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Item Open Access Algae bioremediation of swine and domestic wastewater promotes a reduction of coliforms and antibiotic-resistant bacteria(Elsevier, 2025-06-15) López-Pacheco, Itzel Y.; González-Meza, Georgia María; González-González, Reyna Berenice; Parra-Saldívar, Roberto; Melchor-Martínez, Elda MThe microbiological load that wastewater may contain is an important factor to consider in wastewater treatment to avoid water bodies contamination and has taken on great relevance due to the possible presence of antibiotic-resistant bacteria. This study investigates the feasibility of bacteria control by phycoremediation treatment using Scenedesmus sp. in two types of wastewater (domestic and swine wastewater). It was determined the cell growth of microalgae culture, and the reduction of total coliforms and enterobacteria load throughout ten days of experiment. In addition, the removal of antibiotic-resistant bacteria was performed using five different antibiotics commonly used in clinical diagnosis: Ampicillin Tetracycline, Ciprofloxacin, Sulfamethoxazole, and Ceftriaxone. The results shown a significant decrease in total coliforms and enterobacteria in the phycoremediation process, it was removed up to 98 % of total coliforms [ from (8.7 ± 2.31) × 10^4 to (1.6 ± 0.17) × 10^3 CFU mL^−1] in swine wastewater and 99 % in domestic wastewater [(3.6 ± 0.31) × 10^5 to (2 ± 0.05) × 10^3 CFU mL^−1]. Significant reduction in the case of sulfamethoxazole-resistant bacteria by microalgae in swine wastewater from [(1.47 ± 0.05) × 105 to (5.3 ± 0.57) × 10^3 ] and domestic wastewater [(4.9 ± 0.15) × 10^4 to (2.9 ± 0.36) × 10^3]. These findings demonstrate the versatility and effectiveness of the phycoremediation system since the general microbial control to most specific of antibiotic-resistant bacteria in wastewater, demonstrating its great potential to reduce the risk of public health issues in urban and rural areas.Item Open Access An analysis of factors that influence the spatial pattern of faecal matter flow in unsewered cities(Elsevier, 2025-05-25) Sultana, M. Sufia; Waine, Toby W.; Bari, Niamul; Tyrrel, SeanThe management of sanitation systems in unsewered cities in low and middle income countries is a critical issue, yet it is unclear where the risk hotspots are and where interventions should be focused. This study utilised a prototype model, developed by the authors, to map the spatial pattern of faecal flow in Rajshahi city, a secondary city in northwest Bangladesh with a population around a million. This city serves as a representative example of 60 such secondary cities in Bangladesh and hundreds more in the economically developing region in Asia, Africa and Latin America. The model relies on assumptions that carry significant uncertainties; hence, the study employed a sensitivity analysis with multiple plausible scenarios to characterise these uncertainties, aiming to identify ways to improve the model further. Five major influencing factors on the spatial pattern of faecal flow were identified: the emptying of septic tanks, the use of soak pits, and sludge removal from drains, variations in faecal matter production by building types, and the presence or absence of toilets. These factors were shown to collectively have a significant impact (almost 50 % changed) on the model outcome, depending upon the assumptions made. The study offers insights that will guide future data collection efforts by emphasising the need to understand these specific influencing factors and their spatial pattern. Consequently, this research has broader implications for urban sanitation management as well as associated public health research like wastewater surveillance, risk assessment, and disease dynamics in similar urban settings, offering insights into areas of uncertainty that need to be addressed in future modelling efforts.Item Open Access An overview of non-destructive technologies for postharvest quality assessment in horticultural crops(Taylor & Francis, 2025) O’Brien, Ciara; Alamar, M. CarmenArtificial intelligence and machine vision are increasingly popular within food supply chains for automated decision making in quality grading and disease identification. There are many types of data that these models can be trained on, and choosing which information is needed is a critical factor in minimising both food loss and cost, while maximising the impact on food quality. Non-destructive technologies give information about crop phenotypes (e.g. external colour, oil content, sweetness) without damaging the crop, allowing a greater and more representative proportion the stored food to be analysed. These non-destructive technologies use different methods to analyse the product, each with different intrinsic capabilities and limitations. Therefore, choosing which technology is most appropriate for each application is a complex and costly decision. This mini-review summarises the physical and chemical basis of how some popular non-destructive technologies function, and how these different methods give unique advantages and limitations. The most popular technologies summarised include Red-Green-Blue (RGB) imaging, visible and near-infrared spectroscopy, and vibrometry. We also review technologies that are growing in popularity, including X-ray imaging, ultraviolet spectroscopy, and magnetic resonance imaging.Item Open Access Anaerobic microbial core for municipal wastewater treatment — the sustainable platform for resource recovery(Elsevier, 2025-08-01) Conall Holohan, B.; Trego, Anna; Keating, Ciara; Bressani-Ribeiro, Thiago; Chernicharo, Carlos L.; Daigger, Glen; Galdi, Stephen M.; Knörle, Ulrich; Paissoni, Eleonora; Robles, Angel; Rogalla, Frank; Shin, Chungheon; Soares, Ana; Smith, Adam L.; Szczuka, Aleksandra; Hughes, Dermot; O’Flaherty, VincentThe requirement for carbon neutrality and bioresource recovery has shifted our views on water treatment from health and pollution avoidance to one of sustainability with water and nutrient circularity. Despite progress, the current process of wastewater treatment is linear, based on core aerobic microbiology, which is unlikely to be carbon neutral due to its large use of energy and production of waste sludge. Here, we outline a shift from aerobic to anaerobic microbiology at the core of wastewater treatment and resource recovery, illustrating the state-of-the-art technologies available for this paradigm shift. Anaerobic metabolism primarily offers the benefit of minimal energy input (up to 50% reduction) and minimal biomass production, resulting in up to 95% less waste sludge compared with aerobic treatment, which is increasingly attractive, given dialogue surrounding emerging contaminants in biosolids. Recent innovative research solutions have made ambient (mainstream) anaerobic treatment a ready substitute for the aerobic processes for municipal wastewater in temperate regions. Moreover, utilising anaerobic treatment as the core carbon removal step allows for more biological downstream resource recovery with several opportunities to couple the process with (anaerobic) nitrogen and phosphorus recovery, namely, potential mainstream anaerobic ammonium oxidation (anammox) and methane oxidation (N-DAMO). Furthermore, these technologies can be mixed and matched with membranes and ion-exchange systems, high-value biochemical production, and/or water reuse installations. As such, we propose the reconfiguration of the wastewater treatment plant of the futurewith anaerobic microbiology. Mainstream anaerobic treatment at the core of a truly sustainable platform for modern municipal wastewater treatment, facilitating circular economy and net-zero carbon goals.Item Open Access Appropriate technologies or appropriating technologies? Technopolitics within artisanal and small-scale mining in Ghana(Elsevier, 2025-07-01) Ofori, Alesia Dedaa; Awolorinke, Augustine Chiga; Amankwaah, Gad AmoakoThis article contributes to the discourse on the significance of “appropriate” technologies in formalising artisanal and small-scale gold miners' activities. By raising the question of what or who defines what is “appropriate” for artisanal miners, the paper engages critically with the ignored and complicated spatial and temporal dynamics that underpin miners’ decisions regarding technologies and the impact of these choices on the political ecology of artisanal gold mining. Until recently, technologies used by small and artisanal miners have been known to be crude and rudimentary, with deleterious impacts on the natural environment. Hence, the policy drive to formalise illegal miners has emphasised the essence of appropriate technologies, depoliticizing the complex underpinning factors that shape technology adoption and rejection. Thus, the paper focuses on two technologies that have become prevalent in the artisanal mining scene in Ghana, i.e. the Chinese Changfa and the Trommel, to demonstrate the complex and myriad ways miners determine which technology is appropriate. Appropriate technologies, the paper argues, are determined based on a multifaceted combination of socio-political, economic, ecological, biophysical and cultural factors. The paper concludes by discussing the implications of these observations on the formalisation of artisanal miners amid the increasing demand for energy transition minerals in developing economies.Item Open Access Artificial intelligence for prediction of shelf-life of various food products: recent advances and ongoing challenges(Elsevier, 2025-05-01) Rashvand, Mahdi; Ren, Yuqiao; Sun, Da-Wen; Senge, Julia; Krupitzer, Christian; Fadiji, Tobi; Miró, Marta Sanzo; Shenfield, Alex; Watson, Nicholas J.; Zhang, HongweiBackground: Accurate estimation of shelf-life is essential to maintain food safety, reduce wastage, and improve supply chain efficiency. Traditional methods such as microbial and chemical analysis, and sensory evaluation provide reproducible results but require time and labor and may not be suitable for real-time or high-throughput applications. The integration of artificial intelligence (AI) with advanced analysis techniques offers a suitable alternative for rapid, data-driven estimation of shelf-life in dynamic storage environments. Approach and scope: The current review assesses the application of AI-based techniques such as machine learning (ML), deep learning (DL), and hybrid approaches in food product shelf life prediction. This study highlights how AI can be utilized to examine data from non-destructive testing methods like hyperspectral imaging, spectroscopy, machine vision, and electronic sensors to enhance predictive performance. The review also describes how AI-based techniques contribute to managing food quality, reduce economic losses, and enhance sustainability by ensuring optimized food distribution and reducing waste. Key findings and conclusions: AI techniques overcome conventional techniques by considering intricate, multi-sourced information capturing microbiological, biochemical, and environmental factors influencing food spoilage. Meat, dairy, fruits and vegetables, and beverage case studies illustrate AI techniques' superiority in real-time monitoring and quality assessment. It also identifies limitations such as data availability, model generalizability, and computational cost, constraining extensive applications. Cloud and Internet of Things (IoT) platform integration into future applications has to be considered to enable real-time decision-making and adaptive modeling. AI can be a paradigm-changing tool in food industries with intelligent, scalable, and low-cost interventions in food safety, waste reduction, and sustainability.Item Open Access Artificial intelligence-driven innovation in Ganoderma spp.: potentialities of their bioactive compounds as functional foods(Royal Society of Chemistry (RSC), 2025) Khanal, Sonali; Sharma, Aman; Pillai, Manjusha; Thakur, Pratibha; Tapwal, Ashwani; Kumar, Vinod; Verma, Rachna; Kumar, DineshGanoderma spp., which are essential decomposers of lignified plant materials, can affect trees in both wild and cultivated settings. These fungi have garnered significant global interest owing to their potential to combat several chronic, complicated, and infectious diseases. As technology progresses, researchers are progressively employing artificial intelligence (AI) for studying various fungal strains. This novel approach has the potential to accelerate the knowledge and application of Ganoderma spp. in the food industry. The development of extensive Ganoderma databases has markedly expedited research on them by enhancing access to information on bioactive components of Ganoderma and promoting collaboration with the food sector. Progress in AI techniques and enhanced database quality have further advanced AI applications in Ganoderma research. Techniques such as machine learning (ML) and deep learning employing various methods, including support vector machines (SVMs), Bayesian networks, artificial neural networks (ANNs), random forests (RFs), and convolutional neural networks (CNNs), are propelling these advancements. Although AI possesses the capacity to transform Ganoderma research by tackling significant difficulties, continuous investment in research, data dissemination, and interdisciplinary collaboration are necessary. AI could facilitate the development of customized functional food products by discerning patterns and correlations in customer data, resulting in more specific and accurate solutions. Thus, the future of AI in Ganoderma research looks auspicious, presenting prospects for ongoing advancement and innovation in this domain.Item Open Access Atoxigenic isolates of Aspergillus flavus effectively reduce cyclopiazonic acid in a sorghum-based matrix under simulated abiotic stress conditions(Oxford University Press (OUP), 2025-05-15) Sharma, Vanshika; Cervini, Carla; Verheecke-Vaessen, Carol; Bandyopadhyay, Ranajit; Medina, Angel; Ortega-Beltran, Alejandro; Magan, NareshMaize, groundnut, and sorghum are important staple crops in several countries, but are prone to mycotoxin contamination. In the tropics and subtropics, Aspergillus flavus frequently contaminates those crops with aflatoxins and, sometimes, with cyclopiazonic acid (CPA). However, some genotypes cannot produce one or both toxins. In various countries, atoxigenic isolates of A. flavus are formulated into biocontrol products for field use to outcompete aflatoxin producers. The products effectively limit aflatoxin but their utility to reduce CPA remains unexplored. The abilities of four atoxigenic isolates (AF-) from Burkina Faso to control CPA by an isolate with high capacity to produce aflatoxins (AF+) and CPA was tested in co-inoculations at varying ratios (100+, 75+/25-, 50+/50-, 25+/75-, 100-), under simulated abiotic stress conditions. Experiments were conducted on 2% sorghum-based media at 0.95 and 0.90 water activity (aw), at 30°C and 37°C, for 12 days. CPA was quantified using LC-MS/MS. CPA concentrations gradually decreased as the proportion of atoxigenic isolates increased, with effectiveness varying depending on the environmental conditions.Item Open Access Changes in land capability for agriculture under climate change in Wales(Elsevier, 2025-07-25) Hannam, Jacqueline A.; Keay, Caroline A.; Mukherjee, Kriti; Rugg, Ian; Williams, Arwel; Cooke, JamesLand capability assessments are key models that can identify current and future capacity of land for agricultural production. However, assessments of land capability under climate change do not fully consider climate-soil-crop interactions, are produced at scales too coarse for decision making and exclude key end users. We tackle these gaps by co-developing a predictive fine-scale spatial assessment of Agricultural Land Classification in Wales for baseline climate (1961-1990) and future climate scenarios. The findings revealed an increase in the proportion of land with better agricultural potential in 2020 (2010-2039) and 2050 (2040-2069) compared to the baseline, becoming more favourable for agriculture due to decreased soil wetness. However, by 2080 (2070-2099), there was a reduction in the proportion of higher grade and best and most versatile land for agriculture. During this period, an increase in accumulated temperature and decrease in rainfall during the growing season resulted in higher soil moisture deficits and increased risk of summer drought. We identified soil droughtiness as the most limiting factor for agricultural capability in 2080, resulting in a decrease in the best and most versatile land for agriculture (by 2 to 11% compared to the baseline). The transparency of the approach and prediction of land capabilities at local scale enabled effective policy implementation and decision making. The predicted future changes in land capability highlight that policy instruments used currently to protect high grade agricultural land should also consider the potential impacts of climate change.Item Open Access Circular bioeconomy and sustainable food systems: what are the possible mechanisms?(Elsevier, 2025-07-01) Nguyen, Thi Hoa; Wang, Xinfang; Utomo, Dhanan; Gage, Ewan; Xu, BingThe circular bioeconomy has emerged as a promising pathway for sustainable development, yet its specific role in fostering sustainable food systems remains underexplored. To our best knowledge, this study is the first systematic review to examine how the circular bioeconomy contributes to sustainable food practices. Using content analysis of 111 academic papers from SCOPUS database, we identify key mechanisms through which the circular bioeconomy enhances food safety and security. These include the development of innovative food products manufactured from bio-resources, the extension of product life through utilizing biodegradable films and bio-based compounds, and the improvement of food safety via sustainable packaging. Additionally, circular bioeconomy practices increase agricultural productivity by enhancing crop yields. From a corporate perspective, they optimize resource use, boost profitability, and generate new revenue streams from waste. Socially, these practices improve stakeholder wellbeing and generate employment opportunities. Environmentally, they support natural capital regeneration, reduce ecological footprints, and promote the sustainable use of resources. Despite these benefits, significant research gaps remain, particularly regarding the cross-sectoral relationships and multi-level impacts of circular bioeconomy practices. This study provides actionable implications for policymakers, practitioners, and researchers, emphasizing regulatory development, strategic decision making, and future research on corporate-level impacts.Item Open Access Comment on ‘Estimating methane emissions from manure: a suitable case for treatment?’(IOP Publishing, 2025-06-01) Anthony, Steven G.; Cardenas, Laura C.; Gilhespy, Sarah L.; Sandars, Daniel L.; Chadwick, David R.Ward et al (2024 Environ. Res. 1 025003) recently published a paper in this journal (Ward et al 2024 Environ. Res. 1 025003) asserting that methane emissions from manure management in the United Kingdom Inventory of Greenhouse Gas emissions could be under-estimated by a factor of four to five. This was based on extrapolation of measurements from two farms located in the south-west of England where manure management is purposely set-up to encourage methane release and capture, for use as a fuel source. We argue that methane thus extracted cannot be compared with the quantities emitted to the atmosphere on a typical farm which is what the national Inventory seeks to estimate, and show that existing Inventory calculations are consistent with wider literature and typical management practices in the United Kingdom.Item Open Access Comparative profiling of bioactive compounds and antioxidant activity of extracts from selected medicinal plants: implications for mitigating obesity-related inflammation(Elsevier, 2025-06) Mngoma, Mlungisi F.; Magwaza, Lembe Samukelo; Mditshwa, Asanda; Tesfay, Samson Zeray; Mkhwanazi, Blessing N.; Nkomo, Mbukeni A.Obesity is a metabolic disorder, contributing to various health complications, including diabetes, hypertension, and cardiovascular dysfunction. Increased use of plant extracts to reduce obesity risk reflects consumer preference for natural remedies and scientific validation for their safety and efficacy. This study profiled bioactive compounds in methanolic extracts from the leaves and roots of Merwilla plumbea (Lindl.) Speta, Hypoxis hemerocallidea Fisch, Eucomis autumnalis (Mill.) Chitt, and Pentanisia prunelloides (Klotzsch) Walp. The objective was to explore and compare the medicinal properties of distinct plant parts for their potential to mitigate obesity-induced inflammation. P. prunelloides leaves and roots had higher concentrations of phenolics (123.92 mg/mL and 110.01 mg/mL) and flavonoids (44.4 mg/mL and 55.05 mg/mL), respectively. Gallotannins were significantly higher in H. hemerocallidea roots (5.19 mg/mL) while proanthocyanidins were predominantly found in P. prunelloides roots (35.77 mg/mL). The antioxidant activity was assessed by ferric reducing antioxidant potential (FRAP) and DPPH radical scavenging activity (RSA) assays. P. prunelloides roots had higher FRAP (2.97 mg/mL) and moderate DPPH (RSA) (52.89 %) while M. plumbea roots had the highest DPPH RSA (80.86 %) and lower FRAP (2.25 mg/mL). E. autumnalis roots and leaves showed FRAP values of 2.78 and 2.13 mg/mL, and DPPH RSA of 80.72 and 74.54 %, respectively. The results revealed that all plants investigated had considerable amounts of bioactive compounds with P. prunelloides showing the highest concentration, highlighting its potential for further pharmaceutical and nutraceutical exploration. Further research validating the bioactivity of key compounds in vivo, exploring seasonal variations, and assessing optimal harvesting practices is paramount for the sustainable utilization of these medicinal plants.Item Open Access CRISPR-enabled genetic logic circuits for biosensing(Elsevier, 2025-09-01) Wang, Xiyan; Gao, Yuanli; Zhou, Nan; Yang, Zhugen; Cooper, Jonathan M.; Wang, BaojunSynthetic biology aims to engineer genetic circuits for custom-designed behaviors in living systems, including sophisticated biosensing applications. The CRISPR (Clustered Regularly Interspaced Short Palindromic Repeats) system has gained attention for its potential in genetic circuit design due to its modularity, programmability, precision, and orthogonality. Here we highlight the current CRISPR-based tools for gene regulation at both transcriptional and translational levels. We discuss how these CRISPR technologies facilitate the design and construction of complex genetic circuits that can perform customized logic computations within living systems. Furthermore, we summarize the applications of CRISPR-based genetic logic circuits in biosensing, emphasizing their potential for detecting diverse biological and environmental signals. Finally, we highlight the key challenges facing the development and application of CRISPR-enabled genetic logic circuits and propose directions for future research to overcome these bottlenecks.Item Open Access A critical review of conventional and emerging technologies for the detection of contaminants, allergens and adulterants in plant-based milk alternatives(Elsevier, 2025) Karimi, Zahra; Campbell, Katrina; Kevei, Zoltan; Patriarca, Andrea; Koidis, Anastasios; Anastasiadi, MariaThe increasing popularity of plant-based milk alternatives (PBMAs) necessitates effective safety and authentication measures to ensure food product integrity and maintain consumer trust. This review aims to offer a comprehensive overview of potential contaminants, allergens, and adulterants in PBMAs, and the analytical methodologies employed for their detection and quantitation. It details the advantages and limitations of widely employed testing techniques, such as chromatography, spectroscopy, immunoassays and PCR. In addition, it explores recent advancements in portable detection methods based on novel technologies such as CRISPR and biosensor systems that offer new opportunities for rapid and precise analysis. Despite these technological innovations, important challenges remain, particularly in optimizing sample preparation protocols and improving DNA-based methods efficiency. The integration of multiple detection strategies and the development of rapid, cost-effective analytical tools are critical steps towards enhancing both industry compliance and consumer confidence. Furthermore, green analytical methods — such as solvent-free extraction, AI-driven spectroscopy, and sustainable sample preparation techniques — pave the way toward eco-friendly and more efficient PBMA safety testing.Item Open Access Developing a multifunctional indicator framework for soil health(Elsevier, 2025-06) Hannam, Jacqueline A.; Harris, Maddie; Deeks, Lynda K.; Hoskins, Hannah; Hutchison, James; Withers, Amy J; Harris, Jim A.; Way, Lawrence; Rickson, R. JaneWe developed a proof-of-concept indicator framework to monitor soil health based on the delivery of ecosystem services. Instead of distilling soil health to one metric, the framework enables simultaneous comparison of the delivery and trade-offs between different ecosystem services that are delivered by soils, accounting for inherent capability determined by soil type and land use. The framework has potential to explore a whole systems approach, ascertaining soil system response in real time that can detect emergent properties of the system. Initial development of the framework ranked salient soil properties known to be linked and pertinent to the delivery of ecosystem services. These key soil properties, together with other environmental variables were used to create simple conceptual models representing a causal network for soils’ contributions to the ecosystem services of climate regulation, food production, water regulation and below-ground biodiversity. The conceptual models were developed into Bayesian Belief Networks populated with relevant national data and expert judgement. The resulting outputs gave an indication of how well (i.e. healthy) a soil can deliver each ecosystem service at a land parcel scale presented in a dashboard app. The output at a specific location can be contextualised or benchmarked against to the range of values for areas with similar soil and land use types. The idea was to build the model with readily available data and knowledge but with flexibility for iterative development to refine the framework and models and improve outputs over time. This enables indicator updates using inputs of local knowledge of land management, or when additional soil data becomes available, or when soil policy drivers change, or our understanding of the conceptual and statistical models are improved. The indicator framework can be applied and adapted for use in multiple contexts from reporting national policy targets on soil health to determining soil health for a farmer at the field level.Item Open Access Development and application of DNA hydrogels in biosensing: current status and future implications(Elsevier, 2025-06-01) Chen, Zhuo; Mao, Kang; Xue, Jiaqi; Feng, Rida; Zhang, Kuankuan; Su, Junxia; Du, Wei; Ran, Jiabing; Yang, Changying; Yang, Zhugen; Zhang, HuaAs emerging biopolymer materials, DNA hydrogels quickly respond to external stimuli to specifically recognize DNA through base pairing and have become widely used in the field of biosensors. Unlike traditional biosensing strategies, biosensors based on DNA hydrogels are highly specific, programmable and degradable. In this work, based on the advantages and wide application of DNA hydrogels in the field of biosensors, the progress of DNA hydrogel biosensors is systematically summarized in terms of the types of DNA hydrogels, detection principles and biosensor device integration. First, the types of DNA hydrogels used in biosensors are briefly introduced. Next, we thoroughly demonstrate the detection principles of DNA hydrogel biosensors; the detection principles depend on the recognition elements, signal elements, and transduction types of the DNA hydrogel used in the biosensor. In particular, we demonstrate the great potential of integrated devices and techniques used in DNA hydrogel biosensors, such as microfluidics and portable devices. Finally, the challenges and future development of DNA hydrogels in biosensing are discussed. This work can be used as a reference for research on biosensing analysis using DNA hydrogels.Item Open Access Engineering biology applications for environmental solutions: potential and challenges(Springer Nature, 2025-04) Lea-Smith, David J.; Hassard, Francis; Coulon, Frederic; Partridge, Natalie; Horsfall, Louise; Parker, Kyle D. J.; Smith, Robert D. J.; McCarthy, Ronan R.; McKew, Boyd A.; Gutierrez, Tony; Kumar, Vinod; Dotro, Gabriella; Yang, Zhugen; Curtis, Thomas P.; Golyshin, Peter; Heaven, Sonia; Jefferson, Bruce; Jeffrey, Paul; Jones, Davey L.; Le Corre Pidou, Kristell; Liu, Yongqiang; Lyu, Tao; Smith, Cindy; Yakunin, Alexander; Zhang, Yue; Krasnogor, NatalioEngineering biology applies synthetic biology to address global environmental challenges like bioremediation, biosequestration, pollutant monitoring, and resource recovery. This perspective outlines innovations in engineering biology, its integration with other technologies (e.g., nanotechnology, IoT, AI), and commercial ventures leveraging these advancements. We also discuss commercialisation and scaling challenges, biosafety and biosecurity considerations including biocontainment strategies, social and political dimensions, and governance issues that must be addressed for successful real-world implementation. Finally, we highlight future perspectives and propose strategies to overcome existing hurdles, aiming to accelerate the adoption of engineering biology for environmental solutions.Item Open Access Enhancing process monitoring and control in novel carbon capture and utilization biotechnology through artificial intelligence modeling: an advanced approach toward sustainable and carbon-neutral wastewater treatment(Elsevier, 2025-05) Cairone, Stefano; Oliva, Giuseppina; Romano, Fabiana; Pasquarelli, Federica; Mariniello, Aniello; Zorpas, Antonis A.; Pollard, Simon J. T.; Choo, Kwang-Ho; Belgiorno, Vincenzo; Zarra, Tiziano; Naddeo, VincenzoIntegrating carbon capture and utilization (CCU) technologies into wastewater treatment plants (WWTPs) is essential for mitigating greenhouse gas (GHG) emissions and enhancing environmental sustainability, but further advancements in process monitoring and control are critical to optimizing treatment performance. This study investigates the application of artificial intelligence (AI) modeling to enhance process monitoring and control in a novel integrated CCU biotechnology with a moving bed biofilm reactor (MBBR) sequenced with an algal photobioreactor (aPBR). This system reduces GHG and odour emissions simultaneously. Several machine learning (ML) models, including artificial neural networks (ANNs), support vector machines (SVM), random forest (RF), and least-squares boosting (LSBoost), were tested. The LSBoost was the most suitable for modeling the MBBR + aPBR system, exhibiting the highest accuracy in predicting CO2 (R2 = 0.97) and H2S (R2 = 0.95) emissions from the MBBR. LSBoost also achieved the highest accuracy for predicting CO2 (R2 = 0.85) and H2S (R2 = 0.97) outlet concentrations from the aPBR. These findings underscore the importance of aligning AI algorithms to the characteristics of the treatment technology. The proposed AI models outperformed conventional statistical methods, demonstrating their ability to capture the complex, nonlinear dynamics typical of processes in environmental technologies. This study highlights the potential of AI-driven monitoring and control systems to significantly improve the efficiency of CCU biotechnologies in WWTPs for climate change mitigation and sustainable wastewater management.Item Open Access Environmental stewardship education in Tuvalu Part 2: insights into curriculum integration and classroom realities(MDPI, 2025-05-01) Tinilau, Soseala S.; Hemstock, Sarah L.; Mercer, Theresa G.; Hannaford, Matthew; Kythreotis, Andrew P.This commentary is the second in a two-part series on Environmental Stewardship Education (ESE) in Tuvalu. While Part 1 examined the alignment between education and environmental policies, this follow-up focuses on how those policies are—or are not—translated into formal curriculum and classroom practice. Drawing on both academic research and professional experience in government, this article explores the gap in curriculum design, student engagement, and teaching strategies. It argues for the early integration of ESE in primary education, greater inclusion of traditional ecological knowledge, and participatory teaching approaches. These insights are grounded in Tuvalu’s context but offer valuable lessons for other small island developing states striving to align sustainability policy with educational delivery.Item Open Access Evaluating the potential of oxygen isoscapes for tropical timber tracing(Elsevier, 2025-08-15) Vlam, Mart; Boeschoten, Laura; van der Sleen, Peter; Adzkia, Ulfa; Boom, Arnoud; Bouka, Gaël U. D.; Ciliane-Madikou, Jannici C. U.; Kuzee, Tijs; Obiang, Nestor Laurier Engone; Guieshon-Engongoro, Mesly; Loumeto, Joël J.; Mbika, Dieu-merci M. F.; Moundounga, Cynel G.; Ndangani, Rita M. D.; Bourobou, Dyana Ndiade; Paredes-Villanueva, Kathelyn; Rahman, Mohamad M.; Meyer-Sand, Barbara Rocha Venâncio; Siregar, Iskandar Z.; Tassiamba, Steve N.; Tchamba, Martin T.; Toumba-Paka, Bijoux B. L.; Zanguim, Herman T.; Zemtsa, Pascaline T.; Zuidema, Pieter A.Independent verification of timber origin is needed to enforce legislation aimed at combatting illegal tropical timber trade. A potential technique is tracing back the stable isotope signal preserved in wood samples, but the scarcity of reference data currently hampers its operationalization. This can be overcome by creating isoscapes. Here we develop continental isoscapes (at 0.5° resolution) for five tropical timbers based on wood δ18O ratios and assess their potential for timber tracing. We compiled a pantropical database of δ18O measurements from 712 trees in 20 countries. We tested effects of δ18O in rainfall, potential evapotranspiration (PET), temperature and precipitation on wood δ18O and used these to develop isoscapes based on quantile regression forests. A first indication of the tracing potential of these isoscapes was tested in leave one out cross validation (LOOCV) analyses. Across the five isoscapes, ranges in wood δ18O values (10th-90th percentile) averaged 3.9 ‰ and δ18O differences increased with distance. Yet local variability in wood δ18O was substantial compared to large-scale variability. The LOOCV analysis showed that the actual origin was included in the probable origin for 59–79 % of the cases. The area of probable origin was large, however, suggesting a low spatial precision of assignment. This study finds limited support for a potential to use wood oxygen isoscapes for tropical timber tracing within continents. Necessary future steps in timber isotope tracing include improving regional representation, conducting similar analyses for other isotopes, rigorous testing of species differences and conducting blind sample tests.
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