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Meat Science 122 (2016) 68–75
Contents lists available at ScienceDirect
Meat Science journal homepage: www.elsevier.com/locate/meatsci
Effect of preservative addition on sensory and dynamic profile of Lucanian dry-sausages as assessed by quantitative descriptive analysis and temporal dominance of sensations Ada Braghieri a, Nicoletta Piazzolla a, Fernanda Galgano a, Nicola Condelli a, Giuseppe De Rosa b, Fabio Napolitano a,⁎ a b
Scuola di Scienze Agrarie, Forestali, Alimentari ed Ambientali, Università degli Studi della Basilicata, Via dell'Ateneo Lucano, 10, 85100 Potenza, Italy Dipartimento di Agraria, Università degli Studi di Napoli Federico II, Via Università 133, 80055 Portici, NA, Italy
a r t i c l e
i n f o
Article history: Received 2 December 2015 Received in revised form 21 July 2016 Accepted 25 July 2016 Available online 26 July 2016 Keywords: Lucanian dry-sausages Key-attributes profiling Preservatives Quantitative descriptive analysis Temporal dominance of sensations Pig
a b s t r a c t The quantitative descriptive analysis (QDA) was combined with temporal dominance of sensations (TDS) to assess the sensory properties of Lucanian dry-sausages either added with nitrate, nitrite and L-ascorbic acid (NS), or not (NNS). Both QDA and TDS differentiated the two groups of sausages. NNS products were perceived with higher intensity of hardness (P b 0.05) and tended to be perceived with higher intensities of flavor (P b 0.10), pepper (P b 0.20), and oiliness (P b 0.20), while resulting lower in chewiness (P b 0.20). TDS showed that in all the sausages hardness was the first dominant attribute; then, in NNS products flavor remained dominant until the end of tasting, whereas in NS products oiliness prevailed. In conclusion, TDS showed that the perception of some textural parameters, such as oiliness, during mastication was more dominant in NS products, whereas using conventional QDA this attribute appeared higher in sausages manufactured without preservatives. Therefore, TDS provided additional information for the description and differentiation of Lucanian sausages. © 2016 Published by Elsevier Ltd.
1. Introduction Sensory profiling, namely quantitative descriptive analysis (QDA), is a method for qualifying the type and quantifying the intensity of the sensory properties immediately after sensory stimulation (Stone & Sidel, 2004). Although QDA can give insights into a higher number of attributes, perception is a dynamic process (Piggott, 1994), involving oral activities affecting flavor and texture attributes (Foster et al., 2011). Thus, temporal dominance of sensations (TDS) has been developed (Pineau, Cordelle, Imbert, Rogeaux, and Schlich, 2003): the product perception is depicted by curves indicating the frequency by which a sensation is considered as dominant by a trained panel during the taste of the product (Pineau et al., 2009). Therefore, QDA and TDS methodologies are designed for providing complementary information (Lenfant, Loret, Pineau, Hartmann, and Martin, 2009). Temporal dominance of sensations has been used for different products, including yoghurt (Bouteille et al., 2013), fish sticks (Albert, Salvador, Schlich, and Fiszman, 2012), mozzarella cheese (Rodrigues, Gonçalves, Pereira, Carneiro, and Pinheiro, 2014), and sausages (Devezeaux de Lavergne, Derks, Ketel, de Wijk, R. A., & Stieger, 2015). Dry sausages are typically cured by addition of sodium/potassium nitrite or nitrate, spices, phosphates, sodium chloride and other preservatives as bacteriostatic, ⁎ Corresponding author. E-mail address: [email protected] (F. Napolitano).
http://dx.doi.org/10.1016/j.meatsci.2016.07.020 0309-1740/© 2016 Published by Elsevier Ltd.
bacteriocidal, antioxidant and color stabilizer agents (Sebranek and Bacus, 2007). There are raising concerns about the safety of using nitrate and nitrite for cured meat (Sebranek and Bacus, 2007). In a previous study about consumer liking and choice determinants of Lucanian dry cured sausages, taste and addition of preservatives were identified among the most influential aspects affecting consumer choice (Braghieri, Piazzolla, Carlucci, Bragaglio, and Napolitano, 2016). Thus, in this study the effect of preservative addition on sensory properties of Lucanian dry sausage was assessed, using both the TDS method and the conventional QDA. 2. Materials and methods 2.1. Products Dry-sausages were produced in 8 different manufacturing plants in Basilicata region, southern Italy. These 8 plants were recruited on the basis of their process characteristics, as they all used the following traditional procedure. Pork cuts (shoulder, belly and trimmings of ham) were ground in a meat grinder using a plate of 12–18 mm of hole diameter; then salt and spices (ground sweet red pepper and wild fennel seeds) were added to the mixture. Four plants did not add their products (P3, P5, P7, P8) with any preservatives (no nitrate/nitrite sausages, NNS), whereas other 4 plants added their products (P1, P2, P4, P6) with nitrate, nitrite and L-ascorbic acid (nitrate/nitrite sausages, NS). This
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preservative mix (nitrate up to 150 mg/kg, nitrite up to 150 mg/kg, L-ascorbic up to 500 mg/kg) was chosen because it is the most common-
ly used for dry-sausage manufacturing. The sausage mixture was stuffed in natural casings (36–42 mm of diameter), brought to dry (2–7 days) into dedicated places (15 °C, 65% of relative humidity, RH) and seasoned (13–18 °C, 75–85% RH) for a month. After ripening, the sausages were vacuum packaged (80 mbar) using bell-shaped machines (Mixer Duo, Euromatic Tecnology Srl, Italy) in plastic bags (oxygen transmission rate at 23 °C and 0% R.H. of ≤ 50 cm3/m2/bar/24 h, DIN 53380; water vapor transmission rate at 23 °C and 85% R.H. of ≤ 3 g/m2/24 h, DIN 53122) and refrigerated at 4 °C. 2.2. Chemical composition Moisture, protein, and ash contents in homogenized sausage samples were determined according to AOAC (1995) methods. Total lipids were extracted from 5 g of minced sausage according to Folch, Lees, and Stanley (1957), using chloroform:methanol (2:1) as solvent. Analyses for all samples were carried out in duplicate. 2.3. Key-attribute sensory profiling (KASP) A QDA approach (Murray, Delahunty, and Baxter, 2001) was followed to select key-attributes (i.e. the most effective attributes in discriminating products) to be used for the following TDS analysis. A 9-member trained sensory panel (5 males and 4 females, aging 26–35 years) with three years of experience in the descriptive analysis of sausages was used. Panelists were selected according to ISO recommendations (ISO 3972:, 2011; ISO 8586:, 2012). For this purpose the four basic tastes were used: three levels of sucrose (Carlo Erba, Milan, Italy), sodium chloride (Carlo Erba, Milan, Italy), citric acid (Carlo Erba, Milan, Italy) and quinine hydrochloride (Sigma-Aldrich, USA) were diluted in filtered, deionized water at room temperature (Braghieri et al., 2016). The panelists were informed about the taste of each basic concentration. Then, they tasted a 10 mL quantity of high and low concentration for each taste solution in blind. De-ionized water was used to prepare two blanks. All taste solutions and blanks (totaling 10 samples) were presented in random order. Between each sample, the panelists rinsed their mouths with filtered, de-ionized water. The panelists had to identify the intensity (low and high) of each taste solution. The ability to recognize eight out of the 10 taste solutions was used as cut-off point for selection purposes (arbitrary threshold set on the basis of previous studies, e.g. Albenzio et al., 2013). Then, panelists were trained for the scale use (Stone & Sidel, 2004). Based on results of a previous study on sensory profiling of Lucanian dry-sausages (Braghieri et al., 2016),
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an already reduced vocabulary represented by 10 key attributes was used and the panelists were trained with a specific reference frame in two two-hour sessions (Table 1). Under the guidance of the panel leader, the assessors determined which of the proposed references were most suitable to represent the previously identified sensory attributes. Two points of the scale were anchored to the reference material for training purposes. Then, for each assessment session, four samples were presented; each product was evaluated in triplicate. Samples were coded with three-digit randomized numbers and served in randomized order according to product, replication and assessor. Each subset of 4 products was identical in the 3 replications and among the 9 panelists. Six assessment sessions were needed to complete the KASP. For each sample, two 4.5 mm slices were cut using a commercial slicing machine and immediately served to the panelists. Both the slices and the plates were at room temperature (20–23 °C). Tests were performed at about 10.00 a.m. in a controlled sensory analysis laboratory (ISO 8589, 2007), equipped with individual booths and under red lighting to mask color differences in the samples. The interval between samples was approximately 10 min. Panelists were asked to drink a sip of still water at the beginning of the sensory evaluation and to eat unsalted crackers between samples to try to make the palate conditions similar for each sample. All attributes were rated on unstructured line scales of 100 mm, anchored at the extremities (0 = absent, 100 = very strong). 2.4. Temporal dominance of sensations The same nine panelists performing KASP were used. The panel had no experience in TDS and therefore attended four two-hour training sessions. Panelists were introduced to the notion of temporality of sensations with dark chocolate. Dark chocolate was chosen in order to facilitate the perception and explain the notion of temporality of sensations as it is characterized by a well-defined dynamic profile (Jager et al., 2014); subsequently, panelists tasted commercial sausages in order to refine these notions and relate them to the object of the experiment. According to Pineau et al. (2009), a dominant sensation was defined as the sensation that triggers most of the attention at a point of time, which may not be the most intense. Then, the panelists were trained to use the computerized TDS data capture system (FIZZ, Biosystemes, Courteno, France) and to evaluate the products following the protocol described below. Pineau et al. (2012) indicated that a maximum of 10 attributes could be evaluated using TDS; however, in this study only 5 out of 10 key attributes (overall flavor, hardness, oiliness, chewiness and pepper flavor) were selected, based on KASP results. Six evaluating sessions were performed. Each product was evaluated in triplicate. For each daily session, four samples (5 mm slice) were presented. Each
Table 1 List of sensory attributes of dry sausages and reference frame used by a 9-member trained sensory panel for Key attribute sensory profiling. Attributes
Definition
Low
High
Taste Saltiness Bitterness Flavor
Fundamental taste associated with sodium chloride Fundamental taste associated with quinine hydrochloride
2 g/L sodium chloride 0.27 g/L quinine hydrochloride
8 g/L sodium chloride 1.08 g/L quinine hydrochloride
Overall flavor Fennel flavor Sweet pepper flavor Pepper flavor Texture Hardness Adhesiveness Chewiness Oiliness
Flavor accociated with fennel seed
Fifteen-day seasoned commercial Lucanian sausage Cacciatore salami
Flavor accociated with sweet red pepper powder
Cacciatore salami
Flavor accociated with aromatic spices added to sausage
Commercial Lucanian sausage
Force required to compress the sample with the molars
Cubed Hungarian salami Two-month seasoned cubed commercial Lucanian sausage
Level of overall flavor
Force required to remove the sample from the palate Number of chews required to prepare the sample for swallowing Perception of the amount of fat released by the product during mastication
“Napoli” salami Commercial Lucanian sausage Commercial Lucanian sausage with sweet pepper “Napoli” salami Two-month seasoned cubed Sausage Cubed Ham
Cubed Hungarian salami
Two-month seasoned cubed commercial Lucanian sausage
Cubed dry cured ham
Cubed pancetta
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subset of 4 samples was randomized across the 2 preservative treatments, the 3 replications and the 9 panelists. A total of 24 samples (8 products × 3 replications) were evaluated. Tests were performed at about 10.00 a.m. in a controlled sensory analysis laboratory (ISO 8589, 2007), equipped with individual booths and under red lighting to mask color differences in the samples. Panelists were asked to drink a sip of still water at the beginning of the sensory evaluation and to eat unsalted crackers between samples to try to make the palate conditions similar for each sample. In this methodology, all the attributes were shown on the computer screen with their corresponding unstructured line scales of 100 mm, anchored at the extremities (low to high). The order in which the attributes were listed was randomized across panelists to limit the preferential use of the first attributes listed (Pineau et al., 2012). However, each panelist received the list of attributes always in the same order. Panelists were asked to put the sample in their mouth and then, immediately after, they clicked the start button to begin the evaluation. During the evaluation, the panelist had to consider which of the attributes was perceived as dominant in each moment. Each time the panelist felt the perception changed, the button corresponding to that attribute was to be clicked. Along the tasting of one sample (60 s), the panelist was free to select an attribute several times. They were also free not to choose the attributes they did not perceive. Data acquisition was set so as to stop at 60 s (Albert et al., 2012). 2.5. Statistical analyses Data were analyzed with SAS software (SAS Institute Inc., Cary, NC). Chemical composition was subjected to ANOVA with use of preservative (2 levels) as factor. Sensory profile data (KASP) were subjected to a mixed procedure to assess the fixed effect of preservative addition (2 levels) using product (8 levels) nested into preservative addition and assessor (9 levels) as random factors. The product nested into preservative addition variance was utilized as the error term to test the effect of preservative addition. For each attribute, a TDS score and a dominance rate (%) were calculated by the FIZZ software at each time point. TDS score is the mean intensity of an attribute (i.e. mean intensity scores weighted by duration of each elicitation), whereas duration is defined as “the total duration of a given attribute over all elicitations” (Pineau and Schlich, 2014). The dominance rate is the percentage of selections of an attribute as dominant (i.e. the attribute capturing the assessor attention throughout profiling until the appearance of a new sensation) at a particular time point. The higher the agreement among panelists, the better the dominance rate. TDS data were represented by curves showing for each point of time (recorded every 2 s) the percentage of runs (assessors × replications) for which the given attribute was selected as dominant. Chance level and significance level were calculated and drawn (Labbe, Schlich, Pineau, Gilbert, and Martin, 2009) in the figures representing the pooled TDS data of NS and NNS sausages. Chance level is the dominance rate that an attribute can obtain by chance considering all the attributes evaluated. Its value is equal to 1/p, p being the number of attributes. Attributes with dominant rates below chance level have to be considered negligible. Considering that the trained panel evaluated five attributes, chance level was 0.20, corresponding to a dominance rate of 20%. Accordingly, attributes presenting dominance rates below 20% were not considered dominant. Significance level is the minimum value of a dominance rate an attribute has to obtain to be significantly higher than chance level. TDS curves above the significance level may be considered to be consistent across the panel (Pineau et al., 2009). Significance level was calculated from the confidence interval of a binomial proportion based on a normal approximation taking into account chance level and the 27 evaluations performed by the panelists (9 assessors evaluating in triplicate the 8 products), which resulted in 0.325, corresponding to a dominance rate of 32.5%.
TDS data (scores and dominance rates) were subjected to a mixed procedure to assess the fixed effect of preservative addition (2 levels) using product (8 levels) nested into preservative addition and assessor (9 levels) as random factors. The product nested into preservative addition variance was utilized as the error term to test the effect of preservative addition. A principal component analysis (PCA) was performed on KASP (10 attributes) mean panel data (The Unscrambler X version 10.1 – Camo) to provide a multivariate graphical representation of the product space (8 products). A second PCA was performed on the correlation matrix of the TDS scores (5 attributes) and on the correlation matrix of the TDS dominance rates (5 attributes) to provide a multivariate graphical representation of the product space (8 products) based only TDS. A third PCA was conducted on the correlation matrix of the TDS scores (5 attributes), on the correlation matrix of the TDS dominance rates (5 attributes) and on the Key attribute scores (5 attributes) averaged across assessors in order to study the relationship between TDS and KASP data and their contribution to the differentiation of the 8 products. 3. Results and discussion 3.1. Chemical composition Chemical composition in terms of moisture (31.29 ± 0.50% vs 31.79 ± 0.50% for NNS and NS, respectively), protein (50.8 ± 0.60% vs 49.5 ± 0.60% for NNS and NS, respectively), lipid (33.95 ± 0.96% vs 32.95 ± 0.96% for NNS and NS, respectively) and ash (11.90 ± 0.36% vs 12.33 ± 0.36% for NNS and NS, respectively) percentages was not affected by the use of preservatives (P N 0.05). High fat levels characterized both types of product. Fat content in pork products has controversial effects as its reduction in fermented sausages affects texture attributes causing an increase in chewiness and hardness, and a decrease of consumer liking (Olivares, Navarro, Salvador, and Flores, 2010). However, a recurrent consumers' determinant for purchasing sausages is health (Braghieri et al., 2016), explaining why in other studies consumers preferred the sausages with lower levels of visible fat (Olivares et al., 2010). 3.2. Key-attribute sensory profiling Based on a mixed model (Table 2), NNS products were perceived with higher intensities of hardness (P b 0.05) and tended to be perceived with higher intensities of overall flavor, pepper flavor and oiliness as compared with NS products (P b 0.20). Although only one out of ten attributes was significantly different and three tended to be significant with low absolute difference values (4 to 8 mm) on a 100 mm scale, PCA of KASP mean panel data provided a multivariate graphical representation of the product space with the loadings (LV) of the different KASP attributes differentiating the products (Fig. 1). The first two principal components of the PCA accounted for 65% of the variance in the data (40% for the first component; 25% for the second component). Naturally cured products are mainly located on the upper side of the second component along with hardness, (LV = 0.56), overall flavor (LV = 0,43), pepper flavor (LV = 0.30), oiliness (LV = 0.33) and fennel flavor (LV = 0.33) intensities. Conversely nitrite cured products are placed on the lower side of the second component with the attributes chewiness (LV = − 0.28) and adhesiveness (LV = −0.25). According to Sindelar and Milkowski (2011), although evident differences exist between the cured and uncured types of the same product, little is known about what, specifically, is responsible for these differences. Flavor differences between products containing nitrite and those without may be due to the nitrite-related suppression of oxidation (Shahidi, Rubin, and Wood, 1988). Numerous volatile and nonvolatile compounds are involved in the development of sausage flavor as a consequence of proteolysis, lipolysis, and glycolysis activities
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Table 2 Attributes from QDA and TDS Duration and Score (Least square means) of dry-sausages as affected by use of preservatives. Standard Error (S.E.), mean squares, F and P values are also reported. Preservative addition
QDA Overall flavor Fennel flavor Sweet pepper flavor Pepper flavor Saltiness Bitterness Hardness Adhesiveness Chewiness Oiliness TDS duration Overall flavor Pepper flavor Hardness Chewiness Oiliness TDS score Overall flavor Pepper flavor Hardness Chewiness Oiliness a b
NSa
NNSb
58.83 29.57 18.07 20.00 34.14 44.45 32.00 40.67 42.72 15.04
62.98 32.01 18.62 27.92 32.84 44.42 43.82 40.34 35.10 21.44
16.13 4.24 10.28 9.67 15.81 42.37 11.06 48.28 48.90 28.31
Mean square F(1,6)
P-value
170 620 469 1140 4924 499 1016 888 2809 695
5.46 0.52 0.03 2.97 0.02 0.01 7.43 0.01 1.12 3.19
0.0972 0.4995 0.8590 0.1354 0.8965 0.9907 0.0344 0.9389 0.3314 0.1244
872 78.24 114 79 471
150 34.15 102 39 65
5.81 2.29 1.12 2.01 7.30
0.0525 0.1809 0.3305 0.2061 0.0355
4733 289 11518 0.70 1240
2085 199 8563 265 551
2.27 1.45 1.35 0 2.25
0.0635 0.1963 0.2902 0.9704 0.1843
S.E. Preservative addition
Product (preservative addition)
5.25 6.14 4.80 6.71 7.50 4.77 6.77 6.53 7.82 6.06
929 320 16 3392 91 0.07 7550 6 3135 2217
20.15 5.44 8.82 8.45 12.86
2.38 1.73 1.77 1.34 1.65
51.74 13.37 33.67 49.01 23.52
4.50 4.52 9.80 4.18 4.22
sausages added with nitrate, nitrite and L-ascorbic acid. Sausages with no preservatives.
resulting from the action of microbial and endogenous meat enzymes (Ahmad and Amer, 2013). Ramarathnam, Rubin, and Diosady (1991) indicated hexanal, carbonyl compounds, 3-methylheptane and methylcyclohexane as main compounds contributors to the flavor of meat processed without the addition of chemical preservatives. Possibly, the additives and their antioxidant activity may inhibit the natural development of such compounds. The same authors (Ramarathnam, Rubin, and Diosady, 1993) identified 2-metylcyclopentanol and 2butyl-2-octenol uniquely in the aroma of cured pork. 3.3. Temporal dominance of sensations Based on a mixed model (Table 2), NNS products showed lower oiliness duration (P b 0.05) and tended to show higher overall flavor and
pepper flavor durations and scores, whereas oiliness score tended to be lower as compared with NS products (P b 0.20). KASP and TDS data yielded similar results apart from oiliness, which tended to be higher in NNS according to KASP and higher in NS according to TDS duration and score, and hardness, which was higher in NNS according to KASP, whereas no differences were perceived in terms of TDS duration and score. The first two principal components of the PCA performed on TDS scores and durations (Fig. 2) accounted for 78% of the variance in the data (53% for the first component; 25% for the second component). Naturally cured products are located on the left side of the first component along with flavor duration and score (LV = −0.38 and −0.42, respectively) and Pepper flavor duration and score (LV = −0.34 and −0.30, respectively). Conversely nitrite cured products are mainly placed on
Fig. 1. Principal component analysis (PCA) bi-plot (The Unscrambler X version 10.1 – Camo) from mean Lucanian dry-sausage sensory profiling data based on Quantitative Descriptive Analysis. Four products were made adding nitrate, nitrite and L-ascorbic acid (P1, P2, P4, P6), whereas the other 4 were not (P3, P5, P7, P8).
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Fig. 2. Principal component analysis (PCA) bi-plot (The Unscrambler X version 10.1 – Camo) from mean Lucanian dry-sausage Temporal Dominance of Sensations scores (S) and durations (D). Four products were made adding nitrate, nitrite and L-ascorbic acid (P1, P2, P4, P6), whereas the other 4 were not (P3, P5, P7, P8).
the right side of the first component with the attributes hardness duration and score (LV = 0.25 and 0.27, respectively) and oiliness duration and score (LV = 0.37 and 0.27, respectively). PCA of KASP mean panel together with TDS mean scores provided further multivariate graphical representation of the relationship between the two methods (Fig. 3). The first two principal components of this PCA accounted for 70% of the variance in the data (46% for the first component; 24% for the second component). As also observed by other authors, TDS scores were highly correlated to the KASP scores (Labbe et al., 2009; Ng et al., 2012; Dvezeaux de Lavergne, van Delft et al., 2015); in our study, in particular, both TDS and KASP scores characterized the sausages in relation with the use of preservatives, as depicted in the PCA bi-plot. This figure shows that all the naturally cured sausages are located in the right side of the first component, where some attributes, such as overall and pepper flavors (LV = 0.25 and 0.28, respectively), are highly correlated with the corresponding TDS scores (LV = 0.37 and 0.0.28, respectively) and durations (LV = 0.31 and 0.31, respectively). The
cured products, on the contrary, are mainly located in the left side of the first component, where chewiness from KASP (LV = − 0.21), but also oiliness duration and score (LV = − 0.32 and − 0.27, respectively) and hardness duration and score (LV = − 0.19 and − 0.20, respectively) from TDS can be found. Oiliness and Hardness from TDS gave different results compared with KASP (i.e. in KASP NNS showed higher hardness and oiliness while TDS scores for hardness and oiliness were more related with NS products). As TDS gives a dynamic measure of the intensity of an attribute (i.e. TDS score is the mean intensity of an attribute weighted by duration; Ng et al., 2012), while QDA provides a single intensity value for each attribute at a given time point (Devezeaux de Lavergne et al., 2015), these differences may be attributed to the diverse approach used by the TDS procedure and confirm that the perception of intensity may be different from the perception of the dominant sensation (Ng et al., 2012). In fact, perception of aroma, taste and texture of foods is not a static process as eating with mastication and salivation are dynamic sensory processes.
Fig. 3. Principal component analysis (PCA) bi-plot (The Unscrambler X version 10.1 – Camo) from mean Lucanian dry-sausages sensory profiling data and Temporal Dominance of Sensations scores (S) and durations (D). Four products were made adding nitrate, nitrite and L-ascorbic acid (P1, P2, P4, P6), whereas the other 4 were not (P3, P5, P7, P8).
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Data from the four NS and four NNS sausages were pooled and reported in Figs. 4 and 5, respectively, to make easier the interpretation of the smoothed TDS curves. The first dominant attribute was hardness then, for products NS chewiness and flavor followed, whereas the last dominant sensation was oiliness (Fig. 4). Conversely, for products NNS overall flavor was the second most dominant attribute and it was as such for most of the evaluation time (Fig. 5). The first dominant attributes perceived by judges for all products were related with the textural properties of the products. Numerous authors obtained similar results (Bouteille et al., 2013; de Loubens et al., 2010; Saint-Eve, Panouill, Capitaine, Deleris, and Souchon, 2015) and Albert et al. (2012) noted that even in products characterized by low absolute intensity levels of textural attributes, they always represented the initial dominant perception, which correlates with the fracture properties of the product. This result is not surprising as the perception of textural properties is mainly related to tactile sensations, which in turn depend upon direct innervation of the inner surface of the mouth, and muscle activity starting with mastication, whereas for flavor and odor perception a link between receptors and active molecules is needed before the perceptive process can start (Rosenthal, 1999). Guinard and Mazzucchelli (1996) assigned to texture properties a fundamental role in affecting consumer acceptance and preference for foods. According to Hutchings and Lillford (1988), texture perception of food is a dynamic process as the physical characteristics change continuously when they are manipulated in the mouth in order to make food swallowable after that a swallowing threshold has been reached (Jalabert-Malbos, Mishellany-Dutour, Woda, and Peyron, 2007). The tongue is considered the principal organ involved in perceiving the textural properties of food (Loret et al., 2011) as it senses if food is chopped and moistened enough to be swallowed (Okada, Honma, Nomura, and Yamada, 2007). Thus, texture perception of food is complex, depending on multiple parameters (Devezeaux de Lavergne, van Delft, van de Velde, van Boekel, & Stieger, 2015), such as vision, hearing, touch and kinaesthetic perception (Szcesniak, 2002). In addition, the structure of the food matrix is a key factor affecting the release of flavor compounds during chewing (Foster et al.,
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2011). In QDA textural properties are incorporated next to aroma and taste properties in order to obtain a complete sensory profile of products. Lenfant et al. (2009) demonstrated the importance of TDS analysis in texture perception that can be expressed as sensory trajectories (i.e. in terms of appearance and disappearance of dominant sensory attributes). Differences in dominance perception between the products are depicted in Fig. 6. From 10 to 40 s no differences were perceived, whereas in the second part of tasting, in agreement with the results obtained by the PCA on TDS scores and KASP (Fig. 2), the use of preservatives may have inhibited the perception of flavor, which instead was perceived more in naturally cured sausages. In a previous study on Podolian bresaola Braghieri et al. (2009) observed that taste/flavor were the most influential attributes driving consumer liking, whereas, more recently, they were identified among the main consumer choice determinants in sausages (Braghieri et al., 2016). However, in agreement with Albert et al. (2012), TDS was able to provide complementary information about the dynamic evolution of sensory perception during dry sausage tasting. In particular, in both NS and NNS products we observed that overall flavor followed textural attributes in time, prevailing over the others. However, in products NS the use of preservatives prevented the perception of this attribute to be persistent, thus allowing oiliness to become dominant in the last part of tasting. Conversely, when chemical preservatives were not added (i.e. in NNS), the perception of flavor increased up to the end of the tasting session. Both KASP and TDS showed that flavor perception was higher and more persistent in NNS sausages; thus, sausage manufacturers should take this result into account, as flavor and taste are the most influential attributes driving consumer liking. However, when assessing dry sausage sensory properties, TDS should not be viewed as a potential equivalent or replacer of QDA; along with Meillon, Urbano, and Schlich (2009), it should be rather considered as a complementary technique providing additional information capable to identify even subtle differences between products, which may develop during mastication. In fact, KASP showed that the perception of the textural parameter oiliness during mastication tended to be higher in sausages manufactured without the addition of preservatives, whereas TDS displayed that the perception of this
Fig. 4. Temporal dominance of sensations curves (TDS) for sausages with preservatives (NS). The black line indicates chance level and the blue line the significance level (5%). (For interpretation of the references to in this figure legend, the reader is referred to the web version of this article.)
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Fig. 5. Temporal dominance of sensations curves (TDS) for sausages without preservatives (NNS). The black line indicates chance level and the blue line the significance level (5%). (For interpretation of the references to in this figure legend, the reader is referred to the web version of this article.)
attribute increased during tasting and became dominant for most of the session in NS products. Thus TDS and QDA, used together as synergic methods, can provide a more complete product profile while identifying specific characteristics of typical products such as Lucanian dry sausage in order to differentiate them from other commercial products. In addition, TDS can be effectively used to assess the consequences of the modification of process phases. For instance, as a practical implication of this study, a reduction of added fat in preservative added sausages may be suggested in order to reduce a long lasting perception of oiliness in these products.
4. Conclusions In conclusion, both QDA and TDS showed that preservative addition did not markedly affect sausage sensory properties. Both methods gave similar results about the higher and more persistent flavor perception in NNS sausages. However, based on conventional QDA the perception of the textural parameter oiliness during mastication tended to be higher in sausages manufactured without the addition of preservatives, whereas TDS showed that the perception of this attribute increased during tasting and became dominant for most of the session in NS products.
Fig. 6. Differences in temporal dominant sensations (TDS) between sausages without preservatives (NNS) and sausages with preservatives (NS). Curves above the x-axis indicate dominance rates significantly higher in sausages without preservatives (NNS).
A. Braghieri et al. / Meat Science 122 (2016) 68–75
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