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Green and Tropical Laboratory for Sustainability
Published by Universitas Muhammadiyah Malang
ISSN : -     EISSN : 30645069     DOI : https://doi.org/10.22219/gtlabs.vxiy.xxxxx
Core Subject : Science, Agriculture, Social, Engineering,
Agriculture, Biological Sciences & Forestry Chemical Engineering, Chemistry & Bioengineering Decision Sciences, Operations Research & Management Environmental Science Social Sciences
Green And Tropical Laboratory For Sustainability encompasses a broad range of research areas related to the Sustainable Development Goals (SDGs), including but not limited to: Laboratory-Based Studies on Tropical Ecosystems: Research on biodiversity, climate change, ecosystem restoration, and natural resource management within tropical regions. Development and Application of Laboratory Technologies for Sustainable Energy: Investigations into renewable energy sources, energy efficiency, and clean energy technologies that contribute to sustainable development. Laboratory Research on Waste Management and Pollution Control: Studies focused on waste treatment, recycling, circular economy practices, and pollution mitigation strategies. Laboratory Investigations into Food Security and Sustainable Agriculture: Research on organic farming, agroforestry, food safety, nutritional value, and sustainable agricultural practices. Laboratory Studies on Human Health and Environmental Interactions: Exploration of environmental health risks, infectious diseases, toxicology, and public health interventions. Research on Digital Governance for Sustainable Development: Studies examining the role of digital governance in enhancing sustainability efforts, including the application of digital tools and technologies in managing environmental resources, monitoring ecological impacts, and supporting policy-making processes. Social and Educational Research in the Context of Sustainability: Investigations into social dynamics, educational initiatives, and community engagement strategies that align with sustainability goals, particularly in tropical regions. This includes the integration of sustainability concepts into educational curricula and the promotion of social practices that support green and sustainable development.
Arjuna Subject : Umum - Umum
Articles 15 Documents
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The urgency of green laboratory for sustainability: Review from Scopus AI data H. Husamah; Abdulkadir Rahardjanto; Tutut Indria Permana; Ahmad Adnan Mohd Shukri; Burak Olur; Roimil Latifa
Green and Tropical Laboratory for Sustainability Vol. 2 No. 2 (2025): December
Publisher : Universitas Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22219/gtlabs.v2i2.40734

Abstract

Background: The increasing environmental burden of scientific laboratories has prompted a critical need to adopt sustainable practices. Laboratories consume substantial amounts of energy and water and generate hazardous and plastic waste, making them significant contributors to environmental degradation. Objectives: This study aims to explore the urgency, key themes, and strategic contributions of green laboratories to sustainability. Methods: Using a review approach supported by Scopus AI, the study collected and analyzed peer-reviewed data through natural language and keyword-based queries, combined with thematic mapping. Results: Key findings reveal four dominant themes: real-world labs, green chemistry, sustainability in higher education, and green technological innovation. These green lab practices offer benefits including reduced environmental footprint, cost savings, enhanced safety, and alignment with sustainability goals. However, challenges such as financial constraints and resistance to change must be addressed through stakeholder engagement and education. Conclusion: The study concludes that green laboratories play a vital role in sustainability transitions by bridging innovation, education, and environmental responsibility. This review offers a framework for future research and institutional efforts aimed at accelerating green lab adoption worldwide.
In silico study of beta citronellol compound in lime plant (Citrus aurantifolia) as a drug candidate for enterovirus disease Early Maulina; Tanto Situmorang
Green and Tropical Laboratory for Sustainability Vol. 2 No. 1 (2025): August
Publisher : Universitas Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22219/gtlabs.v2i1.41033

Abstract

Background: Human Enterovirus is an RNA virus affecting millions globally, particularly children, causing a range of symptoms from mild to severe, including serious conditions like meningitis and AFP. Current synthetic treatments have side effects, necessitating the exploration of natural alternatives. Lime (Citrus aurantifolia) is a potential candidate. Objectives: To determine the potential of the beta citronellol compound found in lime (Citrus aurantifolia) as an inhibitor of enterovirus activity in in-silico study. Methods: This research employed an in-silico method. This involved analyzing the bioactivity potential of beta citronellol, assessing its bioavailability and toxicity, and performing molecular docking. Data was sourced from PubChem and RSCB PDB. Bioactivity probability was predicted using PASS Online. Virtual screening was conducted via molecular docking with PyRx. Visualization was performed using PyMol and Discovery Studio. Results: The toxicity prediction and molecular docking analysis of beta citronellol against the 3J3Z protein indicated that this compound has a high and specific potential as a receptor candidate for the enterovirus target. Conclusion: The findings of this in silico study suggest that the beta citronellol compound possesses good antiviral activity against enteroviruses.
Flavor meets function: Red grape juice (Vitis vinifera L.) enrichment enhances the microbiological, chemical, and sensory quality of yogurt Intan Rahma Sari; Muhammad Saefi; Didik Wahyudi
Green and Tropical Laboratory for Sustainability Vol. 2 No. 2 (2025): December
Publisher : Universitas Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22219/gtlabs.v2i2.41590

Abstract

Background: One of the main challenges in yoghurt production is the potential for microbiological contamination, especially by Coliform bacteria. Meanwhile, red grapes (Vitis vinifera L.) are known to have bioactive content that has the potential to improve yoghurt quality by not only suppressing coliform bacteria, but also increasing Lactic Acid Bacteria (LAB), reducing pH and acid levels, and improving sensory preferences. Objectives: This study aims to investigate the microbiological, chemical, and organoleptic characteristics of yoghurt after the addition of red grape juice (Vitis vinifera L.). Methods: This study is an exploratory study conducted with four concentrations: K0 (without the addition of red grape juice), K1 (5%), K2 (10%), and K3 (15%). The parameters observed include the number of Coliform bacteria, LAB, lactic acid levels, pH, and organoleptic tests. Data analysis of the total number of LAB, lactic acid levels, the number of coliform bacteria and pH values ​​was carried out descriptively quantitatively. Meanwhile, the results of the organoleptic test were compared between groups using the Kruskal-Walli’s test statistics. Results: The results showed that K3 produced the highest total BAL of 2.71 × 10⁹ CFU/mL. The lowest number of Coliforms of 3 apm/mL was produced by K2, in accordance with the yoghurt quality standards based on SNI 2981:2009. The highest lactic acid content was recorded in K3 of 1.89%, while the lowest pH value was achieved in K3 with a value of 4.00. Organoleptic tests showed that K2 and K3 gave the highest average values ​​for taste, aroma, and color attributes, with a tendency for consumer preference to increase along with the addition of fruit juice concentration. Conclusion: The most favorable results were obtained at concentrations of 10% (K2) and 15% (K3), which provided an optimal balance between sensory quality, microbiological safety, and chemical stability of the product. The addition of red grape juice increased the functional value of yoghurt in microbiological, chemical, and organoleptic aspects.
Accuracy comparison of remote sensing methods (UAV, LiDAR, Radar) and field allometry in mangrove blue carbon quantification: A systematic literature review Ludwick Satria Romadoni; H. Husamah; Bello Ganiyu
Green and Tropical Laboratory for Sustainability Vol. 2 No. 2 (2025): December
Publisher : Universitas Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22219/gtlabs.v2i2.43380

Abstract

Background: Mangrove ecosystems are crucial blue carbon reservoirs, yet quantifying their carbon stocks faces methodological challenges. Field allometric methods, while accurate, are destructive and labor-intensive. Non-destructive Remote Sensing (RS) (UAV, LiDAR, Radar) offers an efficient alternative for landscape-scale mapping. However, literature comparing the accuracy and bias of these diverse RS sensors remains fragmented. Objectives: This study aims to (1) synthesize and compare accuracy metrics  & RMSE from various RS methods in estimating mangrove biomass and carbon stocks, and (2) identify factors in forest structure and sensor types that most significantly influence estimation bias Methods: This research employs a Systematic Literature Review (SLR) guided by PRISMA. Data were extracted from 10 core empirical articles (2018-2025) covering various platforms from optical satellites to UAV-LiDAR. Results: The SLR results indicate that high-cost technologies like LiDAR do not always guarantee the highest accuracy compared to optical sensors (Sentinel-2) under certain conditions. The primary identified bias factor is signal saturation in dense canopies. Conclusion: These findings provide evidence-based guidance for researchers and biology educators in selecting the most robust methodology for carbon inventory.
AI Integration in green labs to achieve the third SDG goal: Literature review on good health and well being Ahmad Fauzi; Diani Fatmawati
Green and Tropical Laboratory for Sustainability Vol. 2 No. 2 (2025): December
Publisher : Universitas Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22219/gtlabs.v2i2.43425

Abstract

Background: Artificial intelligence (AI) is increasingly applied in healthcare and sustainability-related domains to improve efficiency, health outcomes, and decision-making. However, its expanding use also raises critical concerns regarding environmental impact, ethical governance, and equitable access, necessitating a comprehensive synthesis of existing evidence. Objectives: This review aims to evaluate AI applications that improve sustainability and health outcomes, compare AI-based green laboratory practices against SDG 3, identify integration challenges, compare resource optimization strategies, and analyze interdisciplinary collaboration frameworks. Methods: A systematic analysis of 50 global studies using diverse AI methodologies, including machine learning, deep learning, IoT, and green computing was conducted, with a focus on empirical and conceptual evidence from clinical and research laboratories. Results: Findings reveal that AI significantly improves laboratory efficiency, diagnostic accuracy, and resource management, achieving measurable reductions in energy, water, and waste while advancing personalized healthcare. However, the environmental costs of AI, ethical issues such as algorithmic bias and equitable access, and limited scalability in low-resource settings remain critical challenges. Multisectoral collaboration and governance frameworks are crucial but underdeveloped for the responsible deployment of AI in green laboratories. Conclusion: Integrating AI innovation with sustainability goals requires balancing technological advancements with ethical and environmental imperatives. These insights inform a theoretical framework and practical strategies for optimizing AI integration in sustainable laboratory environments, supporting global health and well-being goals within defined temporal and geographic research boundaries.

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