Cheese is one of the nutritious foods known for its diverse variety of taste, flavor and texture. To meet the global demand of cheese, many alternates for calf rennet have been explored. One such alternate is plantbased milk coagulant. Historical evidence reported usage of Wrightia tinctoria in traditional cheese preparation. An organic solvent-salt based aqueous two-phase system (ATPS) using ethanol and dipotassium phosphate was employed to concentrate the milk clotting proteases from W. tinctoria leaf. Milk clotting index (MCI), partition coefficient (Ke), yield% (Y%), purification factor (PF) and casein hydrolytic pattern were analysed. The system (10 g) with ethanol-14.96% (w/w) and dipotassium phosphate- 32.70% (w/w) favoured the concentration of milk clotting proteases with high milk clotting index (216.98), partition coefficient (433.33), purification factor (8.71) and yield % (288.92). The same system was scaled-up to 100 g and its performance was found comparable to its 10 g counterpart. Physico-chemical parameters of the cheese prepared using partitioned enzyme were comparable to that of the positive control (plant-based milk coagulant - Enzeco® ) used. This study elucidates the efficacy of ATPS comprising ethanol and dipotassium phosphate in concentrating milk clotting proteases from W. tinctoria leaf extract and its utility in cheese preparation.
Effective management of transboundary river systems is a critical global challenge, particularly in developing regions where water quality degradation can fuel interstate conflict and hinder sustainable development. This study applies Principal Component Analysis (PCA), a robust multivariate statistical technique, to evaluate the water quality of the Dhansiri river, a tributary of the river Brahmaputra flowing along the interstate boundary between Assam and Nagaland in north-eastern India. Quarterly monitoring data from January 2022 to June 2024, comprising 19 physicochemical and biological parameters from five stations, were analyzed to identify key pollution sources and regional trends. PCA reduced data dimensionality while preserving explanatory power, revealing site-specific pollution patterns. Upstream stations (Nagaland) exhibited strong loadings for pH, hardness and calcium, indicating geological influence from limestone terrain. Downstream sites (Assam) showed elevated biochemical oxygen demand, nitrate and fecal coliforms, tracing pollution to untreated sewage, agricultural runoff and industrial discharge including effluents from cement plants. For instance, Bokajan and Numaligarh (Assam) stations reflected distinct anthropogenic pressures. These findings underscore PCA’s applicability in transboundary water governance, offering a data-driven framework for policymakers worldwide. The methodology and results are especially relevant for developing countries grappling with similar hydrological and institutional complexities, making the study a transferable model for integrated river basin management.
Polymer nanocomposites have been acknowledged as significant members of the material family, combining the advantages of polymer matrices with the peculiar effects of nanoscale reinforcements. In this study, two novel nanocomposites metallic graphene oxidechitosan Fe3O4@GC and copper graphene oxidechitosan CuO@GC were synthesized and characterized in order to investigate their structural, morphological and functional characteristics. Chitosan (CS) was functionalized with Graphene-oxide (GO) based metallic and copper nanocomposites synthesized earlier by a chemical reduction process. By identifying the important functional groups including C=O, N-H and O-H bonds, FTIR verified the successful creation of these hybrid materials and demonstrated the efficient interaction of GO, chitosan and metal nanoparticles. XRD analysis revealed the unique crystalline phases, confirming the integration of metallic and copper nanoparticles inside the grapheneoxide-chitosan matrix. On the GO-CS surface, FESEM pictures showed a homogeneous dispersion of nanoparticles, with CuO@GC showing a more porous structure than Fe3O4@GC.
Chromium (VI) is a toxic environmental pollutant and its remediation through microbial reduction is of great interest from ecological point of view. This study aimed to optimize the growth and Cr (VI) removal efficiency of the isolated actinobacterial strain, Streptomyces griseoincarnatus, isolated from a Ghazipur landfill. The different parameters (varying concentrations, temperature, pH, other heavy metals and contact time) were checked for the chromium reduction and its effect on bacterial growth. The isolate was cultivated in LB broth under each set of conditions and residual Cr (VI) in the medium was periodically quantified. The optimal conditions for the reduction of Cr (VI) were neutral pH and mesophilic temperature (~30 °C). Under these conditions, the bacterium removed about 80-90% of Cr (VI) within 2 days of incubation. At higher concentrations of Cr (VI), effective reduction still occurred and the presence of other heavy metals did not interfere with this process, indicating the bacterium's tolerance to multi-metal environments. The optimization of parameters such as pH and temperature together led to a noticeable improvement in both Cr (VI) reduction and bacterial growth. In conclusion, Streptomyces griseoincarnatus showed strong potential for removing Cr (VI) under optimized conditions, making it a suitable candidate for bioremediation of chromium-contaminated sites.
Diabetes mellitus is a significant global metabolic illness necessitating the creation of safer and more effective treatment medicines. This study aimed to evaluate the antidiabetic potential of Oxalis latifolia leaf ethanolic extract using an integrated approach of GC–MS profiling, in silico molecular docking and in vitro enzyme inhibition assays. GC–MS study showed 22 bioactive chemicals, with n-hexadecanoic acid, 9- oximino-2,7-diethoxyfluorene and echitamine as main ingredients. Molecular docking demonstrated robust interactions between chosen phytocompounds and diabetes-associated target enzymes, with binding affinities between −3.8 and −8.5 kcal/mol. Echitamine and 9-oximino-2,7-diethoxyfluorene demonstrated the highest affinity for α-glucosidase (−8.5 kcal/mol), indicating significant inhibitory potential. In vitro studies exhibited moderate inhibition of αglucosidase and α-amylase, with IC₅₀ values of 183.25 µg/mL and 226.73 µg/mL respectively in contrast to acarbose (46.12 µg/mL and 44.57 µg/mL). The data collectively suggest that Oxalis latifolia exhibits significant antidiabetic activities, underscoring its potential as a natural resource for future pharmacological research.
The marine alga Caulerpa scalpelliformis was collected from the coastal area of Veraval, Gujarat, India which has been used in this work to examine the green production of zinc oxide nanoparticles (ZnO NPs). Caulerpa scalpelliformis has various economic and environmentally friendly benefits, therefore, green synthesis has garnered a lot of interest. In this study, zinc acetate dihydrate was used as the precursor for the production of nanoparticles and an aqueous extract of the algae was used as a stabilising and reducing agent. An apparent colour shift was the first sign of ZnO nanoparticle production, which was later verified by UV–visible spectroscopy, which showed a distinctive absorption peak at around 240 nm. Fourier Transform Infrared Spectroscopy (FTIR), Xray Diffraction (XRD), Scanning Electron Microscopy (SEM), Energy Dispersive X-ray Analysis (EDX), Transmission Electron Microscopy (TEM) and Dynamic Light Scattering (DLS) were among the analytical methods used to thoroughly characterise the produced nanoparticles. The findings showed that the nanoparticles were crystalline, mostly spherical and varied in size from 17 to 98 nm. Biomolecules such as proteins, phenols and polysaccharides were shown to be involved in the reduction and stabilisation process by FTIR analysis. Additionally, the agar well diffusion technique was used to assess the antibacterial efficacy of the produced ZnO nanoparticles against Bacillus subtilis and Staphylococcus aureus. When compared to zinc acetate, the nanoparticles showed a modest level of antibacterial activity.
Mathematical modelling of the activated sludge process (ASP) enhances the understanding of the process and improves the quality of the effluent released. However, as the process is complex and nonlinear, mathematical modelling of the process has been a challenge. In this study, multi-layer perceptron artificial neural networks (MLP-ANN), artificial neuro fuzzy inference system (ANFIS) and support vector machine (SVR) are investigated and compared to predict biochemical oxygen demand (BOD) for better control of waste water treatment plants employing activated sludge process. The study area selected was in a central district of the southern State of India. The model is evaluated based on statistical parameters of the correlation coefficient R and mean square error (MSE). The software MATLAB 8.6 2015b is used for modelling and simulation study of ANN and ANFIS. Python 3.11 is used for SVR modelling. It has been found that effluent BOD was predicted with maximum correlation coefficient of 0.927 and minimum mean square error of 0.0022 by ANN. It is seen that ANFIS gave a maximum R values of 0.9397 and minimum MSE of 0.0018 for predicting BOD while SVR modelling gave an overall regression R of 0.8661 and MSE of .0021 for BOD prediction.
This study evaluated the spatial and temporal variations in selected physicochemical properties and nutrient ion concentration of the Tigris River in AlShirqat District, Iraq, from October 2025 to January 2026. Eight water quality parameters including electrical conductivity (EC), total dissolved solids (TDS), chlorides (Cl⁻), bicarbonate (HCO₃⁻), sulfate (SO₄²⁻), nitrate (NO₃⁻), nitrite (NO₂⁻) and phosphate (PO₄³⁻) were analyzed. Water samples were collected monthly from five stations along the Tigris River in AlShirqat, district and each sample was analyzed in triplicate. The results indicated significant temporal variations (p< 0.05) in electrical conductivity values which ranged from 529–578 µS/cm with no significant spatial differences. TDS values ranged from 374 to 473.4, mg/L and exhibited significant temporal variations but no significant spatial differences. Chloride Cl⁻) concentrations ranged from 16.5 to 20.7 mg/L with no significant temporal or spatial differences. Bicarbonate (HCO₃⁻) concentrations varied from 128.6-135.4mg/L with significant temporal and spatial differences. Sulfate (SO₄²⁻) concentrations ranged from 66.8 to 71.4mg/L with no significant temporal or spatial differences. Moreover. nitrate (NO₃⁻) concentrations ranged from 0.025 - 0.03 mg/L and showed significant spatial differences but no significant temporal differences. Nitrite (NO₂⁻) concentrations ranged between 0.025-0.028 mg/L and exhibited significant spatial differences. Finally, phosphate (PO₄³⁻) concentrations ranged from 0.132 - 0.224 mg/L and showed significant temporal and spatial differences. Overall, the measured physicochemical parameters were within the permissible limits recommended by Iraqi and World Health Organization (WHO)water quality standards, indicating acceptable water quality.
Heavy metal contamination in soils has emerged as a critical environmental concern, particularly in rapidly urbanizing regions such as Bangalore, India. With a population exceeding 13 million, Bangalore hosts extensive IT infrastructure, mid- and large-scale industries, dense transportation networks and intensive agricultural activities, all of which contribute significantly to soil pollution. Although several studies have examined heavy metal accumulation in localized areas, comprehensive spatial assessments integrating both urban and rural environments remain limited. The present study evaluates the distribution of major heavy metals including lead (Pb), cadmium (Cd), chromium (Cr), nickel (Ni), zinc (Zn), copper (Cu), mercury (Hg) and arsenic (As) across urban areas and rural regions of Bangalore . Total 135 soil samples were analyzed, revealing elevated concentrations of Pb (up to ~119 mg/kg) and Cr (up to ~150 mg/kg) in industrial and trafficinfluenced zones such as Bangalore South, Anekal, Peenya and Hoskote, while moderate contamination levels were observed in Ramanagaram, Magadi and Nelamangala. Environmental parameters, including soil pH (5.5-8.5), annual rainfall (850-970 mm), temperature (24-30ºC) and relative humidity (55-75%), were incorporated to understand their influence on metal behaviour and spatial variability. GIS-based spatial distribution maps effectively delineated zones of high, moderate and low contamination, providing a clear visualization of contamination patterns. The integrated approach adopted in this study supports environmental monitoring, land-use planning and sustainable soil management in rapidly developing urban–rural landscapes.
In semi-arid regions, the deterioration of groundwater quality due to industrialization and intensified agriculture is a serious problem. Because groundwater pollution is so common in Bathinda, Punjab, thorough mapping and forecasting are necessary for sustainable management. The current study uses GIS, remote sensing and machine learning to map and forecast groundwater contamination zones using water quality index (WQI) models. The overarching goal of the framework is to create an integrated geospatialmachine-learning mapping of the risk of groundwater pollution; the secondary goal is to use regressionbased model selection to determine the most significant hydrochemical markers on WQI. When more variables were included in the model, subset regression clearly demonstrated an increase in prediction accuracy. There was some success with single-variable models (Cl), but their predictive power was just 0.08 (R²). Generally speaking, adding more parameters significantly boosted explanation power. Eleven parameters (NO₃, SO₄, HCO₃, K, pH, TDS, TH, Ca, Mg, Na and Cl) in the best-fitting model produced nearly flawless predictions (R2 = 1, MSE ≈ 0) and reduced information criteria (AIC = 0, SBC = 0). This demonstrates how physicochemical characteristics, anions and cations all work together to predict groundwater quality. A great way to monitor Bathinda's water quality is to combine machine learning techniques with GIS tools.
Euphorbia caducifolia, commonly known as the leafless milk hedge, is a xerophytic member of the Euphorbiaceae family with a longstanding reputation in traditional medicine. This plant has been widely utilized for its therapeutic value, particularly in treating inflammation, infections and oxidative disorders. In the present study, FTIR analysis of the methanolic plant extract revealed the presence of major functional groups including amines, alkynes, alkenes and alkanes, indicating its structural diversity. This spectral characterization provides supportive evidence of the extract’s complex phytochemical nature and potential bioactivity. Furthermore, Gas Chromatography–Mass Spectrometry (GC–MS) analysis has been employed to investigate the phytochemical profile of Euphorbia caducifolia. Interestingly, the analysis revealed the presence of some novel compounds that had not been reported in earlier literature or existing phytochemical databases. The study followed a systematic methodology involving plant material extraction, isolation of chemical fractions and detailed structural characterization. The newly identified compounds indicated notable antioxidant, anti-inflammatory and antimicrobial potential, thereby underscoring their prospective relevance in pharmacological applications. Such findings provide strong scientific support for the ethnomedicinal use of Euphorbia caducifolia and suggest that it may serve as a valuable reservoir of bioactive molecules of therapeutic importance. Importantly, this discovery highlights the underestimated potential of arid and harshenvironment plants, which often produce unique secondary metabolites as part of their adaptive strategies. This study contributes to phytochemical knowledge and identifies potential directions for future research in natural products and drug discovery. The findings underscore the importance of further investigation of Euphorbia caducifolia and related species to identify novel compounds with medicinal potential.
(E)-N-(4-methoxybenzylidene)-2-(1H-imidazol-4-yl)et hanamine (HA) has been synthesized and characterized using spectral studies including UV-Visible, FT-IR and NMR spectra. The optimized structure of HA is computationally constructed and theoretically studied using Gaussian 03 with the Density Functional Theory (DFT) method. This utilized the B3LYP functional with the 6-31G(d,p) basis set. Vibrational frequencies are analyzed using potential energy distribution (PED%) calculations through the vibrational energy distribution analysis (VEDA3 ) program. Nonlinear optical (NLO) properties are examined based on calculated values of dipole moment (µ), polarizability (α) and first hyperpolarizability (β_tot). The polar sites of the molecules were identified using molecular electrostatic potential (MEP) surfaces, while orbital overlap was determined through the HOMO-LUMO analysis. We analysed the stabilisation energy of donor-acceptor interactions between the orbital using NBO calculation. Additionally, the electron affinity, electronegativity, chemical potential, hardness and softness of the compounds were characterized via frontier molecular orbital (FMO) studies. In the in silico evaluation, physicochemical parameters and drug-likeness were predicted using Swiss-ADME and pre-ADME web tools.
Trace-level contamination of PTEs in rice poses serious risks to human health, necessitating accurate quantification of As, Pb, Cd and Hg for toxicological and nutritional assessment. This study presents a comprehensive comparison of three microwave assisted wet digestion methods using different acid combinations [Method A: concentrated HNO3 alone, Method B: HNO3–HCl (4:1, v/v) and Method C: HNO3–H2O2 (4:1, v/v)]. In order to evaluate the most efficient and cost-effective protocol that gains the highest analyte recovery, allow the trace level determination of these toxic elements in rice by ICPMS. The methods were validated in accordance with AOAC and EURACHEM guidelines, including HorRat, measurement of uncertainty and fitness studies to generate precise, accurate, valid and reliable data. All methods exhibited linear responses (r² > 0.999) with LODs and LOQs as low as 0.025 and 0.05 mg kg-1 respectively. Method ‘C’ demonstrated superior recovery efficiencies (90–110%) and precision (RSD < 5%) across all analytes, ensuring its fitness for the purpose of routine analysis. Application of method ‘C’ to commercial rice samples revealed a contamination pattern of Pb > As > Cd > Hg. Dietary exposure was assessed using estimated daily intake (EDI) and hazard quotient (HQ). HQ values for Pb and Cd were <1, while As showed HQ >1 in selected samples, indicating a potential non-carcinogenic risk. Overall, method ‘C’ provided a robust, precise, eco-friendly and healthrelevant approach for routine monitoring of Pb, Cd, As and Hg in rice by ICP-MS, ensuring regulatory compliance and supporting food safety monitoring.
Novel series of amide and Schiff's base functionalized quinazolinone hybrids were synthesized and their chemical structures were characterized by 1HNMR and 13CNMR and ESI mass spectral techniques. Further, all compounds were evaluated for their preliminary activity effects against four human cancer cell lines such HeLa - Cervical cancer (CCL-2), COLO 205- Colon cancer (CCL-222), HepG2 Liver cancer (HB8065) and MCF7 - Breast cancer (HTB-22). Obtained results were expressed with IC50 µM and compared with 5-FU as standard reference. Promising compounds which showed good activity, have been further evaluated for docking interactions.
The antimicrobial resistant microbes possess resistance genes as well as synthesize various secondary metabolites which protect them from extreme environmental conditions. Isolating microbial strains from extreme environments like mangrove forest increases the possibility of isolating antimicrobial compounds that have not been previously isolated and secondly, because the pathogens are not exposed to these bacterial compounds, it is unlikely that they will develop antibiotic resistance to the bacteria. The present work encompasses isolation of antibiotic resistant microbes from mangrove forest which has less anthropogenic activity. Culture based method was adapted to isolate strain FMU-55 which was identified to be Stappia indica using 16s rRNA sequencing. In silico approach using CARD-RGI led to the identification of adeF gene that belongs to the RND (Resistance-nodulation-cell-division) and qacJ gene belonging to small multidrug resistance (SMR) antibiotic efflux pump family. Simultaneous metabolomics studies using GCMS led to identification of various antimicrobial metabolites, like N,NDiethylaniline, Oxime-methoxy-phenyl-, Cycloheptasiloxane, Tetradecamethyl, Phenol, Ethanone, 1,1'-(2,6-dimethyl-3,5-pyridinethiol) and Tert-Butyldimethylsilyl trifluoromethanesulfonate. This study provides insight into the genetic targets, their resistance mechanism and potential metabolites that can be exploited for discovery of new drugs.
The application of ionic liquids is ongoing in numerous technological applications, particularly in Enhanced Oil Recovery (EOR). They are organic salts containing anionic and cationic species with melting points below 100 oC. They are environmentally friendly salts with good thermal stability, solubility and effective surface activity. It is observed that ionic liquids can improve oil recovery through the alteration of oil-brine interfacial tension (IFT) and the rock wettability in a favourable way. In this work, a laboratory investigation of 1- dodecylpyridinium chloride ([C12Py][Cl]) ionic liquid was conducted to enhance oil recovery in a part of the Upper Assam Basin. Petrographic analysis of the reservoir rock indicated the presence of clay minerals, muscovite, feldspar and ferruginous cement. The analysis of the reservoir brine and crude oil revealed the presence of divalent cations (Ca2+ and Mg2+) and polar compounds (asphaltene and resin). The characteristics of the Crude Oil/Brine/Rock (COBR) system of the study area indicate its suitability for the application of the ionic liquid. Furthermore, IFT and wettability studies confirm that the ionic liquid [C₁₂Py][Cl] has the potential to improve oil recovery in the study area. A series of core flooding experiments was conducted using [C₁₂Py][Cl] at concentrations of up to 1500 ppm. The experiments showed that oil recovery efficiency increases to 50.89 % of the original oil in place (OOIP) as the [C12Py][Cl] concentration in the formation of brine increases. The maximum oil recovery efficiency is observed at the critical micelle concentration (CMC) of 1000 ppm of the [C12Py][Cl] ionic liquid solution.
Lung cancer is the leading cause of cancer death in the world. Inhibition of apoptosis involves blocking the cell’s natural process of self-destruction. This can occur through various mechanisms including the action of proteins like Bcl-2 family members and apoptosis inhibitors and growth factor upregulation. This study performed molecular docking, molecular dynamics simulation and ADMET prediction on eleven steroidal saponins isolated from Paris rugosa as potential apoptosis inhibitors for lung cancer treatment. The molecular docking results showed that ophiopogonin C’ and 17-hydroxygracillin are more stable and are better localized within the 6GL8 protein pocket. The molecular dynamics simulation results reveal a persistent inhibition mode and consistent binding interactions in all simulations. These findings indicated that the binding of all selected compounds to 6GL8 protein was stable during 100 ns molecular dynamics simulation. The in silico ADMET prediction was further carried out to evaluate the oral bioavailability of selected compounds. As a result, ophiopogonin C’ satisfies all the pharmacokinetic criteria, which are non-toxic, have superior distribution capacity and have high absorption. This steroidal saponin is an inhibitor of the anti-apoptotic protein Bcl-2 (6GL8), serving as a promising candidate for the development of future drugs to treat human lung cancer.
In this study, cerium oxide (CeO₂) and magnesium oxide (MgO) nanoparticles were successfully produced through a fast and environmentally friendly microwave-assisted green synthesis method, employing Boerhavia diffusa leaf extract both as reducing and stabilizing agent. The synthesized nanoparticles were systematically analyzed using UV Visible spectroscopy, Fourier Transform Infrared (FTIR) spectroscopy, Dynamic Light Scattering (DLS), X-ray diffraction (XRD), Scanning Electron Microscopy (SEM) combined with Energy Dispersive X-ray Spectroscopy (EDS) and Cyclic voltammetry (CV). UV Visible analysis verified the presence of CeO₂ and MgO nanoparticles, showing distinct absorption peaks at 336 nm and 256 nm respectively. XRD data showed the creation of highly crystalline, phase-pure nanoparticles, with average crystallite sizes of approximately 15 - 30 nm for CeO₂ and 20-40 nm for MgO. DLS measurements revealed hydrodynamic diameters centered around 110-130 nm for CeO₂ and ≈ 150 - 180 nm for MgO, confirming that the particles are nanoscale with some moderate aggregation. SEM analysis further confirmed the presence of irregular, clustered structures. FTIR spectra indicated that phytochemicals played a role in the reduction and stabilization process. Electrochemical studies showed that CeO₂ nanoparticles exhibited increased redox activity owing to the reversible Ce³⁺/Ce⁴⁺ transition, while MgO displayed relatively weaker electrochemical performance. The antimicrobial activity of the synthesized nanoparticles was tested against selected Grampositive and Gram-negative bacteria, along with fungal strains, revealing inhibition that varied with concentration. Between the two, CeO₂ nanoparticles showed greater antimicrobial effectiveness, producing larger zones of inhibition than MgO nanoparticles due to their increased ability to generate reactive oxygen * Author for Correspondence species (ROS) and higher concentration of oxygen vacancy defects. Overall, the study underscores that microwave-assisted green synthesis is an effective and environmentally friendly approach for producing nanoparticles. CeO₂ nanoparticles show significant potential for use in antimicrobial and biomedical applications.
The present study reports an eco-friendly synthesis of silver oxide nanoparticles (Ag₂O nanoparticles) using Fritschiella tuberosa as a biological reducing and stabilizing agent. The synthesized nanoparticles were evaluated for their antimicrobial, antioxidant, antiinflammatory and anticancer activities. Antimicrobial studies revealed significant dose-dependent inhibition against Escherichia coli, Staphylococcus aureus and Candida albicans, demonstrating broad-spectrum activity. Antioxidant potential assessed through DPPH and hydrogen peroxide scavenging assays showed moderate free radical scavenging activity with IC₅₀ values of 104 µg/mL and 107 µg/mL respectively. The anti-inflammatory activity was evaluated using the protein denaturation assay exhibited a concentrationdependent inhibition with an IC₅₀ value of 76.7 µg/mL, comparable to the standard drug diclofenac sodium. Cytotoxicity studies using the MTT assay against A549 lung carcinoma cells demonstrated strong dosedependent activity, with an IC₅₀ value of 14.88 µg/mL. Morphological analysis further confirmed the induction of apoptosis, supported by acridine orange/ethidium bromide staining, showing characteristic features such as membrane damage, nuclear condensation and increased apoptotic cell population. Overall, the findings suggest that Ag₂O nanoparticles synthesized via a green approach possess significant therapeutic potential for biomedical and environmental applications.
This study focuses on the efficiency of Polyhydroxyalkanoate (PHAs) production from palm oil using Pseudomonas aeruginosa BSE1(OP474060). It was found that the influence of palm oil concentration on the growth and PHAs accumulation of P. aeruginosa BSE1 showed that palm oil concentration affected the growth and PHAs accumulation. At concentrations of 0.50 and 0.75%w/v, the maximum dry cell weights were 3.83 and 4.83 g L -1 respectively. The study of PHAs yield and structural analysis by FTIR technique showed that palm oil concentration of 0.75 % w/v had the highest PHAs yield of 40.83 %. This concentration is suitable for the production and accumulation of PHAs. The results of the structural analysis of the extracted PHAs using the FTIR technique revealed methyl and methylene groups in the range of 2,900-2,800 cm−1 which is the specific position of medium-chain PHAs (mcl-PHA) found from P. aeruginosa BSE1. Further research should focus on the economic feasibility of PHAs production from palm oil. Finally, this research can support the palm oil industry and stimulate demand for bioplastics, thereby facilitating adaptation to climate change.
