1 Introduction
Global climatic changes and a growing population call for the increased production of renewable energy. It is estimated that by 2050, around 10–40% of the world’s primary energy consumption could be covered by woody biomass [
1,
2]. Wood lignocellulose, such as in forest residues, is a potential source of advanced biofuels such as second-generation ethanol. However, the high lignin content in wood (about 20–35% of dry mass) limits enzymatic hydrolysis of cellulose for the production of ethanol [
3]. The development of pretreatment technologies, including physical, chemical and biological methods, aimed at reducing biomass recalcitrance to improve enzymatic saccharification of cellulose, for an eventual industrial production of bioethanol, has been a focus of intense academic research in the last two decades [
4].
Biological pretreatment using lignin-degrading microorganisms, mainly white-rot fungi, has received research attention due to its low energy input, reduced formation of inhibitors and environmental friendliness [
5,
6]. During white-rot fungus growth on woody substrates, lignin is degraded by the oxidoreductases, such as laccases and peroxidases, and used for mycelium formation. This results in a significant decrease of the lignin content and in changes in some physical and biochemical characteristics of the substrate, which improves the efficiency of enzymatic hydrolysis of cellulose [
7].
In spite of the interest within academic research, unless it is combined with other methods [
8], biological pretreatment is not yet viable for industrial implementation, due to its slow rate [
9] and the partial consumption of carbohydrates by pretreatment microorganisms [
10]. A novel concept for biological pretreatment that deserves attention is based on the cultivation of edible white-rot fungi on woody substrates, and shiitake (
Lentinula edodes (Berk.) Pegler) has been revealed as a promising model species [
11]. Although this novel biological pretreatment strategy is still time-consuming and associated with carbohydrate losses, the drawback can be compensated by the co-production of high value-added edible mushrooms. Shiitake is an edible white-rot mushroom that is becoming increasingly popular on the global market because of its flavour, high nutritional content and health-promoting and medicinal properties [
12]. Our previous research has revealed that the spent mushroom substrate (SMS) resulting from harvesting shiitake fruiting bodies on woody biomass is a cellulose-enriched material with a low lignin content and enhanced enzymatic digestibility [
11]. Pretreatment of woody biomass by shiitake cultivation is also effective in improving anaerobic digestion for biomethane production [
13]. However, it is still unclear whether and how cellulose consumption can be reduced while obtaining a high degradation of lignin and a good mushroom yield.
Global shiitake production amounts to 7.5 million tons per year, which corresponds to 22% of the global mushroom market [
14]. It is estimated that around 4–5 kg SMS are generated per kilogram of mushroom harvested [
15]. This suggests a great potential to integrate shiitake and biofuel production, provided that the cellulose that remained in the SMS is efficiently saccharified and converted to ethanol. Different mushroom producers may use different biomass mixtures for the substrates [
16], which may result in differences in lignocellulose degradation and enzymatic digestibility of the spent substrates. An understanding of how the degradation of lignocellulose components during cultivation and the susceptibility of the spent substrate to enzymatic hydrolysis are affected by initial substrate composition is a prerequisite for the further development of a process combining mushroom production and biological pretreatment for lignocellulose bioconversion to ethanol.
Bark constitutes around 10–25% of the dry mass (DM) of a tree stem depending on the species, growing conditions and anatomical part [
17]; for birch, it can be 13–20% in correlation with stems/shoot diameters. It is often a major by-product of sawmills where stemwood is processed. Bark typically has lower carbohydrate contents but higher contents of lignin, extractives and ash than stemwood [
18]. Although the antioxidant and antimicrobial properties detected in bark extractives may inhibit mycelium growth [
19,
20], bark still contains nutrients (minerals) and carbohydrates [
21,
22]. However, due to its higher lignin content (33% DM) compared with stemwood (23% DM), based on our pilot analysis, it might be included as an additive to substrates only within a certain percentage range. However, the inclusion of bark in the substrate formulation for shiitake production based on the nutrient-supplemented woodchip method and the effect of initial lignocellulose fractions on changes in substrate composition and the enzymatic convertibility of SMS cellulose have rarely been addressed in the literature.
Nitrogen supplementation is considered a key factor in substrate formulation for industrial mushroom cultivation. Supplying nitrogen of good quantity and bioavailability has been an important topic for both research and industrial practice for mushroom production [
23], and the effects may vary with the ratio and source (protein and non-protein nitrogen). The activity of the enzymes involved in lignin degradation may be affected differently [
24,
25], probably depending on the bioavailable nitrogen and carbon concentrations. Since the mechanism behind that phenomenon is not yet well understood, additional research is needed to clarify whether the differences in initial substrate composition may have an effect.
This study aimed at a further development of our novel fungal pretreatment process to delignify lignocellulose by cultivation of edible mushrooms on forest residues [
11]. The focus of this study was on how substrate formulation could affect the efficiency of substrate delignification and mushroom production, and our hypothesis was that the nitrogen and bark additions in the substrate were important factors for process optimisation. A factorial experiment was designed to investigate the effects of bark and nitrogen addition on (i) mushroom production on a birch-based substrate, (ii) degradation of lignocellulosic components, and (iii) enzymatic digestibility of cellulose contained in the SMS. The potential use of non-protein versus protein nitrogen resources was also evaluated.
2 Materials and methods
2.1 Substrate materials
White birch (
Betula pubescens) was used as a model species for major substrate material based on our previous study [
11]. Birch is frequently found among early forest thinning residues and remains underutilised in the northern hemisphere [
26]. Birch trees with a breast diameter of 4–12 cm were freshly harvested from a natural forest area in Vännäs, Sweden, in October 2017. The main stems were split into stemwood and bark by manual debarking. Stemwood and bark were then chipped with an Edsbyhuggen chipper (
Edsbyhuggen AB, Sweden) to a particle size of 15–20 mm, dried at 45 °C and ground to < 4 and < 5 mm, respectively (Table
1). Wheat (
Triticum aestivum) bran and barley (
Hordeum vulgare) grain were supplied by a Swedish food and fodder company (Lantmännen). Whey powder (Whey-100, HSNG AB, Sweden), urea and ammonium nitrate (Sigma-Aldrich) were used as nitrogen additives.
Table 1
Substrate ingredients and chemical composition
Birch stemwood (< 4 mm) | 5.0 | 0.3 | 49.8 | 6.1 | 0.1 | 243.5 | 37.2 | 19.9 | 22.8 | 4.46 |
Birch bark (< 5 mm) | 4.8 | 2.2 | 56.0 | 6.7 | 0.5 | 152.5 | 16.2 | 12.3 | 33.0 | 22.1 |
Barley grain (< 8 mm) | 5.9 | 2.1 | 45.7 | 6.0 | 1.6 | 668.6 | 55.3 | 4.4 | 6.7 | 20.4 |
Wheat bran (< 3 mm) | 5.9 | 5.7 | 46.5 | 6.1 | 2.6 | 238.5 | 18.0 | 14.9 | 12.5 | 32.6 |
Whey (< 0.2 mm) | 4.6 | – | – | – | 13.9 | – | | | | |
2.2 Experimental design and treatments
A central composite face (CCF) design with two independent factors (bark and nitrogen addition to substrate) was used, each of them at three levels. Three replicated centre points were included, resulting in a total of 11 treatments (Table
2). Each treatment was replicated four times.
Table 2
Experimental design and fractions of substrate ingredients (% of DM). Bark and whey fractions are the design factors. Total carbon (C) and total nitrogen (N) were used to calculate the C/N ratio
N 1 | 0 | 0 | 80 | 10 | 10 | 0.51 | 97.0 |
N 2 | 0 | 1 | 79 | 10 | 10 | 0.64 | 75.4 |
N 3 | 0 | 2 | 78 | 10 | 10 | 0.78 | 61.5 |
N 4 | 10 | 0 | 70 | 10 | 10 | 0.55 | 90.5 |
N 5-1 | 10 | 1 | 69 | 10 | 10 | 0.69 | 71.6 |
N 5-2 | 10 | 1 | 69 | 10 | 10 | 0.69 | 71.6 |
N 5-3 | 10 | 1 | 69 | 10 | 10 | 0.69 | 71.6 |
N 6 | 10 | 2 | 68 | 10 | 10 | 0.83 | 59.0 |
N 7 | 20 | 0 | 60 | 10 | 10 | 0.59 | 85.0 |
N 8 | 20 | 1 | 59 | 10 | 10 | 0.73 | 68.2 |
N 9 | 20 | 2 | 58 | 10 | 10 | 0.87 | 56.8 |
To examine the effects of nitrogen on mushroom growth and lignocellulose degradation in different substrates, the treatments were arranged so that the nitrogen content was expected to range from 0.51 to 0.87%, but the total carbon content was around 50% of the DM. Three types of nitrogen additive were studied in three separate experiments: whey (0, 1, 2%), urea (0, 0.5, 1%) and ammonium-nitrate (1, 2, 3%). The doses of nitrogen additive were chosen based on the nitrogen contents of all substrate ingredients; thus, each of the three doses of nitrogen addition should have a similar C/N ratio, regardless of the type of nitrogen source. The bark added had a higher lignin content than stemwood, and thus, the designed addition of bark from 0 to 20% should form a gradient from a low to a high ratio of lignin to total carbohydrates in the substrates. It is understood that the range of bark doses also represents different assortments from stemwood (0% bark) to whole trees or branches with bark [
17].
2.3 Substrate preparation and shiitake cultivation
The substrates were prepared by mixing all ingredients according to Table
2; subsequently, water was added to adjust the moisture content of the substrate to 65%, which is a usual industrial practice. The pH was adjusted to around 6.5 by adding 1% CaCO
3 based on substrate DM.
The moisturised substrate was packed into transparent polypropylene microcontainers (125 × 65 × 80 mm) which were sealed by a lid equipped with microporous filters for gas exchange and biofiltration (Microsac,
http://saco2.com/). Each container was filled with 200 g wet substrate (70 g on DM) and then pasteurised immediately in an oven at 85 °C for 4 h in the same way as in a previous study [
11]. After that, the containers were left overnight in the oven to cool down to room temperature before inoculation.
Inoculation was done manually under a sterile hood. Each substrate container was inoculated with 5 g of shiitake spawn M3790 (2.5% of wet mass) (Mycelia BVBA
http://www.mycelia.be/). After that, the containers were incubated under controlled conditions at around 22 °C and 70% relative humidity in the dark in a climate chamber. When the entire block was fully covered with mycelia, the colonisation period was considered complete. When the mushroom fruit bodies emerged, the plastic lid was removed, the temperature was lowered to 18 °C, humidity was increased to 90% and some light (about 500 lx) was induced in the climate chamber until the harvest was completed.
2.4 Mushroom harvest and yield
According to the current standard practice in most European mushroom industries, only one harvest (first flush) of fruit bodies was conducted. The fruit bodies were harvested manually and then dried at 45 °C for 96 h to determine the DM. The date of harvesting was registered for each individual container. Yield was calculated as the weight of fresh fruit bodies (90% water) divided by the DM of the initial substrate for each container and expressed as grams of fresh fruit body per kilogram of dry substrate.
2.5 Substrate sampling
Sampling was performed for initial (day 1, before pasteurisation) and spent substrates (day 65–80, immediately after mushroom harvest). Whenever sampling was carried out, the entire substrate block from each container was manually collected as one sample. The substrate samples were dried at 45 °C for 96 h, milled to ≤ 0.5 mm and stored in airtight plastic bags at room temperature prior to further analyses.
2.6 Chemical analysis
Prior to chemical analysis, the replicated samples of each treatment were pooled into a single grand sample containing equal proportions (20% by weight) of each replicate. Initial substrates and SMS were used for wet chemical analysis with two replicates.
The chemical composition of initial substrates and SMS was determined using standard procedures for wood analysis. The extractive content was determined by successive extraction with water and ethanol according to an NREL protocol [
27]. The structural components were determined by analytical acid hydrolysis followed by quantitation of the sugars and lignin [
28]. Glucose and xylose in the hydrolysates were analysed via HPLC (Shimadzu, Kyoto, Japan), using a Shodex NH
2P-50 4E column and an RI detector operating at 50 °C. As the mobile phase, we used HPLC-grade acetonitrile, supplied at a flow rate of 1.0 mL/min. Klason lignin was determined gravimetrically as the solid residue remaining after analytical acid hydrolysis, while for acid-soluble lignin contained in the analytical acid hydrolysate, spectrophotometric determination at 240 nm (Shimadzu, Kyoto, Japan) was used. Total nitrogen and total carbon contents were determined using an elemental analyzer-isotope ratio mass spectrometer (DeltaV, Thermo Fisher Scientific, Germany). A SensION PH31 pH meter was used to determine pH values, following the method described in [
11].
2.7 Mass degradation of components
The mass degradation of major lignocellulose components from the initial mass could then be calculated using the following equation:
$$ \mathrm{Relative}\ \mathrm{mass}\ \mathrm{degradation}\ \left(\%\right)=\left[1\hbox{--} \left(\mathrm{MSMS}\ast \mathrm{CSMS}/\mathrm{MINI}\ast \mathrm{CINI}\right)\right]\ast 100, $$
where M and C refer to mass and content of component (cellulose, hemicellulose or lignin) of SMS and initial (INI) substrates, respectively. All data are based on dry mass.
2.8 Enzymatic hydrolysis
Analytical enzymatic saccharification [
29] was used for determining the enzymatic susceptibility of cellulose contained in the initial substrates and in the SMS. For each sample, 50 mg DM was suspended in 900 μL of 50 mM sodium citrate buffer (pH 5.2) in 2.0-mL Eppendorf tubes. The tubes containing the reaction mixture were placed in an Ecotron orbital incubator (INFORS HT, Bottmingen, Switzerland) at 45 °C and 170 rpm for 1 h for mixing and attemperation. After that, 6 μL of Cellic CTec2, an enzyme blend containing cellulases, β-glucosidases and hemicellulases, acquired from Sigma-Aldrich Chemie GmbH (Steinheim, Germany), was added. The final enzyme activity in the reaction mixture was 100 CMCase units per gram of biomass. After adding the enzyme blend, the tubes containing the reaction mixture were incubated for 72 h under the above-stated conditions. At the end of the hydrolysis, the tubes were centrifuged; the supernatant was stored frozen at − 18 °C until further analyses, and the precipitate was discarded. Glucose in the supernatants was analysed by HPLC and used for calculating the enzymatic convertibility of cellulose.
2.9 Statistical analysis
Multiple linear regression (MLR) was used to model the relationship between the response variables and the independent factors as well as the factor-to-factor interactions. Modelling and statistical evaluation were performed using the MODDE 11.0 software (Umetrics AB, Umeå, Sweden). The MLR models were evaluated using the coefficients of determination (R2 and Q2), which explained the goodness of fit and the predictive ability of the model; R2 and Q2 values close to 1 indicate that the model fits the data very well. For each response, a model including all the independent factors and their interactions was created. Terms showing no significant effect on the target response variable (p > 0.05) were excluded from the model to obtain optimised R2 and Q2 values, and the model was considered reliable. Principal components analysis (PCA) was used to examine the relations and relative importance of the compositional variables of SMS. The data matrix of compositional variables (11 × 7) was analysed by PCA using SIMCA 14.0 (Umetrics AB, Umeå, Sweden) after mean-centring.
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