Development of Low-Cost Portable Spectrometers for Detection of Wood Defects

Portable spectroscopic instruments are an interesting alternative for in-field and on-line measurements. However, the practical implementation of visible-near infrared (VIS-NIR) portable sensors in the forest sector is challenging due to operation in harsh environmental conditions and natural variability of wood itself. The objective of this work was to use spectroscopic methods as an alternative to visual grading of wood quality. Three portable spectrometers covering visible and near infrared range were used for the detection of selected naturally occurring wood defects, such as knots, decay, resin pockets and reaction wood. Measurements were performed on wooden discs collected during the harvesting process, without any conditioning or sample preparation. Two prototype instruments were developed by integrating commercially available micro-electro-mechanical systems with for-purpose selected lenses and light source. The prototype modules of spectrometers were driven by an Arduino controller. Data were transferred to the PC by USB serial port. Performance of all tested instruments was confronted by two discriminant methods. The best performing was the microNIR instrument, even though the performance of custom prototypes was also satisfactory. This work was an essential part of practical implementation of VIS-NIR spectroscopy for automatic grading of logs directly in the forest. Prototype low-cost spectrometers described here formed the basis for development of a prototype hyperspectral imaging solution tested during harvesting of trees within the frame of a practical demonstration in mountain forests.

[1]  L. Schimleck,et al.  NEAR-INFRARED SPECTROSCOPY : A RAPID NON-DESTRUCTIVE METHOD FOR MEASURING WOOD PROPERTIES , AND ITS APPLICATION TO TREE BREEDING * , 2007 .

[2]  R. Meder Near Infrared Spectroscopy: Seeing the Wood in the Trees , 2016 .

[3]  Jun Cao,et al.  Potential of Near-infrared Spectroscopy to Detect Defects on the Surface of Solid Wood Boards , 2016 .

[4]  H. Hou,et al.  Comparative investigation of partial least squares discriminant analysis and support vector machines for geological cuttings identification using laser-induced breakdown spectroscopy , 2014 .

[5]  B. Hinterstoisser,et al.  Near Infrared Spectroscopy as a Tool for In-Field Determination of Log/Biomass Quality Index in Mountain Forests , 2016 .

[6]  Bo Johnsson,et al.  NIR techniques create added values for the pellet and biofuel industry. , 2009, Bioresource technology.

[7]  K. Héberger,et al.  Supervised pattern recognition in food analysis. , 2007, Journal of chromatography. A.

[8]  S. Avramidis,et al.  Application of near-infrared spectroscopy for moisture-based sorting of green hem-fir timber , 2011, Journal of Wood Science.

[9]  Gianni Picchi,et al.  Development of a Sensorized Timber Processor Head Prototype – Part 1: Sensors Description and Hardware Integration , 2019 .

[10]  B. Leblon,et al.  Determination of moisture content and basic specific gravity of Populus tremuloides (Michx.) and Populus balsamifera (L.) logs using a portable near-infrared spectrometer , 2015 .

[11]  Ying Li,et al.  Lifting Wavelet Transform De-noising for Model Optimization of Vis-NIR Spectroscopy to Predict Wood Tracheid Length in Trees , 2018, Sensors.

[12]  David I. Ellis,et al.  A tutorial review: Metabolomics and partial least squares-discriminant analysis--a marriage of convenience or a shotgun wedding. , 2015, Analytica chimica acta.

[13]  Jakub Sandak,et al.  Relationship between near-infrared (NIR) spectra and the geographical provenance of timber , 2011, Wood Science and Technology.

[14]  Amr H. Abd-Elrahman,et al.  Design and Development of a Multi-Purpose Low-Cost Hyperspectral Imaging System , 2011, Remote. Sens..

[15]  Jorge Luis Monteiro de Matos,et al.  Comparison of Methods for Estimating Mechanical Properties of Wood by NIR Spectroscopy , 2018 .

[16]  Lisbeth G. Thygesen,et al.  NIR Measurement of Moisture Content in Wood under Unstable Temperature Conditions. Part 2. Handling Temperature Fluctuations , 2000 .

[17]  S. Kawano,et al.  Development of a Calibration Equation with Temperature Compensation for Determining the Brix Value in Intact Peaches , 1995 .

[18]  Colin E. Snape,et al.  Bark decay by the white-rot fungus Lentinula edodes: Polysaccharide loss, lignin resistance and the unmasking of suberin , 2006 .

[19]  Christian R. Mora,et al.  Comparison of Whole-Tree Wood Property Maps for 13- and 22-Year-Old Loblolly Pine , 2018 .

[20]  C. Miliani,et al.  FT-NIR spectroscopy for non-invasive identification of natural polymers and resins in easel paintings , 2009, Analytical and bioanalytical chemistry.

[21]  José Tarcísio Lima,et al.  ESTIMATION OF THE MECHANICAL PROPERTIES OF WOOD FROM Eucalyptus urophylla USING NEAR INFRARED SPECTROSCOPY , 2010 .

[22]  Karin Fackler,et al.  A Review of Band Assignments in near Infrared Spectra of Wood and Wood Components , 2011 .

[23]  Jakub Sandak,et al.  Monitoring of Wood Decay by near Infrared Spectroscopy , 2013 .

[24]  R. Meder,et al.  Technical Note: Handheld near Infared Spectroscopy for the Prediction of Leaf Physiological Status in Tree Seedlings , 2014 .

[25]  J. Braga,et al.  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 , 2018 .

[26]  G. I. Muñiz,et al.  Potential use of nir and visible spectroscopy to analyze chemical properties of thermally treated wood , 2018 .

[27]  Miguel Lopo,et al.  A Review on the Applications of Portable Near-Infrared Spectrometers in the Agro-Food Industry , 2013, Applied spectroscopy.

[28]  P. R. Hein,et al.  Challenges in the use of Near Infrared Spectroscopy for improving wood quality: A review , 2018 .

[29]  P. Fardim,et al.  Composition of callus resin of Norway spruce, Scots pine, European larch and Douglas fir , 2008 .

[30]  W.G. Hansen,et al.  Tolerance of near Infrared Calibrations to Temperature Variations; A Practical Evaluation , 2000 .

[31]  Wei Jiang,et al.  Mechanical and Physical Properties of Oriented Strand Board Exposed to High Temperature and Relative Humidity and Coupled with Near-Infrared Reflectance Modeling , 2018 .

[32]  Roger Meder,et al.  The Magnitude of Tree Breeding and the Role of near Infrared Spectroscopy , 2015 .

[33]  Lisbeth G. Thygesen,et al.  NIR Measurement of Moisture Content in Wood under Unstable Temperature Conditions. Part 1. Thermal Effects in near Infrared Spectra of Wood , 2000 .

[34]  J. Sandak,et al.  Assessing Trees, Wood and Derived Products with near Infrared Spectroscopy: Hints and Tips , 2016 .