Two-step Extraction Research Articles

Two-step dual-layer SPE method to separate antibacterial and antioxidant mushroom compounds

We developed a two-step dual-layer solid-phase extraction (SPE) method to separate and concentrate minor bioactive compounds of golden oyster mushroom (Pleurotus citrinopileatus) methanol extract. The mushroom extract is rich in fatty acids, including the highly abundant (20–35 %) and antibacterial linoleic acid. To eliminate the masking effect of linoleic acid in the bioassay, its removal was achieved by homemade dual-layer SPE that consisted of a lower C18 phase and an upper silica gel phase with the dried-on extract. In the first step the elution was performed with water (aqueous eluate), and then the dried C18 and silica gel phases were eluted separately with methanol (C18 methanol eluate and silica gel methanol eluate, respectively). Thin-layer chromatography (TLC)-effect-directed analysis demonstrated that the aqueous eluate contained sugars and antioxidants (TLC-DPPH); fatty acids were present in the silica gel methanol eluate, in the C18 methanol eluate the biologically active minor secondary metabolites were concentrated (TLC–Bacillus subtilis assay) beside 2 % remained linoleic acid according to HPLC-UV measurement. As a result, the antioxidant and antibacterial metabolites divided, and the low-abundant antibacterial compounds could be detected. Based on this study, the substance found at RF 0.25 by TLC-DPPH played the most significant role in generating the antioxidant effect of the aqueous eluate, equivalent to 5.07 ± 0.09 µg of gallic acid. Moreover, each SPE fraction and raw extract were tested for antibacterial effect using a microplate assay with a non-pathogenic Gram-positive Bacillus subtilis. The P. citrinopileatus extract (MIC-value – 50 µg/mL) and C18 methanol eluate (MIC-value - 25 µg/mL) inhibited the growth of B. subtilis while the other eluates did not.

Influence of enzymatic extraction on the properties of corn starch

Corn starch played an important role in the food industries, while traditional extraction method involved using sulfur dioxide that could easily cause environmental pollution and equipment corrosion. Based on these drawbacks, the main objective of this study was to develop a feasible two-step enzymatic extraction method that could isolate starch from corn kernels and evaluate the properties of corn starch. The physicochemical components of steep liquor during enzymatic extraction were researched, the single-factor experiments and response surface methodology were used to optimize the steeping conditions. As a result, optimized steeping parameters of which the first step time was 30 h, the lactic acid solution concentration was 0.45%, the protease content was 480 U/g, the l-cysteine content was 0.45 g, and the second step time was 4 h. The corn starch yield (65.18%) with enzymatic extraction was higher than that of traditional extraction (54.73%). The solubility and swelling power of all starch samples were raised with the temperature increasing. The starch extracted using the enzymatic method had a higher amylose content (35.18%) and mean diameter (30.99 μm). Compared with commercial corn starch, the starch samples presented nearly identical FT-IR spectra, the same A-type crystalline pattern and morphology, furthermore, a higher resistant starch content was detected in corn starch obtained through extraction methods. This finding will provide useful information to food industries for extraction of corn starch.

Development and validation of a liquid chromatography-tandem mass spectrometry (LC-MS/MS) method including 25 novel synthetic opioids in hair and subsequent analysis of a Swiss opioid consumer cohort.

Major public health concern is raised by the evidence that common drugs like heroin are now frequently laced or replaced with highly potent novel synthetic opioids (NSOs). The objective of this study was to explore the prevalence and patterns of NSOs in a cohort of Swiss opioid users by hair analysis. Hair analysis is considered an ideal tool for retrospective consumption monitoring. Hair samples from 439 opioid users in Zurich were analyzed. Study inclusion required a previous positive hair test result for heroin metabolites, oxycodone, fentanyl, methadone, or tramadol. The samples were extracted with a two-step extraction procedure, followed by a targeted LC-MS/MS (QTRAP® 6500+) analysis in multiple reaction monitoring mode for a total of 25 NSOs. The method underwent full validation and demonstrated good selectivity and sensitivity with limits of detection (LOD) as low as 0.1pg/mg. The analyzed sample cohort demonstrated a positivity rate for NSOs of 2.5%, including the following NSOs: butyrylfentanyl, acrylfentanyl, furanylfentanyl, methoxyacetylfentanyl, ocfentanil, U-47700, isobutyrylfentanyl and benzylfentanyl. Furthermore, we were able to identify specific consumption patterns among drug users. The results indicate that hair analysis is a valuable tool for investigating the prevalence of NSOs in drug-using populations, which seems to be low in the case of Swiss opioid users. Nevertheless, the results highlight the need for sensitive analytical detection methods in forensic toxicology to identify and monitor substance distribution in different populations.

Comprehensive two-step supercritical fluid extraction for green isolation of volatiles and phenolic compounds from plant material

A comprehensive two-step supercritical extraction using green solvents allows the extraction of non-polar and polar analytes within one run in two consecutive steps.

A new two-step road extraction method in high resolution remote sensing images.

High-resolution remote sensing technology is an efficient and low-cost space-to-earth observation strategy, which can carry out simultaneous monitoring of large-scale areas. It has incomparable advantages over ground monitoring solutions. Traditional road extraction methods are mainly based on image processing techniques. These methods usually only use one or a few features of images, which is difficult to fully deal with the real situation of roads. This work proposes a two-steps network for the road extraction. First, we optimize a pix2pix model for image translation to obtain the required map style image. Images output by the optimized model is full of road features and can relief the occlusion issues. It can intuitively reflect information such as the position, shape and size of the road. After that, we propose a new FusionLinkNet model, which has a strong stability in the road information by fusing the DenseNet, ResNet and LinkNet. Experiments show that our accuracy and learning rate have been improved. The MIOU (Mean Intersection Over Union) value of the proposed model in road extraction is over 80% in both DeepGlobe and Massachusetts road dataset. The figures are available from https://github.com/jsit-luwei/training-dataset.

Dual optical detection approach for capillary electrophoresis following two-step liquid-liquid extraction to determine ten phenols in water samples

In this research, the analytical method was developed and evaluated for determining phenol and its nine derivatives belong to the US EPA priority pollutant list in water samples by using dual-channeled capillary electrophoresis (CE) coupled with two types of optical detectors, namely LED-induced fluorescence (LEDIF) and ultraviolet (UV) detectors. The optimal background electrolytes for the first and second CE channels were 20 mM borate (pH 9.80) with 400 µM fluorescein and 55 mM borate (pH 11.75), respectively. The two-step liquid-liquid extraction (LLE) was used for sample preparation and enrichment, in which phenol and its derivatives were extracted from the aqueous phase using 10 mL of n-hexane/1-octanol (60/40, v/v) and then were back extracted into a 0.1 M NaOH as a final acceptor phase. Under the optimal CE and two-step LLE conditions, the enrichment factors of 10 phenols were 184 – 1120-fold, and the method detection limits were lowered to 0.02–0.60 µg/L. The obtained intra-day and inter-day precisions in terms of relative standard deviations (RSD) were between 4.0 and 7.3 % and 6.7 and 14 %, respectively. This approach was used to determine phenols in water samples, with recoveries ranging from 82.0 to 108.9 %. In combination with sample enrichment by two-step LLE extraction, this is the first CE study conducted to determine phenols in the EPA list using two detector approaches, specifically CE-LEDIF/CE-UV.

Phenolics-Enhancing Piper sarmentosum (Roxburgh) Extracts Pre-Treated with Supercritical Carbon Dioxide and its Correlation with Cytotoxicity and α-Glucosidase Inhibitory Activities

Piper sarmentosum was found to have various phytochemicals such as polyphenols and flavonoids but also contains asarone isomers, which were reported as carcinogenic in several preclinical studies. Therefore, reducing asarone isomers from this functional food is important while retaining its functional properties. This study compares the total phenolics, total flavonoids, vitexin and naringenin contents, cytotoxicity, and anti-hyperglycaemic activity between various solvent extracts using a two-step extraction with SC-CO2 pre-treatment and a single-step conventional solvent extraction without SC-CO2 pre-treatment. The findings showed that phenolic content was significantly enhanced in ethanol, 50% ethanol, and water extracts pre-treated with SC-CO2, significantly correlated with α-glucosidase inhibitory activity. SC-CO2 pre-treated extracts enhanced the viability of two normal fibroblasts NIH/3T3 and CCD-18Co cell lines. It is concluded that SC-CO2 extraction offers a rapid pre-treatment step to produce safer extracts with better quality and efficacy.

Quantitation of total vitamin D2 and D4 in UV-exposed mushrooms using HPLC with UV detection after novel two-step solid phase extraction

A robust method for quantitation of total vitamin D2 and D4 in mushrooms by high performance liquid chromatography with UV detection (HPLC-UV) was developed to analyze mushrooms exposed to UV light. A two-step solid phase extraction (SPE) (silica, carbon black) removed chromatographic interferences typically resolved only with mass spectrometric detection (LC-MS) and allowed quantitation of all vitamin D and pre-D analytes. The vitamin and pre-vitamin forms of D2, D4 and D3 (internal standard), as well as other photoisomers and sterols were resolved. Results for six types of UV-exposed mushrooms were comparable to LC-MS. Screening of ten additional types of UV-exposed mushrooms without the IS confirmed lack of interference with the IS. The limit of quantification (µg/100 g fresh weight) was 0.4 for vitamin D and 0.9 for pre-vitamin D. Mushrooms do not have to be dried, and separatory funnels and large solvent volumes were also eliminated from sample preparation.

Sensitive and Rapid LCMS/MS Method for the Estimation of recently approved Antiviral drugs Maribavir and Fostemsavir in spiked human plasma

In this study, a straightforward, highly sensitive, and selective liquid chromatography/tandem mass spectrometry (LC–MS/MS) method was developed and rigorously validated for the simultaneous quantification of Maribavir and Fostemsavir in human plasma. To ensure precision and reliability, we employed Dolutegravir as the internal standard (IS). The analytical process involved a two-step extraction method. Initially, protein precipitation was induced by the addition of acetonitrile, followed by liquid–liquid extraction using a 1:1 (v/v) mixture of diethyl ether and dichloromethane as the extracting solvent. Separation of the analytes was achieved through reversed phase high-performance liquid chromatography (HPLC) using a Phenomenex C18 Luna column (4.6 mm×100 mm, 5 µm). A simple isocratic mobile phase consisting of acetonitrile, methanol, and 0.1% formic acid (35:55:10, v/v) was used, operating at a flow rate of 0.5 mL/min. Under these optimized conditions, the LC chromatogram of the spiked standard exhibited distinct peaks at retention times of 2.07 min, 2.59 min, and 4.29 min for Fostemsavir, Maribavir, and the internal standard, respectively. Detection was performed using a triple quadrupole mass spectrometer employing electrospray ionization in positive ion mode and multiple reaction monitoring (MRM) mode. The mass transitions monitored were m/z 377 → 110, m/z 584 → 105, and m/z 420 → 142 for maribavir, fostemsavir, and dolutegravir, respectively. This method provided a rapid analysis within 5 minutes, over a linear concentration range of 15-750 ng/mL for both maribavir and fostemsavir. Method validation was conducted following FDA guidelines for bio-analytical methods, and the results consistently fell within the acceptable limits for both analytes. Therefore, our developed method holds promise for the accurate analysis of maribavir and fostemsavir in human plasma, and it has potential applications in pharmacokinetic studies

Influence of Particle Size and Extraction Methods on Phenolic Content and Biological Activities of Pear Pomace.

The main goal of this research was to investigate how particle size influences the characteristics of pear (Pyrus Communis L.) pomace flour and to examine the impact of different pre-treatment methods on the phenolic content and associated bioactivities. Pear pomace flour was fractionated into different particle sizes, namely 1 mm, 710 µm, 180 µm, 75 µm and 53 µm. Then two extraction methods, namely maceration with methanol and two-step extraction with hexane via Soxhlet followed by ultrasound extraction with methanol, were tested. Total phenolic and total flavonoid contents ranged from 375.0 to 512.9 mg gallic acid/100 g DW and from 24.7 to 34.6 mg quercetin/100 g DW, respectively. Two-step extraction provided antioxidant activity up to 418.8 (in FRAP assay) and 340.0 mg Trolox/100 g DW (in DPPH assay). In order to explore various bioactive properties, this study assessed the inhibitory effects of enzymes, specifically α-amylase and β-glucosidase (associated with antidiabetic effects), as well as angiotensin-converting enzyme (linked to potential antihypertensive benefits). Additionally, the research investigated antibacterial potential against both Gram-negative (E. coli) and Gram-positive (S. aureus) bacteria, revealing significant results (p < 0.05), particularly in the case of the two-step extraction method. This investigation underscores the substantial value of certain food industry wastes, highlighting their potential as bioactive ingredients within the framework of a circular economy.

Platform chemicals recovery from spent coffee grounds aqueous-phase pyrolysis oil

Spent coffee grounds (SCG) are a valuable biogenic waste diffused on a global scale, containing a significant amount of extractives. The aim of this study is to characterize the pyrolysis oil fractions, under various process conditions, targeting their potential applications as biofuels and source of valuable chemicals. Pyrolysis tests were carried out in the range of 400–550 °C with a laboratory-scale screw reactor and a two-step solvent extraction process, was conducted for the aqueous bio-oil phase. The results showed that heavy organic bio-oil resulted in a carbon rich biofuel, with a carbon content of up to 63 % (w/w) and HHV up to 34.8 MJ/kg. Chloroform was selective in extracting xantines (68–74 % of the peak area), furans, phenols, and fatty acids from the aqueous phase, while the ethyl acetate extract was abundant in p-benzoquinone (70–83 % of the peak area), a key-player chemical for the petrochemical industry. The residual unextracted water phase is very rich in organic acids i.e. acetic, propionic, and formic-whose concentration is in the range 47 g/L and 87.9 g/L. The results of this study outline how solvent extraction is a promising technique for extracting valuable chemicals to improve the economic potential of spent coffee grounds pyrolysis-based biorefinery.

An industrial process fault diagnosis method based on independent slow feature analysis and stacked sparse autoencoder network

Deep learning, with its powerful multilayer nonlinear representation of deep neural networks, enables models trained based on deep learning to describe the true distribution of data more accurately and thus have better generalization capabilities. However, the training data are usually assumed to obey independent identical distribution. Industrial process data nowadays usually have complex characteristics such as non-Gaussian, nonlinear, dynamic, strong correlation, and high-dimensional, which make it difficult to meet the assumptions of deep learning. Using industrial process data directly would result in low model accuracy and bias in the model output. This paper proposes a fault diagnosis method based on independent slow feature analysis (ISFA) and stacked sparse autoencoder (SSAE) network. The statistical properties possessed by ISFA are used to perform preliminary feature extraction of industrial process data, and then the extracted preliminary features are input to the SSAE network for fine-grained feature extraction. The proposed two-step feature extraction method not only makes the data input to the SSAE network as close as possible to obey independent identical distribution and provides convincing fault diagnosis results, but also makes full use of the powerful feature extraction capability of the SSAE network, which makes the proposed method also significantly improve the detection accuracy of incipient faults. The feasibility and superiority of the proposed method is verified through the TE process.

All-natural wheat gliadin-gum arabic nanocarriers for encapsulation and delivery of grape by-products phenolics obtained through different extraction procedures.

Grape pomace (GP), the major winery by-product, is still rich in phenolic compounds, scarcely applied in food systems due to physicochemical instability issues. This work aimed at fabricating gliadin (G)-based nanoparticles through antisolvent precipitation, for delivery of GP extracts, investigating different extraction strategies with ethanol/water solution (70:30 v/v). Interestingly, the fabricated nanoparticles were characterized by a nanometric size range with hydraulic diameter values around 100nm and ζ-potential of 18-22mV. The addition of gum arabic (GA), at the optimized G/GA ratio 1:1, improved particle stability and encapsulation efficiency of GP polyphenols. The two-step extraction of GP in the G-rich solvent retrieved from G extraction, as evidenced by total phenolics (1.24 times higher than the two separately obtained extracts G/GP10:10), HPLC-PDA analysis, encapsulation efficiency (62.9% in terms of epicatechin), and simulated digestion (95.6% release of epicatechin), represented the most promising approach to obtain G nanoparticles for efficient delivery of GP extracts.

Entity–relation triple extraction based on relation sequence information

Data overlap is a significant challenge in the task of entity–relation triple extraction. This task includes two research lines, line one first identifies entities and then predicts relations while line two completely shuffles the order. The methods in line two are more conducive to the optimization of the data overlap problem. Recent works have made breakthroughs in dealing with overlapping data, but there are still some defects such as difficulty in convergence and poor performance on datasets with numerous relations. To solve the above problems, we adopt a two-step strategy of first extracting subjects, and then predicting relation–object pairs. Considering the absence of connectivity between the two steps in the conventional method, we adopt the relation sequence as input in both steps and propose the TERS model. The relation sequence can connect two steps and improve the single-step and comprehensive extraction capability of the model. The TERS model consists of two modules. The first module performs information interaction and filters invalid subjects through the Text Relation Attention method. The second module implements multiple iterations of information interaction through the Information Flow method. The combination of these two modules contributes to the strong entity–relation triple extraction capability of our model. We evaluate our method on three public datasets. Extensive experiments show that our TERS model outperforms previous state-of-the-art models in triple extraction and overlapping data processing. Compared with other two-step extraction models, the advantages of our model are more obvious.

Phenolic, tocopherol, and essential fatty acid-rich extracts from dandelion seeds: Chemical composition and biological activity

Dandelion is a sustainable biomass that has occasional use in the food and pharmaceutical industry. However, commercial use of its extracts is restricted by the lack of systematic information on safety, composition, and biological activity. To broaden dandelion use, the present study brings new knowledge on extracts from dandelion seeds that could find application as safe and functional food ingredients. The employed two-step supercritical fluid extraction process, followed by the conventional extraction, enabled the separation of extracts with increased content of phenolics, tocopherols, and essential fatty acids. Those compounds were found to be the major components of dandelion extracts, reaching high values up to 799 mg GE/g, 249 mg α-TE/g, and 75%, respectively. The extracts also contained significant amounts of flavonoids (up to 20.5 mg QE/g) and pigments (chlorophyll A up to 1.0 g/kg, chlorophyll B up to 0.3 g/kg, and carotenoids up to 0.1 g/kg). This study revealed new bioproducts that express strong antioxidant (reaching IC50 values up to 132.5 μg/mL) and antimicrobial activity (with minimum inhibitory concentrations up to 80.0 μg/mL). Among the tested 23 microbial strains, the extracts exhibited the strongest activity against food-borne pathogens Micrococcus luteus and Bacillus subtilis. Furthermore, the antitumor and antiviral activity of separated dandelion biological products was evaluated.

(Selective) Isolation of acetic acid and lactic acid from heterogeneous fermentation of xylose and glucose

The present study focuses on the isolation of acetic and lactic acid from a fermentation broth produced by heterofermentative microorganisms using glucose and xylose as substrate. Especially xylose fermentation to lactic acid leads to unwanted by-product formation of acetic acid. Reactive liquid-liquid extraction is an energy-efficient downstream process, where the use of green solvents such as d-limonene opens the way to a more sustainable production. To find the optimum solvent/reactive extractant pairing, the reactive extractants trioctylamine, trioctylphosphine oxide, Aliquat 336, and tributyl phosphate were used diluted in 1-octanol, 1-decanol, d-limonene or a deep eutectic solvent. The phosphine-based extractants proved to be most effective for both acids. In the first extraction step, 19% of acetic acid and only 3% of lactic acid are extracted with trioctylphosphine oxide/1-octanol when the xylose feed is used without pH adjustment. The pKa value of the acids is responsible for the difference in extraction efficiency leading to the proposal of a two-step extraction separating first acetic acid and after pH adjustment, lactic acid can be extracted. The combination of trioctylphosphine oxide diluted in d-limonene leads to a surprisingly high selectivity for lactic acid isolation in the second extraction step. The present study shows for the first time that green solvents lead to similar extraction efficiencies compared to conventional solvents such as 1-octanol. For back extraction n-heptane and p-cymene are used as disintegration agents and water as stripping phase; n-heptane results in a lactic acid back extraction efficiency of up to 82% and p-cymene up to 70%. This shows that also for the back extraction p-cymene as a green disintegration agent leads to similar results as fossil-based n-heptane.

Comparing Efficiency of Green Methods for Surimi Skin and Bone Gelatin Extraction

Globally, the surimi processing industry produces a large amount of by-products in the form of head and viscera, skin, bones, scale, etc. The aim of this study was to assess the combined biomass of pink perch skin and bones obtained from the surimi industry as a potential source of raw material for gelatin production and identify a green method of gelatin extraction by comparing four green processes. Four green gelatin extraction processes were compared for their gelatin extraction efficiency. Among the four processes, process 1 and process 2 comprised of two-step extraction viz pre-treatment with NaCl and extraction with hot water. Process 3 and process 4 comprised of single-step wherein pre-treatment and extraction were done simultaneously with acidic water using acetic acid. The gelatin extraction efficiency was determined based on the yield and L-hydroxyproline content of the extracted gelatin. Further, the extracted gelatin was characterized for their proximate and amino acid composition. The acetic acid based single-step method was found to be more efficient in the extraction of gelatin than the NaCl pretreatment method. The gelatin extracted with this method had a higher yield (4.2%), protein content (79.6%), and imino acid (27.3%) content than the NaCl pretreatment method, which had 1.51% gelatin yield, 48.1% protein content, and 13.1% imino acid content. The results suggested that the single-step extraction method can be effectively utilized for the extraction of gelatin from pink perch skin and bones combined biomass. This study provides a method for the valorization of the surimi industry by-product into a high value product with potential application in various industries.

Two-step method for rapid isolation of genomic DNA and validation of R81T insecticide resistance mutation in Myzus persicae

Isolation and amplification of nucleic acid (DNA) is considered a vital and potent instrument in molecular biological research. However, its functioning outside of a laboratory setting is difficult because of complex procedures that demand expert personnel and expensive equipment in addition to the fulfillment of several additional requirements. DNA isolation from minute insects is sometimes difficult, making diagnostic and genotyping procedures problematic. Thus, the current work offers a high-throughput, cost-effective, straightforward, and faster approach for isolating DNA from the aphid Myzus persicae. Intriguingly, two-step DNA extraction process yielded a high yield of extremely pure genomic DNA and required only 10 s to complete. PCR investigation aiming at amplifying the non-synonymous R81T region on the loop D site of the nAChR gene of M. persicae was subsequently utilized to successfully validate the recovered DNA. Moreover, the proposed method was compared in terms of yield and purity with conventionally used DNA isolation methods including, phenol:chloroform, salt out, and commercially available kits. In conclusion, this newly developed method would enable researchers to quickly process many biological samples used to analyze genetic diversity, mutant screening, and large spectrum diagnosis both in laboratory and field conditions.

Enhanced Two-Step Extraction from Biomass of Two Cymbopogon Species Cultivated in Santander, Colombia.

The insertion of circular economy principles into the essential oil (EO) production chain aims to reduce waste generation and make integral use of harvested plant material. Higher profits from integral use with reduced waste generation contribute to the eventual use of the EO value chain as an alternative to illicit crops in Colombia (mostly coca). In this study, Java-type citronella (Cymbopogon winterianus) and palmarosa (C. martinii) plant materials were used in two consecutive processes to obtain EOs and extracts. The residual biomass after EO distillation was subjected to ultrasound-assisted hydroethanolic extraction to afford extracts that contained bioactive compounds. Citronella and palmarosa were distilled with typical EO yields (1.0 ± 0.1% for citronella; 0.41 ± 0.06% for palmarosa; n = 5) either through hydrodistillation assisted by microwave radiation or through steam distillation, and their composition (determined via GC/FID/MS analysis) and physicochemical parameters fell within their ISO standard specifications. The concentration of citronellal, the major compound of citronella oil, was 500 ± 152 mg/g. Geraniol, the main component of palmarosa oil, was found at 900 ± 55 mg/g. The citronella and palmarosa hydroalcoholic extracts (4-11% yield) were analyzed with UHPLC-ESI-Orbitrap-MS, which permitted the identification of 30 compounds, mainly C-glycosylated flavones and hydroxycinnamic acids. Both extracts had similar antioxidant activity values, evaluated using the ABTS+● and ORAC assays (110 ± 44 µmol Trolox®/g extract and 1300 ± 141 µmol Trolox®/g extract, respectively).

Chlorella vulgaris microalgae derived blends in micro gas turbine engines: A comprehensive environmental impact analysis for highway vehicle applications

The significant benefits of microalgae biofuel have made it a preferred choice in various industries, including aviation. Microgas turbine engines can be promising choice for highway vehicles. This research paper investigates the process of producing fuel from microalgae, as well as its performance and emission characteristics in the micro gas turbine engine operating at sea level conditions for highway vehicle applications. A two-step extraction and transesterification process were employed to convert the biofuel, using a batch stirrer reactor for esterification. The preparation of biofuel blends followed the volume fraction method at the concentration of 10% and 30%. Additionally, nanoparticles were incorporated into the blends at a 50 ppm concentration to enhance overall characteristics of the engine. Titanium dioxide nanoparticles, known for their high surface-to-volume ratio, were used for this purpose. Experimental tests were conducted on a 30 kW micro gas turbine engine to evaluate the fuel's quality in terms of performance and emissions. Various parameters were measured at different engine speed, including 30,000 rpm, 40,000 rpm, 50,000 rpm, 60,000 rpm, and 70,000 rpm. The results obtained clearly demonstrate that the optimal blending of biofuel with neat Jet-A fuel improves performance by generating the required thrust while significantly reducing harmful gas emissions. Furthermore, the addition of nanoparticles acted as a catalyst and enhanced the quality of the fuel blends, making them an efficient alternative for aircraft engines as well. Added to above, there is an significant reduction in the emission of the CO has been noted across wide range of speed. From the results it is evident that microgas turbine engine can be an ideal choice for the highway vehicles to meet reduced carbon emissions.