the handbook of food engineering practice crc press chapter 10 ...
the handbook of food engineering practice crc press chapter 10 ... the handbook of food engineering practice crc press chapter 10 ...
In practice, since there is experimental error involved in the determination of the values of k, calculations of E A from only two points will give a substantial error. The precision of activation energy calculated from equation (21) is examined by Hills and Grieger-Block (1980). Usually, the reaction rate is determined at three or more temperatures and k is plotted vs. 1/T in a semilog graph or a linear regression fit to equation (20) is employed. It should be pointed out that there is no explicit reference temperature for the Arrhenius function as expressed in Eq. (19), 0 K, the temperature at which k would be equal to k A , being implied as such. Alternatively to Eq. (19) it is often recommended that a reference temperature is chosen corresponding to an average of the temperature range characteristic of the described process. For most storage applications 300 K is such a typical temperature, whereas for thermal processes 373.15 K (100.0 ° C) is usually the choice. The modified Arrhenius equation would then be written as: k = k ref exp (- E A R [ 1 T - 1 T ref ] ) (23) where k ref the rate constant at the reference temperature Tref. Respectively Eq. (20) is modified to: ln k = ln k ref - E A R [ 1 T - 1 T ref ] (24) The above transformation is critical for enhanced stability during numerical integration and parameter estimation. Aditionally, by using a reference reaction rate constant, besides giving the constant a relevant physical meaning, one signals the applicability of the equation within a finite range of temperatures enclosing the reference temperature and corresponding to the range of interest. Indeed, as it will be discussed further in this section the Arrhenius equation may not be uniformly applicable below or above certain temperatures, usually connected with transition phenomena. When applying regression techniques statistical analysis is again used to determine the 95% confidence limits of the Arrhenius parameters. If only three k values 20
are available, the confidence range is usually wide. To obtain meaningfully narrow confidence limits in E A and k A estimation, rates at more temperatures are required. An optimization scheme to estimate the number of experiments to get the most accuracy for the least possible amount of work was proposed by Lenz and Lund (1980). They concluded that 5 or 6 experimental temperatures is the practical optimum. If one is limited to 3 experimental temperatures a point by point method or a linear regression with the 95% confidence limit values of the reaction rates included will give narrower confidence limits for the Arrhenius parameters (Kamman and Labuza, 1985) Alternatively, a multiple linear regression fit to all concentration vs. time data for all tested temperatures, by eliminating the need to estimate a separate A o for each experiment and thus increasing the degrees of freedom, results in a more accurate estimation of k at each temperature (Haralampu et al., 1985). Since it is also followed by a linear regression of ln k vs. 1/T, it is a two step method as the previous ones. One step methods require nonlinear regression of the equation that results by substitution of equations (19) or (23) in the equations of Table 1. For example, for the first order model the following equations are derived: or ⎛-E A⎞ A = A o exp[ -k A t exp ⎝ RT ⎠ ] (25) A =A o exp {- k ref t exp (- E A R [ 1 T - 1 T ref ] )} (26) These equations have as variables both time and temperature and the nonlinear regression gives simultanously estimates of A o , k A (or k ref ) and E A /R (Haralampu et al, 1985; Arabshahi and Lund, 1985). Experimental data of concentration vs. time for all tested temperatures are used, substantially increasing the degrees of freedom and hence giving much narrower confidence intervals for the estimated parameters. The use and the 21
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- Page 3 and 4: It is a working definition for the
- Page 5 and 6: 10.2 KINETICS OF FOOD DETERIORATION
- Page 7 and 8: very small, allowing us to treat it
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- Page 23 and 24: kinetic data is compared. Its main
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- Page 27 and 28: temperatures (Fennema et al., 1973)
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- Page 45 and 46: Figure 8. Characteristic fluctuatin
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- Page 49 and 50: time at each selected temperature.
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- Page 55 and 56: Figure 10. Thiamin retention of a m
- Page 57 and 58: S = SS {1+ N p n-Np F[N p, n-N p ,
- Page 59 and 60: 10.4.2. Examples of shelf life mode
- Page 61 and 62: In Fig. 12a aspartame concentration
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- Page 65 and 66: REFERENCES Arabshashi, A. (1982). E
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- Page 69 and 70: Labuza, T. P. (1975) Oxidative chan
In <strong>practice</strong>, since <strong>the</strong>re is experimental error involved in <strong>the</strong> determination <strong>of</strong> <strong>the</strong> values <strong>of</strong> k,<br />
calculations <strong>of</strong> E A from only two points will give a substantial error. The precision <strong>of</strong><br />
activation energy calculated from equation (21) is examined by Hills and Grieger-Block<br />
(1980). Usually, <strong>the</strong> reaction rate is determined at three or more temperatures and k is<br />
plotted vs. 1/T in a semilog graph or a linear regression fit to equation (20) is employed.<br />
It should be pointed out that <strong>the</strong>re is no explicit reference temperature for <strong>the</strong><br />
Arrhenius function as ex<strong>press</strong>ed in Eq. (19), 0 K, <strong>the</strong> temperature at which k would be<br />
equal to k A , being implied as such. Alternatively to Eq. (19) it is <strong>of</strong>ten recommended that a<br />
reference temperature is chosen corresponding to an average <strong>of</strong> <strong>the</strong> temperature range<br />
characteristic <strong>of</strong> <strong>the</strong> described process. For most storage applications 300 K is such a<br />
typical temperature, whereas for <strong>the</strong>rmal processes 373.15 K (<strong>10</strong>0.0 ° C) is usually <strong>the</strong><br />
choice. The modified Arrhenius equation would <strong>the</strong>n be written as:<br />
k = k ref exp (- E A<br />
R [ 1 T - 1<br />
T ref<br />
] ) (23)<br />
where k ref <strong>the</strong> rate constant at <strong>the</strong> reference temperature Tref. Respectively Eq. (20) is<br />
modified to:<br />
ln k = ln k ref - E A<br />
R [ 1 T - 1<br />
T ref<br />
] (24)<br />
The above transformation is critical for enhanced stability during numerical<br />
integration and parameter estimation. Aditionally, by using a reference reaction rate<br />
constant, besides giving <strong>the</strong> constant a relevant physical meaning, one signals <strong>the</strong><br />
applicability <strong>of</strong> <strong>the</strong> equation within a finite range <strong>of</strong> temperatures enclosing <strong>the</strong> reference<br />
temperature and corresponding to <strong>the</strong> range <strong>of</strong> interest. Indeed, as it will be discussed<br />
fur<strong>the</strong>r in this section <strong>the</strong> Arrhenius equation may not be uniformly applicable below or<br />
above certain temperatures, usually connected with transition phenomena.<br />
When applying regression techniques statistical analysis is again used to<br />
determine <strong>the</strong> 95% confidence limits <strong>of</strong> <strong>the</strong> Arrhenius parameters. If only three k values<br />
20