Meta-analysis of Kinetic Parameter Uncertainty on Shelf Life Prediction in the Frozen Fruits and Vegetable Chain

Food Engineering Reviews - Tập 11 Số 1 - Trang 14-28 - 2019
Maria C. Giannakourou1, Petros Taoukis2
1Department of Food Science and Technology, University of West Attica (former Technological Educational Institute of Athens), Egaleo, Greece
2School of Chemical Engineering, Laboratory of Food Chemistry and Technology, National Technical University of Athens, Athens, Greece

Tóm tắt

Từ khóa


Tài liệu tham khảo

Bonat Celli G, Ghanem A, Su-Ling Brooks M (2016) Influence of freezing process and frozen storage on the quality of fruits and fruit products. Food Rev Int 32:280–304. https://doi.org/10.1080/87559129.2015.1075212

Corradini MG, Peleg M (2006b) Prediction of vitamins loss during non-isothermal heat processes and storage with non-linear kinetic models. Trends Food Sci Technol 17(1):24–34

Mattick KL, Legan JD, Humphrey TJ, Peleg M (2001) Calculating Salmonella inactivation in nonisothermal heat treatments from isothermal nonlinear survival curves. J Food Prot 64(5):606–613

Periago PM, van Zuijlen A, Fernandez PS, Klapwijk PM, ter Steeg PF, Corradini MG, Peleg M (2004) Estimation of the non-isothermal inactivation patterns of Bacillus sporothermodurans IC4 spores in soups from their isothermal survival data. Int J Food Microbiol 95(2):205–218

Valdramidis VP, Geeraerd AH, Bernaerts K, Van Impe JF (2006) Microbial dynamics versus mathematical model dynamics: the case of microbial heat resistance induction. Innov Food Sci Emerg 7:80–87. https://doi.org/10.1016/j.ifset.2005.09.005

Charoenrein S, Harnkarnsujarit N (2016) Food Freezing and Non-Equilibrium States. In: Non-Equilibrium States and Glass Transitions in Foods: Processing Effects and Product-Specific Implications. pp 39–62. doi: https://doi.org/10.1016/b978-0-08-100309-1.00004-3

Reid DS, Sajjaanantakul T, Lillford PJ, Charoenrein S (2010) Water Properties in Food, Health, Pharmaceutical and Biological Systems: ISOPOW 10. Water properties in food, health, pharmaceutical and biological systems: ISOPOW 10. doi: https://doi.org/10.1002/9780470958193

Biliaderis CG, Swan RS, Arvanitoyannis I (1999) Physicochemical properties of commercial starch hydrolyzates in the frozen state. Food Chem 64:537–546. https://doi.org/10.1016/S0308-8146(98)00165-4

Manzocco L, Nicoli MC, Anese M, Pitotti A, Maltini E (1998) Polyphenoloxidase and peroxidase activity in partially frozen systems with different physical properties. Food Res Int 31:363–370. https://doi.org/10.1016/S0963-9969(98)00095-7

Terefe NS, Hendrickx M (2002) Kinetics of the pectin Methylesterase catalyzed De-esterification of pectin in frozen food model systems. Biotechnol Prog 18:221–228. https://doi.org/10.1021/bp010162e

Terefe NS, Van Loey A, Hendrickx M (2004) Modelling the kinetics of enzyme-catalysed reactions in frozen systems: the alkaline phosphatase catalysed hydrolysis of di-sodium-p-nitrophenyl phosphate. Innov Food Sci Emerg 5:335–344. https://doi.org/10.1016/j.ifset.2004.05.004

Syamaladevi RM, Sablani SS, Tang J, Powers J, Swanson BG (2011) Stability of anthocyanins in frozen and freeze-dried raspberries during long-term storage: in relation to glass transition. J Food Sci 76:E414–E421. https://doi.org/10.1111/j.1750-3841.2011.02249.x

Syamaladevi RM, Manahiloh KN, Muhunthan B, Sablani SS (2012) Understanding the influence of state/phase transitions on ice recrystallization in Atlantic Salmon (Salmo salar) during frozen storage. Food Biophys 7:57–71. https://doi.org/10.1007/s11483-011-9243-y

Zhang Y, Zhao J-H, Ding Y, Nie Y, Xiao H-W, Zhu Z, Tang X-M (2017) Effects of state/phase transitions on the quality attributes of mango (Mangifera indica L.) during frozen storage. Int J Food Sci Technol 52:239–246. https://doi.org/10.1111/ijfs.13275

Huang K, Tian H, Gai L, Wang J (2012) A review of kinetic models for inactivating microorganisms and enzymes by pulsed electric field processing. J Food Eng 111:191–207. https://doi.org/10.1016/j.jfoodeng.2012.02.007

DerSimonian R, Laird N (1986) Meta-analysis in clinical trials. Control Clin Trials 7:177–188. https://doi.org/10.1016/0197-2456(86)90046-2

Sutton AJ, Abrams KR, Jones DR (2001) An illustrated guide to the methods of meta-analysis. J Eval Clin Pract 7:135–148. https://doi.org/10.1046/j.1365-2753.2001.00281.x

Van Boekel MAJS (1996) Statistical aspects of kinetic modeling for food science problems. J Food Sci 61:477–486. https://doi.org/10.1111/j.1365-2621.1996.tb13138.x

Gonçalves EM, Abreu M, Brandão TRS, Silva CLM (2011a) Degradation kinetics of colour, vitamin C and drip loss in frozen broccoli (Brassica oleracea L. ssp. Italica) during storage at isothermal and non-isothermal conditions. Int J Refrig 34:2136–2144. https://doi.org/10.1016/j.ijrefrig.2011.06.006

Gonçalves EM, Pinheiro J, Abreu M, Brandão TRS, Silva CLM (2011b) Kinetics of quality changes of pumpkin (Curcurbita maxima L.) stored under isothermal and non-isothermal frozen conditions. J Food Eng 106:40–47. https://doi.org/10.1016/j.jfoodeng.2011.04.004

Huang L (2015a) Direct construction of predictive models for describing growth of Salmonella Enteritidis in liquid eggs - a one-step approach. Food Control 57:76–81. https://doi.org/10.1016/j.foodcont.2015.03.051

Valdramidis VP, Geeraerd AH, Bernaerts K, Van Impe JFM (2008) Identification of non-linear microbial inactivation kinetics under dynamic conditions. Int J Food Microbiol 128:146–152. https://doi.org/10.1016/j.ijfoodmicro.2008.06.036

Valdramidis VP, Taoukis PS, Stoforos NG, Van Impe JFM (2012) In: Cullen PJ, Tiwari BK, Valdramidis VP (eds) novel thermal and non-thermal technologies for fluid foods. Academic Press, London, UK doi: https://doi.org/10.1016/b978-0-12-381470-8.00014-1

Taoukis PS, Giannakourou MC (2018) Modelling food quality. Food Sci Technol (London) 32:38–43

Giannakourou MC, Stoforos NG (2016) In: Carvajal-Millan E, Mohan CO, Ravishankar CN (eds) food process engineering and quality assurance, apple academic press Inc., NJ, USA

Peleg M, Normand MD, Dixon WR, Goulette TR (2018) Modeling the degradation kinetics of ascorbic acid. Crit Rev Food Sci 58:1478–1494. https://doi.org/10.1080/10408398.2016.1264360

Peleg M (2003) Microbial survival curves: interpretation, mathematical modeling, and utilization. Comments on Theoretical Biology 8:357–387

Peleg M, Normand MD, Corradini MG (2005) Generating microbial survival curves during thermal processing in real time. J Appl Microbiol 98:406–417

Taoukis PS, Labuza TP, Saguy S (1997) In: Valentas KJ, Rotstein E,Singh RP (Eds) Handbook of food engineering practice. New York: CRC Press

Van Boekel MAJS (2008) Kinetic modeling of food quality: a critical review. Compr Rev Food Sci Food 7:144–158. https://doi.org/10.1111/j.1541-4337.2007.00036.x

Fu B, Labuza TP (1993) Shelf life prediction: theory and applications. Food Prot 4(3):125–133

Corradini MG, Peleg M (2006a) On modeling and simulating transitions between microbial growth and inactivation or vice versa. Int J Food Microbiol 108:22–35

Arrhenius SA (1889) Über die Dissociationswärme und den Einfluß der Temperatur auf den Dissociationsgrad der Elektrolyte. Z Phys Chem 4:96–116. https://doi.org/10.1515/zpch-1889-0408

Peleg M, Normand MD, Corradini MG (2012a) The Arrhenius equation revisited. Crit Rev Food Sci 52(9):830–851

Peleg M, Normand MD, Corradini MG (2017) A new look at kinetics in relation to food storage. Annu Rev Food Sci Technol 8:135–153

Williams ML, Landel RF, Ferry JD (1955) The temperature dependence of relaxation mechanisms in amorphous polymers and other glass-forming liquids. J Chem Eng 77:3701–3707

Peleg M (1992) On the use of the WLF model in polymers and foods. Crit Rev Food Sci Nutr 32:59–66. https://doi.org/10.1080/10408399209527580

Peleg M, Engel R, Gonzalez-Martinez C, Corradini MG (2002) Non-Arrhenius and non-WLF kinetics in food systems. J Sci Food Agric 82(12):1346–1355

Nelson KA, Labuza TP (1994) Water activity and food polymer science: implications of state on Arrhenius and WLF models in predicting shelf life. J Food Eng 22:271–289. https://doi.org/10.1016/0260-8774(94)90035-3

Taoukis PS, Tsironi TS, Giannakourou MC (2015) handbook of food processing and engineering. In: Tzia K, Varzakas T (eds) food engineering fundamentals, vol I. CRC press, Boca Raton, Florida, USA

Peleg M, Normand MD, Corradini MG (2012b) On Quantifying Nonthermal Effects on the Lethality of Pressure-Assisted Heat Preservation Processes. J Food Sci 77:R47–R56. https://doi.org/10.1111/j.1750-3841.2011.02444.x

Giannakourou MC, Taoukis PS (2003c) Stability of dehydrofrozen green peas pretreated with nonconventional osmotic agents. J Food Sci 68:2002–2010

Labuza TP (1982) Shelf-Life Dating of Foods. Food & Nutrition Press, Inc., Westport

Taoukis PS (2011) In: Heldman DR, Moraru CI (eds) Encyclopedia of Agricultural, Food and Biological Engineering, Vol. II, 2nd edn. CRC Press, Taylor & Francis Group, New York

Dermesonluoglu E, Katsaros G, Tsevdou M, Giannakourou M, Taoukis P (2015) Kinetic study of quality indices and shelf life modelling of frozen spinach under dynamic conditions of the cold chain. J Food Eng 148:13–23. https://doi.org/10.1016/j.jfoodeng.2014.07.007

Giannakourou MC, Taoukis PS (2003b) Kinetic modelling of vitamin C loss in frozen green vegetables under variable storage conditions. Food Chem 83:33–41. https://doi.org/10.1016/S0308-8146(03)00033-5

Martins RC, Silva CLM (2004) Frozen green beans (Phaseolus vulgaris, L.) quality profile evaluation during home storage. J Food Eng 64:481–488. https://doi.org/10.1016/j.jfoodeng.2003.11.015

Gonçalves EM, Cruz RMS, Abreu M, Brandão TRS, Silva CLM (2009) Biochemical and colour changes of watercress (Nasturtium officinale R. Br.) during freezing and frozen storage. J Food Eng 93:32–39. https://doi.org/10.1016/j.jfoodeng.2008.12.027

Dermesonlouoglou EK, Giannakourou M, Taoukis PS (2016) Kinetic study of the effect of the osmotic dehydration pre-treatment with alternative osmotic solutes to the shelf life of frozen strawberry. Food Bioprod Process 99:212–221. https://doi.org/10.1016/j.fbp.2016.05.006

Dermesonlouoglou E, Zachariou I, Andreou V, Taoukis PS (2018) Quality assessment and shelf life modeling of pulsed electric field pretreated osmodehydrofrozen kiwifruit slices. Int J Food Stud 7:34–51. https://doi.org/10.7455/ijfs/7.1.2018.a4

Martins RC, Lopes IC, Silva CLM (2005) Accelerated life testing of frozen green beans (Phaseolus vulgaris, L.) quality loss kinetics: colour and starch. J Food Eng 67:339–346. https://doi.org/10.1016/j.jfoodeng.2004.04.037

Giannakourou MC, Taoukis PS (2002) Systematic application of time temperature integrators as tools for control of frozen vegetable quality. J Food Sci 67(6):2221–2228

Dermesonlouoglou E, Giannakourou M, Taoukis P (2007) Kinetic modelling of the quality degradation of frozen watermelon tissue: effect of the osmotic dehydration as a pre-treatment. Int J Food Sci Technol 42:790–798. https://doi.org/10.1111/j.1365-2621.2006.01280.x

Cruz RMS, Vieira MC, Silva CLM (2009) Effect of cold chain temperature abuses on the quality of frozen watercress (Nasturtium officinale R. Br.). J Food Eng 94:90–97. https://doi.org/10.1016/j.jfoodeng.2009.03.006

Corradini MG, Peleg M (2007) Shelf-life estimation from accelerated storage data. Trends Food Sci Technol 18:37–47

Giannakourou MC, Taoukis PS (2003a) Application of a TTI-based distribution management system for quality optimization of frozen vegetables at the consumer end. J Food Sci 68:201–209

Gogou E, Derens E, Alvarez G, Taoukis P (2014) Field test monitoring of the food cold chain in European markets. Refr Sci Technol 548–554

Gogou E, Katsaros G, Derens E, Alvarez G, Taoukis PS (2015) Cold chain database development and application as a tool for the cold chain management and food quality evaluation. Int J Refrig 52:109–121. https://doi.org/10.1016/j.ijrefrig.2015.01.019

Gwanpua SG, Verboven P, Leducq D, Brown T, Verlinden BE, Bekele E, Aregawi W, Evans J, Foster A, Duret S, Hoang HM, Van Der Sluis S, Wissink E, Hendriksen LJAM, Taoukis P, Gogou E, Stahl V, El Jabri M, Le Page JF, Claussen I, Indergård E, Nicolai BM, Alvarez G, Geeraerd AH (2015) The FRISBEE tool, a software for optimising the trade-off between food quality, energy use, and global warming impact of cold chains. J Food Eng 148:2–12. https://doi.org/10.1016/j.jfoodeng.2014.06.021

Labuza TP (1985) In: Fennema OR (ed) food chemistry, 2nd edn. Marcel Dekker, New York

Aspridou Z, Koutsoumanis KP (2015) Individual cell heterogeneity as variability source in population dynamics of microbial inactivation. Food Microbiol 45(Part B):216–221. https://doi.org/10.1016/j.fm.2014.04.008

Huang L (2015b) Dynamic determination of kinetic parameters, computer simulation, and probabilistic analysis of growth of Clostridium perfringens in cooked beef during cooling. Int J Food Microbiol 195:20–29. https://doi.org/10.1016/j.ijfoodmicro.2014.11.025

Lianou A, Koutsoumanis KP (2011) A stochastic approach for integrating strain variability in modeling Salmonella enterica growth as a function of pH and water activity. Int J Food Microbiol 149:254–261. https://doi.org/10.1016/j.ijfoodmicro.2011.07.001

Channon HA, Hamilton AJ, D'Souza DN, Dunshea FR (2016) Estimating the impact of various pathway parameters on tenderness, flavour and juiciness of pork using Monte Carlo simulation methods. Meat Sci 116:58–66. https://doi.org/10.1016/j.meatsci.2016.01.004

Evrendilek GA, Avsar YK, Evrendilek F (2016) Modelling stochastic variability and uncertainty in aroma active compounds of PEF-treated peach nectar as a function of physical and sensory properties, and treatment time. Food Chem 190:634–642. https://doi.org/10.1016/j.foodchem.2015.06.010

Giannakourou MC, Koutsoumanis K, Dermesonlouoglou E, Taoukis PS (2001) Applicability of the shelf life decision system (SLDS) for control of nutritional quality of frozen vegetables. Acta Hortic 566:275–280

Giannakourou MC, Stoforos NG (2017) A theoretical analysis for assessing the variability of secondary model thermal inactivation kinetic parameters. Foods 6:7

Wesolek N, Roudot AC (2016) Assessing aflatoxin B1 distribution and variability in pistachios: validation of a Monte Carlo modeling method and comparison to the codex method. Food Control 59:553–560. https://doi.org/10.1016/j.foodcont.2015.06.034

Efron B, Tibshirani RJ (1993) An introduction to the bootstrap, 1st edn. Chapman & Hall/CRC Monographs on Statistics & Applied Probability, Boca Raton, FL, USA

Poschet F, Bernaerts K, Geeraerd AH, Scheerlinck N, Nicolaı̈ BM, Van Impe JF (2004) Sensitivity analysis of microbial growth parameter distributions with respect to data quality and quantity by using Monte Carlo analysis. Math Comput Simul 65:231–243. https://doi.org/10.1016/j.matcom.2003.12.002

Poschet F et al (2003) Monte Carlo analysis as a tool to incorporate variation on experimental data in predictive microbiology. Food Microbiol 20:285–295. https://doi.org/10.1016/S0740-0020(02)00156-9

Poschet F, Geeraerd AH, Van Loey AM, Hendrickx ME, Van Impe JF (2005) Assessing the optimal experiment setup for first order kinetic studies by Monte Carlo analysis. Food Control 16:873–882. https://doi.org/10.1016/j.foodcont.2004.07.009

Mishra DK, Dolan KD, Yang L (2011) Bootstrap confidence intervals for the kinetic parameters of degradation of anthocyanins in grape pomace. J Food Process Eng 34:1220–1233. https://doi.org/10.1111/j.1745-4530.2009.00425.x

Dolan KD, Yang L, Trampel CP (2007) Nonlinear regression technique to estimate kinetic parameters and confidence intervals in unsteady-state conduction-heated foods. J Food Eng 80:581–593

Sui X, Zhou W (2014) Monte Carlo modelling of non-isothermal degradation of two cyanidin-based anthocyanins in aqueous system at high temperatures and its impact on antioxidant capacities. Food Chem 148:342–350. https://doi.org/10.1016/j.foodchem.2013.10.060

Rodríguez-Martínez V, Velázquez G, Welti-Chanes J, Torres, JA (2018) In: Barbosa-Cánovas GV, Fontana AJ, Schmidt SJ, Labuza TP (eds.), water activity in foods, Fundamental and applications. Wiley-Blackwell, New York

Destercke S, Chojnacki E (2009) Safety, reliability and risk analysis: theory. In: Martorell S, Soares CG, Barnett J (eds) Methods and applications. Taylor & Francis Group, London

Smid JH, Verloo D, Barker GC, Havelaar AH (2010) Strengths and weaknesses of Monte Carlo simulation models and Bayesian belief networks in microbial risk assessment. Int J Food Microbiol 139:S57–S63. https://doi.org/10.1016/j.ijfoodmicro.2009.12.015

Cassin MH, Paoli GM, Lammerding AM (1998) Simulation modeling for microbial risk assessment. J Food Prot 61(11):1560–1566

Jaykus LA (1996) The Application of Quantitative Risk Assessment to Microbial Food Safety Risks. Crit Rev Microbiol 22(4):279–293. https://doi.org/10.3109/10408419609105483

Singh M, Markeset T (2009) In: Martorell S, Soares CG, Barnett J (eds) Safety, reliability and risk analysis: theory, methods and applications, Taylor & Francis Group, London

Barreto H, Howland FM (2006) Introductory econometrics: using Monte Carlo simulation with Microsoft excel®. Cambridge University Press, New York

Lammerding AM, Fazil A (2000) Hazard identification and exposure assessment for microbial food safety risk assessment. Int J Food Microbiol 58:147–157. https://doi.org/10.1016/s0168-1605(00)00269-5

Taoukis PS (2001). In: Tijkskens LMM, Hertog MLATM, Nicolai BM (Eds) Food process modeling. New York: CRC Press