Micelle separation conditions based on particle size strongly affect carotenoid bioaccessibility assessment from juices after in vitro digestion.

For assessing the carotenoid bioaccessibility during in vitro digestion, obtaining the micelle fraction that can diffuse through the mucin layer according to the particle size is an important step. However, the accuracy of the various approaches to obtaining the right fraction of micelles described in literature has not been investigated. In many studies the reported bioaccessible fraction might therefore be over- or underestimating the real bioaccessibility. The present study aimed to fill this gap and give approaches to get accurate data on the bioaccessible fraction from samples with different properties. Results illustrated that optimizing the centrifugal speed and duration of the digesta are essential in obtaining the micelle fraction. Different digesta have different optimum centrifugal parameters to obtain the bioaccessible fraction. 6,000 rpm and 40 min was selected as the optimum centrifugal parameter for combined juice (CJ). 6,000 rpm and 60 min was the optimum centrifugal parameter for CJ with oil, and CJ with emulsion using non-ionic emulsifier. 8,000 rpm and 20 min was the optimum centrifugal parameter for CJ with emulsion using ionic emulsifier. Polygalacturonanase (PG)-digested systems required higher centrifugal speed (10,000 rpm) compared with CJ-based systems (6,000 rpm or 8,000 rpm). A prediction model to determine the optimal centrifugation speed/time from the properties of the intestinal digesta was developed. Sample preparation conditions strongly affect carotenoid bioaccessibility assessment from juices during in vitro digestion. Based on these results, it is highly recommended to perform an optimized preparation procedure for bioaccessible fraction prior to carotenoid bioaccessibility analysis.

Dealing with variability in food production chains: a tool to enhance the sensitivity of epidemiological studies on phytochemicals.

BACKGROUND: Many epidemiological studies have tried to associate the intake of certain food products with a reduced risk for certain diseases. Results of these studies are often ambiguous, conflicting, or show very large deviations of trends. Nevertheless, a clear and often reproduced inverse association is observed between total vegetable and fruit consumption and cancer risk. Examples of components that have been indicated to have a potential protective effect in food and vegetables include antioxidants, allium compounds and glucosinolates. AIM: The food production chain can give a considerable variation in the level of bioactive components in the products that are consumed. In this paper the effects of this variability in levels of phytochemicals in food products on the sensitivity of epidemiological studies are assessed. METHODS: Information on the effect of variation in different steps of the food production chain of Brassica vegetables on their glucosinolate content is used to estimate the distributions in the levels in the final product that is consumed. Monte Carlo simulations of an epidemiological cohort study with 30,000 people have been used to assess the likelihood of finding significant associations between food product intake and reduced cancer risk. RESULTS: By using the Monte Carlo simulation approach, it was shown that if information on the way of preparation of the products by the consumer was quantified, the statistical power of the study could at least be doubled. The statistical power could be increased by at least a factor of five if all variation of the food production chain could be accounted for. CONCLUSIONS: Variability in the level of protective components arising from the complete food production chain can be a major disturbing factor in the identification of associations between food intake and reduced risk for cancer. Monte Carlo simulation of the effect of the food production chain on epidemiological cohort studies has identified possible improvements in the set up of such studies. The actual effectiveness of food compounds already identified as cancer-protective by current imprecise methods is likely to be much greater than estimated at present.