Almeida, M.G.

Martins, R.C.

Silva, C. L. M.

English

Repositório Institucional da Universidade Católica Portuguesa

SIMULATION OF GREEN BEANS (Phaseolus vulgaris, L.) QUALITY LOSSTHROUGHTOUT THE FROZEN FOODS DISTRIBUTION CHAINMartins, R.C. , Almeida M.G. , Silva C.L.M.(I)Rui C. Martins: Escola Superior de BiotecnologiaUniversidade CatOlica PortuguesaR. Dr. Ant6nio Bernardino de Almeida4200-072 PortoPortugalTlf. +351 22 558 00 43Fax: +351 22 509 03 51e-mail: rmcm@morango.esb.ucp.ptKey Words: frozen foods, green beans, distribution chain, simulationINTRODUCTIONFrozen vegetables are exposed to a wide variety of different environmentaltemperature conditions along the distribution chain. These are responsible for bothnutritional and sensory quality losses of frozen products Quality losses are difficult toquantify, due to the chaotic temperature spectrum to which frozen foods are exposeduntil consumption. This explains why shelf life dating of frozen foods is a difficult task.For example, experimental studies to characterise quality losses throughout thedistribution chain require an enormous amount of resources, and therefore are rarelyperformed.A cost-effective solution to the problem may be by computer simulation. Withthe use of object-oriented computer models, the prediction of quality losses throughoutthe frozen chain is feasible. By building models it is possible to understand why, whereand how quality losses occur. Thereafter, the model can be used as a tool to study thefrozen chain, optimise quality retention, and shelf life dating.Although the simulation of such complex systems is a vast subject, the presentwork presents an overview of the main computational resources, model components,how they work and interact, in order to achieve computer simulations more and morenear the reality.FINITE ELEMENTS METHODWith this method, the physical domain is approached by a mesh [1], where heattransfer and quality changes differential equations are solved. Using this numericalmethod, it is possible to simulate both temperature and quality loss of frozen greenbeans.THERMAL PROPERTIESThermal condutivity (k) and thermal capacity (Cp) change significantly during phasetransition.The FEM needs mathematical relationships with respect to temperature, inorder to simulate phase change. Therefore, thermal capacity was determined, bydifferential scanning calorimetry, and thermal conductivity by reverting the FEMproblem.MODELLING TIME-TEMPERATURE SPECTRUMThe modelling the time-temperature spectrum is necessary to characterise thetemperature oscillations to which frozen foods are subjected. With this technique it ispossible to define the probabilities of occurring temperature abuses and simulate them,as well.TIME-TEMPERATURE DISTRIBUTIONSTime-temperature distributions are necessary to characterise statistically theresidence time and temperature at each step of the distribution chain. With thesestatistical distributions it is possible to simulate stochastically the residence time andtemperature by the Monte Carlo method.QUALITY LOSSFrozen vegetables are well known for their nutritional and sensory quality. However,when they are exposed to temperature abuses, quality loss is accelerated. For example, amajor colour and vitamin c degradation occurs during the transportation from the shopto the consumer's home. The quality degradation kinetics can be implemented in theFEM triangular element. This allows simulating quality loss across the entire physicaldomain.The following quality degradation kinetics are currently integrated: (i) colour,(ii) chlorophyll's, (iii) vitamin C, (iv) starch degradation, (v) reduced sugars increase,(vi) texture and, (vii) ice recrystallisation [2].INTEGRATED MODELEach described component (object) can be integrated into a computationalmodel. The different model objects interact with each other in order to generate ascenario, where the simulation occurs. For example, with the time temperature spectrummodels, it is Possible to create the different scenarios of the frozen distribution chain,such as, refrigerated lorys, freezers and human interaction. Then another object, such asa green beans package, can pass throughout the different scenarios and quality loss canbe estimated [3].With this abstration level, it is possible to define at the most elementary modellevel (the triangular element), all the physical laws and stochastic processes. Ascalculations are made, there is the propagation of uncertainty to the higher level objectmodels, and such an extreme chaotic fenomena emerges, giving to the observer anapparent complex solution. However, these types of simulations require highcomputational power. Therefore, the simulation programs were written in C++, andimplemented in a LINUX cluster, with a BEOWULF architecture, using the softwareParallel Virtual Machine [4].CONCLUSIONSComputational models can simulate quality loss along the frozen food distributionchain. This engineering tool will allow in the future to characterise the differentconfigurations of the distribution chain, to optimise quality retention, reduce operationalcosts, and increase the level of accuracy of shelf-life dating of frozen foods.ACKNOWLEDGEMENTSThe author Martins RC acknoledges the Fundacho para a Ciancia e Tecnologia (FCT)for his PhD grant (PRAXIS XXI BD/18541/98).REFERENCESHenwood D. and Bonet J. 1996. Finite Elements: A Gentle Introduction.Mackmillan Press, London-England.Martins R.C. and Silva C.L.M. 1999. Kinetics of Frozen Stored Green Beans(Phaseolus vulgaris, L.) Quality Changes: Texture, Vitamin C, Reduced Sugarsand Starch. Submitted to the Journal of Food Science.Martins R.C. and Silva C.L.M. 1999. Modelling Quality Changes During FrozenStorage: An Integrated Perspective. Submitted for CRC press.Geist A. et al 1994. PVM: Parallel Virtual Machine - User's guide and tutorialfor networked parallel computing. The MIT Press, Cambrige,Massachusetts.http://www.netlib.org/pvm3/book/pvm-book.html 1/12/2000

Simulation of green beans (Phaseolus vulgaris, L.) quality loss throught the frozen foods distribution chain

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Simulation of green beans (Phaseolus vulgaris, L.) quality loss throught the frozen foods distribution chain

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