On line lab-scale technical multi-device for waste processing [GRIP-D2.2.1]

1 NODES – Nord Ovest Digitale e Sostenibile FLAGSHIP PROJECT GRIP SPOKE 2 –GREEN TECHNOLOGIES AND SUSTAINABLE INDUSTRIES DELIVERABLE D2.2.1: On line lab-scale technical multi-device for waste processing REPORTING PERIOD Period covered: from M10 to M22 Periodic report date and version: 20/10/2024_ver 1 Deliverable D2.2.1 Responsible M. Arlorio RM2 Responsible M. Arlorio This report is part of the project NODES which has received funding from the MUR – M4C2 1.5 of PNRR funded by the European Union - NextGenerationEU (Grant agreement no. ECS00000036) 2 Glossary Definition Hub Coordinator (HC) The Hub Coordinator represents the single point of contact for the implementation of the innovation ecosystem towards the MUR. It carries out the management and coordination activities of the innovation ecosystem, receives the fundings, verifies, and transmits to the MUR the reporting of the activities carried out by the Spoke and their affiliates. National Recovery and Resilience Plan (NRRP) This document uses the Italian acronym for the NRRP, which is PNRR (Piano Nazionale della Ripresa e Resilienza) Research Program Manager The person who will be the responsible for the overall scientific contents of the NODES project. The NODES will appoint the Research Program Manager. It refers to “Responsabile del Programma di Ricerca” in the MUR’s Call of proposal for “Ecosistemi di Innovazione” NODES’ Research and innovation program NODES’ Research and Innovation program is articulated in specific programs for each Spoke, with the aim to promote and support applied research on topics consistent with the Intelligent Specialization Strategy, with the guidelines of the 2021-2027 partnership agreement scheme, with regional operational plans and regional and national research and innovation priorities. Although NODES’ Spokes are concentrated on different themes, they will organize their activities and actions within a common framework – NODES’ Booster Methodoloy Spoke Coordinator The University in charge of coordinating the Spoke’s ecosystem. It refers to “Spoke” in the MUR’s Call of proposal for “Ecosistemi di Innovazione” Spoke Data Manager The person who will be the responsible for the monitoring and management of data generated at the Spoke level. The Spoke Coordinator will appoint the Spoke Data Manager. Spoke Partner The entity associated to the Spoke Coordinator. It can be an Innovation Cluster, Competence Center, Research Center related to the Spoke’s ecosystem and contributes to achieve objectives and impact under the Spoke’ leadership and management. It refers to “soggetti affiliati” in the MUR’s Call of proposal for “Ecosistemi di Innovazione”. Spoke Project manager The person who will be the responsible for the management, coordination and progress of the project at the Spoke level. The Spoke Coordinator will appoint the Spoke Project Manager. Spoke research and innovation program NODES’ Research and Innovation program is articulated in specific programs for each Spokes. The spoke will leverage a consolidated collaboration with leading private and public companies and will focus the applied research activity on technological domains and applications that can favour the integration of SMEs into new value chains. Spoke Scientific and Technical Manager The person who will be the responsible for the overall scientific contents of the project at the Spoke level. The Spoke Coordinator will appoint the Spoke Scientific and Technical Manager. Spoke Stakeholders Committee (SC) Consultation structure formed by relevant stakeholders (Government, universities, companies, civil society, third sector, etc.) Spoke Thematic General target focus and domain of the Spoke research. Spoke Topics Specific areas/lines of development within the Spoke. Spoke Work Package Leader At the Spoke level, Work Packages (WPs) will be organized by WP leaders, who will be responsible for performance evaluation and reporting. Flagship Project Main research project at the Spoke level with the goal of prototyping, testing, demonstrating the research activities towards higher TRLs. 3 List of Deliverables D. No Name Lead Beneficiary Type Dissemination Level Due Date New Due Date (if delay) Delivery Date (actual) D2.1 Data about chemical and nutritional profiling of raw wastes and by products UPO R PU M14 (02/2024) 26/03/ 2024 18/04/2024 D2.2.1 On line lab-scale technical multidevice for waste processing* UPO Other (material) PU M18 04/10/2024 25/10/2024 D2.2.2 Delivery of protocols (lab-scale) ready to scale-up the production of new high-value material (in collaboration with Companies) UPO R PU M22 D2.3.1 New data about valorized matrices characterization and high value products UPO R PU M28 D2.3.2 New characterized ingredients/materials for food, nutraceuticals, pharma and cosmetic applications UPO Other (material) PU M30 D2.4.1 New data about sustainable production of new materials from biomasses UPO R PU M24 D2.4.2 New characterized materials from biomasses UPO Other (material) PU M30 D2.5.2 Porous sorbents from biomasses valorization UPO Other (material) PU M30 D2.6.1 New material produced at pilot scale ready to the formulation or coformulation (in collaboration with Companies) UPO Other (material) PU M32 D2.6.2 New well characterized process and formulated pilotproducts (in collaboration with Companies) UPO R/Other (Material) PU M32 D2.7 Report on the adsorption and/or catalytic performances of porous solids derived from biomasses valorization and nonrecyclable plastic wastes UPO R PU M32 4 A) INTRODUCTION The partners involved in the Tasks 2.2.2, 2.2.3 and 2.2.4 and 2.3 (covering the period M10-M22; UNITO; POLITO; UPO; UNIPV; ENVIPARK) following the identification of the best available technologies as well as the characterization of the selected waste/by-products, developed different methodological approaches to up-cycle and valorize the raw matrices. The activity of these Tasks was focused on the selection of some key processes useful to combine relevant green technologies. The scalability of the processes has been primarily considered to reach the target (selection of some scalable process at pilot level). Moreover, some pilot products were produced and characterized. The principal outcomes of this part of the research (in terms of processing description) are reported here. B) ROLE OF PARTNERS The role of each partner was focused on the application of the available technologies, as previously described in M2.2.1. C) EXPLANATION OF THE WORK CARRIED OUT AND OVERVIEW OF THE PROGRESS The work, as following described, was focused on the selection of the best combined (or potentially combined) techniques useful to process and potentially scale up the most interesting process tested (lab level) on different raw matrices, in order to valorize and upcycle them. Partner: UniPv The unit provided to develop plasmids for the bio-production of high-value molecules. Even if not properly defined as “plants”, following the concept of “cells like a factory” we consider them useful as tool to produce (and eventually to scale-up) the processes. The protocols are still under development. Matrix: Cheese whey permeate Beta-Galactosidase from Aspergillus oryzae (AoGal) was selected as best biocatalyst in the biotransformation of cheese whey permeate for the production of 1-butyl b-D-galactopyranoside, a key intermediate for the synthesis of sugar-based surfactants. The enzyme is commercially available, however the activity is batch-variable and so far it was not possible to identify an optimal immobilization protocol for the wild-type enzyme. With the aim of obtaining a more homogeneous formulation of the biocatalyst and engineering it through site-specific 5 mutagenesis to favor its immobilization on a solid support, its expression in recombinant form was attempted both in bacterial and fungal expression systems. We have produced the plasmids for the over-expression of His-tagged wild-type AoGal in E. coli (pET-24a+) and in Kluyveromyces lactis (pKLAC2). The development of the over-expression protocol is ongoing. Matrix: Rice husk Rice husk was subjected to two different pre-treatments to eliminate the undesired lignin and make more accessible the cellulosic component to the enzymatic activity: i) "conventional" treatment with organic solvents and NaOH and ii) alternative treatment with the use of a deep eutectic solvent. The chemical-physical characterization of the starting husk and pre-treated is ongoing. Partner: Polito The contribute of Polito is strictly related to the collaboration with the other Units, sharing the facilities and contributing in the last part of the research in the “combined” research at least on one up-cyclable raw material. Some activities are undergoing in order to complete the knowledge useful to implement the combination of the technological approaches, particularly concerning the interplays with DSF-UPO and EnviPark Units. Matrix: Brewery spent grains Brewery spent grains (BSG; protein content: 5.95 mg/ g dw; total polyphenols: 3.4 mg/ gdw) was fermented by the ligninolytic fungus Phanerochaete chrysosporium, in order to improve the amount of extracted polyphenols (Solid-State Fermentation; SSF), at lab scale. Currently, different pre-treatments (ultrasound and microwave) are ongoing on the same raw matrix, to improve the total polyphenol recovery. Partner: DSF-UPO Matrix: apple pomace Apple (Malus domestica L.), the fourth most important fruit eaten around the world, is discarded along the food chain supply, including harvesting and processing stages, which generate an enormous quantity of by-products including peels, seeds and pomace. With the aim to obtain the greenest extract from this food by-product, we have applied a heat-assisted extraction (HAE) using water as the only (green) solvent. Moreover, one of the trend of this year is the use of mathematical modeling and digital technologies (AI) to optimize some processes in a shorter time. We have applied and compared three different mathematical models Response Surface Methodology (RSM), Artificial Neural Networks (ANNs, Back Propagation NN) and Random Forest 6 (RF) in order to save time and matrix, as well as to tailor the mathematical model to our needs (yield of extraction). The outcomes from the selected parameters/analyses (Total Phenolic Content, antioxidant activity measuring with DPPH, ABTS and FRAP, chromatographic analyses of phenolic fraction) were processed through mathematical models. The validation of the final model, useful to predict the best parameters for a specific extraction of some bioactive compounds from pomace, especially phloridzin, is ongoing. Treatment on the initial raw material The apple pomace (Fig. 1A), is first subjected to a mild drying process through (40 °C, 24 h) and subsequently subjected to a milling step in order to obtain a matrix as homogeneous as possible ready for the extraction (Fig. 1B). Fig. 1. A) Raw apple pomace; B) Grinded sample of apple pomace The overall work flow is represented below, in Fig. 2. A B 7 Fig. 2: workflow of the solvent-free, heat-assisted extraction experiments Three different independent variable were chosen: temperature (35, 50, 65 and 80 °C); solid to liquid ratio (1:10, 1:20, 1:30, 1:40) and time (15, 30, 45, 60 min.) giving us in combination a total of 64 experiments; to reduce the number of extractions to performed we applied the half factorial design. The experiments were performed in a water bath under shaking and temperature control. The responses chosen ware spectrophotometric assays and chromatographic analyses. The results obtained were processed by a R based software in order to obtained predictive curves. ANNs and RF predictive models show how higher temperature and higher S/L ratio permit to obtain water extract richer in terms of bioactive compounds (phloridzin, rutin, hyperoside…). Following two plots related to the Random Forest algorithm are reported. The validation is currently ongoing, and a specific software useful to specifically predict the best performing conditions for each molecule is under development. Apparently, temperature is poorly affecting the extraction, especially when the processing temperature is lower than 60-70 °C. Fig. 3: Curves obtained through Random Forest curve of phloridzin (left) and cyanidine-3-O-galactoside (right) at fixed S/L ratio. Matrix: Cocoa bean shells CBSs, a residue from cocoa industry, are recovered from roasted pods during the kibbling/winnowing process, where the beans are cracked and then CBS are winnowed, or blown away. They represent 10-17% of cocoa bean weight and more than 700 thousand tons are produced worldwide. CBS is a promising matrix for upcycling applications, being rich in polyphenols and fibers. An innovative technique with a conservative approach has been applied: drying of the US-processed solution was performed to return to a powder, affecting the polyphenolic fraction (releasing soluble polyphenols from the matrix) and retaining the dietary 8 fiber (DF) fraction for its potential prebiotic effect. This approach might lead to a valuable new ingredients, interesting both for its health-related and its technological properties. A process (US intensification of polyphenols extraction and fiber modification) has been optimized (the work flow is reported in Fig. 4). Fig 4: workflow of cocoa US-based processing These powders can be easily processed by fermentation and/or enzymes in a bioreactor, also considering the serial application of US, fermentation and ultrafiltration for the final concentration/fractionation/clean-up of the product. Fig. 5 US system used on cocoa bean shells Also in this case, three different mathematical models were applied and compared: Response Surface Methodology (RSM), Artificial Neural Networks (ANNs, Back propagation NN) and Random Forest (RF), this last fitting our model the best. The results showed that both Total Polyphenolic Content and Total Flavonoid Content were increased when compared to the untreated matrix, unlike antioxidant properties measured by DPPH and ABTS. 9 Finally, a performing combined/serial processing treatment for the selected matrices was set up, combining together an Ultrasound system linked with a Bioreactor (a special chamber of treatment for the sonotrode has been appositely prepared) and an Ultrafiltration benchtop system, as following reported in Fig. 6. Fig. 6: Serial combined system for US treatment, fermentation/enzymatic hydrolysis and ultrafiltration (lab level). Partner: UPO - DiSIT Matrix: Rice husks (Calcination in muffle furnace) The selected waste matrix, rice husk (Fig. 1A), is subjected to a heat treatment in air in a calcination muffle furnace (Fig. 1B), resulting in the conversion of the original material into biogenic silica, a solid enriched in silicon dioxide.