Development and characterization of a new nonenzymatic colored time–temperature indicator
Zahoor Uddin
Department of Food Science and Technology, Faculty of agro-Industry, Kasetsart University, Bangkok, Thailand
Search for more papers by this authorCorresponding Author
Waraporn Boonsupthip
Department of Food Science and Technology, Faculty of agro-Industry, Kasetsart University, Bangkok, Thailand
Correspondence
Waraporn Boonsupthip, Department of Food Science and Technology, Faculty of agro-Industry, Kasetsart University, Bangkok 10900, Thailand.
Email: [email protected]
Search for more papers by this authorZahoor Uddin
Department of Food Science and Technology, Faculty of agro-Industry, Kasetsart University, Bangkok, Thailand
Search for more papers by this authorCorresponding Author
Waraporn Boonsupthip
Department of Food Science and Technology, Faculty of agro-Industry, Kasetsart University, Bangkok, Thailand
Correspondence
Waraporn Boonsupthip, Department of Food Science and Technology, Faculty of agro-Industry, Kasetsart University, Bangkok 10900, Thailand.
Email: [email protected]
Search for more papers by this authorAbstract
Time–temperature indicators (TTIs) are effective tool for monitoring food quality during processing and distribution. In this study, a new colored nonenzymatic browning (fructose and glycine)-based TTI was developed. Twelve TTIs were made at four different substrate concentrations and three pH ranges 8.0–10.0. The mathematical models of each TTI were drawn up, which showed the relationships between the color change in terms of absorbance (420 nm), time and temperature. The activation energies (Ea), calculated from Arrhenius relationship ranged between 58.09 and 95.54 kJ mol−1 of all TTIs. Activation energies could be changed to match the Ea of food product, by modifying pH and the proportion of the fructose and glycine. A visual color change of TTI and a wide range of activation energy illustrated that this new chemical-based TTI could be applied to show the time–temperature history of foodstuffs, and to indicate the food quality, which is associated with the undergoing of the time–temperature exposure.
Practical applications
This work provides the development of a new smart temperature indicator based on nonenzymatic browning. The indicators are more useful for food quality monitoring from manufacturing till consumer consumption. However, the application of the TTI's can be extended to food processing, that is, sterilization, pasteurization, and drying process. Thus, the use of the TTIs can encourage food producers to scrutinize food processing and distribution to deliver good quality to consumers with guaranteed security.
REFERENCES
- Ajandouz, E. H., & Puigserver, A. (1999). Non-enzymatic browning reaction of essential amino acids: Effect of pH on caramelization and Maillard reaction kinetics. Journal of Agriculture & Food Chemistry, 1(15), 928–943.
- Ames, J. M., & Benjamin, C. (2003). Browning: Non-enzymatic. Encyclopedia of food sciences & nutrition (pp. 665–672). Oxford: Academic Press.
- Babalis, S. J., & Belessiotis, V. G. (2004). Influence of the drying conditions on the drying constants and moisture diffusivity during the thin-layer drying of figs. Journal of Food Engineering, 65, 449–458.
- Baranyi, J., Roberts, T. A., & McClure, P. J. (1993). A nonautonomous differential equation to model bacterial growth. Food Microbiology, 10(1), 43–59.
- Chayjan, R., Amiri, P. J., & Esna-Ashari, M. (2011). Modeling of moisture diffusivity, activation energy and specific energy consumption of high moisture corn in a fixed and fluidized bed convective dryer. Spanish Journal of Agriculture Research, 9(1), 28–40.
- Chayjan, R. A., Kamran, S., Qasem, A., & Sabziparvar, A. A. (2013). Modeling moisture diffusivity, activation energy and specific energy consumption of squash seeds in a semi fluidized and fluidized bed drying. Journal Food Science Technology, 50(4), 667–677.
- Echavarría, A. P., Pagán, J., & Ibarz, A. (2016). Optimization of Maillard reaction products isolated from sugar-amino acid model system and their antioxidant activity. Afinidad, 70(562), 86–92.
- Fryer, P. J., Mark, J. H., Phil, W. C., Mehauden, K., Hansriwijit, S., Challou, F., & Serafim, B. (2011). Temperature Integrators as tools to validate thermal processes in food manufacturing. Procedia Food Science, 1, 1272–1277.
10.1016/j.profoo.2011.09.188 Google Scholar
- Garza, S., Ibarz, A., Pagán, J., & Giner, J. (1999). Non-enzymatic browning in peach puree during heating. Food Research International, 32(5), 335–341.
- Grijspeerdt, K., & Vanrolleghem, P. (1999). Estimating the parameters of the Baranyi model for bacterial growth. Food Microbiology, 16(6), 593–605.
- Guiavarc'h, Y. P., Van Loey, A. M., & Hendrickx, M. E. (2005). Extended study on the influence of z-value(s) of single and multicomponent time temperature integrators on the accuracy of quantitative thermal process assessment. Journal of Food Protection, 68, 384–395.
- İbrahim, D. (2011). Determination of Infrared Drying Characteristics and Modelling of Drying Behaviour of Carrot Pomace. Journal of Agricultural Sciences, 19, 44–53.
- Kim, K., Kim, E., & Lee, S. J. (2012). New enzymatic time-temperature integrator (TTI) that uses laccase. Journal of Food Engineering, 113, 118–123.
- Koutsoumanis, K., Stamatio, A., Skandamis, P., & Nychas, G. J. E. (2006). Development of a microbial model for the combined effect of temperature and pH on spoilage of ground meat, and validation of the model under dynamic temperature conditions. Applied and Environmental Microbiology, 72(1), 124–134.
- Labuza, T. P., Fu, B., & Taoukis, P. S. (1992). Prediction for shelf life and safety of minimally processed CAP/MAP chilled foods. Journal of Food Protection, 55, 741–750.
- Lee, S. J., & Boonsupthip, W. (2015). Mathematical modeling of Browning induction period in drying onion as influenced by temperature, equilibrium relative humidity, and inhibitor. International Journal of Drying Technology, 33, 120–127.
- Lertittikul, W., Benjakul, S., & Tanaka, M. (2007). Characteristics and antioxidative activity of Maillard reaction products from a porcine plasma protein–glucose model system as influenced by pH. Food Chemistry, 100(2), 669–677.
- Liu, G., Wang, Y., & Wang, Z. (2011). Nuclear magnetic resonance (NMR)-based metabolomic studies on urine and serum biochemical profiles after chronic cysteamine supplementation in rats. Journal of Agriculture Food Chemistry, 59, 5572–5578.
- Li, Y., Yang, Y., & Yu, A. N. (2016). Effects of reaction parameters on generation of volatile compounds from the Maillard reaction between L-ascorbic acid and glycine. International Journal of Food Science & Technology, 51(6), 1349–1359.
- Lim, S. H., Woo, Y. C., Byung, H. S., & Kwang, W. H. (2014). Development of a microbial time-temperature integrator system using lactic acid bacteria. Journal of Food Science & Biotchnology, 23(2), 483–487.
- López, J., Uribe, E., Vega-Gálvez, A., Miranda, M., Vergara, J., Gonzalez, E., & Di Scala, K. (2010). Effect of air temperature on drying kinetics, vitamin C, antioxidant activity, total phenolic content, non-enzymatic browning and firmness of blueberries variety O'Neil. Food and Bioprocess Technology, 3, 772–777.
- Macrane, R., Robinson, K., & Saadler, M. J. (1993). Encyclopedia of food science, food technology and nutrition. Vol (p. 1). London: Academic Press Limited.
- Mafalda, A., Quintas, C., & Teresa, R. (2007). Branda˜o, S., Cristina L., Silva, M. Modelling colour changes during the caramelisation reaction. Journal of Food Engineering., 83(4), 483–491.
- Martins, S., & van Boekel, M. A. J. S. (2003). Extinction coefficient of melanoidins in the glucose/glycine Maillard reaction: Influence of pH and temperature. Food Chemistry, 83(1), 135–142.
- Martins, S., & Van Boekel, M. A. J. S. (2009). A kinetic model for the glucose/ glycine Maillard reaction pathways. Food Chemistry, 90(1-2), 257–269.
- Matmaroh, K., Benjakul, S., & Tanaka, M. (2006). Effect of reactant concentrations on the maillard reaction in a fructose-glycine model system and the inhibition of black tiger shrimp polyphynoloxidase. Journal of Food Chemistry, 98, 1–8.
- McMeekin, T. A., Olley, J., Ross, T., & Ratkowsky, D. A. (1993). Predictive microbiology: Theory and application. Taunton, UK: Research Studies Press.
- Minaei, S., Motevali, A., Ahmadi, E., & Azizi, M. H. (2012). Mathematical models of drying pomegranate arils in vacuum and microwave dryers. Journal of agricultural Science and Technology, 14, 311–325.
- Mohamed, M. S., Tan, J. S., Kadkhodaei, S., Mohamad, R., Mokhtar, M. N., & Ariffa, A. B. (2014). Kinetics and modeling of microalga Tetraselmis sp. FTC 209 growth with respect to its adaptation toward different trophic conditions. Journal of Biochemical Engineering, 88, 30–41.
- Motevali, A., Ahmadi Chenarbon, H., Minaei, S., Bassiri, A. R., Almassi, M., & Arabhosseini, A. (2012). Effect of drying on the color of St. John's wort (Hypericum perforatum L.) leaves. International Journal of Food Engineering, 8, 1556–3758.
- Nelson, L. (1948). Usnic acid, an antibiotic, and sperm metabolism. The Biological Bullitton, Wood's Hole, 95, 286–287.
- O'Brien, M., & Taghert, P. H. (1998). A peritracheal neuropeptide system in insects: Release of myomodulin-like peptides at ecdysis. Journal of Experimental Biology, 201(2), 193–209.
- Riva, M., Piergiovanni, L., & Schiraldi, A. (2001). Performances of time–temperature indicators in the study of temperature exposure of packaged fresh foods. Packaging Technology Science, 14(1), 1–9.
- Taoukis, P. S. (1989). Time-Temperature Indicators as shelf life monitors of food products. Journal of Food Distribution, 4, 9–18.
- Taoukis, P., & Labuza, T. P. (2003). Time-temperature indicators (TTIs). In R. Ahvenainen (Ed.), Novel food packaging techniques (p. 590). Cambridge, UK: Woodhead Publishing Ltd. ISBN 978-0849317897.
10.1533/9781855737020.1.103 Google Scholar
- Tucker, G. S., Lambourne, T., Adams, J. B., & Lach, A. (2002). Application of a biochemical time-temperature integrator to estimate pasteurization values in continuous food processes. Innovative Food Science & Emerging Technology, 3(2), 165–174.
- Vaikousi, H., Biliaderis, C. G., & Koutsoumanis, K. P. (2008). Development of a microbial time-temperature indicator prototype for monitoring the microbiological quality of chilled foods. Applied and Environmental Microbiology, 74(10), 3242–3250.
- Valdramidis, V., Cullen, P., Tiwari, B., & O'donnell, C. (2010). Quantitative modelling approaches for ascorbic acid degradation and non-enzymatic browning of orange juice during ultrasound processing. Journal of Food Engineering, 96(3), 449–445.
- Voegel-Turenne, C., Mahfouz, M., & Allaf, K. (1999). Three models for determining the induction time in the browning kinetics of the Granny Smith apple under Static conditions. Journal of Food Engineering, 41(3), 133–139.
- Warmbier, H. C., Schnlckels, R. A., & Labuza, T. P. (1976). Effect of glycerol on non-enzymatic Bbowning in a solid intermediate moisture model food system. Journal of Food Science, 41(3), 528–531.
- Yan, S., Huawei, C., Limin, Z., Fazheng, R., Luda, Z., & Hengtao, Z. (2008). Development and characterization of a new amylase type time–temperature indicator. Food Control, 19(3), 315–319.
- Yong-Yan, Z., Ya, L., & Ai-Nong, Y. U. (2016). The effects of reactants ratios, reaction temperatures and times on Maillard reaction products of the L-ascorbic acid/L-glutamic acid system. Food Science & Technology, 36(2), 268–274.
- Zwietering, M. H., Jonegenburger, I., Rombouts, F. M., & van't Riet, K. (1990). Modeling of the bacterial growth curve. Applied and Environmental Microbiology, 56, 1876–1881.