[Consumption of Smoothies Contributes Sufficient Amounts of Phytochemicals]

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Consumption of Smoothies Contributes Sufficient Amounts of Phytochemicals

Monte Carlo simulations were done with Decision Tools software (Palisade).

The conceptual scheme for using Monte Carlo simulations to predict the effects of the variability in food production chains on the outcome of epidemiological studies is shown in Figure 1. For each simulation 30,000 consumers were simulated. More details on the simulation procedure are described in previous research (Dekker and Verkerk, 2003).

For the quantitative description of the variability in phytochemicals, the data on glucosinolate levels as determined in various stages of the food production chain were used (Verkerk, 2002; Tebbenhoff, 2003).

Results and Discussion

Variability

The variation of glucosinolate levels throughout the chain has been determined in a quantitative way. Effects of cultivar, storage, industrial (thermal) processing and domestic cooking have been studied. As an example the variation in the level of two glucosinolates in 170 samples from 12 varieties of Brassica vegetables is shown in Figure 2.

As can be seen from Figure 2, the variation in the different samples from different cultivars is well over 100-fold. This variation could be described by a log-normal distribution using the "BestFit" procedure in the Decision Tools software, that evaluates the fit results for different kinds of distribution to the actual data. Even if only Broccoli samples are taken into account the variation is well over 20-fold. In addition to this variation also further processing will add to the final variability. In a previous paper (Dekker and Verkerk, 2003) this variation was also described by log-normal distributions.

For simplicity, here we will use overall distribution taken into account the cultivar variation as well as the processing/preparation variation. The estimated distribution in the level of phytochemical is a log-normal distribution, with a mean value of 10-3 AU, a standard deviation of 3·10-3, which was truncated at a maximum of 5·10-2 AU. Arbitrary units were used since although the data from glucosinolates were used, the calculations of the further consequences of variability are not limited to this particular group of compounds.

Simulation of Epidemiology

For the calculation of the actual intake of products containing the health promoting compound the calculation scheme as depicted in Figure 1 is used. For product consumtion data three intake groups were defined as depicted in Figure 3.

In the Monte Carlo simulations a sample from the product intake was multiplied with a sample from the distribution on the level of the phytochemical. ...