Wood colorimetry of Lauraceae species native to Brazil

Authors

  • Helena Vieira Federal University of Paraná. Post-Graduate Program of Forest Engineering. Curitiba, Paraná, Brazil.
  • Joielan Xipaia dos Santos Federal University of Paraná. Post-Graduate Program of Forest Engineering. Curitiba, Paraná, Brazil.
  • Deivison Venicio Souza Federal University of Pará. Department of Forest Engineering. Altamira, Pará, Brazil.
  • Tawani Lorena Naide Acosta Federal University of Paraná. Post-Graduate Program of Forest Engineering. Curitiba, Paraná, Brazil.
  • Polliana D’ Angelo Rios University of Santa Catarina State. Department of Forest Engineering. Lages, Santa Catarina, Brazil.
  • Graciela Ines Bolzon de Muñiz Federal University of Paraná. Department of Forest Engineering and Technology, Curitiba, Paraná, Brazil.
  • Simone Ribeiro Morrone Federal University of Paraná. Department of Forest Engineering and Technology, Curitiba, Paraná, Brazil.
  • Silvana Nisgoski Federal University of Paraná. Department of Forest Engineering and Technology, Curitiba, Paraná, Brazil.

DOI:

https://doi.org/10.22320/s0718221x/2024.45

Keywords:

Chromatic coordinates, native wood, Nectandra, Ocotea, species discrimination, visible reflectance spectra

Abstract

Considering the complexity and difficulty of identifying forest species, wooden disks were collected to verify the potential of colorimetry to distinguish native species from Araucaria Forest stands of the Lauraceae family. The following species were used: Nectandra megapotamica, Ocotea indecora, Ocotea diospyrifolia and Ocotea puberula. Nees, to provide data on these species that grow naturally in Santa Catarina state, southern Brazil, enriching a robust database that can be practically applied in the commercialization of native woods. Visible spectra and colorimetric parameters were obtained from each anatomical surface and the results were evaluated by comparing the mean of each species regarding radial trunk position and anatomical surface. The data were also submitted to principal component analysis and performance of discriminant models (k-NN, SVM and ANN) for species discrimination with raw and second-derivative data. In general, colorimetric data presented different behavior, and chromatic coordinates a* and b* had higher potential for distinguishing the species. According to the mean spectra, Ocotea indecora had reflectance values different from the other species. By principal component analysis, raw data indicated the separation only of Ocotea indecora, while second-derivative data allowed better distinction of species. In all discrimination models, second-derivative data produced the best results. Thus, the use of colorimetry has potential for wood distinction of the Lauraceae species evaluated, improving the oversight of illegally traded timber.

Downloads

Download data is not yet available.

Author Biographies

Helena Vieira, Federal University of Paraná. Post-Graduate Program of Forest Engineering. Curitiba, Paraná, Brazil.

Biography

Joielan Xipaia dos Santos, Federal University of Paraná. Post-Graduate Program of Forest Engineering. Curitiba, Paraná, Brazil.

Biography

Deivison Venicio Souza, Federal University of Pará. Department of Forest Engineering. Altamira, Pará, Brazil.

Biography

Tawani Lorena Naide Acosta, Federal University of Paraná. Post-Graduate Program of Forest Engineering. Curitiba, Paraná, Brazil.

Biography

Polliana D’ Angelo Rios, University of Santa Catarina State. Department of Forest Engineering. Lages, Santa Catarina, Brazil.

Biography

Graciela Ines Bolzon de Muñiz, Federal University of Paraná. Department of Forest Engineering and Technology, Curitiba, Paraná, Brazil.

Biography

Simone Ribeiro Morrone, Federal University of Paraná. Department of Forest Engineering and Technology, Curitiba, Paraná, Brazil.

Biography

Silvana Nisgoski, Federal University of Paraná. Department of Forest Engineering and Technology, Curitiba, Paraná, Brazil.

Biography

References

Agresti, G.; Bonifazi, G.; Calienno, L.; Capobianco, G.; Lo Monaco, A.; Pelosi, C.; Picchio, R.; Serranti, S. 2013. Surface investigation of photodegraded wood by colour monitoring; infrared spectroscopy and hyperspectral imaging. Journal of Spectroscopy 2013(1): e380536. https://doi.org/10.1155/2013/380536

Atayde, C.M.; Gonçalez, J.C.; Camargos, J.A.A. 2011. Características colorimétricas entre as seções anatômicas da madeira de muirapiranga (Brosimum sp.). Cerne 17(2): 231-235. https://doi.org/10.1590/S0104-77602011000200011

Autran, C.S.; Gonçalez, J.C. 2006. Caracterização colorimétrica das madeiras de muirapiranga (Brosi- mum rubescenstaub.) e de seringueira (Hevea brasiliensis; clone TJIR 16 Müll Arg.) visando à utilização em interiores. Ciencia Florestal 16(4): 445-451. https://doi.org/10.5902/198050981926

Barros, S.V.S.; Muniz, G.I.B.; Matos, J.L.M. 2014. Caracterização colorimétrica das madeiras de três espécies florestais da Amazônia. Cerne 20(3): 337-342. https://doi.org/10.1590/01047760201420031421

Box, G.E.P.; Cox, D.R. 1964. An analysis of transformation (with discussion). Journal of the Royal Statistical Society: Series B (Methodological) 26(2): 211-243. https://doi.org/10.1111/j.2517-6161.1964.tb00553.x

Cademartori, P.H.G.; Schneid, E.; Gatto, D.A.; Stangerlin, D.M.; Beltrame, R. 2013. Thermal modification of Eucalyptus grandis wood: variation of colorimetric parameters. Maderas. Ciencia y Tecnología 15: 57-64. http://dx.doi.org/10.4067/S0718-221X2013005000005

Calienno, L.; Lo Monaco, A.; Pelosi, C.; Picchio, R. 2014. Colour and chemical changes on photo-degraded beech wood with or without red heartwood. Wood Science and Technology 48:1167-1180. https://doi.org/10.1007/s00226-014-0670-z

Camargos, J. A. A.; Gonçalez, J. C. A. 2001. A colorimetria aplicada como instrumento na elaboração de uma tabela de cores de madeira. Brasil Florestal 71: 30-41. http://www.realp.unb.br/jspui/handle/10482/10497

Garcia, R.A.; de Oliveira, N.S.; do Nascimento, A.M.; de Souza, N.D. 2014. Colorimetria de madeiras dos gêneros Eucalyptus e Corymbia e sua correlação com a densidade. Cerne 20(4): 509-517. https://doi.org/10.1590/01047760201420041316

Gasper, A.L.; Sevegnani, L.; Vibrans, A.C.; Marcos Sobral, M.; Uhlmann, A.; Lingner, D.V.; Rigon Júnior, M. J.; Verdi, M.; Santos, A.S.; Dreveck, S.; Korte, A. 2013. Inventário florístico florestal de Santa Catarina: espécies da Floresta Ombrófila Mista. Rodriguésia 64(2): 201-210. https://doi.org/10.1590/S2175-78602013000200001

Gasson, P. 2011. How precise can wood identification be? Wood anatomy’s role in support of the legal timber trade; especially CITES. IAWA Jornal 32(2): 137-154. http://dx.doi.org/10.1163/22941932-90000049

Herdt, S.T.; Melo Júnior, J.C.F. 2016. Anatomia sistemática e ecológica da madeira de Nectandra Rol. ex Rottb. (Lauraceae). Balduinia 54: 11-21. https://doi.org/10.5902/2358198022563

Hongyu, K.; Sandanielo, V.L.M.; de Oliveira Junior, G.J. 2016. Análise de componentes principais: resumo teórico; aplicação e interpretação. E&S Engineering and Science 5(1): 83-90. https://doi.org/10.18607/ES201653398

Kamperidou, V.; Barboutins, I.; Vasileiou, V. 2013. Response of colour and hygroscopic properties of Scots pine wood to thermal treatment. Journal of Forestry Research 24: 571-575. https://doi.org/10.1007/s11676-013-0389-y

Kassambara, A.; Mundt, F. 2017. Factoextra: Extract and Visualize the Results of Multivariate Data Analyses. R package version 1.0.5. http://dx.doi.org/10.32614/CRAN.package.factoextra

Kuhn, M.; Wing, J.; Weston, S.; Williams, A.; Keefer, C.; Engelhardt, A.; Benesty, M. 2020. Package ‘caret’. https://cran.radicaldevelop.com/web/packages/caret/caret.pdf

Lê, S.; Josse, J.; Husson, F. 2008. FactoMineR: an R package for multivariate analysis. Journal of Statistical Software 25(1): 1-18. https://doi.org/10.18637/jss.v025.i01

Lima, C.M.; Gonçalez, J.C.; Costa, T.R.V.D.; Pereira, R.S.; Lima, J.B.M.; Lima, M.D.S. A. 2013. Comportamento da cor de lâminas de madeira de Paumarfim (Balfourodendron riedelianum) tratada com produtos de acabamento. Revista Árvore 37(2): 377-384. https://doi.org/10.1590/S0100-67622013000200020

Martins, M.F.; Beltrame, R.; Delucis, R.A.; Gatto, D.A.; de Cademartori, P.H.G.; dos Santos, G.A. 2015. Colorimetria como ferramenta de agrupamento de madeira de clones de eucalipto. Pesquisa Florestal Brasileira 35(84): 443-449. https://doi.org/10.4336/2015.pfb.35.84.929

Mori, C.L.S.O.; Lima, J.T.; Mori, F.A.; Trugilho, P.F.; Goncalez, J.C. 2005. Caracterização da cor da madeira de clones de híbridos de Eucalyptus spp. Cerne 11(2): 137-146. http://www.bibliotecaflorestal.ufv.br/bitstream/handle/123456789/18128/Cerne_v11_n2_p137-146_2005.pdf

Moya, R.; Fallas, R.S.; Bonilla, P.J; Tenorio, C. 2012. Relationship between wood color parameters measured by the CIELab system and extractive and phenol content in Acacia mangium and Vochysia guatemalensis from fast-growth plantations. Molecules 17(4): 3639-3652. https://doi.org/10.3390%2Fmolecu-les17043639

Nisgoski, S.; de Muniz, G.I.B.; Gonçalves, T.A.P.; Ballarin, A.W. 2017a. Use of visible and near-infrared spectroscopy for discrimination of eucalypt species by examination of solid samples. Journal of Tropical Forest Science 29(3): 371-379. http://dx.doi.org/10.26525/jtfs2017.29.3.371379

Nisgoski, S.; de Oliveira, A.A.; de Muñiz, G.I.B. 2017b. Artificial neural network and SIMCA classification in some wood discrimination based on near-infrared spectra. Wood Science and Technology 51(4): 929-942. https://doi.org/10.1007/s00226-017-0915-8

Nishino, Y.; Janin, G.; Yainada, Y.; Kitano, D. 2000. Relations between the colorimetric values and densities of sapwood. Journal of Wood Science 46(4): 267-272. https://doi.org/10.1007/BF00766215

Nishino, Y.; Janin, G.; Chanson, B.; Détienne, P.; Gril, J.; Thibaut, B. 1998. Colorimetry of wood specimens from French Guiana. Journal of Wood Science 44(1): 3-8. https://doi.org/10.1007/BF00521867

Oliveira, W.C.; Callado, C. H.; Marquete, O. 2001. Anatomia do lenho de espécies do gênero Nectan- dra Rol. ex Rottb. (Lauraceae). Rodriguesia 52(81): 125-134. https://doi.org/10.1590/2175-78602001528106

Pastore, T.C.M.; Santos, K.O.; Rubim, J.C. 2004. A spectrocolorimetric study on the effect of ultraviolet irradiation of four tropical hardwoods. Bioresource Technology 93(1): 37-42. https://doi.org/10.1016/j.biortech.2003.10.035

R Core Team. 2018. R: A language and environment for statistical computing. R Foundation for Statistical Computing; Vienna. Austria. https://www.R-project.org/

Ribeiro, E.S.; Gonçalez, J.C.; Lima, C.M.; Rodrigues, E.C.C.; Paula, M.H.; Mesquita, R. R.S.; Queiroz, F.L.C.; Lesses, O.M. G. 2018. Colorimetry and anatomical characterization of commercial wood species from the Brazilian Amazon. Australian Jour nal of Basic and Applied Sciences 12(2): 15-23. http://dx.doi.org/10.22587/ajbas.2018.12.2.4

Romagnoli, M.; Segoloni, E.; Luna, M.; Margaritelli, A.; Gatti, M.; Santamaria, U.; Vinciguerra, V. 2013. Wood colour in Lapacho (Tabebuia serratifolia): chemical composition and industrial implications. Wood Science and Technology 47(4): 701-716. https://doi.org/10.1007/s00226-013-0534-y

Rowe, J.W. 2012. Natural products of woody plants: chemicals extraneous to the lignocellulosic cell wall. Springer Science & Business Media; Madison; USA. 1243p. https://doi.org/10.1007/978-3-642-74075-6

Rzanny, M.; Seeland, M.; Wäldchen, J.; Mäder, P. 2017. Acquiring and preprocessing leaf images for automated plant identification: understanding the tradeoff between effort and information gain. Plant Methods 13(1): 1-11. https://doi.org/10.1186/s13007-017-0245-8

Silva, E.S.; Stangerlin, D.M.; Gatto, D.A.; Calegari, L.; Pariz, E. 2015. Colorimetria da madeira de oito espécies nativas do estado do Rio Grande do Sul; Brasil. Brazilian Journal of Wood Science 6(1): 31-37. https://periodicos.ufpel.edu.br/ojs2/index.php/cienciadamadeira/article/view/4292

Silva, R.A.F.; Setter, C.; Mazette, S.S.; de Melo, R.R.; Stangerlin, D.M. 2017. Colorimetria da madeira de trinta espécies tropicais. Brazilian Journal of Wood Science 8(1): 36-41. https://periodicos.ufpel.edu.br/ojs2/index.php/cienciadamadeira/article/view/9686

Sousa, W.C.S.; Barbosa, L.D.J.; Soares, A.A.V.; Goulart, S.L.; Protásio, T.D.P. 2019. Wood colorimetry for the characterization of Amazonian tree species: a subsidy for a more efficient classification. Cerne 25(4): 451-462. https://doi.org/10.1590/01047760201925042650

Teles, R.F.; Costa, A.F. 2014. Influência do intemperismo acelerado nas propriedades colorimétricas da madeira de Angelim pedra. Nativa 2(2): 65-70. https://doi.org/10.31413/nativa.v2i2.1388

Tolvaj, L.; Molnar, Z.; Magoss, E. 2014. Measurement of photodegradation-caused roughness of wood using a new opticalmethod. Journal of Photochemistry and Photobiology B: Biology 134: 23-26. https://doi.org/10.1016/j.jphotobiol.2014.03.020

Tortorelli, L.A. 1956. Maderas y Bosques Argentinos. Editorial Acme: Buenos Aires. 910p.

Vanclay, J.K.; Henson, M.; Palmer, G. 2008. Color variation and correlations in Eucalyptus dunnii sawnwood. Journal of Wood Science 54(6): 431-435. https://doi.org/10.1007/s10086-008-0977-1

Vieira, H.C.; da Silva, E.L.; dos Santos, J.X.; de Muñiz, G.I.B.; Morrone, S.R.; Nisgoski, S. 2019a. Wood colorimetry of native species of Myrtaceae from an Araucaria Forest. Floresta 49(2): 353-362. http://dx.doi.org/10.5380/rf.v49i2.58236

Vieira, H.C.; Rios, P.D.A.; Santos, T.M.G.Q.M.D.; Cunha, A.B.D.; Brand, M.A.; Danielli, D.; Florez, J.B.; Stange, R.; Buss, R.; Higuchi, P. 2019b. Agrupamento e caracterização anatômica da madeira de espécies nativas da Floresta Ombrófila Mista. Rodriguésia 70: e e04382017. https://doi.org/10.1590/2175-7860201970038

Wang, Y.; She, S.; Zhou, N.; Zhang, J.; Yan, H.; Li, W. 2019. Wood Species Identification Using Terahertz Time-domain Spectroscopy. BioResources 14(1): 1033-1048. http://dx.doi.org/10.15376/bio-res.14.1.1033-1048

Zanuncio, A. J.V.; Farias, E. de S.; Silveira, T.A. 2014. Termorretificação e colorimetria da madeira de Eucalyptus grandis. Floresta e Ambiente. 21(1): 85-90. http://dx.doi.org/10.4322/floram.2014.005

Downloads

Published

2024-07-26

How to Cite

Vieira, H., Xipaia dos Santos, J., Venicio Souza, D. ., Naide Acosta, T. L. ., Rios, P. D. A. ., Bolzon de Muñiz, G. I. ., Ribeiro Morrone, S. ., & Nisgoski, S. . (2024). Wood colorimetry of Lauraceae species native to Brazil. Maderas. Ciencia Y Tecnología, 26, 1–15. https://doi.org/10.22320/s0718221x/2024.45

Issue

Section

Article

Most read articles by the same author(s)