydrolysis with the charged aerosol detector (CAD)

NDE-SAH-LC-CAD method : appropriate to quantify cellulose et hemicelluloses

• 3. Results and discussion

3.4. NDE-SAH-LC-CAD and Van Soest method

42

 Separation of the monosaccharides released by the acid hydrolysis

with a classic chromatographic system (LC)

Resolution between chromatographic peaks is higher than 1,50 Critical separation LC column made of a sulfonate divinylbenzene-styrene copolymer substituted with lead

Godin B., Agneessens R., Gerin P. A., Delcarte J., 2011. Talanta, 85, 2014-2026.

NDE-SAH-LC-CAD method : appropriate to quantify cellulose et hemicelluloses

• 3. Results and discussion

3.4. NDE-SAH-LC-CAD and Van Soest method

43

 The NDE-SAH-LC-CAD method

1. Extraction with a pH 7 phosphate buffer containing α-amylase and with Van Soest neutral detergent (NDE) 2. Solubilization and hydrolysis of cellulose and hemicelluloses with sulfuric acid (SAH) 3. Separation of the monosaccharides released by the acid hydrolysis with a classic chromatographic system (LC) 4. Quantification of the monosaccharides released by the acid hydrolysis with the charged aerosol detector (CAD)

NDE-SAH-LC-CAD method : appropriate to quantify cellulose et hemicelluloses

• 3. Results and discussion

3.4. NDE-SAH-LC-CAD and Van Soest method

44

 Quantification of the monosaccharides released by the acid

hydrolysis with the charged aerosol detector (CAD)

Godin B., Agneessens R., Gerin P., Delcarte J., 2011. Talanta, 85, 2014-2026.

 Charged aerosol detector

 Step 1 : Nebulization and drying  Step 2 : Transfer of positive charges to

the particles

 Step 3 : Measurement of the charge by

an electrometer

NDE-SAH-LC-CAD method : appropriate to quantify cellulose et hemicelluloses

• 3. Results and discussion

3.4. NDE-SAH-LC-CAD and Van Soest method

45

Godin B., Agneessens R., Gerin P., Delcarte J., 2011. Talanta, 85, 2014-2026.

NDE-SAH-LC-CAD method : appropriate to quantify cellulose et hemicelluloses

 High accuracy of the NDE-SAH-LC-CAD method

 Monosaccharidic composition of cellulose and hemicelluloses  Precise

• 3. Results and discussion

3.4. NDE-SAH-LC-CAD and Van Soest method

46

 Van Soest method is biased compared to the NDE-SAH-LC-CAD

method

 Importance to know which method is used

Commelinid biomasses (n=306) Non-commelinid magnoliophyta biomasses (n=108) Van Soest method Van Soest method NDE-SAH-LC-CAD method NDE-SAH-LC-CAD method

Godin B., Agneessens R., Gerin P., Delcarte J., 2013. Biomass and Bioenergy. Submitted.

Y = 0,856 X + 1,82 R2 = 0,85 RPD = 2,6 Y = 1,381 X - 0,79 R2 = 0,88 RPD = 2,9

NDE-SAH-LC-CAD method compared to Van Soest method

• 3. Results and discussion

3.4. NDE-SAH-LC-CAD and Van Soest method

47

 The results of the NDE-SAH-LC-CAD method can be predicted by

those of the Van Soest method



NDE-SAH-LC-CAD method  Gives hemicelluloses monosaccharidic composition Commelinid biomasses (n=306) Non-commelinid magnoliophyta biomasses (n=108) Van Soest method Van Soest method NDE-SAH-LC-CAD method NDE-SAH-LC-CAD method

Godin B., Agneessens R., Gerin P., Delcarte J., 2013. Biomass and Bioenergy. Submitted.

Y = 0,856 X + 1,82 R2 = 0,85 RPD = 2,6 Y = 1,381 X - 0,79 R2 = 0,88 RPD = 2,9

NDE-SAH-LC-CAD method compared to Van Soest method

• 3. Results and discussion

3.4. NDE-SAH-LC-CAD and Van Soest method

48

• 1. Context
• 2. Objectives
• 3. Results and discussion
• 4. Conclusions and prospects

Outline

49

Key parameters to assess the gross energy productivity

 Dry matter yield per hectare

 Plant species  Soil and climatic conditions  Plant maturity  Autumn

 Dry matter content

 Combustion

 Relative chemical characteristics of the biomass  Unimportant

 Important for the biofuel conversion process  Plant maturity

• 1. Context
• 2. Objectives
• 3. Results and discussion
• 4. Conclusions and prospects

50

Relevant parameters to assess the suitabilities to be converted into biofuel

 Cellulose, hemicelluloses and mineral compounds content

 Decision tools  Classification key of plant biomasses

• 1. Context
• 2. Objectives
• 3. Results and discussion
• 4. Conclusions and prospects

51

Chemical composition and suitabilities to be converted into biofuel

 Suitabilities to be converted into biofuel

 The indicator for the anaerobic digestion is favorable for cytoplasm-rich

metabolically active cell biomasses

 The indicator for the combustion is favorable for biomasses with a high

• rganic matter content

 Bioethanol potential is favorable for all the biomass groups

 Except for non-commelinid less fibrous magnoliophyta biomasses

• 1. Context
• 2. Objectives
• 3. Results and discussion
• 4. Conclusions and prospects

52

Chemical composition and suitabilities to be converted into biofuel

 The diversity of biomasses is structured in groups with similar

chemical characteristics

 Phylogenetic cleavage

 Hemicelluloses and Lignin / Xylan+Arabinan and Mannan

 Fiber cleavage

 Mineral compounds

• 1. Context
• 2. Objectives
• 3. Results and discussion
• 4. Conclusions and prospects

53

NDE-SAH-LC-CAD method : appropriate to quantify cellulose et hemicelluloses

 Important to know which method is used to assess the available

amounts of cellulose and hemicelluloses

 NDE-SAH-LC-CAD method  High accuracy  Van Soest method  Biased

 The results of the NDE-SAH-LC-CAD method can be predicted by

those of the Van Soest method

 NDE-SAH-LC-CAD method  Gives hemicelluloses monosaccharidic composition

• 1. Context
• 2. Objectives
• 3. Results and discussion
• 4. Conclusions and prospects

54

 Near infrared spectroscopy

 Calibration equations for the measured chemical parameters  Prediction of the suitabilities to be converted into biofuel

Prospects

• 1. Context
• 2. Objectives
• 3. Results and discussion
• 4. Conclusions and prospects

55

 Pilot unit

 Conversion into energy of the biomasses with the best suitabilities to be

converted into biofuel

 Bioproducts

 Biorefinery  Biomass sequential fractionation of its main chemical

components

Prospects

• 1. Context
• 2. Objectives
• 3. Results and discussion
• 4. Conclusions and prospects

56

Thank you for your attention

57

 Godin B., Lamaudière S., Agneessens R., Schmit T., Goffart J.-P., Stilmant D.,

Gerin P. A. & Delcarte J., 2013. Chemical characteristics and biofuel potential of several vegetal biomasses grown under a wide range of environmental conditions. Industrial Crops and Products, 46, 1-12.

 Godin B., Lamaudière S., Agneessens R., Schmit T., Goffart J.-P., Stilmant D.,

Gerin P. A. & Delcarte J., 2013. Chemical characteristics and biofuels potentials of various plant biomasses: influence of the harvesting date. Journal of the Science of Food and Agriculture, DOI 10.1002/jsfa.6159.

 Godin B., Lamaudière S., Agneessens R., Schmit T., Goffart J.-P., Stilmant D.,

Gerin P. A. & Delcarte J., 2013. Chemical composition and biofuel potentials of a wide diversity of plant biomasses. Energy and Fuels, 27, 2588-2598.

 Godin B., Agneessens R., Gerin P. A. & Delcarte J., 2013. Structural carbohydrates

in plant biomasses: correlations between the detergent fiber and the dietary fiber

• methods. Biomass and Bioenergy, Submitted.

 Godin B., Agneessens R., Gerin P. A. & Delcarte J., 2011. Composition of structural

carbohydrates in biomass: Precision of a method using a neutral detergent extraction and a charged aerosol detector. Talanta, 85, 2014-2026

 Godin B., Agneessens R., Gofflot S., Lamaudière S., Sinnaeve G., Gerin P. A. &

Delcarte J., 2011. Revue sur les méthodes de caractérisation des polysaccharides structuraux des biomasses lignocellulosiques. Biotechnol. Agron. Soc. Environ., 15, 165- 182.

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