564 Novel food packaging techniques is known as the optimum storage temperature for the product under study. No extensive literature data is available on monitoring maP in terms of temperature, gas conditions and product quality throughout a logistic chain Without such a complete set of data it is difficult, if not impossible, to know why a certain maP design failed. This could, for instance, be due to a direct temperature effect on the products metabolism, or due to an indirect effect through a failure to establish the intended steady state gas conditions( too high or too low), or an unfortunate combination of other factors like leakage or issues related to product quality(maturity, microbial load, etc. This chapter will focus on the effects of dynamic temperature conditions on the performance of MAP. First of all it will discuss how to define MAP performance; when MAP can be regarded as being successful and how this can be measured. Subsequently it will discuss what risks are involved in MAP and now these risks are affected by a lack of integral temperature control in a logistic chain. This chapter will conclude with a discussion of several simple strategies to maximise MAP performance, making the best of maP given the limited resources available. The different aspects discussed in this chapter are illustrated using simulation results from a fully dynamic MA model using realistic settings for both film and product characteristics 27. 2 MAP performance The first question to answer when discussing MAP performance is how MAP performance should be defined. The aim of MAP is to inhibit retardation of product quality, the means employed to reach this aim is the application of certain optimal MA temperature and gas conditions. To grade the performance of MAP one can test whether the aim was reached (in terms of product quality) or whether the means were employed correctly(in terms of temperature or gas conditions). If life were simple these two measures would be interchangeable, as hey would be strongly correlated to each other From a technical point of view, tracing and tracking gas conditions and mperature in the logistic chain is much easier than tracing and tracking those product properties responsible for the overall product quality. However ssessing the benefits and losses in terms of product quality gives much more insight than just the observation of Ma conditions getting below or above their target levels. The question that should al ways be asked is how possible deviations in temperature or gas condition affect the quality and keeping quality Product quality gives static information on the status of the product at a certain moment, for instance at the point of sale. Keeping quality provides dynamic nformation on how long a product can be stored, kept for sale, transported to distant markets or remain acceptable to the consumer a wide range of equipment is available to monitor temperature throughout a logistic chain. Given that most MA packages are relatively small consumer packs and given the potentially large spatial and temporal variationis known as the optimum storage temperature for the product under study. No extensive literature data is available on monitoring MAP in terms of temperature, gas conditions and product quality throughout a logistic chain. Without such a complete set of data it is difficult, if not impossible, to know why a certain MAP design failed. This could, for instance, be due to a direct temperature effect on the product’s metabolism, or due to an indirect effect through a failure to establish the intended steady state gas conditions (too high or too low), or an unfortunate combination of other factors like leakage or issues related to product quality (maturity, microbial load, etc.). This chapter will focus on the effects of dynamic temperature conditions on the performance of MAP. First of all it will discuss how to define MAP performance; when MAP can be regarded as being successful and how this can be measured. Subsequently it will discuss what risks are involved in MAP and how these risks are affected by a lack of integral temperature control in a logistic chain. This chapter will conclude with a discussion of several simple strategies to maximise MAP performance, making the best of MAP given the limited resources available. The different aspects discussed in this chapter are illustrated using simulation results from a fully dynamic MA model12 using realistic settings for both film and product characteristics. 27.2 MAP performance The first question to answer when discussing MAP performance is how MAP performance should be defined. The aim of MAP is to inhibit retardation of product quality, the means employed to reach this aim is the application of certain optimal MA temperature and gas conditions. To grade the performance of MAP one can test whether the aim was reached (in terms of product quality) or whether the means were employed correctly (in terms of temperature or gas conditions). If life were simple these two measures would be interchangeable, as they would be strongly correlated to each other. From a technical point of view, tracing and tracking gas conditions and temperature in the logistic chain is much easier than tracing and tracking those product properties responsible for the overall product quality. However, assessing the benefits and losses in terms of product quality gives much more insight than just the observation of MA conditions getting below or above their target levels. The question that should always be asked is how possible deviations in temperature or gas condition affect the quality and keeping quality. Product quality gives static information on the status of the product at a certain moment, for instance at the point of sale. Keeping quality provides dynamic information on how long a product can be stored, kept for sale, transported to distant markets or remain acceptable to the consumer. A wide range of equipment is available to monitor temperature throughout a logistic chain. Given that most MA packages are relatively small consumer packs and given the potentially large spatial and temporal variation in 564 Novel food packaging techniques