**Optimized Bioproduction of Itaconic and Fumaric Acids Based on Solid-State Fermentation of Lignocellulosic Biomass**

#### **Amparo Jiménez-Quero 1,2 , Eric Pollet 1 , Luc Avérous 1,\* and Vincent Phalip 1,3**

Received: 9 January 2020; Accepted: 25 February 2020; Published: 27 February 2020

**Abstract:** The bioproduction of high-value chemicals such as itaconic and fumaric acids (IA and FA, respectively) from renewable resources via solid-state fermentation (SSF) represents an alternative to the current bioprocesses of submerged fermentation using refined sugars. Both acids are excellent platform chemicals with a wide range of applications in different market, such as plastics, coating, or cosmetics. The use of lignocellulosic biomass instead of food resources (starch or grains) in the frame of a sustainable development for IA and FA bioproduction is of prime importance. Filamentous fungi, especially belonging to the *Aspergillus* genus, have shown a great capacity to produce these organic dicarboxylic acids. This study attempts to develop and optimize the SSF conditions with lignocellulosic biomasses using *A. terreus* and *A. oryzae* to produce IA and FA. First, a kinetic study of SSF was performed with non-food resources (wheat bran and corn cobs) and a panel of pH and moisture conditions was studied during fermentation. Next, a new process using an enzymatic cocktail simultaneously with SSF was investigated in order to facilitate the use of the biomass as microbial substrate. Finally, a large-scale fermentation process was developed for SSF using corn cobs with *A. oryzae*; this specific condition showed the best yield in acid production. The yields achieved were 0.05 mg of IA and 0.16 mg of FA per gram of biomass after 48 h. These values currently represent the highest reported productions for SSF from raw lignocellulosic biomass.

**Keywords:** lignocellulosic biomass; solid-state fermentation; enzymatic hydrolysis; aerated bioreactor; *Aspergillus oryzae*

### **1. Introduction**

Solid-state fermentation (SSF) has emerged in the last decades as a promising industrial process for several products, especially using agricultural byproducts as the substrates [1,2]. SSF involves the growth of a microorganism on solid particles in the quasi absence of free water, and the majority of processes are performed by filamentous fungi under aerobic conditions [3]. The substrates used in SSF are often the source of nutrients for the microorganisms, and the inter-particle spaces allow gas and nutrients exchange between fungal hyphae and the medium. Fungi also behave as biocatalysts for the bioconversion of the substrates into specific target products such as bio-based fuels, commodity chemicals, enzymes, bioactive compounds, or food products [4].

SSF offers several advantages compared to submerged fermentation (SmF) such as high volumetric productivity, product concentration, simpler and smaller bioreactors because of the minimal free water, a lower sterilization cost, less generation of effluents (reduced cost of effluent treatment), and easier aeration due to lower density of the corresponding medium with high porosity [5,6]. Finally, the conditions of SSF mimic the natural environments of the filamentous fungi. However, the SSF process is slower compared to SmF, and all fermentation conditions cannot be controlled precisely. The main factors affecting fungal growth and metabolism in SSF are the selection of a suitable microorganism and substrate for the targeted generation of products, the pre-treatment of the substrate, the moisture, the temperature, and the removal of metabolic heat and gas transfers [7].

One of the most interesting biotechnological applications of SSF is the production of commodity chemicals [8,9]. The biosynthesis of chemicals from biomass creates a sustainable alternative to the conventional chemical synthesis based on fossil resources [10,11]. In the last two decades, many molecules produced from biomass with a large range of applications have been described [12,13]. Many of these building blocks are organic acids because of their capacities to generate high-value products for widespread industries such as food, pharmaceuticals or polymers [14–16]. The biosynthesis of by filamentous fungi has been studied extensively, and *Aspergilli* are often used for industrial production [17].

Among the organic acids, fumaric and itaconic acids (FA and IA, respectively) are included on the DOE's (Unites State Department of Energy) list as part of the top twelve biomass-derived platform chemicals [12]. Both acids are polyfunctional building blocks that can be polymerized for instance, to give homo- or co-polymers for applications in textile, chemical, and pharmaceutical industries. IA can be used to replace acrylic acid, an important and rather costly chemical that is non-renewable so far, while FA can be used as food additive and in psoriasis treatment [14,16]. These acids are part of the tricarboxylic acid (TCA) cycle, FA being a direct intermediate in the cycle and IA a derivate of cis-aconitate acid, and both are produced under aerobic conditions. Currently, the industrial production of FA is via catalytic isomerization of fossil-based maleic acid. However, FA could also be produced biologically as an intermediate of the TCA cycle that is present in most aerobic organisms. Laboratory-scale fermentations with *Rhizopus oryzae* have shown interesting productivities in SmF of lignocellulosic biomass, around 0.35 g/g corn straw [18,19]. IA is produced industrially by *Aspergillus terreus* in SmF with glucose as the principal carbon and energy source to a yield of 100 g/L [20–22]. The biosynthesis involves the action of the cis-aconitate decarboxylase (CAD) enzyme to transform the cis-aconitate into itaconate. The presence of CAD in *A. terreus* has been demonstrated in different studies, but this enzyme is also present in another Aspergillus species; *A. oryzae* [23,24]. This aerobic, filamentous fungus is frequently used in SSF processes due to its capacity to hydrolyze the lignocellulosic substrates by enzymatic degradation [25]. Nevertheless, the production of IA and FA by SSF with lignocellulosic biomass has not been studied extensively in the literature. A method of SSF using sugarcane pressmud as a support for IA production, which yielded 0.0003 g kg−1 h −1 , was patented in 2001 [26]. In this case, the main carbon source for the acid production has been added as liquid medium and the remaining sucrose for the sugarcane was a supplementary source. A maximum productivity of 0.021 g kg−1 h −1 of FA was reported via SSF of corn distiller grains by *R. oryzae* [27]. In a previous study, we have shown the capacity of *A. terreus* and *A. oryzae* to produce both acids by SSF process [28,29]. The yields obtained by *A. oryzae* from corn cobs were the most interesting, with 0.05 and 0.18 mg acid/g biomass of IA and FA, respectively. As expected, both productivities were lower than values reported from SmF processes utilizing soluble sugars in liquid media.

The aim of this work was to optimize the bioproduction of IA and FA in SSF by two *Aspergillus* species (*A. terreus* and *A. oryzae*) using lignocellulosic biomass as a non-food carbon source (wheat bran and corn cobs). As it is a complex and recalcitrant structure, lignocellulosic biomass is often predigested to be used as a sugar source for fermentation [30]. The bioconversion is carried out by enzymes produced under specific conditions by many microorganisms [31]. This saccharification process requires several hydrolytic enzymes such as cellulases, hemicellulases, xylanases, etc. [32]. The biomass pretreatment is one of the most expensive part of the lignocellulosic material conversion in an industrial scale. Therefore, the process could be coupled with the fermentation in a simultaneous saccharification–fermentation

step, in order to improve the process yields. The study of this simultaneous process can open the possibility to decrease cost and time for an industrial activity in future. Several factors were studied to enhance organic acid production yields (pH, moisture content, enzyme hydrolysis) and large-scale fermentations were tested using these optimized factors.

#### **2. Results**

#### *2.1. Solid-State Fermentation Kinetics*

Fermentations were performed for both fungal species using both biomasses, wheat bran, and corn cobs. Organic acid production and fungal growth were studied. The determination of protein secretion level showed that *A. terreus* and *A. oryzae* present different development trends on wheat bran and corn cobs, Figure 1. The growth of *A. oryzae* on wheat bran reached a plateau after 120 h whereas *A. terreus* grew more slowly and regularly for more than 200 h on both substrates. Both species grew better on wheat bran than on corn cobs, as reported before in our previous studies, where both fungi species were capable of producing higher amounts of hydrolytic enzymes on wheat bran biomass [28,29]. These results were also confirmed by visual observations. More FA was produced from wheat bran with 0.8 and 0.6 mg/g biomass for *A. terreus* and *A. oryzae*, respectively, at the end of the fermentation with a regular increase in the yields. On corn cobs, FA production displayed a completely different profile, with a maximum yield after 48 h (0.14 and 0.12 mg/g for *A. terreus* and *A. oryzae*, respectively) and then a regular decrease.

**Figure 1.** Fermentation kinetics on lignocellulosic biomasses: itaconic acid (IA) and fumaric acid (FA) yields and protein production (fungal growth) from wheat bran (**A**,**C**) and corn cobs (**B**,**D**) by *A. terreus* (**A** and **B**, respectively) and by *A. oryzae* (**C** and **D**, respectively).

Although the fungal growth was significantly higher on wheat bran, IA was produced only on corn cobs for both fungi, Figure 1. The different composition of both biomasses [28] may explain this behavior. A maximum IA yield of 0.025 mg/g corn cobs was produced by *A. oryzae* at 168 h of fermentation. At the same fermentation time, *A. terreus* produced half of this amount (0.012 mg IA/g biomass). The fungal biomass of *A. oryzae* was 15 times lower on corn cobs than on wheat bran and almost 2.5 times lower than the one of *A. terreus* on corn cobs.

### *2.2. Optimization of the SSF Steps*

After testing the fermentations with both biomasses and fungi, the optimization steps were performed in two different ways. Firstly, a study with varying pH and humidity levels was carried out with corn cobs, to further improve the IA production. Secondly, an optimization of *A. oryzae* fermentation (displaying the highest IA production yield) was performed both on wheat bran and corn cobs by adding an enzyme cocktail to better hydrolyze the lignocellulosic biomasses. That could allow a more efficient conversion of accessible fermentable sugars in order to increase the yield of the fermentation products.

#### 2.2.1. Effect of pH and Moisture Level

Optimum pH and moisture level are crucial factors in SSF processes to obtain maximum yields of the products of interest [6,33]. The initial and previously tested conditions for corn cob fermentation (Section 2.1.) were pH 5 for the inoculation and 90% humidity. To optimize the pH and moisture conditions, five different pH values and five different moisture levels were evaluated for the inoculation step of the biomass culture, Figure 2 and Figure S1 in Supplementary Materials.

**Figure 2.** Solid-state fermentation (SSF) on corn cobs at different pH and moisture levels by *A. terreus* (IA and FA yields: **A** and **B**, respectively) and *A. oryzae* (**C** and **D**, respectively).

For *A. terreus,* both acids were produced with higher yields at pH 6, as reported before [28,34]. The moisture content influenced the IA and FA production differently. The best IA production, 0.025 mg IA/g corn cobs, was observed at pH 6 and 130% humidity (Figure 2A) i.e., a doubling of the production compared to the initial conditions (pH 5 and 90% humidity). FA was produced at a yield of 0.095 mg/g biomass (pH 6 and 70% humidity), which is also almost twice the production at initial conditions (Figure 2B). For both acids, a clear trend is that a neutral pH (pH = 7) seems too high (Figure 2A,B). This observation is in good agreement with previous results obtained for SmF [31].

*A. oryzae* also showed a preference for pH 6, for the production of both acids (Figure 2C,D). In the case of IA, the highest yield was 0.045 mg/g biomass at 110% humidity (Figure 2C), which is slightly higher than the yield under the initial conditions (0.039 mg IA/g biomass) and almost twice the yield obtained with *A. terreus.* Under the same conditions (pH 6, 110% humidity), 0.091 mg FA/g was produced (Figure 2D). It is not the highest yield since at 130% humidity, the production was even higher (0.111 mg/g biomass).

#### 2.2.2. Enzymatic Hydrolysis

The enzymatic cocktail was obtained by SSF of wheat bran by *A. oryzae*, as shown in previous studies [29], the solid fermentation of the biomass allows to produce higher protein content with specific lignocellulolytic enzymes for biomass degradation. The cocktail can be store at −20 ◦C and used for simultaneous SSF.

The enzyme cocktail produced by *A. oryzae* showed the best enzymatic activity for endoxylanases (Table 1), which are responsible for hemicellulose hydrolysis. Hemicellulose is the most abundant part of corn cobs [35,36]. Moreover, cellulase and xyloglucanase activities were also found, suggesting an efficient biomass digestion. When the enzymatic cocktail was used for simultaneous saccharification-fermentation of corn cobs, *A. oryzae* rapidly secreted proteins (i.e., it grew) in the first 20 h, and a plateau was subsequently reached (Figure 3B) approximately at the same level as with the raw biomass (Figure 1D). Surprisingly, with the treated wheat bran (Figure 3A), the fungi secreted half of the proteins compared to the untreated biomass (Figure 1C). Moreover, the treatment had a dramatic negative effect on the production of FA from wheat bran (Figure 3A) with a yield (0.08 mg/g biomass) almost 8 times lower than without pretreatment (0.6 mg/g of biomass) (Figure 1C). In contrast, for corn cobs, the FA yield was feebly increased to 0.15 mg/g biomass. The profile of FA production from corn cobs (Figure 3B) was similar to the one without the enzyme cocktail (Figure 1D) with a yield reaching a maximum (after ca. 50 h) followed by a decay.

**Table 1.** Enzymatic activities (in ∆OD/g\*min\*) of the enzymatic cocktail obtained from SSF of wheat bran by *A. oryzae*.

Enzyme activities were expressed in arbitrary units corresponding to optical density variations (∆OD) per minute and per gram of biomass, due to the unknown extinction coefficient of AZCL substrate (Megazymes, Ireland).

**Figure 3.** Kinetics of simultaneous saccharification and fermentation of wheat bran (**A**) and corn cobs (**B**) by *A. oryzae*.

The best contribution of the enzyme cocktail was observed for the production of IA. According to our knowledge, the use of such enzymatic cocktail allowing IA production from wheat bran was reported for the first time in this study. IA production was detectable after 22 h, and a maximum yield of 0.046 mg/g biomass was obtained after 66 h (Figure 3A). With corn cobs, IA production is clearly detected earlier (14 h), and a yield of 0.052 mg/g biomass was achieved (Figure 3B) that was twice the maximum yield produced without enzymatic treatment for optimized pH and moisture level, Figure 2C.

### *2.3. Kinetics of SSF with Optimized Conditions*

According to previous results, the optimum fermentative process was 80 h at pH 6 and 110% humidity. Figure 4 presents the glass flasks and shows the development of *A. oryzae* through the fermentation (with a green color indicating a high spore concentration). The fungus grew progressively during the fermentation until 0.22 mg of protein/g of biomass was obtained, as shown earlier (at pH 5 and 90% moisture level) at the same time of fermentation (Section 2.2.1). In relatively good agreement, FA production was only slightly enhanced (+ 10%) with a maximum yield of 0.16 mg/g biomass within 48 h (Figure 4). However, for IA, the enhancement was higher because the production was more than doubled (0.051 mg/g biomass) after 48 h and higher (0.061 mg/g) after 80 h (factor 2.4). As generally described for fungi, *A. oryzae* metabolism is greatly influenced by pH and the humidity level at the start of the fermentation step [37,38].

**Figure 4.** Kinetics of SSF on corn cobs by *A. oryzae* under optimized conditions (pH 6 and 110% moisture).

## *2.4. Larger Scale Fermentation*

To develop and analyze the scaling up, the fermentation was performed with 200 g of corn cobs i.e., 20 times more than for the previous glass flasks experiments. The optimized conditions of pH and moisture (i.e., 110% moisture and pH = 6) were applied for the scaled-up fermentation. Aeration plays an important role in SSF for the transfer of oxygen and the evacuation of the carbon dioxide produced. Aeration is also used (Figure 5) to dissipate the metabolic heat generated by fermentation [39]. The mixture of substrates (solid lignocellulose particles and fungal mycelium) also helps to equilibrate the gas exchange, temperature, and moisture level [3], avoiding the disruption of the mycelial-substrate contact, which is particularly important for *A. oryzae*, for instance, to produce the degrading enzymes to hydrolyze the biomass.

**Figure 5.**  Prior to autoclaving (middle), corn cobs were introduced as well as the air and humidification tubes (autoclavable tubes in PVC used for the liquid bioreactor). Right: Operative fermenter with aeration and the inoculum to be injected.

Two different processes were used to test the influence of both aeration and mixing. A monolayer reactor presenting the same conditions as the glass flasks except for size was compared with an aerated plastic bag fermenter. The plastic bag fermenter was gently mixed on a rocker shaker and distilled water was added in a timely manner to equilibrate the moisture level. The fungal growth was clearly different between the two fermenters (Figure 6). The aerated plastic bag yielded nearly twice the proteins concentration (0.26 mg/g biomass) as the monolayer fermenter (0.15 mg/g biomass) at the end of the fermentation. Compared with the glass flask fermentation (0.22 mg protein/g biomass, Figure 4) the monolayer fermenter produced less protein whereas the aerated one displayed an amount of protein similar to the small-scale fermentation. This difference in fungal growth was also obvious in observing *A. oryzae* sporulation, which occurred earlier for the monolayer fermenter (until the second fermentation day) than for the aerated fermenter. This premature sporulation indicates that mycelial development was interrupted by inadequate conditions. The aeration and the loss of humidity correction increased the fungal development and also delayed the sporulation.

**Figure 6.** SSF in larger scale fermenters of *A. oryzae* from corn cobs: Organic acid productions and protein secretion (growth).

The FA production was not affected by the different conditions (0.09 mg/g biomass in both reactors), probably because 96 h of fermentation was not an optimized time to recover FA as shown in the glass flask (Figure 4) where the maximum FA yield was produced at 36 h. Conversely, IA production was 60% higher in the aerated fermenter (Figure 6) than in the monolayer reactor.

#### **3. Discussion**

From the SSF kinetics experiments, we can conclude that IA production was inversely linked to growth. Both acid yields were lower than the yields from the current SmF [31–33], then the optimization of the fermentative conditions is necessary to enhance the acid production. During the optimization steps, we could observe how low moisture content causes slower enzyme secretion from the fungus due to the lower solubility of the nutrients and the low level of growth [37,38] (Figure S2 in Supplementary Materials). However, acidic pH (3–5) and low moisture often allowed better production of the acids (Figure 2B,D). This behavior is not observed at higher pHs. These observations are in agreement with the fact that in SSF, pH variation significantly impacts the production and the stability of the enzymes [5,39], with several enzymes responsible for biomass hydrolysis during growth. The pH effect on the organic acid production was in accordance with the simultaneous fermentation and enzymatic hydrolysis study performed previously [29]. Even if the enzymatic cocktail did not improve the growth of the fungus nor FA production, the cocktail created better conditions to produce IA. FA is an intermediate metabolite of fungal fermentation, and its production is directly linked with the development of the microorganism unlike IA, a secondary metabolite [34]. The time lag between growth and IA production is perfectly consistent with a secondary metabolite behavior. These results showed the importance of a separated optimization of FA and IA production, as well as the time of recovery of the carboxylic acids during the fermentation, especially from a continuous production perspective.

The acid yields for the simultaneous saccharification and fermentation process were higher in comparison with the best results obtained for optimized pH and moisture (pH = 6 and 110% humidity) with corn cobs and *A. oryzae, (*Figure 2C,D). However, the production of the enzyme cocktail required four additional days for the entire process. Therefore, the most interesting strategy for the acid production was the kinetic fermentation of corn cob biomass by *A. oryzae* with the optimized conditions of pH and humidity. The kinetic curves showed the differential production over time for both acids, leaving the possibility to improve and optimize the time production of the acids if focusing exclusively on one of them. In this case, the pH and the moisture should be adapted from the previous results (Figure 2 and Figure S1 in Supplementary Materials).

The literature is deficient concerning SSF of FA and IA without biomass pretreatment. For IA, a mutant of *A. terreus* displays a productivity of 0.0003 mg/g h with sugarcane pressmud supplemented with sugars and nutrients [26]. The result obtained in this study was more than two times higher (0.00076 mg/g h) by *A. oryzae* (novel IA producer) with a lignocellulosic substrate without any nutrient addition [29]. Our study can contribute to further optimization on the fermentation conditions (pH, humidity, and aeration level), that combined with new studies using metabolic engineered microorganisms [40,41] providing better yields in IA production from lignocellulosic materials.

Regarding the larger scale fermentation in the plastic bag prototype reactor, the improvement in acid production could be explained by the better supply of oxygen and moisture in the fermenter. Indeed, IA fermentation is strictly aerobic, and previous studies showed that a gain in dissolved oxygen and agitation induced higher yields [42,43]. The moisture level could affect the IA production. Below 70% humidity, the nutrient transfers are limited, and the metabolism is affected [44]. In our experiment, water addition along with aeration may allow better fermentation conditions of the air-solids-water to enhance IA production. Most of these factors were studied for *A. terreus*, long known as an IA producer. However, for *A. oryzae*, conditions still need further optimization. Even if the IA yield obtained in the aerated fermenter (0.05 mg/g biomass) was similar to the small glass flask, the final production was multiplied by 20. Of course, the yields obtained in this work are still far from the industrial scale target, and further work in optimizing the fermentation conditions and down-stream processing have to be carried out. Anyway, *A. oryzae*, which showed the most interesting enzymes production for biomass degradation, seems to be an excellent candidate for further studies.

#### **4. Materials and Methods**

#### *4.1. Feedstock and Microorganisms*

Two agricultural waste biomasses used as non-food carbon sources were wheat bran and corn cobs obtained from Comptoir Agricole (Lauterbourg, France). The lignocellulosic material was milled (SX 100, Retsch) to obtain particles that were 0.5–1 mm in size. The water activity (Aw) was measured on 1 g of dry substrate by an Aw meter Fast-lab (GBX, France).

*A. terreus* (DSM 826) was provided by the Deutsche Sammlung von Mikroorganismen und Zellkulturen (DSMZ, Braunschweig, Germany). *A. oryzae* (UMIP 1042.72) was provided by the Fungal Culture Collection of the Pasteur Institute (France). The strains were revived on potato dextrose broth medium (PDB) for 5–6 days at 25 ◦C. The microorganisms were then grown and sporulated on potato dextrose agar (PDA). The spore suspensions were harvested from 5–6-day-old PDA plates with 0.2% (*v*/*v*) Tween-80. The spores were counted using a Malassez counting chamber and stored at −20 ◦C.

#### *4.2. Initial SSF Step*

In glass flasks, 5 g of solid substrate were autoclaved at 121 ◦C and 3 bars, for 20 min. The substrates were inoculated with spore suspensions to have an initial concentration of 106 spores/g of substrate. Initial moisture was adjusted to 120% for wheat bran and 90% for corn cobs (both corresponding to an Aw near 1). After thorough mixing, the flasks were covered with a porous adhesive film (VWR, Radnor, PA, USA) and incubated at 30 ◦C for 6 days. Unless specified otherwise, these fermentation conditions were maintained throughout the study. All the experiments were conducted in duplicate. After fermentation, the samples were recovered by mixing the fermented substrate with sterilized distilled water (7 mL/g of initial dry substrate). The preparations were centrifuged (8000× *g* for 15 min) to eliminate residual solids. Then, another centrifugation step was performed on the supernatants to remove mycelia and spores (13,600× *g* for 30 min). The resulting solution was finally filtered through a 0.2 µm membrane. The samples were analyzed by high-performance liquid chromatography (HPLC, Waters, Milford, MA, USA) and were stored at −20 ◦C for additional analysis.

#### 4.2.1. pH and Humidity Level Optimization

The initial pH and humidity levels were varied to screen the best conditions for organic acid production. Citrate-phosphate buffer solutions, pH 3 to 7, were prepared. The moisture content was set at 50, 70, 90, 110, and 130 *v*/*w*. Five pH conditions were crossed with five relative humidity level, generating 25 different conditions performed with biological duplicates in SSF.

#### 4.2.2. Enzyme Production for Biomass Hydrolysis

The enzymatic cocktail preparation was performed in a plate with 250 g of wheat bran by *A. oryzae*. The inocula were prepared with 300 mL of Tris buffer at pH 10 to achieve a final spore concentration of 106 per g of biomass, and the incubation temperature was 25 ◦C during the 4 days. The enzymatic cocktail was recovered with 1500 mL of sodium phosphate buffer at pH 6 and filtered with a Vivaflow 200 system (Sartorius, Göttingen, Germany). The cocktail was stored at 4 ◦C, and enzyme activities were determined.

#### *4.3. Scale-Up Steps*

Fermentation at a higher scale, with 200 g of biomass, was performed in two different types of reactor. A monolayer reactor consists of a glass plate covered with a gas exchange Miracloth film (Millipore, Temecula, CA, USA). The second reactor is a prototype of an aerated reactor (Figure 5). This fermenter was made from an autoclaved polypropylene laboratory bag with a central opening covered with a gas exchange film of Miracloth. Two PVC tubes were introduced and connected to stone ceramic air diffusers (3 mm in diameter). Another PVC tube was added for inoculation and

double distilled water addition. The entire reactor was autoclaved with the biomass inside. During fermentation, double distilled water was added at the rate of 11 mL per day to keep the moisture constant (considering 10% evaporation/day). The aeration was provided by an air pump AC-9906 (Resun, Shenzhen, China) at a flow rate of 840 L/hour. A rocker mixer (ThermoFisher, Waltham, MA, USA) was used to shake the fermenter in order to uniformly add the water to the biomass. The influence of these controlled conditions of air and moisture content on the acid production could be studied for the plastic bag reactor but not for the monolayer reactor.

#### *4.4. Analytical Procedure*

#### 4.4.1. Mycelial Growth (Protein Assays)

To determine the fungal proteins produced during the fermentation, Bradford method was used [45]. All the samples were centrifuged and filtered (0.22 µm) before analysis to eliminate the spores. The protein assay was calibrated using BSA (bovine serum albumin) as the standard.

#### 4.4.2. Organic Acid Assays

A chromatographic system based on a 616 pump, a 2996 photodiode array detector operating in a range of 200 to 450 nm, and a 717 Plus autosampler (Waters, Milford, MA, USA) controlled by Empower 2 software (Waters, Milford, MA, USA) was used to analyze the samples, as previously described [29]. The columns were calibrated using commercial IA and FA samples with a 99.9% purity (Sigma-Aldrich, San Luis, MO, USA) and a UV measurement at 205 nm. Each sample was supplemented with 10 ppm IA or FA as the internal standard to confirm the acid production.

#### 4.4.3. Enzyme Activity Assay

Chromogenic substrates, azurine-crosslinked (AZCL) polysaccharides such as AZCL-HE-cellulose, AZCL-xylan, AZCL-xyloglucan, or AZCL-amylose (Megazyme, Bray, Ireland), were used to measure the enzyme cocktail activity. The samples were collected and analyzed as previously described [28], by spectrophotometry determining absorbance of the supernatant at 595 nm that corresponds with the solubilization of dyed compounds (AZCL) by the enzymes present in the cocktail.

### **5. Conclusions**

The IA production process appears to be ideally amenable to SSF conditions, as demonstrated in this work. However, the fermentation conditions still need further optimization to provide yields similar to the yields obtained by submerged fermentation, considering the use of lignocellulosic substrates. Additionally, the use of a novel species, *A. oryzae* (which is used industrially for enzyme production) opens up the possibility of creating a biorefinery process for the production of both organic acids and enzymes. The use of agricultural wastes and cheap and non-food substrates in the bioprocess could lower IA production costs and could therefore promote the use of bio-based IA in the polymerization process to replace petroleum-derived polymers. Furthermore, the simultaneous production of another organic acid as FA by *Aspergillus* species can open the possibility to adapt the use of different lignocellulosic biomass for particular building blocks production. Moreover, in the case of downstream purification processes for both IA and FA, the opportunity of co-polymerization could be an interesting case of study. Anyway, the results showed that time production as well as the fungi needs can differ between IA or FA production, and specific individual optimization for SSF should also be done. Moreover, further studies need to be performed in the use of commercial enzymatic cocktails to improve the production yields, but also to understand the need for better biomass hydrolysis in SSF. In this sense, *A. oryzae* seem to be a great candidate for commercial enzymes production. One possibility could be the use of metabolic engineering to guaranty the strong lignocellulolytic enzyme release combined with specific metabolic route for IA or FA, exclusively. In this work, the organic acids yields were slightly lower than those obtained in previous studies. However, the global time-lapse of the process was greatly decreased considering that no previous pretreatment steps were preformed, or enzymatic cocktails were collected.

**Supplementary Materials:** The following are available online. Figure S1. SSF on corn cobs at different pH and moisture levels by *A. terreus* and *A. oryzae*; Figure S2. Fungal growth (proteins productions) under different pH and moisture conditions.

**Author Contributions:** Conceived and designed the experiments, all authors; performed the experiments, A.J.-Q.; analyzed and interpreted the data, all authors; wrote the paper. All authors have read and agreed to the published version of the manuscript.

**Funding:** This work has received funding from the European Union's 7th Framework Program under grant agreement n◦311815 (SYNPOL Project).

**Conflicts of Interest:** The authors declare no conflict of interest.

## **References**

**Sample Availability:** Not available.

© 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).

**Aleksandra Wawro \* , Jolanta Batog and Weronika Gieparda**

Institute of Natural Fibres and Medicinal Plants, National Research Institute, Wojska Polskiego 71B, 60-630 Poznan, Poland<EMAIL_ADDRESS>(J.B<EMAIL_ADDRESS>(W.G.) **\*** Correspondence<EMAIL_ADDRESS>Tel.: +48-61-84-55-814

**Abstract:** Nowadays, more and more attention is paid to the development and the intensification of the use of renewable energy sources. Hemp might be an alternative plant for bioenergy production. In this paper, four varieties of Polish industrial hemp (Białobrzeskie, Tygra, Henola, and Rajan) were investigated in order to determine which of them are the most advantageous raw materials for the effective production of bioethanol. At the beginning, physical and chemical pretreatment of hemp biomass was carried out. It was found that the most effective is the alkaline treatment with 2% NaOH, and the biomasses of the two varieties were selected for next stages of research: Tygra and Rajan. Hemp biomass before and after pretreatment was analyzed by FTIR and SEM, which confirmed the effectiveness of the pretreatment. Next, an enzymatic hydrolysis process was carried out on the previously selected parameters using the response surface methodology. Subsequently, the two approaches were analyzed: separated hydrolysis and fermentation (SHF) and a simultaneous saccharification and fermentation (SSF) process. For Tygra biomass in the SHF process, the ethanol concentration was 10.5 g·L −1 (3.04 m3 ·ha−1 ), and for Rajan biomass at the SSF process, the ethanol concentration was 7.5 g·L −1 (2.23 m3 ·ha−1 ). In conclusion, the biomass of Polish varieties of hemp, i.e., Tygra and Rajan, was found to be an interesting and promising raw material for bioethanol production.

**Keywords:** hemp biomass; alkaline pretreatment; SEM; FTIR; response surface methodology; SHF; SSF; bioethanol

#### **1. Introduction**

The European Union countries have been obliged to achieve a certain share of biofuels in transport and to take measures to reduce greenhouse gas emissions. It is, therefore, necessary to replace diesel and gasoline with biofuels which are produced from lignocellulosic raw materials and represent an advantageous option for the fuels currently in use due to their renewable nature and the emission of an acceptable quality exhaust gases. Currently, mainly three biofuels are produced: bioethanol, biodiesel, and biogas. According to the EU RED II directive, the contributions of advanced biofuels and biogas produced from raw materials listed in Annex IX, part A to this directive, including lignocellulosic feedstocks as a share of final energy consumption in the transport sector are expected to be at least: 0.2% in 2022, 1% in 2025, and 3.5% in 2030 [1]. The production of biofuels from plant biomass is innovative and contributes to the solution of the key issue in the production of biofuels for transport fuels.

In Poland, high expectations are associated with plant biomass due to a significant amount of waste, including that from agri-food sector and the available acreage of agricultural land that can be used for the cultivation of energy crops. In recent years, there has been an increase in the acreage of cultivated industrial hemp (*Cannabis sativa* L.) in Poland (over 1000 ha). The cultivation of hemp for seed purposes is intensively developed, and there is unused hemp biomass in the field, which can be a suitable raw material for

**Citation:** Wawro, A.; Batog, J.; Gieparda, W. Polish Varieties of Industrial Hemp and Their Utilisation in the Efficient Production of Lignocellulosic Ethanol. *Molecules* **2021**, *26*, 6467. https://doi.org/ 10.3390/molecules26216467

Academic Editors: Alejandro Rodriguez Pascual, Eduardo Espinosa Víctor and Carlos Martín

Received: 10 June 2021 Accepted: 21 October 2021 Published: 26 October 2021

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**Copyright:** © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).

the production of lignocellulosic ethanol. Hemp is an environmentally friendly plant characterized by a short vegetation period (3–4 months), a rapid growth up to 4 m in height, and a dry matter yield up to 15 Mg·ha−1 . These plants improve soil quality and are useful for the remediation of degraded land (e.g., in the region of lignite mine). Hemp is also extremely resistant, perfectly adapts to various climatic conditions, is resistant to various pests, requires a slight number of pesticide treatments, and the cultivation of 1 ha of hemp in one season absorbs approximately 11 Mg of CO2 from the atmosphere [2–4].

The dry matter yields of these hemp varieties described in this study were as follows: Białobrzeskie 8–10 Mg·ha−1 , Tygra 8–11 Mg·ha−1 , Henola 7–8 Mg·ha−1 , and Rajan 9–12 Mg·ha−1 . Based on the data from 2016 (the own research of the Institute of Natural Fibres and Medicinal Plants—National Research Institute), it was estimated that, in Poland, the acreage of devastated and degraded land requiring reclamation and constituting a potential area for hemp cultivation for energy purposes amounts to approximately 65,000 ha. In the INF&MP-NRI, the Hemp Program is carried out, the aim of which is to develop hemp cultivation for seed reproduction. As part of this program, cultivation acreage is significantly increasing every year: 420 ha in 2018, 1000 ha in 2019, and 2000 ha in 2020.

The use of hemp waste straw for the production of lignocellulosic ethanol is beneficial for the environment, as it results in a rational management of bio-waste. The straw remaining after the ginning of the hemp panicles is not suitable for textile purposes, but it can be used, e.g., as a raw material for the production of bioethanol. Additionally, the dynamic growth of the hemp cultivation acreage in Poland may significantly contribute to increasing the efficiency process of obtaining bioethanol.

The process of plant biomass conversion to lignocellulosic ethanol includes several stages, from the preparation of plant material (effective pretreatment), through enzymatic hydrolysis, i.e., the decomposition of polysaccharides into fermentable sugars (the selection of effective enzymatic preparations) and to ethanol fermentation (the selection of appropriate microorganisms). The production of bioethanol from lignocellulosic raw material consists of the deconstruction of cell walls into individual polymers and the hydrolysis of carbohydrates into simple sugars. Currently, one of the main challenges is to increase the efficiency of the fermentation of organic substrates, and alternative solutions that directly affect the quantity and the quality composition of the final product are still being researched.

Hemp biomass as a lignocellulosic raw material contains a polymer complex, i.e., lignocellulose, which is relatively resistant to biodegradation. It is found in cell walls and consists of cellulose, hemicelluloses, and lignin. Cellulose and hemicelluloses are potential substrates in the fermentation process, while lignin adversely affects the conversion of hemp biomass. This necessitates the use of the pretreatment of biomass, the purpose of which is to fragmentate the solid phase and loosen the compact structure of lignocellulose. Recent advances in biomass pretreatment can be found in the review article by Bing et al. [5]. The second important stage in the process of obtaining bioethanol from hemp biomass is enzymatic hydrolysis, which determines the amount of simple sugars metabolized by yeast in the fermentation process. The hydrolysis process can be carried out as the SHF process—separate hydrolysis and fermentation (enzymes operate at 50–60 ◦C)—or the SSF (process of simultaneous saccharification and fermentation), where enzymes must be adapted to the conditions of the fermentation process, i.e., 30–40 ◦C. The last stage in the process of hemp biomass conversion is the ethanol fermentation of the obtained hydrolysates. A method that combines cellulose hydrolysis with sugar fermentation in one bioreactor seems to be more effective and economical [6–11].

The aim of the presented study was to indicate which of the four Polish varieties of industrial hemp (Białobrzeskie, Tygra, Henola, and Rajan) are the most suitable raw materials for the effective production of lignocellulosic ethanol. Thus far, no literature has been published about the possibility of using these Polish varieties of hemp as a raw material in the process of obtaining bioethanol.

#### **2. Results and Discussion**

#### *2.1. Hemp Biomass Preparation*

The hemp biomass of the four varieties (Białobrzeskie, Tygra, Henola, and Rajan) was first cut into fragments up to 1 cm in size and then was comminuted by the knife mill for mesh sizes of 2 and 4 mm. In order to choose the most favorable fractions, the content of reducing sugars released during an enzymatic test was determined. It was found that the highest values of reducing sugars were obtained for fractions up to 2 mm, and two varieties, Tygra and Białobrzeskie, showed higher sugar values for the tested fractions compared to Rajan and Henola (Table 1).

**Table 1.** The amount of reducing sugars (mg·g −1 ) released after an enzymatic test depending on the fraction size.

#### *2.2. Alkaline Pretreatment*

The purpose of chemical pretreatment is removing lignin from materials with lignocelullose and increasing the accessibility of biomass structure. The type of a reagent used has a significant effect on the performance of the chemical pretreatment. Sodium hydroxide is one of the most popular alkaline reagents used in this process.

The optimization of the concentration of sodium hydroxide used in alkaline treatment for the four varieties of hemp biomass was carried out based on the amount of reducing sugars released after the enzymatic test. Concentrations ranging from 1.5% to 3% were tested (Table 2). It was found that, for Tygra and Białobrzeskie varieties, for 2% NaOH, the amount of released reducing sugars was about 13% higher than for 1.5%. In turn, for 3% sodium hydroxide, the content of reducing sugars was at a similar level. For Henola and Rajan varieties, a completely different correlation was observed; the lowest level of released reducing sugars was noted for the concentration of 3% NaOH, while, at the concentration of 2%, the content of reducing sugars was the highest. Moreover, it was noted that two of the varieties, i.e., Tygra and Rajan, were characterized by over 10% higher content of reducing sugars than Białobrzeskie and Henola, which proves that these are the varieties more susceptible to the alkaline pretreatment. Based on the obtained results, the concentration of sodium hydroxide at the level of 2% was selected for further research. Kumar et al. [12] conducted similar research and stated that the sodium hydroxide pretreatment of lignocellulosic biomass resulted in the highest level of delignification at 2% NaOH. In turn, Zhao et al. [10], in the research on the use of American industrial hemp for the production of bioethanol, used the alkaline treatment of 1% NaOH.

**Table 2.** The amount of reducing sugars (mg·g −1 ) released after an enzymatic test depending on the NaOH concentration.

Efficient pretreatment should decrystallize cellulose, depolymerize hemicelluloses, reduce the formation of inhibitors that hinder carbohydrate hydrolysis, require low energy expenditure, and recover value-added products such as lignin.

To confirm the efficiency of the alkaline treatment, the determination of the chemical composition of hemp biomass after NaOH treatment was performed and compared to the chemical composition of the biomass before pretreatment. The results are presented in Table 3.

**Variety Samples Cellulose (%) Hemicelluloses (%) Lignin (%)** Białobrzeskie BP 50.10 ± 0.18 32.10 ± 0.22 15.40 ± 0.03 AP 61.46 ± 0.37 21.59 ± 0.06 15.12 ± 0.16 Tygra BP 50.82 ± 0.12 27.79 ± 0.33 14.68 ± 0.46 AP 62.70 ± 0.09 20.16 ± 0.16 15.12 ± 0.22 Henola BP 46.82 ± 0.04 29.94 ± 0.45 15.48 ± 0.17 AP 57.62 ± 0.08 20.33 ± 0.22 17.80 ± 0.06 Rajan BP 48.69 ± 0.39 31.43 ± 0.04 16.72 ± 0.08 AP 59.30 ± 0.33 19.91 ± 0.25 18.40 ± 0.18

**Table 3.** The chemical composition of hemp biomass (percentage of dry matter); BP: before pretreatment; AP: after pretreatment.

The analysis of the chemical composition of the hemp biomass before and after treatment showed that, in all the four varieties, the alkaline treatment resulted in a visible increase in the cellulose content (by approximately 10%) and the partial degradation of hemicelluloses (as much as 12% for the Rajan variety). The highest content of cellulose after treatment was found in the following varieties: Tygra, Białobrzeskie, and Rajan, and its level was approximately 60%. In the case of the lignin content, only for the Białobrzeskie hemp biomass, a very slight reduction was observed after the alkaline pretreatment. In the case of the remaining varieties, the tendency was contrary. Similar observations were reported by Stevulova et al. [13], who examined the chemical composition of hemp biomass before and after the pretreatment with sodium hydroxide and proved that the content of lignin after the pretreatment was 7% higher than before.

At this stage, due to better properties, availability, and higher yield, only two types of biomass of the Tygra and the Rajan varieties were selected, for which further research on bioethanol production was continued.

The effect of the alkaline treatment on Tygra and Rajan hemp biomass was also confirmed by Fourier transform infrared spectrometer (FTIR) shown in Figure 1a,b and by scanning electron microscopy (SEM) shown in Figure 2.

An effective method for studying the structure of biomass after alkaline treatment is FT-IR [14]. Figure 1a,b show the changes in FTIR spectra after the alkali treatment of hemp biomass between 600 cm−1 and 4000 cm−1 . On the spectra of both varieties, typical vibration bands in the cellulose molecule were observed at 3300 cm−1 , 2900 cm−1 , and 1610 cm−1 . The broad band in the 3600–3100 cm−1 region, which was due to the OH stretching vibration, gave considerable information concerning the hydrogen bonds. The peaks characteristic of hydrogen bonds from the spectra of the Rajan variety AP became a little sharper and more intense compared to the Rajan variety BP. However, in the case of the Tygra variety, this band was less intense. The 2900 cm−1 peak corresponding to the C–H stretching vibration in the case of the Tygra variety shifted to higher wavenumber values and slightly decreased in the intensity. These changes could have resulted from both the increased amount of cellulose after the treatment (2.2, Table 3) and the reduced cellulose crystallinity [15,16]. The band at 1610 cm−1 from the stretching vibrations of the O–H bonds, due to the adsorbed water in the sample, decreased, especially for the Rajan variety, which could be attributed to water loss due to drying the sample [17]. The intensities of peaks at 1160−1170 cm−1 (asymmetric C−O−C stretching from cellulose) and 1110−1120 cm−1 (C−OH skeletal vibration in cellulose) increased after pretreatment in both types of biomass. Furthermore, the intensity at 1050−1060 cm−1 (C−O−C pyranose ring skeletal vibration ascribed to cellulose) also increased slightly after alkali pretreatment.

These changes were confirmed by the increase in the concentration of cellulose in the pretreated biomass in the chemical composition tests (2.2, Table 3) [18]. *Molecules* **2021**, *26*, 6467 5 of 17

**Figure 1.** (**a**) The FTIR spectra of the Tygra biomass before and after the alkaline treatment. (**b**) The FTIR spectra of the Rajan biomass before and after the alkaline treatment. **Figure 1.** (**a**) The FTIR spectra of the Tygra biomass before and after the alkaline treatment. (**b**) The FTIR spectra of the Rajan biomass before and after the alkaline treatment.

**c) g) e)**

**a) d)**

**Figure 2.** The SEM images of hemp biomass: (**a**) Tygra biomass before pretreatment, (**b**) Tygra bio‐ mass after pretreatment, (**c**) Tygra biomass after enzymatic hydrolysis, (**d**) Tygra biomass after en‐ zymatic hydrolysis—selected fragment in high magnification, (**e**) Rajan biomass before pretreat‐ ment, (**f**) Rajan biomass after pretreatment, (**g**) Rajan biomass after enzymatic hydrolysis, (**h**) Rajan biomass after enzymatic hydrolysis—selected fragment in high magnification. **Figure 2.** The SEM images of hemp biomass: (**a**) Tygra biomass before pretreatment, (**b**) Tygra biomass after pretreatment, (**c**) Tygra biomass after enzymatic hydrolysis, (**d**) Tygra biomass after enzymatic hydrolysis—selected fragment in high magnification, (**e**) Rajan biomass before pretreatment, (**f**) Rajan biomass after pretreatment, (**g**) Rajan biomass after enzymatic hydrolysis, (**h**) Rajan biomass after enzymatic hydrolysis—selected fragment in high magnification.

Significant changes on the surface of the biomass were observed and presented in the SEM images taken before and after the biomass pretreatment as well as after enzymatic The vibration band visible at 1730 cm−1 (C=O stretching of acetyl groups in hemicelluloses and aldehydes in lignin) [19] was reduced in both hemp varieties after alkaline treatment, while the change was much more significant for the Rajan variety where the band almost disappeared. This occurred due to the decomposition of hemicelluloses and

the solubilization of lignin during alkali pretreatment. This result correlates very well with the obtained results of the chemical composition of the biomass after pretreatment. According to these studies, the content of hemicelluloses after alkaline treatment in the Rajan variety decreased by as much as 12% (2.2, Table 3).

Moreover, the obtained FTIR spectra showed that the removal of lignin in the alkaline treatment process was problematic (band at 1510 cm−1 ). This was confirmed by the results of the chemical composition of the lignin content presented in Table 2. This problem is widely described in the literature dealing with the studies of lignocellulosic biomass by infrared spectroscopy [20,21]. The process of the degradation or fragmentation of lignin is complicated due to the presence of strong C–C bonds and other functional groups, such as aromatic groups [13].

Significant changes on the surface of the biomass were observed and presented in the SEM images taken before and after the biomass pretreatment as well as after enzymatic hydrolysis (Figure 2). In the case of both varieties of hemp biomass (Tygra and Rajan), similar changes were observed in the biomass surface, which appeared as a result of subsequent processes. However, in the case of the Rajan variety, changes were more intensive, especially after the enzymatic hydrolysis process. The untreated hemp biomass was observed to have intact, rigid, and coarse structures with smooth surface and a wellordered fiber skeleton (Figure 2a,e). This strongly blocked access to cellulose to limit enzymatic attack [22]. As a result of pretreatment, the biomass underwent various specific structural changes. The SEM images of hemp biomass after pretreatment showed that the surface area of the biomass was partially purified (Figure 2b,f). The morphological changes that indicated damage to the structure of biomass and that increased the surface area, making it more accessible to the cellulolytic enzymes [20,23,24], were observed. The enzymatic hydrolysis of the samples subjected to the previous alkaline treatment caused further significant changes in the structure of the biomass visible in the SEM pictures (Figure 2c,d,g,h). The appearance of micropores was very characteristic here.

Undoubtedly, the opening of the hemp biomass and creating the holes all over the biomass enhanced the enzyme accessibility of the structure and facilitated biomass digestibility [25]. Moreover, it was clearly visible that enzymatic hydrolysis of the Rajan hemp biomass made the fibrous structure fragile and was more successful.

#### *2.3. Evaluation of Enzyme Preparations*

The enzymatic hydrolysis process is the second main step in the process of obtaining bioethanol from plant biomass. Enzymatic hydrolysis determines the amounts of simple sugars that are metabolized by yeast in the fermentation process. The breakdown of cellulose into simple sugars requires the synergistic action of different enzymes: cellulases, endoglucanases, cellobiohydrolases, and ß-glucosidases. First, the commercial enzyme preparations of various compositions were gained (Flashzyme Plus 200, ACx8000L, Celluclast 1.5L, Cellobiase, Xylanase), and then their cellulolytic and xylanolytic activities were determined. Taking into account evaluated activity of the tested enzymes and their commercial availability, Flashzyme Plus 200 and Celluclast 1.5L preparations were selected for further research (Table 4).

In order to select the enzyme complex for the SHF and the SSF processes, enzymatic tests were performed using selected enzymes and their supplementation with glucosidase and xylanase and were partially described in our previous studies [4]. For the SHF process in the case of the Tygra biomass, an enzyme complex was selected with the composition of Flashzyme Plus 200, glucosidase, and xylanase, while composition for the Rajan was Flashzyme Plus 200:Celluclast 1.5L hemp biomass in the proportion of 70:30. For the SSF process, the enzyme complex for the Tygra biomass was selected as Flashzyme Plus 200:Celluclast 1.5L (70%:30%) and xylanase and for the Rajan was Flashzyme Plus 200:Celluclast 1.5L hemp biomass in the 50:50 ratio.

**Table 4.** The determination of cellulolytic and xylanolytic activities of commercial enzyme preparations (FPU·mL−1 ).

#### *2.4. Separate Hydrolysis and Fermentation (SHF)*

To determine the optimal conditions of the enzymatic hydrolysis method as a separate process of SHF, based on the literature data and the research experience, the following parameter ranges were selected for testing with the response surface methodology (RSM): dose of the enzyme 10–30 FPU·g −1 of solid, temperature 50–70 ◦C, pH 4.2–5.4, and time 24–72 h. The RSM method is an effective optimization tool consisting of mathematical and statistical techniques and used for the process of optimization [26–28].

Individual enzymatic tests of the hydrolysis process were performed for Tygra and Rajan biomasses, and the evaluation criterion was the amount of released glucose. Figure 3 presents various response surfaces and interaction effects of variables (temperature, time, enzymes' dose, and pH) on the glucose yield. The variable that had the most significant impact on the glucose content turned out to be the temperature. The lower the temperature was, the higher the glucose content was. The pH of the solution, the process time, and the enzymes' dose had lesser effects. However, slight differences were observed in the dependence of these variables on the glucose yield for the two biomass varieties. For the Tygra biomass, it was found that, in the SHF process, the optimal conditions for enzymatic hydrolysis were obtained for the substrate concentration of 5% using the following enzymes: Flashzyme Plus 200 30 FPU·g −1 of solid, glucosidase 20 CBU·g −1 of solid, and xylanase 500 XU·g −1 of solid. The process parameters were: temperature 50 ◦C, pH 4.2, and time 48 h. These parameters provided the opportunity to obtain a maximum glucose yield, which was 36.9 ± 0.64 (g·L −1 ). In the SHF process for the Rajan biomass, optimal enzymatic hydrolysis conditions were obtained for a substrate concentration of 5% using the Flashzyme Plus 200:Celluclast 1.5L (70:30) enzyme complex with a dose of 10 FPU·g −1 of solid. The process parameters were: temperature 50 ◦C, pH 5.4, and time 72 h. The maximum glucose yield was 23.66 ± 0.16 (g·L −1 ).

Similar research was conducted by Abraham [29]; during biomass hydrolysis at 50 ◦C and 18 FPU·g −1 of solid, the highest glucose yield was obtained. Salimi and others [30] optimized the enzymatic hydrolysis of lignocellulosic biomass using the RSM method. They applied the temperature range of 45–60 ◦C and the pH of 4.5—6.0. They obtained the highest content of monosaccharides at 45 ◦C and pH 6.0. Jambo et al. [31], in turn, optimized lignocellulosic biomass using similar parameters—temperature (30–60 ◦C), pH (3.8–5.8), and incubation time (12–72 h)—and obtained the glucose concentration at the level 24.24 g·L −1 .

of Flashzyme Plus 200, glucosidase, and xylanase, while composition for the Rajan was Flashzyme Plus 200:Celluclast 1.5L hemp biomass in the proportion of 70:30. For the SSF process, the enzyme complex for the Tygra biomass was selected as Flashzyme Plus 200:Celluclast 1.5L (70%:30%) and xylanase and forthe Rajan was Flashzyme Plus 200:Cel‐

To determine the optimal conditions of the enzymatic hydrolysis method as a sepa‐ rate process of SHF, based on the literature data and the research experience, the following parameter ranges were selected for testing with the response surface methodology (RSM): dose of the enzyme 10–30 FPU∙g−1 of solid, temperature 50–70 °C, pH 4.2–5.4, and time 24– 72 h. The RSM method is an effective optimization tool consisting of mathematical and

Individual enzymatic tests of the hydrolysis process were performed for Tygra and Rajan biomasses, and the evaluation criterion was the amount of released glucose. Figure 3 presents various response surfaces and interaction effects of variables (temperature, time, enzymes' dose, and pH) on the glucose yield. The variable that had the most signif‐ icant impact on the glucose content turned out to be the temperature. The lower the tem‐ perature was, the higher the glucose content was. The pH of the solution, the process time, and the enzymes' dose had lesser effects. However, slight differences were observed in the dependence of these variables on the glucose yield for the two biomass varieties. For the Tygra biomass, it was found that, in the SHF process, the optimal conditions for enzy‐ matic hydrolysis were obtained for the substrate concentration of 5% using the following enzymes: Flashzyme Plus 200 30 FPU∙g−1 of solid, glucosidase 20 CBU∙g−1 of solid, and xylanase 500 XU∙g−1 of solid. The process parameters were: temperature 50 °C, pH 4.2, and time 48 h. These parameters provided the opportunity to obtain a maximum glucose yield, which was 36.9 ± 0.64 (g∙L−1). In the SHF process for the Rajan biomass, optimal enzymatic hydrolysis conditions were obtained for a substrate concentration of 5% using the

solid. The process parameters were: temperature 50 °C, pH 5.4, and time 72 h. The maxi‐

statistical techniques and used for the process of optimization [26–28].

luclast 1.5L hemp biomass in the 50:50 ratio.

*2.4. Separate Hydrolysis and Fermentation (SHF)*

mum glucose yield was 23.66 ± 0.16 (g∙L−1).

**Figure 3.** Enzymatic hydrolysis process of hemp biomass (RSM). Response surface representing the interaction effects of temperature, time, dose, and pH on glucose yield: (**a**) Tygra biomass, (**b**) Rajan biomass. **Figure 3.** Enzymatic hydrolysis process of hemp biomass (RSM). Response surface representing the interaction effects of temperature, time, dose, and pH on glucose yield: (**a**) Tygra biomass, (**b**) Rajan biomass.

Similar research was conducted by Abraham [29]; during biomass hydrolysis at 50 °C and 18 FPU∙g−1 of solid, the highest glucose yield was obtained. Salimi and others [30] optimized the enzymatic hydrolysis of lignocellulosic biomass using the RSM method. They applied the temperature range of 45–60 °C and the pH of 4.5—6.0. They obtained the highest content of monosaccharides at 45 °C and pH 6.0. Jambo et al. [31], in turn, opti‐ mized lignocellulosic biomass using similar parameters—temperature (30–60 °C), pH (3.8–5.8), and incubation time (12–72 h)—and obtained the glucose concentration at the level 24.24 g∙L−1. The next step in the conversion of hemp biomass to bioethanol in the SHF process was ethanol fermentation. In the SHF process for the Tygra biomass, the highest concen‐ The next step in the conversion of hemp biomass to bioethanol in the SHF process was ethanol fermentation. In the SHF process for the Tygra biomass, the highest concentration of ethanol was observed at 48 hours and was 10.51 g·L −1 . In the following hours of the process, no significant increase in ethanol concentration was observed. In turn, for the Rajan biomass, the highest ethanol concentration was noticed at 96 h, and it was only 2.76 g·L −1 . Such a low concentration of ethanol in this case could be attributed to various reasons, which together may have had a significant negative impact on this parameter—for example, the chemical composition, which was characterized by a higher lignin content compared to the Tygra biomass. The reason could also have been the use of a low enzyme dose (10 FPU g−1 solid) in Rajan biomass as well as the low glucose concentration (23.66 g L−1 ),

tration of ethanol was observed at 48 hours and was 10.51 g∙L−1. In the following hours of

Rajan biomass, the highest ethanol concentration was noticed at 96 h, and it was only 2.76 g∙L−1. Such a low concentration of ethanol in this case could be attributed to various rea‐ sons, which together may have had a significant negative impact on this parameter—for example, the chemical composition, which was characterized by a higher lignin content compared to the Tygra biomass. The reason could also have been the use of a low enzyme dose (10 FPU g−1 solid) in Rajan biomass as well as the low glucose concentration (23.66 g L−1), which was determined immediately after the enzymatic hydrolysis step. Addition‐ ally, after optimizing this step, a pH of 5.4 was chosen based on the glucose concentration, which may have, to some extent, inhibited yeast activity in the initial phase of fermenta‐ tion. Nevertheless, it was noticed that, with each passing day, the concentration of ethanol increased slightly, which ultimately indicates that the process itself was proceeding cor‐ rectly. However, for Tygra biomass, no significant increase in ethanol concentration was observed with time extension of the SHF process (Figure 4). The average yield of bioetha‐ nol for the Tygra variety was equal to 253 L∙Mg−1 (of hemp straw dry matter), i.e., 3.04 m3∙ha−1. For the Rajan variety, the average yield of bioethanol was 69 L∙Mg−1 (of hemp straw dry matter), i.e., 0.80 m3∙ha−1. A similar study was presented by Kusmiyati et al. [32]. In their work, the conversion of the lignocelullosic biomass to bioethanol was carried out

which was determined immediately after the enzymatic hydrolysis step. Additionally, after optimizing this step, a pH of 5.4 was chosen based on the glucose concentration, which may have, to some extent, inhibited yeast activity in the initial phase of fermentation. Nevertheless, it was noticed that, with each passing day, the concentration of ethanol increased slightly, which ultimately indicates that the process itself was proceeding correctly. However, for Tygra biomass, no significant increase in ethanol concentration was observed with time extension of the SHF process (Figure 4). The average yield of bioethanol for the Tygra variety was equal to 253 L·Mg−1 (of hemp straw dry matter), i.e., 3.04 m3 ·ha−1 . For the Rajan variety, the average yield of bioethanol was 69 L·Mg−1 (of hemp straw dry matter), i.e., 0.80 m3 ·ha−1 . A similar study was presented by Kusmiyati et al. [32]. In their work, the conversion of the lignocelullosic biomass to bioethanol was carried out through pretreatment, saccharification, and fermentation processes. Their results showed that the SHF process gave a higher concentration of ethanol (8.11 g·L −1 ). Fischer and others [33], in their research, dealt with lignocellulosic biomass and examined the SHF process, obtaining the ethanol concentration of 12.1 g·L −1 . *Molecules* **2021**, *26*, 6467 11 of 17 through pretreatment, saccharification, and fermentation processes. Their results showed that the SHF process gave a higher concentration of ethanol (8.11 g∙L−1). Fischer and others [33], in their research, dealt with lignocellulosic biomass and examined the SHF process, obtaining the ethanol concentration of 12.1 g∙L−1.

**Figure 4.** The ethanol concentration of hemp biomass in the SHF process. Optimized process condi‐ tions: Tygra biomass—substrate concentration 5%, enzymes: Flashzyme Plus 200 30 FPU∙g−1 of solid, glucosidase 20 CBU∙g‐1 of solid and xylanase 500 XU∙g−1 of solid, temperature 50 °C, pH 4.2, and time 48 h. Rajan biomass—substrate concentration 5%, Flashzyme Plus 200:Celluclast 1.5L (70:30) enzyme complex with a dose of 10 FPU∙g−1 of solid, temperature 50 °C, pH 5.4, and time 72 h. SHF as an alternative process in an industrial bioethanol plant manifests both poten‐ **Figure 4.** The ethanol concentration of hemp biomass in the SHF process. Optimized process conditions: Tygra biomass—substrate concentration 5%, enzymes: Flashzyme Plus 200 30 FPU·g −1 of solid, glucosidase 20 CBU·g -1 of solid and xylanase 500 XU·g −1 of solid, temperature 50 ◦C, pH 4.2, and time 48 h. Rajan biomass—substrate concentration 5%, Flashzyme Plus 200:Celluclast 1.5L (70:30) enzyme complex with a dose of 10 FPU·g −1 of solid, temperature 50 ◦C, pH 5.4, and time 72 h.

tial and limitations. The main advantage of SHF is the possibility to optimize the process steps separately, especially to be able to run the enzymatic hydrolysis at an optimal tem‐ perature with respect to enzymes [34]. However, most literature reports confirm that SSF is a more promising and advantageous approach with respect to SHF because of a low production cost, less processing time, less reactor volume, higher ethanol productivity, a lower requirement of enzyme, the ability to overcome enzymatic inhibition by simultane‐ ous end‐product removal, and a lower requirement for sterile conditions, as bioethanol is produced immediately with glucose conversion [35,36]. *2.5. Simultaneous Saccharification and Fermentation (SSF)* SHF as an alternative process in an industrial bioethanol plant manifests both potential and limitations. The main advantage of SHF is the possibility to optimize the process steps separately, especially to be able to run the enzymatic hydrolysis at an optimal temperature with respect to enzymes [34]. However, most literature reports confirm that SSF is a more promising and advantageous approach with respect to SHF because of a low production cost, less processing time, less reactor volume, higher ethanol productivity, a lower requirement of enzyme, the ability to overcome enzymatic inhibition by simultaneous end-product removal, and a lower requirement for sterile conditions, as bioethanol is produced immediately with glucose conversion [35,36].

#### The simultaneous hydrolysis and fermentation must be carried out under conditions *2.5. Simultaneous Saccharification and Fermentation (SSF)*

that ensure the optimal synergy of enzymes and distillery yeast. To optimize the SSF pro‐ cess according to the RSM, the following ranges of process parameters were selected: sub‐ strate content 5%–7% *w*/*v*, the dose of Flashzyme:Celluclast 1.5L enzymes (50:50) 10–30 FPU∙g−1 of solid using *S. cerevisiae* yeast at 37 °C, pH 4.8, and 96 h. Then, the fermentation The simultaneous hydrolysis and fermentation must be carried out under conditions that ensure the optimal synergy of enzymes and distillery yeast. To optimize the SSF process according to the RSM, the following ranges of process parameters were selected: substrate content 5%–7% *w*/*v*, the dose of Flashzyme:Celluclast 1.5L enzymes (50:50)

was determined. The optimal conditions of the SSF process for the Tygra and the Rajan hemp biomasses were selected. The highest ethanol concentration for Tygra biomass was observed at a substrate content of 5% *w*/*v* and a dose of enzyme at 30 FPU∙g−1 of solid, and it was 6.5 g∙L−1. In turn, for the Rajan biomass, the highest ethanol concentration equal to 7.5 g∙L−1 was recorded for the substrate of 5% and for the enzyme 30 FPU∙g−1 of solid. Higher substrate content above 5% *w*/*v* interfered with the effective mixing of the fermen‐ tation solution, which resulted in poorer access to biomass and thus less effective action of enzymes and yeast. It was also observed that enlarging the enzyme dose enhanced the conversion of cellulose to glucose and thus increased the concentration of ethanol. The

10–30 FPU·g −1 of solid using *S. cerevisiae* yeast at 37 ◦C, pH 4.8, and 96 h. Then, the fermentation tests were carried out using the selected parameters, and the amount of ethanol (HPLC) was determined. The optimal conditions of the SSF process for the Tygra and the Rajan hemp biomasses were selected. The highest ethanol concentration for Tygra biomass was observed at a substrate content of 5% *w*/*v* and a dose of enzyme at 30 FPU·g −1 of solid, and it was 6.5 g·L −1 . In turn, for the Rajan biomass, the highest ethanol concentration equal to 7.5 g·L −1 was recorded for the substrate of 5% and for the enzyme 30 FPU·g −1 of solid. Higher substrate content above 5% *w*/*v* interfered with the effective mixing of the fermentation solution, which resulted in poorer access to biomass and thus less effective action of enzymes and yeast. It was also observed that enlarging the enzyme dose enhanced the conversion of cellulose to glucose and thus increased the concentration of ethanol. The enzyme dose of 10 FPU·g −1 of solid tested in the optimization process turned out to be too low to carry out efficient enzymatic hydrolysis. *Molecules* **2021**, *26*, 6467 12 of 17 enzyme dose of 10 FPU∙g−1 of solid tested in the optimization process turned out to be too low to carry out efficient enzymatic hydrolysis.

For the Tygra biomass, there were no changes in the concentration of ethanol with the time lapse of the process. In turn, for the Rajan biomass, after 24 h, there was observed a decrease in ethanol concentration, and after 48 h of the SSF process, there was noticed a significant increase in ethanol concentration (Figure 5). It was observed that, for the Rajan biomass, in contrast to the Tygra biomass, a higher ethanol concentration was obtained in the SSF process than in the SHF process (Figures 4 and 5). For the Tygra biomass, there were no changes in the concentration of ethanol with the time lapse of the process. In turn, for the Rajan biomass, after 24 h, there was observed a decrease in ethanol concentration, and after 48 h of the SSF process, there was noticed a significant increase in ethanol concentration (Figure 5). It was observed that, for the Rajan biomass, in contrast to the Tygra biomass, a higher ethanol concentration was obtained in the SSF process than in the SHF process (Figures 4 and 5).

**Figure 5.** Ethanol concentration of hemp biomass in the SSF process. Optimized process conditions: Tygra and Rajan biomass‐substrate concentration 5%, enzymes: Flashzyme:Celluclast 1.5L (50:50) 30 FPU∙g−1 of solid, temperature 37 °C, pH 4.8, and time 96 h. **Figure 5.** Ethanol concentration of hemp biomass in the SSF process. Optimized process conditions: Tygra and Rajan biomass-substrate concentration 5%, enzymes: Flashzyme:Celluclast 1.5L (50:50) 30 FPU·g −1 of solid, temperature 37 ◦C, pH 4.8, and time 96 h.

In their research, Fojas and Rosario [37] optimized the enzymatic saccharification of lignocellulosic biomass, and the SSF process was carried out with the following parame‐ ters: 3%–6% the amount of substrate, 20–25 FPU∙g−1 of solid dose of enzyme, and temper‐ ature of 37 °C for 120 h. They achieved an ethanol content of about 9 g∙L−1. In their research, Fojas and Rosario [37] optimized the enzymatic saccharification of lignocellulosic biomass, and the SSF process was carried out with the following parameters: 3%–6% the amount of substrate, 20–25 FPU·g −1 of solid dose of enzyme, and temperature of 37 ◦C for 120 h. They achieved an ethanol content of about 9 g·L −1 .

Research on obtaining bioethanol from hemp biomass was also carried out by Or‐ lygsson [38]; after the SSF process, the author obtained an ethanol concentration of ap‐ proximately 1 g∙L−1. Research on obtaining bioethanol from hemp biomass was also carried out by Orlygsson [38]; after the SSF process, the author obtained an ethanol concentration of approximately 1 g·L −1 .

On the basis of the average ethanol content, the hemp straw yield that could be ob‐ tained from 1 ha of hemp cultivation was specified. The highest average yield of bioetha‐ nol was estimated for the Rajan variety and was equal to 190 L∙Mg−1 (of hemp straw dry matter), i.e., 2.23 m3∙ha−1, while the average yield of bioethanol estimated for the Tygra variety was 165 L∙Mg−1 (of hemp straw dry matter), i.e., 1.81 m3∙ha−1. On the basis of the average ethanol content, the hemp straw yield that could be obtained from 1 ha of hemp cultivation was specified. The highest average yield of bioethanol was estimated for the Rajan variety and was equal to 190 L·Mg−1 (of hemp straw dry matter), i.e., 2.23 m3 ·ha−1 , while the average yield of bioethanol estimated for the Tygra variety was 165 L·Mg−1 (of hemp straw dry matter), i.e., 1.81 m3 ·ha−1 .

Extensive research on industrial hemp as potential raw material for bioethanol pro‐ duction compared to other raw materials such as kenaf and sorghum was conducted by Extensive research on industrial hemp as potential raw material for bioethanol production compared to other raw materials such as kenaf and sorghum was conducted by

lowed the researchers to conclude that industrial hemp can generate higher gross profits per hectare than other crops. In conclusion, this scientific report emphasized that hemp

has the potential to be a promising crop for the production of bioethanol.

Das et al. [39]. According to these studies, the ethanol yield from hemp was 250 L·Mg−1 , which turned out to be much higher than that of kenaf. Moreover, the cost analysis allowed the researchers to conclude that industrial hemp can generate higher gross profits per hectare than other crops. In conclusion, this scientific report emphasized that hemp has the potential to be a promising crop for the production of bioethanol.

#### **3. Materials and Methods**

#### *3.1. Bioethanol Production Process*

#### 3.1.1. Hemp Biomass Preparation

The raw materials used in the study were Białobrzeskie, Tygra, Henola, and Rajan hemp (*Cannabis sativa* L.) biomasses from the Experimental Farm of the Institute of Natural Fibres and Medicinal Plants in P˛etkowo. This material was subjected to preliminary crushing to the particles of size 20–40 mm and then dried in 50–55 ◦C for 24 h. Next, the material was disintegrated on a knife mill (Retsch SM-200, Germany) with the sieves of the mesh size of 2–4 mm. An enzymatic test for the crushed fractions was performed using the Celluclast 1.5L enzyme preparation, and the content of reducing sugars was determined by the Miller's method with 3,5-dinitrosalicylic acid (DNS) [40].

#### 3.1.2. Alkaline Pretreatment

The evaluation of pretreatment conditions for hemp biomass was carried out at 5 h treatment with 1.5%–3% sodium hydroxide in 90 ◦C. NaOH:biomass weight ratio was 10:1. After the alkaline pretreatment was carried out, the biomass solution was filtered on a Büchner funnel, then washed with distilled water until neutralized and dried in a laboratory dryer at 50 ◦C for 24 h. The alkali effect on the biomass was evaluated in the enzymatic test, and content of the released reducing sugars was determined by the Miller's method. This test was performed with the use of Celluclast 1.5L (Novozymes, Bagsværd, Denmark) enzymatic preparation at the dose of 10 FPU·g −1 of solid. The raw material was incubated at 55 ◦C in 0.05 M citrate buffer of pH 4.8 for 24 h. Then, after the enzymatic test, the supernatant was diluted, a DNS reagent was added, and the mixture was incubated in a boiling water bath for 10 min. After cooling to room temperature, the absorbance of the supernatant was measured at 530 nm on UV–VIS Spectrophotometer V-630 (Jasco, Pfungstadt, Germany).

#### 3.1.3. Enzyme Complex

The enzymes cellulolytic activity was determined according to NREL LAP Measurement of Cellulase Activities. In turn, enzymes xylanolytic activity was determined according to the Osaka University procedure (with changes) [41].

In order to select the enzyme complex for SHF and SSF processes, tests were performed using selected enzymes (Flashzyme Plus 200:Celluclast 1.5L) and their supplementation with glucosidase 20 CBU·g −1 of solid and xylanase 500 XU·g −1 of solid (Sigma-Aldrich, Darmstadt, Germany ). Enzymatic tests were carried out for 5% of biomass with the enzyme in the amount of 10 FPU·g −1 of solid, at a pH of 4.8, and during 24 h at 55 ◦C for the SHF process and at 38 ◦C for the SSF process. The selection criterion was the content of reducing sugars determined by the Miller's method.

#### 3.1.4. Separate Hydrolysis and Fermentation (SHF)

The optimization of the enzymatic hydrolysis of hemp biomass in the SHF process was carried out according to the response surface methodology (RSM) using the parameters: biomass content 5%–7% *w*/*v*, temperature 50–70 ◦C, time 24–72 h, pH 4.2–5.4, dose of enzyme 10–30 FPU·g −1 of solid. Then, tests of the hemp biomass hydrolysis process were performed, and the evaluation criterion was the amount of released glucose.

In the next stage, the obtained hydrolyzate was subjected to the ethanol fermentation process carried out in bioreactor Biostat B Plus (Sartorius, Göttingen, Germany) in 2 L vessel equipped with pH, temperature, stirring, and foaming controls. The temperature was

maintained at 37 ◦C and stirring at 900 rpm, while pH was controlled at 4.2 for Tygra and 5.4 for Rajan by adding 1 M NaOH or 1 M HCl. Non-hydrated freeze-dried distillery yeast *S. cerevisiae* (Ethanol Red, Lesaffre, France) at a dose of 1 g·L −1 was used in the process, which corresponded to cell concentration after inoculation of about 1 × 107 cfu/mL. Inoculum grew for 24 h at 30 ◦C. After inoculation, a 96 h fermentation was carried out, and samples were taken every 24 h. All experiments were performed in triplicate.

#### 3.1.5. Simultaneous Saccharification and Fermentation (SSF)

To optimize the SSF process according to the RSM, the ranges of process parameters were selected: substrate content 5%–7% *w*/*v*, dose of (Flashzyme:Celluclast 1.5L) enzymes 10–30 FPU·g −1 of solid. The SSF process was carried out in bioreactor Biostat B Plus (Sartorius, Göttingen, Germany) in 2 L vessel equipped with pH, temperature, stirring, and foaming controls. The temperature was maintained at 37 ◦C and stirring at 900 rpm, while pH was controlled at 4.8 by adding 1 M NaOH or 1 M HCl. In the fermentation process, non-hydrated freeze-dried distillery yeast *S. cerevisiae* (Ethanol Red, Lesaffre, France) at a dose of 1 g·L −1 was used, which corresponded to cell concentration after inoculation of about 1 × 107 cfu/mL. The duration of ethanol fermentation was 96 h. All experiments were performed in triplicate.

#### *3.2. Analytical Methods*

The chemical composition of hemp biomass before and after pretreatment was determined, i.e., cellulose according to TAPPI T17 m-55 [42], hemicelluloses as the difference of holocellulose and cellulose according to TAPPI T9 m-54 [43], and lignin according to TAPPI T13 m-54 [44].

In order to provide a more complete picture of the molecular structure of hemp biomass before and after the chemical pretreatment, the analysis of FTIR spectroscopy was performed using a Fourier Transform Infrared Spectrometer ISS 66v/S (Bruker, Bremen, Germany) at infrared wavenumbers of 400–4000 cm−1 [13].

The physical morphologies of hemp biomass before and after the chemical treatment and after enzymatic hydrolysis were performed using Scanning Electron Microscope S-3400N (Hitachi, Japan) in high vacuum conditions. The samples were covered with gold dust.

The contents of glucose and ethanol were determined by high performance liquid chromatography on Elite LaChrom (Hitachi, Tokio, Japan) using an RI L-2490 detector, Rezex ROA 300x7.80 mm column (Phenomenex, Torrance, CA, USA), as the mobile phase used 0.005 N H2SO4 at a flow rate of 0.6 mL/min at 40 ◦C.

#### *3.3. Calculations*

The ethanol yield from 100 g of raw material Ys (g/100 g of raw material) was calculated according to the Equation (1) [45]:

$$Y\_s = \frac{Et \times 100}{M} \tag{1}$$

where: *Et*—amount of ethanol in 1000 mL of tested sample (g); *M*—mass of material weighed in 1000 mL fermentation sample (g).

Then, based on the ethanol yield from 100 g of raw material, the amount of ethanol in L per ton of straw dry matter (L·Mg−1 ) was calculated, and on the basis of straw yield, the ethanol yield per hectare (m3 ·ha−1 ) was determined.

#### *3.4. Statistical Analysis*

The experiments of ethanol fermentation were carried out in triplicates. Standard deviations were calculated using the analysis of variance ANOVA, Statistica 13.0 software (*p* < 0.05).

#### **4. Conclusions**

To sum up, the Tygra and the Rajan varieties of hemp were selected, which proved to be proper sources of second generation bioethanol as alternatives to petroleum-oil based fossil fuels. Pretreatment, enzymatic hydrolysis, and ethanol fermentation were optimized. Alkaline pretreatment caused an increase in cellulose content and partial degradation of hemicelluloses. Enzymatic hydrolysis allowed us to achieve glucose yield at the level up to 36.9 g·L −1 . For the Tygra biomass in the SHF process, the ethanol concentration was 10.5 g·L −1 (3.04 m3 ·ha−1 ), and for the Rajan biomass in the SSF process, the ethanol concentration was 7.5 g·L −1 (2.23 m3 ·ha−1 ).

In the future, it will be important to conduct research on the mixtures of different varieties of hemp biomass in order to determine their potential for the production of lignocellulosic ethanol, which seems important in practical application, because the industrial production of biofuels occurs most often in large refineries which process the biomass of different varieties and species of plants.

**Author Contributions:** Conceptualization, A.W., J.B., W.G.; Methodology, A.W., J.B., W.G.; Software, A.W., W.G.; Validation, J.B.; Formal Analysis, J.B., A.W.; Investigation, A.W., W.G.; Resources, A.W., J.B. WG.; Data Curation, J.B., A.W., W.G.; Writing—Original Draft Preparation, A.W., W.G; Writing— Review & Editing, A.W., J.B., W.G.; Visualization, A.W.; Supervision, J.B.; Project Administration, J.B.; Funding Acquisition, J.B. All authors have read and agreed to the published version of the manuscript.

**Funding:** This research was funded by the Ministry of Agriculture and Rural Development, Poland, Multiannual Program (2017–2020).

**Institutional Review Board Statement:** Not applicable.

**Informed Consent Statement:** Not applicable.

**Data Availability Statement:** Data is contained within the article.

**Acknowledgments:** The study was conducted as a research project- Multiannual Program (2017– 2020): Reconstruction and sustainable development of production and processing of natural fiber raw materials for the needs of agriculture and the economy was financed by the Ministry of Agriculture and Rural Development, Poland.

**Conflicts of Interest:** The authors declare no conflict of interest.

#### **References**


7.2 Environmental considerations and fermentation parameters for K. marxianus

Several adjustable factors can influence the rate and quality of fermentation by K. marxianus. These factors include the presence of oxygen, nutrient supplementation, substrate, pH and fermentation temperature. In general, hypoxic and anoxic environments favor K. marxianus's fermentative metabolism, and ethanol yields are greater than in an aerobic environment [10, 43]. Aerobic conditions favor the building of cell density and are commercially applied for cell propagation in vessels called "Donas" [9]. The doubling time of K. marxianus is approximately 70 min, and it has one of the fastest growth rates of any eukaryote [37].

Nutrients are not added to the whey/whey permeate during commercial fermentations [9]. Additional supplementation of nitrogen and phosphorus to whey/ whey permeate was shown not to affect ethanol production during fermentation [44]. It has been illustrated experimentally that supplementation of concentrated whey (200 g/l lactose) with bacto-peptone, ergosterol and linoleic acid reduced fermentation time from over 90 to less 60 h [10]. This is a substantial decrease in fermentation time, however large-scale commercial lactose to ethanol fermentations range from 12 to 24 h [8, 9].

K. marxianus is a thermotolerant yeast with reported maximum growth temperatures ranging from 47 to 52°C [10, 35]. Ethanol production has been reported at temperatures as high as 45°C [45] and, other studies indicate that the optimum fermentation temperature is lower. Studies indicate the optimal fermentation temperature range to be 30–40°C [36, 39, 41, 42, 46–48]. This wide range of reported temperatures can likely be attributed to the genetic diversity of K. marxianus strains and differences in experimental design. A pH of approximately 5 is widely reported as the optimum fermentation pH value [36, 39, 42, 46–48]. Agitation of fermenting whey/whey permeate occurs in industrial lactose to ethanol conversion and has been incorporated experimentally [8, 9, 47, 49]. To the authors' knowledge, the effects of the rate of agitation on fermentation efficiency of K. marxianus have not been examined.

Large scale lactose to ethanol production facilities will adjust fermentation time, temperature, tank pressure, and agitation rate to meet production goals [8, 9]. K. marxianus strain UFV-3 may have potential for potable ethanol production. K. marxianus strain UFV-3 was able to produce ethanol at yields 90% of the theoretical maximum with fermentation temperatures between 33.3 and 38.5°C, pH 4.7–5.7 and lactose concentrations between 50 and 108 g/l [42].

#### 7.3 Other fermentation organisms

K. lactis is used to produce lactase and recombinant bovine chymosin on an industrial scale. It is the sister organism to K. marxianus that is more widely studied. K. lactis synthesizes β-galactosidase much like K. marxianus and most strains of K. lactis are considered Crabtree-negative [50]. A small number of isolate have been used by researchers working with K. lactis and it is ubiquitous to fewer environments than K. marxianus [10, 32]. This has led to less genetic variation than within in the species than K. marxianus. Some strains of K. lactis exhibit Crabtree-positive

### Whey to Vodka DOI: http://dx.doi.org/10.5772/intechopen.81679

metabolic characteristics [51, 52] and have been genetically engineered for lactose to bioethanol conversion [53]; however, they have not been adopted on a commercial level for lactose to ethanol conversion.

S. cerevisiae is the microorganism widely used in alcoholic beverage and bioethanol production. S. cerevisiae is used for traditional potable spirit production for several reasons including its fermentative capacity and ethanol tolerance, being considered Crabtree-positive (preferentially ferments in presence of oxygen and an abundance of glucose), and it's GRAS designation [10]. S. cerevisiae is ill-suited for the conversion of lactose to potable ethanol because wild S. cerevisiae does not express the genes necessary to produce β-galactosidase. This requires the lactose within whey/whey permeate to be pre-hydrolyzed or S. cerevisiae to be genetically engineered to produce β-galactosidase. While pre-hydrolysis of lactose has been explored on an experimental scale for bioethanol production, it would require an additional input (enzymes) and/or additional processing equipment. S. cerevisiae preferentially uptakes glucose after lactose hydrolysis and the presence of glucose causes the catabolic repression of enzymes necessary to uptake galactose [54]. The enzymes necessary to uptake galactose will only be synthesized after the glucose has been depleted. This repression causes an increase in fermentation time due to a diauxic lag [10, 55]. While S. cerevisiae has been genetically engineered to synthesize β-galactosidase and to reduce catabolic repression, genetically engineered yeast are not commonly used for beverage production [19, 21, 56].

E. coli has been genetically altered to produce ethanol since 1987 [57]. In 2010, E. coli was genetically modified to express the Vitreoscilla hemoglobin for direct fermentation of sugar to ethanol [58]. This technology has been experimentally developed for the efficient fermentation of whey and other organic by-products. Recently, microbial immobilization has been experimentally applied to E. coli expressing Vitreoscilla hemoglobin and has shown an increase in lactose to bioethanol production efficiency without producing the microbial biomass associated with the traditional fermentation process [59, 60].

The use of genetically modified organisms for the conversion of whey to potable spirit has the potential to increase production efficiency and reduce operating costs. The use of these organisms will require consumer acceptance of potable spirits produced from this technology.


*Bovine Respiratory Disease in Feedlot Cattle: Antimicrobial Resistance in Bovine Respiratory… DOI: http://dx.doi.org/10.5772/intechopen.81718*

antimicrobial compounds such as lactic acid and bacteriocins. They can also prevent adherence of pathogenic bacteria to the host cells via competitive exclusion, as probiotic strains use the same binding sites as the pathogenic bacteria or downregulate the expression of pathogen-binding sites [37]. Probiotic *Lactobacilli* have also been reported to preserve intestinal epithelial barrier function through stimulating mucin secretion, strengthening tight junction and preventing epithelial cell death and thereby inhibit pathogen translocation [37].

In addition, probiotics have the potential to boost host immune defenses against pathogens by modulating immune response [39]. Probiotics regulate innate and adaptive immune response by modulating immune cells and cytokine production via toll-like receptor-regulated signaling pathways [40]. Probiotic-induced alterations in the functions of dendritic cells, macrophages and T lymphocytes have been documented. For example, probiotic *Lactobacillus* strains modulated dendritic cells and thereby altered cell surface antigen expression and cytokine production in dendritic cells [37, 40]. Additionally, the impact of lactobacillus strains on macrophage function and its TNF-α production capacity has also been reported [41]. Probiotic bacteria *L. acidophilus* influenced the activity of regulatory T cells (Tregs) *in vitro* and *in vivo* in mice [42]. Tregs play a vital role in suppressing inflammation and maintaining immune tolerance.

Modulating the balance of pro- and anti-inflammatory cytokine production is one of the most important mechanisms through which probiotics protect the host from pathogen-induced injury and inflammation [43]. Probiotic bacteria have induced anti-inflammatory cytokine, IL-10, in dendritic and regulatory T cells [43]. IL-10, also known as the master regulator of immunity to infection, plays an essential role in facilitating the optimal pathogen clearance by inhibiting the activity of Th1 cells, NK cells and macrophages [44]. In addition, probiotics inhibit pro-inflammatory cytokine production and thereby prevent excessive inflammation. Probiotic strain *L. rhamnosus* GG inhibited the LPS-stimulated TNF-α production in murine macrophages [45]. Also, *L. rhamnosus* GR-1 strain has significantly or partially reduced LPS-induced number of proinflammatory cytokines including TNF, IFN-γ, IL-1β, IL-2 and IL-6 in human decidual cells [46]. Of note, the immune modulation properties of probiotics are species- and strain-specific, and therefore, different species or different strains within a species are expected to have different immunomodulation properties [37].

The role of probiotics on the local microbiota starts to be better understood due to the completion of the human genome project and the development of next generation DNA sequencing platforms that enabled a deeper understanding of the structure and composition of the host microbiome. Studies suggest that probiotics may re-establish the composition of the gut microbiota and confer beneficial effects on the gut microbial communities [47, 48]. However, there is limited information available with respect to the effects of probiotics on respiratory microbiota. A very recently published study showed that the oral probiotics alter respiratory microbiota of healthy cats [49]. The orally ingested probiotics were detected in the respiratory tract of the cat and were also associated with changes in richness and the overall composition of colonizing microbial populations of the respiratory tract. This observation points out that oral probiotics could alter the respiratory microbiota.

## *3.1.2 Using probiotics to mitigate BRD bacterial pathogens*

Beneficial effects of probiotics in the prevention and control of human respiratory tract infections have been studied. For example, probiotic strain *Streptococcus salivarius* K12 can mitigate pharyngitis by inhibiting the colonization of pathogen

*Bacterial Cattle Diseases*

(e.g. *E. coli*) via conjugation [29].

obesity [35] have been identified.

*3.1.1 Mechanisms of probiotic action*

**pathogens**

**3.1 Probiotics**

commonly used as metaphylaxis. Furthermore, Snyder et al. [14] also reported that a significant increase (from 3.7 to 99.2%) in the prevalence of *M. haemolytica* isolates resistant to tulathromycin in newly received feedlot cattle (n = 169) within

Three or more resistant genes have been detected from *M. haemolytica* and *P. multocida* [15, 29]. These resistant genes are most likely occurring from *de novo* mutation or being acquired from other bacteria. It has been reported that some resistant genes present in BRD bacterial pathogens are being encoded in selftransmissible conjugative elements [15]. Klima et al. [29] identified *M. haemolytica, P. multocida* and *H. somni* isolates from the US and Albertan feedlots that contain integrative conjugative elements (ICE) that conferred resistance up to seven different antimicrobial classes. These ICE can be transferred not only from one BRD pathogens to another BRD pathogen but also to other non-BRD-related bacteria

The resistant BRD-related pathogens can not only cause substantial profitability

losses to the beef industry and animal welfare issues due to the higher disease relapse and mortality rate but also pose potential threat to the public health given the possibility of these transferable elements carrying resistant genes transfer into zoonotic pathogens. Therefore, counteracting measurements to reduce the develop-

**3. Alternative antimicrobial approaches to mitigate BRD bacterial**

Probiotics are defined as "live microorganisms administered in adequate amounts that confer a beneficial health effect on the host" [32]. The scientific recognition of the health-promoting properties of live microbes began in the early 1900s when a Ukrainian scientist, Elias Metchnikoff, hypothesized that the beneficial microbes present in fermented milk could normalize bowel health and prolong life by inhibiting 'putrefactive' bacteria in the gut [32]. Then, lactic acid bacteria (LAB) strains isolated from fermented milk were commercialized with the intention to treat diarrhea in French children in 1906. The term probiotics has been used since 1962. In the past 2 decades, a significant research attention has been given to probiotics, and beneficial effects of probiotics for the mitigation of infections of oral cavity; respiratory, urogenital and gastrointestinal tract [33]; cancer [34] and

Bacteria being used as probiotics today include LAB, non-pathogenic *Escherichia coli* and *Bacilli* [36]. The *Lactobacilli* and *Bifidobacteria* genera are the most commonly used as probiotics due to their specific health benefits, high safety profile, and stability [37, 38]. Probiotic bacterium possess unique genetic tools, special membrane structure and composition that allow them to survive under different environmental conditions after ingestion, adhere to the target niche, adapt to

Probiotics deliver their beneficial effects to the host through direct inhibition against potential pathogenic bacteria, improving the epithelial barrier function, stimulating the host immune system and re-establishing the commensal microbial community [37]. Probiotic bacteria can directly inhibit pathogens by producing

special nutrition conditions and integrate with the local microbiota [37].

ment and spread of AMR in BRD pathogens are urgently needed.

2 weeks after tulathromycin was given as metaphylaxis.

**22**

*Streptococcus pyogenes* and stimulating anti-inflammatory response in epithelial cells [50, 51]. A recent study revealed that the relative abundance of nasopharyngeal LAB in cattle entering the feedlot was significantly greater in animals that remained healthy compared with those that developed BRD [52], suggesting that a certain LAB are important to bovine respiratory mucosal health. Furthermore, an *in vitro* pilot study that we conducted to test antimicrobial properties of commercially available LAB strains (*Lactobacillus*) against *M. haemolytica* demonstrated the possibility of using probiotics to mitigate BRD pathogens [53]. The *Lactobacillus* strains isolated from the nasopharynx of healthy feedlot cattle displayed antimicrobial activity against the growth of *M. haemolytica in vitro* [54]. We also recently reported that the intranasal inoculation of *Lactobacillus* spp. strains inhibits the colonization of *M. haemolytica* S1 into the nasopharynx of dairy calves challenged with *M. haemolytica* S1 (Amat et al., unpublished data). These studies suggest the potential application of probiotics to mitigate BRD bacterial pathogens in feedlot cattle as an alternative to antimicrobial metaphylaxis.