Latin American Applied Research - An international journal

Application of the brine method to extend the shelf life of zucchini (Cucurbita pepo L.) flowers: Changes in antioxidant activity, total phenolic contents and phytochemical profile

Ayca Gülhan — 2025-07-15

Edible flowers, demanded by consumers for their distinct sensory properties and health benefits, have a short shelf life. This study aimed to apply the brine method to extend the shelf life of zucchini (Cucurbita pepo L.) flowers, one of the edible flowers. The phytochemical profile of the samples was determined using LC-MS/MS, a method that allows the amount of 56 different phytochemicals to be determined. In this context, zucchini flowers were stored in brines containing 5% and 10% NaCl for the 7th, 14th, 21st and 28th days. The highest antioxidant activities were found in DPPH (19.23±0.74 mgTE/g extract) and CUPRAC (181.43±1.08 mmol Trolox Eq/g) on the 7th day of brining at 10% salt concentration. The highest TPC (32.10±0.33 mg GAE/g) was determined on 7th day of brining and at 10% salt concentration. The dominant phytochemicals were determined as quinic acid, fumaric acid, protocatechuic acid, 4-OH-benzoic acid, routine, hesperidin, isoquercitrin, nicotifluorine, quercetin and kaempferol at 10% salt concentration on the 7th and 14th days. This study demonstrates that the brine method can be used as an appropriate processing technology to extend the shelf life of zucchini flowers and also to broaden their application. Additionally, the findings of this study contributed to optimizing the storage time and salt concentration of brined zucchini flowers. It is thought that brined flowers can gain a place in the market as a commercial food product.

Photocatalytic degradation of metsulfuron methyl in an herbicidal formulation by TiO2 supported on magnetite particles coated with SiO2-TiO2 oxides

Juan Paulo Montañez — 2025-07-15

Aqueous pesticides may be degraded through heterogeneous photocatalysis with TiO₂. Supporting it on different materials, for example, magnetic particles, its further removal is facilitated. In this work, we report the synthesis of TiO₂ supported on TiO₂-SiO₂-coated magnetite particles by a sol-gel process. These supporting materials were synthesized by varying the Si/Ti ratio, thus composites with different structural characteristics were obtained. With a theoretical Si/Ti molar ratio equal to 10, a supporting material with the highest specific surface area was synthesized (FTS-10). By supporting TiO₂ over FTS-10, CM-2 catalyst was obtained. This catalyst degraded 70 % of the herbicide Metsulfuron methyl present in a commercial formulation at persistent conditions, with similar activity to that of the bulk TiO₂. CM-2 can be separated by magnetic attraction, and it can be reused for at least five cycles. We propose this catalyst as a good alternative for the remediation of contaminated effluents with this herbicide.

A comparative study of chemical and enzymatic interesterification for bioparaffin production from soybean oil

Sandra Romero — 2025-07-15

This work focuses on the production of bioparaffins, intended as a substitute for mineral paraffins, derived from partially hydrogenated and interesterified soybean oil mixtures. Chemical interesterification using sodium methoxide and enzymatic interesterification employing a supported lipase are comparatively studied. The synthesized materials were thoroughly characterized, including chemical composition analyses, thermal properties, crystalline structure, and texture. It was observed that both interesterifications produced a decrease in trisaturated and an increase in disaturated-monounsaturated triglycerides. Mono, diglycerides, methyl esters and free fatty acids were also identified as by products. Thus, the interesterification reaction produces materials with lower melting temperatures and improved plasticity compared to the initial mixtures, within the range of commercial mineral paraffins.

Effect of surface modification treatments on the properties of electrodeposited Cu-CNT coatings for self-lubricating surfaces.

Leandro Nicolás Bengoa — 2025-07-15

An eco-friendly alkaline glutamate-based electrolyte was used to produce copper-carbon nanotubes composite coatings with improved tribological properties.

Experiments were performed at different current densities to deposit pure Cu, Cu-CNT and Cu-activated CNT coatings. The electrolyte was agitated by low frequency ultrasound to disperse the particles and consequently, help their incorporation in the Cu matrix. The coatings were characterized by SEM and XRD. The wear resistance and coefficient of friction were evaluated with tribological tests.

Cu-CNT and Cu-activated CNT composites were successfully produced with improved tribological properties respect to those of pure Cu. It was found that the codeposition modified the morphology of the coatings as well as their crystallographic orientation. These modifications were more noticeable when the CNT were activated by acid-treatment.

Mineral oil hydrocarbons in marinated anchovy products

Bilge Bilgin Ficicilar — 2025-07-15

Mineral oil hydrocarbons (MOH), including MOSH and MOAH, pose a contamination risk in food due to their presence in packaging, processing, and environmental sources. While regulatory limits in the EU are still evolving, this study analyzed MOSH and MOAH levels in marinated anchovy samples, a widely consumed fish in Turkey and Europe. Samples were assessed under different marination and packaging conditions.

Results showed MOSH contamination primarily in the C25–35 range, varying with the processing method. Notably, the oil-free, drained sample had no detectable MOSH or MOAH, indicating that sunflower oil and packaging significantly contribute to contamination. These findings highlight the need for stricter monitoring and regulatory measures to minimize hydrocarbon exposure in marinated fish products and ensure consumer safety.

Determining the moisture diffusion coefficient during soaking and cooking of chickpeas

Fladna Moura — 2025-07-15

This study aimed to apply a numerical/experimental approach to determine the moisture diffusion coefficient in chickpeas during the soaking and cooking processes, considering the seed swelling. The mathematical model combines Fick's second law to describe moisture transfer with the Peleg model to describe the expansion of the seed. It was solved numerically using finite differences method and fitted to experimental data of hydration kinetics at different temperature conditions (26, 40, 50, 63, 74, and 86 ºC). The numerical results showed that the D-values estimated considering deformable seeds were around 25-30 % greater than those estimated considering non-deformable seeds. This modeling approach could be useful in analyzing legumes' soaking and cooking process, but further studies are necessary to confirm its efficacy in different seed types and experimental conditions.

Efficient production of honey-enhanced banana chips: A multi-objective optimization approach

María Fernanda Laborde — 2025-07-15

Food industries aim to optimize processes for quality products in shorter times. For fruits, specific storage and transport conditions are essential to maintain quality, extend shelf life, and preserve sensory and nutritional properties. This study aims to maximize honey incorporation into banana slices during osmotic dehydration, assisted by ultrasound, while minimizing processing time. The process includes three stages: 1) 20 min ultrasound-assisted immersion in distilled water, 2) osmotic dehydration in hypertonic honey solution, and 3) hot air drying. The second and third stages were mathematically modeled using a multi-objective MINLP optimization in GAMS with the Baron solver. Optimal conditions achieved an 8.75% gain in soluble solids (SG) in 11.48 h, reducing processing time by 64% with a 70% honey solution. This optimization allows a compromise solution between two contradictory objectives for planning the production process: maintaining product quality and reducing production time. The process leads to lower total costs.

Modeling and control of a new dual-mode power-split hybrid electric transmission

Bentolhoda Eivani — 2025-07-15

This paper introduces a new dual-mode power-split hybrid electric transmission. The system has two modes of operation which provide high-efficient performance of the hybrid electric vehicle in different driving conditions. Dynamic programming method is used as the approach of energy management strategy. This method provides best results for the performance of any hybrid transmission system and its results are used as the benchmark for other optimal control methods. According to the simulation results, the introduced system improves the fuel consumption comparing the well-known hybrid electric vehicle Toyota Prius.

Automated brain tumor segmentation with deep learning

B. Manjunatha — 2025-07-15

Accurate tumor delineation is crucial for effective diagnosis, treatment planning and risk factor identification. This study presents an advanced Deep Learning (DL) framework designed for the precise segmentation of brain tumors and reliable survival prediction for tumor patients. In this work, a cutting-edge approach that leverages an ensemble strategy, combining two distinct 3D UNet architectures (3D U-Net and Attention 3D U-Net) is incorporated for segmentation purpose. This ensemble approach employs a majority rule mechanism and ensures a more reliable and comprehensive delineation of tumor regions. The proposed system's effectiveness and performance are evaluated using BraTS 2018 dataset. The proposed deep learning network trained and validated for brain tumor segmentation achieved promising results on the online final dataset, as evidenced by the Dice coefficient and Hausdorff metric scores. Specifically, the performance metrics for different tumor regions were as follows: Enhancing Tumor (ET), 0.805 Dice Score and Hausdorff Distance about 2.779. For Tumor Core (TC), its about 0.851 and 6.378 and for Necoratic core 0.904 and 6.323.

Multi-way machine learning estimation of hardness of high-carbon martensitic stainless steels depending on the influences of austenitizing temperature, quenching media, and annealing temperature

Cagin Bolat — 2025-07-15

In recent years, parallel to the new industrial trends, the applicability of novel artificial neural network systems and machine learning techniques in the manufacturing and metallurgy sectors has risen due to the increasing competitiveness among steel, pipeline, and construction firms. This work focuses on estimating the hardness of high-carbon martensitic stainless steels depending on the heat treatment media, austenitizing temperature (AT), and secondary annealing temperature using different machine-learning methodologies for the first time in the literature. The attained outcomes indicated that the highest average hardness level was found in the medium-level tempering temperature and low AT in brine. As the tempering temperatures rose to the upper limits, measured hardness results diminished in both quenching media. Besides, according to all fold types and error metrics, the random forest (RF) machine-learning model was the strongest approach to estimate the final hardness values of the heat-treated samples whereas the Bayesian ridge (BR) was the poorest way.

Optimizing beta-carotene bioaccessibility predictions with advanced machine learning algorithms and feature selection strategies

Incilay Yildiz — 2025-07-15

Since the artificial intelligence is of great attention in food science and technology, in the current study it was aimed to utilize machine learning methods including TreeBoost (TB), Multilayer Neural Network (MLP) and Support Vector Machine (SVM) to predict the bioaccessibility of beta-carotene. The emulsion type (micro- or nano-), oil/water phase ratio, the oil type, the type of the emulsifier (protein or carbohydrate), and beta-carotene concentration were selected as variables for the predicted models. Results demonstrated that TB-based model provide the best prediction for the bioaccessibility of beta-carotene with the values of R² = 0.4325, RMSE = 17.2484, NMSE = 0.5675, and MAE = 13.3809. Besides, according to TB-based Model 7, the emulsion type (micro- or nano-), oil/water phase ratio, the oil type, the type of the protein, and beta-carotene concentration were found to be efffective on the bioaccessibility of beta-carotene. Based on the comparison of method performance, The RMSE value of TB-based Model 7, showed an improvement of 9.27 % compared to the SVM method and 13.4 % compared to the MLP method. To conclude, the outcomes of this study will shed light to future experiments by simplifying the variables of any process using different machine learning methods.

Development of a superhydrophobic concrete coating: Using paper sludge ash and lignosulfonate adhesive

Jae Yeol Kim — 2025-07-15

In the contemporary construction, concrete stands out as a prominent material, recognized for its widespread utilization across the globe. Despite its remarkable performance in structures over the past three decades, concrete remains susceptible to degradation, particularly through reinforcing corrosion induced by water absorption. This paper introduces a novel sustainable solution, the nanomaterials-based superhydrophobic for waterproofing concrete coating. The paper sludge ash solution was sprayed on a layer of lignosulfonate adhesive coated on grade 25 concrete, which exhibited a remarkable water contact angle of 156.296°. The cumulative water uptake was significantly curtailed and the void content in the coated concrete was minimized. This innovative approach not only addresses the inherent water absorbency of concrete but also showcases the potential for repurposing waste materials towards enhancing construction elements.

Enhanced cooling techniques for Inconel 718 drilling using nano-ionic liquid coolants

M. Karthikraja — 2025-07-15

The manufacturing industry has thoroughly Examined the use of cutting fluids improved by nanotechnology that have higher heat conductivity to increase the efficiency of drilling operations. Due to their diverse physical & chemical characteristics and environmental compatibility, ionic liquids show significant promise for use as cutting fluids. This study examines how well different combinations of ionanofluids with nanoparticles perform as cutting fluids in drilling, by analyzing heat transfer through computational fluid dynamics and Ansys Fluent software. The thermal properties of a mixture containing TiO₂, Al₂O₃, and Multi-walled carbon nanotube (MWCNT) nanoparticles are studied by mixing them with the ionic fluid 1-ethyl-3-methylnidazolium tetra-fluoroborate at various Reynolds numbers and particle volume fractions. Inconel 718 titanium alloy is used to make the workpiece, and tungsten carbide-cobalt is used to make the drill bit. The drilling temperature of the pure ionic liquid decreases by 23.18% with the addition of MWCNT and ionic coolant. While the particle volume (%) remains higher. For pure ionic coolant, the Al₂O₃, TiO₂, and MWCNT ionanofluids improve the mean heat transfer coefficient by 33.44%, 44.32%, and 59.05%, respectively. When it comes to thermal efficiency and rate of heat dissipation, MWCNT nanocoolants outperformed Al₂O₃and TiO₂ ion nanocoolants.

Effects of Soret, Dufour and melting on micropolar fluid flow near stagnation point over a stretching sheet embedded in porous medium

Krishnandan Verma — 2025-07-15

The current work examines the mixed action of Soret and Dufour effects, melting and chemical reaction on stagnation point flow of micropolar fluid on a stretching sheet in a porous medium. Suitable non-dimensional transformations are adopted to transform the governing equations of flow, heat and mass transfer to dimensionless form. Bvp4c numerical scheme is applied to acquire the result numerically in graphical form for velocity, microrotation, temperature and concentration distributions. The accuracy of the solution has been verified by making comparison with already published work. Numerical values are computed for coefficient of skin-friction, couple stress, Nusselt number and Sherwood number for important parameters to get a deeper insight of the impact of dimensionless shear stress at the surface, heat and mass transmission process. The study discloses the fact that the combined effect of Soret and Dufour hike the fluid temperature but reduces the concentration.

Entropy generation analysis on mixed convection dissipative flow of MHD chemically reactive micropolar fluid with thermo-diffusion effect

Reshmi Dey — 2025-07-15

The research presented in the study provides a fundamental understanding to minimize the irreversibility process in a micropolar flow system, which is essential in the field of Bio-engineering and various designing. In the study of micropolar fluids, the vortex viscosity and scaling material parameters play a crucial role and influences the dynamics of micropolar flow. The flow of a micropolar fluid through a permeable semi-infinite oblique plate submerged in a porous medium has been studied theoretically using an unstable combined convection process. The dynamical equations, which are first non-dimensionalized by using a set of dimensionless quantities, are solved by creating an asymptotic multi-parameter perturbation method. The thermodynamic analysis on entropy generation is also performed for variour flow parameters. It is noticed from the analysis that when the magnetic field parameter (M) changes from 1.0 to 2.0, the entropy generation upsurges by nearly 32 to 49 percent. It is also recorded that when Brinkman number (Br) increases from 0.5 to 1.5, the entropy generation number increases drastically by 33 to 50 percent approximately.