19 Active packaging and colour control: the case of meat M. Jakobsen and G. bertelsen, The Royal Veterinary and Agricultural University, Denmark 1.1 Introduction The colour stability of meat products is influenced by a large number of factors some of biochemical nature, some due to handling during slaughter and processing, and others due to packaging and storage conditions. This chapter focuses on modelling how colour shelf-life is affected by the external factors applied during packaging and storage. However, meat from different sources shows different tendencies to undergo colour deterioration and this variation in internal factors influences the developed models. Therefore some consideration will also be given to discussing how internal factors like, e.g., muscle type and addition of nitrite in cured meat affect the models. modelling can be used to identify the most important factors/interaction of factors affecting quality loss during storage and to define critical levels of these factors, thereby forming the basis for proposing the optimal packaging and storage conditions or the best compromise if several deteriorative reactions need to be considered. Caution in choosing the optimal packaging and storage conditions can largely improve the colour shelf-life of meat products. Modelling of MAP systems shows great potential for optimising/tailoring storage and packaging parameters to maintain product quality, in this case a ood meat colour stability (Jakobsen and Bertelsen, 2000; Lyijynen et al 1998; Pfeiffer et al., 1999). It will be demonstrated how modelling can be sed to identify the most important factors affecting colour shelf-life. Multivariable experimental design is necessary to be able to investigate the large number of influencing factors on several levels as well as the interactions between factors
19.1 Introduction The colour stability of meat products is influenced by a large number of factors: some of biochemical nature, some due to handling during slaughter and processing, and others due to packaging and storage conditions. This chapter focuses on modelling how colour shelf-life is affected by the external factors applied during packaging and storage. However, meat from different sources shows different tendencies to undergo colour deterioration and this variation in internal factors influences the developed models. Therefore some consideration will also be given to discussing how internal factors like, e.g., muscle type and addition of nitrite in cured meat affect the models. Modelling can be used to identify the most important factors/interaction of factors affecting quality loss during storage and to define critical levels of these factors, thereby forming the basis for proposing the optimal packaging and storage conditions or the best compromise if several deteriorative reactions need to be considered. Caution in choosing the optimal packaging and storage conditions can largely improve the colour shelf-life of meat products. Modelling of MAP systems shows great potential for optimising/tailoring storage and packaging parameters to maintain product quality, in this case a good meat colour stability (Jakobsen and Bertelsen, 2000; Lyijynen et al., 1998; Pfeiffer et al., 1999). It will be demonstrated how modelling can be used to identify the most important factors affecting colour shelf-life. Multivariable experimental design is necessary to be able to investigate the large number of influencing factors on several levels as well as the interactions between factors. 19 Active packaging and colour control: the case of meat M. Jakobsen and G. Bertelsen, The Royal Veterinary and Agricultural University, Denmark
402 Novel food packaging techniques 19.2 Packaging and storage factors affecting colour stability Modified atmosphere packed meat is a complex and dyna several factors interact(Zhao et al., 1994). Models can be used to describe how the initial package atmosphere changes over time and how these changes affect product quality and shelf-life. The dynamic changes in headspace gas composition during storage can be modelled as a function of initial gas composition product and package geometry gas absorption in the meat. The knowledge of changes in gas composition can be combined with models on quality changes in the meat as a function of packaging and storage conditions · storage temperature · light exposure and predictions of product shelf-life can be made. Pfeiffer et al.(1999)developed simulations of how product shelf-life changes with different packaging and storage conditions for a wide range of food products(primarily dry products ). However, at present sufficient models for many quality deteriorative reactions are lacking and only few attempts have been made to model chemical quality changes in meat products, in contrast to modelling of microbial shelf-life, where extensive work has been performed(Mc Donald and Sun, 1999) 19.2.1 Modelling dynamic changes in headspace gas composition Permeability of the packaging film Headspace gas composition changes dynamically due to several factors. Gas exchange with the environment occurs over the packaging film if the partial pressure of a gas differs on the two sides of the film. The amount of gas that permeates over the film can be calculated from equation 19.1(Robertson, 1993) Q=P.△p·t·A 19.1 @= the amount of gas that permeates over the film(cm) P= the permeability of the packaging film(cm/m/24h/atm) the difference in gas partial pressure on the two sides of the film(atm) A=the area of the package(m2) Different gases have different permeability through the same film. For conventional films, the permeability of CO2 is generally 4-6 times larger than
19.2 Packaging and storage factors affecting colour stability Modified atmosphere packed meat is a complex and dynamic system where several factors interact (Zhao et al., 1994). Models can be used to describe how the initial package atmosphere changes over time and how these changes affect product quality and shelf-life. The dynamic changes in headspace gas composition during storage can be modelled as a function of: • gas transmission rates of the packaging material • initial gas composition • product and package geometry • gas absorption in the meat. The knowledge of changes in gas composition can be combined with models on quality changes in the meat as a function of packaging and storage conditions such as: • storage time • storage temperature • gas composition • light exposure and predictions of product shelf-life can be made. Pfeiffer et al. (1999) developed simulations of how product shelf-life changes with different packaging and storage conditions for a wide range of food products (primarily dry products). However, at present sufficient models for many quality deteriorative reactions are lacking and only few attempts have been made to model chemical quality changes in meat products, in contrast to modelling of microbial shelf-life, where extensive work has been performed (McDonald and Sun, 1999). 19.2.1 Modelling dynamic changes in headspace gas composition Permeability of the packaging film Headspace gas composition changes dynamically due to several factors. Gas exchange with the environment occurs over the packaging film if the partial pressure of a gas differs on the two sides of the film. The amount of gas that permeates over the film can be calculated from equation 19.1 (Robertson, 1993): Q P p t A 19:1 Q the amount of gas that permeates over the film (cm3 ) P the permeability of the packaging film (cm3 /m2 /24h/atm) p the difference in gas partial pressure on the two sides of the film (atm) t the storage time (24h) A the area of the package (m2 ) Different gases have different permeability through the same film. For conventional films, the permeability of CO2 is generally 4–6 times larger than 402 Novel food packaging techniques
Active packaging and colour control: the case of meat 403 that of O2 and 12-18 times larger than that of N2. The permeability of a plastic film is roughly proportional to the thickness of the film. Doubling film thickness approximately halves film permeability Permeability is also influenced by storage temperature and relative humidity Pfeiffer et al.(1999) found that the empirical equation 19.2 fitted well with literature data for oxygen permeability P(T, RH)=exp(co+c1/T+C2 RH +C3 RH) 19.2 P= the permeability of the packaging film storage temperature RH storage relative humidity 3 are experimental derived coefficients Gas exchange over the packaging film is of particular importance when the film needs to maintain a narrowly defined gas concentration as shown in the example in section 19.3.2, where the permeability of even small amounts of O2 into a package containing a cured meat product is considered a critical packaging arameter Gas absorption in the meat Headspace gas composition can also change due to gas absorption in the meat Packaging in elevated levels of CO2 can result in large amounts of CO2 absorbed in the meat(Jakobsen and Bertelsen, 2002; Zhao et al., 1994) and thereby large changes compared to the initially applied gas composition. Absorption of O2 and N2 is negligible compared to the absorption of CO2 (Jakobsen and Bertelsen 2002). Models for CO solubility as a function of packaging and storage parameters such as product to headspace volume ratio, temperature and initial CO2 level were developed by Zhao et al. (1995)and Devlieghere et al. (1998) Fava and Piergiovanni(1992)developed models of CO2 solubility as a function of different compositional parameters, aw, pH, protein, fat and moisture content The amount of absorbed CO2 ranges from 0-1. 8 L CO2/Kg meat, depending on the applied CO2 partial pressure, temperature, pH of the meat, etc (Jakobsen and Bertelsen 2002). As regards gas absorption, equilibrium is obtained during the first one or two days. Microbial or meat metabolism can also cause slight changes in gas composition by using O2 and producing CO 19.3 Modelling the impact of MAP When it is understood how the gas atmosphere can change from the initially applied atmosphere under different packaging and storage conditions, this knowledge can be used to evaluate the effect on quality deteriorating reactions Besides microbial growth, the primary concern when packaging both fresh meat and cured meat products is colour stability. The mechanisms of colour changes
that of O2 and 12–18 times larger than that of N2. The permeability of a plastic film is roughly proportional to the thickness of the film. Doubling film thickness approximately halves film permeability. Permeability is also influenced by storage temperature and relative humidity. Pfeiffer et al. (1999) found that the empirical equation 19.2 fitted well with literature data for oxygen permeability. P T; RH exp c0 c1=T c2 RH c3 RH2 19:2 P the permeability of the packaging film T storage temperature RH storage relative humidity C0ÿ3 are experimental derived coefficients. Gas exchange over the packaging film is of particular importance when the film needs to maintain a narrowly defined gas concentration as shown in the example in section 19.3.2, where the permeability of even small amounts of O2 into a package containing a cured meat product is considered a critical packaging parameter. Gas absorption in the meat Headspace gas composition can also change due to gas absorption in the meat. Packaging in elevated levels of CO2 can result in large amounts of CO2 absorbed in the meat (Jakobsen and Bertelsen, 2002; Zhao et al., 1994) and thereby large changes compared to the initially applied gas composition. Absorption of O2 and N2 is negligible compared to the absorption of CO2 (Jakobsen and Bertelsen, 2002). Models for CO2 solubility as a function of packaging and storage parameters such as product to headspace volume ratio, temperature and initial CO2 level were developed by Zhao et al. (1995) and Devlieghere et al. (1998). Fava and Piergiovanni (1992) developed models of CO2 solubility as a function of different compositional parameters, aw, pH, protein, fat and moisture content. The amount of absorbed CO2 ranges from 0–1.8 L CO2/Kg meat, depending on the applied CO2 partial pressure, temperature, pH of the meat, etc. (Jakobsen and Bertelsen 2002). As regards gas absorption, equilibrium is obtained during the first one or two days. Microbial or meat metabolism can also cause slight changes in gas composition by using O2 and producing CO2. 19.3 Modelling the impact of MAP When it is understood how the gas atmosphere can change from the initially applied atmosphere under different packaging and storage conditions, this knowledge can be used to evaluate the effect on quality deteriorating reactions. Besides microbial growth, the primary concern when packaging both fresh meat and cured meat products is colour stability. The mechanisms of colour changes Active packaging and colour control: the case of meat 403
404 Novel food packaging techniques in fresh meat and cured meat products are completely different as can be seen from the examples on modelling given in the following two sections When packaging fresh meat products an elevated oxygen partial pressure needs to be maintained to keep the meat pigment myoglobin in its oxygenated bright red state. By modelling a MAP system for fresh beef, the most critical external factors are identified to be storage temperature and gas composition Jakobsen and Bertelsen, 2000). By modelling a MAP system for cured meat products the most critical external factors are identified to be low availability of oxygen combined with exclusion of light to prevent degradation of nitrosylmyoglobin by photo oxidation( storage temperature was kept constant at 5.C)(Moller et al, 2003 ). However, low availability of oxygen is not ensured olely by reducing the residual oxygen level in the headspace during the packaging process. Other equally critical factors are a high product to headspace ratio and a packaging film of low oxygen transmission rate (OtR) of the packaging film(Moller et al., 2003) 19.3.1 Optimising colour stability of fresh beef Jakobsen and bertelsen(2000) and Bro and Jakobsen(2002)modelled colour ability of fresh beef under different packaging and storage conditions. In all cases colour measurements were performed with a Minolta Colorimeter using the L, a, b coordinates. Red colour was expressed as the a-value, the higher the a-value the redder the sample. When packaging fresh red meats elevated O partial pressures are used to stabilise myoglobin in its bright red oxygenated form (oxymyoglobin). However, elevated O2 levels may increase some deteriorative reactions e.g. lipid oxidation. Consequently it is interesting to investigate if a level of O2 exists that is acceptable when considering both colour stability and lipid oxidation. Jakobsen and Bertelsen (2000) investigated different packaging and storage conditions (Table 19. 1)and developed a egression model/response surface model predicting the colour a-value as a iunction of storage time, storage temperature and O2 level based on steaks of ongissimus dorsi muscles from four different animals The resulting model(equation 19.3)contains the main effects of the three actors plus two-way interactions and two squared effects. Interpretation of the model is best done by exploring the response surface plot(Fig. 19.1) a-value=o+ Bi Day + B2 Temp+B3. 02 64- Day.Temp+ B5 Day.O2+6·Temp·O2+ Day. Day+Bg·Temp.Temp 19.3 where the betas are regression coefficients temperature and O2 level, while keeping the third factor, storage time, constant at day no. 6. Figure 19. 1 also reveals an interval of approximately 50-80%O2 where the O2 level does not affect the colour a-value significantly(the nearly
in fresh meat and cured meat products are completely different as can be seen from the examples on modelling given in the following two sections. When packaging fresh meat products an elevated oxygen partial pressure needs to be maintained to keep the meat pigment myoglobin in its oxygenated bright red state. By modelling a MAP system for fresh beef, the most critical external factors are identified to be storage temperature and gas composition (Jakobsen and Bertelsen, 2000). By modelling a MAP system for cured meat products the most critical external factors are identified to be low availability of oxygen combined with exclusion of light to prevent degradation of nitrosylmyoglobin by photo oxidation (storage temperature was kept constant at 5ºC) (Møller et al., 2003). However, low availability of oxygen is not ensured solely by reducing the residual oxygen level in the headspace during the packaging process. Other equally critical factors are a high product to headspace ratio and a packaging film of low oxygen transmission rate (OTR) of the packaging film (Møller et al., 2003). 19.3.1 Optimising colour stability of fresh beef Jakobsen and Bertelsen (2000) and Bro and Jakobsen (2002) modelled colour stability of fresh beef under different packaging and storage conditions. In all cases colour measurements were performed with a Minolta Colorimeter using the L, a, b coordinates. Red colour was expressed as the a-value, the higher the a-value the redder the sample. When packaging fresh red meats elevated O2 partial pressures are used to stabilise myoglobin in its bright red oxygenated form (oxymyoglobin). However, elevated O2 levels may increase some deteriorative reactions e.g. lipid oxidation. Consequently it is interesting to investigate if a level of O2 exists that is acceptable when considering both colour stability and lipid oxidation. Jakobsen and Bertelsen (2000) investigated different packaging and storage conditions (Table 19.1) and developed a regression model/response surface model predicting the colour a-value as a function of storage time, storage temperature and O2 level based on steaks of Longissimus dorsi muscles from four different animals. The resulting model (equation 19.3) contains the main effects of the three factors plus two-way interactions and two squared effects. Interpretation of the model is best done by exploring the response surface plot (Fig. 19.1). a-value 0 1 Day 2 Temp 3 O2 + 4 Day Temp + 5 Day O2 6 Temp O2 7Day Day 8 Temp Temp 19:3 where the betas are regression coefficients. Figure 19.1 shows a response surface plot varying the two factors, temperature and O2 level, while keeping the third factor, storage time, constant at day no. 6. Figure 19.1 also reveals an interval of approximately 50–80% O2, where the O2 level does not affect the colour a-value significantly (the nearly 404 Novel food packaging techniques
Active packaging and colour control: the case of meat 405 Table 19.1 Packaging and storage conditions used in the models developed in Jakobsen and Bertelsen(2000) Modelling factor Abbreviat No of levels etting of levels Storage time(days) 2,4,6,8,10 O2 level (% 20,35,50,65,80 horizontal lines in this interval means that the a-value is depends only on the temperature). The borders of this interval change a little depending on the setting of the day. But it is evident that the O2 level can be reduced from the normal used 70-80% without adverse effect on the colour shelf-life The complexity of the interactions/squared terms in equation 19.3 called for further search for adequate models. A novel approach called GEMANOVA Generalized Multiplicative ANOVA)was therefore used in Bro and Jakobsen (2002). In this study the effect of different packaging and storage conditions (Table 19.2)on the colour stability of steaks of Longissimus dorsi muscles from three different animals was investigated The effect of light was evaluated as the time of exposure to a fluorescent tube commonly used for retail display (1000 ux at the package surface for 0, 50 or 100% of the storage time Even when considering only two factor interactions a traditional ANOVA 30) 623.9-255 8 O-level Fig. 19.1 Response surface plot of predicted a-values(average of four animals)after six days storage at different temperatures and different oxygen levels. ( Adapted from Jakobsen and bertelsen, 2000)
horizontal lines in this interval means that the a-value is depends only on the temperature). The borders of this interval change a little depending on the setting of the day. But it is evident that the O2 level can be reduced from the normally used 70–80% without adverse effect on the colour shelf-life. The complexity of the interactions/squared terms in equation 19.3 called for further search for adequate models. A novel approach called GEMANOVA (Generalized Multiplicative ANOVA) was therefore used in Bro and Jakobsen (2002). In this study the effect of different packaging and storage conditions (Table 19.2) on the colour stability of steaks of Longissimus dorsi muscles from three different animals was investigated. The effect of light was evaluated as the time of exposure to a fluorescent tube commonly used for retail display (1000 lux at the package surface for 0, 50 or 100% of the storage time). Even when considering only two factor interactions a traditional ANOVA Table 19.1 Packaging and storage conditions used in the models developed in Jakobsen and Bertelsen (2000) Modelling factor Abbreviation No. of levels Setting of levels Storage time (days) Day 5 2, 4, 6, 8, 10 Temperature (ºC) Temp 3 2, 5, 8 O2 level (%) O2 5 20, 35, 50, 65, 80 Fig. 19.1 Response surface plot of predicted a-values (average of four animals) after six days storage at different temperatures and different oxygen levels. (Adapted from Jakobsen and Bertelsen, 2000). Active packaging and colour control: the case of meat 405