Assessment of the relationships between extractive content, mould growth, and drying methods of Scots pine wood using multivariate data analysis

Assessment of the relationships between extractive content, mould growth, and drying methods of Scots pine wood using multivariate data analysis | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Assessment of the relationships between extractive content, mould growth, and drying methods of Scots pine wood using multivariate data analysis Anastasiia Postovoitova, Olena Myronycheva, Olov Broman, Olov Karlsson This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6253804/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 26 Aug, 2025 Read the published version in European Journal of Wood and Wood Products → Version 1 posted 12 You are reading this latest preprint version Abstract Wooden construction material is a sustainable contribution to carbon sequestration and long-term storage. Despite its strength, sustainability, and versatility, the vulnerability to biodeterioration is an issue. Therefore, this study aimed to identify the differences in mould growth features and surface extractive composition of the Scots pine ( Pinus sylvestris L.) sapwood sideboards between the air- and kiln-drying methods using multivariate data analysis. Air and kiln-dried sideboards were used to extract different low molecular compounds from the surface layer, assess the moisture content, and conduct a mould test. Principal component analysis revealed grouping for the drying types of the sideboards. This was confirmed by partial least-squares discriminant analysis, which allowed the sideboard characteristics of two wood drying types to be described. An outlier was detected among the air-dried observations. More intensive mould growth was detected on kiln-dried Scots pine sideboards than on air-dried. A higher amount of total lipophilic compounds, phenols and inorganic components were found on the kiln-dried sideboard surface. The surface extractives from kiln-dried sideboards contained a higher amount of almost all analysed fatty and resin acids, except for the oleic acid, the amount of which prevailed precisely on the air-dried sideboard surface. Low-molecular-weight sugars, namely glucose, saccharose and fructose, were present in significant amounts on the surface of the kiln-dried sideboards. This is presumably contributed to the rapid spread of mould. In general, multivariate modelling allowed to establish that the method of wood drying significantly influenced the redistribution of extractive components on the surface and the subsequent mould growth. Wood drying type extractives mould multivariate analysis Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 1 Introduction Mould growth is undesirable in wood construction because it is associated with aesthetic issues, increased maintenance costs, and poses a health hazard (Platt et al. 1989 ). The mould includes various species of fungi that cause wood discolouration due to the growth of their biomass on the surface. Although mould does not change the mechanical properties of wood, it is necessary to treat the material to prevent mould development through chemical and thermal wood modification or wood coating (Sheikh et al. 2013 ; Niemz et al. 2023 ). Mould growth on wood surfaces depends on many factors, such as local climate conditions (temperature, relative humidity, etc.), geographical location, fungal diversity, moisture content and extractive content of the wood (Terziev and Boutelje 1998 ; Råberg et al. 2005 ; Poohphajai et al. 2023 ). Among these factors, the content of wood extractives demonstrates significant practical interest. In addition to cellulose, hemicelluloses, and lignin as the main structural components, wood contains various non-structural low molecular weight compounds that can be extracted using appropriate solvents (Fengel and Wegener 1984 ; Sjostrom 1993 ). The waxes, fats, terpenes and terpenoids, saturated and unsaturated fatty acids, monosaccharides and complex carbohydrates, alkanes, proteins, alkaloids, phenolic compounds and flavonoids refer to wood extractives (N'Guessan et al. 2023 ). However, the qualitative and quantitative characteristics of the various components vary significantly in different wood materials. This is directly related to the tree species, age, geographical location, and climate conditions during its growth. Seasonal characteristics of tree cutting and wood material storage time also significantly impact extractive composition (Terziev et al. 1997 ; Flaviano et al. 2011). In addition, the qualitative profile of the extractive components is so unique that it allows for creating a unique "chemical signature" for identifying wood material through belonging to a specific family, genus and wood species (N'Guessan et al. 2023 ). In general, extractives provide a physical and chemical barrier against wood-degrading agents. The composition of extractives affects many physical properties and, to a lesser extent, mechanical properties of wood, namely colour, odour, water permeability, durability, density and hardness, and acoustic properties (Pettersen 1984 ; Santana et al. 2010 ; N'Guessan et al. 2023 ). Also, the protective properties of certain extractives against fungal, bacterial and insect agents have been proven (N'Guessan et al. 2023 ). It was found that lignivorous organisms (fungi and termites) destroyed wood from which extractives had previously been removed much faster than unextracted wood (Kirker et al. 2013 ). The biocidal properties of wood extractives could be used in developing preparations for preserving the natural durability of wood (Lovaglio et al. 2017 ). Since extractives are complex mixtures, their composition can vary depending on the extraction method chosen (Diouf et al. 2009 ) and the application of various technological operations such as drying. The wood is dried to remove water and produce a lighter, more durable and stable material. Drying together with heat treatment not only causes a change in the physical and mechanical properties of wood but also causes a change in the composition of extractives and their distribution in the wood layers (Sehlstedt-Persson et al. 2010). Scots pine ( Pinus sylvestris L.) wood, as one of the main sources of wood constructions in Nordic countries, is rich in extractives, which significantly affects the final material's properties during wood processing (drying, modification, heating, etc.). Given the susceptibility of Scots pine wood to mould (Sehlstedt-Persson et al. 2011 ; Sheikh et al. 2013 ), it was chosen for this study. Given all of the above, studying the relationships between wood pre-treatment processes, the composition of extractives and their effect on the growth of pathogenic organisms, particularly mould fungi, is a critically important issue for the wood industry and requires detailed research. Because of this, our study was conducted to assess the impact of the air-and kiln-drying methods of Scots pine wood on the composition of the selected extractives from the sideboard surfaces and the growth characteristics of mould fungi using multivariate data analysis. 2 Materials and methods 2.1 Sample preparation and drying A total of 20 Scots pine sideboards were analysed. The sideboards were obtained initially from 10 Scots pine trees cut and sawn in a Sawmill in Norrbotten County (Sweden). Each board had dimensions of 25mm tangential (T) × 100mm radial (R) × 220mm longitudinal (L) and contained only sapwood. No permits were required for this study as no protected or endangered species were used. Two wood-drying methods were used in the study: air- and kiln-drying. Ten randomly selected Scots pine sideboards were single-stacked and dried indoors on stickers for 30 days at a temperature of 20 ℃ and RH of about 10%. The other 10 sideboards were dried in a laboratory kiln (Valutec, Sweden) with air circulation. During kiln drying, the sideboards were placed in pairs, and the sapwood sides of each pair were blown with air. This resulted in a rapid movement of water and moisture from the deep layers of the wood to the wood surface. Drying was carried out for 44 hours, including a heating phase (1.7 hours), the main drying phase (37.3 hours) and a cooling phase (5 hours). The drying temperature was 60℃ and rose to 77℃ during the drying phase (Myronycheva et al. 2018 ). The conditioning phase was excluded from the kiln drying process to eliminate its influence on the distribution of extractive components on the board surface. 2.2 Analysis of extractive content Planing of the surface of wooden sideboards (0.25 mm depth) from the bark side of sapwood from 10 air-dried sideboards and 10 kiln-dried sideboards was done to obtain material for extraction of lipophilic and water-soluble compounds. The planned surface wood from each board was separately milled in a planetary mill (Fritsch, Germany). The resulting material was stored at – 20 ℃. The milled wood (0.5 g) was used to determine the moisture content by heating it in an oven at 103℃ according to the standard SS-EN 13183-1 (2004). Extractives were extracted from 1.0 g of milled surface wood with acetone (VWR Chemicals: 20165.323) in a Soxhlet extractor as described in SCAN-CM 49:03 ( 2003 ) standard method. After acetone evaporation and drying of the residue, the total extractives content was measured in mg/g of dry mass. The content of total phenols (mg/g of dry mass) was evaluated using the Folin-Ciocalteu (FC) approach (Julkunen-Tiitto 1985 ) with tannic acid (VWR Chemicals; 83510.260) as a standard. After adding all components to the sample, the absorption was measured after 40 minutes at 735 nm in a UV spectrophotometer (U-1500, Hitachi, Japanese). Saturated (palmitic and stearic), unsaturated (oleic and linoleic) fatty acids and resin (pimaric, isopimaric, abietic and dehydroabietic) acids and glycerol were measured in the dried acetone extracts using a Gas Chromatography-Mass Spectrometry (GC-MS) system (GCMS-QP2020, Shimadzu, Japan) with A SUPELCO SLB-5 MS capillary column (30 m, 0.25 mm inner diameter, 0.25 µm film thickness). Before GC-MS, trimethylsilylation was done by treatment with 100 µl of N,O-bis-(trimethylsilyl)trifluoroacetamide (BSTFA) and 50 µl of trimethylsilyl chloride (TMSCl) in an oven at 70˚C for 20 minutes (Sjostrom and Alen 1999 ) with 1-methylnaphthalene dissolved in pyridine as internal standard (Lai 1992 ). The oven temperature program used a heating rate of 10 ℃/min starting from 100 ℃ (1 min at initial temperature) to 270 ℃ (holding for 2 min. at final temperature). The analysis cycle took 25 minutes, and the mass spectrum was recorded at 70 eV in 40–500 m/z with a scan speed of 1000. NIST Mass Spectral Library was used to identify fatty and resin acids (Johnson 2016). Quantification was performed by comparing the target peak area with the peak area of the internal standard. The low molecular weight sugars (saccharose, glucose and fructose) in the water extracts were analysed by High-Performance Liquid Chromatography (HPLC) (Shimadzu, Japan) with Hi-plex Pb-column (250 mm length, 7.7 inner diameter, 8 µm particle size) (Karlsson et al. 2012 ). Water extracts were previously made by mixing the wood with water, followed by an ultrasonic treatment for 1 hour, and then left overnight. Water extracts were filtered (50 µm) and analysed in HPLC at 60 ℃ using water as eluent with 0.3 mL/min flow rate. An RI detector was used to detect sugars, and quantitative values were determined by comparing them with calibration curves for target compounds. The amount of nitrogen was investigated as described in Kjeldahl ( 1883 ). The ash content was determined by thermogravimetric analysis using a hardening furnace (N7, Nabertherm, Germany). All measurements of extractive compounds are presented in mg/g of dry mass. Microsoft Excel software was used to calculate the minimum, mean, and maximum values for each variable, namely the 'MIN', 'AVERAGE', and ' MAXIMUM' functions. More detailed data are presented in Table 1 . Table 1 The minimum, mean and maximum values of extractive components obtained from air- and kiln-dried Scots pine sideboards. The data was previously reported (Karlsson et al. 2017 ) Name of component Air-dried Kiln-dried Minimum (mg/g) Mean (mg/g) Maximum (mg/g) Minimum (mg/g) Mean (mg/g) Maximum (mg/g) Total extractives 25.16447 35.94391 49.06973 41.86167 57.0666 69.70297 Palmitic acid 0 0.451979 2.13298 0 0.268747 1.254856 Oleic acid 0.488388 3.63414 25.05234 0 0.200793 1.77299 Linoleic acid 0 0.677081 6.225504 0 0.200793 0.484073 Stearic acid 0.086986 0.291703 0.903579 0 0.325746 1.249394 Pimaric acid 0.381058 1.575837 6.687396 0.111469 1.94274 3.770454 Isopimaric acid 0.282911 1.046451 3.342869 0.102333 1.492612 3.132764 Dehydroabietic acid 0.778021 4.366863 17.61476 0.324956 4.549238 7.584099 Abietic acid 0.246364 0.813388 4.119094 0.331476 0.854376 2.245718 Glycerol 0.123983 0.432197 1.054243 0 0.815225 1.67847 Total phenols 0.221447 0.443865 0.813221 0.006388 0.808393 2.063208 Nitrogen 0.032927 0.381367 2.47457 0 0.267047 0.697599 Saccharose 0.066026 0.086289 0.146079 0 0.416249 1.710012 Glucose 0.017586 0.160287 0.467799 0 0.805327 1.827902 Fructose 9.51E-05 0.131653 0.702911 0 0.602831 2.475419 Ash 0.179372 0.329013 0.439078 0 0.805689 1.851852 2.3 Mould test Ten air-dried and ten kiln-dried Scots pine sideboards were investigated in this study. Mould growth on the board surfaces was induced by the spraying of a water mixture which contained spore suspension of the five fungal species ( Aspergillus niger van Tieghem, Penicillum commune Trom, Paecilomyces variotii Bainier, Mucor plumbeus Bonord and Trihoderma longibrachiatum Rifai). All fungal cultures belong to the Division of Wood Science and Engineering collection at Luleå University of Technology (Skelleftea, Sweden). Fungal cultures were grown in Petri dishes (Ø 90 mm) using malt extract agar medium (Milipore; 70145) in the laboratory chamber (HPP260eco, Memmert, Germany) at 25 ℃ and RH of 90% for 7 days. The dilution buffer (10 mL) (0.02 M Potassium dihydrogen phosphate (VWR Chemicals; 7778.77.0), 0.05 M Disodium hydrogen phosphate dehydrate (Merck KGaA; 10028.24.7), 0.074 M Sodium chloride (Sigma Aldrich; 7647.14.5), 0.01% (v/v) Tween 80 (VWR Chemicals; 9005.65.6), 1L distilled water) was used to wash the spores from the surface of each Petri dishes separately. Spores from hyphae were removed into the dilution buffer using a sterile glass spreader. The spore suspension was filtered through sterile mineral wool to remove residual mycelium parts. The number of spores was counted using a hemocytometer, and the suspension was diluted to a concentration of 10 6 spores/mL. Equal volumes of spore suspensions of five fungal cultures were mixed and stored at 4 ℃ until use. The resulting suspension (2 mL) was sprayed on each Scots pine board, and sideboards were left in the laboratory chamber (HPP260eco, Memmert, Germany) at 22 ℃ and RH of 90% for 30 days. ImageJ (NIH, Maryland, USA) software determined the percentage of mould coverage on the board surface by image analysis of all board sides. The mould class was determined according to the method described by Myronycheva et al. ( 2019 ). The spread, density, and colour intensity of mould on wood surfaces were visually assessed. Through visual assessment of all sides of the sideboards, each sample was assigned a mould growth intensity class (0–6). If there was no visible mould growth, the sample was assigned class 0. In the case of the most intensive mould growth, the sample had the highest class 6. 2.4 Principal Component Analysis (PCA) and Partial Least-Squares Discriminant Analysis (PLS-DA) As a result of the analysis of the composition of extractives, moisture content and the mould test, a dataset containing 20 observations and 20 variables was obtained. The SIMCA 18 (Sartorius AG, Göttingen, Germany) software package was used for PCA and PLS-DA modelling, aiming to describe the differences in mould growth features and extractive composition of the sideboard surface between the two wood drying methods (air- and kiln-drying). PCA was used to overview the correlation pattern, and PLS-DA was used to describe the sideboard characteristics for the two wood drying types. Cross-validation was used to test the robustness of the models. External validation of the models was not performed due to the small dataset limited to only 20 observations. Prior to analysis, all variables were scaled to unit variance. 3 Results and discussion 3.1 Investigation of extractive content and mould growth features A quantitative evaluation of 16 extractive components from 10 air-dried sideboards and 10 kiln-dried Scots pine sideboards was conducted. The minimum, mean, and maximum values of each component are given in Table 1 . The data obtained for each wood sample were used for further multivariate analysis using PCA and PLS-DA. Examples of mould growth on the surface of the boards after a 30-day mould test are shown in Fig. 1 . The percentage of mould surface coverage and mould class were determined by visual inspection. As seen in Table 2 , more intensive mould growth was detected on the surfaces of the kiln-dried boards. As many as 7 out of 10 kiln-dried samples were completely covered with mould (90–100%), and 9 kiln-dried boards were assigned the highest class 6. At the same time, significantly less mould growth was observed on the air-dried sideboards. Half or less than half of the surface (5–50%) was covered with mould for 8 out of the 10 air-dried samples analysed. The determined class for mould on the air-dried sideboards was lower than on the kiln-dried sideboards (class 4 and lower for 7 samples). The average moisture content of the sideboards after air- and kiln-drying was 4.6% and 4.4%, respectively. Detailed data for each wood sample are presented in Table 2 . Table 2 The mould area and class on air- and kiln-dried Scots pine sideboards after a 30-day mould test. The moisture content was measured before the mould test. The data was previously reported (Karlsson et al. 2017 ) Board ID Drying type, (Air/Kiln) Moisture, (%) Mould area, (%) Mould class AD1 Air 5.9 60 4 AD2 Air 4.7 5 2 AD3 Air 4.8 30 5 AD4 Air 3.7 45 4 AD5 Air 4.5 100 4 AD6 Air 3.8 5 6 AD7 Air 10.7 20 4 AD8 Air 3.5 50 4 AD9 Air 5.6 5 3 AD10 Air 4.4 50 6 KD1 Kiln 5.0 90 6 KD2 Kiln 4.3 50 4 KD3 Kiln 6.2 60 6 KD4 Kiln 4.5 100 6 KD5 Kiln 3.5 100 6 KD6 Kiln 2.0 100 6 KD7 Kiln 2.7 100 6 KD8 Kiln 4.5 90 6 KD9 Kiln 4.0 70 6 KD10 Kiln 6.5 100 6 3.2 Principal Component Analysis PCA was performed to get an overview and identify correlation patterns between the type of wood drying, the mould growth and the resulting composition of extractives on the dried wood surfaces. PCA is a linear approach that allows the visualisation of such data by creating linear combinations of the original variables onto principal components in plots and histograms. In this way, differences and similarities between samples become highlighted. The result of the PCA analysis of the entire dataset is shown in Fig. 2 . The systematic variation in the dataset was summarised by two significant principal components explaining 57.7% of the total variability ( R 2 [1] = 0.349 and R 2 [2] = 0.228). In general, the robustness of the model is displayed through the explained variance ( R 2 ) and the cross-validated predictive ability ( Q 2 ) values. In the score plot (Fig. 2 a), the observations are coloured by the type of sideboard drying (air- and kiln-dried). The two drying types group well and show a difference between the surface extractive composition and mould growth dependency. The data has one clear outlier, AD2, in the score plot. The reason for AD2 being a strong outlier is seen in Fig. 3 , where its data is compared to the rest of the air-dried sideboard observations. AD2 data compared to all the other air-dried sideboards show that it has extreme values on almost all fatty and resin acids. Linoleic, oleic, pimaric, dehydroabietic and abietic acid values were considerably higher for the AD2 than for other observations in the air-dried group. The data collection procedure was followed up, but the reason for such extreme values could not be verified. Thus, it is unclear whether this strong divergent behaviour results from a measurement error or if AD2 is a unique and extreme observation. A sign of a strong outlier is when the first principal component is oriented towards the outlier and explains the difference between AD2 and the other observations. Hence, the outlier AD2 was excluded from further analysis. A second PCA model without AD2 observation can be seen in Fig. 4 . The model explains 52.6% of the variations of the variables ( R 2 [1] = 0.369 and R 2 [2] = 0.156). In the score plot (Fig. 4 a), the observations are positioned rather well in two groups, following the type of wood drying. One air-dried sample, AD10, is more grouped within the kiln-dried type group. However, in the previous PCA model, it was also closely localised with the kiln-dried group. The grouping of observations shows a difference between the drying types regarding the chemical composition on the board surfaces in the data presented. In the loading plot (Fig. 4 b), it can be seen that the kiln-dried samples are associated with having higher values on the variables to the right and high up in the plot. The air-dried samples show the opposite pattern, with lower values on most variables. Oleic acid is the only chemical compound that seems to be more significant for the air-dried group. A discriminant analysis of the two drying types was executed to simplify the interpretation of the results. 3.2 Partial least-squares discriminant analysis PLS-DA is a classification approach which allows the prediction of dependent output Y variables from input X variables (Eriksson et al. 2006 ). Qualitatively dividing groups among themselves and visualising the profile of each group by adding group labels or hidden (latent) variables is also possible by creating PLS-DA models. Creating Y hidden variables in PLS-DA models is a handy tool that simplifies the analysis of the obtained results by creating a set of coefficients for each investigated group. Here, PLS-DA was used to determine prediction profiles of air- and kiln-dried Scots pine sideboards in relation to surface extractives after 30 days of mould growth. PLS-DA classified air- and kiln-drying types (Y variables) based on all extractive variables with mould class and mould area (X variables). Two components were significant, and the PLS-DA model explained 85.6% of variations in class ( R 2 = 0.856) and a predictive ability of 68.5% ( Q 2 = 0.685). The observed/predicted plot in Fig. 5 shows the correctness of the observation discrimination. All observations from the air- and kiln-dried groups were clearly separated. No observation was misclassified. On the score plot (Fig. 6a), a clear division of observations into two groups (air- and kiln-dried sideboards) was visualised. The two class variables can be seen in the loading plot marked $M2.DA(Air) and $M2.DA(Kiln) (Fig. 6b). They visualised the variance weight for each investigated wood drying type and separated them using the available variables data. The class variables are located on opposite sides of the plot. In particular, the air-dried type positively correlated with moisture, nitrogen, palmitic and oleic acids. All other 15 variables correlated positively with the kiln-drying type. In general, these results confirm the results obtained from the PCA model. The two coefficient plots for air- and kiln-drying types are shown as a visual representation of the contribution of each predictor variable to the PLS-DA classification model (Fig. 7 a, b). The coefficients are mirrored to describe the difference between the two groups. A typical predicted Scots pine board dried according to the air-drying method contains more oleic acid and, to some extent, more nitrogen. In our data, the air-dried samples had slightly higher moisture on the surface than the kiln-dried. The mould growth on air-dried boards is less intense (5–60% of the covered surface), and the mould class is lower. A typical predicted Scots pine board dried according to the kiln-dried method is richer in total extractive and nonorganic components (ash) and contains a higher amount of phenols, low molecular weight sugars, glycerol, some fatty (stearic, linoleic) and resin (pimaric, isopimaric, abietic and dehydroabietic). After our mould test, such a kiln-dried board will likely be covered entirely (90–100% of the covered surface) in high-mould class. It is worth noting that the contribution of palmitic acid is close to zero, which indicates the same amount of this acid on the surface of the sideboards of both types of drying. The VIP plot shows the specified variables that have the most significant impact on the separation between groups in the PLS-DA model (Fig. 7 c). During the analysis of the coefficient plots, a limitation arose that distorts the results - too large confidence intervals for most of the variables. The standard error will be more minor as the sample size of representative samples increases. However, given the small size of the analysed observations, wide confidence intervals were expected. The most influential variables in the PLS-DA model have VIP values of more than 1.0. A total of 6 variables had VIP > 1. The total extractives variable was the most influential in the PLS-DA model. Table 3 contains summarised data on all three models presented in the study. Table 3 The summarised data from PCA and PLS-DA models on drying type of Scots pine sideboards in correlation with mould growth characteristics and extractive composition from the wood surface. Type of model No.of observations No.of variables No. of components R 2 Q 2 PCA 20 20 2 0.577 0.101 PCA 19 a 20 2 0.526 0.124 PLS-DA 19 a 20 2 0.856 0.685 a AD2 observation was excluded as an outlier The total extractives content, which contains triglycerides and other lipophilic compounds in their composition, was higher on the surface of the sideboards dried in the kiln. Also, the highest content of phenolic components was found on the surface of kiln-dried sideboards. Considering that these components are insoluble (i.e. triglycerides) or appreciably (i.e. phenols) soluble in water, the evaporation and movement of capillary water during the drying process could not affect the distribution of these extractives and their concentration in the surface layers of the Scots pine sideboards. Presumably, the migration of lipophilic components to the wood surface occurs due to the pressure gradient in the thickness of the board during drying in a kiln chamber (Stehr and Johansson 2000; Myronycheva et al. 2018 ). More intensive mould growth was observed on the kiln-dried sideboards. At the same time, a significant inhibition of the mould growth of the air-dried sideboards was found. The presence of a greater amount of oleic acid, which has proven antifungal properties (Pohl et al. 2011 ; Guimaraes et al. 2022), on the air-dried wood surface contributed to this. These results are confirmed by data obtained by Sehlstedt-Persson et al. ( 2011 ). Also, the extractives from kiln-dried sideboards had high concentrations of low-molecular-weight sugars (glucose, saccharose, fructose). This can be explained by the rapid movement of water with soluble carbohydrates to the wood surface during the kiln-drying process. Heating causes rapid movement and evaporation of water from the capillaries of the wood (Karlsson et al. 2012 ). At the same time, substances dissolved in water precipitate on the cell walls as water is evaporated and deposited at the wood surface due to liquid or capillary water flow during drying (Theander et al. 1993 ). That is why extractives from kiln-dried sideboards contained higher amounts of low molecular weight sugars on wood surfaces. In addition, the sugars present in the wood after drying are used as an energy source for more intensive mould growth (Terziev et al. 1997 ). Also, a more significant amount of glycerol was detected on the surface of the kiln-dried sideboards, indicating a more intense degradation process of triglycerides during wood drying in the kiln chamber (Myronycheva et al. 2018 ). In addition, it was found that the ash content on the kiln-dried board surfaces was significantly higher than on the air-dried. The composition of ash includes inorganic components of wood. The concentration of inorganic compounds on the surface of kiln-dried sideboards is likely due to the movement of water-soluble inorganic compounds, such as potassium-based salts, along with capillary water during drying. A larger amount of nitrogen was detected on the surface of the air-dried sideboards, but this difference was not significant. The reasons for those minor differences are also a more complex question that should not be speculated based on the limited number of samples tested. The obtained results show that the method of drying Scots pine wood significantly affects the composition and distribution of extractives on the material surface and, accordingly, affects the characteristics of mould growth. Sideboards were more protected from mould growth after air-drying treatment. The kiln-drying method is often used due to the significantly shorter drying time of wood, but it decreases the resistance of Scots pine wood to fungal agents. The Scots pine wood during/or after the kiln-drying process should be additionally treated with anti-fungal agents to prevent rapid mould spread. 4 Conclusion Multivariate data analysis was used to identify the differences in mould growth features and surface extractive composition of the Scots pine sideboards between the two wood drying methods (air- and kiln-drying). This study presented two PCA and one PLS-DA model, which allowed the clustering of observations by type of wood drying to be identified. Significant differences in the composition of surface extractives and mould growth characteristics between air- and kiln-dried sideboards were found. More intense mould growth was detected on kiln-dried Scots pine sideboards than on air-dried. Higher amounts of oleic acid were found on the air-dried sideboard surfaces, presumably contributing to its resistance to mould growth. The kiln-drying method significantly affected the redistribution of wood extractives and contributed to the concentration of lipophilic compounds (total extractives) and phenols on the surface of the boards, presumably due to the pressure gradient in the thickness of the sideboard during the drying process. At the same time, water-soluble inorganic components and low-molecular-weight sugars, namely glucose, saccharose and fructose, had higher values on the surface of the kiln-dried sideboards caused by the intense movement of capillary water together with dissolved components to the wood surface. Higher amounts of low-molecular-weight sugars contributed to more intensive mould growth on the kiln-dried wood surface and proved the need for additional antifungal treatment of the wood after/during kiln-drying. Declarations Acknowledgements The authors are grateful to the Kempe Foundation and, personally, Alice Kempe for providing a 2-year fellowship to Anastasiia Postovoitova as a postdoctoral researcher at the Luleå University of Technology. The authors thank Benedikt Neyses for supporting the data analysis process. Author contributions Anastasiia Postovoitova: investigation; visualisation; writing – original draft; writing – review & editing. Olena Myronycheva: investigation; formal analysis; writing – review & editing. Olof Broman: formal analysis; writing – review & editing. Olov Karlsson: conceptualization; project administration; methodology; writing – review & editing. Funding The authors are grateful for the financial support from the Kempe Foundation and the Swedish Research Council for the Environment, Agricultural Sciences and Spatial Planning (FORMAS) projects “Experimental studies of capillary phenomena in bio-based materials” 942-2016-64, and “Fungal growth on modified wood-based products under subarctic conditions” 2017-00419. Open access funding provided by Wood Science and Engineering subject at Luleå University of Technology. Data availability The dataset obtained and analysed in this study is stored on the university servers. Access to the data is available by requesting it from the corresponding author. Ethics approval and consent to participate Not applicable Competing interests The authors declare no competing interests. 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To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ References Diouf PN, Stevanovic T, Boutin Y (2009) The effect of extraction process on polyphenol content, triterpene composition and bioactivity of yellow birch ( Betula alleghaniensis Britton) extracts. Ind Crops Prod 30(2):297–303. https://doi.org/10.1016/j.indcrop.2009.05.008 Eriksson L, Andersson PL, Johansson E, Tysklind M (2006) Megavariate analysis of environmental QSAR data. Part I – a basic framework founded on principal component analysis (PCA), partial least squares (PLS), and statistical molecular design (SMD). Mol Div 10:169–186. https://doi.org/10.1007/s11030-006-9024-6 Fengel D, Wegener G (1984) Wood: chemistry, ultrastructure, reactions. Walter de Gruyter, Berlin, New York Guimaraes A, Venancio A (2022) The Potential of Fatty Acids and Their Derivatives as Antifungal Agents: A Review. Toxins (Basel) 14(3):188–209. https://doi.org/10.3390/toxins14030188 Johnson S (2014) NIST Standard Reference Database 1A v14. NIST. https://www.nist.gov/srd/nist-standard-reference-database-1a-v14. Created 19 June 2014 Julkunen-Tiitto R (1985) Phenolic constituents in the leaves of northern willows: methods for the analysis of certain phenolics. J Agric Food Chem 33:213–217. https://doi.org/10.1021/jf00062a013 Karlsson O, Myronycheva O, Sehlstedt-Persson M, Öhman M, Sandberg D (2017) Multivariate modeling of mould growth in relation to extractives in dried Scots pine sapwood. Proceedings IRG Annual Meeting, IRG/WP 17-20629, 6 pp Karlsson O, Yang Q, Sehlstedt-Persson M, Moren T (2012) Heat treatments of high temperature dried Norway spruce sideboards: Saccharides and furfurals in sapwood surfaces. BioRes 7(2):2284–2299. https://doi.org/10.15376/biores.7.2.2284–2299 Kirker GT, Blodgett AB, Arango RA, Lebow PK, Clausen CA (2013) The role of extractives in naturally durable wood species. Int Biodeterior Biodegrad 82:53–58. https://doi.org/10.1016/j.ibiod.2013.03.007 Kjeldahl J (1883) New method for the determination of nitrogen in organic substances. Zeitschrift für analytische Chemie 22(1):366–383. https://doi.org/10.1007/BF01338151 Lai YZ (1992) Determination of phenolic hydroxyl groups. In: Lin SY, Dence CW (ed) Methods in lignin chemistry, Springer, Berlin, Heidelberg, pp 423–434. Lovaglio T, D’Auria M, Rita A, Todaro L (2017) Compositions of compounds extracted from thermo-treated wood using solvents of different polarities. iForest - Biogeosci For 10(5):824–828. https://doi.org/10.3832/ifor2360-010 Myronycheva O, Karlsson O, Sehlstedt-Persson M, Ohman M, Sandberg D (2018) Distribution of low-molecular lipophilic extractives beneath the surface of air- and kiln-dried Scots pine sapwood sideboards. PloS ONE 13(10):e0204212. https://doi.org/10.1371/journal.pone.0204212 Myronycheva O, Poohphajai F, Sehlstedt-Persson M (2019) Application of GRAS Compounds for the Control of Mould Growth on Scots Pine Sapwood Surfaces: Multivariate Modelling of Mould Grad. Forests 10:714–730. https://doi.org/10.3390/f10090714 N'Guessan JLL, Niamke BF, Yao NJC, Amusant N (2023) Wood extractives: main families, functional properties, fields of application and interest of wood waste. For Prod J 73(3):194–208. https://doi.org/10.13073/FPJ-D-23-00015 Niemz P, Teischinger A, Sandberg D (2023) Springer handbook of wood science and technology. Springer International Publishing, Cham. https://doi.org/10.1007/978-3-030-81315-4 Pettersen RC (1984) The chemical composition of wood. In: Rowell R (ed) The chemistry of solid wood, American Chemical Society, Washington, USA, pp 54–126 Platt SD, Martin CJ, Hunt SM, Lewis CW (1989) Damp housing, mould growth, and symptomatic health state. BMJ 298(6689):1673–1678. https://doi.org/10.1136/bmj.298.6689.1673 Pohl CHK, Kock JLF, Thibane VS (2011) Antifungal free fatty acids: A review. Sci Against Microb Pathog Commun Curr Res Technol Adv 1:61–71 Poohphajai F, Myronycheva O, Karlsson O et al (2023) Fungal colonisation on wood surfaces weathered at diverse climatic conditions. Heliyon 9:e17355. https://doi.org/10.1016/j.heliyon.2023.e17355 Råberg U, Edlund ML, Terziev N, Land CJ (2005) Testing and evaluation of natural durability of wood in above ground conditions in Europe – an overview. J Wood Sci 51:429–440 Santana ALBD, Maranhao CA, Santos JC et al (2010) Antitermitic activity of extractives from three Brazilian hardwoods against Nasutitermes corniger . Int Biodeterior Biodegrad 64:7–12. https://doi.org/10.1016/j.ibiod.2009.07.009 SCAN-CM 49:03 (2003) Wood chips for pulp production and pulp – Content of acetone-soluble matter. PFI Sehlstedt-Persson M, Karlsson O, Wamming T, Moren T (2011) Mold growth on sapwood sideboards exposed outdoors: the impact of wood drying. For Prod J 61:170–179. https://doi.org/10.13073/0015-7473-61.2.170 Sehlstedt-Persson M, Wamming T. (2010) Wood drying process: impact on Scots pine lumber durability. J Wood Sci 56:25–32. https://doi.org/10.1007/s10086-009-1066-9 Sheikh AA, Sehlstedt-Persson M, Moren T (2013) Mould susceptibility of Scots pine ( Pinus sylvestris L.) sapwood: Impact of drying, thermal modification, and copper-based preservative. Int Biodeterior Biodegrad 85:284–288. https://doi.org/10.1016/j.ibiod.2013.06.031 Silverio FO, Barbosa LCA, Fidencio PH et al (2011) Evaluation of chemical composition of eucalyptus wood extracts after different storage times using principal component analysis. J Wood Che Tech 31:26–41. http://doi.org/10.1080/02773811003650463 Sjostrom E (1993) Wood chemistry: Fundamentals and applications. Academic Press, San Diego Sjostrom E, Alen R (1999) Analytical methods in wood chemistry, pulping, and papermaking. Heid, Berlin SS-EN 13183–1 (2004) The moisture content of a piece of sawn timber – Part 1: Determination by oven dry method. SIS Swedish Standards Inst. https://www.sis.se/en/produkter/wood-technology/wood-sawlogs-and-sawn-timber/ssen131831ac2004/ Terziev N, Boutelje J (1998) Effect of felling time and kiln-drying on color and susceptibility of wood to mold and fungal stain during an above-ground field test. Wood Fiber Sci 30:360–367 Terziev N, Boutelje J, Larsson K (1997) Seasonal fluctuations of low-molecular-weight sugars, starch and nitrogen in sapwood of Pinus sylvestris L. Scand J For Res 12:216–224. https://doi.org/10.1080/02827589709355403 Theander O, Bjurman J, Boutelje J (1993) Increase in the content of low-molecular carbohydrates at lumber surfaces during drying and correlations with nitrogen content, yellowing and mould growth. Wood Sci Tech 27:381–389 Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 26 Aug, 2025 Read the published version in European Journal of Wood and Wood Products → Version 1 posted Editorial decision: Revision requested 05 May, 2025 Reviews received at journal 24 Apr, 2025 Reviews received at journal 16 Apr, 2025 Reviews received at journal 12 Apr, 2025 Reviewers agreed at journal 10 Apr, 2025 Reviewers agreed at journal 10 Apr, 2025 Reviewers agreed at journal 09 Apr, 2025 Reviewers agreed at journal 29 Mar, 2025 Reviewers invited by journal 28 Mar, 2025 Editor assigned by journal 28 Mar, 2025 Submission checks completed at journal 19 Mar, 2025 First submitted to journal 18 Mar, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6253804","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":431108771,"identity":"bb211809-8a06-4b76-bd99-81d63e6e2a76","order_by":0,"name":"Anastasiia Postovoitova","email":"data:image/png;base64,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","orcid":"","institution":"Luleå University of Technology","correspondingAuthor":true,"prefix":"","firstName":"Anastasiia","middleName":"","lastName":"Postovoitova","suffix":""},{"id":431108772,"identity":"684e3f3a-1769-4019-b297-e298be3a2f66","order_by":1,"name":"Olena Myronycheva","email":"","orcid":"","institution":"Luleå University of Technology","correspondingAuthor":false,"prefix":"","firstName":"Olena","middleName":"","lastName":"Myronycheva","suffix":""},{"id":431108774,"identity":"cca20297-f75f-48a0-b289-002a2bf26b61","order_by":2,"name":"Olov Broman","email":"","orcid":"","institution":"Luleå University of Technology","correspondingAuthor":false,"prefix":"","firstName":"Olov","middleName":"","lastName":"Broman","suffix":""},{"id":431108778,"identity":"56bdd8fb-335b-405b-8adb-644e0334160c","order_by":3,"name":"Olov Karlsson","email":"","orcid":"","institution":"Luleå University of Technology","correspondingAuthor":false,"prefix":"","firstName":"Olov","middleName":"","lastName":"Karlsson","suffix":""}],"badges":[],"createdAt":"2025-03-18 13:53:09","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6253804/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6253804/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s00107-025-02315-y","type":"published","date":"2025-08-26T15:58:05+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":79155870,"identity":"1849d914-a95d-4e8b-ae67-361f4a90482c","added_by":"auto","created_at":"2025-03-25 06:12:29","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":417051,"visible":true,"origin":"","legend":"\u003cp\u003eExamples of surfaces of air- (\u003cstrong\u003ea\u003c/strong\u003e) and kiln-dried (\u003cstrong\u003eb\u003c/strong\u003e) Scots pine sideboards covered by mould after a 30-day mould test. The arrows mark the mould growth area on the air-dried board. The kiln-dried board is completely covered in mould.\u003c/p\u003e","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-6253804/v1/3cf7e2d56a48eaf05af90e9b.jpeg"},{"id":79155865,"identity":"2b67aa05-2eed-4448-8a0f-ee4eacc2fa9f","added_by":"auto","created_at":"2025-03-25 06:12:28","extension":"jpeg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":98823,"visible":true,"origin":"","legend":"\u003cp\u003eThe PCA score plot (\u003cstrong\u003ea\u003c/strong\u003e) and loading plot (\u003cstrong\u003eb\u003c/strong\u003e) of component 1 and component 2 for two types of Scots pine wood drying.\u003c/p\u003e","description":"","filename":"floatimage2.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-6253804/v1/918e075a4ca657a492baa2bc.jpeg"},{"id":79155866,"identity":"c324d6bf-71b2-4215-87c0-bf8f4210727d","added_by":"auto","created_at":"2025-03-25 06:12:28","extension":"jpeg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":89703,"visible":true,"origin":"","legend":"\u003cp\u003eThe PCA score contribution plot for AD2 observation. Arrows indicate variables with extreme values. AD2 had extreme values of almost all fatty acids.\u003c/p\u003e","description":"","filename":"floatimage3.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-6253804/v1/a41d0ebbf0bd4d6677375897.jpeg"},{"id":79155868,"identity":"25a80737-fb80-4310-9112-5bb1e73e4481","added_by":"auto","created_at":"2025-03-25 06:12:29","extension":"jpeg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":115123,"visible":true,"origin":"","legend":"\u003cp\u003eThe PCA score plot (\u003cstrong\u003ea\u003c/strong\u003e) and loading plot (\u003cstrong\u003eb\u003c/strong\u003e) of component 1 and component 2 for two types of board drying \u003cstrong\u003ewithout AD2 observation\u003c/strong\u003e.\u003c/p\u003e","description":"","filename":"floatimage4.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-6253804/v1/d5a54b25740c7a75918756ed.jpeg"},{"id":79156183,"identity":"d48fff75-b208-4f7f-a09d-37d1cadd49ef","added_by":"auto","created_at":"2025-03-25 06:20:29","extension":"jpeg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":51855,"visible":true,"origin":"","legend":"\u003cp\u003eObserved (vertical) and predicted values of the PLS-DA model showing complete separation between the drying groups.\u003c/p\u003e","description":"","filename":"floatimage5.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-6253804/v1/7922ff035124b2c6b846deec.jpeg"},{"id":79156185,"identity":"0ef63430-ead1-4c3c-b18f-57d611b60d20","added_by":"auto","created_at":"2025-03-25 06:20:29","extension":"jpeg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":216948,"visible":true,"origin":"","legend":"\u003cp\u003eThe PLS-DA score plot (\u003cstrong\u003ea\u003c/strong\u003e) and loading plot (\u003cstrong\u003eb\u003c/strong\u003e) of component 1 and component 2 for two types of Scots pine board drying. $M2.DA(Air) and $M2.DA(Kiln) are the class variables in the discriminant analysis.\u003c/p\u003e","description":"","filename":"floatimage6.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-6253804/v1/e85661ddc4dc8864d6451f73.jpeg"},{"id":79155875,"identity":"4dc0878a-a653-4c94-828d-2ff27c352b4e","added_by":"auto","created_at":"2025-03-25 06:12:29","extension":"jpeg","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":178643,"visible":true,"origin":"","legend":"\u003cp\u003eThe PLS-DA coefficient plots for air- (\u003cstrong\u003ea\u003c/strong\u003e) and kiln-drying (\u003cstrong\u003eb\u003c/strong\u003e) types of Scots pine sideboards and the variable importance in projection (VIP) plot (\u003cstrong\u003ec\u003c/strong\u003e).\u003c/p\u003e","description":"","filename":"floatimage7.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-6253804/v1/4c1ba0fee0156c4598ed00bb.jpeg"},{"id":90345152,"identity":"c0f39fe6-1dff-4240-99e6-725b3619316f","added_by":"auto","created_at":"2025-09-01 16:10:11","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2068850,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6253804/v1/6e329d72-e66d-404c-9a96-d18e5605803e.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Assessment of the relationships between extractive content, mould growth, and drying methods of Scots pine wood using multivariate data analysis","fulltext":[{"header":"1 Introduction","content":"\u003cp\u003eMould growth is undesirable in wood construction because it is associated with aesthetic issues, increased maintenance costs, and poses a health hazard (Platt et al. \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e1989\u003c/span\u003e). The mould includes various species of fungi that cause wood discolouration due to the growth of their biomass on the surface. Although mould does not change the mechanical properties of wood, it is necessary to treat the material to prevent mould development through chemical and thermal wood modification or wood coating (Sheikh et al. \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Niemz et al. \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Mould growth on wood surfaces depends on many factors, such as local climate conditions (temperature, relative humidity, etc.), geographical location, fungal diversity, moisture content and extractive content of the wood (Terziev and Boutelje \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e1998\u003c/span\u003e; R\u0026aring;berg et al. \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2005\u003c/span\u003e; Poohphajai et al. \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Among these factors, the content of wood extractives demonstrates significant practical interest. In addition to cellulose, hemicelluloses, and lignin as the main structural components, wood contains various non-structural low molecular weight compounds that can be extracted using appropriate solvents (Fengel and Wegener \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e1984\u003c/span\u003e; Sjostrom \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e1993\u003c/span\u003e). The waxes, fats, terpenes and terpenoids, saturated and unsaturated fatty acids, monosaccharides and complex carbohydrates, alkanes, proteins, alkaloids, phenolic compounds and flavonoids refer to wood extractives (N'Guessan et al. \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). However, the qualitative and quantitative characteristics of the various components vary significantly in different wood materials. This is directly related to the tree species, age, geographical location, and climate conditions during its growth. Seasonal characteristics of tree cutting and wood material storage time also significantly impact extractive composition (Terziev et al. \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e1997\u003c/span\u003e; Flaviano et al. 2011). In addition, the qualitative profile of the extractive components is so unique that it allows for creating a unique \"chemical signature\" for identifying wood material through belonging to a specific family, genus and wood species (N'Guessan et al. \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). In general, extractives provide a physical and chemical barrier against wood-degrading agents. The composition of extractives affects many physical properties and, to a lesser extent, mechanical properties of wood, namely colour, odour, water permeability, durability, density and hardness, and acoustic properties (Pettersen \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e1984\u003c/span\u003e; Santana et al. \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; N'Guessan et al. \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Also, the protective properties of certain extractives against fungal, bacterial and insect agents have been proven (N'Guessan et al. \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). It was found that lignivorous organisms (fungi and termites) destroyed wood from which extractives had previously been removed much faster than unextracted wood (Kirker et al. \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). The biocidal properties of wood extractives could be used in developing preparations for preserving the natural durability of wood (Lovaglio et al. \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eSince extractives are complex mixtures, their composition can vary depending on the extraction method chosen (Diouf et al. \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2009\u003c/span\u003e) and the application of various technological operations such as drying. The wood is dried to remove water and produce a lighter, more durable and stable material. Drying together with heat treatment not only causes a change in the physical and mechanical properties of wood but also causes a change in the composition of extractives and their distribution in the wood layers (Sehlstedt-Persson et al. 2010).\u003c/p\u003e \u003cp\u003eScots pine (\u003cem\u003ePinus sylvestris\u003c/em\u003e L.) wood, as one of the main sources of wood constructions in Nordic countries, is rich in extractives, which significantly affects the final material's properties during wood processing (drying, modification, heating, etc.). Given the susceptibility of Scots pine wood to mould (Sehlstedt-Persson et al. \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Sheikh et al. \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2013\u003c/span\u003e), it was chosen for this study.\u003c/p\u003e \u003cp\u003eGiven all of the above, studying the relationships between wood pre-treatment processes, the composition of extractives and their effect on the growth of pathogenic organisms, particularly mould fungi, is a critically important issue for the wood industry and requires detailed research. Because of this, our study was conducted to assess the impact of the air-and kiln-drying methods of Scots pine wood on the composition of the selected extractives from the sideboard surfaces and the growth characteristics of mould fungi using multivariate data analysis.\u003c/p\u003e"},{"header":"2 Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Sample preparation and drying\u003c/h2\u003e \u003cp\u003eA total of 20 Scots pine sideboards were analysed. The sideboards were obtained initially from 10 Scots pine trees cut and sawn in a Sawmill in Norrbotten County (Sweden). Each board had dimensions of 25mm tangential (T) \u0026times; 100mm radial (R) \u0026times; 220mm longitudinal (L) and contained only sapwood. No permits were required for this study as no protected or endangered species were used.\u003c/p\u003e \u003cp\u003eTwo wood-drying methods were used in the study: air- and kiln-drying. Ten randomly selected Scots pine sideboards were single-stacked and dried indoors on stickers for 30 days at a temperature of 20 ℃ and RH of about 10%. The other 10 sideboards were dried in a laboratory kiln (Valutec, Sweden) with air circulation. During kiln drying, the sideboards were placed in pairs, and the sapwood sides of each pair were blown with air. This resulted in a rapid movement of water and moisture from the deep layers of the wood to the wood surface. Drying was carried out for 44 hours, including a heating phase (1.7 hours), the main drying phase (37.3 hours) and a cooling phase (5 hours). The drying temperature was 60℃ and rose to 77℃ during the drying phase (Myronycheva et al. \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). The conditioning phase was excluded from the kiln drying process to eliminate its influence on the distribution of extractive components on the board surface.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Analysis of extractive content\u003c/h2\u003e \u003cp\u003ePlaning of the surface of wooden sideboards (0.25 mm depth) from the bark side of sapwood from 10 air-dried sideboards and 10 kiln-dried sideboards was done to obtain material for extraction of lipophilic and water-soluble compounds. The planned surface wood from each board was separately milled in a planetary mill (Fritsch, Germany). The resulting material was stored at \u0026ndash; 20 ℃. The milled wood (0.5 g) was used to determine the moisture content by heating it in an oven at 103℃ according to the standard SS-EN 13183-1 (2004).\u003c/p\u003e \u003cp\u003eExtractives were extracted from 1.0 g of milled surface wood with acetone (VWR Chemicals: 20165.323) in a Soxhlet extractor as described in SCAN-CM 49:03 (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2003\u003c/span\u003e) standard method. After acetone evaporation and drying of the residue, the total extractives content was measured in mg/g of dry mass.\u003c/p\u003e \u003cp\u003eThe content of total phenols (mg/g of dry mass) was evaluated using the Folin-Ciocalteu (FC) approach (Julkunen-Tiitto \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e1985\u003c/span\u003e) with tannic acid (VWR Chemicals; 83510.260) as a standard. After adding all components to the sample, the absorption was measured after 40 minutes at 735 nm in a UV spectrophotometer (U-1500, Hitachi, Japanese).\u003c/p\u003e \u003cp\u003eSaturated (palmitic and stearic), unsaturated (oleic and linoleic) fatty acids and resin (pimaric, isopimaric, abietic and dehydroabietic) acids and glycerol were measured in the dried acetone extracts using a Gas Chromatography-Mass Spectrometry (GC-MS) system (GCMS-QP2020, Shimadzu, Japan) with A SUPELCO SLB-5 MS capillary column (30 m, 0.25 mm inner diameter, 0.25 \u0026micro;m film thickness). Before GC-MS, trimethylsilylation was done by treatment with 100 \u0026micro;l of N,O-bis-(trimethylsilyl)trifluoroacetamide (BSTFA) and 50 \u0026micro;l of trimethylsilyl chloride (TMSCl) in an oven at 70˚C for 20 minutes (Sjostrom and Alen \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e1999\u003c/span\u003e) with 1-methylnaphthalene dissolved in pyridine as internal standard (Lai \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e1992\u003c/span\u003e). The oven temperature program used a heating rate of 10 ℃/min starting from 100 ℃ (1 min at initial temperature) to 270 ℃ (holding for 2 min. at final temperature). The analysis cycle took 25 minutes, and the mass spectrum was recorded at 70 eV in 40\u0026ndash;500 m/z with a scan speed of 1000. NIST Mass Spectral Library was used to identify fatty and resin acids (Johnson 2016). Quantification was performed by comparing the target peak area with the peak area of the internal standard.\u003c/p\u003e \u003cp\u003eThe low molecular weight sugars (saccharose, glucose and fructose) in the water extracts were analysed by High-Performance Liquid Chromatography (HPLC) (Shimadzu, Japan) with Hi-plex Pb-column (250 mm length, 7.7 inner diameter, 8 \u0026micro;m particle size) (Karlsson et al. \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). Water extracts were previously made by mixing the wood with water, followed by an ultrasonic treatment for 1 hour, and then left overnight. Water extracts were filtered (50 \u0026micro;m) and analysed in HPLC at 60 ℃ using water as eluent with 0.3 mL/min flow rate. An RI detector was used to detect sugars, and quantitative values were determined by comparing them with calibration curves for target compounds.\u003c/p\u003e \u003cp\u003eThe amount of nitrogen was investigated as described in Kjeldahl (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e1883\u003c/span\u003e). The ash content was determined by thermogravimetric analysis using a hardening furnace (N7, Nabertherm, Germany). All measurements of extractive compounds are presented in mg/g of dry mass.\u003c/p\u003e \u003cp\u003eMicrosoft Excel software was used to calculate the minimum, mean, and maximum values for each variable, namely the 'MIN', 'AVERAGE', and ' MAXIMUM' functions. More detailed data are presented in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eThe minimum, mean and maximum values of extractive components obtained from air- and kiln-dried Scots pine sideboards. The data was previously reported (Karlsson et al. \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2017\u003c/span\u003e)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eName of component\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eAir-dried\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003eKiln-dried\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMinimum (mg/g)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMean\u003c/p\u003e \u003cp\u003e(mg/g)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMaximum\u003c/p\u003e \u003cp\u003e(mg/g)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMinimum\u003c/p\u003e \u003cp\u003e(mg/g)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMean\u003c/p\u003e \u003cp\u003e(mg/g)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eMaximum\u003c/p\u003e \u003cp\u003e(mg/g)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal extractives\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25.16447\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e35.94391\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e49.06973\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e41.86167\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e57.0666\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e69.70297\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePalmitic acid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.451979\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.13298\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.268747\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.254856\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOleic acid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.488388\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3.63414\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e25.05234\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.200793\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.77299\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLinoleic acid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.677081\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6.225504\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.200793\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.484073\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStearic acid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.086986\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.291703\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.903579\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.325746\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.249394\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePimaric acid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.381058\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.575837\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6.687396\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.111469\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.94274\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e3.770454\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIsopimaric acid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.282911\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.046451\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3.342869\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.102333\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.492612\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e3.132764\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDehydroabietic acid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.778021\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4.366863\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e17.61476\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.324956\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e4.549238\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e7.584099\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAbietic acid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.246364\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.813388\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4.119094\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.331476\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.854376\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2.245718\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGlycerol\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.123983\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.432197\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.054243\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.815225\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.67847\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal phenols\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.221447\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.443865\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.813221\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.006388\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.808393\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2.063208\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNitrogen\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.032927\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.381367\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.47457\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.267047\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.697599\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSaccharose\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.066026\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.086289\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.146079\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.416249\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.710012\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGlucose\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.017586\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.160287\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.467799\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.805327\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.827902\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFructose\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9.51E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.131653\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.702911\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.602831\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2.475419\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAsh\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.179372\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.329013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.439078\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.805689\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.851852\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3 Mould test\u003c/h2\u003e \u003cp\u003eTen air-dried and ten kiln-dried Scots pine sideboards were investigated in this study. Mould growth on the board surfaces was induced by the spraying of a water mixture which contained spore suspension of the five fungal species (\u003cem\u003eAspergillus niger\u003c/em\u003e van Tieghem, \u003cem\u003ePenicillum commune\u003c/em\u003e Trom, \u003cem\u003ePaecilomyces variotii\u003c/em\u003e Bainier, \u003cem\u003eMucor plumbeus\u003c/em\u003e Bonord and \u003cem\u003eTrihoderma longibrachiatum\u003c/em\u003e Rifai). All fungal cultures belong to the Division of Wood Science and Engineering collection at Lule\u0026aring; University of Technology (Skelleftea, Sweden). Fungal cultures were grown in Petri dishes (\u0026Oslash; 90 mm) using malt extract agar medium (Milipore; 70145) in the laboratory chamber (HPP260eco, Memmert, Germany) at 25 ℃ and RH of 90% for 7 days. The dilution buffer (10 mL) (0.02 M Potassium dihydrogen phosphate (VWR Chemicals; 7778.77.0), 0.05 M Disodium hydrogen phosphate dehydrate (Merck KGaA; 10028.24.7), 0.074 M Sodium chloride (Sigma Aldrich; 7647.14.5), 0.01% (v/v) Tween 80 (VWR Chemicals; 9005.65.6), 1L distilled water) was used to wash the spores from the surface of each Petri dishes separately. Spores from hyphae were removed into the dilution buffer using a sterile glass spreader. The spore suspension was filtered through sterile mineral wool to remove residual mycelium parts. The number of spores was counted using a hemocytometer, and the suspension was diluted to a concentration of 10\u003csup\u003e6\u003c/sup\u003e spores/mL. Equal volumes of spore suspensions of five fungal cultures were mixed and stored at 4 ℃ until use. The resulting suspension (2 mL) was sprayed on each Scots pine board, and sideboards were left in the laboratory chamber (HPP260eco, Memmert, Germany) at 22 ℃ and RH of 90% for 30 days.\u003c/p\u003e \u003cp\u003eImageJ (NIH, Maryland, USA) software determined the percentage of mould coverage on the board surface by image analysis of all board sides. The mould class was determined according to the method described by Myronycheva et al. (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). The spread, density, and colour intensity of mould on wood surfaces were visually assessed. Through visual assessment of all sides of the sideboards, each sample was assigned a mould growth intensity class (0\u0026ndash;6). If there was no visible mould growth, the sample was assigned class 0. In the case of the most intensive mould growth, the sample had the highest class 6.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4 Principal Component Analysis (PCA) and Partial Least-Squares Discriminant Analysis (PLS-DA)\u003c/h2\u003e \u003cp\u003eAs a result of the analysis of the composition of extractives, moisture content and the mould test, a dataset containing 20 observations and 20 variables was obtained. The SIMCA 18 (Sartorius AG, G\u0026ouml;ttingen, Germany) software package was used for PCA and PLS-DA modelling, aiming to describe the differences in mould growth features and extractive composition of the sideboard surface between the two wood drying methods (air- and kiln-drying). PCA was used to overview the correlation pattern, and PLS-DA was used to describe the sideboard characteristics for the two wood drying types. Cross-validation was used to test the robustness of the models. External validation of the models was not performed due to the small dataset limited to only 20 observations. Prior to analysis, all variables were scaled to unit variance.\u003c/p\u003e \u003c/div\u003e"},{"header":"3 Results and discussion","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\n \u003ch2\u003e3.1 Investigation of extractive content and mould growth features\u003c/h2\u003e\n \u003cp\u003eA quantitative evaluation of 16 extractive components from 10 air-dried sideboards and 10 kiln-dried Scots pine sideboards was conducted. The minimum, mean, and maximum values of each component are given in Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e. The data obtained for each wood sample were used for further multivariate analysis using PCA and PLS-DA.\u003c/p\u003e\n \u003cp\u003eExamples of mould growth on the surface of the boards after a 30-day mould test are shown in Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e. The percentage of mould surface coverage and mould class were determined by visual inspection. As seen in Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e, more intensive mould growth was detected on the surfaces of the kiln-dried boards. As many as 7 out of 10 kiln-dried samples were completely covered with mould (90\u0026ndash;100%), and 9 kiln-dried boards were assigned the highest class 6.\u003c/p\u003e\n \u003cp\u003eAt the same time, significantly less mould growth was observed on the air-dried sideboards. Half or less than half of the surface (5\u0026ndash;50%) was covered with mould for 8 out of the 10 air-dried samples analysed. The determined class for mould on the air-dried sideboards was lower than on the kiln-dried sideboards (class 4 and lower for 7 samples). The average moisture content of the sideboards after air- and kiln-drying was 4.6% and 4.4%, respectively. Detailed data for each wood sample are presented in Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e\n \u003ctable id=\"Tab2\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eThe mould area and class on air- and kiln-dried Scots pine sideboards after a 30-day mould test. The moisture content was measured before the mould test. The data was previously reported (Karlsson et al. \u003cspan class=\"CitationRef\"\u003e2017\u003c/span\u003e)\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eBoard ID\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eDrying type,\u003c/p\u003e\n \u003cp\u003e(Air/Kiln)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eMoisture,\u003c/p\u003e\n \u003cp\u003e(%)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eMould area,\u003c/p\u003e\n \u003cp\u003e(%)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eMould class\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAD1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAir\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAD2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAir\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAD3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAir\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAD4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAir\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAD5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAir\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAD6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAir\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAD7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAir\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e10.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAD8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAir\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAD9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAir\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAD10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAir\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eKD1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eKiln\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eKD2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eKiln\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eKD3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eKiln\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eKD4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eKiln\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eKD5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eKiln\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eKD6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eKiln\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eKD7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eKiln\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eKD8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eKiln\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eKD9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eKiln\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eKD10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eKiln\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\n \u003ch2\u003e3.2 Principal Component Analysis\u003c/h2\u003e\n \u003cp\u003ePCA was performed to get an overview and identify correlation patterns between the type of wood drying, the mould growth and the resulting composition of extractives on the dried wood surfaces. PCA is a linear approach that allows the visualisation of such data by creating linear combinations of the original variables onto principal components in plots and histograms. In this way, differences and similarities between samples become highlighted. The result of the PCA analysis of the entire dataset is shown in Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e\n \u003cp\u003eThe systematic variation in the dataset was summarised by two significant principal components explaining 57.7% of the total variability (\u003cem\u003eR\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e[1]\u0026thinsp;=\u0026thinsp;0.349 and \u003cem\u003eR\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e[2]\u0026thinsp;=\u0026thinsp;0.228). In general, the robustness of the model is displayed through the explained variance (\u003cem\u003eR\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e) and the cross-validated predictive ability (\u003cem\u003eQ\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e) values.\u003c/p\u003e\n \u003cp\u003eIn the score plot (Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003ea), the observations are coloured by the type of sideboard drying (air- and kiln-dried). The two drying types group well and show a difference between the surface extractive composition and mould growth dependency. The data has one clear outlier, AD2, in the score plot. The reason for AD2 being a strong outlier is seen in Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e, where its data is compared to the rest of the air-dried sideboard observations. AD2 data compared to all the other air-dried sideboards show that it has extreme values on almost all fatty and resin acids. Linoleic, oleic, pimaric, dehydroabietic and abietic acid values were considerably higher for the AD2 than for other observations in the air-dried group. The data collection procedure was followed up, but the reason for such extreme values could not be verified. Thus, it is unclear whether this strong divergent behaviour results from a measurement error or if AD2 is a unique and extreme observation. A sign of a strong outlier is when the first principal component is oriented towards the outlier and explains the difference between AD2 and the other observations. Hence, the outlier AD2 was excluded from further analysis.\u003c/p\u003e\n \u003cp\u003eA second PCA model without AD2 observation can be seen in Fig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e. The model explains 52.6% of the variations of the variables (\u003cem\u003eR\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e[1]\u0026thinsp;=\u0026thinsp;0.369 and \u003cem\u003eR\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e[2]\u0026thinsp;=\u0026thinsp;0.156). In the score plot (Fig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003ea), the observations are positioned rather well in two groups, following the type of wood drying. One air-dried sample, AD10, is more grouped within the kiln-dried type group. However, in the previous PCA model, it was also closely localised with the kiln-dried group. The grouping of observations shows a difference between the drying types regarding the chemical composition on the board surfaces in the data presented.\u003c/p\u003e\n \u003cp\u003eIn the loading plot (Fig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003eb), it can be seen that the kiln-dried samples are associated with having higher values on the variables to the right and high up in the plot. The air-dried samples show the opposite pattern, with lower values on most variables. Oleic acid is the only chemical compound that seems to be more significant for the air-dried group. A discriminant analysis of the two drying types was executed to simplify the interpretation of the results.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\n \u003ch2\u003e3.2 Partial least-squares discriminant analysis\u003c/h2\u003e\n \u003cp\u003ePLS-DA is a classification approach which allows the prediction of dependent output Y variables from input X variables (Eriksson et al. \u003cspan class=\"CitationRef\"\u003e2006\u003c/span\u003e). Qualitatively dividing groups among themselves and visualising the profile of each group by adding group labels or hidden (latent) variables is also possible by creating PLS-DA models. Creating Y hidden variables in PLS-DA models is a handy tool that simplifies the analysis of the obtained results by creating a set of coefficients for each investigated group.\u003c/p\u003e\n \u003cp\u003eHere, PLS-DA was used to determine prediction profiles of air- and kiln-dried Scots pine sideboards in relation to surface extractives after 30 days of mould growth. PLS-DA classified air- and kiln-drying types (Y variables) based on all extractive variables with mould class and mould area (X variables).\u003c/p\u003e\n \u003cp\u003eTwo components were significant, and the PLS-DA model explained 85.6% of variations in class (\u003cem\u003eR\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.856) and a predictive ability of 68.5% (\u003cem\u003eQ\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.685). The observed/predicted plot in Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e shows the correctness of the observation discrimination. All observations from the air- and kiln-dried groups were clearly separated. No observation was misclassified.\u003c/p\u003e\n \u003cp\u003eOn the score plot (Fig. 6a), a clear division of observations into two groups (air- and kiln-dried sideboards) was visualised. The two class variables can be seen in the loading plot marked $M2.DA(Air) and $M2.DA(Kiln) (Fig. 6b). They visualised the variance weight for each investigated wood drying type and separated them using the available variables data. The class variables are located on opposite sides of the plot. In particular, the air-dried type positively correlated with moisture, nitrogen, palmitic and oleic acids. All other 15 variables correlated positively with the kiln-drying type. In general, these results confirm the results obtained from the PCA model.\u003c/p\u003e\n \u003cp\u003eThe two coefficient plots for air- and kiln-drying types are shown as a visual representation of the contribution of each predictor variable to the PLS-DA classification model (Fig. \u003cspan class=\"InternalRef\"\u003e7\u003c/span\u003ea, b). The coefficients are mirrored to describe the difference between the two groups.\u003c/p\u003e\n \u003cp\u003eA typical predicted Scots pine board dried according to the air-drying method contains more oleic acid and, to some extent, more nitrogen. In our data, the air-dried samples had slightly higher moisture on the surface than the kiln-dried. The mould growth on air-dried boards is less intense (5\u0026ndash;60% of the covered surface), and the mould class is lower. A typical predicted Scots pine board dried according to the kiln-dried method is richer in total extractive and nonorganic components (ash) and contains a higher amount of phenols, low molecular weight sugars, glycerol, some fatty (stearic, linoleic) and resin (pimaric, isopimaric, abietic and dehydroabietic). After our mould test, such a kiln-dried board will likely be covered entirely (90\u0026ndash;100% of the covered surface) in high-mould class. It is worth noting that the contribution of palmitic acid is close to zero, which indicates the same amount of this acid on the surface of the sideboards of both types of drying.\u003c/p\u003e\n \u003cp\u003eThe VIP plot shows the specified variables that have the most significant impact on the separation between groups in the PLS-DA model (Fig. \u003cspan class=\"InternalRef\"\u003e7\u003c/span\u003ec). During the analysis of the coefficient plots, a limitation arose that distorts the results - too large confidence intervals for most of the variables. The standard error will be more minor as the sample size of representative samples increases. However, given the small size of the analysed observations, wide confidence intervals were expected. The most influential variables in the PLS-DA model have VIP values of more than 1.0. A total of 6 variables had VIP\u0026thinsp;\u0026gt;\u0026thinsp;1. The total extractives variable was the most influential in the PLS-DA model. Table \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e contains summarised data on all three models presented in the study.\u003c/p\u003e\n \u003cdiv align=\"left\" class=\"colspec\"\u003e\u003cbr\u003e\u003c/div\u003e\n \u003ctable id=\"Tab3\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eThe summarised data from PCA and PLS-DA models on drying type of Scots pine sideboards in correlation with mould growth characteristics and extractive composition from the wood surface.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eType of model\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eNo.of observations\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eNo.of variables\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eNo. of components\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eR\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eQ\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePCA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.577\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.101\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePCA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e19\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.526\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.124\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePLS-DA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e19\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.856\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.685\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"6\"\u003e\n \u003cp\u003e\u003csup\u003ea\u003c/sup\u003eAD2 observation was excluded as an outlier\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003cp\u003e\u003c/p\u003e\n \u003cp\u003eThe total extractives content, which contains triglycerides and other lipophilic compounds in their composition, was higher on the surface of the sideboards dried in the kiln. Also, the highest content of phenolic components was found on the surface of kiln-dried sideboards. Considering that these components are insoluble (i.e. triglycerides) or appreciably (i.e. phenols) soluble in water, the evaporation and movement of capillary water during the drying process could not affect the distribution of these extractives and their concentration in the surface layers of the Scots pine sideboards. Presumably, the migration of lipophilic components to the wood surface occurs due to the pressure gradient in the thickness of the board during drying in a kiln chamber (Stehr and Johansson 2000; Myronycheva et al. \u003cspan class=\"CitationRef\"\u003e2018\u003c/span\u003e).\u003c/p\u003e\n \u003cp\u003eMore intensive mould growth was observed on the kiln-dried sideboards. At the same time, a significant inhibition of the mould growth of the air-dried sideboards was found. The presence of a greater amount of oleic acid, which has proven antifungal properties (Pohl et al. \u003cspan class=\"CitationRef\"\u003e2011\u003c/span\u003e; Guimaraes et al. 2022), on the air-dried wood surface contributed to this. These results are confirmed by data obtained by Sehlstedt-Persson et al. (\u003cspan class=\"CitationRef\"\u003e2011\u003c/span\u003e).\u003c/p\u003e\n \u003cp\u003eAlso, the extractives from kiln-dried sideboards had high concentrations of low-molecular-weight sugars (glucose, saccharose, fructose). This can be explained by the rapid movement of water with soluble carbohydrates to the wood surface during the kiln-drying process. Heating causes rapid movement and evaporation of water from the capillaries of the wood (Karlsson et al. \u003cspan class=\"CitationRef\"\u003e2012\u003c/span\u003e). At the same time, substances dissolved in water precipitate on the cell walls as water is evaporated and deposited at the wood surface due to liquid or capillary water flow during drying (Theander et al. \u003cspan class=\"CitationRef\"\u003e1993\u003c/span\u003e). That is why extractives from kiln-dried sideboards contained higher amounts of low molecular weight sugars on wood surfaces. In addition, the sugars present in the wood after drying are used as an energy source for more intensive mould growth (Terziev et al. \u003cspan class=\"CitationRef\"\u003e1997\u003c/span\u003e).\u003c/p\u003e\n \u003cp\u003eAlso, a more significant amount of glycerol was detected on the surface of the kiln-dried sideboards, indicating a more intense degradation process of triglycerides during wood drying in the kiln chamber (Myronycheva et al. \u003cspan class=\"CitationRef\"\u003e2018\u003c/span\u003e). In addition, it was found that the ash content on the kiln-dried board surfaces was significantly higher than on the air-dried. The composition of ash includes inorganic components of wood. The concentration of inorganic compounds on the surface of kiln-dried sideboards is likely due to the movement of water-soluble inorganic compounds, such as potassium-based salts, along with capillary water during drying. A larger amount of nitrogen was detected on the surface of the air-dried sideboards, but this difference was not significant. The reasons for those minor differences are also a more complex question that should not be speculated based on the limited number of samples tested.\u003c/p\u003e\n \u003cp\u003eThe obtained results show that the method of drying Scots pine wood significantly affects the composition and distribution of extractives on the material surface and, accordingly, affects the characteristics of mould growth. Sideboards were more protected from mould growth after air-drying treatment. The kiln-drying method is often used due to the significantly shorter drying time of wood, but it decreases the resistance of Scots pine wood to fungal agents. The Scots pine wood during/or after the kiln-drying process should be additionally treated with anti-fungal agents to prevent rapid mould spread.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"4 Conclusion","content":"\u003cp\u003eMultivariate data analysis was used to identify the differences in mould growth features and surface extractive composition of the Scots pine sideboards between the two wood drying methods (air- and kiln-drying). This study presented two PCA and one PLS-DA model, which allowed the clustering of observations by type of wood drying to be identified. Significant differences in the composition of surface extractives and mould growth characteristics between air- and kiln-dried sideboards were found. More intense mould growth was detected on kiln-dried Scots pine sideboards than on air-dried. Higher amounts of oleic acid were found on the air-dried sideboard surfaces, presumably contributing to its resistance to mould growth. The kiln-drying method significantly affected the redistribution of wood extractives and contributed to the concentration of lipophilic compounds (total extractives) and phenols on the surface of the boards, presumably due to the pressure gradient in the thickness of the sideboard during the drying process. At the same time, water-soluble inorganic components and low-molecular-weight sugars, namely glucose, saccharose and fructose, had higher values on the surface of the kiln-dried sideboards caused by the intense movement of capillary water together with dissolved components to the wood surface. Higher amounts of low-molecular-weight sugars contributed to more intensive mould growth on the kiln-dried wood surface and proved the need for additional antifungal treatment of the wood after/during kiln-drying.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e The authors are grateful to the Kempe Foundation and, personally, Alice Kempe for providing a 2-year fellowship to Anastasiia Postovoitova as a postdoctoral researcher at the Lule\u0026aring; University of Technology. The authors thank Benedikt Neyses for supporting the data analysis process.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u0026nbsp;\u003c/strong\u003eAnastasiia Postovoitova: investigation; visualisation; writing \u0026ndash; original draft; writing \u0026ndash; review \u0026amp; editing. Olena Myronycheva: investigation; formal analysis; writing \u0026ndash; review \u0026amp; editing. Olof Broman:\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eformal analysis; writing \u0026ndash; review \u0026amp; editing. Olov Karlsson: conceptualization; project administration; methodology; writing \u0026ndash; review \u0026amp; editing.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eThe authors are grateful for the financial support from the Kempe Foundation and the Swedish Research Council for the Environment, Agricultural Sciences and Spatial Planning (FORMAS) projects \u0026ldquo;Experimental studies of capillary phenomena in bio-based materials\u0026rdquo; 942-2016-64, and \u0026ldquo;Fungal growth on modified wood-based products under subarctic conditions\u0026rdquo; 2017-00419.\u003c/p\u003e\n\u003cp\u003eOpen access funding provided by Wood Science and Engineering subject at\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eLule\u0026aring; University of Technology.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e The dataset obtained and analysed in this study is stored on the university servers. Access to the data is available by requesting it from the corresponding author.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e Not applicable\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u0026nbsp;\u003c/strong\u003eThe authors declare no competing interests.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eOpen Access\u003c/strong\u003e This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article\u0026rsquo;s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article\u0026rsquo;s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eDiouf PN, Stevanovic T, Boutin Y (2009) The effect of extraction process on polyphenol content, triterpene composition and bioactivity of yellow birch (\u003cem\u003eBetula\u003c/em\u003e \u003cem\u003ealleghaniensis\u003c/em\u003e Britton) extracts. Ind Crops Prod 30(2):297\u0026ndash;303. https://doi.org/10.1016/j.indcrop.2009.05.008\u003c/li\u003e\n\u003cli\u003eEriksson L, Andersson PL, Johansson E, Tysklind M (2006) Megavariate analysis of environmental QSAR data. Part I \u0026ndash; a basic framework founded on principal component analysis (PCA), partial least squares (PLS), and statistical molecular design (SMD). Mol Div 10:169\u0026ndash;186. https://doi.org/10.1007/s11030-006-9024-6\u003c/li\u003e\n\u003cli\u003eFengel D, Wegener G (1984) Wood: chemistry, ultrastructure, reactions. Walter de Gruyter, Berlin, New York\u003c/li\u003e\n\u003cli\u003eGuimaraes A, Venancio A (2022) The Potential of Fatty Acids and Their Derivatives as Antifungal Agents: A Review. Toxins (Basel) 14(3):188\u0026ndash;209. https://doi.org/10.3390/toxins14030188\u003c/li\u003e\n\u003cli\u003eJohnson S (2014) NIST Standard Reference Database 1A v14. NIST. https://www.nist.gov/srd/nist-standard-reference-database-1a-v14. Created 19 June 2014\u003c/li\u003e\n\u003cli\u003eJulkunen-Tiitto R (1985) Phenolic constituents in the leaves of northern willows: methods for the analysis of certain phenolics. J Agric Food Chem 33:213\u0026ndash;217. https://doi.org/10.1021/jf00062a013\u003c/li\u003e\n\u003cli\u003eKarlsson O, Myronycheva O, Sehlstedt-Persson M, \u0026Ouml;hman M, Sandberg D (2017) Multivariate modeling of mould growth in relation to extractives in dried Scots pine sapwood. Proceedings IRG Annual Meeting, IRG/WP 17-20629, 6 pp\u003c/li\u003e\n\u003cli\u003eKarlsson O, Yang Q, Sehlstedt-Persson M, Moren T (2012) Heat treatments of high temperature dried Norway spruce sideboards: Saccharides and furfurals in sapwood surfaces. BioRes 7(2):2284\u0026ndash;2299. https://doi.org/10.15376/biores.7.2.2284\u0026ndash;2299\u003c/li\u003e\n\u003cli\u003eKirker GT, Blodgett AB, Arango RA, Lebow PK, Clausen CA (2013) The role of extractives in naturally durable wood species. Int Biodeterior Biodegrad 82:53\u0026ndash;58. https://doi.org/10.1016/j.ibiod.2013.03.007\u003c/li\u003e\n\u003cli\u003eKjeldahl J (1883) New method for the determination of nitrogen in organic substances. Zeitschrift f\u0026uuml;r analytische Chemie 22(1):366\u0026ndash;383. https://doi.org/10.1007/BF01338151 \u003c/li\u003e\n\u003cli\u003eLai YZ (1992) Determination of phenolic hydroxyl groups. In: Lin SY, Dence CW (ed) Methods in lignin chemistry, Springer, Berlin, Heidelberg, pp 423\u0026ndash;434. \u003c/li\u003e\n\u003cli\u003eLovaglio T, D\u0026rsquo;Auria M, Rita A, Todaro L (2017) Compositions of compounds extracted from thermo-treated wood using solvents of different polarities. iForest - Biogeosci For 10(5):824\u0026ndash;828. https://doi.org/10.3832/ifor2360-010\u003c/li\u003e\n\u003cli\u003eMyronycheva O, Karlsson O, Sehlstedt-Persson M, Ohman M, Sandberg D (2018) Distribution of low-molecular lipophilic extractives beneath the surface of air- and kiln-dried Scots pine sapwood sideboards. PloS ONE 13(10):e0204212. https://doi.org/10.1371/journal.pone.0204212\u003c/li\u003e\n\u003cli\u003eMyronycheva O, Poohphajai F, Sehlstedt-Persson M (2019) Application of GRAS Compounds for the Control of Mould Growth on Scots Pine Sapwood Surfaces: Multivariate Modelling of Mould Grad. Forests 10:714\u0026ndash;730. https://doi.org/10.3390/f10090714\u003c/li\u003e\n\u003cli\u003eN\u0026apos;Guessan JLL, Niamke BF, Yao NJC, Amusant N (2023) Wood extractives: main families, functional properties, fields of application and interest of wood waste. For Prod J 73(3):194\u0026ndash;208. https://doi.org/10.13073/FPJ-D-23-00015\u003c/li\u003e\n\u003cli\u003eNiemz P, Teischinger A, Sandberg D (2023) Springer handbook of wood science and technology. Springer International Publishing, Cham. https://doi.org/10.1007/978-3-030-81315-4\u003c/li\u003e\n\u003cli\u003ePettersen RC (1984) The chemical composition of wood. In: Rowell R (ed) The chemistry of solid wood, American Chemical Society, Washington, USA, pp 54\u0026ndash;126\u003c/li\u003e\n\u003cli\u003ePlatt SD, Martin CJ, Hunt SM, Lewis CW (1989) Damp housing, mould growth, and symptomatic health state. BMJ 298(6689):1673\u0026ndash;1678. https://doi.org/10.1136/bmj.298.6689.1673\u003c/li\u003e\n\u003cli\u003ePohl CHK, Kock JLF, Thibane VS (2011) Antifungal free fatty acids: A review. Sci Against Microb Pathog Commun Curr Res Technol Adv 1:61\u0026ndash;71\u003c/li\u003e\n\u003cli\u003ePoohphajai F, Myronycheva O, Karlsson O et al (2023) Fungal colonisation on wood surfaces weathered at diverse climatic conditions. Heliyon 9:e17355. https://doi.org/10.1016/j.heliyon.2023.e17355\u003c/li\u003e\n\u003cli\u003eR\u0026aring;berg U, Edlund ML, Terziev N, Land CJ (2005) Testing and evaluation of natural durability of wood in above ground conditions in Europe \u0026ndash; an overview. J Wood Sci 51:429\u0026ndash;440\u003c/li\u003e\n\u003cli\u003eSantana ALBD, Maranhao CA, Santos JC et al (2010) Antitermitic activity of extractives from three Brazilian hardwoods against \u003cem\u003eNasutitermes corniger\u003c/em\u003e. Int Biodeterior Biodegrad 64:7\u0026ndash;12. https://doi.org/10.1016/j.ibiod.2009.07.009\u003c/li\u003e\n\u003cli\u003eSCAN-CM 49:03 (2003) Wood chips for pulp production and pulp \u0026ndash; Content of acetone-soluble matter. PFI \u003c/li\u003e\n\u003cli\u003eSehlstedt-Persson M, Karlsson O, Wamming T, Moren T (2011) Mold growth on sapwood sideboards exposed outdoors: the impact of wood drying. For Prod J 61:170\u0026ndash;179. https://doi.org/10.13073/0015-7473-61.2.170\u003c/li\u003e\n\u003cli\u003eSehlstedt-Persson M, Wamming T. (2010) Wood drying process: impact on Scots pine lumber durability. J Wood Sci 56:25\u0026ndash;32. https://doi.org/10.1007/s10086-009-1066-9\u003c/li\u003e\n\u003cli\u003eSheikh AA, Sehlstedt-Persson M, Moren T (2013) Mould susceptibility of Scots pine (\u003cem\u003ePinus sylvestris\u003c/em\u003e L.) sapwood: Impact of drying, thermal modification, and copper-based preservative. Int Biodeterior Biodegrad 85:284\u0026ndash;288. https://doi.org/10.1016/j.ibiod.2013.06.031\u003c/li\u003e\n\u003cli\u003eSilverio FO, Barbosa LCA, Fidencio PH et al (2011) Evaluation of chemical composition of eucalyptus wood extracts after different storage times using principal component analysis. J Wood Che Tech 31:26\u0026ndash;41. http://doi.org/10.1080/02773811003650463\u003c/li\u003e\n\u003cli\u003eSjostrom E (1993) Wood chemistry: Fundamentals and applications. Academic Press, San Diego\u003c/li\u003e\n\u003cli\u003eSjostrom E, Alen R (1999) Analytical methods in wood chemistry, pulping, and papermaking. Heid, Berlin\u003c/li\u003e\n\u003cli\u003eSS-EN 13183\u0026ndash;1 (2004) The moisture content of a piece of sawn timber \u0026ndash; Part 1: Determination by oven dry method. SIS Swedish Standards Inst. https://www.sis.se/en/produkter/wood-technology/wood-sawlogs-and-sawn-timber/ssen131831ac2004/\u003c/li\u003e\n\u003cli\u003eTerziev N, Boutelje J (1998) Effect of felling time and kiln-drying on color and susceptibility of wood to mold and fungal stain during an above-ground field test. Wood Fiber Sci 30:360\u0026ndash;367\u003c/li\u003e\n\u003cli\u003eTerziev N, Boutelje J, Larsson K (1997) Seasonal fluctuations of low-molecular-weight sugars, starch and nitrogen in sapwood of \u003cem\u003ePinus sylvestris\u003c/em\u003e L. Scand J For Res 12:216\u0026ndash;224. https://doi.org/10.1080/02827589709355403\u003c/li\u003e\n\u003cli\u003eTheander O, Bjurman J, Boutelje J (1993) Increase in the content of low-molecular carbohydrates at lumber surfaces during drying and correlations with nitrogen content, yellowing and mould growth. Wood Sci Tech 27:381\u0026ndash;389\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"european-journal-of-wood-and-wood-products","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"harw","sideBox":"Learn more about [European Journal of Wood and Wood Products](http://link.springer.com/journal/107)","snPcode":"107","submissionUrl":"https://submission.nature.com/new-submission/107/3","title":"European Journal of Wood and Wood Products","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Wood, drying type, extractives, mould, multivariate analysis","lastPublishedDoi":"10.21203/rs.3.rs-6253804/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6253804/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eWooden construction material is a sustainable contribution to carbon sequestration and long-term storage. Despite its strength, sustainability, and versatility, the vulnerability to biodeterioration is an issue. Therefore, this study aimed to identify the differences in mould growth features and surface extractive composition of the Scots pine (\u003cem\u003ePinus sylvestris\u003c/em\u003e L.) sapwood sideboards between the air- and kiln-drying methods using multivariate data analysis. Air and kiln-dried sideboards were used to extract different low molecular compounds from the surface layer, assess the moisture content, and conduct a mould test. Principal component analysis revealed grouping for the drying types of the sideboards. This was confirmed by partial least-squares discriminant analysis, which allowed the sideboard characteristics of two wood drying types to be described. An outlier was detected among the air-dried observations. More intensive mould growth was detected on kiln-dried Scots pine sideboards than on air-dried. A higher amount of total lipophilic compounds, phenols and inorganic components were found on the kiln-dried sideboard surface. The surface extractives from kiln-dried sideboards contained a higher amount of almost all analysed fatty and resin acids, except for the oleic acid, the amount of which prevailed precisely on the air-dried sideboard surface. Low-molecular-weight sugars, namely glucose, saccharose and fructose, were present in significant amounts on the surface of the kiln-dried sideboards. This is presumably contributed to the rapid spread of mould. In general, multivariate modelling allowed to establish that the method of wood drying significantly influenced the redistribution of extractive components on the surface and the subsequent mould growth.\u003c/p\u003e","manuscriptTitle":"Assessment of the relationships between extractive content, mould growth, and drying methods of Scots pine wood using multivariate data analysis","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-03-25 06:12:24","doi":"10.21203/rs.3.rs-6253804/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-05-05T16:24:07+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-04-24T21:11:00+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-04-16T09:41:47+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-04-12T14:07:56+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"171188819298366283961232853790582337031","date":"2025-04-10T16:01:53+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"258508411380403434540668443852162932376","date":"2025-04-10T07:26:22+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"165450200457974244132282717377468663200","date":"2025-04-09T06:58:03+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"53613767748752445881705533673267661520","date":"2025-03-29T12:13:09+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-03-28T10:50:08+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-03-28T10:39:12+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-03-19T14:25:22+00:00","index":"","fulltext":""},{"type":"submitted","content":"European Journal of Wood and Wood Products","date":"2025-03-18T13:39:46+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"european-journal-of-wood-and-wood-products","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"harw","sideBox":"Learn more about [European Journal of Wood and Wood Products](http://link.springer.com/journal/107)","snPcode":"107","submissionUrl":"https://submission.nature.com/new-submission/107/3","title":"European Journal of Wood and Wood Products","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"19a8ec9c-1c89-42ab-a569-ef226f877a4d","owner":[],"postedDate":"March 25th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-09-01T16:07:35+00:00","versionOfRecord":{"articleIdentity":"rs-6253804","link":"https://doi.org/10.1007/s00107-025-02315-y","journal":{"identity":"european-journal-of-wood-and-wood-products","isVorOnly":false,"title":"European Journal of Wood and Wood Products"},"publishedOn":"2025-08-26 15:58:05","publishedOnDateReadable":"August 26th, 2025"},"versionCreatedAt":"2025-03-25 06:12:24","video":"","vorDoi":"10.1007/s00107-025-02315-y","vorDoiUrl":"https://doi.org/10.1007/s00107-025-02315-y","workflowStages":[]},"version":"v1","identity":"rs-6253804","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6253804","identity":"rs-6253804","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}