RESUMEN
Acrylamide levels in commercially available potato chips in Japan were monitored between August 2006 and June 2010 using the xanthydrol derivative gas chromatography-mass spectrometry (GC-MS) method. Seasonal and annual changes in acrylamide concentrations were determined. Nationwide bimonthly sampling of potato chips was carried out using a four-level design, and seasonal variations were detected in which the minimum acrylamide concentration was observed in August, and the maximum between February and June. Seasonal variations became less apparent after August 2008 as a result of annual effects and/or mitigation measures taken by the potato chip producers. Sampling uncertainties were separated into time-to-time, city-to-city, and lot-to-lot variation, and the largest variation was shown to be lot-to-lot including bag-to-bag.
Asunto(s)
Acrilamida/análisis , Carcinógenos/análisis , Comida Rápida/análisis , Contaminación de Alimentos , Tubérculos de la Planta/química , Solanum tuberosum/química , Contaminación de Alimentos/prevención & control , Manipulación de Alimentos , Cromatografía de Gases y Espectrometría de Masas , Japón , Límite de Detección , Reproducibilidad de los Resultados , Estaciones del AñoRESUMEN
To give a quantitative guide to sample size allocation for developing sampling designs for a food composition survey, we discuss sampling strategies that consider the importance of each food; namely, consumption or production, variability of composition, and the restrictions within the available resources for sample collection and analysis are considered., Here we consider two strategies: 'proportional' and 'Neyman' are discussed. Both of these incorporate consumed quantity of foods, and we review some available statistics for allocation issues. The Neyman optimal strategy allocates less sample size for starch than proportional, because the former incorporates variability in the composition. Those strategies improved accuracy in dietary nutrient intake more than equal sample size allocation. Those strategies will be useful as we often face sample size allocation problems, wherein we decide whether to sample 'five white potatoes and five taros or nine white and one taros'. Allocating sufficient sample size for important foodstuffs is essential in assuring data quality. Nevertheless, the food composition table should be as comprehensive as possible.