Portable microNIR sensor for the evaluation of mould contamination on wooden surfaces

Convention Theme: Renewable Materials and the Wood-based Bioeconomy

Document identifier: oai:DiVA.org:ltu-76467
Keyword: Engineering and Technology, Mechanical Engineering, Other Mechanical Engineering, Teknik och teknologier, Maskinteknik, Annan maskinteknik, Mould fungi, MicroNIR, Wood, Naturally seasoned, Kiln-dried, Multivariate model, Träteknik, Wood Science and Engineering
Publication year: 2019
Relevant Sustainable Development Goals (SDGs):
SDG 9 Industry, innovation and infrastructure
The SDG label(s) above have been assigned by OSDG.ai

Abstract:

The traditional assessment of mould growth is sometimes subjective and can differ from person to person. By applying spectroscopic tools, it is possible to create an individual fingerprint of a wooden material and create databases for obtaining more objective information related to the chemical and biological composition. Side-boards (the flat-sawn sapwood part of the log) of Scots pine were single stacked on stickers and naturally dried indoors at 20°C to an average moisture content (MC) of 4.6%. Another ten side-boards were dried in a small-scale laboratory air-circulation kiln to an average MC of 14%. Another group of side-boards were double-stacked with the bark-side surfaces of each pair turned outwards in order to get a high extractive concentration on these surfaces, and less concentration on opposite surfaces. The different flat-side surfaces were planed according to a planing-depth scheme : 0 mm (unplanned), 0.25, 0.75, and 1.75 mm depth from the surface, and the residual wood particles were collected for further analysis. The planned surfaces were exposed to a mould test, performed by spraying a spore suspension of five mould fungi on the wood surfaces followed by incubation at the temperature of 24°C and 95±3%RH for 35 days. Thereafter, the surfaces were graded according to mould growth. A portable microNIR sensor (wave-length range 900-1670 nm, step 6 nm) was used for NIRspectra detection on the surfaces after mould test, and a data matrix was created. Multivariate analysis of obtained spectra was performed. The results show that the principal component analysis (PCA) can describe and predict 99.7% of the spectroscopic data obtained. No influence of the drying method or planned depth was discovered during classification. Two mould-classes could, however, be clearly separated; no mould, and with mould growth respectively, and the separation could be detected on a 93.4% level.

The study demonstrates that mould growth on the wooden surface could be evaluated by portable MicroNIR spectrometer, which is sensitive enough to detect chemical differences caused by fungal contamination.

Authors

Olena Myronycheva

Luleå tekniska universitet; Träteknik
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Olov Karlsson

Luleå tekniska universitet; Träteknik
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Margot Sehlstedt-Persson

Luleå tekniska universitet; Träteknik
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Micael Öhman

Luleå tekniska universitet; Träteknik
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Dick Sandberg

Luleå tekniska universitet; Träteknik
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