Dinkum Journal of Medical Innovations (DJMI)

Publication History

Submitted: July 15, 2024
Accepted:   July 25, 2024
Published:  July 31, 2024

Identification

D-0297

Citation

Tanka Bhattarai (2024). Optimization of Vegetables Proportion in Emulsion Type Chicken Sausage & Study on Its Storage Stability. Dinkum Journal of Medical Innovations, 3(07):533-549.

Copyright

© 2024 The Author(s).

Optimization of Vegetables Proportion in Emulsion Type Chicken Sausage & Study on Its Storage StabilityOriginal Article

Tanka Bhattarai 1 *, Babita Adhikari Dahal 2, Bikram Limbu 3, Dinesh Subedi 4, Sangam Dahal 5, Samrita Shakya 6

  1. Central Department of Food Technology, Institute of Science and Technology, Tribhuvan University, Nepal.
  2. Central Department of Food Technology, Institute of Science and Technology, Tribhuvan University, Nepal.
  3. Central Department of Food Technology, Institute of Science and Technology, Tribhuvan University, Nepal.
  4. Central Department of Food Technology, Institute of Science and Technology, Tribhuvan University, Nepal.
  5. Central Department of Food Technology, Institute of Science and Technology, Tribhuvan University, Nepal.
  6. Central Department of Food Technology, Institute of Science and Technology, Tribhuvan University, Nepal.

* Correspondence: tankabhattarai55@gmail.com

Abstract: Sausages are one of the oldest processed foods known to man. Several hundreds of varieties of sausages are produced worldwide with outstanding social and economic relevance. Sausage making has a rich history in most cultures. Sausage was a way to store meat for extended periods when mechanical refrigeration was unavailable. Today, the combination of meat and seasonings produces a broad type of sausages and generates different categories from fresh, smoked, cured, and cooked sausages. The wide variety of sausages is due to differences in composition, shape, size, and cultural preferences and traditions. This study was conducted with an objective of optimizing vegetables proportion in emulsion type chicken sausage and evaluation of storage stability. The primary screening process was conducted in the first phase with various percentages (10%, 20%, 30% and 40%) of vegetables on the basis of sensory evaluation and physicochemical properties of the prepared sausage. 30% formulation was selected from primary screening and 11 runs were generated from D-optimal mixture design. In second phase, the best percentage formulation was carried out on the basis of sensory evaluation and physicochemical properties which was then further analyzed for proximate composition, carotenoids content and antioxidant properties. The final phase of the study was carried out on storage stability of optimized sausage samples at -2°C in polyester based films (PET). Finally, optimized product was compared on the basis of sensory score with chicken sausage (control) available in market. The optimized product from sensory analysis has a proximate composition of 60.47%, 11.89%, 17.55%, 0.43% and 4.17% moisture, crude fat, crude protein, crude fiber and total ash respectively. The carotenoid content of the superior product was found to be 30 μg/ 100 g and DPPH radical scavenging activity of sausage was found to be 46.76%.There was a gradual increase in Total plate count (TPC) reaching maximum in day 18 (9 log/cfu) while salmonella and coliform were not detected up to day 18. Peroxide value was also found to be increase during refrigeration storage of sausage from 3.05 MeqO2/kg at day 0 and 11.46 MeqO2/kg in day18.The expected output for the development of vegetable incorporated chicken sausages was successfully developed by incorporating vegetables in the formulation without any deteriorating effect on the sensory attributes and acceptability of the product. The results probably suggest that vegetables used are potentially useful in improving the nutritional quality and exhibiting some antioxidant properties in chicken-based sausage-like product.

Keywords: optimization of vegetables, emulsion type, chicken sausage

  1. INTRODUCTION

Sausages are one of the oldest processed foods known to man. Several hundreds of varieties of sausages are produced worldwide with outstanding social and economic relevance [1]. Sausage making has a rich history in most cultures. Sausage was a way to store meat for extended periods when mechanical refrigeration was unavailable [2]. Today, the combination of meat and seasonings produces a broad type of sausages and generates different categories from fresh, smoked, cured, and cooked sausages. The wide variety of sausages is due to differences in composition, shape, size, and cultural preferences and traditions [3].Healthier meat-sausage formulations need to contain less saturated fat and/or promote the presence of specific healthy compounds as they affect the quality attributes of cooked meat emulsions [4]. Fibers in the form of vegetables and fruits have been found successful in improving functional value, enhancing cooking yield and improving texture of the products besides reducing the formulation [5]. High-fiber foods tend to reduce the risk of colon cancer, obesity, cardiovascular diseases and several other disorder [6]. Several studies have proven that dietary fibers have the potential to reduce blood low density lipoprotein cholesterol in blood, risk of diabetes mellitus type 2, coronary heart disease, blood pressure, obesity and colorectal cancer [7]. Thus, an increase in the level of dietary fiber in the daily diet has been recommended by several scientific organizations (Eastwood, 1992). Solubility, water binding, swelling, viscosity, gelation and surfactant properties are important functional properties of soy proteins in meat and dairy based systems [8]. Comminuted meats (sausage, bologna, luncheon meats) usually contain more fat than normal meat, hence soy proteins are used to enhance and stabilize fat emulsion, improve viscosity, impart texture upon gelation following cooking and improve moisture retention and overall yields (Jideani, 2011). Nitrite can cause the formation of carcinogenic nitrosamines in cured products due to its reaction with secondary amines and amino acids in muscle proteins. Residual nitrite in cured meats may form N-nitrosamines in the gastrointestinal tract Thus, the meat industry continues to search for alternative methods to produce nitrite-free meats that maintain the color characteristics of nitrite cured meat products [9]. Processed chicken meats are generally manufactured with the addition of various food additives for improvement of shelf life and sensorial properties and for convenience. Sodium chloride is an essential ingredient of processed meats because of its multiple roles [10]. Generally, processed meats contain 7–39 g/kg sodium chloride. Nevertheless, the high concentration of sodium in processed meats is considered a health risk factor because high intake of dietary sodium increases the risks [11].The winter mushrooms are popular edible mushroom and widely cultivated in many Asian countries [12]. Various studies have shown that the winter mushroom has several biological functions such as anticancer and anti-inflammatory effects [13]. Various studies have revealed the water-binding effect of dietary fiber in processed meat. Furthermore, the increase of pH in pork meat batter with the addition of winter mushroom powder was recently reported [14]. The winter mushroom contains various flavor precursors such as free amino acids and nucleotides, which are the compounds responsible for the sweet and umami flavors of mushrooms [15].Lipid oxidation and microbial growth in meat products can be controlled or minimized by using either synthetic or natural food additives. Various synthetic antioxidants, such as butyrate hydroxyanisole (BHA) or butyrate hydroxytoluene (BHT), are commonly used to delay the development of rancidity in food products [16]. However, consumers are concerned about the safety of synthetic food additives. This concern has led to arouse a great interest in natural additives. Natural agents possessing antioxidant and antimicrobial properties have the advantage of being readily accepted by consumers, as they are considered natural. Garlic is one of the most commonly used ingredients as a flavor enhancement for sausage. In addition to flavoring the foods, garlic is appreciated for its medicinal properties [17].In this age, not only production of vegetables is being decreased but also loss of this is increased drastically. The reason behind of heavy loss is improper preservation of vegetable. As vegetable is highly prone to spoilage but it can be processed and incorporate to other processed product so that its nutrient value will be retained. Consequently, decrease the loss of vegetables. Many researches have been conducted to explore the feasibility of using non-meat ingredients to promote a healthier meat sausage product, emphasizing the physicochemical properties and sensory characteristics in relation to the addition of new ingredient [18].

  1. MATERIALS & METHODS

Mechanically Deboned Chicken Meat (MDCM) and three types of vegetables; soybeans, carrot and mushroom were purchased from a local market, Dhahran sub-metropolitan city, Sun sari, Nepal.  Instruments and equipment were provided by Central Department of Food Technology (CDFT) and all the process were carried out in pilot plant and laboratory of the department. Raw material during preparation was fresh and frozen. Chicken were brought from Ganga farm house, sub-metropolitan city. The lean meat was well trimmed. The trimmed lean meat thus, being practically free from sinews and gristle and entirely frees from ligament, bone and cartilage particles and finally chopped to 4 mm opening size using mincer and bowl chopper for 12 minutes .Fresh soybean seeds were used in the sausage preparation and the preparation of soybean flour was done as described .Fresh good quality mushroom was prepared before adding to the sausage as method described.

Preparation of soy flour.

Figure 01: Preparation of soy flour.

Preparation of Mushroom

Figure 02: Preparation of Mushroom

Preparation of carrot

Figure 03: Preparation of carrot

According to literature, corn starch which is relatively cheap and readily available for vast production was used as both binding and filling agent .Pepper, chilly, onion, garlic, turmeric and clove were used in powder foam and others cinnamon, cardamom and nutmeg were cleaned and ground to very fine past without remaining of fiber parts in paste.

Table 01: Preliminary screening for acceptability test of different vegetables incorporated sausage

Ingredients E (Control) A (10%) B (20%) C (30%) D (40%)
Meat (%) 100 90 80 70 60
Vegetable (%) 0 10 20 30 40
Fat (%) 20 20 20 20 20
Water (%) 10 10 10 10 10
Cornstarch (%) 8 8 8 8 8
Salt (%) 2.1 2.1 2.1 2.1 2.1
Sodium tri-phosphate (%) 0.5 0.5 0.5 0.5 0.5
Chili powder (%) 1.2 1.2 1.2 1.2 1.2
Pepper powder (%) 0.8 0.8 0.8 0.8 1.5
Turmeric powder (%) 0.2 0.2 0.2 0.2 0.2
Garlic (%) 0.9 0.9 0.9 0.9 0.9
Onion (%) 0.2 0.2 0.2 0.2 0.2
Clove (%) 0.5 0.5 0.5 0.5 0.5
Cardamom (%) 0.15 0.15 0.15 0.15 0.15
Cinnamon (%) 0.15 0.15 0.15 0.15 0.15
Nutmeg (%) 0.1 0.1 0.1 0.1 0.1

During preliminary screening, number of sausage formulations were prepared using different percentage levels of vegetables (10%, 20%, 30% and 40%) in equal proportion of vegetables in all level and control (100% chicken). From the selected percent level (30%), the numbers of combinations were obtained from the mixture; D-optimal design with 11 numbers of runs. Other ingredients added in the sausage processing were spices, water, fat, salt, additives and preservatives. Recipe used is shown in table 3.1.

Typical flow diagram of vegetable incorporated chicken sausage

Figure 04: Typical flow diagram of vegetable incorporated chicken sausage

The experiment was arranged as a design of experiment (DoE) in Design- Expert software, version 10. The screening process was conducted in the first step with various percentages (10, 20, 30% and 40%) of vegetables in the sausage formulations. The proportions of all the vegetables in all percent level were made equal. Based on sensory attributes and physicochemical characteristics (cooking loss, folding test, moisture retention and fat retention), optimized percent level of the vegetable incorporation was selected. From the selected percent level, the numbers of combinations were obtained from the mixture; D-optimal design with 11 numbers of runs to optimize the formulation of the product and desirability was calculated based on the effect of different responses.

Table 02: Formulation of sausage with 30% combination of vegetables

S.N Meat (70%) Combination of vegetables (30%)
Mushroom Soybean Carrot
1 70 0 15 15
2 70 22 0 8
3 70 15 15 0
4 70 5 5 20
5 70 0 15 15
6 70 10 10 10
7 70 15 0 15
8 70 5 20 5
9 70 15 15 0
10 70 22 8 0
11 70 15 0 15

 

  1. RESULTS & DISCUSSIONS

The present study was conducted to prepare vegetable incorporated chicken sausage. Three vegetables (mushroom, carrot and soybean) were used to replace 30% of meat in sausage preparation. Effect on different physiochemical analysis (cooking loss, folding test, moisture retention and fat retention) and sensory evaluation of the prepared sausage were studied. Sausage prepared without addition of vegetable was used as control for comparative analysis. Finally, the optimized formulation was obtained. Further, proximate analysis and sensory evaluation of the optimized formulation was carried out. Overall result and discussion are discussed in following headings.

Table 03: Proximate composition of incorporated vegetables

Parameters Soybean
(means)
Mushroom
(means)
Carrot
(means)
Moisture content (%) 9.26±0.01 89.89±1.88 89.89±1.88
Crude fat (%) 18.50±0.10 0.5±0.01 0.18±0.03
Protein (%) 27.0±0.05 9.92±0.01 0.38±0.09
Total ash(%) 4.60±0.02 1.20±0.03 3.38±0.01
Crude fiber (%) 0.43±0.02 0.57±0.10 0.38±0.38

*Values are the means of triplicate with standard deviation

The moisture content of soybean, mushroom and carrot was found to be 9.26±0.01, 89.89±1.88, and 89.89±1.88% respectively as shown in table 4.1. The difference in moisture content of soybean was found to be 1.19 and the value was 7.30% as reported by. The difference in value may be due to the processing methods. The moisture content in mushroom is in the range of 85-89%. Sausage prepared with mushroom will have high moisture content as the moisture content of mushroom is high.  The moisture content of carrot varies from 86-89% .Hence data was found to be similar. High Moisture content of carrot increases the moisture content of the carrot incorporated products. According to addition of dietary fiber increases the moisture content of meat emulsion systems, providing higher water retention and improves emulsion stability.

Table 04: Physicochemical analysis of different formulated sausage

Sample Folding test Cooking
loss (%)
Moisture retention (%) Fat
retention (%)
A (10%) 4 1.92 72.77 40.25
B (20%) 3 2.4 69.42 47.55
C (30%) 3 8.7 55.50 70.20
D (40%) 3 9.25 59.63 68.12
E (Control) 4 1.52 88.56 51.89

*Values are the means of triplicate

Table 05: Sensory evaluation of different formulated sausages

Attributes A B C D E p-value
Color 5.9a 7.3 b 7.4b 5.8 a 7.4 b 0.447
Flavor 5.8 a 6.2 b 7.5 c 7.6 b 8.0 b 0.148
Taste 5.4 a 6.3 b 7.4 c 5.6 a 7.8 c 0.072
Texture 7.3 a 7.6 ab 7.8 b 7.8 b 7.7 ab 0.238
Overall Acceptance 5.3 a 6.0 b 7.2 c 5.1 a 7.7 c 0.057

*Values are the means of triplicate

Table 06: Effect of responses with different formulation in experimental plan

Comp1 Comp2 Comp3 R1 R2 R3 R4
Run A: Mushroom B: Soybean C: Carrot Cooking
loss
Folding test Moisture retention Fat
retention
1 0 15 15 10.2 2 59.2 70.1
2 22 0 8 9.7 3 9.6 75.9
3 15 15 0 7.2 2 57.5 71.6
4 5 5 20 13.4 3 50.1 63.2
5 0 15 15 9.4 3 59 73.4
6 10 10 10 9.9 2 60.1 73.2
7 15 0 15 8.9 2 49.7 72.1
8 5 20 5 7.7 3 56.5 71.6
9 15 15 0 7.1 2 58.7 71.3
10 22 8 0 7.4 4 57.4 70.4
11 15 0 15 10.2 2 51.2 69.4

*Values are the means of triplicate

* Responses were measured in terms of cooking loss, moisture retention and fat retention in percent (%) and folding test in terms of scale that ranges from 1 to 4.

Table 07: ANOVA for Response cooking loss for mixture cubic and extra term model

Source       Sum of Square df Mean Square F-value P-value  
Model 26.35 2 13.18 13.09 0.0030 significant
Linear Mixture 26.35 2 16.18 13.09 0.0030
Residual 8.06 8 1.01
Lack of Fit 6.89 5 1.38 3.53 0.1640 Not significant
Pure Error 1.17 3 0.3900
Cor Total 34.41 10

The “Model F-value” of 1309 implies the model is significant. There is a only 0.30% chance that model F-value this large could occur due to noise. The lack of fit F-value of 3.53 implies the Lack of Fit is not significant relative to the pure error. Non-significant lack of fit is good; we want the model to fit .Values of “Probe> F” less than 0.0500 indicate model terms are significant. In this case A, B and C are significant model terms. Values greater than 0.1000 indicate the model terms are not significant. If there are many insignificant model terms, model reduction may improve the model.

Final equation in terms of actual components:

Cooking loss (%) = +0.248011*A +0.222476*B +0.460501*C

Where, A= Mushroom, B= Soybean, C= Carrot

Cooking Loss

Figure 05: Cooking Loss

The figure 05 shows the relationship between the different proportion of mushroom, soybean and carrot in the mixture with cooking loss in the sausage. The cooking loss values were found to be higher in sample with higher carrot percent. This could be due to formation of comparatively less stable emulsion in the formulations containing carrot also observed an increasing trend in the cooking loss of the chicken sausages with increasing levels of carrot. Increase in cooking loss was noticed up to 15% carrot incorporated turkey meat sausages as compared to control the figure indicates that cooking loss increases with increase in proportion of carrot. The product with higher amount of soybean has lower cooking loss which is favorable. The cooking loss of the desired product was 8.37% and the mushroom: soybean: carrot ratio was 20:5:5.

Table 08: ANOVA for folding test in mixture quadratic and extra term model

Source Sum of

square

Df Mean

Square

F-value P-value
Model 3.90 6 0.6508 3.160 0.0020 significant
Linear Mixture 0.1561 2 0.0780 0.3796 0.7064
AB 2.22 1 2.22 10.79 0.0304
AC 2.90 1 2.90 14.08 0.0199
BC 1.23 1 1.23 5.96 0.0710
ABC 1.58 1 1.58 7.69 0.0501
Residual 0.8225 4 0.2056
Lack of Fit 0.3225 1 0.3225 1.93 0.2584 Not significant
Pure Error 0.5000 3 0.1667
Cor Total 4.73 10

The Model F – value of 3.16 implies the model is significant. Values of Probe> F less than 0.0500 indicates model term are significant. In this case A, B, C, AB, AC are significant model terms. Values greater than 0.1000 indicate the model terms are not significant. If there are many insignificant model terms (not counting those required to support hierarchy), model reduction may improve the model as shown in the Figure 4.3.The Lack of Fit F-value of 1.93 implies the Lack of Fit is not significant relative to the pure error. Non – significant lack of fit is good; we want the model to fit.

Final equation in terms of L Pseudo component

Folding test = +8.42*A +7.10*B +8.11*C -22.45*AB-25.65*AC-20.42*BC+46.90*ABC

Where, A= Mushroom, B= Soybean, C= Carrot

 

Folding Test

Figure 06: Folding test

The 3-D plot shows the relationship between the different proportions of mushroom, soybean and carrot with folding test of the prepared sausage. The folding test score increases with increase in the proportion of soybean and mushroom while increase of carrot proportion decreases the score.

Table 09: ANOVA for fat retention in mixture quadratic and extra term model

Source Sum of square Df Mean square F-value P-value
Model 82.78 5 16.56 4.53 0.0040  significant
Linear Mixture 15.79 2 7.89 2.16 .2110
AB 0.1002 1 0.1002 0.0274 0.8750
AC 21.78 1 21.78 5.96 0.0586
BC 19.49 1 19.49 5.33 0.0690
Residual 18.29 5 3.66
Lack of Fit 9.15 2 4.58 1.50 0.3530 not significant
Pure Error 9.14 3 3.05
Cor Total 101.07 10

 

The Model F–value of 4.53 implies that there is a 6.15% chance that a Model F-value this large could occur due to noise. Values of Probe> F less than 0.0500 indicates model term are significant. In this case A, B, Care significant model terms. Values greater than 0.1000 indicate the model terms are not significant. If there are many insignificant model terms (not counting those required to support hierarchy), model reduction may improve the model.

The Lack of Fit F-value of 1.50 implies the Lack of Fit is not significant relative to the pure error. Non – significant lack of fit is good; we want the model to fit.

Final equation in terms of L Pseudo components:

Fat retention (%) = +74.04*A +68.44*B +40.90*C -3.54*AB+52.25*AC+65.66*BC

Where, A= Mushroom, B= Soybean, C= Carrot

 

Fat retention

Figure 07: Fat retention

The 3-D plot shows the relationship between the different proportions of mushroom, soybean and carrot with fat retention of the prepared sausage. The fat retention increases with increase in the proportion of mushroom while increase of carrot proportion decreases the retention. Moisture retention value represents the amount of moisture in the cooked product. The lowest and highest value observed for moisture retention was 49.6% and 60.1% respectively. The addition of carrot fiber improved water binding capacity of pork sausage. Verma  have reported that fiber retains water and improves moisture retention. Soy proteins are hydrophilic which hold moisture and fat by creation of an adhesive gel matrix and consequently bring about stabilization for emulsion (Serdaroglu and Ozsumer, 2003). Similar results were reported by Zaini where the addition of 5% albedo orange to sausage resulted in a rise of moisture retention up to 75.68%, whereas the control sausage had moisture retention of 73.61%

Table 10: ANOVA for moisture retention for mixture quadratic and extra term model

Source Sum of

square

Df Mean

Square

F-value P-value
Model 171.26 5 34.25 16.17 0.0042 Significant
Linear Mixture 125.25 2 62.63 29.57 0.0017
AB 27.66 1 27.66 13.06 0.00153
AC 13.39 1 13.39 6.32 0.0535
BC 40.70 1 40.70 19.22 0.0071
Residual 10.59 5 2.12
Lack of Fit 8.72 2 4.36 7.02 0.0739 not significant
Pure Error 1.87 3 0.6217
Cur Total 181.85 10

The Model F–value of 16.17 implies the model is significant. There is only a 0.42% chance that a Model F-value this large could occur due to noise.  of Probe>F less than 0.0500 indicates model term are significant. In this case A, B, C, AB, BC are significant model terms. Values greater than 0.1000 indicate the model terms are not significant. If there are many insignificant model terms (not counting those required to support hierarchy), model reduction may improve the model The Lack of Fit F-value of 7.02 implies the Lack of Fit is not significant relative to the pure error. There is a 7.39% chance that a Lack of Fit F-value this large could occur due to noise. Lack of fit is bad—we want the model to fit. This relatively low probability (<10%) is troubling. Final equation in terms of L Pseudo components:

Moisture retention (%) = +47.61*A +38.90*B+30.65*C+58.87*AB+40.96*AC+94.87*BC Where, A= Mushroom, B= Soybean, C= Carrot.

Moisture Retention

Figure 08: Moisture retention

The 3-D plot shows the relationship between the different proportions of mushroom, soybean and carrot with moisture retention of the prepared sausage. The moisture retention increases with increase in the proportion of mushroom while increase of carrot proportion decreases the retention.

Table 11: Selected treatment based on the desirability with desire and expected response.

Run Mushroom soybean Carrot Cooking loss Folding test Moisture retention Fat retention Desirability  
1 20 5 5 8.37 3.10 57.05 74.81 0.732 Selected
2 5 20 5 7.99 2.88 57.19 73.13 0.680
3 5 5 20 11.56 3.12 51.57 64.01 0.211

From the solution of desirability table obtained from Design Expert® the sample with high proportion of mushroom had higher desirability. The ratio of mushroom: soybean: carrot in the selected sample was 20:5:5 and the desirability were found to be 0.732 But the sensory evaluation showed the sample B was the most preferred in terms of the sensory attributes (color, flavor, taste, texture and overall acceptance). The ratio of mushroom: soybean: carrot in the sample B was 5:20:5 and the desirability was found to be 0.68. So, the sample with second desirability score was accepted as best formulation. The cooking loss, folding test, moisture retention and fat retention of the accepted sample was found to be 7.99%, 2.8, 57.19% and 73.13% respectively.

Mean scores of sensory attributes

Figure 09: Mean Scores of Sensory Attributes

From two-way ANOVA, it was found that there was no significant difference in color between samples A and D. Similarly, samples B and C show no significant difference while they differ from A and D. The mean score for color of the samples A, B, C and D was found to be 6.1, 7.1, 7.7 and 6.0 with standard deviation 0.99, 0.48, 0.51, and 0.51 respectively. Comparing the 30% vegetable incorporated sausage sample with control, sample C (control) was more preferred. After sample C, second best score was of sample B followed by A and D. In processing, color has been identified as the single most important factor of meat products that influences consumer buying decision and affects their perception of the freshness of the product   found that the addition of isolated soy protein to sausages resulted increase in lightness because of the brightness of isolated soy protein as compared to meat protein. Also, reported an increase in yellowness after incorporation of corn, oat and rye bran which was attributed to the presence of carotenoid pigments and to be most superior in terms of flavor than other samples. Likewise, the least mean score was obtained for the sample A observed increase in the appearance and color and flavor scores of Chinese style sausages incorporated with carrot and onion. According to the quality of light pork sausage containing knock gel was improved by incorporating 2% SPI levels, which produced a juicy and appreciable flavor. He quality attributes of sausages could deteriorate due to microbial growth. This can lead to major public health hazards and economic loss in terms of food poisoning and meat spoilage. Hence, the incorporation of vegetables into sausage formulation anticipated to serve both functions; antioxidant and antimicrobial properties useful for preserving meat quality, extending shelf-life and preventing economic loss The initial salmonella and Coliform count of 30% vegetable incorporated sausage on 0 day was nil. The total plate count of sausage was 1 log cfu/g on the 1st day. On 12th day, the total plate count increased to 6 log cfu/g, which is below the typical spoilage level of ~7.0 log cfu/g (Osburn and Keeton, 1994). All the microbial counts were within acceptability limits up to 12th day of storage. TPC crossed acceptability limit after 12th day of storage. Increase in total plate count after 12thday could be due to less use of nitrite as preservative. Also, cross contamination during preparation of the product may have occurred.Fayaz Ahmed Zargar  observed that chicken patties prepared by replacing spent hen meat with 5% sorghum flour, 10% barley flour and 5% pressed rice flour recorded higher total plate count and psychrophilic count, which increased significantly during storage up to 35 days of storage. A previous study by VO and Arroyo proved that mushrooms contain some bioactive compounds such as ruin, Gallic acid and catching, which contain a high antimicrobial effect. The trend was similar with the TPC result obtained where incorporation of vegetables in sausage lowered the yeast and mold count. The inhibition of yeast and mold growth was also probably due to the growth of lactic acid-producing bacteria under anaerobic packaging conditions during refrigerated storage.

Change in Total Plate Count During Storage

Figure 10: Change in Total Plate Count During Storage

The peroxide value (PV) is used as an indicator of the primary oxidation in sausage samples. A gradual increase in PV was observed for all samples throughout the storage from day 0 until day 18. As the storage time increased, the PV also increased from 3.05 at day 0 to 11.46 at day 18, indicating that lipid oxidation was increasing in the sample. PV lower than 25 MeqO2/kg, is the limit of acceptability for fatty foods. Sausages incorporated with vegetables will have a lower PV comparative to the chicken sausage probably due to free radical scavenging antioxidants interfere with the initiation or propagation steps of lipid oxidation reactions by scavenging lipid radicals and forming low-energy antioxidant radicals that do oxidation of unsaturated fatty acids (Maqsood and Benjakul, 2010). Devatkal and Naveena (2010) observed that the peroxide value increased during the refrigerated storage in cooked goat meat patties added with different plant extract. Disha found a significant increase in peroxide value of control and carrot fiber enriched sausage with an increase in storage period. The results indicate that dried carrot pomade was effective in controlling the lipid oxidation in chicken sausages during refrigerated storage. Presence of bioactive compounds in carrot pomade which exert andante-oxidant effect may have caused less increase of peroxide value in carrot incorporated sausages.

Change in peroxide value during storage period

Figure 11: Change in peroxide value during storage period

The study was conducted with an objective of optimizing vegetables proportion in emulsion type chicken sausage and evaluation of storage stability [19]. The primary screening process was conducted in the first phase with various percentages (10%, 20%, 30% and 40%) of vegetables on the basis of sensory evaluation and physicochemical properties of the prepared sausage [20]. 30% formulation was selected from primary screening and 11 runs were generated from D-optimal mixture design. Meat is a product with high nutritional value, containing large quantities of available bio-compounds and consumers have a great passion for its flavorful taste. However, in terms of food security, in the area of production, processing of meat products has more sensitivity compared to other food product [21]. Despite massive processed meat consumption, it has always been criticized by medical nutrition specialists. Many studies have shown adverse effects on human health included colon, breast, and prostate cancers, growth hormone abuse, cardiovascular disease, preventive antibiotic residues, diabetes and classical swine fever [22]. Mentioned diseases can be accorded due to high amount saturated fatty acids (40-50%) in meat fat like meristic and palmate acids, which play a vital role in increasing blood levels of LDL cholesterol. Furthermore, during meat frying, the oxidation of cholesterol and other fatty acids may occur which can give rise carcinogenic compounds like aldehydes, esters, alcohols and short-chain carboxylic acids [23].

  1. CONCLUSIONS

Increasing the different vegetable in the sausage changes the technological and sensory properties (cooking loss, fat retention, moisture retention and folding test) of the sausage.30% vegetable incorporation in sausage can be successfully done with satisfactory technological and sensory attributes. Based on physicochemical properties, optimal mixture of vegetables (mushroom: soybean: carrot) in 30% substitution in sausage was found to be 20:5:5 percent respectively. Sausage with vegetable proportion (mushroom: soybean: carrot) 5:20:5 was most preferred by the sensory panelists. The optimized product from sensory analysis has a proximate composition of 60.47%, 11.89%, 17.55%, 0.43% and 4.17% moisture, crude fat, crude protein, crude fiber and total ash respectively. The carotenoid content of the optimized product was found to be 30 μg/100g and DPPH radical scavenging activity of sausage was found to be 46.76%.There was a gradual increase in Total plate count (TPC) reaching maximum in day 18 (9) while salmonella and coliform were not detected up to day18.Peroxide value was also found to be increase during refrigeration storage of sausage from 3.05 MeqO2/kg at day 0 and 11.46 MeqO2/kg at day18.Vegetable incorporation in sausage showed significant effect on response parameters, the observed models accurately predicted the response parameters (cooking loss, folding test, moisture retention and fat retention) indicated by higher R2 value .Optimized vegetable incorporated sausage had low shelf-life than market product because sodium nitrate was not used during the preparation of the product.

  1. RECOMMENDATIONS

Mushroom: soybean: carrot in 5:20:5 proportions is recommended to prepare 30% vegetable substituted sausage .Similar study with different vegetable combination in sausage can be carried out. Effect on different technological, nutritional and functional properties, storage stability in different packaging materials and storage condition can be studied.

REFERENCES

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Publication History

Submitted: July 15, 2024
Accepted:   July 25, 2024
Published:  July 31, 2024

Identification

D-0297

Citation

Tanka Bhattarai (2024). Optimization of Vegetables Proportion in Emulsion Type Chicken Sausage & Study on Its Storage Stability. Dinkum Journal of Medical Innovations, 3(07):533-549.

Copyright

© 2024 The Author(s).