Microalgae are rich in valuable biomolecules and grow on non-arable land with rapid growth rate, which has a host of new possibility as alternative protein sources. In the present study, extraction of proteins from Chlorella vulgaris via an efficient technique, Liquid Triphasic Flotation (LTF) system, was studied. The optimized conditions in LTF system were 70% v/v of t-butanol, 40% w/v of salt solution, 0.5% w/v of biomass, pH 5.54, 1:1 of salt to t-butanol solution, and 10 min of air flotation time to attain 87.23% of protein recovery and 56.72% of separation efficiency. Besides, the study on recycling t-butanol has demonstrated that only one run was sufficient to maintain the performance of system. The efficiency of LTF in extracting protein has performed better than just Three Phase Partitioning (TPP) system. LTF system is hence an effective protein extraction and purification method with minimum operation unit and processing time.
Ionic liquids (ILs) have emerged as an alternative solvent used in the bioprocessing of microalgae for recovery of valuable biomolecules. The aim of this work is to extract fucoxanthin from Chaetoceros calcitrants (C. calcitrans) by using the readily distillable CO2-based alkyl carbamate ILs. The degree of cell permeabilization was analysed by the quantification of extracted fucoxanthin and the analyses of cell surface morphology. Among the tested CO2-based alkyl carbamate ILs, diallylammonium diallylcarbamate (DACARB) extraction system gave the maximal yield of fucoxanthin at 17.51 mg/g under the optimal extraction conditions [90% (v/v), 3 min and 25 °C]. Moreover, the extracted fucoxanthin fraction exhibited the satisfactory antioxidant activities. The recyclability of DACARB was demonstrated in the multiple batches of fucoxanthin extraction. Hence, CO2-based alkyl carbamate ILs can prospectively substitute conventional organic solvents in the downstream processing of bioactive compounds from microalgae.
The accumulation of conventional petroleum-based polymers has increased exponentially over the years. Therefore, algae-based biopolymer has gained interest among researchers as one of the alternative approaches in achieving a sustainable circular economy around the world. The benefits of microalgae biopolymer over other feedstock is its autotrophic complex to reduce the greenhouse gases emission, rapid growing ability with flexibility in diverse environments and its ability to compost that gives greenhouse gas credits. In contrast, this review provides a comprehensive understanding of algae-based biopolymer in the evaluation of microalgae strains, bioplastic characterization and bioplastic blending technologies. The future prospects and challenges on the algae circular bioeconomy which includes the challenges faced in circular economy, issues regard to the scale-up and operating cost of microalgae cultivation and the life cycle assessment on algal-based biopolymer were highlighted. The aim of this review is to provide insights of algae-based biopolymer towards a sustainable circular bioeconomy.
The work aimed to study the potential in producing a system with high microalgal protein recovery and separation by utilizing a one-step or integrated downstream process. This in turn enables green biorefinery of protein, contributing to circular bioeconomy whereby less energy, labor, and cost are required for the process. By utilizing electric three phase partitioning flotation system, high protein recovery yield, R of 99.42 ± 0.52% and high separation efficiency, E of 52.72 ± 0.40% system was developed. Scaling up also showed high protein recovery yield with R value of 89.13 ± 1.56%. Total processing duration (extraction, separation, and purification) was also significantly reduced to 10 min. This system showed remarkable potential in reducing processing time, alternatively cost of production, benefiting microalgal downstream processing. Concisely, through this system, microalgal bioprocessing will no longer be complex allowing a wide array of potentials for further studies in this field.
Industrial effluents such as pharmaceutical residues, pesticides, dyes, and metal processes holds abundant value-added products (VAPs), where its recovery has become essential. The purpose of such recovery is for sustainable treatment, which is an approach that considers the economic, social, and environmental aspects. Microalgae with its potential in the recovery process from effluents, can reduce energy usage of waste management strategies and regenerate nutrients such as carbon, phosphorus, and nitrogen. Microalgae cultures offer the use of inorganic materials by microalgae for their growth and the help of bacteria to produce biomass, thus, resulting in the absence of secondary emissions due to its ability to eliminate volatile organic compounds. Moreover, recovered bioactive compounds are transformed into bioethanol, bio-fertilizers, biopolymer, health supplements and animal feed. Therefore, it is significant to focus on an economical and efficient utilization of microalgae in recovering nutrients that can be further used in various commercial applications.
Continuous automation of conventional industrial operations with smart technology have drawn significant attention. Firstly, the study investigates on optimizing the proportion of industrial biscuit processing waste powder, (B) substituted into BG-11 as a source of cultivation medium for the growth of C. vulgaris. Various percentages of industrial biscuit processing waste powder, (B) were substituted in the inorganic medium to analyse the algal growth and biochemical composition. The use of 40B combination was found to yield highest biomass concentration (4.11 g/L), lipid (260.44 mg/g), protein (263.93 mg/g), and carbohydrate (418.99 mg/g) content compared with all the other culture ratio combination. Secondly, the exploitation of colour acquisition was performed onto C. vulgaris growth phases, and a novel photo-to-biomass concentration estimation was conducted via image processing for three different colour model pixels. Based on linear regression analysis the red, green, blue (RGB) colour model can interpret its colour variance precisely.
Microalgae biorefinery is presently receiving a lot of attention as driven by its production of high value-added products. In this study, an oleaginous microalga Aurantiochytrium limacinum SR21 was cultured for docosahexaenoic acid (DHA) production using 20% (w/v) of K2HPO4-waste feedstock to replace 0.005% (w/v) of KH2PO4 in the flask culture. DHA is an essential nutrient for human's brain functionalities. Collectively, the K2HPO4-waste feedstock with working concentration of 0.005% (w/v) in the cultivation prompted a higher lipid content (8.29%) and DHA production (128.81 mg.L-1). Moreover, natural plant pigment products containing stabilised betacyanins were utilised as natural red colourants for hard candy production. This study develops microalgal cultivation using salt-rich waste feedstock for a higher lipid and DHA content as well as application of natural colouring agents in food products.
Liquid biphasic flotation (LBF), an integrated process of liquid biphasic system (LBS) and adsorptive bubbles flotation, was used for the purification of C-phycocyanin from S. platensis microalgae. Various experimental parameters such as type of phase forming polymer and salt, concentration of phase forming components, system pH, volume ratio, air flotation time and crude extract concentration were evaluated to maximise the C-phycocyanin recovery yield and purity. The optimal conditions for the LBF system achieving C-phycocyanin purification fold of 3.49 compared to 2.43 from the initial LBF conditions was in polyethylene glycol (PEG) 4000 and potassium phosphate combination, with 250 g/L of polymer and salt concentration each, volume ratio of 1:0.85, system pH of 7.0, air flotation duration of 7 min and phycocyanin crude extract concentration of 0.625 %w/w. The LBF has effectively enhanced the purification of C-phycocyanin in a cost effective and simple processing.
The thermal characteristics of Actinobacillus succinogenes (AS) from pyrolysis, torrefaction, and combustion are analyzed to evaluate the potential of this biomass as a renewable fuel. AS pyrolysis can be classified into four stages, and its main decomposition zone is at 200-500 °C. The solid yield of AS after 60 min torrefaction is over 60 wt%, and the torrefaction severity index map indicates that a high torrefaction temperature with a short duration has a more profound influence on its decomposition. The Py-GC/MS analysis of AS suggests that the volatile products from 500 °C pyrolysis are similar to microalgae-derived pyrolysis bio-oils. The combustibility index (S) of AS is 4.07 × 10-7 which is much higher than that of lignite coal (0.39 × 10-7) and bituminous coal (0.18 × 10-7), and close to those of biochar and bio-oil. The obtained results are conducive to the development of microorganisms as fuel to achieve a circular bioeconomy.
Microalgae are autotroph organisms that utilise light energy to synthesize various high-value bioactive compounds such as polysaccharides, proteins and lipids. Due to its fast growth rate and capability to survive in harsh environment, microalgae nowadays are applied in various industrial areas. The process of obtaining microalgae-based biomolecules starts with the selection of suitable microalgae strain, cultivation, followed by downstream processing of the biomass (i.e., pre-treatment, harvesting, extraction and purification). The end products of the processes are biofuels and other valuable bioproducts. Nevertheless, low production yield and high-cost downstream processes are the emerging bottlenecks which need to be addressed in the upscaling of extracted compounds from microalgae biomass. To conclude, tremendous efforts are required to overcome these challenges to revolutionize microalgae into a novel and green factory of different bioactive compounds for industrial necessities to satisfy and fulfil global demands.
Haematococcus pluvialis is one of the most abundant sources of natural astaxanthin as compared to others microorganism. Therefore, it is important to understand the biorefinery of astaxanthin from H. pluvialis, starting from the cultivation stage to the downstream processing of astaxanthin. The present review begins with an introduction of cellular morphologies and life cycle of H. pluvialis from green vegetative motile stage to red non-motile haematocyst stage. Subsequently, the conventional biorefinery methods (e.g., mechanical disruption, solvent extraction, direct extraction using vegetable oils, and enhanced solvent extraction) and recent advanced biorefinery techniques (e.g., supercritical CO2 extraction, magnetic-assisted extraction, ionic liquids extraction, and supramolecular solvent extraction) were presented and evaluated. Moreover, future prospect and challenges were highlighted to provide a useful guide for future development of biorefinery of astaxanthin from H. pluvialis. The review aims to serve as a present knowledge for researchers dealing with the bioproduction of astaxanthin from H. pluvialis.
The aim of this work was to study the ultrasonication-assisted Liquid Tri-phasic Flotation (LTF) System to obtain lipid and protein from microalgae Chlorella sorokiniana in a single step as a novel process. In the current study, biorefinery of Chlorella sorokiniana was performed using LTF system in a single step. The highest protein recovery of 97.43 ± 1.67% and lipid recovery of 69.50 ± 0.54% were obtained. The corresponding parameters were microalgae biomass loading of 0.5 w/v%, ammonium sulphate concentration of 40 w/v%, volume ratio of 1:1.5 (salt:alcohol), ultrasonication pulse mode of 20 s ON/20 s OFF at 20% amplitude for 5 mins, flotation air flowrate of 100 mL/min. Additionally, recycling of alcohol phase to study the circular nature of proposed biorefinery was investigated. The proposed LTF system for extraction of proteins and lipid reduces the number of operation units required in this biorefinery approach.
The efforts have been made to review phyllosilicate derived (clay-based) heterogeneous catalysts for biodiesel production via lignocellulose derived feedstocks. These catalysts have many practical and potential applications in green catalysis. Phyllosilicate derived heterogeneous catalysts (modified via any of these approaches like acid activated clays, ion exchanged clays and layered double hydroxides) exhibits excellent catalytic activity for producing cost effective and high yield biodiesel. The combination of different protocols (intercalated catalysts, ion exchanged catalysts, acidic activated clay catalysts, clay-supported catalysts, composites and hybrids, pillared interlayer clay catalysts, and hierarchically structured catalysts) was implemented so as to achieve the synergetic effects (acidic-basic) in resultant material (catalyst) for efficient conversion of lignocellulose derived feedstock (non-edible oils) to biodiesel. Utilisation of these Phyllosilicate derived catalysts will pave path for future researchers to investigate the cost-effective, accessible and improved approaches in synthesising novel catalysts that could be used for converting lignocellulosic biomass to eco-friendly biodiesel.
Microalgae have emerged as an effective dual strategy for bio-valorisation of food processing wastewater and food waste hydrolysate which favours microalgae cultivation into producing value-added by products mainly lipids, carbohydrates, and proteins to the advantages of bioplastic production. Moreover, various microalgae have successfully removed high amount of organic pollutants from food processing wastewater prior discharging into the environment. Innovation of microalgae cultivating in food processing wastewater greatly reduced the cost of wastewater treatment compared to conventional approach in terms of lower carbon emissions, energy consumption, and chemical usage while producing microalgae biomass which can benefit low-cost fertilizer and bioplastic applications. The study on several microalgae species has all successfully grown on food waste hydrolysates showing high exponential growth rate and biomass production rich in proteins, lipids, carbohydrates, and fatty acids. Multiple techniques have been implemented for the extraction of food wastes to be incorporate into the bioplastic production.
The litter of persistent organic pollutants (POPs) into the water streams and soil bodies via industrial effluents led to several adverse effects on the environment, health, and ecosystem. For the past decades, scientists have been paying efforts in the innovation and development of POPs removal from wastewater treatment. However, the conventional methods used for the removal of POPs from wastewater are costly and could lead to secondary pollution including soil and water bodies pollution. In recent, the utilization of green mechanisms such as biosorption, bioaccumulation and biodegradation has drawn attention and prelude the potential of green technology globally. Microalgae-bacteria consortia have emerged to be one of the latent wastewater treatment systems. The synergistic interactions between microalgae and bacteria could proficiently enhance the existing biological wastewater treatment system. This paper will critically review the comparison of conventional and recent advanced wastewater treatment systems and the mechanisms of the microalgae-bacteria symbiosis system.
This research work aims to fabricate an optimized up-scaled photobioreactor and extraction tank which incorporates the Internet of Things (IoT) for remote monitoring of selected parameters without being present in the lab as the industry is gradually moving towards the direction of remote operation. Several design factors were considered where modelling using ANSYS was carried out before the finalised design is drawn using AutoCAD. To monitor critical parameters that include liquid level, temperature, and pH condition during the operation of the tanks, water-proof sensors are implemented with the aid of Arduino NodeMCU board and the sensors are linked with Blynk, a smartphone application that allows remote monitoring via Wi-Fi connection. The sensors' results obtained using the Blynk application show high accuracy as compared with manual data except for photobioreactor liquid level. This shows that IoT and remote monitoring can be integrated successfully.
Artificial intelligence (AI) and machine learning (ML) are currently used in several areas. The applications of AI and ML based models are also reported for monitoring and design of biological wastewater treatment systems (WWTS). The available information is reviewed and presented in terms of bibliometric analysis, model's description, specific applications, and major findings for investigated WWTS. Among the applied models, artificial neural network (ANN), fuzzy logic (FL) algorithms, random forest (RF), and long short-term memory (LSTM) were predominantly used in the biological wastewater treatment. These models are tested by predictive control of effluent parameters such as biological oxygen demand (BOD), chemical oxygen demand (COD), nutrient parameters, solids, and metallic substances. Following model performance indicators were mainly used for the accuracy analysis in most of the studies: root mean squared error (RMSE), mean square error (MSE), and determination coefficient (DC). Besides, outcomes of various models are also summarized in this study.
The identification of microalgae species is an important tool in scientific research and commercial application to prevent harmful algae blooms (HABs) and recognizing potential microalgae strains for the bioaccumulation of valuable bioactive ingredients. The aim of this study is to incorporate rapid, high-accuracy, reliable, low-cost, simple, and state-of-the-art identification methods. Thus, increasing the possibility for the development of potential recognition applications, that could identify toxic-producing and valuable microalgae strains. Recently, deep learning (DL) has brought the study of microalgae species identification to a much higher depth of efficiency and accuracy. In doing so, this review paper emphasizes the significance of microalgae identification, and various forms of machine learning algorithms for image classification, followed by image pre-processing techniques, feature extraction, and selection for further classification accuracy. Future prospects over the challenges and improvements of potential DL classification model development, application in microalgae recognition, and image capturing technologies are discussed accordingly.
Microalgae are photoautotrophic microorganisms which comprise of species from several phyla. Microalgae are promising in producing a varieties of products, including food, feed supplements, chemicals, and biofuels. Medicinal supplements derived from microalgae are of a significant market in which compounds such as -carotene, astaxanthin, polyunsaturated fatty acids (PUFA) such as docosahexaenoic acid (DHA) and eicosapentaenoic acid (EPA), and polysaccharides such as -glucan, are prominent. Microalgae species which are commonly applied for commercial productions include Isochrysis sp., Chaetoceros (Chlorella sp.), Arthrospira sp. (Spirulina Bioactive) and many more. In this present review, microalgae species which are feasible in metabolites production are being summarized. Metabolites produced by microalgae as well as their prospective applications in the healthcare and pharmaceutical industries, are comprehensively discussed. This evaluation is greatly assisting industrial stakeholders, investors, and researchers in making business decisions, investing in ventures, and moving the production of microalgae-based metabolites forward.
The rapid expansion of industrialization and continuous population growth have caused a steady increase in energy consumption. Despite using renewable energy, such as bioethanol, to replace fossil fuels had been strongly promoted, however the outcomes were underwhelming, resulting in excessive greenhouse gases (GHG) emissions. Microalgal biochar, as a carbon-rich material produced from the pyrolysis of biomass, provides a promising solution for achieving net zero emission. By utilizing microalgal biochar, these GHG emissions can be captured and stored efficiently. It also enhances soil fertility, improves water retention, and conduct bioremediation in agriculture and environmental remediation field. Moreover, incorporating microalgal biochar into a zero-waste biorefinery could boost the employ of biomass feedstocks effectively to produce valuable bioproducts while minimizing waste. This contributes to sustainability and aligns with the concepts of a circular bioeconomy. In addition, some challenges like commercialization and standardization will be addressed in the future.