Search

Copyright of Materiały Budowlane is the property of Wydawnictwo SIGMA-NOT and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Water-lubricated rubber bearings are a critical component of the propulsion systems in underwater vehicles. Particularly under conditions of low speed and high load, friction-induced vibration and wear often occur. Surface texturing technology has been proven to improve lubrication performance and reduce friction and wear; however, research on how different texture parameters affect friction-induced vibration and wear mechanisms remains insufficient. In this study, various texture patterns with different area ratios and aspect ratios were designed on the surface of water-lubricated rubber bearings. By combining these designs with an in situ observation system based on computer vision technology, the effects of texture parameters on bearing friction, vibration, and wear were thoroughly investigated. The experimental results show that surface textures play a critical role in improving hydrodynamic effects and stabilizing the lubrication film at the friction interface. Specifically, textures with a high area ratio (15%) and aspect ratio (3:1) exhibited the best vibration suppression effect, primarily due to the reduction in actual contact area. However, excessively high area ratios may lead to increased surface wear. This study concludes that a reasonable selection of texture area and aspect ratios can significantly reduce frictional force fluctuations and vibration amplitude, minimize surface wear, and extend bearing life. [ABSTRACT FROM AUTHOR]

CoCrMo alloys are often used in the manufacture of artificial joints in the medical field, and their special working environment will lead to corrosion and abrasion of the surface materials, thus reducing the service life of the joints. Surface texturing technology can improve the friction performance of joints by reducing the friction area, storing abrasive particles and lubricants, etc. Its application in the field of CoCrMo alloy joint surface strengthening is of great significance. This paper analyses the characteristics of surface fabrication processing technology and the friction reduction mechanism of surface fabrication under fluid lubrication and dry friction conditions, summarizes the influence of various fabrication parameters (fabrication depth, size, density, shape, etc.) on the friction performance of the alloy, introduces other surface technologies of CoCrMo alloy as well as common medical materials, summarizes the existing problems in the research of CoCrMo alloy surface reinforcement technology at this stage and makes a study on the development direction of the surface reinforcement technology of CoCrMo alloy in the field of artificial joints. The development direction of CoCrMo alloy in the field of artificial joints is also prospected. [ABSTRACT FROM AUTHOR]

One of the most crucial factors in determining the consumer acceptability of processed or non-processed food products is their textural characteristics. Textural properties of food items can be created during processing by different techniques, one of which is drying. Drying which is one of the most widely used preservation methods of food products can extend their shelf life and generate unique sensory characteristics. The complicated process of drying is characterized by massive deformations while simultaneously transferring heat and moisture. Texture parameters of the dried food products vary depending on the type of dried food product (fruit and vegetables, grain and cereals, meat and marine), including the final volume, porosity, crust formation, and bulk density. Thus, this review focused on the examination of the textural characteristics of dried food items, the impact of the drying process, and the applied method on textural parameters. This study has also investigated the importance of pretreatment methods in improving the textural properties and quality of dried products. Furthermore, this review also considers the importance of modeling for texture prediction, discussing the different modeling approaches and their principles and applications. Recent applied nondestructive methods for textural analysis have been discussed in terms of application and performance. [ABSTRACT FROM AUTHOR]

Copyright of Modern Food Science & Technology is the property of Editorial Office of Modern Food Science & Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Leaf Area Index (LAI) remains one of the most important forest structural attributes, as accurate estimation of LAI is crucial for predicting the growth of different species. Using the Partial Least Squares Regression (PLS-R) algorithm, this study investigated three image processing techniques to determine the best technique for estimating LAI using WorldView-3 imagery in the Midlands, KwaZulu-Natal province of South Africa. The PLS-R texture ratios model achieved the highest accuracy of R2 = 0.70, RMSE = 1.21 (2.32% of the mean measured LAI) and R2 = 0.72, RMSE = 1.26 (2.41% of the mean measured LAI) for the wet and dry seasons, respectively. This was followed by the PLS-R single texture band model that produced an accuracy of R2 = 0.65, RMSE = 1.35 (2.58% of the mean measured LAI) and R2 = 0.67, RMSE = 1.32 (2.52% of the mean measured LAI) for the wet and dry seasons, respectively. The PLS-R model using a combination of vegetation indices had the lowest estimation accuracy of R2 = 0.59, RMSE = 1.38 (2.64% of the mean measured LAI) and R2 = 0.60, RMSE = 1.40 (2.67% of the mean measured LAI) for the wet and dry seasons, respectively. The results of this study provided evidence that image texture ratios can be used to estimate LAI effectively. [ABSTRACT FROM AUTHOR]

In order to study the effects of the distribution,number,density,placement angle and depth of different shapes of texture on the bearing performance of the misaligned gas foil thrust bearing,the Reynolds equation for the gas foil thrust bearing was solved by combining Successive Over Relaxation (SOR) and the finite difference method (FDM), and the load carrying capacity and frictional moment of the bearing were obtained by MatLab simulation under different texture parameters.The results show that the bearing load carrying capacity is significantly increased when the texture is distributed at the junction of the base area and the wedge area of the thrust bearing compared to other distribution methods. The load carrying capacity and frictional moment of the bearing increase first and then decrease with the increase of the proportion of micro-texture.The bearing performance is best improved when the maximum cross section of different shaped texture is placed along the radial direction of the thrust bearing. The micro-texture can improve the bearing performance only when its depth reaches a certain range.It is found that there exists optimal number, density,and depth of micro-textures that can make the thrust bearing have a higher bearing load capacity at a smaller friction torque. Compared to the bearings without texture, the elliptical micro texture with optimal micro-texture parameters can increase the load carrying capacity by 41.22% and reduce the friction torque by 0.81%. [ABSTRACT FROM AUTHOR]

This study aims to explore the changing trends in external characteristics of passion fruit pericarp and their application in predicting shelf-life, assessing storage quality, and advancing the field of non-destructive testing. Through storage experiments, the evolving patterns of passion fruit pericarp during storage and correlations among relevant physical parameters were analyzed. Three attribute parameters, namely minor-axis diameter, hardness, and mass, were extracted from the characteristic parameters of passion fruit, exhibiting the strongest interrelationships with storage time variable. The findings indicate a negative correlation between storage duration and minor-axis diameter of passion fruit, while no correlation was observed with major-axis diameter. The pericarp's contraction behavior is influenced by both thickness reduction and internal collapse. Moreover, a linear correlation existed between hardness of pericarp layers. The minor-axis diameter was positively correlated with puncture force at two peak positions (R = 0.87, P < 0.01; R = 0.95, P < 0.01). Simultaneously, minor-axis positively correlated with thickness and mass (R = 0.97, P < 0.01; R = 0.98, P < 0.01). To better quantify the degree of pericarp change, a passion fruit pericarp change index was proposed. Using the index as an independent variable and storage duration as the dependent variable, an equivalent fruit age prediction model was established. The results show a coefficient of determination (R2) of 0.997 and a significance level of P < 0.05 between predicted and actual values. This research has the potential to provide a theoretical foundation and methodological framework for predicting passion fruit shelf-life in the context of food preservation and storage, and to offer practical support for real-world applications in the field. [ABSTRACT FROM AUTHOR]

This study aimed to formulate flour blends from modified cassava flour (MCF) and suweg flour (SF) and use them to produce gluten-free steamed brownies (GFSB) with desirable qualities. The blends varied in the proportions of MCF and SF by weight, namely 80:20 (F1), 70:30 (F2), and 60:40 (F3). Wheat flour-based steamed brownies (WFSB) served as the control. The results showed that the MCF to SF ratio significantly influenced various parameters of flour blends, such as chemical compositions, color characteristics, pasting, and functional properties. Higher SF content in the blend decreased peak viscosity, breakdown, and setback. Water absorption capacity also decreased as the MCF to SF ratio in the flour blend increased. The color of flour blends with an increasing proportion of SF was getting darker and more different from the color of wheat flour. GFSB exhibited lower volume expansion than WFSB. Increasing SF content in the flour blend increased the texture parameters of GFSB including hardness, cohesiveness, gumminess, and chewiness. Values of color difference, representing color variation between gluten-free and control brownies, ranged from 2.30 to 6.32, where the GFSB-F1 was more similar in color to WFSB. Preference levels for color, aroma, and texture of GFSB did not significantly differ from WFSB. However, GFSB-F2 was preferred in taste and overall acceptance over WFSB. The utilization of modified cassava flour and suweg flour blends in gluten-free steamed brownies offers a promising avenue for diversifying gluten-free baking options. [ABSTRACT FROM AUTHOR]

The effects of the supplier and the mass of pork thighs together with some production parameters including mass loss during ham production, mass of the final products and relative content of non-protein nitrogen (NPN) on the texture profile of Slovenian dry-cured ham -- Kraški pršut were investigated to determine its optimal texture. The study included 32 dry-cured hams from two mass classes (heavy with thigh mass at salting of 11.7-12.1 kg and light with thigh mass at salting of 10.5-10.7 kg) and two different pork thigh suppliers from regular production. Slices cut transversally from the thigh at approximately 8 cm from the femur head were used for physicochemical parameter (pH, contents of moisture, total fat, protein, NaCl, and NPN) analysis, instrumental texture analysis profile analysis (TPA), and sensory analysis. Pork thigh mass had a significant effect on the TPA parameters; light samples were harder, chewier, springier, more cohesive and resilient compared to the heavy samples. NaCl content and sensory scores for saltiness were higher in the light Kraški pršut samples than in the heavy ones. Based on the median for hardness in the sensory analysis, the samples were classified into three ranks of texture using linear discriminant analysis (9 variables, 100% correct classification): optimal (median 4.0; 19% of samples), slightly too soft (median 3.5, 72% of samples), and soft (median 3.0; 9% of samples). Kraški pršut mass and hardness were significantly correlated to saltiness, pastiness, aroma, and all TPA parameters (p≤0.05). Positive correlation (p≤0.05) was also observed between NPN and pastiness. These findings indicate the importance of supplier, mass of pork thighs, and production parameters for optimizing the texture of Kraški pršut. [ABSTRACT FROM AUTHOR]

To solve the problem of premature failure of the rubber stator of the screw pump due to wear, reduce the frictional resistance torque of the screw pump to solve the problem of difficulty in starting after the shutdown of the screw pump production system in Daqing Oilfield. The effects of micron dot texture and lubricating medium on the tribological properties of 42CrMo metal and acrylonitrile–butadiene rubber mating surfaces were studied by theoretical analysis and tribological tests. The friction coefficient, wear amount, and rubber wear morphology were used as the measurement indexes of drag reduction, wear resistance, and wear degree, respectively. The results showed that the best combination of texture area ratio and the lubricating medium was 10% silicone grease, the friction coefficient and wear amount were reduced by 11% and 10.7%, respectively, compared with untextured, and the main order of chip storage and oil supply effect was 10% > 5% > 15%. [ABSTRACT FROM AUTHOR]

Nowadays, Functional food products as healthy diets have been considered extensively among consumers. Moreover, the use of particular microorganisms, for instance probiotic bacteria, offers probabilities to progress novel foods with appropriate shelf life. In the current research, in order to produce a functional ultrafiltrated (UF)-cheese, demineralized UF-whey powder (DUWP) at the levels of 0, 1 and 2%, and lactulose powder at the levels of 0 and 1% were used. Furthermore, bifidobacterium bifidum was used as probiotic bacteria. The textural characteristics in terms of hardness, cohesiveness, adhesiveness, springiness, gumminess and chewiness and sensorial propertis of the symbiotic cheese samples including odor, color, texture and taste were evaluated during 60 days of storage period at 4 ◦C. Results showed that addition of DUWP and lactulose powders except for adhesiveness and springiness caused significant decrease in all textural parameters (P<0.001). Besides, except for adhesiveness and cohesiveness, the mean values of textural parameters usually enhanced up to middle of the storage time and thereafter decreased up to end of storage period (p<0.05). Sensory results revealed that although addition of both DUWP and lactulose powders resulted in lower sensory scores, no significant differences were found between control (without DUWP and lactulose) and sample containing 1% of each both mentioned powders (P>0.05). Therefore, based on the obtained results, sample having 1% of DUWP and 1% of lactulose determined as the best symbiotic UF-cheese sample. Since the potential contribution of this product in community health promotion and reduction of diseases risk, the production and consumption of this functional cheese is proposed. [ABSTRACT FROM AUTHOR]

Lacto‐fermented foods may have health benefits. Therefore, the consumption of lacto‐fermented fruit and vegetables is important. The objective of this study was to assess the effect of lacto‐fermentation on zucchini flesh after 1 week and 3 months. The zucchini slices were classified using models built based on image textures using different machine learning algorithms. The developed models were characterized by overall accuracies of up to 99.33% for a combined set of textures selected from images in color channels R, G, B, L, a, b, X, Y, and Z (IBk algorithm). Only fresh zucchini slices were correctly classified with an accuracy of 100% and Precision, F‐Measure, Matthews Correlation Coefficient (MCC), Receiver Operating Characteristic (ROC) Area, and Precision‐Recall (PRC) Area of 1.000 for selected models. The greater changes in the zucchini flesh structure were observed after the first week of lacto‐fermentation compared to the fresh slices than between samples lacto‐fermented for 1 week and 3 months. Practical Applications: The obtained results confirmed that the developed procedure combining image analysis and machine learning can be used for the quality assessment of the lacto‐fermented zucchini and the detection of the optimal period to obtain desired changes. The determination of changes in product quality as a result of lengthening the lacto‐fermentation time can be useful for detecting the optimal period of the process. [ABSTRACT FROM AUTHOR]

Cyst nematodes are plant parasitic nematodes infecting crops, causing extensive crop damage and annual losses, and affecting food production. The precise species identification is significant to initiate their control. The repeatable, less expensive, and less laborious distinguishing cyst nematode species using image processing and artificial intelligence can be advantageous. The objective of this study was to distinguish cyst nematodes belonging to the species Globodera pallida, Globodera rostochiensis, and Heterodera schachtii based on image parameters using artificial neural networks (ANN). The application of parameters selected from a set of 2172 textures of images in color channels L, a, b, X, Y, Z, R, G, B, V, U, and S to build classification models using a narrow neural network, medium neural network, wide neural network, trilayered neural network, WiSARD, multilayer perceptron, and RBF network is a great novelty of the present study. Algorithms allowed for distinguishing cyst nematode species with an average accuracy reaching 89.67% for a model developed using WiSARD. The highest correctness was obtained for H. schachtii and this species was distinguished from each other with the highest accuracy of 95–98% depending on the classifier. Whereas the highest number of misclassified cases occurred between G. pallida, G. rostochiensis belonging to the same genus Globodera. The developed procedure involving image parameters and artificial neural networks can be useful for non-destructive and objective distinguishing cyst nematode species. [ABSTRACT FROM AUTHOR]

Black rockfish (Sebastes schlegelii) is a demersal economic species widely distributed in China's coastal regions. In order to determine the differences between wild (wild group) and recirculating aquaculture system (RAS)-farmed (RAS group) black rockfish, several parameters affecting quality were evaluated, such as proximal, texture, amino acids, fatty acids, muscle cellularity, and the expression of muscle growth-related genes. The results showed that the crude lipid, amino acids, polyunsaturated fatty acids (PUFA), and monosaturated fatty acids (MUFA) contents of RAS group were significantly higher (P < 0.05) than of wild group. Hardness, springiness, chewiness, muscle fiber diameter, cross-sectional area, crude protein, eicosapentaenoic acid (EPA), and docosahexaenoic acid (DHA) contents of wild group were significantly higher than of RAS group (P < 0.05). The muscle fiber density showed a positive and significant correlation with hardness, gumminess, springiness, and chewiness, whereas muscle fiber diameter showed a negative correlation. Expression of muscle growth-related genes including myogenic differentiation antigen (MyoD) and myosin heavy chain (MYH) in wild group was significantly higher than in RAS group. Moreover, MyoD and MYH expression was positively correlated with both muscle fiber density and cross-sectional area, and negatively correlated with fiber diameter, which could be a useful indicator for predicting flesh textural properties. It can be concluded that the exogenous and endogenous factors may determine variations of nutrient composition, flesh quality parameters, and muscle growth patterns of wild and RAS-farmed black rockfish. [ABSTRACT FROM AUTHOR]

Monitoring and identifying the freshness levels of meat holds significant importance in the field of food safety as it directly relates to human dietary safety. Traditional packaging methods for lamb meat quality assessment present issues such as cumbersome operations and irreversible damage. This research proposes a quality assessment method for modified atmosphere packaging lamb meat using near-infrared spectroscopy and multi-parameter fusion. Fresh lamb meat quality is taken as the research subject, comparing various physicochemical indicators and near-infrared spectroscopic information under different temperatures (4 °C and 10 °C) and different modified atmosphere packaging combinations. Through precision parameter comparison, rebound and TVB-N values are selected as the modeling parameters. Six spectral preprocessing methods (multi-scatter calibration, MSC; standard normal variate transformation, SNV; normalization; Savitzky–Golay smoothing, SG; Savitzky–Golay 1 derivative, SG-1st; and Savitzky–Golay 2 derivative, SG-2nd), and three feature wavelength selection methods (competitive adaptive reweighted sampling, CARS; successive projections algorithm, SPA; and uninformative variable elimination, UVE) are compared. Partial least squares (PLS) and support vector machine (SVM) are used to construct prediction models for chilled fresh lamb meat quality. The results show that when rebound is used as a parameter, the SG-2nd-SPA-PLSR model has the highest accuracy, with a determination coefficient R2p of 0.94 for the prediction set. When TVB-N is used as a parameter, the MSC-UVE-SVM model has the highest accuracy, with an R2p of 0.95 for the prediction set. In conclusion, the use of near-infrared spectroscopic analysis enables rapid and non-destructive prediction and evaluation of lamb meat freshness, including its textural characteristics and TVB-N content under different modified atmosphere packaging. This study provides a theoretical basis and technical support for further encapsulating the models into portable devices and developing portable near-infrared spectrometers to rapidly determine lamb meat freshness. [ABSTRACT FROM AUTHOR]

Different cultivars of seeds may have different properties. Therefore, distinguishing cultivars may be important for seed processing and product quality. This study was aimed at revealing the usefulness of innovative models developed based on selected image textures built using traditional machine algorithms for cultivar classification of quince seeds. The quince seeds belonging to four cultivars 'Uspiech', 'Leskovac', 'Bereczki', and 'Kaszczenko' were considered. In total, 1629 image textures from different color channels for each seed were extracted from color images acquired using a flatbed scanner. Texture parameters were used to build models for a combined set of selected textures from all color channels, sets of selected textures from color spaces RGB, Lab, and XYZ, and individual color channels R, G, B, L, a, b, X, Y, and Z using algorithms from different groups. The most successful models were developed using the Logistic (group of Functions), IBk (Lazy), LogitBoost (Meta), LMT (Trees), and naïve Bayes (Bayes). The classification accuracy reached 98.75% in the case of a model based on a combined set of textures selected from images in all color channels developed using the Logistic algorithm. For most models, the greatest misclassification of cases was observed between seeds 'Bereczki' and 'Kaszczenko'. The developed procedure can be used in practice to distinguish quince seeds in terms of a cultivar and avoid mixing seed cultivars with different properties intended for further processing. [ABSTRACT FROM AUTHOR]

The objective of this study was to evaluate the differences in texture parameters between freeze-dried and fresh carrot slices using image processing and artificial intelligence. Images of fresh and freeze-dried carrot slices were acquired using a digital camera. Texture parameters were extracted from slice images converted to individual color channels L, a, b, R, G, B, X, Y, and Z. A total of 1629 texture parameters, 181 for each of these color channels, were obtained. Models for the classification of freeze-dried and fresh carrot slices were created using various machine learning algorithms, based on attributes selected from a combined set of textures extracted from images in all color channels (L, a, b, R, G, B, X, Y, and Z). Using three different feature selection methods (Genetic Search, Ranker, and Best First), the 20 most effective texture parameters were determined for each method. The models with the highest classification accuracy obtained by applying various machine learning algorithms from Trees, Rules, Meta, Lazy, and Functions groups were determined. The classification successes obtained with the parameters selected from all three different feature selection algorithms were compared. Random Forest, Multi-class Classifier, Logistic and SMO machine learning algorithms achieved 100% accuracy in the classification performed with texture features obtained by each feature selection algorithm. [ABSTRACT FROM AUTHOR]

Buckwheat hulls which are rich in fiber are good ingredients to increase the nutritional value of food products. The aim of this study was to determine the effect of the applied additives in the form of fiber and apple juice on the properties of both potato and corn starch (normal and waxy). In order to characterize the rheological properties of kissel, the pasting characteristic was measured. In the obtained gels, the basic quality parameters were determined. The analysis of texture, color parameters, and also total polyphenol content were determined. Buckwheat hulls, in addition to their high fiber content, are a valuable source of phenolic compounds and can be a great additive in starch desserts. The addition of buckwheat hulls and apple juice improved the nutritional value of the final products but also caused changes in the technological qualities: it increased the initial temperature of potato starch mixtures (by approx. 9 °C); it decreased the viscosity of cold desserts (from 8 to 55%); and increased the hardness of the final product by more than 7 times. In the case of other starches, the recorded changes were much smaller than for potato starch-based products. [ABSTRACT FROM AUTHOR]

By researching the influence of micro-groove texture on the surface tribological properties of the stator and rotor pair of oil production hydraulic motors, this paper aims to reduce the frictional resistance moment of the spiral pair of hydraulic motors, and further solve the problem of the difficult restart of the pump of a certain type of hydraulic-driven screw pump. According to the spiral pair of screw motors, a metal-rubber flat plate reciprocating friction model is established, and rectangular micro-grooves with different texture angles and depths are machined on the surface of the metal specimen. A combination of finite element simulation and tribological tests is used to carry out a study on the influence of different texture parameters on the friction performance of the hydraulic motor spiral pair. The results showed that at a certain texture angle, the friction coefficient of each specimen basically increases with the texture depth. When the texture depth is constant, the friction coefficient increases first and then decreases with the increase of the texture angle. The texture angle is the main factor affecting the friction coefficient. Under the same test conditions, the friction coefficient of the textured specimen can be reduced by 20.2% compared with the untextured specimen. In the metal-rubber contact pair of the stator and rotor of the hydraulic motor, the friction reduction mechanism of the texture mainly transport the lubricating medium through the micro-grooves to improve the lubricating conditions. Samples with a reasonable design of texture parameters can effectively reduce the friction coefficient of the friction pair without reducing the service life of the hydraulic motor, which is conducive to the smooth restart of the oil production system of the hydraulically driven screw pump. [ABSTRACT FROM AUTHOR]

Copyright of Proceedings of the YSU B: Chemical & Biological Sciences / Gitakan Teghekagir. K'imia, Kensabanut'yun is the property of Publishing House of Yerevan State University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Currently, the computer vision area, which represents one of the subfields of artificial intelligence and machine learning, has been widely used to process data in the oil and gas industry. In this context, the detection of specific properties inside carbonate rocks in different datasets from petroleum reservoirs represents a considerable challenge, that consumes enormous resources and time. Therefore, the automatic separation of the lithologies within rocks of reservoirs has attracted the increasing attention of many research groups. The consistent classification of these lithologies is the main factor for the construction of reliable depositional, diagenetic, and reservoir models. This work deals with this last issue by presenting the development of a technique for the automatic classification of carbonate thin sections obtained from plane-polarized and cross-polarized microscopy images corresponding to natural rocks belonging to the Brazilian pre-salt reservoir. Our proposed model transforms the analyzed images into structured data by defining texture parameters (Haralick parameters), and Wavelets transforms. Later, a stacked autoencoder neural network is used to eliminate images with anomalies and/or distortions in order to define relevant characteristics of the data. This stage is followed by supervised classifier called multilayer feed-forward neural network. The definition of the model's hyperparameters is tuned by Bayesian optimization and the Gaussian process. For training and testing of the network, images of 570 thin sections were used (each image obtained with plane-polarized and cross-polarized light) totaling 1140 images. Our model reported an accuracy of 83% for the test samples, confirming the validity of the proposed model in the automatic classification of carbonate rocks. [ABSTRACT FROM AUTHOR]

The objective of this study was to assess the influence of storage under different storage conditions on black currant quality in a non-destructive and inexpensive manner using image processing and artificial intelligence. Black currants were stored at a room temperature of 20 ± 1 °C and a temperature of 3 °C (refrigerator). The images of black currants directly after harvest and fruit stored for one and two weeks were obtained using a digital camera. Then, texture parameters were computed from the images converted to color channels R (red), G (green), B (blue), L (lightness component from black to white), a (green for negative and red for positive values), b (blue for negative and yellow for positive values), X (component with color information), Y (lightness), and Z (component with color information). Models for the classification of black currants were built using various machine learning algorithms based on selected textures for RGB, Lab, and XYZ color spaces. Models built using the IBk, multilayer perceptron, and multiclass classifier for textures from RGB color space, and the IBk algorithm for textures from Lab color space distinguished unstored black currants and samples stored in the room for one and two weeks with an average accuracy of 100%, and the kappa statistic and weighted averages of precision, recall, Matthews correlation coefficient (MCC), receiver operating characteristic (ROC) area, and precision–recall (PRC) area equal to 1.000. This indicated a very distinct change in the external structure of the fruit after the first week and more and more visible changes in quality with increasing storage time. A classification accuracy reaching 98.67% (multilayer perceptron, Lab color space) for the samples stored in the refrigerator may indicate smaller quality changes caused by storage at a low temperature. The approach combining image textures and artificial intelligence turned out to be promising to monitor the quality changes in black currants during storage. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Chinese Institute of Food Science & Technology / Zhongguo Shipin Xuebao is the property of Journal of Chinese Institute of Food Science & Technology Periodical Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Food processing allows for maintaining the quality of perishable products and extending their shelf life. Nondestructive procedures combining image analysis and machine learning can be used to control the quality of processed foods. This study was aimed at developing an innovative approach to distinguishing fresh and lacto-fermented red bell pepper samples involving selected image textures and machine learning algorithms. Before processing, the pieces of fresh pepper and samples subjected to spontaneous lacto-fermentation were imaged using a digital camera. The texture parameters were extracted from images converted to different color channels L, a, b, R, G, B, X, Y, and Z. The textures after selection were used to build models for the classification of fresh and lacto-fermented samples using algorithms from the groups of Lazy, Functions, Trees, Bayes, Meta, and Rules. The highest average accuracy of classification reached 99% for the models developed based on sets of selected textures for color space Lab using the IBk (instance-based K-nearest learner) algorithm from the group of Lazy, color space RGB using SMO (sequential minimal optimization) from Functions, and color space XYZ and color channel X using IBk (Lazy) and SMO (Functions). The results confirmed the differences in image features of fresh and lacto-fermented red bell pepper and revealed the effectiveness of models built based on textures using machine learning algorithms for the evaluation of the changes in the pepper flesh structure caused by processing. [ABSTRACT FROM AUTHOR]

Purpose: This study aims to solve the premature failure of the rubber stator due to wear, reduce the frictional resistance moment of the screw pump to solve the problem of a model of Daqing oilfield screw pump oil recovery system shutdown after the difficult start. Design/methodology/approach: For the first time, the rotor surface of a screw pump was treated with dot-matrix texture to study the effect of dot matrix texture on the tribological performance of the stator-rotor friction subsets of screw pump. Reciprocating friction tests with different texture morphologies (S-shape, double tongue) and angular parameters (0°, 45° and 90°) were conducted at 10% of the texture area and pump silicone grease. Findings: When point texture was added to the surface of the rotor sample, the friction coefficient and wear quantity of the sample were lower than those of the surface without texture treatment, and the double tongue 0° combination showed the best tribological properties. At this time, the average coefficient of friction and wear is reduced by 22.8% and 62%, 28.6% and 64.8%. Originality/value: The introduction of texture can effectively improve the tribological performance of progressive screw pumps, and this paper provides important theoretical and experimental support for the design of progressive screw pumps in practical applications. [ABSTRACT FROM AUTHOR]

Copyright of Lubrication Engineering (0254-0150) is the property of Editorial Office of LUBRICATION ENGINEERING and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The aim of this study was to investigate the effects of the dry-aging method on the sensory properties, chemical composition, and profile parameters of the texture of beef obtained from local farms. The qualitative characteristics of the beef were investigated for five samples, respectively, fresh meat, and dry-aged beef for 14, 21, 28, and 35 days, in aging rooms with controlled parameters: temperature (1 ± 1 °C), relative humidity (80 ± 5%), and air circulation speed (0.5–2 m/s). During the dry-aging period, there was a decrease in humidity by about 6.5% in the first 21 days, which allowed the concentration of fat, protein, and total collagen content. The dry-aging process considerably influenced the pH value of the meat, which, in the second part of the dry-aging process (14–35 days), increased from 5.49 to 5.66. These values favored the increase by 37.33% of the water retention capacity and the activation of the meat's own enzymes (calpain, cathepsin, collagenase). This influenced the solubilization process of proteins and collagen, thus contributing to the improvement of the texture profile. Because variations in organoleptic and physicochemical parameters occurred simultaneously during dry-aging and storage, the method of analyzing the information was applied. Mutual information on the influence of physicochemical indicators on the texture profile parameters was followed, a factor of major importance in the consumer's perception. The degree of influence of soluble proteins, sarcoplasmic and myofibrillar proteins, fats, and soluble collagen content on the texture profile parameters (hardness, cohesiveness, springiness, gumminess, and chewiness) of the dry-aged beef for 35 days was established. These investigations allowed the optimization of the beef dry-aging technological process in order to obtain a product with a sensory profile preferred by the consumer. [ABSTRACT FROM AUTHOR]

The different cultivars of apricot seeds may differ in their properties. To ensure economical and efficient seed processing, knowledge of the cultivars' composition and physical properties may be necessary. Therefore, the correct identification of the cultivar of the apricot seeds may be very important. The objective of this study was to develop models based on selected textures of apricot seed images to distinguish different cultivars. The images of four cultivars of apricot seeds were acquired using a flatbed scanner. For each seed, approximately 1600 textures from the image, converted to the different color channels R, G, B, L, a, b, X, Y, and Z, were calculated. The models were built separately for the individual color channels; the color spaces Lab, RGB, XYZ; and all color channels combined based on selected texture parameters using different classifiers. The average accuracy of the classification of apricot seeds reached 99% (with an accuracy of 100% for the seeds of the cultivars 'Early Orange', 'Bella', and 'Harcot', and 96% for 'Taja') in the case of the set of textures selected from the color space Lab for the model built using the Multilayer Perceptron classifier. The same classifier produced high average accuracies for the color spaces RGB (90%) and XYZ (86%). For the set of textures selected from all color channels, i.e., R, G, B, L, a, b, X, Y, and Z, the average accuracy reached 96% (Multilayer Perceptron and Random Forest classifiers). In the case of individual color channels, the highest average accuracy was up to 91% for the models built based on a set of textures selected from color channel b (Multilayer Perceptron). The results proved the possibility of distinguishing apricot seed cultivars with a high probability using a non-destructive, inexpensive, and objective procedure involving image analysis. [ABSTRACT FROM AUTHOR]

Purpose: This paper aims to study the effect of isosceles triangle micro concave texture with different parameters on the performance of oil seal to obtain a reasonable combination of parameters. Design/methodology/approach: Based on the theory of elastohydrodynamic lubrication, a numerical model is established by coupling the texture parameters of isosceles triangle with concave lip with the two-dimensional average Reynolds equation considering surface roughness. Findings: The results show that there is an optimal combination of parameters to improve the performance of the oil seal. When hp = 5µm-6.5 µm, a = 110°−130°, O = 1.4, C = 1.6 mm-2.2 mm, the oil seal with isosceles triangle micro concave texture can show good lubrication characteristics, friction characteristics and sealing ability. Originality/value: The model provides a new idea for the design of new oil seal products and provides a theoretical support for the application of surface texture technology in the sealing field in the future. [ABSTRACT FROM AUTHOR]

This study was aimed at evaluating the effect of freeze-drying and lacto-fermentation on the texture parameters of images and sensory attributes of beetroots. The samples were imaged using a flatbed scanner, and textures from images converted to color channels L, a, b, R, G, B, X, Y, Z were computed. The discrimination of raw and processed beetroots was performed using models based on textures selected for each color channel. The sensory quality of processed samples was determined using the attributes related to smell, color, texture and taste. The highest discrimination accuracy of 97.25% was obtained for the model built for color channel b. The accuracies for other channels were equal to 96.25% for channel a, 95.25% for channel R, 95% for channel Y, 94.75% for channel B, 94.5% for channel X, 94% for channel L, 92.5% for channel G, 88.25% for channel Z. In the case of some models, the raw and lacto-fermented beetroots were discriminated with 100% correctness. The freeze-dried and freeze-dried lacto-fermented samples were also the most similar in terms of sensory attributes, such as off-odor, attractiveness color, beetroot color, crunchiness, hardness, bitter taste, overall quality. The results indicated that the image parameters and sensory attributes may be related. [ABSTRACT FROM AUTHOR]

Purpose: This study aims to study the effect of micro-groove texture geometric parameters on the lubrication characteristics of the tripod universal coupling. Design/methodology/approach: The Navier–Stokes equation was used to analyse the influence of micro-groove geometric parameters on the coupling's lubrication performance. Further, Kriging approximate model and neighborhood cultivation genetic algorithm (NCGA) were used to optimise the micro-groove geometric parameters and improve the coupling's lubrication performance. Findings: The results show that as the micro-groove depth and width increase, respectively, the oil film-bearing capacity first increases and then decreases; on the contrary, the friction coefficient first decreases and then increases. With the increase of the micro-groove inclination angle, the bearing capacity of the oil film first increases and then remains unchanged. At the same time, the friction coefficient first decreases and then increases slightly. The lubricating performance of the optimised coupling is significantly improved: the optimised oil film-bearing capacity increases by 12.5%, the friction coefficient reduces by 14% and the maximum oil film pressure increases by 4.3%. Originality/value: At present, the grease lubrication performance of the micro-groove textured tripod universal coupling has not been studied. The micro-groove parameters are optimised, and the coupling's lubrication performance is improved greatly by the Kriging model and NCGA algorithm. It is of great significance to extend the coupling's fatigue life. [ABSTRACT FROM AUTHOR]

This study aimed to determine the discriminatory power of textural features to differentiate the sorghum grains subjected to normal, mild deficit, and severe deficit irrigation. The studies were carried out with the use of image processing, discrimination analysis, analysis of variance and cluster analysis using the selected texture parameters calculate for images from individual color channels L, a, b, R, G, B, U, V, S, X, Y and Z. The results indicated that different levels of irrigation can discriminate the sorghum grain with an accuracy of up to about 100%. Most of the genotypes for each level of irrigation were different in the terms of values of textural features and formed separate homogeneous groups. Drought is one of the limiting factors contributing to a decrease in sorghum grain productivity and nutritional quality, especially when it is cultivated in a marginal area. Therefore, low-quality grains produced under water stress should be recognized before they enter into the food and feed chain. The application of image analysis based on textures of sorghum grain images proved to be useful for the discrimination of sorghum grains subjected to drought stress. The applied procedure provided the fast, objective results that may be applied in practice for screening distinguishing the sorghum grains with different irrigation levels. [ABSTRACT FROM AUTHOR]

Purpose: This study aims to study the effect of micro-groove texture geometric parameters on the lubrication characteristics of the tripod universal coupling. Design/methodology/approach: The Navier–Stokes equation was used to analyse the influence of micro-groove geometric parameters on the coupling's lubrication performance. Further, Kriging approximate model and neighborhood cultivation genetic algorithm (NCGA) were used to optimise the micro-groove geometric parameters and improve the coupling's lubrication performance. Findings: The results show that as the micro-groove depth and width increase, respectively, the oil film-bearing capacity first increases and then decreases; on the contrary, the friction coefficient first decreases and then increases. With the increase of the micro-groove inclination angle, the bearing capacity of the oil film first increases and then remains unchanged. At the same time, the friction coefficient first decreases and then increases slightly. The lubricating performance of the optimised coupling is significantly improved: the optimised oil film-bearing capacity increases by 12.5%, the friction coefficient reduces by 14% and the maximum oil film pressure increases by 4.3%. Originality/value: At present, the grease lubrication performance of the micro-groove textured tripod universal coupling has not been studied. The micro-groove parameters are optimised, and the coupling's lubrication performance is improved greatly by the Kriging model and NCGA algorithm. It is of great significance to extend the coupling's fatigue life. [ABSTRACT FROM AUTHOR]

Objectives: We aimed to evaluate pre-treatment MRI predictors of high-grade malignant parotid gland cancer by comparing MRI findings and texture parameters between high-grade and intermediate/low-grade parotid gland cancers. Methods: Patients underwent a pre-treatment MRI and had a parotid gland cancer resection with pathological evaluation. Evaluation objectives included attributive factors such as age and gender, several MRI findings of T1- and T2-weighted images, post-contrast fat suppression T1-weighted images, ADC value and 40 texture parameters calculated from T2-weighted axial images. Such objects were compared between high-grade and intermediate/low-grade lesions. Results: Of the parotid gland cancers surveyed, 39 were included for analysis. Of these, 18 were high-grade lesions, 2 were intermediate-grade lesions, and 19 were low-grade lesions. The high-grade group was significantly older than the low- and intermediate-grade groups (p = 0.01). There were more males in the high-grade group than in the low- and intermediate-grade groups (p = 0.01). There were also significantly more MRI findings of neck lymph node metastases in the high-grade group than in the low- and intermediate-grade groups (p < 0.001). Other MRI findings and texture parameters did not show significant differences between the two groups (p = 0.07–1.00). Conclusions: Morphological assessment on MRI and texture parameters alone is not sufficient to estimate the grade of parotid cancer. MRI findings of neck lymph node metastases, as well as patient characteristics such as age (older patients) and gender (male) can be suggestive of high-grade parotid gland cancer in pre-treatment evaluation. [ABSTRACT FROM AUTHOR]

Accurate surface texture design is of great significance to improve the performances of gas bearings. In this article, the finite difference method and Newton's method were combined to obtain the oil film pressure distribution, and the effect of rectangular groove on the lubrication performance was analyzed by changing representative texture parameters. The results show that the performances were more affected by the rectangular texture size compared with the distribution and the bottom shape of texture. The increasing of the surface texture number can only enhance the stability of the bearing. The bearing can provide 30% more bearing capacity by choosing larger size, radial arrangement and plane bottom. These results and analysis can provide technical reference for the bearing texture design. [ABSTRACT FROM AUTHOR]

Over the past few years, the market for cheese substitutes has been growing on account of the simple and cost‐effective production of these cheese‐like products. It is well established that the functional properties of cheeses are directly related to their composition. Therefore, the variation of fat in cheese substitutes certainly affects the characteristics of the cheeses. The purpose of this review was to summarize the latest research on the effects of milk fat replacement with vegetable oils on the rheological, textural, and microstructural properties of cheese analogues. The findings suggest that the primary effects of modifying fat in cheese analogues are associated with an alteration in the interactions among the components of the protein matrix, which varies because of milk fat extraction. Overall, changes in the functional properties of analogous cheeses will depend on the type of oil, the percentage of fat modification, and the type of cheese produced. [ABSTRACT FROM AUTHOR]

The study was aimed at the evaluation of the usefulness of textures of the outer surface from the images of apple skin and flesh for discrimination of different cultivars. The texture parameters were calculated from color channels: R, G, B, L, a, b, U, V, H, S, I, X, Y, Z. In the case of cultivar discrimination performed for the apple skin, the highest accuracies were obtained for textures from channels R, a and X. In the case of channels R and a, the apples were classified with the total accuracy of up to 93%. For channel X, the highest total accuracy was 90%. For discrimination based on the textures selected from images of a longitudinal section of apples, the total accuracy reached 100% for channels G, b and U. In the case of the cross-section images, the total accuracies were also satisfactory and reached 93% for channel G, 97% for channels b and U. The obtained results proved that the use of image processing based on textures can allow the discrimination of apple cultivars with a high probability of up to 100% in the case of textures selected from images of a longitudinal section. The results can be applied in practice for cultivar discrimination and detection of the falsification of apple cultivars. The obtained results revealed that texture features can allow for cultivar identification of apples with a very high probability in an inexpensive, objective, and fast way. [ABSTRACT FROM AUTHOR]

The aim of this study was to evaluate the effect of potato boiling on the correctness of cultivar discrimination. The research was performed in an objective, inexpensive and fast manner using the image analysis technique. The textures of the outer surface of slice images of raw and boiled potatoes were calculated. The discriminative models based on a set of textures selected from all color channels (R, G, B, L, a, b, X, Y, Z, U, V, S), textures selected for color spaces and textures selected for individual color channels were developed. In the case of discriminant analysis of raw potatoes of cultivars 'Colomba', 'Irga' and 'Riviera', the accuracies reached 94.33% for the model built based on a set of textures selected from all color channels, 94% for Lab and XYZ color spaces, 92% for color channel b and 92.33% for a set of combined textures selected from channels B, b, and Z. The processed potatoes were characterized by the accuracy of up to 98.67% for the model including the textures selected from all color channels, 98% for RGB color space, 95.33% for color channel b, 96.67% for the model combining the textures selected from channels B, b, and Z. In the case of raw and processed potatoes, the cultivar 'Irga' differed in 100% from other potato cultivars. The results revealed an increase in cultivar discrimination accuracy after the processing of potatoes. The textural features of the outer surface of slice images have proved useful for cultivar discrimination of raw and processed potatoes. [ABSTRACT FROM AUTHOR]

Copyright of Informacion Tecnica Economica Agraria is the property of Asociacion Interprofesional para el Desarrollo Agrario (AIDA) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Food & Dairy Sciences is the property of Egyptian National Agricultural Library (ENAL) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Purpose: Surface textures have been widely used in thrust bearings as a means of enhancing the tribological performance. The effect of textures with a spiral distribution on the lubrication characteristics of thrust bearings has not been fully covered. This paper aims to investigate and find the optimal structure and distribution parameters of textures with the maximum loading capacity and minimum friction force as goals. Design/methodology/approach: Combining the multi-objective optimization method based on the non-dominated sorted genetic algorithm-II with response surface methodology, the key textured parameters are optimized. Local sensitivity analysis is used to evaluate the impact level of each parameter. Findings: Spiral distribution of textures can effectively improve the lubrication performance of the thrust bearing compared with the linear distribution. The distribution with high amplitudes and high cycle numbers will weaken the spiral effect and destroy the high-pressure region. Through the multi-objective optimization of the textured structure and distribution parameters, the loading capacity demonstrates a 55.05per cent improvement compared to the basic model. Textured width is the most sensitive parameter for both loading capacity and friction force. Originality/value: Present research provides a fundamental design guide for textured thrust bearings. [ABSTRACT FROM AUTHOR]

Utilization of agricultural wastes and residues resulted from food industry in animal nutrition is a matter of great concern nowadays. Dried citrus peel (DCP) and flax meal (FM) are potential sources of some valuable bioactive nutrients for animals and poultry. This experiment was conducted to evaluate the effects of dietary supplementation of FM used together with two different DCP: dried orange peel (DOP) and dried red grapefruit peel (DRGP) on few breast meat quality traits of broiler chickens. One hundred-twenty broiler chicks (1 day old) were randomly allocated to three groups for the starter phase (14 d) where they were fed with a standard diet. At day 14, they were individually weighed (average 440.77 g) and homogenous assigned to three dietary treatments comprised of: basal diet (C) with 4% FM, basal diet supplemented with 2% DOP and 4% FM (DOP) and basal diet supplemented with 2% DRGP and 4% FM (DRGP), for both grower and finisher phases. At the end of the experiment (d 42) 6 broilers chicks/group were slaughtered and samples of breast meat were collected, and assayed for chemical composition, texture profile analysis (TPA), color parameter and fatty acid composition. Results of the present study indicated that use of FM together with DOP and DRGP in broiler diets significantly (P < 0.05) improved the color and some texture parameters and didn't affected the chemical composition or fatty acids from raw chicken breast meat. [ABSTRACT FROM AUTHOR]

Since the signal-to-noise ratio of synthetic aperture radar (SAR) image is low, it is difficult to match SAR images with optical images accurately. A new method of SAR village targets extraction and heterogonous image registration is proposed in this study. Median filter and partial differential method are first used to remove speckle noise; next, the grey level co-occurrence matrix algorithm is used by calculating four typical texture parameters of it to obtain preliminary regions of interest (ROI) of village targets and false alarm areas are cleared by proposed local-grey-level congruency method; then proper numbers of Fourier descriptors and morphological algorithms are used to describe ROI again to maintain the boundary features of targets better. Finally, HU moment invariants, which is combined with Euclidean distance and cosine similarity measurements, are utilised to achieve heterogonous image registration. The experimental results show that the root-mean-square-error of the registration image is small and the heterogonous registration image is accurate, demonstrating that the authors' method is stable and accurate, and owns certain research value and broad application prospect as well. [ABSTRACT FROM AUTHOR]

Copyright of Xinjiang Agricultural Sciences is the property of Xinjiang Agricultural Sciences Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of China Petroleum Machinery is the property of China Petroleum Machinery Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The aim of this research was to identify the appropriate aging period for the optimal development of quality traits and desirable consumer perception of traditional dry-cured ham, dried and ripened under natural climatic conditions. Three different samples from traditional Bulgarian dry-cured Elena ham were studied with aging periods of 8, 18 and 36 months. The samples were evaluated for various quality aspects, including colour and textural parameters, and sensory analysis was performed. The dynamics of the colour parameters of the samples showed that, in spite of a pronounced tendency towards a decrease in the redness values (α*) with the increase in the ripening and drying time, simultaneous with minor changes in the yellowness values (b*), no significant colour changes were observed in the 8- and 18-month samples. Their complex colour remained located in the red area with a lower percentage of other colour hues compared to the 36-month sample where there was a slow shift of colour from the red area. However, when comparing these data with the sensory assessments for colour, there was no reason to assert that prolonged aging had a significant negative impact on the colour; the results were even indicated as satisfactory. A negative relationship between the textural parameters from the TPA analysis and the sensory textural scores were determined for excessive aging up to 36 months. However, the aging of ham up to 18 months in a natural drying chamber received the highest scores, whereas the extension of this period led to textural worsening and a decline in the sensory scores. [ABSTRACT FROM AUTHOR]

[Objectives] This study was carried out to determine texture parameters for texture profile analysis (TPA), and optimize the texture determination of 'Yali' by texture analyzer. [Methods] The traditional varieties of 'Yali' were taken as the materials, and texture parameters were determined at different compression rates and deformations at target. [Results] In the process of the TPA, the deformation at target had an extremely significant influence on 8 TPA texture parameters, namely, the hardness, cohesiveness, springiness, adhesiveness, gumminess, resilience, fracturability, and chewiness (P≤0.01), while the compression rate had significant influence on the hardness and gumminess (P≤0.05), had an extremely significant influence on fracturability (P≤0.01), and had no significant influence on other 5 TPA parameters. [Conclusions] Taking the compression rate of 1 mm/s and 20% deformation at target as the experimental conditions for TPA could avoid the impact load of high speed on the tissue and objectively reflect the textural characteristics of 'Yali' pulp tissue. [ABSTRACT FROM AUTHOR]

Copyright of Meat Technology is the property of Institute of Meat Hygiene & Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)