OPTIMIZATION OF THE COMPOSITION OF A MIXTURE OF SELECTED ADDITIVES IN THE PRODUCTION OF RAW SAUSAGES

Agnieszka Bilska
Institute of Meat Technology, University of Life Sciences in Poznań, Poland

ABSTRACT

The aim of the study was to determine an optimal composition of a mixture of selected additives: isoascorbic acid, sodium ascorbate and glucon-delta-lactone – GDL, in order to obtain a product with an appropriately high consumer quality in a given time. It was also observed that the application of optimal amounts of isoascorbic acid, sodium ascorbate and glucon-delta-lactone makes it possible to obtain the maximum score for overall acceptability already after 10 days of storage. The application of isoascorbic acid, sodium ascorbate and glucon-delta-lactone in arbitrarily selected amounts may result in a significant deterioration of quality. It was also found that the developed methodological and mathematical procedure facilitates a faster and cheaper determination of an optimal composition of a mixture of additives (especially that containing many additives) than using the trial and error method.

Key words: quality, sensory, examination, optimization, raw sausage, isoascorbic acid, sodium ascorbate, glucon-delta-lactone, additives.

INTRODUCTION

Quality of raw sausages is dependent on the raw material used in their production, the type and amounts of applied additives, parameters of technological processes and interactions of the above factors during production and post-production storage [9, 10]. The possibility of predicting the time, during which quality of food products remains satisfactory, is of great importance. Most solutions applied at present are based on the assumption that changes in quality are subjected to the zero-order reaction and that the coefficient of changes in time is constant at constant temperature. Such an approach is useful and in selected cases makes possible a correct estimation of quality stability. Parameters, changing during storage (including microbial and organoleptic parameters), need to be verified during storage testing [4]. They may be divided into two classes of variables: the control variable and the original variable. The control variable (independent variable) is such a process parameter, which is found during technological processing and which may affect its value. Examples here include temperature, mixing rate, duration of the process or the content of a component in the mixture. The original variable (dependent variable) is a parameter concerning the final product, i.e. product colour, consistency, yield or costs of producing one ton of a given product [1, 2, 3].

Using the small steps approach, of certain slight changes in control variables, we may obtain an optimal system of original variables, equivalent to the achievement of three possible types of goals. These objectives may include:

• Maximization of an advantageous characteristic of the final product;

• Minimization of a disadvantageous characteristic (e.g. minimization of manufacturing costs);

• Achieving the target value of one of the original variables defining quality [3].

AIM AND SCOPE OF THE STUDY

The aim of the study was to determine an optimal composition of a mixture of additives: isoascorbic acid, sodium ascorbate and glucon-delta-lactone – GDL, in order to obtain a product with an appropriately high consumer quality in a given time.

MATERIAL AND METHODS

Experimental material consisted of raw sausage with a brand name of “Bydgoska”, produced in the Pilot Plant of Institute of Meat Technology at the Agricultural University of Poznań. In the investigation the following additives were applied: isoascorbic acid (KA), sodium ascorbate (AS) and glucon-delta-lactone (GDL) (Table 1). The reference sample was sausage with no additives (sample “0”).

Sausages were stored at the temperature of approx. 10°C for 30 days. During storage of experimental sausages samples for analyses were collected 7 times. Changes in sausage quality during storage were determined on the basis of consumer sensory examination. The following attributes were assessed using a 5-point score method: appearance and external colour, colour at cross-section, aroma, taste, consistency, saltiness and overall acceptability [PN-ISO 5492:1997, PN-ISO:1998, PN-ISO 4121:1998, PN-A 82007/A1:1998]

All results (from two series) were subjected to statistical analysis. The analysis of variance and regression analysis were performed at the level of significance α = 0.05.

Results were interpreted using the response plane method, which makes it possible to determine the dependence between analyzed factors. It was conducted, on the basis of the determination of coefficients of a quadratic equation of the following form:

y = A₀ + aX₁ +bX₂ + cX₃ + dX₁² + eX₂² + fX₃² + gX₁X₂ + hX₁X₃ + iX₂X₃

where:
y – dependent variable (original variable),
X₁, X₂, X₃ – levels of independent factors of the experiment (control variable),
a, b, ... – coefficients of quadratic equation.

The general fit of the model was inferred on the basis of the coefficient of determination R², while the significance of variation in case of individual parameters of equations were inferred on the basis of the F test.

Calculations were performed using Microsoft Excel 2000, STATISTICA 6.0 and STORM software.

DISCUSSION AND RESULTS

Testing results obtained in the experiment were subjected to statistical analysis. A two-way analysis of variance was conducted, where the source of variation was storage time and the type of model sausage (variable amounts of applied additives). Table 2 lists significance indexes for the analyzed dependencies.

It results from data presented in Table 2 that storage time had a statistically significant effect on all the analyzed attributes of sensory quality. In turn, the amount and type of applied additives had a significant effect on acceptability and intensity of colour at cross-section, consistency, taste and overall acceptability.

The attribute of consumer quality, combining the assessment of all the other attributes, is overall acceptability of the product. For this reason the optimization procedure is presented using this attribute as an example.

The conducted analysis showed that storage time and the amounts of applied additives had a statistically significant effect on overall acceptability of experimental sausages. Figure 1 presents the effect of storage time on changes in overall acceptability of experimental sausages.

In the sample with no addition of sodium ascorbate, isoascorbic acid and glucon-delta-lactone (sample “0”) no significant changes were observed in the first 10 days after production. Only a longer storage had a negative effect on the assessment of this attribute. Overall acceptability in the other sausages was improving until day 13 after production. The extension of storage time, to day 30 after the completion of production caused a deterioration of point scores for model sausages. However, each variant of the mixture of additives ensured that during storage a higher score than that of the control sample was given to the model sausage.

In order to determine the optimum composition of a mixture of additives and the product with an appropriately high consumer quality, the obtained results were subjected to further mathematical analysis.

The cycle of calculations was initiated by the determination of regression combining all the additives investigated in this study and storage time (equation 1).

p = 5.498*10^-8, R² = 0.795

A quadratic equation was obtained, in which the score (dependent variable – y) is described by four independent variables (additives and time). The equation may be the basis for the optimization calculations facilitating an optimal selection of analyzed additives.

Next the objective of optimization is defined and in most cases it is to obtain the best possible score,

y max, for the assumed storage time (t = const.)

As the sample of calculation a 10-day product aging (t = 10 days) was selected for the above optimization analysis. At medium-length and long-term aging starter cultures are used to acidify sausage batter. In contrast, at short-term aging, during which the product is ready-to-eat already 10 days after the completion of the production process, acidification of sausage batter is performed using the microbial or chemical methods and in that case additives affecting the concentration of hydrogen ions in the system have a significant technological effect.

At the assumption that t = 10 days the above equation (1) takes the form:

At the same time possible limitations of the amounts of additives (resulting from the binding regulations) need to be taken into consideration. In case of the analyzed additives these limitations are as follows:

0 < sodium ascorbate < 0.5 [g/kg batter],
0 < isoascorbic acid < 0.5 [g/kg batter],
0 < glucon-delta-lactone < 5.0 [g/kg batter].

Next appropriate calculations were performed using the computer optimization software. The highest scores for overall acceptability were given to three mixtures of sodium ascorbate, isoascorbic acid and glucon-delta-lactone (Table 3).

As it can be seen, for one quality attribute, in this case overall acceptability, three quantitative sets of additives may be applied. A similar situation may be repeated at calculations for the other attributes. Thus, it is rather understandable that the selection of one composition of the mixture, which would be optimal for all attributes, must be very difficult to attain.

The process of searching for such a solution may be facilitated by the application of appropriate mathematical procedures (minimization of the sum of deviations or deviation squares).

However, usually it is sufficient to select attributes with the highest impact on the assessed quality of the product. In case of the analyzed sausages this may be overall consumer acceptability, the acceptability and intensity of colour at cross-section, taste or consistency. It is possible to apply a simple tabular graphic method. We select a quality parameter, e.g. colour intensity, and calculate the optimal composition of a mixture of additives. Next we verify how a given mixture, optimal from the point of view of colour intensity, would affect the other quality attributes (taste, consistency, etc.). The whole procedure is repeated successively for all the significant quality parameters. Table 4 lists expected values of scores for quality attributes for optimal, calculated amounts of additives.

As it can be seen in case of mixtures 7 and 8, expected values of scores for all attributes amounted to at least 5 points. This means that these mixtures are optimal for the high consumer examination scores of model sausage assessed on the 10th day after production. At the same time it means that flavour is the most significant attribute in the assessment of quality of analyzed sausages.

However, in practice it is sufficient if this score is lower, but remains at a specific level, e.g. at least 4.5 points. This condition is met also for mixtures no. 1 and no. 9. In case when we decide the score of at least “good” is sufficient, we may use any mixture no. 1 to 10.

In a situation when we have several mixtures with an equal, good effect, an additional optimization condition may be the minimization of price.

The above table (4) contains also an example of mixture no. 11, for which very negative values of expected consumer examination scores were obtained. This example indicates a danger connected with an arbitrary selection of mixtures of technological additives.

CONCLUSIONS

1. In the conducted investigations it was observed that the quality of analyzed sausages at a simultaneous application of isoascorbic acid, sodium ascorbate and glucon-delta-lactone has a significant effect on storage time as well as the amounts of applied additives, especially their ratios.

2. The application of optimal amounts of isoascorbic acid, sodium ascorbate and glucon-delta-lactone makes it possible to obtain the maximum score for overall acceptability already after 10 days of storage.

3. The application of isoascorbic acid, sodium ascorbate and glucon-delta-lactone in arbitrarily selected amounts may result in a significant deterioration of quality.

4. The developed methodological and mathematical procedure facilitates a faster and cheaper determination of an optimal composition of a mixture of additives (especially that containing many additives) than using the trial and error method.

REFERENCES

1. Bilska A., 2006. The effect of the addition of isoascorbic acid and sodium ascorbate on sensory quality of raw sausage. Acta Sci. Pol., Technol. Aliment. 5(1), 143-154, www.food.actapol.net/pub/12_1_2006.pdf.

2. Darewicz M., Dziuba J., 2005. Advanced statistical methods as a new tool for data analysis in food and nutrition science. Acta Sci. Pol., Technol. Aliment. 4(1), 17-25, www.food.actapol.net/pub/2_1_2005.pdf.

3. Kitzman P., 2005. Optymalizacja procesów technologicznych metoda simpleksów [Optimization of technological processes using the simplex method]. Gosp. Mięs. 5, 14-22 [in Polish].

4. Kołożyn-Krajewska D., 1995. Gwarantowana jakosc mikrobiologiczna żywnosci a metody predyktywne [Guaranteed microbial quality of food and predictive methods]. Żywn. Techno. Jakosc 2(3), 53 [in Polish].

5. PN-ISO 5492:1997. Analiza sensoryczna. Terminologia. [Sensory analysis. Terminology] [in Polish].

6. PN-ISO:1998. Analiza sensoryczna. Metodologia. Wytyczne ogólne [Sensory analysis. Methodology. General guidelines. [in Polish].

7. PN-ISO 4121:1998. Analiza sensoryczna. Metodologia. Ocena produktów żywnosciowych przy użyciu metod skalowania [Sensory analysis – Methodology – Evaluation of food products by methods using scales] [in Polish].

8. PN-A 82007/A1:1998. Przetwory mięsne. Wędliny. [Meat products. Sausages] [in Polish].

9. Pyrcz J., Kowalski R., Konieczny P., Danyluk B. 2005. The quality of fermented raw sausages manufactured using porcine blood plasma. EJPAU, Food Sci. Technol. 8(3), www.ejpau.media.pl.

10. Schnäckel W., Reuter T., Wiegand D., 2000. Rohe Fleischerzeugnisse ohne NPS [Raw meat products without NPS]. Fleischwirtschaft 1, 35 [in German].

Accepted for print: 25.01.2007

Responses to this article, comments are invited and should be submitted within three months of the publication of the article. If accepted for publication, they will be published in the chapter headed 'Discussions' and hyperlinked to the article.