Clasificación de Maderas Mediante el Uso de Tecnologías de Olfato Electrónico

Naren Arley Mantilla Ramírez; Homero Ortega Boada; Luisa Fernanda Ruiz Jiménez; Franklin Alexander Sepúlveda Sepúlveda

doi:10.59410/RACYT-v08n02ep07-0116

Authors

Naren Arley Mantilla Ramírez Industrial University of Santander
Homero Ortega Boada Industrial University of Santander
Luisa Fernanda Ruiz Jiménez Universidad Industrial de Santander
Franklin Alexander Sepúlveda Sepúlveda Industrial University of Santander

DOI:

https://doi.org/10.59410/RACYT-v08n02ep07-0116

Keywords:

Timber species, Technology, Electronic nose, Deforestation, Logging

Abstract

One of the main causes of the acceleration in the forest deforestation and degradation in Colombia is illegal logging. It is difficult for authorities to determine the legality or illegality status of a specific load because, despite having experts in forest engineering and some tools for wood species identification, these resources are insufficient due to their scarcity or low availability. Another strategy is using new technologies, which is an interesting option in the development of solutions that meet technical, operational and economic needs. There are advances in innovative, low-cost and easily accessible devices: electronic nose systems (e-noses). The "Universidad Industrial de Santander" has experience in using electronic noses for different applications, but it is interesting to involve this and other technologies in environmental monitoring. Therefore, an electronic nose based methodology is proposed to classify timber species according to the volatile compounds that they emanate, that is, their smell. A first case study was carried out using 29 samples of two timber species: cedar and monsoon, sawn in different areas of Santander (Colombia). It was possible to demonstrate, as expected, the separability of these two kinds of wood from their odor footprint, with a high success rate. This exploratory research allows the study of the performance of tools such as electronic noses in different applications. Also, it invites to investigate the feasibility of using them as an application of environmental monitoring for timber species classification, as it leaves open many questions that may contribute to the development of a more robust tool. All this seeks to generate a positive impact in the fight against illegality, as well as becoming a pilot for different applications where the use of technology can be involved.

Downloads

Download data is not yet available.

Metrics

Metrics Loading ...

References

Aazam, M., Khan, I., Alsaffar, A. A., & Huh, E. N. (2014). Cloud of Things: Integrating Internet of Things and cloud computing and the issues involved. Proceedings of 2014 11th International Bhurban Conference on Applied Sciences and Technology, IBCAST 2014, 414–419 DOI: https://doi.org/10.1109/IBCAST.2014.6778179

Baietto, M., Wilson, A. D., Bassi, D., & Ferrini, F. (2010). Evaluation of three electronic noses for detecting incipient wood decay (Vol. 10). Sensors DOI: https://doi.org/10.3390/s100201062

Cabral, E. C., Simas, R. C., Santos, V. G., Queiroga, C. L., Da Cunha, V. S., De Sá, G. F., … Eberlin, M. N. (2012). Wood typification by Venturi easy ambient sonic spray ionization mass spectrometry: The case of the endangered Mahogany tree. J. Mass Spectrom., 47(1), 1–6 DOI: https://doi.org/10.1002/jms.2016

Capelli, L., Sironi, S., & Del Rosso, R. (2014). Electronic Noses for Environmental Monitoring Applications. Sensors, 14(11), 19979–20007 DOI: https://doi.org/10.3390/s141119979

Cordeiro, J. R., Li, R. W. C., Takahashi, É. S., Rehder, G. P., Ceccantini, G., & Gruber, J. (2016). Wood identification by a portable low-cost polymer-based electronic nose. RSC Adv., 6(111), 109945–109949 DOI: https://doi.org/10.1039/C6RA22246C

Delgado Agudelo, M. A. (2013). Maderas de Colombia (WWF). WWF

Departamento Nacional de Planeación. DNP. (2007). Agenda Interna Para la Productividad y La Competitividad. Documento Regional: SANTANDER

Dickson, A., Nanayakkara, B., Sellier, D., Meason, D., Donaldson, L., & Brownlie, R. (2017). Fluorescence imaging of cambial zones to study wood formation in Pinus radiata D. Don. Trees - Structure and Function, 31(2), 479–490 DOI: https://doi.org/10.1007/s00468-016-1469-3

Fedele, R., Galbally, I. E., Porter, N., & Weeks, I. A. (2007). Biogenic VOC emissions from fresh leaf mulch and wood chips of Grevillea robusta (Australian Silky Oak). Atmos. Environ., 41(38), 8736–8746 DOI: https://doi.org/10.1016/j.atmosenv.2007.07.037

Garneau, F. X., Riedl, B., Hobbs, S., Pichette, A., & Gagnon, H. (2004). The use of sensor array technology for rapid differentiation of the sapwood and heartwood of Eastern Canadian spruce, fir and pine. Holz Als Roh-Und Werkstoff, 62(6), 470–473 DOI: https://doi.org/10.1007/s00107-004-0508-8

Guo, L., Yang, Z., & Dou, X. (2017). Artificial Olfactory System for Trace Identification of Explosive Vapors Realized by Optoelectronic Schottky Sensing. Adv. Mater., 29(5), 1–8 DOI: https://doi.org/10.1002/adma.201604528

Hanssen, F., Wischnewski, N., Moreth, U., & Magel, E. A. (2011). Molecular identification of Fitzroya cupressoides, Sequoia sempervirens, and Thuja plicata wood using taxon-specific rDNA-ITS primers. IAWA J., 32(2), 273–284 DOI: https://doi.org/10.1163/22941932-90000057

Ideam. (2017). Resultados Monitoreo de la Deforestación.

Kalaw, J. M., & Sevilla, F. B. (2018). Discrimination of wood species based on a carbon nanotube/polymer composite chemiresistor array. Holzforschung, 72(3), 215–223 DOI: https://doi.org/10.1515/hf-2017-0097

Müller, K., Haferkorn, S., Grabmer, W., Wisthaler, A., Hansel, A., Kreuzwieser, J., … Herrmann, H. (2006). Biogenic carbonyl compounds within and above a coniferous forest in Germany. Atmos. Environ., 40, 81–91 DOI: https://doi.org/10.1016/j.atmosenv.2005.10.070

Najib, M. S., Ahmad, M. U., Funk, P., Taib, M. N., & Ali, N. A. M. (2012). Agarwood classification: A case-based reasoning approach based on E-nose. Proceedings-2012 IEEE 8th International Colloquium on Signal Processing and Its Applications, CSPA 2012, 120–126 DOI: https://doi.org/10.1109/CSPA.2012.6194703

Rana, R., Müller, G., Naumann, A., & Polle, A. (2008). FTIR spectroscopy in combination with principal component analysis or cluster analysis as a tool to distinguish beech (Fagus sylvatica L.) trees grown at different sites. Holzforschung, 62(5), 530–538 DOI: https://doi.org/10.1515/HF.2008.104

Rinne, H. J. I., Guenther, A. B., Greenberg, J. P., & Harley, P. C. (2002). Isoprene and monoterpene fluxes measured above Amazonian rainforest and their dependence on light and temperature. Atmos. Environ., 36(14), 2421–2426 DOI: https://doi.org/10.1016/S1352-2310(01)00523-4

Rodriguez-Lujan, I., Fonollosa, J., Vergara, A., Homer, M., & Huerta, R. (2014). On the calibration of sensor arrays for pattern recognition using the minimal number of experiments. Chemometrics and Intelligent Laboratory Systems, 130, 123–134. https://doi.org/10.1016/j.chemolab.2013.10.012 DOI: https://doi.org/10.1016/j.chemolab.2013.10.012

Ruiz Jiménez, L. F. (2018). Detección de los insectos de la subfamilia Triatominae basado en narices electrónicas

Santos, J. P., & Lozano, J. (2015). Real time detection of beer defects with a hand held electronic nose. Proceedings of the 2015 10th Spanish Conference on Electron Devices, CDE 2015, 1–4 DOI: https://doi.org/10.1109/CDE.2015.7087492

Scott, S. M., James, D., & Ali, Z. (2006). Data analysis for electronic nose systems. Microchim. Acta, 156, 183–207 DOI: https://doi.org/10.1007/s00604-006-0623-9

Shi, H., Zhang, M., & Adhikari, B. (2017). Advances of electronic nose and its application in fresh foods: A review. Crit. Rev. Food Sci. Nutr., 8398, 1–11

Wilson, A. D. (2012). Application of a Conductive Polymer Electronic-Nose Device to Identify Aged Woody Samples. The Third International Conference on Sensor Device Technologies and Applications, 77–82

Wilson, A. D., Lester, D. G., & Oberle, C. S. (2005). Application of conductive polymer analysis for wood and woody plant identifications. For. Ecol. Manage., 209(3), 207–224 DOI: https://doi.org/10.1016/j.foreco.2005.01.030

Yan, J., Guo, X., Duan, S., Jia, P., Wang, L., Peng, C., & Zhang, S. (2015). Electronic Nose Feature Extraction Methods: A Review. Sensors, 15(11), 27804–27831 DOI: https://doi.org/10.3390/s151127804

Yu, M., Liu, K., Zhou, L., Zhao, L., & Liu, S. (2016). Testing three proposed DNA barcodes for the wood identification of Dalbergia odorifera T. Chen and Dalbergia tonkinensis Prain. Holzforschung, 70(2), 127–136 DOI: https://doi.org/10.1515/hf-2014-0234