EVALUATION OF TEXTURE OF PECTIN JELLIES WITH THE VOLAND-STEVENS TEXTURE ANALYZER

Texture profile analysis (TPA) parameters were determined with a Voland-Stevens Texture Analyzer-1000 (VSTA) and an Instron Universal Testing Machine. Because of the nature of the design of VSTA, reliable magnitudes of TPA parameters based on the force-time curves recorded during the down stroke can be calculated. With a 2.54 cm diameter plexiglas plunger, the TPA parameters with the VSTA were higher than those with the Instron by 1.45% for hardness to 16.1% for fracturability.     

INSTRUMENTAL TEXTURE PROFILE ANALYSIS WITH PARTICULAR REFERENCE TO GELLED SYSTEMS

Instrumental Texture Profile Analysis (TPA) was developed about 30 years ago, constituting an interesting way of analyzing a series of textural parameters in only one test. Since then much work has been done and new tools have been developed. This paper focuses on gelled food systems, reviewing and discussing the evolution of the initial terminology, testing conditions and sampling methods. New parameters, experimental and calculation methods, and some newly proposed are also analyzed, updating the instrumental TPA as applied to gelled systems.     

EFFECT OF DEGREE OF COMPRESSION ON TEXTURE PROFILE PARAMETERS

Texture Profile Analysis (TPA) was performed on apple, carrot, frankfurter, cream cheese and pretzels with the Instron and the effect of the degree of compression on TPA parameters measured at a compression speed of 5 cm/min. Fracturability is almost independent of the degree of compression. Hardness, area 1, area 2, cohesiveness, gumminess, and chewiness usually increase with increasing compression but the rate of increase varies widely. Springiness increases for pretzel sticks and decreases for the four other commodities as compression increases. Adhesive force and adhesive area of cream cheese increase but stringiness decreases with increasing compression. Since the TPA parameters vary so widely with degree of compression, all TPA measurements should standardize the degree of compression and clearly state in reports what compression was used.     

COMPUTER-ASSISTED READOUT OF DATA FROM TEXTURE PROFILE ANALYSIS CURVES1

The speed of computer readout plus the flexibility of interpretation of the various features of the Texture Profile Analysis (TPA) curves by an experienced operator was accomplished by placing the Instron re- corder charts ouer a digitizer interfaced to a computer. The digitizer provides a 14″× 14″ digitizing area with a resolution of 100 lines per inch. The operator guides a cursor over the TPA curve and the com- puter records X and Y coordinates in units of 0.01 in. A trigger on the cursor allows the operator to select designated foxes, distances and areas to be used by the computer in subsequent calculations of TPA parameters. Correlation coefficients between manually measured TPA parameters and computer-assisted readout of the same force-distance curues using apples, carrots, cream cheese, frankfurters and pretzel sticks were generally higher than r = 0.99.     

TEXTURE OF FRESH-PACK WHOLE CUCUMBER PICKLES: CORRELATION OF INSTRUMENTAL AND SENSORY MEASUREMENTS*

Correlations were determined between Texture Profile Analysis parameters of brittleness, hardness or total work of compression obtained with the Instron testing machine and sensory responses of firmness or crispness in evaluating texture of fresh-pack processed whole cucumbers (1-in. diam) of three ‘firm’ pickling cultivars (Explorer, Chipper, GY 3), two ‘soft’ pickling cultivars (Green F, Mincu) and a parthenocarpic slicer (MSU 6902 G). Further, correlations were determined between the TPA parameters and Magness-Taylor fruit pressure test (FPT) firmness. TPA hardness and total work correlated well with sensory responses; FPT firmness correlated satisfactorily with sensory firmness. Mean textural values from the various methods were compared with those obtained in the same manner for raw cucumbers. TPA brittleness tended to disappear in the processed fruit. Processing reduced mean TPA values across the six varieties to 35-58% of raw fruit values; it decreased mean FPT firmness to only 88%.     

TEXTURE OF SALT STOCK WHOLE CUCUMBER PICKLES: CORRELATION OF INSTRUMENTAL AND SENSORY MEASUREMENTS*

Correlations were determined between Texture Profile Analysis (TPA) parameters of brittleness, hardness or total work of compression obtained with the Instron testing machine and sensory responses of firmness or crispness in evaluating texture of fermented salt stock whole cucumbers (1-in. diam) of three ‘firm’ pickling cultivars (Explorer, Chipper, GY 3), two ‘soft’ pickling cultivars (Green F, Mincu) and a partheonocarpic slicer (MSU 6902 G). Correlations were also determined between the TPA parameters and Magness-Taylor fruit pressure test (FPT) firmness. Correlations were good between TPA parameters and FPT firmness. Correlations were poorer between instrumental and sensory methods due largely to inordinately high sensory scores assigned to salt stock of the slicer by all panelists. Mean textural values from the various methods were compared with those obtained in the same manner for raw cucumbers. TPA brittleness tended to disappear in salt stock. Processing reduced mean TPA values across the six varieties to 39-86% of raw fruit values. Mean FPT firmness was relatively unchanged at 99% that of raw fruit. Desalting from 16% down to 8 % or 4% NaCl reduced TPA values but increased FPT firmness.     

BI-CYCLICAL INSTRUMENT FOR ASSESSING TEXTURE PROFILE PARAMETERS AND ITS RELATIONSHIP TO SENSORY EVALUATION OF TEXTURE

The most popular instrumental imitative test is the Texture Profile Analysis (T.P.A.). It was originated in the General Foods Laboratories (Szczesniak et al. 1963) and adapted to the Instron by Bourne (1978). T.P.A. involves a double compression test that uses flat plates attached to an Instron Universal Testing Machine (I.U.T.M.). Several instrumental parameters can be extracted from the force/deformation curve generated by the test (e.g. hardness, cohesiveness, springiness, and chewiness). Recently developed in our laboratory, the Bi-cyclical Instrument for Texture Evaluation (B.I.T.E. master) uses the I.U.T.M. to generate its motion and features a set of artificial dentures as well as a tri-dimensional movement simulating a chewing motion. Five parameters were extracted from the force/deformation curve to evaluate their potential use for the prediction of cohesiveness.     

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.     

TEXTURE OF TABLE OLIVES AND PIMENTOS

Mechanical and chemical methods applied to quantifying the texture of table olives and pimientos are reviewed, and examples are given of studies on factors affecting the texture of these products (such as fruit maturity and processing) in which these methods have been used. The four instruments found applicable to olives are: Christel Texturometer, FFL Penetrometer, IG Texturometer and Kramer Shear Press (compression and shear/compression cells). The latter has also been used with pimientos. Advantages and disadvantages of each are discussed. Additional work is needed on correlating the mechanical tests with sensory evaluation. The chemical methods involve quantification of pectic substances and their degradation products.     

COMPARISON OF TWO INSTRUMENTAL METHODS WITH SENSORY TEXTURE OF PROTEIN GELS2

The textural attributes of 8 different heat-induced protein gel preparations evaluated by torsion failure testing and Instron texture profile analysis (TPA) were compared to sensory ratings by a trained texture profile panel. The gels presented a wide range of textural properties as determined by the instrumental and sensory parameters. Among the instrumental parameters, true shear strain at failure was the most frequent and significant predictor of sensory notes. Initial shear modulus and 50% compression force had the poorest correlations with sensory notes. Comparison of the two instrumental tests produced high correlations between shear stress at failure and TPA hardness; true shear strain at failure and TPA cohesiveness; and, initial shear modulus and 50% compression force. High correlations were also observed among various panel notes. Canonical correlation analyses showed that sets of linear combinations of parameters from each one of the 3 tests (torsion, TPA or sensory) were highly correlated to sets from either of the other two. Regression equations relating each of the instrumental tests to sensory notes were developed. Of the torsion failure parameters, the logarithm of true shear strain most commonly appeared in the equations. Of the TPA parameters, cohesiveness and its logarithm were the terms that were most frequent. High R² values were obtained for regression equations developed for predicting torsion failure parameters based on TPA parameters.     

INSTRUMENTAL TEXTURE PROFILE ANALYSIS OF PECANS OF VARIOUS OIL AND MOISTURE CONTENTS AFTER FREEZING TREATMENTS

Freezing of pecans is done to maintain flavor but has a lesser-known effect on other quality factors such as texture. Pecans were frozen by various methods, thawed and tested for texture by 50% compression of 3-mm dia. × 5-mm long cylinders. The Texture Profile Analysis (TPA) parameters, which were, affected most were fracturability, hardness and Area 1. The most extreme, slowest and fastest, freezing rates produced similar TPA values and were different from intermediate freezing rates that simulate commercial cold storage practices. The effect of the various freezing treatments on texture was similar for full-oil and reduced-oil pecans and for those sprayed or not sprayed with water.     

TEXTURE PROFILE ANALYSIS OF PROCESSED FOODS USING THE TENSIPRESSER AND THE MULTI-POINT MENSURATION METHOD

This paper reviews a considerable amount of research that has been performed in Japan on the development and application of a modified Texture Profile Analysis (TPA) system using a new instrument. Most of this work has heretofore only been available in Japanese. The Tensipresser is an instrument that has some special features that allow it to perform TPA rather easily. The multi-point mensuration method is a form of TPA that uses several variable degrees of compressions or bites on each piece of food. In ordinary work, two successive compressions or bites at predetermined clearances are applied to the sample. It is shown that the type of compressing or biting plunger plays an important role i n the shape o f the TPA curve. Examples of the use o f the Tensipresser and the multi-point mensuration method are given using breads and other baked goods, cooked rice, bean curd, pudding, sweet potato, noodle dough and cooked noodles.     

PREDICTION OF TEXTURE IN GREEN ASPARAGUS BY NEAR INFRARED SPECTROSCOPY (NIRS)

NIR spectroscopy was used to estimate three textural parameters of green asparagus: maximum cutting force, energy and toughness. An Instron 1140 Texturometer provided reference data. A total of 199 samples from two asparagus varieties (Taxara and UC‐157) were used to obtain the calibration models between the reference data and the NIR spectral data. Standard errors of cross validation (SECV) and r² were (5.73, 0.84) for maximum cutting force, (0.58, 0.66) for toughness, and (0.04, 0.85) for cutting energy. The mathematical models developed as calibration models were tested using independent validation samples (n =20); the resulting standard errors of prediction (SEP) and r² for the same parameters were (6.73, 0.82), (0.61, 0.57) and (0.04, 0.89), respectively. For toughness, substantially improved r² (0.85) and SEP (0.36) when four samples exhibiting large residual values were removed. The results indicated that NIRS could accurately predict texture parameters of green asparagus.     

EFFECT OF MANNITOL TREATMENT ON ULTRASOUND EMISSION DURING TEXTURE PROFILE ANALYSIS OF POTATO AND APPLE TISSUE

An ultrasound acoustic emission (AE) signal was recorded during texture profile analysis (TPA) of potato and apple tissue with different texture. The acoustic sensor was in contact with the sample through solid medium. Texture of the tissue was controlled by soaking it in different mannitol solutions. Both TPA and AE parameters change with the texture of potato and apple samples. However, correlation coefficients of linear regression of acoustic parameters are higher than TPA parameters and all of them are significant at a higher confidence level. Critical stress and strain indicate micro‐cracking of the material and they increase with decreasing tissue turgor. The ratio of the critical stress to hardness allows an analysis of sound duration. The sound lasts longer when the tissue is more turgid as a result of the decrease of critical stress to hardness ratio. Counts of AE recorded in the whole TPA test decreased logarithmically with tissue osmolality. The article showed that contact AE can be used for texture evaluation of potato and apple tissue.     

GENERAL FOODS TEXTURE PROFILE REVISITED-TEN YEARS PERSPECTIVE

The history of the development of the GF Texture Profile is traced and modifications introduced since it was first published are reported. The method is based on the recognition that texture is a multi-dimensional attribute. While the method is widely accepted, criticisms have been made which are acknowledged and answered. The present day status with respect to applications to both sensory and instrumental measurements is briefly summarized.     

SOME EXPERIENCES WITH THE GENERAL FOODS TEXTUROMETER*

Abstract As part of a programme of investigation into the effects of processing on the texture of food the General Foods Texturometer was adopted, because it appeared to offer versatility, multiple-property determination and a fair degree of objectivity. Preliminary investigations with the instrument indicated a high degree of reproducibility when used on a ‘recoverable’ material (rubber). The results are highly dependent on the dimensions of the sample and reproducibility decreases somewhat with increasing hardness of material under test. The ‘representativeness’ of the results for a range of food materials varied widely, being influenced by the uniformity of the material and the accuracy with which samples can be prepared. Experiments to correlate the results from this instrument with those from the Instron Universal Testing Machine, the Kramer Shear Press and a subjective panel method indicate that the Texturometer ‘hardness’ might prove the most useful measure of the firmness/hardness of foods as judged subjectively. None of the other textural properties measured by the Texturometer in this work proved of value in indicating subjective textural characteristics and further study of such properties is currently in progress.     

GENERAL FOODS TEXTUROMETER APPLICATION TO FOOD TEXTURE RESEARCH IN JAPAN

Applications of the General Foods Texturometer to food research in Japan are reviewed based mainly on information published in Japanese scientific journals. The instrument is being used on various food items such as rice, fish, soybeans, gels, meat, cheese and spaghetti. Correlations with sensory evaluation, development of a similar apparatus for crispness characterization of vegetables and new interpretation of Texturometer parameters are also discussed.     

TEXTURE IMPROVEMENT OF FRESH-PACK DILL PICKLES BY ADDITION OF LACTOSE AND SUCROSE

The influence of small amounts of lactose or sucrose on texture of fresh-pack dill pickles was evaluated by Instron texture profile analysis (TPA). Pickles were prepared with 0, 2, 4 and 6% by weight of either lactose or sucrose in a commerical brine. After equilibration of pickles with brine (30, 64 and 77 days), TPA values were obtained for brittleness, hardness, elasticity and total work of compression. Analysis of variance for the linear regression showed significant relationships between TPA values and sugar concentration. A minimum of 6% sugar is considered necessary for meaningful texture improvement. Sensory evaluation showed that sweetness may be detectable at the 4% and 6% sucrose levels. The presence of lactose was not objectionable at these levels.