Texture Parameters Research Articles

KEARNS TEXTURE PARAMETERS AND PROPERTIES OF HEXAGONAL MONO- AND POLYCRYSTALS

Problem statement. Polycrystals' physical and mechanical properties are determined by the corresponding properties of single crystals (crystallites) that make up the polycrystal, and their distribution by orientation in the polycrystal (texture). In metals with a hexagonal structure, the use of Kearns texture parameters, which show the degree of coincidence of the hexagonal axis of crystallites with a given direction in a polycrystalline sample, allows determining the property of a polycrystal in this direction, if the properties of a single crystal in the direction of its hexagonal axis and the perpendicular direction are known. It is also possible to solve the inverse problem: determining the properties of a single crystal in the direction of its hexagonal axis and the perpendicular direction based on the properties of the polycrystal and the determined of the Kearns texture parameters. Materials and methods. Elastic and mechanical characteristics of hexagonal alloys based on titanium (Grade 1 and VT1-0) and magnesium (Mg − 10 % Li and ZE10) were studied after different types of deformation − rolling, alternating bending, and twist extrusion. The Kearns texture parameters were determined by the X-ray method based on the data of the construction of inverse pole figures (IPF) in the normal direction (ND) to the sheets plane and the rolling direction (RD). The results of the experiment. It is shown that the specified method allows to calculate the elastic and mechanical properties of the specified polycrystals after they undergo various types of deformation with an error of no more than 5−10 %, as well as to solve the inverse problem of calculating the properties of single crystals with an error of no more than 5 %. Conclusions. Using the parameters of the Cairns texture and the characteristics of single crystals of magnesium alloys ZE10, Mg 5 % Li, titanium Grade1 and VT1-0 made it possible to calculate the corresponding properties of polycrystals and their anisotropy. The use of Cairns texture parameters, experimental values of the modulus of elasticity, tensile strength and yield strength of polycrystalline sheets of the studied magnesium and titanium alloys made it possible to evaluate the characteristics. There are strong correlations between the values of the modulus of elasticity, the mechanical characteristics of the studied sheets of magnesium and titanium alloys, on the one hand, and the corresponding parameters of the Cairns texture, on the other hand.

The Influence of Selected Titanium Alloy Micro-Texture Parameters on Bacterial Adhesion.

The colonization of microbes and the resulting formation of biofilms on dental implants are significant contributors to peri-implantitis and the failure of these implants. The aim of the research was to analyze the impact of density and depth of laser texturing of the Ti-6Al-7Nb alloy surface on the colonization of selected microorganisms and biofilm formation. Standard strains of Gram-negative and Gram-positive bacteria and yeasts from the American Type Culture Collection-ATCC-were used to demonstrate the ability to form single-species biofilms in vitro. The study evaluated three types of titanium samples with different texture density and depth. The colonization and biofilm formation abilities of the tested microorganisms were assessed. The obtained results were subjected to statistical analysis. Among the analyzed strains, L. rhamnosus showed the highest colonization of the tested surfaces. It was found that there is no relationship between the texture parameters and the number of colony-forming units (CFU/mL) for C. albicans, S. mutans, and L. rhamnosus. For the F. nucleatum strain, it was shown that the number of colony-forming bacteria is related to the texture density.

Control and Modelling of Laser Shock Peening without Coating (LSPwC) Texture of AISI 9310 Steel.

LSPwC is an important development of Laser shock peening (LSP) technology, and surface texturing is an effective method to improve tribological properties. The combination of these is expected to innovate a new surface texturing technology with a strengthing effect, but no one has attempted it. In this paper, a new LSPTwC technology combining them is innovatively proposed and validated on AISI 9310 steel, which is commonly used in helicopter transmission components for surface texturing. The LSPTwC surface was studied using an optical microscope, electron microscope, energy dispersive spectrometer, and so on. The results proved that LSPTwC is an effective texturing method of AISI 9310 steel, which modulates the texture and improves the properties, such as the microhardness increased by more than 10%. A model for calculating the texture and process parameters is also constructed on a statistical basis, and a modeling method for textured surfaces is proposed. It is verified that the calculation results and the constructed model are highly consistent with the test, with a diameter deviation <3% and depth deviation <4%. The above results can provide the experimental basis, process design method, and calculation model for single-point LSPwC texturing of AISI 9310 steel parts for helicopters, which have application value.

A Study of Tribological Performance Prediction Based on Surface Texture Parameters

Surface texture parameters are a quantitative way of characterising surface topographical features and are closely related to tribological properties. In this paper, the correlation between surface topographic features and friction coefficient is investigated on the basis of the proposed improved correlation analysis model for high-speed milling surface topography of hardened steel. It was found that the friction coefficient could not be accurately reflected by a single parameter, so a prediction model for the friction coefficient based on Sxp, Sq, Sp, Sz, Sku and Sdq was developed. In this paper, the parameter screening was completed based on the changing characteristics of the data, and a multi-parameter prediction model of the friction coefficient in the stable wear stage was established, which provides a new idea to investigate the influence of the characteristics of surface topography on tribological performance.

The impact of fenugreek, black cumin, and garlic on dough rheology, bread quality, antimicrobial activity, and microstructural analysis using a scanning electron microscope

Fenugreek, black cumin, and garlic are herbs that are rich sources of antimicrobial and nutritional bioactive compounds. This study investigated the influence of herbs on the rheological characteristics of dough and the quality parameters of bread. The antimicrobial activity of the herbs was determined against the pathogens at 50 and 100 mg/mL concentrations. Maximum zone inhibition was measured for fenugreek against Salmonella typhimurium (16.5 mm) at 100 mg/mL concentration. Dough development time and departure time increased with the increase in concentration of the herbs. Farinograph quality number (FQN), mixing tolerance index, and stability varied significantly with the treatments such as physio-chemical, structural, textural, and sensory parameters at herbs con-centration 0.25, 0.5, and 0.75%, respectively. Ash, fiber, fat, protein content, firmness, and total phenolic content were increased with treatments. However, a decrease in moisture content and total plate count was observed due to the addition of herbs. The microstructure revealed that the addition of fenugreek significantly improves the bread structure. The sensory profile of bread was not affected with the addition of herbs at a concentration of 0.50%.

Sensory profile of cream cheese and plant‐based analogues: an approach through flash‐profile, CATA and RATA tests

SummaryThe distinct techno‐functional and sensory attributes conferred by milk proteins and fat are fundamental in defining the structure, texture and flavour of dairy products. Thus, reproducing cheese‐like characteristics in plant‐based alternatives while ensuring consumer acceptance is a major challenge. This study aimed to evaluate the sensory profile of commercial cream cheese and plant‐based analogues, quantifying consumer perception and discrimination, and correlating with instrumental texture analysis. For that, two milk‐based (MB1 and MB2) and three plant‐based products (PB1, PB2 and PB3) were evaluated for their proximate composition, texture profile (spreadability and firmness) and sensory properties by combining Flash Profile method (n = 13), Check‐All‐That‐Apply (CATA) test, and Rate‐all‐that‐apply (RATA) test (n = 102) with global acceptance. Milk‐based cream cheeses (MB1 and MB2) did not differ significantly from each other and presented greater spreadability when compared to all plant‐based cream cheeses (PB1, PB2 and PB3). The texture parameters of the samples were inversely related: the greater the firmness, the lower the spreadability. All forty‐two sensory attributes allowed discrimination of the samples into three distinct clusters, with no difference between the milk‐based products. The results of the CATA test showed that the attributes most correlated with the sample MB1 were the most desirable for good acceptance of the product. In turn, PB3 showed lower acceptance scores when compared to the plant‐based samples PB1 and PB2, and the attributes rancid flavour, vegetable oil aroma and nut aroma mostly contributed to the lower acceptance of PB3. Milk‐based products were very close to the ideal product, presenting a creamy and spreadable texture as key attributes for product characterisation and acceptance. The results of RATA test showed a significant difference (P &lt; 0.05) in the intensity of nineteen sensory attributes. Milk‐based cream cheeses were more accepted than their plant‐based counterparts. The instrumental assessments of firmness and spreadability exhibited a negative correlation, once they were inversely proportional and strongly correlated to sensory data of firm and spreadable texture, respectively. The sensory characteristics of cream cheese analogues may present a barrier to their acceptance by consumers. Attributes such as coconut and flour flavour, artificial cheese aroma and flavour, and spreadable texture played a key role in differentiating dairy products from plant‐based ones, contributing to the lower acceptance of the latter.

Impact of organic and conventional farming practices on the multidimensional characteristics of flour and indirectly on bread

The demand for organic and locally sourced products is on the rise. This study investigates the impact of farming practices (organic versus conventional) on the microbiological, microscopic, and physical-chemical properties of 'Caaveiro' flour, alongside the physical-chemical, instrumental texture parameters, and sensory attributes of breads, using two fermentation methods (sourdough versus mixed leavening). 'Caaveiro' flour and bread, recognized under the Protected Geographical Indication ‘Galician Bread’, were employed as a case study. Organic flours exhibited higher counts of aerobic plate microorganisms, yeasts, and molds, yet these levels posed no health risks. Overall, farming practices demonstrated negligible influence on the evaluated flour and bread characteristics. Instead, fermentation method emerged as the predominant factor shaping bread attributes. Consequently, promoting organic production could help maintain the distinctive qualities of traditional breads under Protected Geographical Indications.

Texture analysis based on CT for predicting the differentiation of esophageal squamous cancer: An observational study.

To explore the feasibility and application value of texture analysis based on computed tomography (CT) for predicting the differentiation of esophageal squamous cell carcinoma (ESCC). Patients diagnosed with ESCC who underwent chest contrast-enhanced CT before treatment were selected. Based on the pathological results, the patients were stratified into poorly differentiated and moderately well-differentiated groups. FireVoxel software was used to analyze the region of interest based on venous phase CT images. Texture parameters including the mean, median, standard deviation (SD), inhomogeneity, skewness, kurtosis, and entropy were obtained automatically. Differences in the texture parameters and their relationship with the degree of differentiation between the 2 groups were analyzed. The value of CT texture parameters in identifying poor differentiation and moderate-well differentiation of esophageal cancer was analyzed using the ROC curve. A total of 48 patients with ESCC were included, including 24 patients in the poorly differentiated group and 24 patients in the moderate-well-differentiated group. There were negative correlations between SD, inhomogeneity, entropy, and the degree of differentiation of esophageal cancer (P < .05). The correlation of inhomogeneity was the highest (r = -0.505, P < .001). SD, inhomogeneity, and entropy could effectively distinguish between the poorly and moderately well-differentiated groups, with statistically significant differences between the 2 groups (P < .05). The best critical values for SD, inhomogeneity, and entropy were 17.538, 0.017, and 3.917, respectively. The areas under the ROC curve were 0.793, 0.792, and 0.729, respectively, with the SD and inhomogeneity being the best. The application of texture analysis on venous phase CT images holds promise as a method for forecasting the degree of differentiation in esophageal cancers, which could significantly contribute to the preoperative noninvasive evaluation of tumor differentiation.

Relationship between consumer acceptance, sensory characteristics, and physicochemical characteristics of "Fuji" apples from different origins.

This study examines the acceptance of young Chinese consumers for different "Fuji" apples, focusing on their sensory characteristics and physicochemical foundations. The sensory attributes of the samples were evaluated using a combination of static descriptive analysis (DA) and temporal check-all-that-apply fading (TCATA-fading) methods. Furthermore, the volatile compounds, soluble sugars, organic acids, and textural parameters of the samples were analyzed. The findings revealed that participants favored apples that were perceived as "sweet," "crunchy," "juicy," and "aromatic." The results from the DA indicated that certain sensory attributes, such as "sweet," "vanilla," "honey," and "pear" positively influenced acceptance, while attributes like "sour," "hard," and "grass" had a negative impact. The findings from both the DA and TCATA-fading methods were consistent with each other. In terms of dynamic evaluation, sweetness, and sourness were the initial perceptions, followed by a range of other flavors. Notably, our data suggested that sweetness perception could be enhanced by attributes such as "honey" and "banana." Additionally, the sugar-acid ratio and specific volatile compounds, including hexanal, (E)-2-hexenal, β-damascenone, butyl acetate, and propyl 2-methylbutyrate, were found to influence the perception of sweetness in apples. PRACTICAL APPLICATION: This study helps to understand the effect of different origins on the acceptance of "Fuji" apples and to know the sensory and material basis for the emergence of such differences. It is beneficial for growers and marketers to improve 'Fuji' apples.

Insulin-Loaded Chitosan-Cellulose-Derivative Hydrogels: In Vitro Permeation of Hormone through Strat-M® Membrane and Rheological and Textural Analysis.

This work is part of the current research trend to develop a hydrogel carrier of insulin to promote wound healing. Topically applied insulin promotes keratinocyte proliferation and migration, increases collagen synthesis, reduces inflammation and oxidative stress, and exhibits antimicrobial activity. The aim of this study was to design an insulin hydrogel matrix based on selected cellulose derivatives (methylcellulose, hydroxyethylcellulose, and hydroxypropylmethylcellulose) and chitosan. Rheological parameters of the formulations were evaluated using rotational rheometry and an oscillation test. Textural tests were performed. In vitro pharmaceutical insulin availability studies were carried out using the innovative Strat-M® membrane to imitate the skin barrier. It was found that the pharmaceutical formulation of insulin based on chitosan and methylcellulose showed an acceptable balance between rheological and textural parameters and ease of application. The API was released from the carrier in a prolonged manner, eliminating the need to apply the formulation several times per day. The developed hydrogel shows potential for use in clinical practice.

Integration of texture analysis based on DCE-MRI Ktrans map and metabolomics of early bone marrow microvascular changes in alloxan-induced diabetic rabbits

ObjectiveTo evaluate early bone marrow microvascular changes in alloxan-induced diabetic rabbits using IDEAL-IQ fat quantification, texture analysis based on DCE-MRI Ktrans map, and metabolomics.Materials and methods24 male Japanese rabbits were randomly divided into diabetic (n = 12) and control (n = 12) groups. All rabbits underwent sagittal MRI of the lumbar vertebrae at the 0th,4th, 8th, 12th, and 16th week, respectively. The fat fraction (FF) ratio and quantitative permeability of the lumbar bone marrow was measured. Texture parameters were extracted from DCE-MRI Ktrans map. At 16th week, lumbar vertebrae 5 and 6 were used for histological analysis. Lumbar vertebra 7 was crushed to obtain bone marrow for metabolomics research.ResultsThe FF ratio and Ktrans of the lumbar bone marrow in diabetic group were increased significantly at 16th week (t = 2.226, P = 0.02; Z = -2.721, P < 0.01). Nine texture feature parameters based on DCE-MRI Ktrans map were significantly different between the groups at the 16th week (all P < 0.05). Pathway analysis showed that diabetic bone marrow microvascular changes were mainly related to linoleic acid metabolism. Differential metabolites were correlated with the number of adipocytes, FF ratio, and permeability parameters.ConclusionThe integration of metabolomics with texture analysis based on DCE-MRI Ktrans map may be used to evaluate diabetic bone marrow microvascular changes at an early stage. It remains to be validated in clinical studies whether the integration of metabolomics with texture analysis based on the DCE-MRI Ktrans map can effectively evaluate diabetic bone marrow.

Machine Learning to Differentiate Malignant and Non-malignant Pleural Effusion Findings

Introduction: This study developed a method using machine learning techniques to differentiate between malignant and non-malignant pleural effusions, analyzing texture parameters in computed tomography scans Method: The study involved forty-one patients, with their computed tomography examinations classified into three groups: True Positive - patients with both cytopathological analysis and pleural biopsy indicating malignancy; True Negative - patients with negative results in both tests; and False Negative - patients with negative cytopathological analysis but positive pleural biopsy results. Four machine learning methods were applied across three analyses: True Positive versus True Negative, True Positive versus False Negative, and True Negative versus False Negative. The logistic regression model demonstrated notable effectiveness, achieving an Area Under the Curve of 0.84 ± 0.02 in the True Positive versus True Negative analysis and 0.81 ± 0.05 in the True Positive versus False Negative comparison. In the True Negative versus False Negative analysis, the Naive Bayes model achieved an Area Under the Curve of 0.72 ± 0.02. Results: Statistically significant differences were observed in the liquid Lactate Dehydrogenase and protein content between the True Positive and True Negative groups (p-values of 0.0390 and 0.0249, respectively), and in the liquid pH level between the True Positive and False Negative groups (p-value of 0.0254). The use of textural features in combination with machine learning techniques provided a reliable classification for investigating suspected pleural effusion findings. This method represents a potential tool for assisting in clinical diagnosis and decision-making, enhancing the accuracy of pleural effusion assessments Conclusion: In conclusion, our approach not only improves diagnostic accuracy but also offers a faster and non-invasive alternative, significantly benefiting clinical decision-making and patient care.

PSIX-3 Dental stick extrusion utilizing spray dried plasma

Abstract Dental stick extrusion utilizes various ingredients to form the ideal texture and quality product. Alternative ingredients to enhance or impact texture, palatability and/or plaque removal can be useful to improve dental stick manufacturing. Spray dried plasma (SDP) is a consistent high protein ingredient commonly utilized in pet food for functional texture properties, enhancing palatability, and supporting overall health. Thus, the study objective was to evaluate how SDP inclusion with other ingredients impacts texture of extruded dental formulas. Three formulas were developed utilizing SDP to replace wheat starch (WS) or Arabic gum in the control formula. The formulas were: Control: WS and gum; SDP1: SDP and WS replacing gum; and SDP2: SDP replacing WS and gum. Dental sticks were made at the Extru-Tech technology testing center using a 525 single screw extruder with the product densification unit (PDU) removed and replaced with a mid-barrel valve and 3 cooling heads to cause densification. The sticks were manufactured as solid square sticks. Generally, a single screw with a PDU, or a traditional parallel-shaft twin screw is used to manufacture dental sticks. However, the equipment alterations used worked like a single screw with a PDU; thus, it would be expected that the results would translate to a traditional single screw configuration. Glycerin at 12% (% to dry feed rate) and chicken fat were added to the pre-conditioner at set rates to optimize expansion and product quality. Processing conditions were monitored and adjusted on the various formulations during production to optimize extrusion. Texture was measured on a TA.XT Plus utilizing an adjustable bridge with a rounded-end knife probe for a 3-point bend. Dental sticks of 8 cm in length were placed over the two bridge spans spaced 5 cm apart to measure maximum force (hardness) and work to peak force (work to break) to determine texture parameters. Ten dental sticks per treatment were analyzed. All formulas utilizing SDP were successful in producing dental sticks. No differences (P &amp;gt; 0.05) were noted in force with SDP formulas compared with control. Work to peak was greater (P &amp;lt; 0.05) in SDP formulas compared with control formula. Formulation matrix impacts results. In the current formulas, both Arabic gum and WS were altered in the formulas and depending on amount of SDP used similar texture was noted. In conclusion, SDP can be incorporated into dental stick formulas and utilized as a processing aide. Overall, depending on target hardness and ingredient matrix, SDP can be an alternative to various ingredients to maintain or improve product quality.

Quantifying rheology and texture of chocolate products with oleogels using fractional calculus

Oleogels, a novel technology for structuring fats, show great potential for partially or completely replacing solid fats in chocolate products containing unhealthy saturated fatty acids. However, how to maintain similar rheological properties and sensory texture attributes is a major challenge. Given the lack of a concise and effective mathematical framework, simulating the rheological response and quantifying the textural parameters of the hybrid oleogel-dispersed chocolate products, is complicated. In this work, the rheological power law behavior of hybrid oleogel-dispersed chocolate products is accurately captured by using a fractional constitutive mathematical framework with few constitutive parameters. The sensory texture parameter firmness is quantified on the basis of creep response. The rheological response and firmness index are linked together on the basis of the fractional derivative model. This work helps provide heuristic insights into the structure-texture engineering of this food type. Such insights may, in turn, guide the formulation and design of food products.

Image texture analysis of pellets made of lignocellulosic materials

This experiment aimed to find the relation between image texture features of pellets made of various lignocellulosic materials (wood, wheat straw, hay, giant miscanthus, prairie spartina, and giant knotweed) and their physico-mechanical properties (density, compressive energy, maximum compressive strength, modulus of elasticity). Using the Kruskal-Wallis's test, the effect of materials on these properties was examined. Texture features were derived from the grey-level co-occurrence matrix, grey-level run-length matrix, absolute gradient matrix, autoregressive model, and wavelet decomposition, resulting in 86 features, later reduced to 8 factors via explanatory factor analysis. These factors were used as predictors in regression models for physico-mechanical properties. The models for modulus of elasticity achieved R2adj values of 0.91–0.99 (except for hay and wood), compressive stress models achieved 0.65–0.99 (excluding hay and wood), compressive energy models ranged from 0.60 to 0.97 (excluding hay), and density models ranged from 0.56 to 0.97 (excluding wood). The study confirmed a significant correlation between material type, texture parameters and compression resistance, suggesting this method could monitor pellet quality in production.

Supervised learning-based artificial senses for non-destructive fish quality classification

Human sensory techniques are inadequate for automating fish quality monitoring and maintaining controlled storage conditions throughout the supply chain. The dynamic monitoring of a single quality index cannot anticipate explicit freshness losses, which remarkably drops consumer acceptability. For the first time, a complete artificial sensory system is designed for the early detection of fish quality prediction. At non-isothermal storages, the rainbow trout quality is monitored by the gas sensors, texturometer, pH meter, camera, and TVB-N analysis. After data preprocessing, correlation analysis identifies the key parameters such as trimethylamine, ammonia, carbon dioxide, hardness, and adhesiveness to input into a back-propagation neural network. Using gas and textural key parameters, around 99 % prediction accuracy is achieved, precisely classifying fresh and spoiled classes. The regression analysis identifies a few gaps due to fewer datasets for model training, which can be reduced using few-shot learning techniques in the future. However, the multiparametric fusion of texture with gases enables early freshness loss detection and shows the capacity to automate the food supply chain completely.

Influence of surface texture on pocket pairs lubrication performance of cylindrical roller bearings

PurposeThis paper aims to reveal the influence of the grooved texture parameters on the lubrication performance of circular pocket-roller pairs in cylindrical roller bearings.Design/methodology/approachIn this paper, the thermal elastohydrodynamic lubrication mathematical model of the grooved texture circular pocket-roller pair was established, the finite difference method and successive over-relaxation method were used to solve the model, the influence of texture quantity, texture depth and texture area ratio on circumferential bearing capacity, friction coefficient, maximum temperature rise, stiffness and damping of the circular pocket-roller pairs were analyzed.FindingsThe results show that texture quantity, texture depth and texture area ratio significantly influence the static and dynamic characteristics of circular pocket-roller pairs. The suitable surface groove texture parameters can dramatically improve the circumferential bearing capacity, reduce the friction coefficient, inhibit the maximum temperature rise and increase the stiffness and damping of the circular pocket-roller pairs.Originality/valueThe research in this paper can provide a theoretical basis for the optimization design of pockets in cylindrical roller bearings to reduce friction and vibration.

Fine evaluation of surface integrity of hardened 1.4418 stainless steel after finish dry turning

1.4418 hardened stainless steel (SS) is widely used in mechanical engineering because of its high functional properties. They can also be enhanced by procuring improvements in the state of the surface layer (SL) and, above all, in the factors of its strengthening, among others the average size of coherent scattering regions (ASCSR), dislocation density (DD), residual stresses (RS) of first and second orders, and relative micro-deformations of the crystal lattice (RMCL). This study investigates the effect of cutting speed (vc) ranging from 100 to 250 m/min and feed rate (f) ranging from 0.005 to 0.25 mm/rev on the indicators of SL condition after finish turning the steel tested. A reduction in ASCSR values below 8 nm was obtained for vc = 100–135 m/min, while an increase of ~ 20% was obtained for 180–250 m/min and with the f ranging from 0.2 to 0.25 mm/rev. An increase in RMCL of ~ 90% was registered for vc = 170–230 m/min and f = 0.2–0.25 mm/rev. A decrease in DD below 109 cm−2 was obtained for vc = 180–250 m/min and its ~ 25% increase for vc = 100–135 m/min. A high correlation between ASCSR and DD was shown. In the deformed material, the dislocation’s resistance to motion increases in proportion to the increase in its density. A high linear correlation coefficient in the range of 0.8–0.9 is found between ASCSR, DD, and first-order RS on the one hand, and Sa and Sz surface texture parameters, which are used in the industry to assess product quality, on the other. Additionally, the effect of plastic side flow (PSF) was observed and described. When machining with vc = 119 m/min and f = 0.22 mm/rev, the intense plastic deformation of the material causes outflow and shearing of the surface micro-hills. Favorable compressive stresses (below − 100 MPa) were registered in the range of vc = 225–250 m/min at f = 0.005–0.05 m/rev and 0.2–0.25 mm/rev, as well as vc = 115–180 m/min and f = 0.05–0.17 mm/rev. The study proved the existence of a relationship between the cutting parameters and indicators of the thin crystalline structure of SL. This means that by proper controlling of these parameters, it is possible to obtain such a state of the SL workpiece, which will ensure its long-term use.

Development and Application of the Quality Index Method for Ice-Stored King Weakfish (Macrodon ancylodon).

The freshness of raw fish has become one of the industry's and consumers' main concerns regarding quality, safety, and shelf-life estimation. To determine the freshness of the king weakfish (Macrodom ancylodom), the quality index method (QIM) was employed for sensory analyses, along with the assessment of proximate composition, pH, total volatile bases (TVB-N), thiobarbituric acid reactive substances (TBARS), biogenic amines, fatty acids, texture, and microbiological parameters. The results show that the QIM obtained over the storage period exhibited a linear increase, ranging from 2 to 21 demerit points, with a high correlation (R2 = 0.9868) among the data. The microbiological results indicated an increase in the counts of psychrotrophic and mesophilic bacteria throughout the storage period. TVB-N values ranged from 11 to 28 mg/100 g, and TBARS values ranged from 0.235 to 0.298 mg MDA/kg when stored in ice. The presence of putrescine, cadaverine, spermidine, and toxic volatile compounds was a potential indicator of fish freshness. Based on the correlation between the methods considered indicators of freshness and quality, it can be concluded that the king weakfish maintains its commercial stability for up to 11 days when stored in ice.

Utilization and Effect of Apple Pomace Powder on Quality Characteristics of Turkey Sausages.

The present study was conducted to develop turkey sausages by incorporating freeze-dried apple pomace (FDAP) at 3, 5, and 8% by replacing turkey breast meat. Three sausage formulations and the control of turkey sausages were subjected to physicochemical properties: proximate content, water-holding capacity (WHC), cooking yield, pH, color, textural parameters, antioxidant activity, and microbiological and sensory properties. The parameters were analyzed during storage from days 0 to 7. The addition of FDAP to turkey sausages resulted in a significant (p ≤ 0.05) decrease in moisture and protein contents, whereas no significant difference was found in fat and ash contents. The increased incorporation of FDAP resulted in decreased pH, cooking loss, lightness, redness, and yellowness in turkey sausages, whereas an increase in total phenolic content, fiber content, ABTS, and DPPH values was observed. FDAP, as a low-cost source of valuable phenolic content, strongly inhibited microorganism growth during the storage of turkey sausages. The sensory scores of turkey sausages containing 3% FDAP for other sensory traits, such as flavor, texture, juiciness, tenderness, and overall acceptability, were comparable to those of the control. Scores for sensory attributes declined significantly with a further increase in FDAP in turkey sausages. It is concluded that turkey sausages with very good acceptability can be prepared by incorporating freeze-dried apple pomace each at a 3% level.