A Novel Approach to Identify Wood Species Optically Using Fluorescence Lifetime Imaging Microscopy

DOI 10.5162/SMSI2021/B10.2

A Novel Approach to Identify Wood Species Optically using Fluorescence Lifetime Imaging Microscopy

Nina Leiter1, Maximilian Wohlschläger1, Veronika Auer1, Martin Versen1, Christian Laforsch2 1 Technical University of Applied Sciences Rosenheim, Hochschulstr. 1, 83024 Rosenheim, Germany 2 University Bayreuth, Universitätsstr. 30, 95447 Bayreuth, Germany [email protected]

Summary: This contribution presents the results obtained with fluorescence lifetime imaging microscopy (FLIM) within the optical identification and differentiation of the four wood species walnut, beech, spruce, and maple. The experimental setup as well as the evaluation algorithm, with which the experiments were carried out, is explained briefly.

Keywords: Fluorescence Lifetime, wood species identification, Fluorescence, wood, FLIM

Introduction The main component responsible for fluorescence signal of wood under excitation in the Wood is the world's most important renewable ultraviolet (UV) of visual (VIS) region is lignin in raw material, which can be used several times the cell walls [5]. The spectral fluorescent prop- within a life cycle, as material and for energy erties can be used for an identification purpose production at the end of the life cycle. The are- of wood, but vary in a significant manner [6]. as of material application are manifold and span Also, the fluorescence lifetime, measured in from building, construction, engineered material time-domain, can be used to identify wood spe- and interior products. After the specific product cies [7, 8]. In order to use the method of fluo- life time, the then so called post-consumer rescence decay time measurement in the time wood can be recycled and reprocessed. Actual- domain, fast synchronization and expensive ly, recycled wood is mainly used within particle equipment is required, which seems uneconom- boards (up to 33% [1]). However, this material ical. flow represents only 17% of the yearly resulting post-consumer wood in 2016. If the 6 % of pol- Alternatively, the fluorescence decay time can luted wood is taken into account, approximately be measured in the frequency domain with a 77 % of the post-consumer wood would poten- FD-FLIM (frequency domain fluorescence life- tially be available [2]. Therefore, the non- time imaging microscopy) camera. In this case, invasive and in-situ identification of wood spe- larger areas can be examined at once and the cies opens new material utilisation pathways of costs are considered to be lower. For this rea- post-consumer wood, e.g. in massive wood son, the FD-FLIM method is investigated in this products or in biorefineries. contribution. At the moment, there are two main techniques Description of the New Method under research to identify wood: near-infrared In the FD FLIM method, the sample is excited spectroscopy (NIRS) and X-ray fluorescence by a sinusoidal or rectangular modulated light spectroscopy (XRF). According to [3], it is pos- signal. The resulting fluorescence signal (emis- sible to identify wood types using NIRS. Unfor- sion) is phase shifted to the excitation signal. If tunately, the detection is complicated because the phase shift ϕ is measured at a known the NIR spectrum is superimposed with the modulation frequency ω, the fluorescence life- absorption band of the variable moisture con- time can be calculated according to eq. (1). tent in wood. The second method to identify wood is XRF [4]. This method is not appropriate 𝜏𝜏𝜏𝜏1 τ ⋅= tan(φ) (1) for an automated wood identification, since only ω pollutants such as heavy metals with high atom- ic numbers can be identified.. Thus, there is a The PCO AG from Kelheim has developed an demand for the development of a reliable and FD-FLIM camera system, which can measure automatable method of wood identification and fluorescence decay times from 100 ps up to sorting. 100 µs with a dynamic range of 10 bit [9]. For

SMSI 2021 Conference – Sensor and Measurement Science International 169 DOI 10.5162/SMSI2021/B10.2

each of the 1008x1008 pixels, the intensity, the tional wood species should be investigated to phase shift, the modulation depth and the exploit the full potential. phase and modulation lifetime can be deter- Tab. 1: Calculated mean values of the fluorescence mined. lifetime and corresponding standard deviation. The experimental setup consists of a laser di- ode Omicron PhoxX-488 that emits a sinusoidal Wood species Fluorescence lifetime [ns] modulated light signal of 488 nm wavelength Walnut 1.29 ± 0.06 with a definite modulation frequency ω. As fluorescence detector a pco.flim camera is used. Beech 1.51 ± 0.09 Two optical filters placed in the excitation and Spruce 1.84 ± 0.04 emission paths narrow the bandwidth and block stray and reflected light. All components are Maple 1.92 ± 0.04 assembled to a Motic PSM 1000 microscope, which contains a 20x magnification objective. References [1] Klinker G., In praise of recycled wood. PFL Inspi- Four images of each sample at random posi- rations, 2016 tions are captured with the experimental setup http://inspirations.pfleiderer.com/13680-in-praise- and evaluated with a Gaussian analyzation as of-recycled-wood. (Last Accessed 23 Nov. 2020) described in [10]. [2] Flamme S., Hams S., Bischoff J., Fricke C., For the experiments wooden probes of walnut, Evaluierung der Altholzverordnung im Hinblick beech, spruce and maple with a size of 2x2x0.5 auf eine notwendige Novellierung, Umweltbun- cm are prepared. desamt, Münster, 2019, ISSN 1862-4804 [3] Mauruschat, D., Plinke, B., Aderhold, J., Gun- Results schera, J., Meinlschmidt, P., Salthammer, T., Ap- The measured fluorescence decay times for plication of near-infrared spectroscopy for the fast each wood specie are presented in Fig. 1. The detection and sorting of wood–plastic composites measured values fit very well to Gaussian dis- and waste wood treated with wood preservatives. tributions. With this representation, a graphical Wood Sci Technol 50, 2016, pp. 313–331. DOI: differentiation and identification of the individual 10.1007/s00226-015-0785-x types of wood is possible. [4] Hasan R., Solo-Gabriele, H.; Townsend T., Online sorting of recovered wood waste by automated XRF-technology: part II. Sorting efficien- cies. In: Waste management, 31, 4, 2011a, pp. 695–704. DOI: 10.1016/j.wasman.2010.10.024. [5] Albinsson, B., Li, S., Lundquist, K. & Stomberg, R. (1999) The origin of lignin fluorescence. J. Mol. Struct. 508, 19–27. [6] Donaldson L.A., Softwood and hardwood lignin fluorescence spectra of wood cell walls in different mounting media. IAWA J 34, 2013, pp. 3–19. DOI: 10.1163/22941932-00000002 [7] Donaldson L.A., Radotic K, Fluorescence lifetime imaging of lignin autofluorescence in normal and compression wood. J Microsc., 251, 2, 2013, pp. 178-187, DOI: 10.1111/jmi.12059 Fig. 1. Visualization of the measured fluorescence [8] Burkhardt, H. Die Fluoreszenzlebensdauer in der lifetimes of the four different wood species. Holztechnologie. Holztechnologie 60,6 , 2019, pp. 26–30. In addition, the calculated mean values of the fluorescence lifetimes and the corresponding [9] Chen H., Holst G., Gratton E., Modulated CMOS standard deviations show similar results assum- Camera for Fluorescence Lifetime Microscopy, ing a Gaussian distribution (see Tab. 1). Thus, Microscopy Research & Technique, 78, 12, 2015, pp. 1075-1081. DOI: 10.1002/jemt.22587 an identification is also possible by calculation. [10] M. Wohlschläger, G. Holst, M. Versen, A novel In summary, the wood species are unambigu- approach to optically distinguish plastics based ously distinguishable and identifiable graphical- on fluorescence lifetime measurements, IEEE ly and by calculation due to their characteristic Sensor Applications Symposium 2020, Kuala fluorescence lifetime. This study clearly reveals Lumpur, Malaysia, 2020, pp. 1-6. the potential of the FD-FLIM technique for wood DOI: 10.1109/SAS48726.2020.9220084 identification procedures. In the future, addi-

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