Source: UNIVERSITY OF HOUSTON SYSTEM submitted to
IOT BASED SMART AUTOMATED MUSHROOM PRODUCTION SYSTEM
Sponsoring Institution
National Institute of Food and Agriculture
Project Status
EXTENDED
Funding Source
Reporting Frequency
Annual
Accession No.
1026673
Grant No.
2021-67022-34889
Project No.
TEXW-2020-08884
Proposal No.
2020-08884
Multistate No.
(N/A)
Program Code
A1521
Project Start Date
Jun 1, 2021
Project End Date
May 31, 2025
Grant Year
2021
Project Director
Balan, V.
Recipient Organization
UNIVERSITY OF HOUSTON SYSTEM
4800 CALHOUN ST STE 316
HOUSTON,TX 770042610
Performing Department
Engineering Technology
Non Technical Summary
The small-scale production of mushrooms, a nutritious food source with essential vitamins, proteins and minerals, could significantly improve food security, human health, and the local economy. Notably, the number of small-scale mushroom farmers decreased by 63% nationally from 2017 to 2019. A need also exists to develop smart and efficient ways of growing mushrooms that reduces labor and benefits small-scale mushroom farmers. Accordingly, the goal of the proposed research is to use Internet of Things (IoT) technology and big-data analysis to accurately measure and control environmental factors during mushroom production and to significantly improve process efficiency through automation, therefore reducing labor. The objectives are to: 1) develop a smart, IoT-based growth chamber; 2) develop a mechanized, automatic substrate-processing system; 3) improve mushroom production via resource and energy calculations; and 4) integrate systems developed in Objectives 1-3 into three shipping containers. We will develop and demonstrate an efficient and automated substrate preparation process to produce different mushrooms. Enabled by real-time IoT-based data collection and machine learning and optimization algorithms, the new process will continuously generate densified substrate with improved fresh-air circulation during fungal colonization of the substrate, yielding mushrooms in 25 days compared to the traditional 50 days. We will evaluate both mass and energy balances for the new process and compare with existing processes to demonstrate efficiency and economic improvements using IoT data. The proposed mushroom production methods will benefit small-scale mushroom growers and will enable the sustainability of food security within our society.
Animal Health Component
0%
Research Effort Categories
Basic
25%
Applied
50%
Developmental
25%
Classification

Knowledge Area (KA)Subject of Investigation (SOI)Field of Science (FOS)Percent
40214701102100%
Goals / Objectives
(i) Objective 1: Develop a smart, IoT based growth chamber:We will develop a lab-scale mushroom production system equipped with the required environmental sensors (temperature, humidity, CO2, and light intensity), as well as adjustable mobile device controls. The system will also be equipped with instrumentation including flow meters, electrical power meters, and a camera for human interaction and ML applications. The IoT capability will be developed using open-source tools hosted by the UH High-Performance Computing Center. Dr. Benhaddou's team will lead this objective with input from the research team and stakeholders. The developed growth chamber will then be used for growing different variety of mushrooms by varying the environmental conditions.(ii) Objective 2: Develop an automated, mechanized substrate processins system:In this objective we will develop the mechanical system necessary to process mushroom substrate in a safe and clean manner, using IoT and Programmable Logic Controllers (PLC), resulting in a processing system that needs minimal human involvement. This approach will reduce the labor required to prepare the substrate. Dr. Zhu will be the main developer, in collaboration with Dr. Benhaddou for IoT development. Interactions with the Dr. Balan's team for growing mushrooms are especially important as they will use the system to prepare their substrate.(iii) Objective 3: Optimize mushroom production using resource and energy calculations. In this objective Dr. Balan will lead the development of the protocols and procedures to inoculate the densified substrates (developed in Objective 2) with different grain mycelia to produce mushrooms using the newly developed IoT-based growth chamber (implemented in Objective 1). We will use the IoT infrastructure to measure the amount of energy and resources (substrate, water, and ingredients) needed to produce the mushrooms. We aim to optimize the mushroom growth cycle time, given all the constraints including cost, time in each step, and resources needed.(iv) Objective 4: Integrate the systems developed in Objectives 1-3 into three containers. To demonstrate the technology on a scale that mushroom producers will value and potentially use, the innovations developed in Objectives 1-3 will be integrated in three modular containers. Both the mechanized substrate preparation and the growth chambers will be precisely controlled using IoT-based data collection and analysis. Developing such a container-scale system will enable us to study the implications for future modular vertical mushroom cultivation and provide training to workshop participants.
Project Methods
OBJECTIVE 1. Develop asmart, IoT-based growth chamber.IoT platform technology: This technology is becoming popular for industrial processes as it offers real-time monitoring, allowing applications ranging from monitoring, control, to maintenance.Software control and distribution technology: To keep track of different versions and iterations, we will use git-version technology and the GitHub server to distribute the software among team members.Publish/subscribe framework: This enables the decoupling of background data and event processing from both the user interface and user interactions, lowering the complexity of developing the system. This will enable us to analyze data in real-time without impacting the performance of the system. We will use the open-source Kaa platform for development.OBJECTIVE 2. Automated, densified substrate preparation Substrate preprocessing using a hammer mill: We will evaluate combinations of substrates such as wheat straw, sorghum stubble, rice straw, oat bran, rice bran, wheat bran, cotton seed hull, and grain flour. Straw bales will be shredded using a hammer mill and its size will be reduced using different screen sizes to create variable lengths for later use in mushroom beds.Substrate mixing and steam conditioning: Different substrates will be mixed with lime and gypsum in different ratios (to adjust pH) in a mini ribbon blender and subjected to low pressure during blending using a steam generator. Steaming the biomass prior to pelleting will add moisture and reduce microbial contamination. This will also aid in more efficient biomass pelletizing and reduce erosion of the pelleting die. Steam pressure and conditioning time will be varied to generate microbe-free biomass pellets.DNA extraction from microorganisms present in the substrate: Densified biomass will be extracted first to evaluate microorganism's presence using culture plates. Selected samples will be analyzed using metagenomics analysis to identify different organisms. The samples will be extracted using a commercially available Power Soil DNA isolation kit and additional clean-up will be performed using a PowerClean Pro DNA Kit according to the manufacturer's instructions. Humic acids and other substances that interfere with polymerase chain reaction (PCR) will be removed, followed by subsequent visualization of the DNA on an agarose gel and quantification using a spectrophotometer. After evaluating the purity of the extracted DNA using a spectrophotometer, a known amount from each extraction will be used to analyze bacterial and fungal contamination.Substrate densification: Forcing the conditioned substrate through a flat die increases the bulk density of the biomass. Concurrently, the friction between the substrate and the die generates heat, which will aid in reducing microorganisms in the substrate pellets. The pellets discharged from the mill will be collected in sterile containers. If the pellet biomass is contaminated with microorganisms, the process will be repeated until the substrate for growing the mycelium is free from contamination, as determined by microbial and genomics analysis.Library preparation and sequencing of bacterial and fungal ribosomal markers 16S rRNA: Sequencing techniques are critical for verifying the absence of bacterial contaminants and purity of mushroom cultures. The V4 variable region from the 16S ribosomal RNA gene of the isolated microbes will be amplified in triplicate (pooled after amplification) using the primers and an established protocol. We will use Illumina's barcodes on the forward and reverse primers. The PCR conditions will be as follows: denaturation at 98°C for 30 s, followed by 30 cycles of 98°C for 10 s, 50°C for 30 s, 72°C for 30 s, and a final extension step at 72°C for 5 min. The PCR products will be run on a 1% agarose gel (45 min/100 V) and quantified using a spectrophotometer.Sequence processing: Raw Illumina bacterial sequence reads will be processed using the Mothur package (v.1.38.1) following the pipeline analysis developed by the Schloss laboratory. The dataset will be replicated, and unique sequences will be aligned to a 50,000 column-wide SILVA-based reference alignment using the reported Needleman-Wunsch pairwise alignment method. Sequence classifications will be made against the SILVA database (release 123), which contains 152,308 bacterial small subunit (SSU) rRNA sequences as well as Archaea and Eukarya sequences. Using this method, the sequences will be sorted by decreasing abundance and sequentially compared to each of the rarer sequences. Chimera sequences will be treated separately from sequencing errors using the UCHIME algorithmby comparing all sequences to the most abundant sequences in the dataset, implemented by the Mothur software.OBJECTIVE 3. Optimize mushroom production using resource and energy calculations.Mycelium inoculation and substrate colonization: Fungal mycelium (liquid or solid spawn) prepared in the lab will be used to inoculate the densified substrate following the addition of sterile water to raise the moisture content to between 65-70%. The inoculated substrates (in bottles or bags) will then be transferred to the growth chamber for mycelium colonization for 7-10 days. At this stage, the substrate will be fully covered by white fungal mycelium.Producing different mushrooms: Growth conditions in the chambers will be changed to favor the growth of the different mushroom varieties. In some cases, colonized substrates will be frozen at -20°C for a few minutes and then brought back to ambient temperature to trigger mushroom growth. For other mushrooms, sterile water will be sprayed, or moistened peat moss will be placed on top of the bed to trigger mushroom growth. The amount of oxygen and CO2in the growth chamber is critical for producing a high mushroom yield. This process will continue for another 10-12 days, with mushrooms harvested and their weight measured and documented at regular intervals.Composition analysis: The fiber, protein, mineral, and vitamin contents, as well as antioxidant and nutritional compounds, of the harvested mushrooms will be analyzed using an established standard protocol.OBJECTIVE 4. Integrate the systems developed in Objectives 1-3 into three containers.Big-data analysis: Sensors generates a large amount of data related to the environment and operations. Depending on the sampling frequencies, the amount of data available for processing could be very large. Analyzing such big data will provide insights into the process and guidance for process optimization. Big data are usually edited and pre-processed prior to the application of ML algorithms.Machine learning (ML): ML algorithms can handle classification, regression, and problems associated with classification. In our application, we will use ML in a regression problem to determine the relationship between operation parameters and mushroom production.Computational optimization: Optimization problems can be modeled by means of a set of decision variables and constraints. The challenge is to find an optimal solution quickly within a large solution-space composed of many parameters and constraints. Optimization solution techniques can be classified intoexactandheuristicmethods. Exact methods are guaranteed to find optimal solutions for a given optimization problem, but they often perform very poorly on complex optimization problems. Usingheuristicmethods, the guarantee of finding an optimal solution is often traded for finding an acceptable solution within a reasonable amount of time. For NP-hard (Non-polynomial hard) problems,heuristicmethods are the only feasible way to find good solutions within a reasonable timeframe. In this project, we will use population-basedheuristics(e.g., genetic algorithms) combined with ML models to optimize production-process parameters.

Progress 06/01/22 to 05/31/23

Outputs
Target Audience:The target audence(s) are small scale mushroom producers. Our goal is develop methods of sustainably processing substrates and producing high value mushroom in shipping containers. We also train undergraduate and gradatue students studying at University of Houston Changes/Problems:Due to the long lead time in receiving the incubators and substrate processing machines there was some delay in completing some of the milestones on time. Also, there were some delays in getting the approval for installing the shipping container testbed. We will make a formal no-cost extension of the project for one year to complete all the proposed project milestones. What opportunities for training and professional development has the project provided?This USDA project has helped to recruit and train undergraduate senior design students from mechanical engineering programs, capstone students from biotechnology programs and complete their research projects. It has also helped to recruit Ph.D., and M.S., students to complete their thesis on producing and processing mycelium and mushrooms using newly developed methods. It also helped us to receive an additional UH infrastructure grant to establish a permanent test best at UH to train and educate students and small scale mushroom producers. Some of the students and their completed projects are given below. Two biotechnology undergraduate students (Juhee Lim and Yiyi Zhang) completed a capstone project on the topic 'Evaluate growth promoting properties of fungus using trisaccharide's and plant enzyme extracts' in July 2022.? Three biotechnology undergraduate students (Dinithi Jayasinghe, Jazmin Valle and Rob Schmyler) completed a capstone project on the topic 'Producing mycelium and recycling spent mushroom substrate' in May 2023. Six biotechnology undergraduate students (Aaron Martinez, Jarod Nguygen, Aiden Tran, Caitlin Tran, Ha Truong, Swami Sundaravel) completed a capstone project on the topic 'Composting and Mixing SMS to Use as Casing Layer Materials for A. bisporus Cultivation' in December 2022. Four senior design students from mechanical engineering program (Adrian Gonzalez, Efrin Guerrero, Alex ?Reyes, Rumaldo Villaseñor) has jointly developed a 'Automatic Tumbling composter system to convert spent mushroom substrate as fertilizer and casing material to replace peat moss' using cement mixer in May 2023. Master student (Mengchuan Zhuang) defended his M.S. thesis on the topic 'Sequence Annotation of Edible Fungus Calocybe indica Using Different Bioinformatics Tools' in May 2023. Three Ph.D. students from (Mahsa Alian, Sandesh Risal, Ezra Wari) are researching 'Modeling small scale mushroom cultivation in shipping containers'. One M.S. student (Yiyi Zhang) received training on 'Evaluating the efficiency and economics of different sterilization methods'. Three Biotechnology undergraduate student (Ayser Muhammad, Isabella Sanchez Hernandez, Rohana Kuriakose) completed in summer undergraduate research project on 'Fractionating Chitin and Co-products from Pleurotus ostreatus Mushrooms' and presented the work at American Chemical Society (ACS) conference held in Indianapolis, IN in March 2023. How have the results been disseminated to communities of interest?For this funding period we have published two conference papers and are in the process of writing five other manuscripts that will be published in various peer reviewed scientific journals. We have developed a website to disseminate our research findings to mushroom growing communities and presented some of our research findings at the recently concluded ACS spring conference held in Indianapolis, IN. As the COVID traveling restrictions have been lifted, we will present our research finding at domestic and international conferences. What do you plan to do during the next reporting period to accomplish the goals?In the third year, we are looking forward to installing the new testbed comprising of two 40-ft. shipping containers at UH Sugar Land campus that will have several infrastructures such as substate processing room, inoculation room and mushroom producing rooms with proper control system. The newly purchased substrate processing machines will be installed in one of the shipping containers and the processing method will be optimized to produce mycelium and mushrooms. This will help us to train high school, undergraduate, graduate students and small scale mushroom producers with hands-on experience with necessary training materials.

Impacts
What was accomplished under these goals? Substrate processing system: We have successfully placed the order for the substrate processing system comprising of a steam generator, substrate milling machine, substrate mixer and densification unit. We are anticipating delivery of the system at the end summer 2023 that will be installed in one of the two 40 ft. shipping containers that will be commissioned at UH Sugar Land campus. Shipping container testbed: We were successful in receiving a UH infrastructure grant ($320,000) that will be used to build a test bed comprising of two shipping containers. This funding will help to establish a permanent testbed at UH campus. Several small and medium scale mushroom producers will receive hands-on training by participating in a certification program. We have finalized the design, identified the vendor and are in the process of receiving approval from UH facilities to place order and install the containers at UH Sugarland campus at the end of summer 2023. Using image processing to harvest mushrooms: Image processing and data analysis is an emerging technology used to assess the size and quality of mushrooms to determine the growth rate and measure yield. In this paper, we report different steps involved in collecting and processing image data in a large-scale commercial mushroom farm. We have demonstrated the technical feasibility of measuring the quantity and yield at different stages of mushroom cultivation which can be automated in the future. Developing this technology would allow mushroom producers to adjust the microclimate conditions to get better yield and coordinate harvesting schedules when quality is at its peak to maximize their profit. To extract relevant information about the mushrooms at a specific time, we followed the 8 steps for the 1960 time-series images captured during the experiment. 1) Image reading and cropping, 2) Grayscale conversion, 3) Image segmentation, 4) Contrast adjustment, 5) Canny edge detection, 6) Stitching sub-images, 7) Masking out noise and 8) Circular Hough transform algorithm. The above steps were applied on the images we collected for this project. This work has been published the 2023 IEEE International Wireless Communications & Mobile Computing Conference (IWCMC) and in IEEE conference proceeding in 2023. Steam conditioning of substrates and densification: Biotech capstone students completed a one semester project of substrate conditions using steam followed by densification using pelleting mill. The students identified the processing methods and successfully produced the biomass pellets. A master student has identified the protocols reported in the literature to evaluate the sterility of the densified biomass using an ATP measuring kit, culture plate and metagenomic analysis. Six different sterilization methods are currently being tested such as autoclaving, pasteurization, formalin, ozone, Bavistin and the newly developed method of steam conditioning followed by densification. We are in the process of checking the sterility of different sterilized substrates. Modeling small scale mushroom cultivation system: We have modeled a medium-scale mushroom farm with substrate storage and substrate processing. Unit operations such as milling, mixing, packing, sterilization, and mycelium inoculation to produce hundreds to a few thousand pounds of mushrooms per day using a 40-foot-long shipping container as a growth chamber. We used a computer-aided design (CAD) model in a software called SOLIDWORKS. We used substrate and processing condition information of oyster mushrooms growth conditions reported in the literature. We also evaluated the organization of different substrate beds packed in bottles, bags, and buckets to maximize the utilization of space and calculated the amount of oyster mushrooms that could be produced per container. This modeling study has helped us to determine the minimum footprint requirement to build a medium scale mushroom farm including the total number of required shipping containers. This will lay the foundation to estimate the cost of establishing such farm and return of investment based on the volume of mushroom produced. Similar modeling studies can be used to evaluate the cultivation of different varieties of mushrooms at different scales by varying the substrate combinations, packing methods, and growth conditions. We are in the process of summarizing this work and submitting two manuscripts. Micro and macroalgae to produce fungal mycelium and mushrooms: various types of micro- and macroalgae were evaluated as potential substrates for mycelium growth. The study aimed to explore the suitability of different algae species as a substrate for mushroom cultivation, focusing on the impact of algae on the growth and development of mycelium. Microalgae such as Chlorella and Spirulina were used, either alone or in combination, and were evaluated. Macroalgae, such as dulse, nori, wakame, kelp extract, Irish moss, and bladderwrack was evaluated. These species were selected for their high nutritional value and potential suitability as substrates for mushroom cultivation. Edible fungal mycelium requires a range of nutrients, including nitrogen, phosphorus, potassium, amino acids, and lipids to grow and develop properly. All algae are rich in these essential nutrients, as well as other micronutrients like vitamins and minerals that are important for mycelial growth. By incorporating these natural growth-promoting compounds, the development and growth of the mycelium can be enhanced up to four folds, ultimately resulting in denser and more robust fungal networks. This represents an innovative approach to mushroom cultivation that has the potential to improve the yield and quality of mushroom production. We have proved the concept using Calacybe indica (a tropical edible fungus) and are planning to explore several other commercially important fungi. We have submitted a patent application to UH intellectual property office based on these research findings.

Publications

  • Type: Conference Papers and Presentations Status: Published Year Published: 2023 Citation: 1. Sandesh Risal, Venkatesh Balan, Weihang Zhu, Ezra Wari, Mahsa Alian, Modeling and Optimization of Shipping Container-based Mushroom Farms for Agaricus biporus, and Pleurotus ostreatus, IISE Annual Conference proceedings 2023, New Orleans, LA.
  • Type: Conference Papers and Presentations Status: Awaiting Publication Year Published: 2023 Citation: 2. Risal S, Wari E, Alian M, Zhu W, Balan V. Modeling Urban Medium-scale Oyster Mushroom Cultivation using Shipping Container. Proceedings of the IISE Annual Conference & Expo 2023. K. Babski-Reeves, B. Eksioglu, D. Hampton, eds. (In press)
  • Type: Conference Papers and Presentations Status: Awaiting Publication Year Published: 2023 Citation: 3. Benhaddou D, Balan V, Merchant F, De La Graza A. Estimating Mushroom Yield and Quality Using Image Processing and Deep Learning. In the 2023 IEEE International Wireless Communications & Mobile Computing Conference (IWCMC) proceedings, Marrakech, Morocco, June 19-23, 2023. (In press).


Progress 06/01/21 to 05/31/22

Outputs
Target Audience:The target audence(s) are small scale mushroom producers. Our goal is develop methods of sustainably processing substrates and producing high value mushroomin shipping containers. Changes/Problems:Due to the long lead time in the current supply chain problem, we started identifying containers in the first year. Also, due to inflation the cost of materials and mushroom growth chambers has gone high. Also, there is significant deley in getting the growth chambers on time. What opportunities for training and professional development has the project provided?A group of four senior design undergraduate students from mechanical engineering program and two master students from computer engineering technology were mentored about developing environmental growth chambers prototype to produce mushrooms. They worked for two semesters to design a data driven growth chamber using different sensors and successfully demonstrated the operation of the prototype. Another group of four undergraduate students from biotechnology program and a Ph.D., student from Environmental Engineering received training to mushroom tissue culturing, producing mycelium, conditioning substrates, and producing mushrooms. A group of three BTEC capstone undergraduate student were trained to grow fungal mycelium to produce leather like material. One BTEC master student has received training on extracting fungal genome, carry out sequencing and annotation. One Mechanical Engineering Ph.D. student assists in the substrate system design and configuration. He also started working on mushroom product application exploration. How have the results been disseminated to communities of interest?We recently published two manuscripts in peer reviewed journals. One of the manuscripts is a review article that provide details about challenges in mushroom cultivation and discuss four major processing steps: (i) producing solid and liquid spawn, (ii) conventional and mechanized processing lignocellulosic biomass substrates to produce mushroom beds, (iii) maintaining growth conditions in climate-controlled rooms, and (iv) energy requirements and managements to produce mushrooms are also provided. This is an excellent resource for mushroom producers. We are developing a website to disseminate to mushroom growing communities. What do you plan to do during the next reporting period to accomplish the goals?We will complete the web-site with necessary education materials for mushroom producers. This platform will help us to connect with small scale mushroom growers in US. The machines will be installed, and the substrate processing conditions will be optimized to produce mushrooms in a shorter period and with good yield. We plan develop a computer model using Simio simulation software that will capture all the unit operations of mushroom cultivation and energy requirements. We will separately perform techno-economic analysis to calculate the cost of establishing a small scale mushroom cultivation using containers. We will connect with small scale mushroom growers and organize a two-day workshop at UH to demonstrate the substrate processing and mushroom cultivation.

Impacts
What was accomplished under these goals? Developing data driven mushroom growth chamber: A senior design team comprising four students used SolidWorks software and designed the mushroom growth chamber prototype. The dimension of the mushroom growth chamber (17 x 20 x 15 inches). The chamber was made using square aluminum tubing and polycarbonate sheets. A master student from computer engineering install sensors such as temperature, humidity, and CO2 in the growth chamber. The sensors were interphase with Raspberry Pi controller and different environmental parameters were controlled using a software. The data was displayed on a small LCD screen. The function of the growth chamber was evaluated by maintaining the environmental condition at 85+2% humidity, 75+2oF, 1000+100 ppm CO2, and LED light for few days. This prototype will be used to train farmers about maintaining the right environmental conditions to produce good quality mushrooms with high yield. Substrate processing system: We first identified all the machineries (steam generator, substrate milling machine, substrate mixer and densification unit) that are needed for substrate processing to produce mushrooms by enquiring different vendors. We also designed a control panel to connect and operate all the machines. We used Solid works software to model all the machines and simulated the operation to monitor the flow in a shipping container. Then we placed the order to custom manufacture these machines and control panel to a vendor. There is some delay in shipping the machine due to supply chain problem. Once the machines arrive, they will be installed in a 40-foot insulated shipping container and will be used to condition the substrate for growing mushrooms in a growth chamber. Mushroom Cultivation: Four undergraduate BTEC student and Ph.D., students were trained to carry out tissue culturing two different fungus (Oyster and milky white) and produce fungal mycelium using grains. The pictures taken during the training were used in prepare a figure in the Applied Microbiology and Biotechnology review article 'Challenges and opportunities in producing high?quality edible mushrooms from lignocellulosic biomass in a small scale'. The students also received training to densify the biomass substrates and in the process of developing protocols to check their sterility. One master student from computer engineering technology developed an Imaging tool for commercial mushroom yield and quality estimation. A computer vision algorithm was developed that specializes in the identification of mushrooms in a growing room where mycelium growth and obstructions are common due to the ever-changing conditions inside a busy mushroom farm. The radii measurements obtained, has been used to count, measure area, and identify trends in the growth process. This new method will help measure mushroom production yields and profit margins by understanding what is happening in their growing rooms in real time.

Publications

  • Type: Journal Articles Status: Published Year Published: 2022 Citation: 1. Balan V, Novak D, Knudson W, Jones AD, Iniguez-Franco FM, Auras R, Cho S, Rodgers A, Ubanwa B. Nutritious mushroom protein crisp healthy alternative to starchy snack. Food Production, Processing and Nutrition 3:33 (2021). https://doi.org/10.1186/s43014-021-00077-7. 2. Balan V, Zhu W, Krishnamoorthy H, Benhaddou D, Mowrer J, Husain H, Eskandari A. Challenges, and opportunities in producing high?quality edible mushrooms from lignocellulosic biomass in a small scale. Applied Microbiology and Biotechnology. 106:13551374 (2022) https://doi.org/10.1007/s00253-021-11749-2.