TYPE: Review Article

Current Perspectives in the Forensic Analysis of Timbers using Vibrational Spectroscopy: A Review

Arti Yadav¹, Sweety Sharma², Lovlish Gupta², Vaibhav Singh², Rajinder Singh¹*

¹Department of Forensic Science, Punjabi University, Patiala, Punjab, India, 147002.
²LNJN National Institute of Criminology and Forensic Science, National Forensic Science University, Delhi Campus, Ministry of Home Affairs, Government of India.

RECEIVED 19 April 2024
ACCEPTED 02 August 2024
ONLINE EARLY 06 August 2024

https://doi.org/10.63033/JWLS.KRNG5178

Abstract

Wildlife crime has increased significantly with respect to timbers such as illegal timber trading, logging, harvesting, and counterfeiting. It has tremendously drained the economy of different countries since timber trafficking at the global level has an average annual net worth of US$ 50-150 billion. Moreover, timbers can act as important forensic evidence as they can be found at the crime scenes revealing the relationships between the crime scene and corpus delicti. Since ancient times, various traditional techniques have been used for timber identification such as anatomical investigation by visual method at the macroscopic and microscopic levels. However, morphological and anatomical techniques have some advantages, such as cost effectiveness, and limitations as they require experienced personnel. Vibrational spectroscopic tools such as infrared and Raman spectroscopy help in discriminating various species of timber as different timber species have unique phytochemicals. By examining the concentrations of cellulose, lignin, and hemicelluloses, the chemical composition can also be estimated. Herein, this review is carried out using vibrational spectroscopic methods for timber identification to combat criminal activities related to timbers for the dissemination of justice. Recent advancements and prospects are also emphasized in this review paper.

Keywords:Timbers, FTIR, NIR, Spectroscopy, Chemometrics, Forensic.

Introduction

Timbers are utilized in our day-to-day life owing to their multifarious applications such as paper production, fuel source, carpentry, furniture, musical instruments, railway foundations, and flooring. Some timber species are valuable for their medicinal and aromatic properties. It is also used as a biodegradable composite and a significant source of energy. Timber as a fuel has an advantage over other fossil fuels as the emission of carbon dioxide is 90% lower. It is used in many forms such as trusses, piles, beams, girders, and columns. Due to its magnificent properties, it is being used at a large scale resulting in the overexploitation of some precious timber species such asagarwood (Aquilaria spp.), mahogany (Swietenia macrophylla), monkey puzzle (Araucaria araucana), red sandalwood (Pterocarpus santalinus), etc. that are now on the verge of extinction or being endangered. These valuable timbers are illegally traded at the global level and have a market worth billions. Global timber trafficking accounts for 15-30 % of the total timber trade, estimated to be around US$50-150 billion per year (Wallen, 2018). The smuggling of timber strips can severely impact a large economy, especially if it has been generated through illegal logging. It has not only deeply affected the forest by depleting the lands but has also threatened the livelihood of the indigenous tribes and destroyed the habitat of flora and fauna.

International measures to mitigate the problem often include the implementation of legislation intended to discourage illicit timber trade and restrict the trafficking of particular species from specific areas. These are listed in the various plant-protecting organizations at the global level such as the International Union for Conservation of Nature (IUCN) Red List and the Convention on International Trade in Endangered Species of Wild Fauna and Flora (CITES), which includes three appendices based on the degree of protection required (Dormontt et al., 2015; Schloenhardt, 2008). Appendix I includes species that are threatened with extinction. Therefore, the trade of such species is strictly forbidden, and can only be permitted in exceptional circumstances. Appendix II includes species not yet on the verge of extinction, although the trade of these species must be controlled and monitored to avoid their complete extinction. In Appendix III, the species of least concern have been listed and these species can be exported or imported with an appropriate document for clearance at entry or exit on the port as mentioned in the United Nations Environmental Programme (UNEP), 2019.

Forensic science is a vast field with its root spread into nearly all domains. One of the subfields of forensic science is forensic botany which involves the application of the theory and the principles of botany to seek justice in criminal investigation (Solinge et al., 2016). Another important aspect of forensic botany is controlling illegal logging and harvesting timber species. A major issue in the identification process is that most of the timber products lack the diagnostic characteristics essential for plant identification (fruit, pollen, flowers, and leaves), and therefore, it becomes very difficult to identify a specific timber species (Dormontt et al., 2015; Wiedenhoeft, 2016). Timbers are mainly composed of cellulose, hemicellulose, and lignin. However, the concentrations are not only species- dependent but also affected by environmental conditions, geographical locations, ageing, and fossilization. The level of precision of timber identification varies significantly through physical, chemical, and genetic methods. The summary of the research conducted so far to identify timbers is represented in Figure 1.

In addition to investigating timber involved in illicit timber logging, adulteration (Kannangara et al., 2020), and harvesting, forensic agencies are also interested in knowing: What is the age of the specimen procured? To what geographical location does the specimen belong? The prior question becomes important to find out whether the timber was harvested before the implementation of legislation or not. Determining the geographical area is crucial as some species are restricted to specific areas within their distributional range.

Most traditional morphological traits cannot identify and classify plant material (timber) at the species level, especially when the specimens are collected in a decayed form and lack physical features (Dormontt et al., 2015; Kannangara et al., 2020). Traditionally, timber species were identified using time-consuming and laborious methods such as physical, visual, and anatomical inspections (Yang et al., 2015). Nowadays, quick approaches are preferred over traditional methods such as Fourier Transfer Infrared (FTIR) spectroscopy, DNA barcoding, and stable isotopes (Dormontt et al., 2015). All techniques have some advantages and limitations. Certain studies also show that Raman and NIR spectroscopic methods have evolved to analyze particularly non-structural extractive substances from timbers. These characteristics were examined for decades using traditional techniques, whereas due to expensiveness, and time consumption, alternative spectroscopic methods such as Near-Infrared Spectroscopy (NIRS) and Raman spectroscopy are more frequently utilized at current times (Schimleck & Workman, 2004). Various characteristics of timber have been studied for a long time and are analyzed by specific spectroscopic methods. For example, surface and chemical characteristics are widely analyzed using FTIR spectroscopic methods, whereas biological components and origin in terms of geographical region of timber species can be easily identified using NIR Spectroscopy. These characteristics are summarized and represented in Figure 2.

The era of IR spectroscopy started with Borga et al. (1992), who were the pioneers in the field of applying FTIR spectroscopy for timber identification. It was followed by Schimleck (2004) by classifying species of Eucalypts using NIRS in conjunction with principal component analysis (PCA). There is a wide applicability of NIRS for the analysis of timbers, such as discriminating similar-looking timber species (Flæte et al., 2006; Haartveit & Flæte, 2008), discriminating same timber species belonging to different geographical origins (Rana et al., 2008), analyzing the structure of photodegraded wood (Colom et al., 2003), and studies on timbers subjecting to physical and chemical treatments (Hinterstoisser et al., 2003; Schwanninger et al., 2004). A detailed list of the spectroscopy methods applied in timber forensics so far is given in Table 1.

Fourier Transform Infrared (FTIR) Spectroscopic

FTIR spectroscopy is a very useful method for characterizing the structural chemistry of timber with minimum sample preparation (Popescu et al., 2007). Primarily, FTIR spectroscopy along with multivariate data analysis chemometric tools such as PCA, Linear Discriminant Analysis (LDA), Partial Least Square Regression (PLSR), and Soft Independent Modelling of Class Analogies (SIMCA) are used for the qualitative and quantitative analysis of timbers. Spectroscopic analysis is a handy tool over conventional methods, as the latter may often destroy the timber sample and require a large sample size for the time-consuming analysis procedure (Soest, 1963).

Analysis of surface characteristics of timbers is one of the major advantages of FTIR spectroscopic analysis; this was indicated by similar research where the surface texture and other characteristics of a corn stalk were analyzed using FTIR spectroscopy and X-ray diffraction techniques (Zhao et al., 2013). Timber biomass is one of the most valuable, renewable and abundant biomasses present on the earth. However, the analysis of these timber samples using FTIR spectroscopy needs certain physical modifications, such as a reduction in the size of biomass to increase its bulk density, new surface area, pore size, etc. Hence, a superfine grinding technology is used nowadays for analysis in FTIR spectroscopy (Zhao et al., 2013).

FTIR spectroscopy along with a chemometric approach is one of the best options to analyze timber samples without requiring time-consuming sample preparation. This has helped in the qualitative and quantitative analysis of timbers and has made the highly complex procedure easier compared to procedures that involve the isolation of timber components and degradation of the monomeric fragment. FTIR coupled with multivariate analysis is the most straightforward spectroscopic analysis used for rapid analysis of the structural components of timber. When compared to traditional chemical analytic methods, this technique is non-destructive and also utilizes a very small sample size (Chen et al., 2010). Colom et al. (2003) showed that the photodegraded timbers can also be subjected to structural analysis using FTIR spectrometry. The degradation in the timber samples indicates the chemical and structural strength of particular timber samples. FTIR not only determines the potency and extent of degradation of timber but also identifies the cause of the deterioration such as natural ageing, oxidation, thermochemical degradation, artificial ageing, etc.

Figure 1: Methods used for the analysis of timber.

Figure 2: Spectroscopic techniques and analysis of individual characteristics of timber.
Table 1. Analysis of timbers using various spectroscopic methods coupled with statistical or chemometric approaches.

Photoacoustic spectroscopic method (PAS) is one of the most valuable tools as it is equipped with specialized high-sensitivity microphones, low-noise electronics, computerized data handling, etc. PAS associated with FTIR is more practical and has various advantages as it does not require the transmission of samples and can be probed upon a range of sample sizes, multiple depths, etc. (Dang et al. 2007). Another remarkable IR spectroscopy is headspace FTIR analysis, this technique helps in timber headspace analysis and is the best alternative for timber species identification. Although the spectra can only be generated through FTIR, indicating the presence of several organic or inorganic functional groups. However, the visual discrimination becomes complicated by the use of spectra alone. Therefore, PCA (resulting in 89.57% accuracy) and Hierarchal Cluster Analysis (HCA) were used to discriminate timber species by their taxonomic categories at the species level (Kalaw & Sevilla, 2019).

Attenuated Total Reflectance Fourier Transform Infrared (ATR-FTIR) spectrometry is another method for the characterization of timber. A moderate amount of work has been done using ATR-FTIR spectroscopy. Traore et al. (2016) differentiated two archaeological timbers using Pyrolysis Gas Chromatography Mass Spectrometry (PY-GC-MS) and ATR-FTIR spectroscopy along with multivariate analysis. The timber samples were collected from different regions of the old Nave Cathedral of Segovia, Central Spain, and the shipwreck in Ribadeo Bay in northwest Spain. The results showed a low amount of lignin in the shipwreck, whereas the beam wood had abundant amounts of carbohydrates present in it. The lower contents of lignin were indicative of enhanced oxidation in oxygenated conditions. The obtained spectra reflected similarities between oak in the case of the shipwreck and pine in the case of the beam. ATR-FTIR spectroscopy can provide appropriate information on the chemical composition along with analytical tools such as PY-GC-MS for timber discrimination and the retained state of the lignin in archaeological timber.

Sharma et al. (2020) performed a study in which 24 different timber species were procured from the Timber Science Department, Brno, Czech Republic to discriminate between softwood and hardwood using ATR-FTIR spectroscopy along with multivariate statistical analysis, which became a boon to analysts as PCA-LDA resulted in about 87.5% of correct classification between timber samples from unknown origin. Whereas HCA was able to distinguish samples with 81% accuracy. The technique not only identified and distinguished timber species, but also helped in locating the samples geographically and determining its classification in the hierarchical system up to species and genus level. Also, ATR-FTIR spectrometric analysis is a non-destructive and quick approach. Hence, samples can be easily preserved and reused. Moreover, this method can be employed to build a large database of timbers for future studies and references. Several studies have used FTIR for timber samples such as investigating the effect of photodegradation in softwood, and hardwood by observing the chemical changes of cellulose and lignin (Colom et al., 2003). Popescu et al. (2009) used FTIR in addition to X-ray diffraction techniques for the differentiation of softwood (Norway spruce Picea abies) and hardwood (Eucalyptus sp.) from pulp fibers. A total of 12 timber samples including a mixture of seven softwoods and four hardwoods, were identified and characterized by using FTIR along with chemometric models such as PCA, PLS, and LDA (Popescu et al., 2009).

Recently, Traore & Cortizas, (2023) compared four timber species belonging to southern Mali, West Africa using FTIR spectroscopy in conjunction with chemometric approaches. The study was aimed at determining the chemistry and molecular structure of the species of Pterocarpus erinaceus, Daniellia oliveri, and Khaya senegalensis. The FTIR results showed that the characterization of the timber species was possible with the help of the molecules and functional groups of lignin and carbohydrates.

Fourier Transform Raman Spectrometry

Ozgenc et al. (2017) used Fourier Transform Raman (FT-Raman) and ATR-FTIR spectrometry to determine the structural and chemical changes occurring in the timber samples caused by heat treatments. Three different timber species were analyzed, including oriental spruce (Picea orientalis), oriental beech (Fagus orientalis), and scot pine (Pinus sylvestris). Both techniques indicated changes at the chemical level caused by heat treatment. The results showed that the organic acid content of the timber, mainly formic and acetic acid accumulated as these acids are responsible for the degradation of polysaccharides and reduction in the degree of polymerization. Analysis of the lignin formation through FT Raman showed that the lignin band changed at 1600 cm-1. The content of lignin increased, whereas the relative cellulose and hemicellulose content decreased. The changes observed after the heat treatment varied with the timber species.

Identification of Fossil and Present-Day Timber

NIR spectrometry is one of the reliable spectroscopic techniques for qualitative and quantitative estimation of timber samples, and fossilized timbers (Tsuchikawa, 2007; Adedipe et al., 2008; Braga et al., 2011). Recent advances in vibrational spectroscopic methods such as FTIR and FT Raman have also helped in differentiating the characteristics of fossil timbers from present-day timbers. One such study was conducted by Ozgenc et al. (2018) for timber analysis by procuring two timber samples, viz., Sequoioxylon sp., a fossil timber & Sequoiadendron giganteum, a present-day timber. The fossilized timber was collected from Istanbul, Turkey and it belonged to the Oligocene- Miocene period. The analysis using FT Raman revealed that the fossilized timber cell wall generally has more deteriorated lignin content than the carbohydrates. FT Raman analysis also estimated that fossilized timber has lower contents of cellulose and hemicellulose, with more detailed results compared to FTIR spectrometry. Another spectroscopic technique, Laser Induced Breakdown Spectroscopy (LIBS) estimated the oxygen and hydrogen contents in the fossilized timber samples, which is the main reason for the decrease in molecular mass and total body weight.

Fuchtner & Thygesen (2023) used confocal Raman spectroscopy along with chemometric methods to study the effect of heartwood extractives on brown rot decay in Norway spruce. The authors concluded that the rate of degradation was slower in Norway spruce due to the effect of extractives which delayed lignin degradation in the cell wall enriched with lignin.

Near Infrared (NIR) Spectrometry

The past ten years of analysis of timber species using NIR indicate that NIR spectrometry,, along with various chemometric tools such as PCA, LDA, SIMCA, and Partial Least Squares – Discriminant Analysis (PLS-DA), is an efficient technique for the identification and differentiation of various timber species. NIR spectrometry can determine the chemical composition of timber such as lignin, cellulose, water, and phenolic substances. It can provide additional information on the physical and chemical properties of timber samples. Physical properties such as moisture content, surface texture, grain angle, density, and other anatomical as well as mechanical parameters can be analyzed by NIR spectrometry. Information related to various engineered timbers was also reviewed such as laminated veneer lumber, particleboard, medium-density fibreboard, and urea-formaldehyde resin. NIR spectroscopy can give good spectra for various timber samples, such as wet stored timbers, and also, it gives indicative results for the analysis of decay resistance offered by a heartwood. The technique is also efficient in characterizing raw materials of timber such as pulp, used for paper manufacturing. Hence, examination of a paper via NIR spectrometry coupled with multivariate analysis or chemometric analysis helps in its constituent analysis and can correlate it to specific timber. Adedipe et al. (2008) conducted a study on different timber samples, including white oak (Quercus alba) and red oak (Quercus alba) that were collected from five different counties of the USA, viz., Randolph County, Mason County, Preston County, etc. The two timber samples were subsequently analyzed using NIR spectrometry coupled with SIMCA. The wavelength ranges between 800-2500 nm were used to obtain spectra of 150 timber samples. However, the calibration models in the ranges of 1100-2200 nm, 100-2500 nm, and 1400-1900 nm were developed by SIMCA using standard normal variate (SNV) transformation. NIR spectra in the wavelength range from 800-2500 nm provided useful information for the discrimination of the above-mentioned species.

Timbers are composed of complex organic and inorganic materials; therefore, NIR spectral analysis hence becomes complicated at this point. However, it can analyze the contributions of different cellulosic contents in two spectral domains (Schubert et al., 2022). Scientists have evaluated that a combination of UV-visible and NIR spectrometry was efficient in studying the chemical composition of the timber. NIR spectroscopic analysis gives better spectra through transverse and radial surfaces instead of tangential surfaces, indicating, that surface analysis is an important aspect. Root mean squares are generally used to evaluate moisture content however, it was well measured in timber samples using the multilayer PLS method. NIR spectrometry is a boon for botanists and forensic scientists in estimating the origin and source of timber samples and industrially processed timber pellets (Mancini et al., 2018).

The literature has accounts of the analysis of seven timber chip samples with a controlled amount of moisture, which were acacia (Robinia pseudoacacia), ash-tree (Fraxinus silvatica), aspen (Populus tremula), beech (Fagus silvatica), birch (Betul alba), cherry (Cerasus avium) and hornbeam (Carpinus betulus) (Adedipe et al., 2008; Chen et al., 2010; Gigac & Fišerová, 2010; Ramalho et al., 2018; Teodorescu et al., 2021). The spectra were obtained using NIR and the variation in moisture content in various timbers significantly affected the results. Timber chips with a higher water content were easily and better analyzed by NIR spectrometry. However, the timber chips with lower moisture content were not differentiated easily. Hence, a high identification accuracy (90%) was observed in acacia, aspen, birch, and hornbeam whereas, ash-tree and cherry were identified with low accuracy. The actual versus predicted relationship for all the studied timber sample was linear with a coefficient of determination (R2) of 0.8054 (Russ et al., 2009). This indicated that most of the timber species have similar chemical composition but different moisture content. The change in the moisture content of the wooden components affects their density, volume, exterior features, biological and mechanical properties. These changes can affect the integrity of the results of timber analysis.

NIR spectroscopy is also efficient in discriminating softwood and hardwood. A study conducted by Abe et al. (2020), differentiated softwood and hardwood statues in the Nazenji temple, Japan using NIR spectroscopy. The results showed that NIRS combined with PCA efficiently separated archeological wood. Similarly, Silva et al., (2018) analysed the origin of the country of true mahogany timber species using NIR spectroscopy and multivariate data analytical tools such as SIMCA and PLS-DA. It was observed that SIMCA resulted in 67-100 % and 70-98 % accuracy in the NIR range of 1595-2396 nm and 950-1650 nm wavelengths respectively. Similarly, the PLS-DA approach was significant with 90-100 % accuracy.

Subsequent studies using FT-NIR spectroscopic techniques have also been carried out to identify and link timber species with their geographical location. One study conducted by Bachle et al. (2012) classified thermally modified wood using FT-NIR spectrometry and chemometric tools such as SIMCA. Sandak et al. (2011) determined the geographical provenance of timber using FT-NIR. Various timber samples of spruce (Picea abies) were collected from four different regions, viz., Finland, Italy, northern and southern Poland. Depending on the geographical provenance, the timbers were collected as two different sample types. In the first sample type, timbers were collected from different regions of Europe, whereas in the second type, it was collected from different localities in Italy. FT-NIR helped in the analysis of chemical compositions that vary in timber samples of different locations. The results showed that for methods 1 and 2, the accuracy of 100% and 99.5% were obtained respectively. The separation among the timber was more prominent in the samples collected from a different region of Europe compared to the samples from a narrow region of Italy, although the separation within Italy was also significant. Therefore, the method is applicable in deciphering geographical provenance and to curb illicit timber harvesting from protected areas.

Studies have revealed that NIR coupled with chemometrics can determine the age of various timber species. The reliability of spectroscopic methods in determining the chemical constituents, age, moisture content, and differentiation of fossilized timber is already high. NIR coupled with PLS-DA has helped differentiate virgin timber and glue laminated timbers with 100% accuracy. An alternative to PLS-DA is multivariate analysis, which rapidly determines the the origin of timber and biomass when used with NIR spectrometry (Mancini et al., 2018; Colom et al., 2003; Sandak et al., 2011). Ramalho et al. (2018) reported that NIR spectrometry determined the timber species from plantation and native forests. Timbers were taken from several tropical trees in Brazil. The sample timber obtained from planted forests were Eucalyptus clones which were commercially produced, whereas specimens from natural forests were of genera Aspidosperma, Apuleia, and Jacaranda. PLS-DA coupled with NIR clearly distinguished Aspidosperna, Apuleia, and Jacaranda from Eucalyptus species. However, this differentiation can also be done using PCA based on NIR spectra. About 86% of the correct results were obtained using PLS-DA models from untreated NIR spectra. However, treated NIR along with the PLS-DA models are robust in determining and classifying timber specimens from planted and natural forests.

Pastore et al. (2011) analyzed solid timber specimens of Swietenia macrophylla and three other timber samples namely andiroba (Carapa guianensis), curupixá (Mecropholis melinoniana), and cedar (Cedrela odorata). Samples of mahogany, andiroba, curupixá, and cedar were collected from 29, 25, 31, and 26 trees, respectively. Analysis from different faces also revealed that the spectra had differences. Therefore, the analyses must be carried out in a repeatable protocol. Yang et al., (2015) used NIR spectroscopy along with chemometric models such as PCA (Case I), and PLS-DA (Case II) to identify three timber species including Pometia sp, Couratari sp., and Instia sp. which were collected from Dongba in Beijing, China. A total of 315 timber samples were prepared. In Case I, PCA was applied to the NIR spectra which resulted in 100% accuracy. In Case II, PCA along with PLS DA was used to identify the three species resulting in the construction of three different identification models based on locations. The results obtained after calibration correctness were 67%, 99%, and 94% for Pometia sp., Couratari sp., and Instia sp., respectively. A comparison of the IR and Raman spectroscopy for timber analysis is given in Table 2.

Hyphenated Techniques

Ebner et al. (2023) compared two different charring treatments employed on the surface of fir wood samples, which is used to enhance its aesthetic appearance and weather protection capacity. The authors compared the gas-burning charring method with the traditional Japanese technique using ultraviolet resonance Raman and FTIR spectroscopy along with X-ray-computed micro-tomography analysis. The results of FTIR spectroscopy showed major changes in the bands indicating lignin and carbohydrates when compared with the spectra of reference samples. Moreover, the results indicate the degradation of carbohydrates due to pyrolysis. The ultraviolet resonance Raman spectroscopy helped to estimate the differences in the chemical composition of the samples using these charring methods. Whereas the X-ray-computed micro-tomography techniques estimated the morphological changes in the wood samples after the charring process.

Similarly, Tuncer et al. (2024) studied the changes in the wood chemistry after the contact charring and submersion in linseed oil in the wood of Eucalyptus bosistoana, and Pinus taeda by using FTIR, Raman spectroscopy, and Scanning Electron Microscope (SEM). The Raman spectroscopy showed that as a result of charring, the total lignin content increased, whereas the carbohydrate content decreased. The charring of the wood samples had resulted in elevated contact angles due to raised hydrophobicity in addition to the homogeneity, and sensitivity in the cell walls. The FTIR analysis showed a decrease in the content of carbohydrates, and the building of aromatic compounds due to charring. A detailed list of the chemometric methods and hyphenated modifications used in spectroscopic techniques is given in Table 3.

Table 2: Comparison of Infrared (IR) and Raman spectroscopy for the analysis of timbers.

Table 3. Summarised chemometric models and hyphenated modifications used with spectroscopic techniques.

Conclusion

Several wildlife crimes concerning timbers have significantly and rapidly increased in past decades. It has led to a major economic loss when considering its illegal trade to the extent that it has caused recession in countries such as the Central African Republic (Hellwig-Botte, 2014). Another major issue concerning timber is that construction buildings and furniture can be made with substandard timber species, claiming to be a superior material. Besides the identification of timber by morphological studies (macroscopic), chemical methods are also useful for determining timber up to the genus level. Vibrational spectroscopic methods are described in this review article with their significant advantages. There is a growing need to examine timber in a rapid way where illegal timber logging is routinely escalating. Various spectroscopic approaches discussed in this review can provide a thorough analysis of species of timbers. Methods such as IR spectroscopy, Raman spectroscopy with chemometric tools such as Least-squares Support Vector Machine models (LS-SVM), Artificial Neural Networks (ANN), PLSR, PCA, etc., as well as other technical methods such as photoacoustic rapid scan, Fourier transform, attenuated total reflectance, etc., have been proven crucial in the identification of timber species, estimation of the age of timber, and fossilization of ancient timber samples recovered from crime scenes. Hyphenated techniques such as ATR-FTIR coupled with FT-Raman, and ATR-FTIR coupled with Pyrolysis GC-MS had more significant results. These techniques successfully measured the chemical and physical differences in timber samples, as well as substantial measurements of environmental impacts such as oxidation, degradation, and any other measurable physiochemical or biological changes. These methods provide tools to link suspects, victims, and the crime scene. This review also discussed various significant chemometric tools, which are of equal importance when analysing any biological material.

Acknowledgements

The authors would like to express their sincere gratitude to the University Grants Commission (UGC), Ministry of Human Resource Development, Government of India for providing financial assistance to the first author (UGC Ref. No. 200510156051).

CONFLICT OF INTEREST
The authors have no competing interests to declare that are relevant to the content of this article.

DATA AVAILABILITY
No data was used in this research.

AUTHOR CONTRIBUTIONS
Arti Yadav: Writing- Original draft, review & editing.
Sweety Sharma: Writing- review & editing.
Lovlish Gupta: Writing- review & editing. Vaibhav Singh: Writing- review & editing.
Rajinder Singh: Conceptualization, Supervision, Writing-review & editing.

Issue2-cover

July 2024

E9780

Edited By
Ajay Gaur
Centre for Cellular & Molecular Biology, Hyderabad, India

*CORRESPONDENCE
Rajinder Singh
rajinder_forensic@pbi.ac.in


CITATION
Yadav, A., Sharma, S., Gupta, L., Singh, V., Singh, R. (2024). Current Perspectives in the Forensic Analysis of Timbers using Vibrational Spectroscopy: A Review. Journal of Wildlife Science,1 (2), 69-80.


COPYRIGHT
© 2024 Yadav, Sharma, Gupta, Singh, Singh. This is an open-access article, immediately and freely available to read, download, and share. The information contained in this article is distributed under the terms of the Creative Commons Attribution License (CC BY), allowing for unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited in accordance with accepted academic practice. Copyright is retained by the author(s).

PUBLISHED BY
Wildlife Institute of India, Dehradun, 248 001 INDIA

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Hinterstoisser, B., Schwanninger, M., Stefke, B., Stingl, R. & Patzelt, M., (2003), April. Surface analyses of chemically and thermally modified wood by FT-NIR. In Acker, VJ, Hill, C. The 1st European conference on wood modification. Proceeding of the first international conference of the European society for wood mechanics,15-20.

Kalaw, J.M. & Sevilla, I.I.I.F., (2019). Differentiation of wood species using headspace fingerprinting through fourier-transform infrared spectroscopy. Acta Manilana, 67, 31-38.

Kannangara, S., Karunarathne, S., Ranaweera, L., Ananda, K., Ranathunga, D., Jayarathne, H., Weebadde, C. & Sooriyapathirana, S., (2020). Assessment of the applicability of wood anatomy and DNA barcoding to detect the timber adulterations in Sri Lanka. Scientific Reports, 10(1), 4352. https://doi.org/10.1038/s41598-020-61415-2

Mancini, M., Rinnan, Å., Pizzi, A., Mengarelli, C., Rossini, G., Duca, D. & Toscano, G., (2018). Near infrared spectroscopy for the discrimination between different residues of the wood processing industry in the pellet sector. Fuel, 217, 650-655.

Özgenç, Ö., Durmaz, S., Boyaci, I.H. & Eksi-Kocak, H., (2017). Determination of chemical changes in heat-treated wood using ATR-FTIR and FT Raman spectrometry. Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy, 171, 395-400. https://doi.org/10.1016/j.saa.2016.08.026

Ozgenc, O., Durmaz, S., Serdar, B., Boyaci, I.H., Eksi-Kocak, H. & Öztürk, M., (2018). Characterization of fossil Sequoioxylon wood using analytical instrumental techniques. Vibrational Spectroscopy, 96, 10-18. https://doi.org/10.1016/j.vibspec.2018.02.006

Pastore, T.C.M., Braga, J.W.B., Coradin, V.T.R., Magalhães, W.L.E., Okino, E.Y.A., Camargos, J.A.A., de Muñiz, G.I.B., Bressan, O.A. & Davrieux, F., (2011). Near infrared spectroscopy (NIRS) as a potential tool for monitoring trade of similar woods: Discrimination of true mahogany, cedar, andiroba, and curupixá. Holzforschung, 65(1), 73-80. https://doi.org/10.1515/hf.2011.010

Popescu, C.M., Popescu, M.C., Singurel, G., Vasile, C., Argyropoulos, D.S. & Willfor, S., (2007). Spectral characterization of eucalyptus wood. Applied spectroscopy, 61(11), 1168-1177. https://doi.org/10.1366/000370207782597076

Popescu, C.M., Singurel, G., Popescu, M.C., Vasile, C., Argyropoulos, D.S. & Willför, S., (2009). Vibrational Spectroscopy and X-ray diffraction methods to establish the differences between hardwood and softwood. Carbohydrate polymers, 77(4), 851-857. https://doi.org/10.1016/j.carbpol.2009.03.011

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. https://doi.org/10.1515/HF.2008.104

Ramalho, F.M., Andrade, J.M. & Hein, P.R., (2018). Rapid discrimination of wood species from native forest and p lantations using near infrared spectroscopy. Forest Systems, 27(2), e008-e008. https://doi.org/10.5424/fs/2018272-12075

Russ, A., Fišerová, M. & Gigac, J., (2009). Preliminary study of wood species identification by NIR spectroscopy. Wood Research, 54(4), 23-32.

Sandak, A., Sandak, J. & Negri, M., (2011). Relationship between near-infrared (NIR) spectra and the geographical provenance of timber. Wood Science and Technology, 45, 35-48. https://doi.org/10.1007/s00226-010-0313-y

Schimleck, L. & Workman Jr, J., (2004). Analysis of timber and paper. Near‐Infrared Spectroscopy in Agriculture, 44, 633-646.. https://doi.org/10.2134/agronmonogr44.c22

Schubert, M., Panzarasa, G. & Burgert, I., (2022). Sustainability in wood products: a new perspective for handling natural diversity. Chemical Reviews, 123(5), 1889-1924. https://doi.org/10.1021/acs.chemrev.2c00360

Schloenhardt, A. & Schloenhardt, A., (2008). The illegal trade in timber and timber products in the Asia-Pacific region (No. 89). Canberra: Australian Institute of Criminology.

Schwanninger, M., Hinterstoisser, B., Gierlinger, N., Wimmer, R. & Hanger, J., (2004). Application of Fourier transform near infrared spectroscopy (FT-NIR) to thermally modified wood. Holz als Roh-und Werkstoff, 62, 483-485.

Sharma, V., Yadav, J., Kumar, R., Tesarova, D., Ekielski, A. & Mishra, P.K., (2020). On the rapid and non-destructive approach for wood identification using ATR-FTIR spectroscopy and chemometric methods. Vibrational Spectroscopy, 110, 103097. https://doi.org/10.1016/j.vibspec.2020.103097

Silva, D.C., Pastore, T.C., Soares, L.F., de Barros, F.A., Bergo, M.C., Coradin, V.T., Gontijo, A.B., Sosa, M.H., Chacón, C.B. & Braga, J.W., (2018). Determination of the country of origin of true mahogany (swietenia macrophylla King) wood in five Latin American countries using handheld NIR devices and multivariate data analysis. Holzforschung, 72(7), 521-530. https://doi.org/10.1515/hf-2017-0160

Soest, P.V., (1963). Use of detergents in the analysis of fibrous feeds. II. A rapid method for the determination of fiber and lignin. Journal of the Association of official Agricultural Chemists, 46(5), 829-835. https://doi.org/10.1093/jaoac/46.5.829

Solinge, T.V., Zuidema, P., Vlam, M., Cerutti, P.O. and Yemelin, V., (2016). Organized forest crime: a criminological analysis with suggestions from timber forensics.nIUFRO World Series, 35, 81-96.

Teodorescu, I., Erbasu, R.I., Branco, J.M. & Tapusi, D., (2021). Study in the changes of the moisture content in wood. IOP Conference Series: Earth and Environmental Science, 664, 012017. https://doi.org/10.1088/1755-1315/664/1/012017

Traoré, M. & Martínez Cortizas, A., (2023). Comparative study of four timber wood species in southern Mali (West Africa) by combining FTIR spectroscopy and multivariate analysis. European Journal of Wood and Wood Products, 81(6), 1513-1524. https://doi.org/10.1007/s00107-023-01979-8

Traoré, M., Kaal, J. & Cortizas, A.M., (2016). Application of FTIR spectroscopy to the characterization of archeological wood. Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy, 153, 63-70. https://doi.org/10.1016/j.saa.2015.07.108

Tsuchikawa, S., (2007). A review of recent near infrared research for wood and paper. Applied spectroscopy Reviews, 42(1), 43-71. https://doi.org/10.1080/05704920601036707

Tuncer, F.D., Kartal, S.N., Soytürk, E.E., Arango, R.A., Ohno, K.M., Önses, M.S., Çelik, N. & Ibanez, C.M., (2024). Changes in chemical properties and microstructure of Pinus taeda and Eucalyptus bosistoana woods modified by contact charring. European Journal of Wood and Wood Products, 82(1), 107-121.

Wiedenhoeft, A., (2016). Best practice guide for forensic timber identification. In: United Nations Office on Drugs and Crime: International Consortium on Combating Wildlife Crime. Vienna, Austria: Laboratory and Scientific Section, Global Programme for Combating Wildlife and Forest Crime: 1-226.

Wallen, K.E., (2018). Global timber trafficking harms forests and costs billions of dollars–here’s how to curb it. The Conversation, 24.

Yang, Z., Liu, Y., Pang, X. & Li, K, (2015). Preliminary investigation into the identification of wood species from different locations by near infrared spectroscopy. BioResources, 10(4), pp.8505-8517.

Zhao, X., Chen, J., Chen, F., Wang, X., Zhu, Q. & Ao, Q., (2013). Surface characterization of corn stalk superfine powder studied by FTIR and XRD. Colloids and Surfaces B: Biointerfaces, 104, 207-212., https://doi.org/10.1016/j.colsurfb.2012.12.003

Edited By
Ajay Gaur
Centre for Cellular & Molecular Biology, Hyderabad, India

*CORRESPONDENCE
Rajinder Singh
rajinder_forensic@pbi.ac.in


CITATION
Yadav, A., Sharma, S., Gupta, L., Singh, V., Singh, R. (2024). Current Perspectives in the Forensic Analysis of Timbers using Vibrational Spectroscopy: A Review. Journal of Wildlife Science,1 (2), 69-80.


COPYRIGHT
© 2024 Yadav, Sharma, Gupta, Singh, Singh. This is an open-access article, immediately and freely available to read, download, and share. The information contained in this article is distributed under the terms of the Creative Commons Attribution License (CC BY), allowing for unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited in accordance with accepted academic practice. Copyright is retained by the author(s).

PUBLISHED BY
Wildlife Institute of India, Dehradun, 248 001 INDIA

PUBLISHER'S NOTE
The Publisher, Journal of Wildlife Science or Editors cannot be held responsible for any errors or consequences arising from the use of the information contained in this article. All claims expressed in this article are solely those of the author(s) and do not necessarily represent those of their affiliated organisations or those of the publisher, the editors and the reviewers. Any product that may be evaluated or used in this article or claim made by its manufacturer is not guaranteed or endorsed by the publisher.

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Füchtner, S. & Thygesen, L.G., (2023). Subcellular level impact of extractives on brown rot decay of Norway spruce elucidated by confocal Raman microscopy and multivariate data analysis. Wood Science and Technology, 1-33. https://doi.org/10.1007/s00226-023-01476-4

Gigac, J. & Fišerová, M., (2010). Identification of wood species by application of visible spectral reflectance. Wood Research, 55(1), 79-86.

Hellwig-Bötte, M., (2014). Wildlife crime in Africa global challenge: successful countermeasures must involve local populations (No. 12/2014). SWP Comments.

Hinterstoisser, B., Schwanninger, M., Stefke, B., Stingl, R. & Patzelt, M., (2003), April. Surface analyses of chemically and thermally modified wood by FT-NIR. In Acker, VJ, Hill, C. The 1st European conference on wood modification. Proceeding of the first international conference of the European society for wood mechanics,15-20.

Kalaw, J.M. & Sevilla, I.I.I.F., (2019). Differentiation of wood species using headspace fingerprinting through fourier-transform infrared spectroscopy. Acta Manilana, 67, 31-38.

Kannangara, S., Karunarathne, S., Ranaweera, L., Ananda, K., Ranathunga, D., Jayarathne, H., Weebadde, C. & Sooriyapathirana, S., (2020). Assessment of the applicability of wood anatomy and DNA barcoding to detect the timber adulterations in Sri Lanka. Scientific Reports, 10(1), 4352. https://doi.org/10.1038/s41598-020-61415-2

Mancini, M., Rinnan, Å., Pizzi, A., Mengarelli, C., Rossini, G., Duca, D. & Toscano, G., (2018). Near infrared spectroscopy for the discrimination between different residues of the wood processing industry in the pellet sector. Fuel, 217, 650-655.

Özgenç, Ö., Durmaz, S., Boyaci, I.H. & Eksi-Kocak, H., (2017). Determination of chemical changes in heat-treated wood using ATR-FTIR and FT Raman spectrometry. Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy, 171, 395-400. https://doi.org/10.1016/j.saa.2016.08.026

Ozgenc, O., Durmaz, S., Serdar, B., Boyaci, I.H., Eksi-Kocak, H. & Öztürk, M., (2018). Characterization of fossil Sequoioxylon wood using analytical instrumental techniques. Vibrational Spectroscopy, 96, 10-18. https://doi.org/10.1016/j.vibspec.2018.02.006

Pastore, T.C.M., Braga, J.W.B., Coradin, V.T.R., Magalhães, W.L.E., Okino, E.Y.A., Camargos, J.A.A., de Muñiz, G.I.B., Bressan, O.A. & Davrieux, F., (2011). Near infrared spectroscopy (NIRS) as a potential tool for monitoring trade of similar woods: Discrimination of true mahogany, cedar, andiroba, and curupixá. Holzforschung, 65(1), 73-80. https://doi.org/10.1515/hf.2011.010

Popescu, C.M., Popescu, M.C., Singurel, G., Vasile, C., Argyropoulos, D.S. & Willfor, S., (2007). Spectral characterization of eucalyptus wood. Applied spectroscopy, 61(11), 1168-1177. https://doi.org/10.1366/000370207782597076

Popescu, C.M., Singurel, G., Popescu, M.C., Vasile, C., Argyropoulos, D.S. & Willför, S., (2009). Vibrational Spectroscopy and X-ray diffraction methods to establish the differences between hardwood and softwood. Carbohydrate polymers, 77(4), 851-857. https://doi.org/10.1016/j.carbpol.2009.03.011

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. https://doi.org/10.1515/HF.2008.104

Ramalho, F.M., Andrade, J.M. & Hein, P.R., (2018). Rapid discrimination of wood species from native forest and p lantations using near infrared spectroscopy. Forest Systems, 27(2), e008-e008. https://doi.org/10.5424/fs/2018272-12075

Russ, A., Fišerová, M. & Gigac, J., (2009). Preliminary study of wood species identification by NIR spectroscopy. Wood Research, 54(4), 23-32.

Sandak, A., Sandak, J. & Negri, M., (2011). Relationship between near-infrared (NIR) spectra and the geographical provenance of timber. Wood Science and Technology, 45, 35-48. https://doi.org/10.1007/s00226-010-0313-y

Schimleck, L. & Workman Jr, J., (2004). Analysis of timber and paper. Near‐Infrared Spectroscopy in Agriculture, 44, 633-646.. https://doi.org/10.2134/agronmonogr44.c22

Schubert, M., Panzarasa, G. & Burgert, I., (2022). Sustainability in wood products: a new perspective for handling natural diversity. Chemical Reviews, 123(5), 1889-1924. https://doi.org/10.1021/acs.chemrev.2c00360

Schloenhardt, A. & Schloenhardt, A., (2008). The illegal trade in timber and timber products in the Asia-Pacific region (No. 89). Canberra: Australian Institute of Criminology.

Schwanninger, M., Hinterstoisser, B., Gierlinger, N., Wimmer, R. & Hanger, J., (2004). Application of Fourier transform near infrared spectroscopy (FT-NIR) to thermally modified wood. Holz als Roh-und Werkstoff, 62, 483-485.

Sharma, V., Yadav, J., Kumar, R., Tesarova, D., Ekielski, A. & Mishra, P.K., (2020). On the rapid and non-destructive approach for wood identification using ATR-FTIR spectroscopy and chemometric methods. Vibrational Spectroscopy, 110, 103097. https://doi.org/10.1016/j.vibspec.2020.103097

Silva, D.C., Pastore, T.C., Soares, L.F., de Barros, F.A., Bergo, M.C., Coradin, V.T., Gontijo, A.B., Sosa, M.H., Chacón, C.B. & Braga, J.W., (2018). Determination of the country of origin of true mahogany (swietenia macrophylla King) wood in five Latin American countries using handheld NIR devices and multivariate data analysis. Holzforschung, 72(7), 521-530. https://doi.org/10.1515/hf-2017-0160

Soest, P.V., (1963). Use of detergents in the analysis of fibrous feeds. II. A rapid method for the determination of fiber and lignin. Journal of the Association of official Agricultural Chemists, 46(5), 829-835. https://doi.org/10.1093/jaoac/46.5.829

Solinge, T.V., Zuidema, P., Vlam, M., Cerutti, P.O. and Yemelin, V., (2016). Organized forest crime: a criminological analysis with suggestions from timber forensics.nIUFRO World Series, 35, 81-96.

Teodorescu, I., Erbasu, R.I., Branco, J.M. & Tapusi, D., (2021). Study in the changes of the moisture content in wood. IOP Conference Series: Earth and Environmental Science, 664, 012017. https://doi.org/10.1088/1755-1315/664/1/012017

Traoré, M. & Martínez Cortizas, A., (2023). Comparative study of four timber wood species in southern Mali (West Africa) by combining FTIR spectroscopy and multivariate analysis. European Journal of Wood and Wood Products, 81(6), 1513-1524. https://doi.org/10.1007/s00107-023-01979-8

Traoré, M., Kaal, J. & Cortizas, A.M., (2016). Application of FTIR spectroscopy to the characterization of archeological wood. Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy, 153, 63-70. https://doi.org/10.1016/j.saa.2015.07.108

Tsuchikawa, S., (2007). A review of recent near infrared research for wood and paper. Applied spectroscopy Reviews, 42(1), 43-71. https://doi.org/10.1080/05704920601036707

Tuncer, F.D., Kartal, S.N., Soytürk, E.E., Arango, R.A., Ohno, K.M., Önses, M.S., Çelik, N. & Ibanez, C.M., (2024). Changes in chemical properties and microstructure of Pinus taeda and Eucalyptus bosistoana woods modified by contact charring. European Journal of Wood and Wood Products, 82(1), 107-121.

Wiedenhoeft, A., (2016). Best practice guide for forensic timber identification. In: United Nations Office on Drugs and Crime: International Consortium on Combating Wildlife Crime. Vienna, Austria: Laboratory and Scientific Section, Global Programme for Combating Wildlife and Forest Crime: 1-226.

Wallen, K.E., (2018). Global timber trafficking harms forests and costs billions of dollars–here’s how to curb it. The Conversation, 24.

Yang, Z., Liu, Y., Pang, X. & Li, K, (2015). Preliminary investigation into the identification of wood species from different locations by near infrared spectroscopy. BioResources, 10(4), pp.8505-8517.

Zhao, X., Chen, J., Chen, F., Wang, X., Zhu, Q. & Ao, Q., (2013). Surface characterization of corn stalk superfine powder studied by FTIR and XRD. Colloids and Surfaces B: Biointerfaces, 104, 207-212., https://doi.org/10.1016/j.colsurfb.2012.12.003