A COMPARISON OF THREE INSTRUMENTAL TESTS FOR PREDICTING SENSORY TEXTURE PROFILES OF CHEESE

Multivariate analysis techniques were used to seek correlations between texture sensory attributes assessed by a trained professional panel and instrumental measurements (compression, puncture and penetration) carried out on various types of cheeses. Twenty-nine cheeses were assessed by the panel and instruments. Correlation was sought using Partial Least Squares regression. Hardness (R=0.87), springiness (R=0.98) and cohesiveness of mass (R=0.89) were best predicted by instrumental data from a cone penetration test. The prediction of cohesiveness was acceptable using any of the three instrumental tests performed (0.76相似文献   

Physicochemical,textural and sensory properties of white soft cheese made from buffalo and cow milk mixtures

The physicochemical, textural and sensory properties of white soft cheeses made from three different buffalo and cow milk mixtures (100:0, 70:30 and 30:70) during 3‐month storage were studied. The increase in buffalo milk concentration resulted in increasing total cheese yield, dry matter (DM) and fat retention and fat in DM content. However, it caused reductions in moisture content, salt intake, hardness, chewiness, elasticity, sensory hardness and sensory cohesiveness of the samples. The percentage of water‐soluble nitrogen to total nitrogen increased during storage resulting in decreased fracturability, hardness (textural and sensory), cohesiveness (textural and sensory), springiness, chewiness and elasticity. The panellists evaluated the white soft cheese made with buffalo milk as the most acceptable.     

Correlation between instrumental and sensory ratings by evaluation of some texture reference scales

The objective of this study was to investigate instrumental–sensory relationships of some texture scales using argentine foods as references. Textural characteristics of these foods were instrumentally investigated by the texture profile analysis technique. Principal component analysis (PCA) was used to describe the main attributes of the food samples. High Pearson’s correlation coefficients were found between hardness and fracturability (r = 0.94; P < 0.0001), hardness and gumminess (r = 0.71; P < 0.0001) and springiness and cohesiveness (r = 0.85; P < 0.0001). PCA identified two significant principal components, which accounted for 81.2% of the variance in the instrumental data. Additionally, a trained panel described the texture characteristics of the food samples according to the standard reference scales. The correlation curves showed nonlinear relationships (R² between 85.6% and 99.9%) which were used to predict sensory attributes of other food samples. Some texture attributes like hardness and fracturability were accurately predicted by mechanical properties, while others like cohesiveness and adhesiveness were less representative.     

PREDICTING SENSORY COHESIVENESS, HARDNESS AND SPRINGINESS OF SOLID FOODS FROM INSTRUMENTAL MEASUREMENTS

ABSTRACT

The sensory evaluation of cohesiveness, hardness and springiness of 15 solid food samples was performed by eight trained assessors. The rheologic response of the 15 samples was estimated by performing cyclic compression tests and stress–relaxation tests. From the force–deformation curves of the first two cycles of the compression test, texture profile analysis parameters related to cohesiveness, hardness and springiness were calculated. Young's modulus (E), strain (d_i) and stress (s_i) at peak as well as irrecoverable strain (r_i) and irrecoverable work (L_i) were monitored during the first five cycles. From the stress–relaxation response, Peleg's linearization model parameters, K₁ and K₂, were estimated by best‐fit regression. These parameters were used for predicting sensory attributes. Hardness and springiness were both accurately predicted by rheologic properties, while cohesiveness prediction was less representative.

PRACTICAL APPLICATIONS

This study contributes to enhance the knowledge in the research area of sensory instrumental correlation. Also, the research allows to better understanding that no single instrument is able to measure all texture attributes adequately. In fact, the results demonstrate that both stress–relaxation and cyclic compression tests need to be performed for the correct prediction of sensory responses.     

DRY TOFU CHARACTERISTICS AFFECTED BY SOYMILK SOLID CONTENT AND COAGULATION TIME1

The effects of soymilk solid content (°Brix) and coagulation time on the yield, proximate composition, and textural characteristics of dry tofu were investigated. Soymilk °Brix significantly (p < 0.05) influenced tofu yield, fracturability, hardness, springiness, cohesiveness, and chewiness. Among soymilk °Brix of 7.1, 7.8, 8.4, and 9.2 tested, °Brix 9.2 (9:1 water/bean ratio) produced the lowest yield (201g/100g bean), but the highest fracturability, hardness, cohesiveness, springiness, and chewiness. Coagulation time for 5 min resulted in a significantly lower tofu yield but higher cohesiveness than coagulation for 15 min. The fracturability and hardness of tofu from 9.2 °Brix soymilk coagulated for 5 min were greatest (18.0 and 19.6 kg, respectively). Lower soymilk °Brix and longer coagulation time produced tofu with a significantly higher moisture content. Dry tofu contained approximately 75–78% moisture (wet basis), 55–58% protein (dry basis), and 20–23% fat (dry basis).     

PECAN TEXTURE AS AFFECTED BY MOISTURE CONTENT BEFORE FREEZING AND THAWING RATE

The texture of pecans was determined as affected by initial moisture content before freezing (3 vs 5%), thawing rate (IX, 1.2X, 2.7X, 5.6X), and multiple freeze‐thaw cycles (0, 1X, 3X, 6X, 9X, 12X). Texture was determined by instrumental Texture Profile Analysis (TPA) and sensory evaluation. Initial moisture content before freezing had a significant effect on all of the sensory evaluation parameters (hardness, fracturability, cohesiveness, and denseness) and most of the instrumental TPA texture parameters (hardness, fracturability, springiness, resilience, and chewiness). Thawing rate only affected TPA hardness and resilience. TPA fracturability correlated best with sensory fracturability. The sensory panel could not detect any differences between the different thawing rates. The slowest thawing rate affected more parameters than the medium and faster rates. More freeze/thaw cycles significantly decreased most TPA texture values, especially for pecans at higher moisture content.     

EFFECT OF PROTEIN HYDROLYSATE ON THE INSTRUMENTAL TEXTURE PROFILE OF GELATIN GELS

The texture of gels containing 2 to 8% of gelatin and 1 to 10% of alcalase protein hydrolysate obtained from poultry meat was examined using the instrumental texture profile analysis (TPA) method in compression and penetration mode. Response surface analysis modelled the effects of the two components of the gels on textural properties. In both tests the addition of hydrolysate decreased hardness and chewiness, and the effect was more pronounced for higher gelatin concentrations. The senses of changes in cohesiveness and springiness as measured in both tests employed here were not in agreement with each other owing to different consequences produced on the sample. In the case of compression, both parameters decreased with increased hydrolysate addition, whereas for penetration an increase in cohesiveness was observed as well as small changes in springiness. Hydrolysate produced a statistically significant negative linear and positive quadratic effect with regard to the majority of the studied texture parameters. This component interacted significantly with gelatin with regard to hardness, chewiness, and fracturability which led to a decrease in the first two and an increase in the last texture parameter. The weakening effect of the protein hydrolysate upon texture may be of great importance for the quality of gelatin gels.     

PREDICTION OF RICE TEXTURE BY SPECTRAL STRESS STRAIN ANALYSIS: A NOVEL TECHNIQUE FOR TREATING INSTRUMENTAL EXTRUSION DATA USED FOR PREDICTING SENSORY TEXTURE PROFILES

Sensory texture characteristics of cooked rice for three cultivars (74 samples) were predicted using an extrusion cell and a novel data analysis method (i.e. Spectral Stress Strain Analysis). Eight sensory texture characteristics were evaluated and force values from the instrumental tests were used in combination with Partial Least Squares regression to evaluate predictive models for each of the sensory attributes studied. Relative Ability of Prediction (RAP) values were evaluated for each model; they ranged from 0.06 to 0.85. Satisfactory models are proposed for the two major texture characteristics of cooked rice, namely hardness (RAP=0.85) and stickiness as evaluated by adhesion to lips (RAP=0.76). Other sensory attributes such as roughness of mass (RAP=0.73) and toothpack (RAP=0.81) were also satisfactorily predicted. Sensory attributes such as toothpull (RAP=0.12) and loose particles (RAP=0.06) could not be predicted using the Spectral Stress Strain Analysis.     

Prediction of sensory textural properties from rheological analysis for process cheeses varying in emulsifying salt,protein and moisture contents

Textural characteristics of process cheeses varying in emulsifying salt (disodium phosphate), protein and moisture contents were evaluated by rheological compression using texture profile analysis and by sensory evaluation. The primary objective of this study was to predict sensory textural parameters using instrumental rheological parameters. All sensory parameters correlated with one or more instrumental parameters, e.g. rheological firmness versus sensory firmness (R = 0.98, P < 0.001), rheological chewiness versus sensory rubbery (R = 0.92, P < 0.001) and rheological chewiness versus sensory chewy (R = 0.86, P < 0.001). Partial least squares calibration models were developed for each of nine sensory parameters using instrumental parameters. Principal component analysis of instrumental and sensory parameters illustrated relationships among parameters. It was shown that instrumental parameters could be used to supplement sensory evaluation of process cheese texture. Increasing emulsifying salt content increased firmness, springiness and chewiness and decreased adhesiveness, mouthcoating and mass formation. Increasing protein content resulted in increased fracture strain and stress and chewiness and decreased melting. Increasing moisture content increased cohesiveness and decreased firmness and chewiness. Copyright © 2007 Society of Chemical Industry     

Effect of Ultrastructure on Changes of Textural Characteristics between Crisp Grass Carp (Ctenopharyngodon Idellus C.Et V) and Grass Carp (Ctenopharyngodon Idellus) Inducing Heating Treatment

The research studies the ultrastructure effect on texture of crisp grass carp (CGC) and grass carp (GC) fillets inducing heating for 15, 25, and 40 min with boiling water. After heating, the hardness, fracturability, springiness, chewiness, resilience, and cohesiveness of CGC were higher than that of raw CGC, whereas the all textural characteristics of heating GC were lower obviously than that of raw GC. The hardness, fracturability, springiness, chewiness, resilience, and cohesiveness of CGC for heating 15 min were higher by 6.3%, 9.0%, 27.0%, 71.8%, 9.4%, and 23.9%, respectively, than that of raw CGC (RCGC). The hardness increasing of CGC flesh with the extension of heating time related closely to more coagulating connective tissue in interstitial spaces, especially relating to smaller muscle fiber diameter and denser muscle fiber density. The more and larger spaces between fiber and fiber with the extension of heating time results in the decrease of cohesiveness and resilience of CGC flesh. For chewiness, the stronger chewiness of cooked CGC associated with more detachment of myofiber–myocommata and fiber–fiber. Overall, the results show that the changes of texture characteristics of CGC fillet with extension of heating time correlates positively with the ultrastructure.     

Chemical, physical, and sensorial characteristics of "Terrincho" ewe cheese: changes during ripening and intravarietal comparison

The objectives of this study were to monitor the changes in chemical [moisture, acidity, pH, and water activity (a(w))] and physical (color and texture) parameters of "Terrincho" ewe cheese during 60 d of ripening, and to determine the correlations between the changes in instrumental texture and color parameters and the ripening time of the product. Intravarietal comparison of Terrincho ewe cheese from 5 different dairy plants was performed by evaluation of mechanical parameters from texture profile analysis (TPA) and color parameters in terms of CIELAB color space (L*, a*, and b*). In addition to mechanical and color tests, composition analyses and sensory tests were performed. The results were evaluated with statistical methods (single valued and multivariate analysis). During the first 20 d of ripening, an increase in hardness, fracturability, gumminess, chewiness, and yellowness occurred. Simultaneously, adhesiveness, resilience, L* (inside cheese, "i" and external "e"), and cohesiveness decreased. After 20 d of ripening hardness, fracturability, gumminess, and chewiness decreased and cohesiveness increased. The ripening time of Terrincho cheeses can be estimated with 6 variables: L* (external, e), L* (i), b* (inside cheese, i), hardness, a* (i), chewiness, and a constant. The estimation error was 4.2 d. Evaluation of composition, pH, texture profile analyses, color, and related sensory characteristics of Terrincho cheeses from 5 different dairy plants (with 30 d of ripening) revealed correlations between these parameters.     

Comparison of Sensory and Instrumental Texture Profile Techniques for the Evaluation of Beef and Beef-Soy Loaves

Relationships among sensory texture profile parameters, among values for textural parameters obtained through different methods of interpreting instrumental texture profile analysis (TPA) curves obtained with an Instron, and between sensory and instrumental TPA values were examined for beef and beef-soy loaves. The only singificant relationship among sensory parameters was between cohesiveness and springiness. Although a number of significant relationships existed between the various methods of interpreting instrumental parameters, a number of these were associated with secondary parameters having common primary parameters. A strong relationship was found between sensory springiness and adjusted downstroke cohesiveness. Sensory cohesiveness was related both to this instrumental parameter and to downstroke cohesiveness. Chewiness values calculated for these two methods for obtaining cohesiveness values showed strong negative associations with sensory fracturability scores.     

熏煮香肠保水性评价模型研究

为了构建熏煮香肠保水性(water-holding capacity,WHC)评价模型,本研究以添加不同胶体辅料的熏煮猪肉香肠的硬度、弹性、内聚性、咀嚼性、WHC、保油性(fat-holding rate,FHR)等品质指标为研究对象,采用主成分分析、聚类分析等多元分析方法,研究了熏煮香肠品质指标间的关系,构建了保水性...     

Effect of Storage Conditions of Dry Bean Seeds (Phaseolus vulgaris L.) on Texture Profile Parameters After Cooking

Red kidney beans were stored at constant moisture and high and low temperature for 6 months. Instrumentally measured parameters of hardness, fracturabihty, gumminess, chewiness, springiness and cohesiveness were higher in samples stored at elevated temperatures than the control (2°C). The sensory panel found the stored beans had higher hardness, fracturability, lumpiness, chewiness, and skin toughness and less starchiness, gumminess, pastiness and moisture absorption than the control. Puncture forces followed approximately a normal distribution curve, and there was always some overlap between stored and control beans even when the stored beans had a much higher mean puncture force than the control. All textural parameters of cooked bean cotyledons changed substantially during storage of the seeds at elevated temperatures and high relative humidity.     

INSTRUMENTAL AND SENSORY TEXTURAL PROPERTIES OF FURA

ABSTRACT

A uniaxial compression test and sensory textural analysis was conducted of fura samples made from millet flour. Significant differences (p<0.05) existed among the samples for hardness (the force to compress the sample between molar teeth), cohesiveness (extent to which sample falls apart during chewing) and gumminess (denseness and cohesion persisting during mastication). Correlations between sensory and instrumental tests revealed that a significant relationship exists between modulus of deformability and cohesiveness (r=?0.93, p<0.05); gradient and springiness (r=?0.90, p<0.05); deformation at failure and chewiness (r=0.98, p<0.05); energy per unit mass and gumminess (r=?0.95, p<0.05). A fura quality scale was established based on the peak force; soft and poor quality fura have a peak force of <19 kN; acceptable fura has a peak force of 19–24 kN; a firm and good quality fura, 24–25 kN; very hard and very poor quality fura have a peak force of >25 kN.     

Colour and textural attributes of sucuk during ripening

The sensory (flavour, colour, and ease of cutting scores), colour (Hunter L, a, b, YI, total colour difference, hue angle, chroma, and browning index values) and textural (hardness, adhesiveness, springiness, cohesiveness, gumminess, chewiness, and resilience) attributes of sucuk were followed during the ripening period. Colour scores increased (P<0.05) from score 4 to 6 during the first 3 days of the ripening period and then decreased (P<0.05). The lightness (L values), yellowness (b), and hue angle of sucuk decreased (P<0.05) during the ripening period. The major colour changes occurred between the 5th and 9th days of the ripening period. Pearson correlation test indicates that a positive relationship (P<0.01) exists between a-values and sensory colour scores. The overall sensory scores changed (P<0.05) in parallel to the flavour scores. Hardness, gumminess, and chewiness of sucuk increased (P<0.05) during the ripening period. Strong relationships (P<0.01) were found between hardness and cutting scores. Adhesiveness values of sucuk decreased significantly (P<0.05) about 10 times from -9.3 to -92.6 during the ripening period. Springiness and cohesiveness values decreased during the ripening period, but not significantly (P>0.05). Cutting scores were related (P<0.01) to gumminess (0.921) and chewiness (0.922) values but not to resilience (P>0.05). It was observed that most instrumental colour and textural attributes were in agreement with sensory attributes. These results indicated that instrumental methods could be easily adapted and can be used for evaluation of quality attributes of sucuk during the ripening period.     

TRAINING A TEXTURE PROFILE PANEL AND CONSTRUCTING STANDARD RATING SCALES IN ARGENTINA

A method is described for constructing reference scales for the sensory texture profile method in countries outside the U. S., such as Argentina. A complete set of 13 reference scales were constructed for Argentine foods: hardness, adhesiveness to palate, fracturability, cohesiveness, denseness, wetness, adhesiveness to lips, roughness, selfadhesiveness, springiness, cohesiveness of mass, moisture absorption and adhesiveness to teeth. Scores given by the panel trained using these scales were compared to those given by a panel trained using the US scales and found to be similar, in direction and magnitude, among the tested food samples.