This paper presents a novel methodology based on semistatic nondestructive testing of fish for the analytical computation of its textural characteristics via closed-form mathematical expressions. The novelty is that, unlike alternatives, explicit values for both stiffness and viscoelastic textural attributes may be computed, even if fish of different size/weight are tested. Furthermore, the testing procedure may be adapted to the specifications (sampling rate and accuracy) of the available equipment. The experimental testing involves a fish placed on the pan of a digital weigh scale, which is subsequently tested with a ramp-like load profile in a custom-made installation. The ramp slope is (to some extent) adjustable according to the specification (sampling rate and accuracy) of the equipment. The scale’s reaction to fish loading, namely, the reactive force, is collected throughout time and is shown to depend on the fish textural attributes according to a closed-form mathematical formula. The latter is subsequently used along with collected data in order to compute these attributes rapidly and effectively. Four whole raw sea bass (
Texture of fish is one of the principal characteristics indicative of its quality. Alterations of texture depend on many endogenous parameters including the species, sex, genetic background, and maturity. Texture is also affected by exogenous parameters such as the fish dietary history, aquaculture management in case of farmed fish, and fish handling during both slaughtering and postmortem [
The evaluation of fish texture by non-destructive techniques is mainly performed via specific organoleptic methods. These are essentially based on human sensory perception to evaluate texture and, thus, involve a degree of human subjectivity. Other alternatives for the nondestructive evaluation of texture include various indirect methods based on electric stimulation [
By the past, effort has been invested in achieving the nondestructive assessment of fish hardness by means of commercially available instruments such as the Zwick hardness tester. The instrument applies static pressure on the tissue (fish fillet) and the hardness value is determined after dwell times of 1 or 3 seconds. Moreover, attempts to map hardness variations to changes in fish freshness were also carried out in Schubring [
Other attempts to estimate variations in mechanical properties of fish (stiffness and viscoelastic characteristics) and relate them to its freshness level may be found in Grigorakis and Dimogianopoulos [
The proposed methodology innovates in two ways. First, it establishes the theoretical link between fish mechanical properties (stiffness and viscoelastic characteristics, which are relevant to its textural attributes) and the data collected from the fish nondestructive testing. This link consists in a closed-form mathematical formula, which relates the mechanical properties (and, hence, textural attributes) to experimental data in an explicit manner, independently of the fish weight. Second, it allows for a more flexible testing procedure via the use of a potentially semistatic loading profile. As will be shown in Materials and Methods, the testing procedure involves the application of a ramp-like load onto the fish, the slope of which is (to some extent) configurable according to the accuracy/sampling rate of the test equipment.
The benefit of these innovations lies in the fact that, contrary to all indirect methods found in previous works [
The paper is organized as follows. In Introduction, a quick overview of the proposed methodology and its positioning with respect to other texture assessing schemes is given. In Materials and Methods, details are given on the tested fish, the testing procedure is explained, and the theoretical framework for the computation of the texture-related mechanical quantities is presented. In Results and Discussion, the application of the methodology on four whole raw sea bass (
European sea bass (
The testing procedure involves a digital weigh scale (electronic force gauge), which can measure force exercised on its pan throughout time and store these values in a file readable by a personal computer. The fish is placed on the scale pan and a load of ramp-like profile is exercised on its dorsal area (Figure
(a) The testing structure involving the fish, scale, conical tube support secured by fixed rods, and water supply; (b) the Kelvin-Voigt model of the fish.
The pan’s response in form of reactive force
The fish, placed on the pan of the weigh scale, is represented by the Kelvin-Voigt model shown in Figure
According to the Kelvin-Voigt model, the fish mass
In the current case, applying an external load
The weigh scale pan is solidly placed on the ground and is not deformable, thus forming one group upon which the fish is set. That means that the group of pan-and-ground receives the forces from the spring and damping elements and responds with an equal but opposite force
Hence, one may proceed by defining the characteristic quantities of second-order systems [
A brief outline of the steps required for the computation of constants A fish placed on the pan is tested with a known ramp-like load Each of the values Using curve-fitting algorithms (commonly available in software packages like MATLAB(R)), suitable values for By means of (
Given that four fish are tested by means of the proposed methodology, four sets of measurements are involved. Each set includes forty data values of reactive force and consequently forty values for
The postmortem spoilage process has indeed a significant effect on the mechanical properties of fish.
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7mc |
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The post hoc grouping of the four fish appears in Table
The values obtained for the standard deviation point to the current limitation of the proposed methodology, which is primarily related to a purely technical matter: the way that the load is applied onto the fish. The main concern is to ensure that water filling of the tube is done in the same way under all circumstances, with water level rising in a steady manner. The latter is, currently, the subject of fine-tuning efforts towards obtaining better accuracy and repeatability of testing conditions. Such improvements would result in easier discrimination between samples of different texture properties, like, in this case, between samples of 1 day and 7 days of ice storage.
Finally, given that the total reactive force includes forces due to both
It is known that fish, and sea bass in particular, becomes softer and less elastic after rigor mortis resolution, which occurs in about 6 days postmortem when stored in ice [
It is important to note that the hardness force measured corresponds to the total reactive force in the proposed methodology in (
In [
Note also that since the first sampling occurred in day 1 postmortem, the onset of rigor mortis is in progress according to findings in Molina et al. [
A nondestructive methodology using semistatic test loading of fish in order to analytically compute textural attributes (relevant to fish stiffness and viscoelasticity) has been presented. The testing procedure may be (to some extent) configured in order to suit the specifications (sampling rate and accuracy) of the available equipment. Under conditions, this loading procedure may also highlight similarities between specific textural results obtained via the proposed method and TPA. The testing involves a fish placed on the pan of a digital weigh scale, a ramp-like load applied onto it by means of a simple custom-made installation, and the recording of reactive force measured by the scale throughout time. It is demonstrated that the reactive force depends upon the texture-related mechanical quantities of the fish via a closed-form mathematical formula. This is, hence, used along with the data collected for a tested fish in order to compute the texture-related mechanical quantities in a rapid and efficient manner. Four whole raw sea bass (
The views expressed in this work are the sole responsibility of the authors and do not necessarily reflect the views of the European Commission.
The authors declare that there are no competing interests regarding the publication of this paper.
This study was funded by the European Union (ARRAINA, FP7-KBBE-2011-5-288925, Advanced Research Initiatives for Nutrition and Aquaculture).