Design of Predictive Tools to Estimate Freshness Index in Farmed Sea Bream (Sparus aurata) Stored in Ice
Abstract
:1. Introduction
2. Materials and Methods
2.1. Fish, Storage Conditions and Sampling
2.2. Physico–Chemicals Analysis in Seabreams Stored in Ice
2.2.1. Freshness Degree Measured by Torrymeter® (TM)
2.2.2. Temperature Measurements and pH
2.2.3. Total Volatile Basic Nitrogen (TVB-N)
2.3. Microbiological Counts in Fish
2.4. Sensory Analyses for Freshness Assessment (Analytical Procedure)
Sensory Score Sheets Employed
2.5. Statistical Analysis
Design of Predictive Tools and External Validation
3. Results and Discussion
3.1. Physico–Chemical Parameters in Seabream Stored in Ice
3.2. Microbial Counts in Seabream Stored in Ice
3.3. Sensory Profiles and Characterization of Fish Spoilage
3.4. Global Analysis and Design of Predictive Tools
3.5. Validation for Predictive Tools Developed
4. Conclusions
Author Contributions
Funding
Conflicts of Interest
References
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Days | TORRY | QIM | EU | TM | TVB-N | pH | ST | IT | PST | MVC | ET | PS | |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|
0 | m | 92.24 a | 89.08 a | 94.76 a | 14.00 a | 5.40 a | 6.50 | 0.26 | 0.10 | ND | ND | ND | ND |
s | 1.34 | 5.21 | 1.10 | 0.28 | 0.76 | 0.00 | 0.11 | 0.14 | ND | ND | ND | ND | |
1 | m | 84.77 a | 85.30 a | 83.33 b | 13.17 a | 8.44 ab | 6.50 | 0.15 | 0.09 | 3.00 a | 3.23 a | 0.43 a | 1.16 a |
s | 10.25 | 1.71 | 13.77 | 0.06 | 4.27 | 0.00 | 0.13 | 0.07 | 0.76 | 0.53 | 0.74 | 0.33 | |
2 | m | 83.72 ab | 69.17 bc | 80.60 b | 12.09 a | 8.59 ab | 6.65 | 0.34 | 0.32 | 4.01 ab | 3.51 a | 1.39 abc | 1.60 a |
s | 4.85 | 10.03 | 5.68 | 0.53 | 1.76 | 0.28 | 0.41 | 0.35 | 0.51 | 0.76 | 1.32 | 0.44 | |
3 | m | 80.61 ab | 63.28 bc | 76.28 bc | 12.52 a | 10.21 bc | 6.41 | 0.25 | −0.04 | 4.36 ab | 3.48 a | 1.82 abc | 1.98 a |
s | 2.50 | 7.72 | 6.68 | 0.10 | 1.63 | 0.07 | 0.43 | 0.11 | 0.40 | 0.46 | 0.82 | 0.31 | |
5 | m | 77.15 abc | 64.13 bc | 69.00 c | 10.87 abc | 12.82 bc | 6.45 | 0.18 | 0.01 | 3.92 b | 3.40 a | 1.59 abcd | 2.55 ab |
s | 8.97 | 10.58 | 4.48 | 1.03 | 1.37 | 0.16 | 0.09 | 0.06 | 0.94 | 0.12 | 1.42 | 0.42 | |
6 | m | 68.45 abc | 52.91 cd | 57.30 d | 9.55 bc | 12.54 bcd | 6.43 | 0.42 | −0.02 | 4.44 bc | 3.60 a | 1.76 abcd | 2.77 b |
s | 3.41 | 12.52 | 5.29 | 2.24 | 1.89 | 0.17 | 0.42 | 0.14 | 0.63 | 0.15 | 1.22 | 0.33 | |
7 | m | 64.40 cde | 42.50 d | 50.08 de | 7.86 bc | 12.85 bcd | 6.30 | 0.31 | −0.09 | 4.97 bcd | 4.02 ab | 2.68 bc | 2.83 b |
s | 6.37 | 8.42 | 1.97 | 2.42 | 2.64 | 0.00 | 0.28 | 0.10 | 0.72 | 0.66 | 0.20 | 0.25 | |
8 | m | 59.99 de | 41.21 d | 49.77 de | 6.64 cd | 13.88 cde | 6.44 | 0.40 | 0.17 | 5.43 cd | 4.32 ab | 3.08 cd | 3.01 b |
s | 2.44 | 10.08 | 2.41 | 3.15 | 2.33 | 0.28 | 0.07 | 0.50 | 1.00 | 0.63 | 0.33 | 0.24 | |
10 | m | 52.62 ef | 37.37 d | 48.10 de | 5.61 e | 17.15 de | 6.47 | 0.19 | 0.23 | 6.89 e | 5.04 b | 3.14 cde | 2.99 b |
s | 6.67 | 10.37 | 3.81 | 3.40 | 1.45 | 0.44 | 0.10 | 0.36 | 0.09 | 1.01 | 0.25 | 0.37 | |
13 | m | 42.54 f | 32.20 e | 44.01 e | 4.44 e | 17.71 e | 6.52 | 0.02 | 0.19 | 8.30 e | 6.42 c | 4.46 e | 3.39 b |
s | 12.98 | 6.62 | 2.85 | 3.68 | 1.81 | 0.51 | 0.04 | 0.50 | 0.07 | 0.84 | 0.68 | 0.36 | |
16 | m | 36.52 f | 33.16 e | 38.40 e | 2.16 e | 17.97 e | 6.83 | 0.07 | 0.48 | 8.85 e | 7.52 d | 4.67 e | 3.71 c |
s | 19.18 | 0.00 | 0.59 | 2.98 | 3.27 | 0.72 | 0.04 | 0.71 | 0.38 | 0.64 | 0.02 | 0.38 | |
*** | *** | *** | *** | *** | NS | NS | NS | *** | ** | *** | ** |
Variable Contrasted | Variable Compared | r2 | Variable Compared | r2 | Variable Compared | r2 |
---|---|---|---|---|---|---|
Sensory Analyses (SFI) | ||||||
TORRY | EU | 0.942 *** | QIM | 0.908 *** | TVB-N | −0.953 *** |
TORRY | TM | 0.970 *** | PST/ET | ≤−0.965 *** | MVC/PS | ≤−0.925 *** |
EU | QIM | 0.951 *** | TM | 0.965 *** | TVB-N | −0.908 *** |
EU | PST | −0.853 *** | MVC | −0.769 ** | ET/PS | ≤−0.917 *** |
QIM | TM | 0.921 *** | TVB-N | −0.859 *** | PST | −0.853 * |
QIM | MVC | −0.769 ** | ET | −0.930 *** | PS | −0.915 *** |
Physicochemical Parameters | ||||||
TM | TVB-N | −0.910 *** | ET | −0.958 *** | PST | −0.920 *** |
TM | MVC | −0.861 ** | PS | −0.911 *** | ||
TVB-N | MVC | 0.860 *** | PS | 0.962 *** | ET/PST | ≥0.901 *** |
PH | IT | 0.881 *** | ||||
IT | PST | 0.594 * | MVC | 0.685 * | ||
TM | TVB-N | −0.761 ** | ST | −0.674 * | ||
Microbiological Count | ||||||
PST | MVC | 0.969 *** | ET | 0.962 ** | PS | 0.866 *** |
MVC | ET | 0.904 *** | PS | 0.780 ** | ||
ET | PS | 0.895 *** | ||||
Storage Time (ST) | ||||||
ST | TORRY | −0.990 *** | EU | −0.925 *** | QIM | −0.880 *** |
ST | PST | 0.970 *** | ET | 0.958 *** | PS/MVC | 0.936 *** |
ST | TM | −0.957 *** | TVB-N | 0.960 *** |
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Calanche, J.; Pedrós, S.; Roncalés, P.; Beltrán, J.A. Design of Predictive Tools to Estimate Freshness Index in Farmed Sea Bream (Sparus aurata) Stored in Ice. Foods 2020, 9, 69. https://doi.org/10.3390/foods9010069
Calanche J, Pedrós S, Roncalés P, Beltrán JA. Design of Predictive Tools to Estimate Freshness Index in Farmed Sea Bream (Sparus aurata) Stored in Ice. Foods. 2020; 9(1):69. https://doi.org/10.3390/foods9010069
Chicago/Turabian StyleCalanche, Juan, Selene Pedrós, Pedro Roncalés, and José Antonio Beltrán. 2020. "Design of Predictive Tools to Estimate Freshness Index in Farmed Sea Bream (Sparus aurata) Stored in Ice" Foods 9, no. 1: 69. https://doi.org/10.3390/foods9010069
APA StyleCalanche, J., Pedrós, S., Roncalés, P., & Beltrán, J. A. (2020). Design of Predictive Tools to Estimate Freshness Index in Farmed Sea Bream (Sparus aurata) Stored in Ice. Foods, 9(1), 69. https://doi.org/10.3390/foods9010069