Journal of texture studies最新文献

Walnuts (Juglans regia L.) are valued for their nutritional profile and economic significance. Despite the advancement in cultivar development and production globally, growers face challenges such as the oxidation of unsaturated fatty acids during storage, leading to rancidity and consumer rejection. Local growers also need to identify the uniqueness of their products compared to overseas imports. Rapid profiling methods, such as Napping, have been developed to generate sensory characteristics at low cost, although no study has been conducted on walnuts. This study aimed to understand the driving factors of consumer acceptability of walnut kernels, in the context of the New Zealand market, using Napping combined with consumer preference mapping. The products were sourced commercially from the market. Physicochemical properties, including oxidation indices, color, moisture content, and texture profiles, were assessed. The sensory characteristics were profiled by Napping. The products were then tested for consumer acceptability. Products were sensorily distinct, differentiated mostly by creamy and rancid attributes. The preference mapping revealed that the preferred zones by most consumers corresponded to light brown, smooth, woody, sweet, fresh, and creamy attributes. Products featuring rancid and astringent are disliked by most consumers. Despite the commonality, two consumer clusters were identified. One cluster disliked those with high chemically measured oxidation, while the other cluster disliked those with high texturally measured resilience and springiness. These findings demonstrate that Napping, combined with Preference Mapping, offers a practical approach for small-scale producers to assess and improve the quality of walnut while probing the variability of consumer market.

A naturally phosphorylated starch from Syzygium malaccense seeds was evaluated for its potential in dysphagia-oriented food formulations. Functional characterization included solubility, swelling, emulsification, phosphorus content, paste clarity, rheology, and digestibility. Additionally, starch preparations were classified according to the International Dysphagia Diet Standardization Initiative (IDDSI). Water solubility and swelling increased with temperature (50°C–90°C). Emulsifying capacity reached 51.6%, with 94.6% stability. The starch formed a clear paste (5.2% transmittance) and contained 48.1 mg P/100 g, exceeding commercial starches. After 180 min of digestion, 39.7% hydrolysis yielded a hydrolysis index of 15.88 and glycemic index of 48.44, values lower than those found for commercially available starches. Rheologically, it behaved as a non-Newtonian dilatant fluid without hysteresis. The IDDSI flow test showed that a 2% (w/v) starch suspension produces level 1–2 slightly thick fluid, and the IDDSI fork pressure test evidenced a level 4 starch gel, which is considered an extremely thickened or pureed food. Gathering the findings of this study, it is possible to conclude that S. malaccense starch exhibits desirable properties that enable it to be used as a thickener for liquid and solid dysphagia diets.

This study investigates the texture, meltability, and rheology of faba bean protein concentrate (FPC)/kappa-carrageenan (KC) emulsion gels, focusing on the impact of protein concentration (1%–4% w/w), pH (4–7), ionic strength (0 and 0.171 M NaCl), and storage time (1 and 15 days). At pH 4, FPC aggregated near its isoelectric point (ζ-potential≈0 mV), while KC maintained a strongly negative charge (≈−50 mV). Maximum turbidity was observed at pH 4, indicating protein-polysaccharide complex formation. Texture analysis revealed non-linear behavior, with 4% FPC gels exhibiting the highest hardness (34.13 ± 3.95 N at pH 7), while NaCl addition reduced hardness (e.g., 18.05 ± 1.58 N to 2.24 ± 0.09 N at pH 6) and water holding capacity (86.80% ± 0.72% to 69.14% ± 1.28% at pH 5). Meltability peaked at 2% FPC (51.56 ± 3.30 mm at pH 6), correlating with reduced cohesiveness. Rheological analysis confirmed strong elastic behavior (G′ > G″), with phase transition temperatures decreasing from 81.85°C ± 1.17°C (pH 5) to 73.11°C ± 0.35°C (pH 7). These results offer a framework for optimizing the texture and stability of FPC/KC-based gels, addressing challenges in plant-based food formulations.

Model food bars were produced with different cooking temperatures and compression distance in order to determine if changing these processing parameters could produce meaningful differences in texture. The food bars were characterized by instrumental texture analysis using a cutting test and three-point bending test, and texture parameters were extracted from the resulting force curves. In order to determine if the changes in texture were meaningful, a selected set of texture-parameters were used to propose a novel approach to the classification of the texture of different food bars. The novel approach is to coarse-grain each texture parameter into a discrete number of bins, such as “high” and “low” value bins, based on some algorithm for defining the number of bins and the cutoff value between bins; thereby reducing the texture characterization from essentially infinite variability, to one with a fixed number of texture categories (e.g., 32 or 243, depending of the number of bins and parameters selected). Using a set of 30 commercial food bars, seven classification algorithms were evaluated for their utility in showing similarities and differences between the texture of the various food bars. When applied to the model food bars, the results showed that both the cooking temperature and the compression distance were able to alter the texture, though the former had a stronger effect. We conclude that this novel approach to texture classification is an easy-to-implement framework that can provide valuable insights for market research and product formulation of food bars.

In this study, aerosols formed via oral movement while drinking wine were hypothesized as an oral-nasal delivery mechanism for aroma compounds with limited volatility, potentially inducing specific retronasal sensory perception. To this end, the formation mechanism of flavored aerosol particles (hexyl hexanoate) using model wine samples was investigated in vitro using the mechanical agitation method. The physical and physicochemical property variations of model wine samples had a significant impact on the total quantity of formed aerosol and average particle size, as well as flavor release, validated using gas chromatography. Taken together, this is the first study demonstrating that flavored ethanol aerosols could be formed using an in vitro method, and generated aerosol droplets could be suspended in and transported with air, and had the potential to settle onto mucus and trigger sensory perception.

Image texture refers to the visual patterns, variations, or configurations of pixel intensities within an image. Classifying textures is a fundamental goal in computer vision, applicable in areas ranging from medical picture analysis to distant sensing. Throughout the years, numerous strategies have been proposed to address this challenge; however, recent advances in deep learning have significantly transformed the subject. The proposed work delineates reliable and resilient local descriptors termed Texture Classification using Effective Texture Descriptors (TCETD), which integrates Locally Directional and Extremal Pattern (LDEP) with Gray-Level Co-occurrence Matrix (GLCM) to effectively acquire directional, extremum statistics, and spatial relationships among pixel intensities. To communicate directions related to the local area, it first obtains the directional local difference count pattern (DLDCP), which is divided into symmetric and asymmetric positions. By integrating the extremum location, differential, and compression pattern from adjacent sites, we extract the neighbor's extremum-related local pattern to acquire the extremum data generated by the initial segment. The two elements are combined to create the LDEP. The GLCM extracts spatial correlations, pixel intensity patterns, and features based on the distance and angle of pixels within an image. This descriptor can be utilized alongside the LDEP approach to offer a more thorough and resilient representation of the picture texture features, hence enhancing classification accuracy. The outcomes of experiments performed on three notable texture image databases—Klyberg (Stex), Kth-tips2-a, and CUReT—exhibit comparable correct classification rates of 97.91%, 93.82%, and 97.25%, respectively. These rates were achieved using our recently proposed TCETD descriptor under diverse conditions, including rotational and illumination variations, scale differences, and viewpoint alterations, in contrast to traditional methods for classifying texture images. The efficacy of the proposed strategy is corroborated using the Bonn BTF dataset, and the recommended method demonstrated superior performance.

To investigate the effects of irrational irrigation on tomato yield and quality, and the effects of different irrigation regimes on tomato biotexture mechanics, irrigation experiments were carried out in greenhouses, focusing on the two factors of irrigation frequency and irrigation quantity. Results showed that when the irrigation regime was A1 (150% ETc, 1 time/interval 1 day) or E3 (50% ETc, 1 time/interval 13 days), the fruit cracking rate was up to 69.53%; when the irrigation regime was C3 (50% ETc, 1 time/interval 5 days), the cracking rate was as low as 8.75%. Irrigation regime also had significant effects on the mechanical indicators. Meanwhile, the irrigation regime significantly affected the content and status of pectin in the cell wall but had no significant effect on hemicellulose and cellulose. With a short irrigation cycle and large irrigation amount, WSP (Water-soluble Fraction) increased, CSP (CDTA-soluble Fraction) and NSP (Na2CO3-soluble Fraction) decreased, and the fruit was easy to crack. The crystallinity, supporting power, and cracking resistance of pectin polysaccharides in C were strong, while those in A, B, D, and E were opposite. Research showed that the cracking of tomato induced by irrigation was due to the change of the composition and structure of the polysaccharide in the cell wall. This study can provide a reasonable irrigation regime such as C3 treatment for fruit farmers, which has the effect of both saving water and improving quality. The screened mechanical phenotypic indexes are conducive to reverse localization of crack control genes and enhancing tomato crack resistance breeding level.