Chemical Engineering Journal 425 (2021) 131620 Contents lists available at ScienceDirect Chemical Engineering Journal journal homepage: www.elsevier.com/locate/cej Fungal biopesticide production: Process scale-up and sequential batch mode operation with Trichoderma harzianum using agro-industrial solid wastes of different biodegradability Arnau Sala, Raquel Barrena *, Antoni Sánchez, Adriana Artola Department of Chemical, Biological and Environmental Engineering, Universitat Autònoma de Barcelona, Edifici Q, Campus de Bellaterra, 08193 Cerdanyola del Vallès, Spain A R T I C L E I N F O A B S T R A C T Keywords: This work presents a sequential batch operational strategy (SBR) for fungal conidia production in solid-state Solid-state fermentation fermentation (SSF) to improve the traditional batch operation, while also aiming to present a robust and scal­ Sequential-batch reactor able process. Trichoderma harzianum was fermented using two substrates with different biodegradability (rice Fungal conidia husk and beer draff), scaling from 1.5 L to 22 L bioreactors. Before the SBR operation, the optimum time to get Packed bed reactor Substrate biodegradability inoculum from each SBR batch was determined as 4 days. While single batch process scale-up was successful with both substrates, SBR strategy was only feasible using beer draff as substrate: conidia production was sustained during 3 consecutive batches in 1.5 L bioreactors and for 5 batches at 22 L. At both scales conidia production was around 2.0x109 conidia g-1dm, achieving maximum specific oxygen consumption rate (sOUR) values close to 4 g O2 kg-1dm h-1 in most reactors. Air filled porosity was found as a key parameter regarding process scale-up, with a minimum value of 80% as necessary to proper scaling up to 22 L. Process robustness was statistically demonstrated as no significant differences in conidia production, moisture and pH were found at different reactor heights using both substrates in most 22 L reactors tests. Consequently, SBR operation has been presented as a reproducible method to overcome traditional packed-bed drawbacks while also improving SSF performance in comparison to traditional industrial SSF processes. 1. Introduction of the most interesting fungal biocontrol agents is Trichoderma spp., mainly due to its recognized antagonistic capabilities, presenting great Massive use of chemical pesticides presents a threat to both human success against soil-borne diseases [7,8]. Several agro-industrial resi­ health and to the environment, urging a shift to greener options [1,2]. dues have been used to produce fungal conidia by SSF using various Fungal biopesticides represent one of the most attractive options among Trichoderma strains, effectively generating an added value on obtained biocontrol agents, as they present no harm to humans, crops or eco­ products due to waste valorization [9]. A comprehensive list of used systems while being highly pathogenic to more than 1000 insect species substrates (including agro-industrial wastes) with the genera Tricho­ [3,4]. A wide range of culture media can be used to produce fungal derma (among others) was reviewed by Sala et al. [4]. biopesticides, both by submerged fermentation (SmF) and solid-state Different reactor configurations have been reported to produce fermentation (SSF). Although each system presents several advantages fungal biocontrol agents by SSF. From static tray reactors to agitated and drawbacks [5], SSF (defined as a process that occurs in the absence rotatory drums and both static or agitated packed beds, each design has or near absence of free water) offers lower costs in comparison to SmF, several advantages and drawbacks. Packed bed reactors (mainly pre­ mainly related to the use of agro-industrial wastes as substrates, serving sented as cylindrical columns) facilitate oxygen availability via contin­ both as nutrient and support for fungal growth and sporulation [6]. In uous forced aeration as well as maintaining constant moisture when air addition to this, aerial conidia, which can only be produced by SSF, are supplied is previously saturated with water. However, the main disad­ the primary infective propagule of most fungal biopesticides [2], making vantage of using packed bed reactors lies in heat removal, causing SSF preferred over SmF as fungal biopesticide production method. One important difficulties in process scale-up [10]. * Corresponding author. E-mail address: raquel.barrena@uab.cat (R. Barrena). https://doi.org/10.1016/j.cej.2021.131620 Received 4 May 2021; Received in revised form 29 July 2021; Accepted 1 August 2021 Available online 11 August 2021 1385-8947/© 2021 The Author(s). Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). A. Sala et al. Chemical Engineering Journal 425 (2021) 131620 A possible method to improve packed-bed reactors operation lies in 2.2. Raw materials sequential batch reactor operation (SBR) [11,12]. This strategy elimi­ nates the requirements of preparing fresh inoculum for each batch Rice husk (Husk Ventures S.L., Barcelona) and beer draff (Cervesa (reducing the quantity of required inoculum to process the same amount del Montseny S.L., Sant Miquel de Balenyà, Barcelona) were used as of substrate) and has already been tested using SSF technology to pro­ substrates for fungal conidia production. Rice husk was stored at room duce cellulases using coffee husk [11] and to produce rose-like aroma temperature (20-25℃) and beer draff was stored frozen before its use. compounds using sugarcane bagasse [12]. Regarding heat removal, the Different conservation conditions were used due to the different prop­ use of high porosity substrates to allow maximum heat transfer is a erties of the materials, with rice husk presenting a moisture lower than possible path to overcome, or at least reduce, heat transfer effects on 10% while the value for beer draft was over 80%. In order to maintain fungal growth and sporulation. Achieving accurate porosity measure­ values of 55–60%, initial moisture was adjusted before inoculation by ments is still difficult, which highlights the role of air-filled porosity adding the necessary volume of water when using rice husk and the (AFPR) as a more reliable value of the space in the available space in the necessary quantity of wood chips (Acalora, Ivars d’Urgell) when using matrix for air content and movement [13]. Substrates presenting high beer draff: 70 beer draff/30 wood chips (w/w) when working with 1.5 L AFPR such as rice husk have been previously tested [14]; whereas the volume reactors and 40 beer draff/60 wood chips (w/w) when working use of highly porous bulking agents of very low respiration activity just at 22 L. Wood chips were added to beer draff in order to ensure a value of as wood chips also helps at maximizing heat removal throughout the AFPR in the range of 40–80%, stated as proper for composting processes packed bed [15], being necessary when working with residues pre­ [22], necessary to ensure a proper air circulation throughout the packed senting low AFPR values such as beer draff [16]. Both rice husk and beer bed. Raw materials and initial fermentation mixtures characterization draff are mass produced worldwide. Rice husk is a by-product of rice, for all performed tests is presented in Table 1. All substrates were third agricultural commodity in terms of production by the year 2014, autoclaved (121℃ for 30 min) prior to inoculation, considering the 10% with production growing each year (estimated on 215 M tones on 2018 inoculum volume in the initial moisture calculations. Autoclaving of using the correlation of 0.28 kg rice husk obtained per kg of milled rice) substrates was performed prior to their use at all reactor’s scales studied. [17–18]. Beer draff is easy to obtain as is a by-product of the brewery industry, one of the most productive beverage industries in the world, 2.3. Solid-state fermentation generating large quantities of brewer’s spent grain or beer draff, a solid leftover obtained after the fermentation process which is primarily used Different SSF tests were performed at two packed-bed reactor scales as animal feed [19–20]. Additionally, inoculant age plays an important (1.5 and 22 L) using two agro-industrial wastes with different biode­ role in fungal growth since conidia germination tends to decrease as gradability as main substrates (rice husk and beer draff). Previous culture ages in most strains, leading to a quality loss [21]. As such, it studies in 0.5 L reactors were performed to determine the preferred should be investigated prior to the use of any SBR strategy when working with fungal cultures. Table 1 In a context of increasing relevance on environmentally-friendly Raw substrates and mixtures characterization for all used substrates. production processes, biopesticide production using SSF emerges as a Parameter/ RH1 RH2 BDr1 WC1 70/30 40/60 great tool to achieve this objective. However, most of the actual fungal Substrate w/w w/w SSF fermentations using packed bed bioreactors have been performed at (BDr/ (BDr/ lab scale [4], while achieving more results at higher scales has become a WC)2 WC)2 necessity [10]. Assuming its challenges, a viable process where inoc­ MC (%) 10.2 58.7 76.4 ± 9.7 ± 63.8 ± 55.2 ± ulum production does not represent a hindrance neither for equipment ± 0.1 ± 0.4 0.5 0.3 5.1 4.8 nor for economy is needed. In addition, organic wastes with different OM (%) 82.6 82.6 93.6 ± 98.4 ± 95.0 ± 96.5 ± biodegradability can be used as substrate in SSF. The proper scaling-up ± 2.6 ± 2.6 0.9 0.6 1.4 1.2 pH 5.7 ± 6.3 ± 6.5 ± 5.1 ± 5.7 ± 0.2 5.1 ± 0.8 of the SBR strategy using packed-bed reactors would help at overcoming 0.3 0.3 0.3 0.2 all of the previously mentioned SSF challenges. To the authors’ knowl­ Carbon (%) 40.3 40.3 48.2 ± 46.9 ± 47.8 ± 47.4 ± edge, scale-up of fungal SSF in packed bed reactors under a SBR strategy ± 0.8 ± 0.8 0.7 0.6 0.6 0.6 has not been previously tested and it can be a starting point to reduce Hydrogen (%) 5.2 ± 5.2 ± 6.9 ± 6.2 ± 6.7 ± 0.3 6.5 ± 0.3 0.2 0.2 0.3 0.3 associated costs by overcoming inoculum production problems of solid- Nitrogen (%) 0.4 ± 0.4 ± 4.04 ± 0.4 ± 3.0 ± 0.6 1.9 ± 0.6 state operation at commercial scale, reducing the quantity of inoculum 0.1 0.1 1.2 0.2 necessary to process the same amount of substrate by eliminating fresh Sulphur (%) <0.1 <0.1 0.1 ± <0.1 <0.1 <0.1 inoculum preparation in each batch. The aims of this paper are: i) to 0.01 develop a robust, reproducible and scalable process for Trichoderma C/N ratio 85.4 85.4 12.6 ± 117.4 16.0 ± 25.0 ± 2.5 ± 13.6 6.2 6.2 harzianum (TH) conidia production in packed bed reactors using agro- ± ± 15.2 15.2 industrial wastes as substrates, ii) to present and adapt SBR as a TSC (mg g- 17.9 17.9 123.4 13.1 ± 96.7 ± 67.9 ± feasible operation strategy to substitute traditional batch in packed bed 1 dm) ± ± ± 0.4 10.3 5.3 TH fungal growth and iii) to test SBR using substrates presenting 0.2 0.2 9.3 AFPR (%) 90.3 85.6 64.0 ± 95.3 ± 70.3 ± 81.2 ± different biodegradability and AFPR in order to compare its effect to­ ± 0.5 ± 0.6 0.3 0.5 0.9 0.5 wards the reactors’ temperature. DRI 1.2 ± (-) 6.5 ± (-) (-) (-) (g O2 kg- 0.1 0.4 2. Materials and methods 1 OM h-1) Max sOUR (g 0.6 ± 0.8 ± 3.2 ± 0.4 ± 2.5 ± 0.7 1.7 ± 0.4 O2 kg-1dm 0.2 0.1 0.4 0.1 2.1. Fungal strain h-1) COC6d (g O2 1.5 ± 1.5 ± 16.8 ± 1.0 ± 12.1 ± 7.3 ± 0.7 All tests were carried out using TH strain CECT 2929 (isolated from kg-1dm) 0.3 0.3 2.2 0.2 1.0 soil in the United Kingdom before 23/01/1991) and provided by RH: rice husk; BDr: beer draff; OM: organic matter; WC: wood chips; w/w: Spanish Type Culture Collection (CECT). The original strain was pre­ weight/weight; MC: moisture content; C/N: carbon/nitrogen; TSC: total sugar served at − 80℃ in sterile cryovials (FisherbrandTM, Fisher Scientific S. content; AFPR: air filled porosity; DRI: dynamic respirometric index; sOUR: L.) containing 10% glycerol, as established by the strain provider. TH specific oxygen uptake rate; COC6d: cumulative oxygen consumption at day 6; 1: was cultured in malt extract agar at 25℃ for 6–8 days before use. raw material; 2: initial batch material. 2 A. Sala et al. Chemical Engineering Journal 425 (2021) 131620 conditions for the fermentations presented in this paper, more infor­ basket were cleaned with water, bleach and alcohol before and after mation on them can be found in Sala et al [23]. Although finding these every batch, as they could not be autoclaved due to the reactor’s volume. conditions using higher volume reactors (1.5 L) would have been more Inoculation was performed in ambient conditions in the laboratory representative, it has not been considered due to the time and effort before loading the substrate directly into the basket, using previously associated to each test. Moreover, Design of Experiments technique was cleaned trays and appropriate volumes to ensure homogeneous distri­ applied with 0.5L reactors ensuring statistical reliability. First fermen­ bution of the inoculum throughout the packed bed. tations were carried out in 1.5 L reactors because of their easily opera­ tion. The 22 L reactor was used to validate and study in detail the main 2.3.4. SSF sequential batch operation parameters of the proposed process. Previous inoculant age test was also SBR operation was performed in the same way both at 1.5 L and 22 L performed. Most relevant parameters used to monitor SSF evolution scales. A total of 4–5 batches were charged in each SBR operation. A were conidia counting, respiration analyses (by means of sOUR) and schematic representation of the SBR process is presented in Fig. 1. temperature, as explained later. pH and moisture were determined for The fungal inoculum of the first reactor in the series was cultured as initial and final SSF materials. aerial conidia as described in section 2.1. Conidia were harvested and resuspended using 10 mL Tween 80 0.1%. Conidia in the suspension 2.3.1. Inoculant age test were counted using Neubauer chamber (BrandTM 717805) and diluted A test to determine the optimum day to extract conidia as inoculum to 6.6x106 conidia per gram dry matter (g-1dm) in all tests using Tween for consequent SBR fermentations was performed. A 22 L rice husk batch 80 0.1%. The inoculum volume in each reactor was 10% of its total was run for 9 days. Sampling of this reactor was performed in days 4, 6, 8 volume. and 9. Sampling times were chosen according to results on optimal Inoculum for the following batches of the sequence was obtained by conidia production time obtained in previous experiments [23]. In all liquid extraction of fungal conidia contained in the solid material of the these samples (25 g each), conidia were extracted using the 125 mL of previous batch in the day determined through to inoculant age test Tween 80 0.1% and used as inoculum for triplicate 0.5 L reactors using (section 3.1). Conidia were extracted from the calculated quantity of rice husk as substrate. To determine best inoculant age, conidia were fermented solid material using a 1/5 ratio (solid/liquid, w/w, using counted 6 days from the start of the 0.5 L reactors’ fungal growth using Tween 0.1%) and diluted to 6.6x106 conidia g-1dm. Neubauer chamber (BrandTM 717805). To follow the evolution of the process and assuming 6 days as the maximum conidia productivity time as obtained in previous experi­ 2.3.2. Experimental set-up for 1.5 L reactors ments [23], sampling was performed from two to three times in each 1.5L Reactors consisted of polyvinyl chloride cylindrical reactors of reactor on days 4, 6 or 8 from the beginning of each batch. In 1.5 L 0.21 m height and 0.105 m internal diameter, corresponding to a reactors, samples were alternatively taken from a different reactor of the working volume of 1.35 L. A total of 300 g of each substrate were fer­ triplicate each day, leaving at least one reactor untouched for all the mented per triplicate for 5–8 days, according to results on optimal fermentation time and sampling all three reactors in the last sample of conidia production time obtained in previous experiments [23]. Tem­ the fermentation. In 22 L reactors, samples during fermentation were perature sensors (standard Thermochron iButton device, Maxim Inte­ taken from the surface area. A different approach was taken for samples grated, U.S.) were used to obtain accurate temperature profiles at corresponding to the end of each batch, being sampled as 10 equally different reactor heights (0, 5, 10, 15 and 20 cm in each reactor) and weighted samples at different bed heights (assuming 0 cm height at the ambient temperature. Constant aeration (0.18–0.33 mL min− 1 g-1dm for bottom of the bed and 40 cm as maximum height). These samples were rice husk and 0.71–0.96 mL min− 1 g-1dm for beer draff) was continu­ divided into three groups: upper samples (28–40 cm height), medium ously provided by means of a mass flowmeter (Mass-Stream D-6311, samples (12–28 cm height) and bottom samples (0–12 cm height) and Bronkhorst, NL). The oxygen percentage in the output gases was were used to analyse conidia production, temperature and moisture measured by an electrochemical O2-A2 oxygen sensor (Alphasense, UK). variability at different reactor heights using a one-way ANOVA (p < Data analysis was performed by a non-commercial tailor-made software 0.05 confidence) with the Tukey test using the software Minitab 17 Arduino® based that calculates the respiration rates as explained in (Minitab Ltd.). section 2.3.3. Reactors were loaded and mixed in a laminar flow chamber with the 2.3.5. Oxygen uptake rate appropriate volume of inoculum, ensuring a homogeneous distribution On-line oxygen consumption has been considered as an indicator of and sterile conditions. Prior to the start of each test, all reactors were the biological activity. Specific oxygen uptake rate (sOUR) was calcu­ cleaned with water and bleach to prevent possible contamination, as lated according to Puyuelo et al. [24], expressed as 1 h average value they could not be autoclaved for them being made of polyvinyl chloride. (sOUR) (Equation (1)) and recorded on-line in order to provide an in­ dicator of the biological activity: 2.3.3. Experimental set-up for 22 L reactor In this case, the reactor consisted of a cylindrical stainless-steel vessel PÂ⋅32Â⋅60Â⋅103 sOUR = FÂ⋅(0.209 − yO2 )Â⋅ (1) with a removable basket of 48 cm height × 24.5 cm diameter, presenting RÂ⋅T Â⋅DW a total volume of 22 L. In all tests, the working volume was approxi­ where: sOUR is the specific Oxygen Uptake Rate (g O2 kg− 1 dm h− 1); F, mately 90% of the reactor capacity. When working with rice husk, 3000 airflow (mL min− 1); yO2, is the oxygen molar fraction in the exhaust g of non-inoculated substrate were loaded, while when working with gases (mol O2 mol− 1); P, pressure of the system assumed constant at beer draff, 4000 g of mixture with wood chips were loaded into the 101325 Pa; 32, oxygen molecular weight (g O2 mol− 1 O2); 60, conver­ basket. Air supply and acquisition data system were the same as in sion factor from minute to hour; 103, conversion factor mL to L; R, ideal section 2.3.1. Constant specific aeration in the ranges of 0.27 – 0.42 mL gas constant (8310 Pa L K− 1 mol− 1); T, temperature at which F is min− 1 g-1dm for rice husk and 0.53 – 0.87 mL min− 1 g-1dm for beer draff measured (K); DW, initial dry weight of solids in the reactor (g); 103, was provided. Temperature of the solid media was monitored on-line in conversion factor g to mg. the lower half of the bed by means of a temperature probe (Pt-100 The area below the O2 consumption curve was also determined, sensors, Sensotrans), while also obtaining accurate temperature profiles which represents the cumulative oxygen consumption (COC), also at different heights of the bed (0, 12, 24 and 36 cm) both at the centre of providing information on the biological activity in the SSF reactor and as the packed bed and at the basket wall using the temperature sensors a direct measure of the degraded carbon [25]. described above. Room temperature was also monitored. To work in conditions as sterile as possible, the reactor and the 3 A. Sala et al. Chemical Engineering Journal 425 (2021) 131620 Substrate Fresh inoculum (plate) Substrate Substrate (10% working volume) SSF 1 spore SSF 2 spore extraction extraction Inoculum Inoculum (10% working (10% working 9% product volume) 9% product volume) SSF reactor 1 SSF reactor 2 SSF reactor n 91% product 91% product 91% product Fermented solids for spore extraction Fig. 1. Schematic representation of SBR operation on 1.5L or 22L reactors. Part of the Figure was provided by Biorender (https://biorender.com/). 2.4. Conidia counting AFPR was calculated for all used substrates according to Equation (4) as presented by Richard et al. [13]: To determine fungal spore concentration, conidia counting method (( ) ( )) 1 − DM DM*OM DM(1 − OM) described in previous experiments [23] was used. Briefly, a Neubauer AFPR = 1 − BDt + + (4) chamber (BrandTM 717805) was used. 10 g of sample (conidiated sub­ DW PDOM PDash strate) were mixed with 50 mL of Tween 80 0.1%, shaken for 20 min at where: AFPR, air-filled porosity (%); BDt, total bulk density on a wet 150 rpm and appropriately diluted before counting. All cell counts were basis (kg m− 3); dm, dry matter on a wet basis (%); OM, organic matter performed per triplicate and related to the dry matter present in the on a dry basis (%); Dw, water density (1000 kg m− 3); PDOM, organic reactor at the counting time, following the equation: fraction particle density (1600 kg m− 3) and PDash, ash particle density Nºofconidia EV SWW (2500 kg m− 3). Concentration = Â⋅ Â⋅ (2) CVÂ⋅DF SWW SDM where: Concentration is the conidia concentration in the initial tube (conidia g-1dm); n◦ of conidia, the counted conidia in the Neubauer chamber at a known dilution; CV, Neubauer chamber counting volume (mL); DF, dilution factor of the counting tube; EV, extraction volume (mL); SWW, sample wet weight (g ww); SDM, sample dry matter (g dm). 8x108 2.5. Total sugar content analysis a Produced conidia (conidia g dm) Total sugar content was empirically determined using the Anthrone 6x108 method, using glucose for the calibration curve [26]. Total sugar content -1 was expressed as gram of glucose equivalent per gram of dry matter b according to equation:Totalsugarcontent = CP Â⋅V (3) b where: Total sugar content (g g-1dm); C, concentration of glucose 4x108 equivalents (g L-1); P, weight of dry sample analysed (g); V, total volume of the supernatant (L). c 2x108 2.6. Analytical methods Moisture (%), dry matter (%), organic matter (%) and pH have been 0 determined for initial and final samples using standardized methods Day 4 Day 6 Day 8 Day 9 [27]. C/N analysis was performed by means of chemical elemental Process time (d) analysis in all initial samples. Results are shown in Table 1. Results are shown in Table 1. C/N analysis includes carbon, nitrogen, hydrogen and Fig. 2. Conidia production using TH inoculum obtained at different process sulphur analyses for raw substrates and mixtures used in the presented times from a previous SSF assay. Different letters indicate significant differences fermentations. between the evaluated groups (p < 0.05) based on the Tukey analysis. 4 A. Sala et al. Chemical Engineering Journal 425 (2021) 131620 3. Results and discussion 3.2. Rice husk sequential-batch reactor: Scaling from 1.5 L to 22 L 3.1. Determination of the optimal fermentation time for inoculum Fig. 3 shows obtained profiles in rice husk SBR operation in both extraction to use in a sequential-batch operation scales; Fig. 3a shows conidia production, sOUR and temperature in 1.5 L reactors, while Fig. 3b shows same parameters for 22 L reactors. Fig. 2 shows conidia productions using inoculum extracted from the In both scales, final conidia production on each reactor decreased fermentation reactor at days 4, 6, 8 and 9. Conidia concentration from halfway, starting around 1.4x109 ± 5.0x108 conidia g-1dm in batch 1 the inoculum extracted at day 4 was significantly higher to the rest of the and decreasing to values around 6.0x107 ± 2.3x107 conidia g-1dm in tested inoculant ages’. Thus, 4 days was established as the optimum time batch 4 or 5. Maximum conidia production was achieved in day 6 of for inoculum extraction. fermentation in all batches from 1 to 3, however, in batches 4 or 5 in Inoculant age relevance has been highlighted for various fungal both scales it was extended, achieving maximum conidia production in strains, as conidia quality tends to diminish with age. This is the case of day 7. Conidia production reduction throughout the batches was Smith and Edgington [28] using Metarhizium spp., Hallsworth and apparently caused by the appearance of contaminant Aspergillus niger Magan [29] using Beauveria bassiana and Múñiz-Paredes et al. [30] using (AN) from batch 3 to batch 5. At both scales, AN conidia concentration Isaria fumosorosea. However, and to our knowledge, this is the first time (also presented in Fig. 3a and 3b as white dots) doubled in each batch, it has been tested using TH. Despite its relevance, inoculum age is not starting at values close to 9.0x106 ± 2.0x106 conidia g-1dm and rising to often studied in fungal optimization processes [21]. 8.3x107 ± 3.0x107 conidia g-1dm in batch 5 in 1.5 L SBR, surpassing TH Fig. 3. Rice husk SBR profiles (conidia production, temperature, sOUR and AN conidia production) in 1.5L reactors (a) and 22L reactors (b). Batch 1: black. Batch 2: brown. Batch 3: orange. Batch 4: green. Batch 5: blue. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.) 5 A. Sala et al. Chemical Engineering Journal 425 (2021) 131620 conidia production in the last batch. No fifth batch was performed at 22 Barrena et al. [15]. L scale due to its behaviour being similar to 1.5 L. AN is a common Obtained values for moisture, pH and total sugar content were contaminant in rice and its by-products [31–33]. Despite TH’s anti­ similar between scales: moisture ranged from 50 to 60% in most batches fungal properties [7], AN conidia were still able to grow in the substrate, and pH started at values close to 6 and raised to values close to 7 at the being capable of withstanding autoclaving as reported in previous works end of all batches. Similar values for both parameters were observed at [23]. Conidia production loss suggests AN growth started in the second both scales. AFPR could easily be maintained at correct values in order to batch, taking advantage of inoculum quality loss in comparison to pure ensure proper oxygen transfer at both scales (around 85%, as shown in inoculum extracted from plates used in the first batch, even though AN Table 1, being superior to the highest values of 80% indicated for the conidia could not be detected when counting due to their low numbers composting process by Ruggieri et al. [22]). Despite all parameters being in comparison to TH conidia. With this result, production using rice husk adequate for TH growth and sporulation according to Zhang and Yang at higher scales is still possible if working with single batch strategy [34], co-culture growth was observed from batch 3 onwards. Regarding using pure inoculum extracted from fresh plate. AN growth parameters and according to several authors [35,36], TH and In terms of biodegradability, respiration profiles were similar in all AN co-culture growth was possible within the observed parameters’ batches working at both scales, reaching maximum values close to 1 g O2 ranges, with both of them being present at least from batch 2 onwards. kg-1dm h-1 at similar times in most of the batches, being similar to the However, AN growth over TH suggests faster growth of contaminant in ones presented in previous works using the same substrate [23]. Ac­ rice husk in comparison to TH, promoting its prevalence in the co- cording to Barrena et al. [15], rice husk is a substrate that presents low culture in batch 5 in the 1.5 L SBR and assuming similar results would biodegradability (DRI lower than 2 g O2 kg-1 OMh− 1). In consonance, have been obtained in case of performing a fifth 22 L batch. temperature profiles in both scales also show low potential biodegrad­ Rice husk has been found as an easy to scale-up substrate due to its ability, as even at 22 L scale mean temperatures in the reactor never naturally high porosity and low biodegradability, greatly reducing surpassed 32℃, starting approximately at 25℃ in all fermentations. possible drawbacks caused by heat accumulation. However, despite Higher temperature variation is to be expected when using substrates successful scaling-up of the process (achieving similar results between that present high or even moderate biodegradability, according to both tested scales), presence of AN in the substrate suggests not to follow Fig. 4. Beer draff SBR profiles (conidia production, temperature and sOUR) in 1.5L reactors (a) and 22L reactors (b). Batch 1: black. Batch 2: brown. Batch 3: orange. Batch 4: green. Batch 5: blue. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.) 6 A. Sala et al. Chemical Engineering Journal 425 (2021) 131620 a SBR strategy when using rice husk. In fact, AN gradually takes over the In terms of biodegradability, all obtained respiration profiles were culture until it surpasses TH in terms of conidia concentration. Conse­ similar, reaching maximum values close to 3.5 g O2 kg-1dm h-1 at quently, a batch strategy using fresh inoculum appears to be the most comparable times in nearly all of the batches, with the only exception of optimal to maintain conidia concentration at its maximum, as best batch 5 in 22 L SBR, which only reached 2.5 g O2 kg-1dm h-1. These performances were obtained in the first batch (fresh inoculum) at both oxygen consumption rate values indicate higher biodegradability when scales and could not be replicated in subsequent batches. As such, this comparing to rice husk. Much higher total sugars available (80–88 mg g- 1 strategy could be performed not only using rice husk as substrate but dm) combined with higher values of DRI, sOUR and COC6d also indi­ also when working with substrates which pose similar difficulties in cated higher substrate biodegradability when comparing to rice husk. terms of sterilization, which are common when working in SSF with Mean temperatures in batch 5 were lower than those obtained in the rest agro-industrial wastes due to substrate heterogeneity [37]. of batches, being even lower than 20℃ at the beginning of the fermentation. Due to the relevance of temperature in fungal growth 3.3. Beer draff sequential-batch reactor: Scaling from 1.5 L to 22 L [23,29], lower values of this parameter might be the cause of fungal growth and conidia production lengthening time in batch 5. Even Fig. 4 shows obtained profiles in beer draff SBR scaling. Contrarily to though mean temperature profiles at both scales did not highly differ rice husk SBR results, different performances were observed between 1.5 from profiles when working with rice husk, using a substrate with higher L and 22 L SBR reactors. In 1.5 L reactors (Fig. 4a) conidia concentration potential biodegradability caused temperature gradients in the reactor. was sustained for 3 consecutive batches, showing no significant differ­ Packed bed bioreactors often present problems related to temperature ences among them, obtaining values between 1.6x109 conidia g-1dm ± gradients due to heat removal difficulties [40], as such, the effect of 3.2x108 and 2.1x109 conidia g-1dm ± 3.7x108. However, batch 4 yielded temperature in different areas of the reactor will be discussed in depth in a significantly low conidia production of 5.6x108 conidia g-1dm ± section 3.4. It can be concluded that observed differences in batch 5 in 9.7x107. Maximum conidia production was achieved in day 6 of 22 L SBR were caused by several non-optimal range values in the ana­ fermentation in batches 1 and 2; however, in batches 3 and 4 fermen­ lysed parameters rather than lower inoculum quality as might have tation time was extended and maximum conidia production was ach­ happened at 1.5 L scale. Optimal values for TH growth and sporulation ieved in day 8. In contrast, conidia concentrations at 22 L (Fig. 4b) was for all process parameters will be discussed in section 3.4. sustained in all batches, obtaining values between 1.7x109 conidia g- Successful scaling from 1.5 L to 22 L has been achieved using beer 1 dm ± 1.1x108 and 2.2x109 conidia g-1dm ± 3.7x108, showing no sig­ draff as substrate and wood chips as bulking agent in a SBR operation. nificant differences between all 5 batches. Maximum conidia concen­ However, SBR performance differed between scales: while at 1.5 L tration was achieved within 6 days in 4 out of 5 batches, while in batch conidia concentration decreased from batch 4 onwards due to loss of 5, 8 days were needed. Longer time might have been due to differences inoculum quality, at 22 L scale 5 batches were performed achieving in temperature profiles between batch 5 and the rest of the SBR batches. similar maximum conidia concentrations. Differences between the two AN contamination was not detected at any scale, confirming the sub­ scales have been mainly caused by the use of different substrate mix­ strate change as a valid decision. tures, being 70–30% in 1.5 L and 40–60% in 22 L (as presented in section Differences in performance between SBR at 1.5 L and SBR at 22 L 2.2). These results suggest that a minimum AFPR value of around 80% is were attributable to the combined effects of three parameters: AFPR, pH needed to ensure proper fungal growth when working with packed bed and moisture. As presented in Table 1, initial AFPR was different be­ reactors, highlighting the need to find the optimal AFPR value when tween scales: 72.6 ± 0.7 in 1.5 L vs 81.2 ± 0.5 in 22 L. These differences scaling up SSF fungal conidia production processes using packed bed were caused by substrate proportions used at each scale, being 70/30 w/ reactors operating with and SBR strategy. Particle size relevance in w (beer draff/wood chips) at 1.5 L and 40/60 w/w (beer draff/wood solid-state fermentation studies has been highlighted by Yazid et al. chips) at 22 L. A failed 22L batch using proportion 70/30 is shown in [37]. Small particle size provides larger surface area for fungal growth Figure S1 in the supplementary material. TH conidia production was not while being prone to agglomeration and difficulties in oxygen transfer. achieved in this batch. Mean temperatures superior to 40℃ were ach­ In contrast, large particle size provides better oxygen transfer and re­ ieved, while sOUR reached values close to 8 g O2 kg-1dm h-1. This duces heat accumulation at the cost of limiting surface growth area. behaviour completely differed in comparison to any of the batches Higher surface area helps at maximizing mycelial growth, which is shown in Figs. 3 and 4, achieving much higher values both for tem­ necessary for correct fungal sporulation. Additionally, mycelial growth perature and sOUR. 1.5 L substrate mixture was not adequate for 22 L does not affect substrate porosity, meaning it should be maximized reactor due to substrate compaction, which highly reduces AFPR and before sporulation [41]. Balance between different sizes in large reactors oxygen transfer, subsequently difficulting fungal growth and sporula­ is mandatory to ensure proper fungal growth and sporulation. These tion and facilitating the appearance of contaminants [38]. AFPR findings are highly relevant to fungal SSF, as they establish a repro­ adjustment was key for the success of both scale-up and SBR strategy ducible method to overcome SSF traditional drawbacks while defining performance, as 22 L SBR had 5 consecutive batches which presented biodegradability and AFPR as the key parameters in SSF scale –up. The the same behaviour, with the possibility of lengthening the process even results presented open the possibility of performing the current process more, while 1.5 L SBR only had 3. In addition, pH was also significantly using packed-beds at higher scales. different between scales: while 1.5 L behaviour was similar to that observed for rice husk (with pH starting at values close to 5.5 and ending 3.4. 22 L reactor global analysis performance close to 7.5–8), in 22 L reactors pH started at more acidic values (4.5–5), ending in most cases at values lower than 6.0. These variations might In order to test the robustness and reproducibility for fungal conidia also be attributed to the use of different proportions of substrate and production in packed bed reactor operating of a SBR strategy, statistical bulking agent, being batch 1 in 22 L SBR the one with the lowest conidia analyses were performed using data collected from sampling of the final concentration in this test, acidic pH might have been favourable both for solid material of each 22 L batch performed with both substrates (4 TH fungal growth and conidia production, as presented by some authors batch using rice husk and 5 batch using beer draff). As explained in [34,38]. Regarding moisture, while in 1.5 L SBR this parameter ranged section 2.3.4, samples points were divided depending on their height in from 60 to 67%, it was much lower in most batches of the 22 L SBR, the packed bed. ranging from 51 to 58%, both of them corresponding to the optimum Fig. 5 shows mean values and standard deviations obtained when range presented by most Trichoderma strains [39]. Optimum range for analysing samples at the end of each batch depending on their height. TH conidia production is of 55–60% according to previous works [23], Results are shown for conidia production, moisture and pH in all per­ suggesting better moisture adjustment in the 22 L SBR. formed 22 L batches. When comparing process parameters within the 7 A. Sala et al. Chemical Engineering Journal 425 (2021) 131620 a) 70 8.0 b) a c) a a a a a a a b b Conidia production (conidia g-1 dm) a 60 a a a a a b b a a,b b a,b a a 109 b b a 6.0 50 b Moisture (%) 40 a 4.0 pH a a 30 108 a a 20 2.0 10 107 0 0.0 Batch 1 Batch 2 Batch 3 Batch 4 Batch 1 Batch 2 Batch 3 Batch 4 Batch 1 Batch 2 Batch 3 Batch 4 28-40 cm 12-28 cm 0-12 cm 70 8.0 d) e) f) aaa aa aa a b a a a a aa aa a b a aa a aa,b aa,b a,b Conidia production (conidia g-1 dm) 60 a a aa a 109 6.0 aa a a aa 50 a a,b b aa b Moisture (%) 40 4.0 pH 30 10 8 20 2.0 10 0 0.0 107 Batch 1 Batch 2 Batch 3 Batch 4 Batch 5 Batch 1 Batch 2 Batch 3 Batch 4 Batch 5 Batch 1 Batch 2 Batch 3 Batch 4 Batch 5 Fig. 5. Mean values and standard deviations obtained in samples collected at different reactor heights at the end of all 22L batches. a) Rice husk conidia production, b) Rice husk moisture, c) Rice husk pH, d) Beer draff conidia production, e) Beer draff moisture and f) Beer draff pH. Different letters indicate significant differences between the evaluated groups (p < 0.05) based on the Tukey analysis. same batch, little significant differences are shown thorough the packed both rice husk and polyurethane foam as substrate and inert support for bed in both substrates, while no patterns are followed in terms of Trichoderma asperellum conidia production, although their analysis was maximum conidia production height in the reactor. It can be assumed based on airflow rate variation while the work presented in this paper is that conidia production does not depend on bed height in a 22 L rice not focused in this parameter. However, in beer draff batches, radial husk or beer draff packed bed reactor, even though it could still be temperature differences were observed, as temperatures at the reactors’ dependent on bed height at higher scales. This is consequent with little wall and the centre of the bed were different during all the fermentation moisture and pH variations shown in all batches, with nearly all the process, with differences ranging from minimal 2-3℃ to more than 10℃ compared samples not presenting significant differences with the rest of depending on fermentation time, effectively creating different zones in the samples in the same batch. When significant differences exist, it the reactor in terms of radial temperature. Higher temperatures were always corresponds to a slight variation in terms of absolute numbers. achieved in the centre of the bed in beer draff reactors, which is These data highlight the robustness of the process, as both tested sub­ consequent with the higher respiration indexes observed when using strates packed beds had similar physical properties at all heights. In beer draff in comparison to rice husk, leading to an overall increase of addition, pH differences between substrates are clearly shown in Fig. 5c) the bed’s temperature. Similar approach was presented by da Cunha and 5f). Lower pH values were achieved with beer draff in comparison to et al. [46] working with Metarhizium anisopliae and a mixture of rice and rice husk and corresponding to the batches which yielded highest con­ sugarcane bagasse in a similar packed bed bioreactor to the one pre­ idia productions, meaning acidic pH might have been beneficial for TH sented in this study. However, their analysis was focused on axial tem­ growth and sporulation. These results differ from the majority of the perature, finding relevant temperature differences depending on the references in bibliography, as TH growth and sporulation optimums are substrate axial position, behaviour that has not been studied in this normally located near neutral pH [34,42], even though TH can grow and paper. As no significant differences between axial conidia productions sporulate within an initial pH range of 3–9 according to Zhang and Yang have been found, we can assume that observed axial temperature dif­ [34]. These differences in behaviour when comparing with literature ferences did not negatively affect conidia production, although in spe­ could have been caused by using a specific Trichoderma strain which cific moments corresponding to the maximum biological activity, could present better results when working at acidic pH. Some Tricho­ differences of 10-15℃ between reactor wall and centre of the packed derma spp. strains have been demonstrated to work optimally under bed were observed. Given the high influence of temperature on fungal acidic pH conditions [43]. conidia production [23,29], it can be assumed that observed differences Temperature variation in different areas of the 22 L reactors (centre did not significantly affect conidia production. Although it has not been of the packed bed, close to the reactor’s wall, mean values and external analysed in this paper, Finkler et al. [47] described heat transfer in a SSF temperature) is shown in Figure S2 in the supplementary material. packed-bed reactor using data obtained at various reactor heights, Despite differences between reactors and substrates, in most cases demonstrating an axial uniformity of the packed-bed which might also analysed temperatures were close to the optimal growth temperature have happened in this work using both presented substrates. range for most Trichoderma strains, being 25-30℃ according to Kubieck Fig. 6 shows contour and mesh graphs of obtained data corre­ and Harman [44]. Reactors corresponding to rice husk showed little to sponding to last samples of all 22 L beer draff performed batches, pre­ no difference in temperature values between different reactor areas, senting conidia production dependence on moisture and pH. A defined with minimal temperature differences being of a maximum of 3℃, area of maximum conidia production was found, corresponding to a effectively achieving similar temperature on all the packed beds’ vol­ moisture range of 56–60% and a pH range of 5–6. Both ranges were ume. This behaviour is comparable to the one obtained by Barrera et al. consequent with results obtained in other works performed with similar [45], who reported advantageous temperature axial gradients using strains [23,34]. 8 A. Sala et al. Chemical Engineering Journal 425 (2021) 131620 7.0 a) 6.5 6.0 pH 5.5 5.0 0 52 54 56 58 60 62 5.0x10e8 1.0x10e9 Moisture (%) 1.5x10e9 2.0x10e9 2.5x10e9 3.0x10e9 b) -1 dm) 3.0x109 tion (conidia g 2.5x109 2.0x109 1.5x109 Conidia produc 109 62 5.0x108 60 58 0 56 ) 7.0 (% 6.5 e 6.0 54 tur 5.5 ois 5.0 52 M pH Fig. 6. 3D graphics (x axis moisture, y axis pH and z axis conidia production) corresponding to results obtained in last samples of all 22L beer draff batches. a) Contour graph, b) 3D mesh graph. These analyses demonstrate that a reproducible and robust SBR implementing a SBR strategy. process has been achieved when fermenting beer draff complemented Future work should be focused on further scaling up the SBR strategy with wood chips in 40/60% w/w proportion, as obtained results have using beer draff complemented with the adequate quantity of wood not been significantly different for 5 consecutive batches. Aside from chips. In order to ensure correct fungal growth and sporulation, AFPR temperature, values of relevant parameters can be considered constant should be used as main scale-up parameter. Other relevant parameters throughout the reactor bed, ensuring the robustness of the process. A such as temperature and moisture but also pH should be thoroughly minimum AFPR value of 80% is needed to correctly perform fungal monitored and controlled or adjusted when scaling the process to pilot fermentation at 22 L scale, as results were better in terms of consecutive plant scale. batches when comparing to 70% AFPR tested at 1.5 L scale (Table 1), showing the high relevance of the parameter in the scaling process. 4. Conclusions These findings are highly relevant to fungal SSF, as most SSF processes performed using packed beds do not present uniformity due to heat A robust, reproducible, and scalable process to produce TH conidia in transfer and bed packing issues [48], which is not only achieved in single SSF packed bed bioreactors using substrates of different biodegrad­ batch in this work but also in a maximum of 5 consecutive batches by ability has been achieved. Process scale-up has been successful using 9 A. Sala et al. Chemical Engineering Journal 425 (2021) 131620 both rice husk or beer draff and wood chips as substrates. SBR strategy [13] T.L. Richard, A.H.M. Veeken, V. deWilde, H.V.M. Hamelers, Air-filled porosity and permeability relationships during solid-state fermentation, Biotechnol. Progr. 20 has been successful using the mixture of beer draff and wood chips, (5) (2004) 1372–1381. sustaining conidia production for 5 consecutive batches at values close [14] S. Mishra, P. Kumar, A. Malik, Suitability of agricultural by-products as production to 2.0x109 conidia g-1dm. Prioritizing the use of the safest and sterilis­ medium for spore production by Beauveria bassiana HQ917687, Int. J. Recy. Org. able substrate, rice husk was discarded in favour of beer draff under this Waste Agr. 5 (2) (2016) 179–184. [15] R. Barrena, T. Gea, S. Ponsá, L. Ruggieri, A. Artola, X. Font, A. Sánchez, operational strategy for beer draff not presenting AN contamination, Categorizing raw organic material biodegradability via respiration activity despite sterilization. Differences in performance between scales when measurement: a review, Compost Sci. Util. 19 (2) (2011) 105–113. using beer draff allowed the definition of a minimum AFPR value of 80%, [16] J. Llimós-Turet, O. Mauricio Martínez, E. Martí, C. Corchado-Lopo, L. Llenas, T. Gea, S. Ponsà, Brewer’s spent grain biotransformation to produce determining AFPR as a key parameter in SSF process scale-up. Process lignocellulolytic enzymes and polyhydroxyalkanoates in a two-stage valorization robustness was demonstrated with packed-bed uniformity in all 22 L scheme, Bioref. (2020), https://doi.org/10.1007/s13399-020-00918-4. reactors with both substrates despite their different biodegradability. No [17] Food and Agriculture organization of the United Nations (FAO), 2020. FAOSTAT: Corporal Statistical Database. Crops/Regions/World Elements/Area harvested/ significant variations throughout the height of the reactor for conidia Production quantity Items/rice (paddy) Years/Select all. Retrieved: June 21. production, moisture and pH, were detected showing only minimum [18] International Rice Research Institute (IRRI), 2020. Rice knowledge bank. Home/ temperature rise when scaling beer draff. Implementing a SBR strategy Step-by-step production/Postproduction/By-products/Rice husk. Consulted: June 21. with adequate AFPR values helps at overcoming major scale-up draw­ [19] S. Aliyu, M. Bala, Brewer’s spent grain: a review of its potentials and applications, backs, at least up to a scale of 22 L, being a feasible alternative to African J. Biotechnol. 10 (2011) 324–331. traditional batch operation. [20] J. Ibarruri, M. Cebrián, I. Hernández, Solid state fermentation of brewer’s spent grain using Rhizopus sp. to enhance nutritional value, Waste Biomass Valori. 10 (12) (2019) 3687–3700. Declaration of Competing Interest [21] F. Múñiz-Paredes, F. Miranda-Hernàndez, O. Loera, Production of conidia by entomopathogenic fungi: from inoculants to final quality tests, World J. Microb. The authors declare that they have no known competing financial Biot. 33 (2017) 1–9. [22] L. Ruggieri, T. Gea, A. Artola, A. Sánchez, Air filled porosity measurements by air interests or personal relationships that could have appeared to influence pycnometry in the composting process: A review and a correlation analysis, the work reported in this paper. Bioresource Technol. 100 (2009) 2655–2666. [23] A. Sala, A. Artola, A. Sánchez, R. Barrena, Rice husk as a source for fungal biopesticide production by solid-state fermentation using B. bassiana and Acknowledgments T. harzianum, Bioresource Technol. 296 (2020), 122322. [24] B. Puyuelo, T. Gea, A. Sánchez, A new control strategy for the composting process The authors thank the Spanish Ministerio de Economía y Com­ based on the oxygen uptake rate, Chem. Eng. J. 165 (1) (2010) 161–169. [25] S. Ponsá, T. Gea, A. Sánchez, Different indices to express biodegradability in petitividad, which gave financial support (Project CTM2015-69513-R) organic solid wastes, J. Environ. Qual. 39 (2) (2010) 706–712. to this work. Arnau Sala also thanks Universitat Autònoma de Barce­ [26] T.A. Jr, E.H.M. Scott, Determination of dextran with anthrone, Anal. Chem. 25 (11) lona for a predoctoral scholarship. (1953) 1656–1661. [27] US Composting Council, Test Methods for the Examination of Composting and Compost, Edaphos International (2001) Houston. Appendix A. Supplementary material [28] C. Smith, S. Edgington, Germination at different water activities of similarly aged Metarhizium conidia harvested from ageing cultures, J. Stor. Prod. Res. 47 (3) (2011) 157–160. Supplementary data to this article can be found online at https://doi. [29] J.E. Hallsworth, N. Magan, Culture age, temperature, and pH affect the polyol and org/10.1016/j.cej.2021.131620. trehalose contents of fungal propagules, Appl. Environ. Microb. 62 (7) (1996) 2435–2442. References [30] F. Múñiz-Paredes, P.M. Garza-López, G. Viniegra-González, O. Loera, Comparison between superficial and solid-state cultures of Isaria fumosorosea: conidial yields, quality and sensitivity to oxidant conditions, World J. Microb. Biot. 32 (2016) 111. [1] I. Thakore, The biopesticide market for global agricultural use, Genet. Eng. [31] A. Aydin, H. Aksu, U. Gunsen, Mycotoxin levels and incidence of mould in Turkish Biotechnol. 2 (2006) 194–208. rice, Environ. Monit. Assess. 178 (1-4) (2011) 271–280. [2] G.M. Mascarin, S.T. Jaronski, The production and uses of Beauveria bassiana as a [32] E. Fredlund, A.-M. Thim, A. Gidlund, S. Brostedt, M. Nyberg, M. Olsen, Moulds and microbial insecticide, World J. Microbiol. Biotechnol. 32 (2016) 1–26. mycotoxins in rice from the Swedish retail market, Food Addit. Contam. A. 26 (4) [3] J.P.M. Araújo, D.P. Huges, Diversity of entomopathogenic fungi: which groups (2009) 527–533. conquered the insect body? Adv. Gen. 94 (2016) 1–39. [33] E. Streit, G. Schatzmayr, P. Tassis, E. Tzika, D. Marin, I. Taranu, C. Tabus, [4] A. Sala, R. Barrena, A. Artola, A. Sánchez, Current developments in the production A. Nicolau, I. Aprodu, O. Puel, I.P. Oswald, Current situation of micotoxin of fungal biological control agents by solid-state fermentation using organic solid contamination and co-ocurrence in animal feed – focus on Europe, Toxins 4 (2012) waste, Crit. Rev. Environ. Sci. Technol. 49 (8) (2019) 655–694. 788–809. [5] A. Pandey, Current developments in solid-state fermentation, Biochem. Eng. J. 81 [34] J.D. Zhang, Q. Yang, Optimization of solid-state fermentation conditions for (2003) 146–161. Trichoderma harzianum using an orthogonal test, Genet. Mol. Res. 14 (1) (2015) [6] R. De la Cruz Quiroz, S. Roussos, D. Hernández, R. Rodríguez, F. Castillo, C. 1771–1781. N. Aguilar, Challenges and opportunities of the bio-pesticides production by solid- [35] R. Bhateria, R. Dhaka, Optimization and statistical modelling of cadmium state fermentation: filamentous fungi as a model, Crit. Rev. Biotechnol. 35 (3) biosorption process in aqueous medium by Aspergillus niger using response surface (2015) 326–333. methodology and principal component analysis, Ecol. Eng. 135 (2019) 127–138. [7] M. Verma, S.K. Brar, R.D. Tyagi, R.Y. Surampalli, J.R. Valéro, Antagonistic fungi, [36] N. Velasco-Alvarez, M. Gutiérrez-Rojas, I. González, Alterations in Aspergillus Trichoderma spp.: Panoply of biological control, Biochem. Eng. J. 37 (2007) 1–20. brasiliensis ATCC 9642 membranes associated to metabolism modifications during [8] P. Sharma, M. Sharma, M. Raja, V. Shanmugam, Status of Trichoderma research in application of low-intensity electric current, Bioelectrochemistry. 118 (2017) 1–7. India: a review, Indian Phytopathol. 67 (2014) 1–19. [37] N.A. Yazid, R. Barrena, D. Komilis, A. Sánchez, Solid-state fermentation as a novel [9] C. Ballardo, R. Barrena, A. Artola, A. Sánchez, A novel strategy for producing paradigm for organic waste valorization: A review, Sustainability. 9 (2017) 1–28. compost with enhanced biopesticide properties through solid-state fermentation of [38] C. Krishna, Solid-state fermentation systems – an overview, Crit. Rev. Biotechnol. bio- waste and inoculation with Bacillus thuringiensis, Waste Manage. 70 (2017) 25 (1-2) (2005) 1–30. 53–58. [39] R.S. Cavalcante, H.L.S. Lima, G.A.S. Pinto, C.A.T. Gava, S. Rodrigues, Effect of [10] A. Pandey, C. Larroche, C.R. Soccol, General considerations about solid-state moisture on trichoderma conidia production on corn and wheat bran by solid state fermentation processes, in: A. Pandey, C.R. Soccol, C. Larroche, C. (Eds.), Current fermentation, Food and Bioprocess Technol. 1 (1) (2008) 100–104. developments in solid-state fermentation, Springer, Asiatech Publishers, New [40] F. Méndez-González, O. Loera-Corral, G. Saucedo-Castañeda, E. Favela-Torres, Delhi, 2008, pp. 26–48. Bioreactors for the production of biological control agents by solid-state [11] A. Cerda, T. Gea, M.C. Vargas-García, A. Sánchez, Towards a competitive solid fermentation, in: A. Pandey, C. Larroche, C.R. Soccol (Eds.), Current developments state fermentation: Cellulases production from coffee husk by sequential batch of bio- technology and bioengineering: current advances in solid-state operation and role of microbial diversity, Sci. Total. Environ. 589 (2017) 56–65. fermentation, Elsevier, 2018, pp. 109–121. [12] O. Martínez, A. Sánchez, X. Font, R. Barrena, Bioproduction of 2-phenylethanol [41] F.P. Casciatori, C.L. Laurentino, S.R. Taboga, P.A. Casciatori, J.C. Thoméo, and 2-phenethyl acetate by Kluyveromyces marxianus through the solid-state Structural properties of beds packed with agro-industrial solid by-products fermentation of sugarcane bagasse, Appl. Microb. Biot. 102 (11) (2018) applicable for solid-state fermentation: Experimental data and effects on process 4703–4716. performance, Chem. Eng. J. 255 (2014) 214–224. [42] M. Papagianni, Fungal morphology and metabolite production in submerged mycelial processes, Biotechnol. Adv. 22 (3) (2004) 189–259. 10 A. Sala et al. Chemical Engineering Journal 425 (2021) 131620 [43] H.-J. LIU, W.-D. DUAN, C. LIU, L.-X. MENG, H.-x. LI, R. LI, Q.-R. SHEN, Spore [46] L.P. da Cunha, F.P. Casciatori, I.V. Vicente, R.L. Garcia, J.C. Thoméo, Metarhizium production in the solid-state fermentation of stevia residue by Trichoderma anisopliae conidia production in packed-bed bioreactor using rice as substrate in guizhouense and its effects on corn growth, J. Inegr. Agr. 20 (5) (2021) 1147–1156. successive cultivations, Process Biochem. 97 (2020) 104–111. [44] C. Kubicek, G.E. Harman, Trichoderma and Gliocladium Volume 1 Basic biology, [47] A.T.J. Finkler, M.Z. Weber, G.A. Fuchs, L.A. Scholz, L.F.L. Luz Jr, N. Krieger, D.A. taxonomy and genetics, in: W. Gams, J. Bissett (Eds.), Morphology and Mitchell, L.M.M. Jorge, L. M. M, Estimation of heat and mass transfer coefficients identification of Trichoderma, Taylor & Francis group, London, 1998, pp. 3–34. in a pilot packed-bed solid-state fermentation bioreactor, Chem. Eng. J. 408 (2021) [45] M.C. Barrera, M.I. Gómez, J.C. Serrato Bermúdez, Towards the production of 127246. fungal biocontrol candidates using inert supports: a case of study of Trichoderma [48] M. Krishania, R. Sindhu, P. Binod, V. Ahluwalia, R.S. Sangwan, A. Pandey, Design asperellum in a pilot fixed bed fermenter, Biocontrol Sci. Tech. 29 (2019) 162–184. of bioreactors in solid-state fermentation. In: A. Pandey, C. Larroche, C.R. Soccol (Eds)., Current Developments in Biotechnology and Bioengineering: Current advances in Solid-state Fermentation. ElSevier. (2018) 83–96. 11