Raw Material Variability Research Articles

A Comprehensive Review on Sugarcane Bagasse in Food Packaging: Properties, Applications, and Future Prospects

This comprehensive review examines the potential of sugarcane bagasse as a sustainable alternative in the food packaging industry. The study analyses recent research on bagasse-based packaging materials, focusing on their composition, mechanical properties, biodegradability, and applications. Sugarcane bagasse, primarily composed of cellulose, hemicellulose, and lignin, offers promising characteristics for developing eco-friendly packaging solutions. The review highlights the enhancement of material properties through the incorporation of cellulose nanofibers and the formation of bio-composites. Various applications in rigid and flexible packaging, as well as active and intelligent packaging systems, are explored. The study also addresses challenges such as raw material variability, processing complexities, and limitations in barrier properties, even as bagasse-based materials demonstrate significant advantages in terms of biodegradability and environmental impact. The study identifies key areas for future research, including standardization of processing methods, improvement of barrier properties, and ensuring food safety compliance. Additionally, the review discusses the potential economic implications of adopting bagasse-based packaging materials and the need for life cycle assessments to fully understand their environmental impact. The integration of bagasse-derived components in advanced packaging technologies, such as antimicrobial and antioxidant systems, is also examined. Overall, this review underscores the significant potential of sugarcane bagasse in revolutionising food packaging, while emphasising the need for continued research and development to overcome existing limitations and optimise its properties for widespread industrial adoption.

From physicochemical characteristics variability to purple passion fruit (Passiflora edulis f. edulis) powders nutritional value: on the path of zero-waste.

Purple passion fruit (Passiflora edulis f. edulis) is a highly appreciated fruit typically consumed in fresh or processed into various food products. The peel and seeds, which are by-products of fruit processing, are rich in nutrients and bioactive compounds with potential to be valorised into food applications. However, raw material variability is often a major obstacle to successfully achieve such valorisation. The present study aimed to contribute to a zero-waste valorisation strategy of purple passion fruit by evaluating its temporal variability and provide a comprehensive insight into the nutritional value of fruit fraction powders. Fruit analysis demonstrated similar characteristics between three consecutive harvests because variation observed on maturity parameters, fruit mass and dimensions, fractions fresh weight, moisture, total phenolic compounds and antioxidant activity was not significant. This was attained despite variable weather conditions, as long as irrigation was provided during fruit development to avoid water stress. The development and subsequent analysis of the nutritional value of minimum processed powders of the fruit (peel, pulp and seeds) revealed that they can be used as a source of several macronutrients, essential minerals and vitamins. A single serving (10 g) of these fruit powders provide enough fiber (peel and seeds) and vitamin C (peel and pulp) to sustain nutritional claims. The present study provides valuable insights into the maintenance of physicochemical properties of all fruit fractions across three consecutive harvests. The nutritional characterization of fruit fractions also contributes to move towards a zero-waste value chain in passion fruit processing through whole fruit usage. © 2024 Society of Chemical Industry.

Environmental Evaluation of Chemical Plastic Waste Recycling: A Life Cycle Assessment Approach

Due to the high environmental burden of plastics, this study aimed to evaluate the environmental performance of chemical recycling of plastic waste through Life Cycle Assessment (LCA), focusing on pyrolysis oil production as the primary output. A pyrolysis plant in Almería, Spain, was chosen as a case study. The results indicate that the production of 1 L of pyrolysis oil from plastic waste generates about 0.032 kg CO2 eq and a water consumption of 0.031 m3, with other impact categories registering values of less than 0.1 kg/L or 0.01 m2a crop eq/L, reducing impacts in 17 out of 18 categories compared to fossil diesel. In addition, its chemical and physical properties, close to those of fossil diesel, suggest its suitability for internal combustion engines, although as a blend rather than a complete substitute. Chemical recycling also appears to be more environmentally favorable than incineration and landfilling in all 18 impact categories, achieving significant benefits, including a reduction in global warming of −3849 kg CO2 eq/ton, ionizing radiation of −22.4 kBq Co-60 eq/ton, and fossil resource consumption of −1807.5 kg oil eq/ton. These results, thus, highlight the potential dual role of chemical recycling of plastic waste, both in mitigating environmental impacts and in supporting circular economy goals by reducing demand for virgin plastics. However, although it appears to be a promising technology, challenges associated with high energy requirements, raw material variability, and scale infrastructure still need to be addressed to ensure industrial competitiveness and significant environmental benefits.

PENGARUH PERSEDIAAN BAHAN BAKU DAN TENAGA KERJA TERHADAP VOLUME PRODUKSI PADA PT BUKIT INTAN ABADI DI MEDAN

The availability of sufficient raw materials of good quality and support from qualified and highly committed workers will significantly determine the achievement of the targeted production volume. PT. Bukit Intan Abadi, as the locus of this research, is a company engaged in the wood sector with plywood as its main product. This study intends to determine the effect of raw material supply and labor on PT Bukit Intan Abadi production volume. This quantitative study uses data collection techniques carried out by observation, documentation studies, interviews, and questionnaires, with multiple linear regression data analysis techniques, t-tests, F-tests, and determination tests. The survey results with the t-test showed that the t-value of the raw material inventory variable was 4.526 t-count> t-table (4.526> 1.66757). The raw material inventory variable positively and significantly affects PT Bukit Intan Abadi Belawan's production volume. Furthermore, for the labor variable, the t-count value is known (13,322> 1.66757). It means that the labor variable positively and significantly affects production volume. Meanwhile, the results of the F test show that the F-count value is 96,330 compared to F-table 3.13, so F-count> F-table (96,330> 3.13). This means that the raw material and labor inventory variables positively affect PT Bukit Intan Abadi's production volume. Furthermore, the results of the determination test show that the R Adjust Square value is 0.742 or 74.2%. This means that raw materials and labor inventory can affect production volume by 74.2%, while the rest is influenced by other factors that have yet to be studied

Massive Screening of Food Extracts for Quality Assessment and Standardization of Allergenic Activity.

(1) Background: In drug discovery and pharmaceutical quality control, a challenge is to assess protein extracts used for allergy therapy and in vivo diagnosis, such as prick tests. Indeed, there are significant differences between the features of marketed products due to variations in raw materials, purification processes, and formulation techniques. (2) Methods: A protein array technology has been developed to provide comprehensive information on protein-biomarker interactions on a large scale to support the pharmaceutical industry and clinical research. The biosensing method is based on immobilizing low volumes of protein extracts (40 nL) on thermoplastic chips in array format. The biological activity was estimated by incubating with serum from representative food allergy patients. (3) Results: The reproducible optical signals were registered (deviation lower than 10%) using low-cost technologies such as a smartphone and a reader of digital versatile discs. The method was applied to pharmaceutical products to diagnose ten common food allergies, including barley, kiwi, milk, prawn, egg, peanut, wheat, peach, walnut, and squid. Quality indicators were established from spot intensities, enabling an effective comparison of manufacturers. (4) Conclusions: A biosensing-based strategy for screening pharmaceutical products emerges as a reliable and advantageous alternative to traditional approaches such as electrophoresis, fluorescence chips, and ELISA assays. This high-throughput method can contribute to understanding complex biological processes and evaluate the performance of pharmaceutical products.

Metagenomic Insights into the Bacterial Diversity of Balinese Fermented Sausage (Urutan) from the Household Industry

Fermented urutan is a dry fermented sausage made from a mixture of pork and Balinese spices, traditionally prepared using conventional methods. However, variations in spices and raw materials may affect the bacterial diversity of urutan. This study aimed to reveal the bacterial diversity of urutan from household industries using a metagenomic approach. A bacterial diversity analysis was conducted using Nanopore Sequencing Technology (ONT). Samples were collected from household industries in two regencies: Tabanan and Gianyar. The results show that Bacillota (98%) had the highest abundance in all samples at the phylum level. At the genus level, variations in bacterial composition were observed, with Staphylococcus (8–89%), Weissella (5–32%), and Lactococcus (3–39%) being the most abundant. The richness and diversity of bacterial species were greater in the KH group (Gianyar regency) than in the BRT group (Tabanan regency). A correlation analysis revealed that five genera—Staphylococcus, Lactococcus, Mammalicoccus, Macrococcoides, and Citrobacter—showed a strong correlation with the pH, water activity (aW), and acidity of fermented urutan. These findings provide insights into the bacterial community and could aid in the development of starter cultures to improve the consistency and quality of traditional fermented foods.

Microstructure-informed deep learning model for accurate prediction of multiple concrete properties

Predicting multiple properties of concrete using empirical models has become increasingly challenging due to the complexity of modern concrete formulations and the nonlinear behavior of their constituents. This study introduces a sequential model that integrates mix proportions with microstructural information of concrete. The model addresses the limitations of small datasets and the inherent variability in concrete's raw materials and production processes. A novel dataset comprising concrete mix proportions, 56,160 scanning electron microscope images, and their corresponding macroscopic properties was constructed for training and validation. We developed a sequential model integrating a Swin Transformer (Swin-T) with a Back Propagation Neural Network (BPNN), achieving superior accuracy in predicting compressive strength and permeability. Comprehensive evaluations using SHAP and GradCAM reveal the critical role of hydration products in these predictions, underscoring the enhanced interpretability and efficacy of our approach. This work advocates for the integration of microstructural insights to improve the reliability and precision of concrete assessments.

Identification of constitutive law for 3d-printed bioresorbable thermosensitive polymer to design medical devices for soft tissue reconstruction

Breast cancer concerns 1 in 8 women in the world and is followed in 40% of cases by a mastectomy. Only 14% of women receive reconstructive surgery because of unfavorable clinical issues. The need of innovative tissue engineering devices leads Lattice Medical company to bring a new 3D-printed device, allowing the regeneration of soft tissue in order to replace the withdrawn breast. The implant, based on TEC (tissue engineering chamber) and fat-flat surgical technique, is constituted with bioresorbable thermosensitive materials to be fully absorbed by the body in several months, once the regeneration process is completed. In this industrial context, we need to assess some properties for predictive simulation: the TEC mechanical and biological properties over time, its sensitivity to implantation in the body temperature, its batch raw material variability and its structural 3D-printed behavior. This would lead to a more enlightened numerical design and topological optimization work. To do so, mechanical testing are conducted to gather necessaries information for fully border the behaviour of the material and eventually the impact of the process on the final prosthesis. Then, the G’sell Law is chosen to model the mechanical behaviour of the material taking into account all particularities of this medical case. Finally, the behaviour law is used in Finite Element Method (FEM) in a compression simulation to compare with experimental results which find good similarity in the mechanical response.

Batch-to-batch differences in nutritional quality of selected raw and cooked pork offal

With a pressing need to enhance sustainability and reduce waste, harnessing the untapped nutritional wealth buried in by-products of the meat processing industry is more critical than ever. The research was aimed at comparing variation in raw material between batches and establishing a comprehensive database that would serve as a valuable resource for manufacturers seeking to exploit the potential of pork offal. This study is focused on analysing both raw and cooked offal, including liver, heart, kidney, spleen, blood, tongue, esophagus, as well as meat trimmings. Four batches were analysed with regard to their chemical composition, micro- and macro-element content, amino as well as fatty acid profile. The results indicate significant differences in raw material supplies from the same supplier across batches. In our study, all analysed pork offal and meat trimmings exhibited statistically significant variations between individual batches. Furthermore, clustering analysis conducted on the data will be beneficial in optimising recipes and formulations that utilise pork offal. This research may contribute to the sustainable utilization of meat by-products, waste reduction and overall value enhancement in the meat processing industry.

Carbohydrate composition of cow's milk and plant-based milk alternatives

The prevalence of lactose intolerance is one of the factors driving consumers toward plant-based milk alternatives (PBMA). This study aimed to analyze the carbohydrate profile of cows' milk (regular and lactose-free from both pasteurized and UHT milks; n = 80) and PBMA (n = 60) by HPLC. The study revealed that there was no significant difference in the energy content and total carbohydrate content between regular milk and lactose-free milk. Although milk and PBMA are entirely different food matrices, some PBMA types, as soya and coconut, may have energy contents and total carbohydrate contents comparable to those of milk. Furthermore, the variability observed in total carbohydrate content, as well as in carbohydrate profile, both between PBMA types and within samples of the same type, arises not only from variations in raw materials but also from the number of dilutions of the vegetable extract and the addition of different types and levels of carbohydrates, such as sucrose, fructose, or sorbitol, during PBMA manufacture. Although, milk presents a regular carbohydrate composition, differing solely between presentations (regular/lactose-free), the PBMA differs significantly between types and among the same type, not being for that reason regarded as a milk substitute.

Proses Negosiasi Antara UMKM A.M Tahu Dan Pemasok Bahan Baku Produksi

SME’s are an industry that play an important role in the Indonesia’s economic development. A.M Tahu as one of SME’s have problems in fulfilling raw materials. The existence of special orders and moral hazard from suppliers were often obstacles in the production process so that A.M. Tahu is needed to make a negotiation process to get affordable prices, good quality, and flexibility in the quantity of raw materials with a limited choice of suppliers. The negotiation process certainly does not immediately reach the desired agreement, but efforts need to be made to convince both parties. The research aims to determine the negotiation process that occurs between A.M Tahu and raw material suppliers in reaching agreements. The types of data used in this study are primary and secondary data using AHP (Analysis Hierarchy Process) analysis methods and qualitative descriptive. The results showed that the negotiation process for A.M Tahu has several stages in reaching an agreement between the two parties, including starting from preparation, meetings, offers, and finally agreements. A.M Tahu gets a more convenient raw material price of Rp3,000 per kilo than the price should be, soybean quantity flexibility, and good quality assurance of soybean grain raw materials. A.M Tahu is also prioritized to choose suppliers who are outside the sub-district, and make raw material variables the main thing to consider in supplier selection.

Thermal Performance of Lightweight Earth: From Prediction to Optimization through Multiscale Modeling

This study investigates the prediction of the thermal conductivity of lightweight earth and raw earth blocks incorporating plant aggregates. Given the high variability of raw materials, it is not currently possible to predict the thermal performance of this type of material before sample production. This is a major obstacle to using these eco-materials, although their use is widely encouraged to improve building performance under evolving regulatory frameworks such as The French RE2020 standard. The incorporation of plant aggregates into earth-based materials offers improved insulation properties without compromising their mechanical integrity, positioning them as promising sustainable alternatives. Mean-field homogenization techniques, including the Mori-Tanaka as well as double inclusion models, are used to develop predictive tools for thermal behavior, using rigorously selected experimental data. The selected methods are particularly relevant. The Mori-Tanaka model appears to be better suited when the proportion of aggregates is limited, whereas the double inclusion scheme proves its worth when a higher proportion of aggregates is incorporated. This study emphasizes the influence of aggregate types and processing methods on thermal conductivity, highlighting the need for precise formulation and processing techniques to optimize performance. This paper demonstrates the relevance of the applied homogenization techniques applied. It enables the real morphology of the materials studied, such as aggregate shape and intrinsic cracking, to be taken into account. It contributes to the advancement of eco-material modeling toward predictive digital twins, with the goal of simulating and optimizing complex material behavior under various environmental conditions.

Recommendation on the selection of powdered activated carbon as carrier to enhance performance of polymeric UF membrane

The addition of powdered activated carbon (PAC) has been widely accepted as a solution to alleviate membrane fouling and maintain a sustainable flux in membrane bioreactor (MBR) and anaerobic membrane bioreactor (AnMBR). This is due to PAC's unique characteristics, such as serving as a supportive medium for bacterial attachment and growth, achieving adsorption of organic foulants and providing abrasion effect that minimizes the formation of cake layers on membrane surfaces. While majority of ultrafiltration (UF) membranes used in MBR and AnMBR application are polymeric, no study has yet investigated the integrity of polymeric UF membranes with the addition of PAC adsorbents. The abrasive effects of PAC on membrane surfaces under gas sparging in AnMBR or air scouring in MBR have not been studied, and no guidelines have been established for selecting a reliable PAC for such purposes. To address these concerns, this study systemically investigated the integrity of polymeric UF membranes with five different types of PACs to establish recommendations for PAC selection. Based on the integrity testing of polymeric UF membranes, a recommendation for PAC selection was formulated, highlighting bulk density and Gold Number (GN) as pivotal criteria. Five distinct types of PACs were studied to determine the optimal characteristics for polymeric UF membranes, considering variations in raw materials (coal-based and wood-based), activation methods (chemical and steam), particle morphology (sharp and granular), bulk densities (ranging from 0.23 to 0.6 kg/L) and GNs (spanning from 0.1 to > 6.0). The investigation extended beyond 100 d or until irreversible defects were observed in the UF membranes. This study provides guidelines for selecting PACs to be used with polymeric UF membranes, aiming to improve membrane performance while minimising their impact on membrane surfaces.

Impact of surfactant raw material variability on extrudate clarity appearance (transparency) in HME continuous manufacturing

The appearance of an extrudate formulation was monitored during hot-melt extrusion (HME) continuous manufacturing over 3 days. The formulation matrix consisted of a polymeric component, copovidone, and a low molecular weight surfactant, polysorbate 80. Based on studies prior to the continuous manufacturing, the desired appearance of the target extrudate is translucent. Although process parameters such as feed rate and screw speed were fixed during the continuous manufacturing, the extrudate appearance changed over time from turbid to translucent. For root-cause investigation, the extrudates were analyzed offline by differential scanning calorimetry (DSC) and advanced polymer chromatography (APC™). Although the polysorbate 80 content of both turbid and translucent extrudates was within target, the glass transition temperature of the turbid extrudate was 2 °C above expected value. The observed turbidity was traced to lot-to-lot variability of the polysorbate 80 used in the continuous manufacturing, where APC™ analysis revealed that the relative content of the low molecular weight component varied from 23% to 27% in correlation with the evolution from turbid to translucent extrudates. This work stresses the importance of taking feeding material variability into account during continuous manufacturing.

A FRAMEWORK FOR LEAN MANUFACTURING IMPLEMENTATION IN THE TEXTILE INDUSTRY: A RESEARCH STUDY

This study investigates the implementation of lean manufacturing in the textile industry, focusing on its potential to enhance efficiency, reduce waste, and improve product quality. Lean manufacturing principles, including Just-In-Time (JIT) production, Kanban systems, value stream mapping, 5S workplace organization, and continuous improvement (Kaizen), have been widely recognized for their effectiveness in various manufacturing sectors. However, their application in the textile industry remains underexplored. Through a systematic literature review of 60 review papers and empirical analysis involving case studies, interviews, and surveys with industry experts, managers, and workers, this research identifies the significant benefits of lean practices in textile manufacturing. The findings reveal substantial efficiency gains, waste reduction, and quality improvements among companies adopting lean principles. Nevertheless, the study also highlights several industry-specific challenges, such as high variability in raw materials, complex production processes, and market pressures from fast fashion. These challenges necessitate tailored approaches and effective change management strategies for successful lean integration. Additionally, the research emphasizes the need for investment in advanced technologies and flexible manufacturing systems to enhance responsiveness to market changes. The study concludes that despite the challenges, lean manufacturing offers valuable strategies for textile companies aiming to improve their competitiveness and sustainability in the global market. This research contributes to the growing body of knowledge on lean manufacturing and provides practical insights for textile manufacturers seeking to adopt and optimize lean practices.

Back-propagation ANN to Predict Cleanliness and Quality of Cotton Spinning Preparatory Output: A Comprehensive Research

Background: Modern spinning preparatory has undergone drastic technological changes, but still, individual’s expertise-based decisions govern the complex and non-linear multivariant relationships prevailing amongst raw material (cotton) variables, machine variables, process variables (waste), and product (card sliver) quality. The scientifically precise prediction regarding the cleanliness and quality of card sliver and waste control for the given inputted cotton variables processed on the state-of-the-art machinery setup without waiting for the production and testing of card sliver is still impossible. Methods: The present work describes the use of Aritificial Neural Networks (ANN) for ruling out these limitations on scientific grounds. A complex system targeted at ANN was developed using the "newff" function on the mill's five-year database. Single-group ANN was initially designed to determine the influence of inherent variations in raw cotton fibre properties and trash content on blow room and card performance. A multi-group approach of ANN was developed at a later stage to define the influence of complex interactions amongst various fibre properties on three main quality measures considered at blow room and carding, viz., i) influence of blow room and card on fibre length properties, ii) fibre damage at blow room or improvement at card, and iii) degree of cleanliness of the output material. Results: Reverse modelling for both groups was also successfully designed to demarcate feed cotton quality and cleanliness requirements for targeted blow room or card cleaning performance. Conclusion: A high level of positive endurance was observed for all ANNs. Multigroup networking has proven to be more precise than single group networking.

Cycle-Based Control of Injection Moulding Process in Presence of Material Dual Sourcing Using Mass Feedback.

The low cost and precise tolerances of plastic injection moulded products are a major reason for the popularity of the manufacturing method. The tolerances are greatly influenced by the equipment, raw material and moulding process. One challenge is the raw material variation. This paper presents a production process using cycle based feedback of cycle mass, for control of part properties in the presence of material variation from dual sourcing. The part properties considered are part mass and outer dimensions. The process uses direct cycle mass feedback without additional process measurements in the proposed controller structure. The designed controller structure is tested in a multi-cavity mould while using raw materials from multiple vendors, encompassing five different grades. The results show a total decrease in part mass variance of approximately 50% and a decrease of length and width variance of approximately 40% compared to a moulding process with fixed settings.

Geopolymer Cement in Pavement Applications: Bridging Sustainability and Performance

Sustainability and the quest for a more robust construction material cannot be divorced from each other. While Portland cement has revolutionized the construction sector, its environmental toll, particularly in greenhouse gas emissions and global warming, cannot be ignored. Addressing this dilemma requires embracing alternatives like geopolymer cement/geopolymer binder (GPC/GPB). Over the last few decades, considerable strides have been achieved in advancing GPC as a sustainable construction material, including its utilization in pavement construction. Despite these advances, gaps still exist in GPC optimal potential in pavement construction, as most studies have concentrated on specific attributes rather than on a comprehensive evaluation. To bridge this gap, this review adopts a novel, holistic approach by integrating environmental impacts with performance metrics. To set the stage, this review first delves into the geopolymer concept from a chemistry perspective, providing an essential broad overview for exploring GPC’s innovations and implications in pavement applications. The findings reveal that GPC not only significantly reduces greenhouse gas emissions and energy consumption compared to Portland cement but also enhances pavement performance. Further, GPC concrete pavement exhibits superior mechanical, durability, and thermal properties to ensure its long-term performance in pavement applications. However, challenges to GPC utilization as a pavement material include the variability of raw materials, the need for suitable hardeners, the lack of standardized codes and procedures, cost competitiveness, and limited field data. Despite these challenges, the process of geopolymerization presents GPC as a sustainable material for pavement construction, aligning with Sustainable Development Goals (SDGs) 3, 9, 11, and 12.

Past human decision-making based on stone tool performance: Experiments to test the influence of raw material variability and edge angle design on tool function

One of the main interests in the interpretation of the archaeological record and its variability within and through time and space is the production and use of past human stone tool technologies. Tool design and function are inevitably intertwined and strongly related to tool use. Understanding tool design provides information about early human technological adaptations and reflects human behaviour in the sense of conscious or unconscious decision-making. Nevertheless, the reason for major changes (including novelties, innovations, and loss) in past human stone tool technology is still poorly understood. A comprehensive approach focusing on tool function (What was the tool meant for?) and use (What was the tool used for?) can help to overcome this gap. While tool function (including performance) can be investigated experimentally, tool use can be addressed with use-wear analyses. These questions can be best investigated on technological systems showing little tool variability but strong evidence of maintenance and long-term use, such as Middle Palaeolithic industries.The Late Middle Palaeolithic record of Central and Eastern Europe is marked by the emergence of an asymmetric tool-type called Keilmesser (bifacial backed knives). Due to their sophisticated morphology, Keilmesser as a case study offer the potential to address aspects of raw material selection, tool production, maintenance, and reworking.This paper presents the results of an experiment designed to study the tool performance of Keilmesser from three archaeological sites, namely Balver Höhle, the Upper site of Buhlen and Grotte de Ramioul by testing raw material, edge angle and movement as independent variables. A highly controlled, sequential experiment was conducted using a mechanical device performing unidirectional cutting and carving movements on hard contact material. Results demonstrate the possibility to perform the mentioned task with 35° and 45° edge angles, maintaining function, albeit at differing levels of efficiency. The data has a direct impact on the interpretation of the archaeological assemblages regarding aspects such as stone tool morphology and resharpening. At the same time, the study highlights the importance of raw material analysis to understand the variability in the archaeological record and the implications on past human decision-making strategies.

Addressing raw material variability: In-line FTIR sugar composition analysis of lignocellulosic process streams

For a sustainable economy, biorefineries that use second-generation feedstocks to produce biochemicals and biofuels are essential. However, the exact composition of renewable feedstocks depends on the natural raw materials used and is therefore highly variable. In this contribution, a process analytical technique (PAT) strategy for determining the sugar composition of lignocellulosic process streams in real-time to enable better control of bioprocesses is presented. An in-line mid-IR probe was used to acquire spectra of ultra-filtered spent sulfite liquor (UF-SSL). Independent partial least squares models were developed for the most abundant sugars in the UF-SSL. Up to 5 sugars were quantified simultaneously to determine the sugar concentration and composition of the UF-SSL. The lowest root mean square errors of the predicted values obtained per analyte were 1.02 g/L arabinose, 1.25 g/L galactose, 0.50 g/L glucose, 1.60 g/L mannose, and 0.85 g/L xylose. Equipped with this novel PAT tool, new bioprocessing strategies can be developed for UF-SSL.