Potential field-deployable NIRS identification of seven Dalbergia species listed by CITES

Abstract

Near-infrared spectroscopy (NIRS) is a potential, field-portable wood identification tool. NIRS has been studied as tool to identify some woods but has not been tested for Dalbergia. This study explored the efficacy of hand-held NIRS technology to discriminate, using multivariate analysis, the spectra of some high-value Dalbergia wood species: D. decipularis, D. sissoo, D. stevensonii, D. latifolia, D. retusa, all of which are listed in CITES Appendix II, and D. nigra, which is listed in CITES Appendix I. Identification models developed using partial least squares discriminant analysis (PLS-DA) and soft independent modeling by class analogy (SIMCA) were compared regarding their ability to answer two sets of identification questions. The first is the identification of each Dalbergia species among the group of the six above, and the second is the separation of D. nigra from a single group comprising the other species, grouping all Dalbergia as one class. For this latter study, spectra of D. cearensis and D. tucurensis were added to the broader Dalbergia class. These spectra were not included in the first set because the number of specimens was not enough to create an exclusive class for them. PLS-DA presented efficiency rates of over 90% in both situations, while SIMCA presented 52% efficiency at specieslevel separation and 85% efficiency separating D. nigra from other Dalbergia. It was shown that PLS-DA approaches are far better suited than SIMCA for generating a field-deployable NIRS model for discriminating these Dalbergia.

Hygromechanical properties of grenadilla wood (Dalbergia melanoxylon)

“…In this case, it should be the cell walls. At the same time, grenadilla has been known to possess high level of extractives, which is a non-structural part of the wood but still contribute to its mass (Donnelly et al 1975;Sjostrom 1993). Yin et al (2018), specifically, have conducted a thorough study regarding the extractives of grenadilla wood and found that the extractive percentage could reach up to 16.05% from extractions using a mixture of benzene/ethanol alone.…”

“…In 2017, CITES added grenadilla wood, together with all other wood species from the Dalbergia genus, to its appendix of endangered species (Snel et al 2018). Such a decision was justified by the ever-increasing pressure of the demand of this wood, insufficiently compensated by plantation efforts: Grenadilla is a slowgrowing tree species, with time needed to reach mature size ranging from 50-80 to 70-100 years (Malimbwi et al 2000;Ball 2004).…”

A computer-aided method for identifying the presence of softwood growth ring boundaries

“…The traditional methods of wood identification include manual comparison, dichotomous keys, multiple entry keys, punch card search and computer database program search [ 1 ]. Researchers have also tried to use DNA molecular marker technology [ 2 ], near-infrared spectroscopy technology [ 3 ], GC-MS technology [ 4 ], computer vision technology [ 5 ] and other auxiliary identification methods to improve the accuracy of traditional methods in wood identification and speed the process of identifying wood species.…”

A Computer-aided Method for Identifying the Presence of Softwood Growth Ring Boundaries

“…The traditional methods of wood identification include manual comparison, dichotomous keys, multiple entry keys, punch card search and computer database program search (Wheeler & Baas 1998). Researchers have also tried to use DNA molecular marker technology (Yu et al 2017), near-infrared spectroscopy technology (Snel et al 2018), GC-MS technology (Wang et al 2018), computer vision technology (Hwang et al 2018) and other auxiliary identification methods to improve the accuracy of traditional methods in wood identification and speed the process of identifying wood species.…”