Process optimization and evaluation of the effects of different time-temperature sous vide cooking on physicochemical, textural, and sensory characteristics of whiteleg shrimp (Litopenaeusvannamei)

Abstract

The objective of the current study was to optimize the cook-chill conditions of high-value whiteleg shrimp (Litopenaeus vannamei) processed using the sous vide (SV) technique and to assess the effects of various time-temperature combinations on the physicochemical, textural, and sensory qualities. For optimization, a Response Surface Methodology (RSM) approach utilizing a Central Composite Design (CCD) was adopted. Optimum SV cooking conditions to acquire minimum texture (hardness) of 7235 g was 13.48 min and 81.87 °C, expressible moisture of 18.48% was 14.5 min and 84.5 °C, and cook loss of 5.58% was 5 min and 75 °C. Texture (hardness) and expressible moisture decreased while cooking loss increased with increasing time-temperature treatment. Redness and yellowness values increased (p < 0.05) with increasing SV cooking time-temperature, but lightness values were nearly consistent in all treatments. With increasing time and temperature, TBARs and total carotenoid content increased (p < 0.05). However, the TBARs values were within accepted limits and ranged from 0.05 to 0.08 mg malonaldehyde/kg. Sensory evaluation indicated that all SV cooked samples were well accepted, with overall scores ≥7. These results suggest that the SV cooking temperature and time had a substantial impact on the textural, physicochemical, and sensory characteristics of shrimp. In addition, increasing time-temperature increased cooking and moisture loss, but decreased hardness and higher sensory scores made the product more acceptable to consumers.

Graphical abstract

Highlights

• •Using response surface approach, sous vide (SV) shrimp product cooking conditions were optimized.
• •Texture (hardness) reduced with increasing SV cooking time and temperature.
• •Cooking loss and moisture loss increased as SV cooking time and temperature increased.
• •Redness and yellowness values increased as SV cooking time and temperature increased.
• •Sensory analysis revealed that all SV cooked shrimp samples were well accepted.

1. Introduction

Shrimps are valuable seafood that is consumed globally and are valued for their distinctive texture and flavour, as well as their high nutritious content. In India, shrimps are one of the major exported fishery products, accounting for 31% and 64.1% in terms of quantity and value [1]. Whiteleg shrimp (Litopenaeus vannamei) has received a lot of attention recently in the American and European markets owing to its flavour and quality. Simultaneously, it gained popularity among Indian shrimp farmers due to its rapid growth and strong disease resistance [2]. This led to an expansion of the culture areas and exceptionally high levels of production in recent years. However, it is crucial to emphasize that India's consumption of whiteleg shrimp is either extremely low or non-existent, and the majority of the shrimp produced is exported. Since the shrimp is shipped in large quantities, maintaining its quality has become a priority. Moreover, compared to finned fish, shrimp has a much shorter shelf life and is more susceptible to post-harvest quality loss owing to their smaller size, chemical composition, and high content of non-protein nitrogenous compounds [3,4]. Therefore, it is crucial that the shrimp processing industry establish a storage method to maintain the freshness and high quality of shrimp. Although there are numerous preservation options available, freezing and cooking are the most commonly employed techniques to preserve shrimp to maintain quality and safety issues. Although freezing efficiently maintains shrimp quality, the texture of shrimp may be affected due to damage to muscle tissue during the freeze-thaw cycle [5]. Similarly, cooking can negatively affect the organoleptic characteristics of shrimp, including texture, mouthfeel, flavour, and appearance [6]. Therefore, there is still a continuous search for an alternative method that provides fresh seafood that is convenient, safe, and requires minimal processing.

A surge in ready-to-eat and convenience foods, which comprise both simplicity of preparation and product shelf life, is the result of new technologies that reflect shifting consumer behaviours [7]. Modern food technology research aims to enhance conventional techniques and develop industry-adapted food processing methods like sous vide (SV) cooking [8]. SV processing involves placing raw or partially cooked foods in a vacuum-sealed bag, followed by pasteurization, immediate cooling, and maintaining refrigeration at 3 °C until serving [9,10]. Contrary to conventional food processing, SV cooking has numerous advantages, such as a hermetic seal that prevents contamination and moisture loss during and after treatments. Additionally, the original flavour, texture, and nutritional value are maintained by the mild cooking temperature. Moreover, vacuum packaging extends the shelf life of products by inhibiting oxidation and aerobic spoilage microorganisms [11,12]. SV cooked fishery products, particularly shrimps, have received very little attention compared to other meat products. For seafood products, SV cooking is often performed between 50 and 75 °C for a few minutes to hours to stop or inhibit the growth of pathogens [13]. For instance, lobster which was SV cooked at 50 °C for 12 min, had improved taste and texture compared to normal overcooked lobster [14]. In another study, salmon slices were SV cooked at 90 °C for 15 min, which significantly increased the shelf life of fish kept at 2 °C (>45 days) and effectively inhibited the growth of aerobic and anaerobic spore-forming bacteria [15]. Singh et al. [16] optimized SV cooking conditions of seerfish steaks by using RSM with time (5–15 min), temperature (70–80 °C), and salt concentration (3–10%) as independent variables and Thiobarbituric acid reactive substances (TBARS) value as response variable; results showed that throughout the 65 days of refrigerated storage, all quality parameters were found to be within the accepted level.

The RSM approach is an experimental design strategy that makes it easier to design, develop, and optimize technologies when one or more responses may be influenced by a number of different factors [17]. The aim of the response surface approach is to make statistical predictions by using a set of mathematical and statistical techniques based on the fit of a polynomial equation to experimental data [18]. The choice of independent variables that would have a significant impact on the response of the system studied and the selection of experimental design are crucial to the effectiveness of RSM optimization [18]. In this study, RSM was used to optimize the effects of two independent variables viz SV cooking time and temperature on the texture, expressible moisture, and cook loss of SV shrimp product. The temperature and cooking time used during SV cooking have a significant impact on the quality of the final product [13]. So, the two independent variables chosen were time (5–15 min) and temperature (75–85 °C) (Table 1). For cook-chill products, the UK's Advisory Committee on the Microbiological Safety of Food recommends a heat treatment of 90 °C for 10 min or similar lethality and stringent chill conditions to reduce the risk of Clostridium botulinum [15]. Also, Listeria monocytogenes and other non-spore-forming pathogens must be destroyed with a heat treatment of 70 °C for 2 min or a comparable heating procedure [19]. Therefore, the levels of time and temperature were selected in the range of 5–15 min and 75–85 °C for process optimization, as illustrated in Table 1.

Table 1.

Levels of independent variables for experimental design.

Symbol	Independent variables	Levels
		-α (Lowest)	−1 (Low)	0 (Mid)	+1 (High)	+α (Highest)
A	Time (min)	2.93	5	10	15	17.07
B	Temperature (°C)	72.93	75	80	85	87.07

Among the numerous experimental designs in RSM, the Central Composite Design (CCD) is the most widely utilized response surface designed experiment [20]. In CCD, a group of axial points, also known as star points, are added to a factorial or fractional factorial design with center points to allow for curvature estimation [20]. This design allows for the rapid estimation of first- and second-order terms. Hence, in this study, The CCD was utilized to conduct the experiments.

The purpose of this research was to develop SV-processed shrimp product, optimize their production processes, and assess how different time-temperature combinations affected the physicochemical, textural, and sensory qualities.

2. Materials and methods

2.1. Raw materials

Freshly harvested whiteleg shrimp (Litopenaeus vannamei) with a size range of 15–18 cm length and an average weight range of 35–45 g (25–30 count/kg) were obtained from shrimp farms in Vijayawada, Andhra Pradesh, India, and transported to the laboratory under iced conditions by keeping them in insulated boxes filled with crushed ice in a 1:1 ratio for further analysis.

2.2. Experimental design for optimization of SV cooking conditions

A series of experiments were designed using the Central Composite Design (CCD) of RSM to investigate the effect of SV cooking time (A) and temperature (B) on the texture (Y₁), expressible moisture (Y₂), and cook loss (Y₃) of whiteleg shrimp. Based on the preliminary experiments, the factors and their levels were chosen. Table 1 depicts the factor levels along with their coded values. The complete design was executed randomly and comprised 11 combinations with three replicates at a central point (Table 2). To analyze experimental data and fit a second-order polynomial model, multiple regression equations were used. Software (Design Expert version 8, StatEase) was used to create the model and conduct the statistical analysis. The model's validity was determined by assessing the coefficient of determination (R²), significance of the regression coefficients, p-value, lack of fit, and the F-test result obtained from the analysis of variance (ANOVA).

Table 2.

Central composite design (uncoded) for texture, expressible moisture, and cook loss.

Experimental Runs	Type	Independent variables		Dependent variables
		Time (min)	Temperature (°C)	Texture (hardness, g)	Expressible moisture (w/w %)	Cook loss (w/w%)
T1	Factorial	5	75	9200.28	30.18	5.13
T2	Factorial	15	75	9046.64	31	5.49
T3	Factorial	5	85	8677.4	31.54	7.67
T4	Factorial	15	85	8007.9	19.76	9.25
T5	Axial	2.93	80	10074.2	29.56	7.44
T6	Axial	17.07	80	7654.74	20.88	8.18
T7	Axial	10	72.93	9988.35	27.09	5.58
T8	Axial	10	87.07	8309.82	20.48	10.36
T9	Center	10	80	7778	21.42	8.61
T10	Center	10	80	7719	22.55	9.17
T11	Center	10	80	8092	24.2	9.22

2.3. Preparation of sous vide shrimp product

Shrimps were washed before being beheaded, peeled, deveined, and washed again in chilled potable water (1–2 °C). The shrimps were then vacuum packed in a sterile food-grade plastic (low-density polypropylene) pouch (dimension: 25 × 20 cm) using a vacuum packaging machine (Spinco, Jumbo Plus, Mylapore, Chennai, India). The pouch's seal area was wiped with tissue paper to avoid contamination. According to the experimental design, the bagged shrimps were cooked in a water bath (Racy Biotech, Delhi, India) under various time-temperature conditions. After cooking, the samples were quickly cooled in cold water and kept at a refrigerated temperature (3–4 °C) for subsequent analysis.

2.4. Proximate composition

The SV cooked shrimp samples’ proximate composition was determined in accordance with AOAC [21]. The moisture content of fish muscle was measured using a moisture analyzer (Sartorius, Germany). The ash content was determined using a muffle furnace (EXPO HI-TECH, i-therm AL-7941) set to 550 °C for approximately 6–7 h. The Micro-Kjeldahl instrument was used to determine the crude protein content. Fat was extracted using a soxhlet apparatus, and petroleum ether was used as a solvent.

2.5. Analysis of quality indices

2.5.1. Texture profile analysis (TPA)

The textural characteristics of SV cooked shrimps were evaluated using a texture analyzer (TA-XT PLUS Stable Micro Systems, Surrey, England, UK). A compression plate with a 75 mm diameter and a 50 kg sensor was employed as the load cell. Each treatment had three SV cooked shrimp that were evaluated. The distance was 8 mm/s, the trigger force was 5 g, the pre-test and test speeds were 1 mm/s, while the post-test speed was 5 mm/s. The TPA parameters were calculated using the force by time data from each test. The final value of each parameter was calculated as the average of the three close values.

2.5.2. Cooking loss

The cooking loss was calculated according to the method of Chaurasiya et al. [22] with minor modifications. Briefly, shrimps were placed in a low-density polypropylene bag and cooked for the specified time and temperature combination, then cooled in iced water for 1 min before draining at 4 °C for 5 min. Weighing the shrimp before and after pre-cooking was used to determine cooking loss. Weighing the pre-cooked shrimp. The following equation (equation (1)) was used to compute the cooking loss.

$$\mathrm{C}\mathrm{o}\mathrm{o}\mathrm{k}\mathrm{i}\mathrm{n}\mathrm{g}\mathrm{l}\mathrm{o}\mathrm{s}\mathrm{s}(\%)=\frac{\left(A-B\right)}{A}\times 100$$ (1)

Where A represents the weight before cooking and B represents the weight after cooking.

2.5.3. Expressible moisture (EM)

The methodology of Remya et al. [23] with minor modifications was used to calculate the EM content. The center of an SV cooked sample was cut into a 10 mm test piece, which was carefully weighed (W₁). The test piece was placed between two Whatman filter papers with two boards at the bottom and top of the filter paper. For 2 min, a 1 kg standard weight was placed on the board. After pressing, the test piece was precisely weighed (W₂). The following equation (equation (2)) was used to compute expressible moisture.

$$\mathrm{E}\mathrm{x}\mathrm{p}\mathrm{r}\mathrm{e}\mathrm{s}\mathrm{s}\mathrm{i}\mathrm{b}\mathrm{l}\mathrm{e}\mathrm{m}\mathrm{o}\mathrm{i}\mathrm{s}\mathrm{t}\mathrm{u}\mathrm{r}\mathrm{e}(\%)=\frac{\left(W_{1-}{W}_2\right)}{W_1}\times 100$$ (2)

2.5.4. Instrumental color analysis

L* (lightness), a* (redness/greenness), and b* (yellowness/blueness) were used to determine the color of SV cooked shrimps. A spectrocolorimeter (Colourflex EZ, Hunter Associates Laboratory, Inc., Reston, VA, USA) with a D 65/10° illuminant was used to measure a piece of cooked shrimp meat. The study used the CIELAB color scale and color analysis was done according to the method of Young and Whittle [24]. The ventral body (second segment) of shrimp muscle was used for color measurements.

2.5.5. Total carotenoid content (TCC)

TCC was determined according to the method of Dayakar et al. [25]. The following equation (equation (3)) was used to estimate the carotenoid content (C) of the samples:

$$C(\mu g/g)=\frac{\left(A468\times volumeofextract\times Dilutionfactor\right)}{\left(0.2\times Weightofsampleusedingram\right)}$$ (3)

Where A468 is the absorbance at 468 nm; 0.2 is the absorbance value of the 1 μg/ml astaxanthin standard.

2.5.6. Thiobarbituric acid reactive substances (TBARs)

The TBARs assay was performed as described by Buege and Aust [26] and the values were expressed as mg malonaldehyde/kg of shrimp.

2.5.7. Sensory evaluation

Sensory evaluation of SV cooked shrimp samples were carried out by following the method of Meilgaard et al. [27]. In brief, a panel of 10 trained panelists were presented with SV cooked shrimp samples. Using a 9-point hedonic scale, the panelists were asked to evaluate samples as acceptable or unacceptable based on appearance, texture, juiciness, taste, flavour, aroma, colour, and overall impression. Scores of 6 and higher were regarded as acceptable and vice versa (Table S1).

2.6. Statistical analysis

All the data were analyzed using the SPSS version 22.0 for Windows (SPSS, Chicago, IL). The significance of the main effects was determined using one-way ANOVA. Duncan's Multiple Range Test was used to determine significant differences (p < 0.05) between the means (Post hoc analysis). Data from three independent replications (n = 3) are presented as mean ± standard deviation. Means in the same column with different superscripts in the lowercase letter on tables are statistically significantly different (p < 0.05).

2.7. Ethical statement

The experiments were conducted according to the established ethical guidelines, and informed consent was obtained from the sensory analysis participants.

3. Results and discussion

3.1. Optimization of process conditions and validation of the model

The processing conditions were optimized using a combination of RSM and CCD, accounting for the most important process factors, namely time (A, min) and temperature (B, °C), in order to achieve the minimum texture (Y₁), expressible moisture (Y₂), and cook loss (Y₃). Table 2 shows the responses of Y₁, Y₂, and Y₃. Table 3 summarizes the ANOVA for the response surface quadratic model for texture, expressible moisture, and cook loss. Fig. 1 illustrates the contour plots and 3D response surface plots of the time and temperature combination effect on the texture, expressible moisture, and cook loss. Fig. 1(A and D) shows that as time and temperature increases, texture (hardness) decreases and the minimal optimum hardness is near the high level (+1) of the experimental design. Similarly, Fig. 1(B and E) indicates that expressible moisture decreases as time and temperature increases, and that the minimal optimum expressible moisture is close to the high level (+1) of the experimental design. In contrast, Fig. 1(C and F) demonstrates that cook loss increases with time and temperature, and the minimal optimum cook loss is near to the low level (−1) of the experimental design.

Table 3.

ANOVA for response surface quadratic models.

Source	Texture		Expressible moisture		Cook loss
	F value	p-value	F value	p-value	F value	p-value
Model	5.90	0.0368	6.37	0.0316	12.14	0.0080
A	10.15	0.0244	11.83	0.0185	2.27	0.1925
B	8.55	0.0329	8.42	0.0337	45.50	0.0011
AB	0.32	0.5943	6.79	0.0479	0.59	0.4762
A2	4.72	0.0820	4.18	0.0963	7.90	0.0375
B2	8.62	0.0324	1.84	0.2325	8.10	0.0360
Lack of Fit	7.65	0.1178	3.78	0.2165	7.58	0.1188
	R2 = 0.8551		R2 = 0.8643		R2 = 0.9239
	Adj R2 = 0.7103		Adj R2 = 0.7286		Adj R2 = 0.8478

Italic values indicate significance of p value (p < 0.05).

Fig. 1.

Response surface plots (A, B, C) and contour plots (D, E, F) for the effect of SV cooking time and temperature on texture (hardness) (A, D), expressible moisture (B, E), and cook loss (C, F).

For determining the minimal texture (equation (4)), expressible moisture (equation (5)), and cook loss (equation (6)), the experimental data were fitted into a quadratic polynomial equation as follows:

Texture (Y₁) = +88.67 − 2.84A − 2.6 B − 0.72 AB + 2.3 A² + 3.11 B² (4)

Expressible moisture (Y₂) = +4.77 − 0.29 A − 0.25 B − 0.31 AB + 0.21 A² + 0.14 B² (5)

Cook loss (Y₃) = +3.00 + 0.0674 A + 0.3B + 0.049 AB − 0.15 A² − 0.15 B² (6)

The determination coefficient R², which explains the total variations of a model, indicates that the design is valid [28]. Table 3 shows that the R² values for texture, expressible moisture, and cook loss were 0.8551, 0.8643, and 0.9239, respectively, indicating that the model can account for 85.51%, 86.43% and 92.39% of the variation in the data. These values indicate that the selected model is suitable for illustrating the relationships between the chosen variables. The model's significance was demonstrated by the low p-values (p < 0.05) and high F values of 5.90, 6.37, and 12.14 in the ANOVA for texture, expressible moisture, and cook loss models. Additionally, the models' lack of fit for texture, expressible moisture, and cook loss were non-significant (p > 0.05), showing a good fit of the models [29].

Table 4 shows the predicted and experimental values of texture (hardness), expressible moisture, and cook loss under the optimum extraction conditions. The optimum SV cooking conditions were 13.48 min at 81.87 °C, 14.5 min at 84.5 °C, and 5 min at 75 °C, respectively, for minimum texture (hardness) of 7590 g, expressible moisture of 18.39%, and cook loss of 5.67%. To validate the predicted outcomes, the experiment was repeated using the optimal extraction conditions for each dependent variables. From real experiments, mean values of 7235 g texture (hardness), 18.48% expressible moisture, and 5.58% cook loss were achieved, which validated the RSM models. The results of texture, expressible moisture, and cook loss show that there was no significant difference (p > 0.05) between experimental and predicted values. Therefore, the models can be employed to optimize the process conditions for the development of ready-to-eat shrimp products cooked by the SV method.

Table 4.

Predicted and experimental values of texture (hardness), expressible moisture, and cook loss under the optimum extraction conditions.

Response variables	Optimum extraction conditions		Minimum values
	Time (min)	Temp (°C)	Predicted	Experimentala
Texture (hardness, g)	13.48	81.87	7590	7235 ± 0.20
Expressible moisture (w/w %)	14.5	84.5	18.39	18.48 ± 0.16
Cook loss (w/w %)	5	75	5.67	5.58 ± 0.12

^aMeans ± standard deviation (n = 3).

3.2. Proximate composition

Table 5 shows the proximate composition changes of ready-to-eat SV cooked shrimp with different temperature and time treatments. The protein, moisture, fat, and ash content differed significantly (p < 0.05) among treatments. With increasing time and temperature, the moisture content of SV cooked shrimp meat decreased. High temperatures and time may have a negative impact on the moisture content by denaturing muscle proteins, which reduces their ability to retain water [1,30]. Conversely, treatments that involved longer cooking times and higher temperatures had higher levels of protein, fat, and ash content. The decrease in moisture content of the samples may be responsible for the increase in protein content. Similar to our result, fat and ash content were reported to be increased in SV cooked shrimp than in raw shrimp [1].

Table 5.

Proximate composition of sous-vide cooked shrimp product at different time-temperature treatments on a wet weight basis.

Treatments	Moisture (g/100 g)	Crude protein (g/100 g)	Fat (g/100 g)	Ash (g/100 g)
T1	72.77 ± 0.11a	25.37 ± 0.24e	0.59 ± 0.30f	1.46 ± 0.03g
T2	70.86 ± 0.22b	26.77 ± 0.13d	0.82 ± 0.41d,e	1.64 ± 0.04e
T3	69.70 ± 0.22c,d	27.66 ± 0.33c	0.88 ± 0.44a,b,c	1.79 ± 0.02c,d
T4	68.51 ± 0.12f	28.79 ± 0.14a	0.94 ± 0.47a	1.87 ± 0.02a
T5	69.90 ± 0.26c	27.71 ± 0.46c	0.85 ± 0.43c,d,e	1.76 ± 0.01d
T6	68.78 ± 0.14e,f	28.55 ± 0.36a	0.92 ± 0.05a,b	1.86 ± 0.03a,b
T7	70.97 ± 0.27b	26.71 ± 0.26d	0.80 ± 0.03e	1.58 ± 0.05f
T8	68.97 ± 0.16e	28.36 ± 0.28a,b	0.87 ± 0.43b,c,d	1.84 ± 0.05a,b,c
T9	69.65 ± 0.22c,d	27.71 ± 0.33c	0.88 ± 0.44b,c	1.80 ± 0.01b,c,d
T10	69.46 ± 0.14d	27.84 ± 0.43b,c	0.90 ± 0.04a,b,c	1.85 ± 0.03a,b,c
T11	69.58 ± 0.29c,d	27.77 ± 0.47c	0.89 ± 0.02a,b,c	1.83 ± 0.04a,b,c

Data are expressed as the mean ± SD of three independent replications (n = 3), Mean values with different letters in the same column are significantly different (p ˂ 0.05).

3.3. Physicochemical properties

3.3.1. Expressible moisture and cooking loss

The expressible moisture and cook loss values of SV cooked shrimp at different time-temperature treatments are given in Table 2. Among the treatment groups, samples cooked at higher temperatures for longer time (T4, T6, T8, T9, T10, and T11) showed considerably lower expressible moisture and higher cook loss than samples cooked at lower temperatures for shorter time (T1, T2, T3, T5, and T7). The lowest expressible moisture of 19.76% was shown by treatment T4 (time: 15 min and temperature: 85 °C), while the highest expressible moisture of 31.54% was shown by treatment T3 (time: 5 min and temperature: 85 °C) followed by T1 (30.18%; time: 5 min and temperature: 75 °C), indicating that time and time-temperature combinations significantly influenced the moisture content of SV cooked shrimp. The decrease in moisture content in higher time-temperature cooked SV shrimp can be attributed to thermal denaturation and shrinkage of muscle proteins, leading to a reduction in water holding capacity [31]. Our findings are consistent with those found in other studies [[32], [33], [34], [35]]. Similarly, the highest cooking loss was shown by treatment T8 (10.36%; time: 10 min and temperature: 87.07 °C), followed by T4 (9.25%; time: 15 min and temperature: 85 °C), while the lowest was shown by T1 (time: 5 min and temperature: 75 °C) which had a cooking loss of 5.13%. The increased cooking loss in SV method with increasing time and temperature is in parallel with other researchers’ findings [31,36,37]. Increased time and temperature during SV cooking cause a decrease in sarcoplasmic and myofibrillar protein, which increases cooking loss [31].

3.3.2. Color

Color is one of the most blatant and significant sensory indicators of food quality. Due to heme and carotenoid oxidation during heat treatment, seafood products are susceptible to discolouration. Additionally, the meat will develop undesirable colours when seafood products are cooked at high temperatures for an extended period of time [38]. In contrast, seafood prepared by SV cooking maintains its consistency and appeal. The instrumental color values of SV cooked shrimp under the different time-temperature conditions are presented in Table 6. The lightness values of SV cooked shrimp were high, which ranged from 69.70 ± 0.15 to 71.18 ± 0.18 and were significantly different (p < 0.05) among treatments. Similarly, the redness (a*) and yellowness (b*) values also differed significantly (p < 0.05) among treatments. The yellowness values were higher than the redness values among various time-temperature treatments. The highest yellowness value was observed in T4, which was cooked at 85 °C for 15 min and the lowest was observed in T1 cooked at 75 °C for 5 min. Meat cooked for extended heating durations has higher yellowness values [39]. In addition, more cooked meat has a slight dryness and a greyish-brown colour [30]. Additionally, meat cooked with the SV technique has higher b* values, that may be attributed to an increase in metmyoglobin, which results in brownish products [40]. The increase in redness value with increasing time-temperature treatment can be attributed to liberation of red astaxanthin during SV cooking [25]. Astaxanthin, a red carotenoid, is present in the carapace of shrimp bound to proteins as carotenoprotein complex called ovoverdin [41]. This can also be correlated to the increasing carotenoid content with increasing time and temperature in our SV cooked samples (Table 6). Another factor contributing to the increase in redness value could be the leaching of myoglobin from the shrimp muscles during SV cooking [13].

Table 6.

Carotenoid content, TBARS, and instrumental colour analysis of sous vide cooked shrimp product at different time-temperature treatments.

Treatments	Carotenoid content (μg/g)	TBARS (mg MDA/kg)	Instrumental color analysis
			Lightness (L*)	Redness (a*)	Yellowness (b*)
T1	12.65 ± 0.18f	0.05 ± 0.01d	70.69 ± 0.18b	12.55 ± 0.08d	16.73 ± 0.16d
T2	16.77 ± 0.12e	0.05 ± 0.01c,d	70.47 ± 0.12c,d	14.69 ± 0.17c	18.55 ± 0.21c
T3	20.73 ± 0.23d	0.06 ± 0.01c,d	70.25 ± 0.09d,e	16.49 ± 0.18b	20.43 ± 0.05b
T4	25.60 ± 0.18a	0.08 ± 0.01a	69.70 ± 0.15f	18.28 ± 0.06a	22.20 ± 0.04a
T5	20.76 ± 0.17d	0.06 ± 0.01c,d	71.18 ± 0.18a	14.74 ± 0.15c	18.72 ± 0.17c
T6	25.37 ± 0.18a	0.08 ± 0.01a,b	70.26 ± 0.09d,e	18.12 ± 0.21a	20.36 ± 0.09b
T7	16.82 ± 0.09e	0.05 ± 0.01c,d	70.56 ± 0.11b,c	14.75 ± 0.11c	18.63 ± 0.05c
T8	25.51 ± 0.17a	0.08 ± 0.01a,b,c	70.34 ± 0.08d	18.18 ± 0.21a	20.45 ± 0.08b
T9	21.75 ± 0.20c	0.06 ± 0.01b,c,d	70.10 ± 0.12e	18.04 ± 0.07a	22.14 ± 0.04a
T10	22.76 ± 0.16b	0.06 ± 0.01c,d	70.33 ± 0.10d	18.10 ± 0.12a	20.34 ± 0.13b
T11	22.94 ± 0.04b	0.07 ± 0.01a,b,c,d	70.26 ± 0.07d,e	18.17 ± 0.16a	20.27 ± 0.08b

Data are expressed as the mean ± SD of three independent replications (n = 3), Mean values with different letters in the same column are significantly different (p ˂ 0.05).

3.3.3. TBARS

TBARs value indicates the formation of secondary lipid oxidation products, which is particularly associated with the unpleasant flavour and odour of fisheries products. A TBARs value of less than 2 is acceptable for seafood products [42]. The TBARs value of SV cooked shrimps at different time-temperature are shown in Table 6. The TBARs value differed significantly among treatments (p < 0.05) with higher values of 0.08 mg MDA/kg in treatments (T4, T6, and T8) which were cooked at higher time-temperature as compared to treatments (T1, T2, and T7) which were cooked at lower time-temperature with TBARs value of 0.05 mg MDA/kg. Several authors have reported that time and temperature of cooking have a significant effect on lipid oxidation in seafood products [31,43]. Moreover, higher cooking temperatures and times lead to more lipid oxidation [44]. Similar to our result, TBA value of shrimp (Fenneropenaeus indicus) increased slightly after SV cooking [1]. TBARs value of all the samples in this study were less than 1.0 mg malonaldehyde/kg and thus were within acceptable limits.

3.3.4. Total carotenoid content

Astaxanthin (C₄₀H₅₂O₄), an orange pigment and exceptionally potent antioxidant, is present in the tissues of marine animals, including shrimp [25,45,46]. The total carotenoid content of SV cooked shrimp at different time-temperature are shown in Table 6. The results indicate that with increasing time-temperature treatment, total carotenoid content increased. The highest carotenoid content of 25.60 μg/g was found in treatment T4 (time: 15 min and temperature: 85 °C), while the lowest carotenoid content of 12.65 μg/g was found in treatment T1 (time: 5 min and temperature: 75 °C). As of now, there are no reports available on the impact of SV cooking on carotenoid content of shrimps. However, there are reports suggesting that carotenoid content increases in vegetable samples after SV cooking. For instance, SV cooked carrots and Brussels sprouts had increased carotenoids concentrations compared to raw and steamed cooked samples [47]. The increased SV cooking may be responsible for the increase in carotenoid content in vegetable samples because it effectively releases carotenes that are typically contained in cellular crystals and bound by protein complexes or residual membranes [47,48]. Similarly, in this study, the increase in carotenoid content with increasing time-temperature can be attributed to the release of carotenoid which are normally bound to proteins in shrimp as carotenoprotein complex [45].

3.4. Textural properties

The textural changes of ready-to-eat shrimp as a result of varied temperature and time SV cooking treatments are shown in Table 7. SV cooking time-temperature significantly (p < 0.05) affected the textural attributes. The most important textural attribute in meat or seafood products, among all other characteristics, is hardness [49]. Samples cooked at higher temperatures for longer durations (T4, T6, T8, T9, T10, and T11) had considerably lower hardness than those cooked at lower temperatures for shorter durations (T1, T2, T3, T5, and T7). Comparatively, all the SV cooked samples had lower hardness in the range of 7654.74–10074.20 g than the initial raw material, which had a hardness of 11755.67 g. Our results are comparable to that of Ahmad and Traynor [35], where SV cooking resulted in a significant decrease in hardness of shrimp (Litopenaeus setiferus) compared to the raw sample. During heat treatment, the texture of fish meat undergoes remarkable changes giving rise to structures that are primarily stabilized by hydrophobic interactions and disulfide bonds [50,51]. Roldán et al. [52] showed that SV cooking of meat at high temperature of 80 °C for a long time shows less hardness than low-temperature SV cooking at 60 °C, which is in line with our results. SV cooking makes meat tender and reduces hardness due to solubilization of connective tissues [53]. Contrasting to hardness, the springiness and cohesiveness values in this experiment were noticeably higher in treatments with higher cooking time-temperature than initial raw material, with treatment T4 having highest springiness and cohesiveness values of 0.86 mm and 0.78, respectively, while raw material had springiness and cohesiveness values of 0.55 mm and 0.42, respectively. The increase in cohesiveness value is consistent with research conducted by Biyikli et al. [54] on the effects of various SV cooking temperature-time combinations on the characteristics of turkey cutlets.

Table 7.

Instrumental texture parameters of raw and sous vide cooked shrimp product at different time-temperature treatments.

Treatments	Hardness (g)	Springiness (mm)	Cohesiveness	Gumminess (g)	Chewiness (g)
Raw shrimp	11755.67 ± 905.05a	0.55 ± 0.09g	0.42 ± 0.10d	4974.63 ± 1432.37a,b,c	3446.96 ± 209.00b,c
T1	9200.28 ± 659.81b,c	0.67 ± 0.04e,f	0.54 ± 0.04c	5407.04 ± 966.93a,b,c	3564.12 ± 333.88b,c
T2	9046.64 ± 673.41b,c,d	0.76 ± 0.03c,d	0.56 ± 0.04c	5860.77 ± 376.20a	4070.13 ± 117.93b,c
T3	8677.40 ± 880.54c,d,e	0.76 ± 0.06c,d	0.67 ± 0.09b	5943.25 ± 52.71a	5369.76 ± 1250.04a
T4	8007.90 ± 646.78d,e	0.86 ± 0.03a	0.78 ± 0.01a	4103.33 ± 188.66b,c,d	3391.95 ± 123.95b,c
T5	10074.20 ± 139.22b	0.70 ± 0.03d,e	0.55 ± 0.01c	5881.12 ± 248.16a	4226.95 ± 706.55a,b
T6	7654.74 ± 208.76e	0.79 ± 0.03b,c	0.75 ± 0.02a	3267.22 ± 511.45d	2648.77 ± 394.66c
T7	9988.35 ± 11.54b	0.63 ± 0.05f	0.55 ± 0.02c	5746.14 ± 455.27a	3306.85 ± 1010.31b,c
T8	8309.82 ± 338.37c,d,e	0.84 ± 0.03a,b	0.77 ± 0.02a	3834.62 ± 1678.50c,d	3192.91 ± 1289.96b,c
T9	7778.00 ± 446.73e	0.75 ± 0.02c,d	0.67 ± 0.03b	5067.72 ± 249.02a,b,c	3927.86 ± 285.40b,c
T10	7719.00 ± 701.77e	0.74 ± 0.005c,d,e	0.64 ± 0.01b	5420.33 ± 760.71a,b,c	3742.88 ± 796.52b,c
T11	8092.00 ± 799.57d,e	0.68 ± 0.01e,f	0.54 ± 0.02c	5515.28 ± 1155.48a,b	3750.56 ± 807.58b,c

Data are expressed as the mean ± SD of three independent replications (n = 3), Mean values with different letters in the same column are significantly different (p ˂ 0.05).

3.5. Sensory properties

One of the crucial factors that customers take into account is sensory attributes [55]. The sensory scores of SV cooked shrimp product at different time-temperature treatments are shown in Table 8. The results indicate that all SV-cooked treatments were well accepted, with overall scores ≥7. Among the treatments, the overall acceptability of samples cooked at higher time-temperature (T4, T6, T8, T9, T10, and T11) were higher as compared to samples cooked at lower time-temperature (T1, T2, T3, T5, and T7). Based on the scores, treatment T4 (time: 15 min and temperature: 85 °C) fetched highest overall score of 8.80, while treatment T1 (time: 5 min and temperature: 75 °C) fetched the lowest overall score of 7.20. This indicated that with increasing SV cooking time and temperature, sensory attributes increased. Our results are comparable to previous studies by Biyikli et al. [54] and Naveena et al. [56]. According to Biyikli et al. [54], as SV cooking temperature and time are raised, the sensory qualities of turkey cutlets tend to get improved. Similarly, according to Naveena et al. [56], the flavour, juiciness, colour, and texture of SV cooked chicken increased after 30 and 60 min at 100 °C.

Table 8.

Sensory scores of sous vide cooked shrimp product at different time-temperature treatments.

Treatments	Appearance	Texture	Juiciness	Taste	Flavour	Odour	Colour	Overall Impression
T1	7.50 ± 0.53b	7.40 ± 0.52b	7.30 ± 0.67b	6.90 ± 0.88b	6.80 ± 0.42c	6.80 ± 0.89b	6.70 ± 0.67b	7.20 ± 0.79b
T2	7.60 ± 0.84b	7.50 ± 0.71b	7.40 ± 0.70b	7.30 ± 048b	7.20 ± 0.92b,c	7.10 ± 0.55b	7.00 ± 0.47b	7.30 ± 0.48b
T3	7.70 ± 0.48b	7.50 ± 0.53b	7.50 ± 0.53b	7.40 ± 0.70b	7.30 ± 0.82b,c	7.20 ± 0.82b	7.20 ± 0.42b	7.50 ± 0.53b
T4	8.90 ± 0.32a	8.80 ± 0.42a	8.70 ± 0.48a	8.60 ± 0.70a	8.50 ± 0.53a	8.40 ± 0.52a	8.30 ± 0.82a	8.80 ± 0.42a
T5	7.70 ± 0.48b	7.60 ± 0.70b	7.60 ± 0.52b	7.50 ± 0.53b	7.40 ± 0.52b	7.30 ± 0.63b	7.20 ± 0.63b	7.50 ± 0.85b
T6	8.70 ± 0.48a	8.60 ± 0.52a	8.50 ± 0.53a	8.40 ± 0.52a	8.30 ± 0.48a	8.20 ± 0.75a	8.10 ± 0.74a	8.50 ± 0.53a
T7	7.70 ± 0.82b	7.60 ± 0.52b	7.50 ± 0.71b	7.40 ± 0.52b	7.30 ± 0.48b,c	7.30 ± 0.41b	7.20 ± 0.42b	7.50 ± 0.71b
T8	8.70 ± 0.48a	8.60 ± 0.52a	8.50 ± 0.53a	8.40 ± 0.70a	8.30 ± 0.48a	8.20 ± 0.63a	8.10 ± 0.74a	8.40 ± 0.52a
T9	8.70 ± 0.48a	8.60 ± 0.52a	8.50 ± 0.53a	8.40 ± 0.52a	8.40 ± 0.52a	8.20 ± 0.41a	8.30 ± 0.48a	8.50 ± 0.53a
T10	8.90 ± 0.32a	8.70 ± 0.48a	8.60 ± 0.52a	8.50 ± 0.53a	8.40 ± 0.52a	8.30 ± 0.55a	8.20 ± 0.42a	8.60 ± 0.52a
T11	8.80 ± 0.42a	8.70 ± 0.48a	8.60 ± 0.52a	8.50 ± 0.53a	8.40 ± 0.52a	8.30 ± 0.52a	8.20 ± 0.42a	8.50 ± 0.53a

Data are expressed as the mean ± SD of three independent replications (n = 3), Mean values with different letters in the same column are significantly different (p ˂ 0.05).

4. Conclusion

The research concludes that different SV cooking time-temperature combinations significantly altered the physicochemical, textural, and sensory characteristics of Litopenaeus vannamei. Maintaining optimal cooking conditions to obtain desired quality attributes is vital for better acceptability in terms of the overall quality of the SV-cooked shrimp product. Although the current time-temperature combination is suitable for shrimp, it might not be for other seafood products like finfish, cephalopods, and crab. Therefore, future research and the usage of SV-based procedures in diverse species are needed.

Author contribution statement

Rupali Das: Performed the experiments; Analyzed and interpreted the data; Wrote the paper. Naresh Kumar Mehta, Soibam Ngasotter: Analyzed and interpreted the data; Contributed reagents, materials, analysis tools or data; Wrote the paper. Amjad K. Balange, Binaya Bhusan Nayak, Lakshmi Narasimha Murthy: Analyzed and interpreted the data; Contributed reagents, materials, analysis tools or data. K.A. Martin Xavier: Conceived and designed the experiments; Analyzed and interpreted the data; Contributed reagents, materials, analysis tools or data; Wrote the paper.

Funding statement

None.

Data availability statement

Data will be made available on request.

Additional information

No additional information is available for this paper.

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Appendix A. Supplementary data

The following is the supplementary data related to this article: