Monday, 14 November 2016

Chemical composition of lignocellulosic biomass in the wood of Abies religiosa across an altitudinal gradient

Published Date

Original article
DOI: 10.1007/s10086-016-1585-0

Cite this article as: 
Musule, R., Alarcón-Gutiérrez, E., Houbron, E.P. et al. J Wood Sci (2016). doi:10.1007/s10086-016-1585-0

Author
  • Ricardo Musule
  • Enrique Alarcón-Gutiérrez
  • Eric P. Houbron
  • Guadalupe M. Bárcenas-Pazos
  • M. del Rosario Pineda-López
  • Zaira Domínguez
  • Lázaro R. Sánchez-Velásquez
Abstract

Tree adaptation to environment has been extensively studied. However, little is known about the variations in structure and chemical composition of lignocellulosic biomass (LB) in relation to altitudinal gradient. We wonder, are there significant variations in the LB in the wood across an altitudinal gradient? To answer this, we carried out a study of Abies religiosa. Wood samples were collected from 36 trees, grown between 3000 and 3500 masl, and then subjected to gravimetric and FTIR (Fourier Transform Infrared) spectroscopic analyses. The gravimetric results showed a proportion of 54.81 ± 2.20 % cellulose, 12.37 ± 1.33 % hemicellulose and 24.68 ± 1.16 % of insoluble lignin. Using the principal components analysis with analysis of variance (ANOVA), significant differences were found at 3100 and 3200 masl in two independent components related to both hemicellulose and lignin, through gravimetry as well as the spectroscopic bands assigned to the carbonyl groups of these polymers, respectively. However, the observed changes in chemical composition of LB did not follow a linear relationship with respect to the altitudinal gradient, which suggests that complex environmental interactions could also be playing an important role. Also, there were significant differences (p < 0.05) in two of the empirical indexes calculated from the FTIR analysis.

References


  • 1.
    Kačík F, Šmíra P, Kačíková D, Reinprecht L, Nasswettrova A (2014) Chemical changes in fir wood from old buildings due to ageing. Cellul Chem Technol 48:79–88Google Scholar
  • 2.
    Dahlquist E (2013) Biomass as energy source: resources, systems and applications (sustainable energy developments). CRC Press/Taylor & Francis, London, pp 137–138Google Scholar
  • 3.
    Guerriero G, Hausman JF, Strauss J, Ertan H, Siddiqu KS (2016) Lignocellulosic biomass: biosynthesis, degradation, and industrial utilization. Eng Life Sci 16:1–16CrossRefGoogle Scholar
  • 4.
    Sluiter JB, Ruiz RO, Scarlata CJ, Sluiter AD, Templeton DW (2010) Compositional analysis of lignocellulosic feedstocks. 1. Review and description of methods. J Agric Food Chem 58:9043–9053CrossRefPubMedPubMedCentralGoogle Scholar
  • 5.
    Burton RA, Fincher GB (2014) Plant cell wall engineering: applications in biofuel production and improved human health. Curr Opin Biotechnol 26:79–84CrossRefPubMedGoogle Scholar
  • 6.
    Van Acker R, Vanholme R, Storme V, Mortimer JC, Dupree P, Boerjan W (2013) Lignin biosynthesis perturbations affect secondary cell wall composition and saccharification yield in Arabidopsis thaliana. Biotechnol Biofuels 6:46CrossRefPubMedPubMedCentralGoogle Scholar
  • 7.
    Guerriero G, Sergeant K, Hausman JF (2014) Wood biosynthesis and typologies: a molecular rhapsody. Tree Physiol 34:839–855CrossRefPubMedGoogle Scholar
  • 8.
    Tao G, Lestander TA, Geladi P, Xiong S (2012) Biomass properties in association with plant species and assortments I: a synthesis based on literature data of energy properties. Renew Sustain Energy Rev 16:3481–3506CrossRefGoogle Scholar
  • 9.
    Brandt A, Gräsvik J, Hallett JP, Welton T (2013) Deconstruction of lignocellulosic biomass with ionic liquids. Green Chem 15:550–583CrossRefGoogle Scholar
  • 10.
    Hames BR (2009) Biomass compositional analysis for energy applications. In: Jr Mielenz (ed) Biofuels, methods in molecular biology. Humana Press, Totowa, pp 145–167Google Scholar
  • 11.
    Rodziewicz P, Swarcewicz B, Chmielewska K, Wojakowska A, Stobiecki M (2014) Influence of abiotic stresses on plant proteome and metabolome changes. Acta Physiol Plant 36:1–19CrossRefGoogle Scholar
  • 12.
    Gall H, Philippe F, Domon JM, Gillet F, Pelloux J, Rayon C (2015) Cell wall metabolism in response to abiotic stress. Plants 4:112–166CrossRefPubMedPubMedCentralGoogle Scholar
  • 13.
    Osborne PL (2012) Tropical ecosystems and ecological concepts. Cambridge University Press, CambridgeCrossRefGoogle Scholar
  • 14.
    Serrada Hierro R (2008) Apuntes de selvicultura. In: Serrada Hierro R (ed) Apuntes de selvicultura universidad politécnica de madrid (in Spanish). EUI Técnica Forestal, Madrid, pp 83–131Google Scholar
  • 15.
    Suter L, Ruegg M, Zemp N, Hennig L, Widmer A (2014) Gene regulatory variation mediates flowering responses to vernalization along an altitudinal gradient in Arabidopsis thaliana. Plant Physiol 166:1928–1942CrossRefPubMedPubMedCentralGoogle Scholar
  • 16.
    Galván-Hernández DM, Lozada-García JA, Flores-Estévez N, Galindo-González J, Vázquez-Torres SM (2015) Altitudinal gradient effect on morphometric variation and leaf symmetry of Platanus mexicana Moric. Rev Chapingo Ser Ciencias For y del Ambient 21:171–183CrossRefGoogle Scholar
  • 17.
    Garten CT (2011) Comparison of forest soil carbon dynamics at five sites along a latitudinal gradient. Geoderma 167–168:30–40CrossRefGoogle Scholar
  • 18.
    Coomes DA, Allen RB (2007) Effects of size, competition and altitude on tree growth. J Ecol 95:1084–1097CrossRefGoogle Scholar
  • 19.
    Hoch G, Körner C (2012) Global patterns of mobile carbon stores in trees at the high-elevation tree line. Glob Ecol Biogeogr 21:861–871CrossRefGoogle Scholar
  • 20.
    Tsui CC, Tsai CC, Chen ZS (2013) Soil organic carbon stocks in relation to elevation gradients in volcanic ash soils of Taiwan. Geoderma 209–210:119–127CrossRefGoogle Scholar
  • 21.
    Xu G, Jiang H, Zhang Y, Korpelainen H, Li C (2013) Effect of warming on extracted soil carbon pools of Abies faxoniana forest at two elevations. For Ecol Manage 310:357–365CrossRefGoogle Scholar
  • 22.
    Michalet R, Schöb C, Lortie CJ, Brooker RW, Callaway RM (2014) Partitioning net interactions among plants along altitudinal gradients to study community responses to climate change. Funct Ecol 28:75–86CrossRefGoogle Scholar
  • 23.
    Richardson AD (2004) Foliar chemistry of balsam fir and red spruce in relation to elevation and the canopy light gradient in the mountains of the northeastern United States. Plant Soil 260:291–299CrossRefGoogle Scholar
  • 24.
    Genet M, Li M, Luo T, Fourcaud T, Clément-Vidal A, Stokes A (2011) Linking carbon supply to root cell-wall chemistry and mechanics at high altitudes in Abies georgei. Ann Bot 107:311–320CrossRefPubMedGoogle Scholar
  • 25.
    Battipaglia G, De Micco V, Sass-Klaassen U, Tognetti R, Makela A (2014) Special issue: WSE symposium: Wood growth under environmental changes: the need for a multidisciplinary approach. Tree Physiol 34:787–791CrossRefPubMedGoogle Scholar
  • 26.
    Sánchez-Velásquez LR, Pineda-López MR, Martínez AH (1991) Distribución y estructura de la población de Abies religiosa (H.B.K.) Schl. et Cham., en el Cofre de Perote, Estado de Veracruz, México (in Spanish). Acta Botánica Mex 16:45–55Google Scholar
  • 27.
    Pineda-López MR, Sanchez-Velásquez LR, Vazquez-Domínguez G, Rojo-Alboreca A (2013) The effects of land use change on carbon content in the aerial biomass of an Abies religiosa (Kunth Schltdl. et Cham.) forest in central Veracruz, Mexico. For Syst 22:82–93Google Scholar
  • 28.
    Rzedowski J (1978) Vegetación de México (in Spanish). Limusa, MexicoGoogle Scholar
  • 29.
    Pineda-López MR, Ortega-Solis R, Sánchez-Velásquez LR, Ortiz-Ceballos G, Vázquez-Domínguez G (2013) Population structure of Abies religiosa (Kunth) Schltdl. et Cham., in the ejido El Conejo of the national park Cofre de Perote, Veracruz, Mexico (in Spanish). Rev Chapingo Ser Ciencias For y del Ambient 19:375–385CrossRefGoogle Scholar
  • 30.
    Hoch G (2007) Cell wall hemicelluloses as mobile carbon stores in non-reproductive plant tissues. Funct Ecol 21:823–834CrossRefGoogle Scholar
  • 31.
    Chapin S, Matson PA, Vitousek P (2012) Plant carbon budgets. In: Chapin S, Matson PA, Vitousek P (eds) Principles of terrestrial ecosystem ecology. Springer, New York, pp 157–181Google Scholar
  • 32.
    Lara-González R, Sánchez-Velásquez LR, Corral-Aguirre J (2009) Regeneration of Abies religiosa in canopy gaps versus understory, Cofre de Perote national park, México (in Spanish). Agrociencia 43:739–747Google Scholar
  • 33.
    TAPPI T 264 cm-07 (2007) Preparation of wood for chemical analysis. Technical Association of the Pulp & Paper Industry, Peachtree CornersGoogle Scholar
  • 34.
    Goering HK, Van Soest PJ (1970) Forage fiber analyses (apparatus, reagents, procedures and some applications). USDA-ARS agricultural handbook 379, US Government Printing Office, Washington, DC, p 20
  • 35.
    Stewart CE, Moturi P, Follett RF, Halvorson AD (2015) Lignin biochemistry and soil N determine crop residue decomposition and soil priming. Biogeochemistry 124:335–351CrossRefGoogle Scholar
  • 36.
    Mclean JP, Jin G, Brennan M, Nieuwoudt MK, Harris PJ (2014) Using NIR and ATR-FTIR spectroscopy to rapidly detect compression wood in Pinus radiata. Can J For Res 44:820–830CrossRefGoogle Scholar
  • 37.
    Nelson ML, O’Connor RT (1964) Relation of certain infrared bands to cellulose crystallinity and crystal lattice type. Part II. A new infrared ratio for estimation of crystallinity in celluloses I and II. J Appl Polym Sci 8:1325–1341CrossRefGoogle Scholar
  • 38.
    Poletto M, Zattera AJ, Santana RMC (2012) Structural differences between wood species: evidence from chemical composition, FTIR spectroscopy, and thermogravimetric analysis. J Appl Polym Sci 126:E337–E344CrossRefGoogle Scholar
  • 39.
    Chen C, Luo J, Qin W, Tong Z (2014) Elemental analysis, chemical composition, cellulose crystallinity, and FT-IR spectra of Toona sinensis wood. Monatsh Chem 145:175–185CrossRefGoogle Scholar
  • 40.
    Euring D, Löfke C, Teichmann T, Polle A (2012) Nitrogen fertilization has differential effects on N allocation and lignin in two Populus species with contrasting ecology. Trees Struct Funct 26:1933–1942CrossRefGoogle Scholar
  • 41.
    Popescu MC, Popescu CM, Lisa G, Sakata Y (2011) Evaluation of morphological and chemical aspects of different wood species by spectroscopy and thermal methods. J Mol Struct 988:65–72CrossRefGoogle Scholar
  • 42.
    Conover WJ, Iman RL (1981) Rank transformations as a bridge between parametric and nonparametric statistics. Am Stat 35:124–129Google Scholar
  • 43.
    Lupoi JS, Singh S, Parthasarathi R, Simmonsa BA, Henry RJ (2015) Recent innovations in analytical methods for the qualitative and quantitative assessment of lignin. Renew Sustain Energy Rev 49:871–906CrossRefGoogle Scholar
  • 44.
    Xu F, Yu J, Tesso T, Dowell F, Wang D (2013) Qualitative and quantitative analysis of lignocellulosic biomass using infrared techniques: a mini-review. Appl Energy 104:801–809CrossRefGoogle Scholar
  • 45.
    So CL, Eberhardt TL (2013) A mid-IR multivariate analysis study on the gross calorific value in longleaf pine: impact on correlations with lignin and extractive contents. Wood Sci Technol 47:993–1003CrossRefGoogle Scholar
  • 46.
    Santoni I, Callone E, Sandak A, Sandak J, Dirè S (2015) Solid state NMR and IR characterization of wood polymer structure in relation to tree provenance. Carbohydr Polym 117:710–721CrossRefPubMedGoogle Scholar
  • 47.
    Chen H, Ferrari C, Angiuli M, Yao J, Raspi C, Bramanti E (2010) Qualitative and quantitative analysis of wood samples by Fourier transform infrared spectroscopy and multivariate analysis. Carbohydr Polym 82:772–778CrossRefGoogle Scholar
  • 48.
    Sammons RJ, Harper DP, Labbé N, Bozell JJ, Elder T, Rials TG (2013) Characterization of organosolv lignins using thermal and FT-IR spectroscopic analysis. Bioresources 8:2752–2767CrossRefGoogle Scholar
  • 49.
    Maréchal Y, Chanzy H (2000) The hydrogen bond network in I (β) cellulose as observed by infrared spectrometry. J Mol Struct 523:183–196CrossRefGoogle Scholar
  • 50.
    Espinoza-Herrera R (1996) Aspectos químicos de la Madera de Abies religiosa var. Típica (Oyamel) (in Spanish). Ciencia y Tecnología de la madera 10:11–17Google Scholar
  • 51.
    Avendaño-Hernández DM, Acosta-Mireles M, Carrillo-Anzures F, Etchevers-Barra JD (2009) Estimación de biomasa y carbono en un bosque de Abies religiosa (in Spanish). Rev Fitotec Mex 32:233–238Google Scholar
  • 52.
    Moura JCMS, Bonine CAV, Viana JdOF, Dornelas MC, Mazzafera P (2010) Abiotic and biotic stresses and changes in the lignin content and composition in plants. J Integr Plant Biol 52:360–376CrossRefPubMedGoogle Scholar
  • 53.
    Tenhaken R (2014) Cell wall remodeling under abiotic stress. Front Plant Sci 5:771PubMedGoogle Scholar
  • 54.
    Largo-Gosens A, Hernández-Altamirano M, García-Calvo L, Alonso-Simón A, Álvarez J, Acebes JL (2014) Fourier transform mid infrared spectroscopy applications for monitoring the structural plasticity of plant cell walls. Front Plant Sci 5:1–16CrossRefGoogle Scholar
  • 55.
    Whittaker RH (1978) Direct gradient analysis: techniques. In: Whittaker RH (ed) Handbook of vegetation science 5. Ordination and classification of communities. Dr Junk W. Springer, The Hague, pp 9–51Google Scholar
  • 56.
    Laureano RG, Lazo YO, Linares JC, Luque A, Martínez F, Seco JI, Merino J (2008) The cost of stress resistance: construction and maintenance costs of leaves and roots in two populations of Quercus ilex. Tree Physiol 28:1721–1728CrossRefPubMedGoogle Scholar
  • 57.
    Liu N, Guan LL, Sun FF, Wen DZ (2014) Alterations of chemical composition, construction cost and payback time in needles of Masson pine (Pinus massoniana L.) trees grown under pollution. J Plant Res 127:491–501CrossRefPubMedGoogle Scholar
  • 58.
    Grubb PJ (2015) Trade-offs in interspecific comparisons in plant ecology and how plants overcome proposed constraints. Plant Ecol Divers 0874:1–31Google Scholar
  • 59.
    Rosu D, Teaca CA, Bodirlau R, Rosu L (2010) FTIR and color change of the modified wood as a result of artificial light irradiation. J Photochem Photobiol B Biol 99:144–149CrossRefGoogle Scholar
  • 60.
    Emmanuel V, Odile B, Céline R (2015) FTIR spectroscopy of woods: a new approach to study the weathering of the carving face of a sculpture. Spectrochim Acta Part A Mol Biomol Spectrosc 136:1255–1259CrossRefGoogle Scholar
  • 61.
    Emandi A, Vasiliu CI, Budrugeac P, Stamatin I (2011) Quantitative investigation of wood composition by integrated FT-IR and thermogravimetric methods. Cellul Chem Technol 45:579–584Google Scholar
  • 62.
    Lupoi JS, Singh S, Simmons BA, Henry RJ (2013) Assessment of lignocellulosic biomass using analytical spectroscopy: an evolution to high-throughput techniques. Bioenergy Res 7:1–23CrossRefGoogle Scholar
  • 63.
    Popescu CM, Popescu MC, Vasile C (2011) Structural analysis of photodegraded lime wood by means of FT-IR and 2D IR correlation spectroscopy. Int J Biol Macromol 48:667–675CrossRefPubMedGoogle Scholar
  • 64.
    Calienno L, Lo Monaco A, Pelosi C, Picchio R (2014) Colour and chemical changes on photodegraded beech wood with or without red heartwood. Wood Sci Technol 48:1167–1180CrossRefGoogle Scholar

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