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Progress on reducing acrylamide levels in potato crisps in Europe, 2002 to 2019.

Stephen J PowersDonald S MottramAndrew CurtisNigel G Halford
Published in: Food additives & contaminants. Part A, Chemistry, analysis, control, exposure & risk assessment (2021)
European Snacks Association (ESA) data on acrylamide in potato crisps from 2002 to 2019 (99704 observations) were analysed. Acrylamide levels have plateaued since 2011, although the lowest mean so far was attained in 2018 at 353 ± 2.7 ng g-1: a 54% reduction since 2002. The 85th, 90th and 95th quantiles did show evidence of continued downward progress, the 90th quantile being lower than the 750 ng g-1 European Benchmark Level from 2017 to 2019. A smaller dataset from the European Food Safety Authority (2124 observations) for 2011-2018 was also analysed. The yearly means were higher than those of the ESA data but showed a fall in average acrylamide from 715 ± 40.5 ng g-1 in 2015 to 505 ± 28.5 ng g-1 in 2018, as well as steep falls in the 85th, 90th and 95th quantiles. Nevertheless, even the 85th quantile remained above the 750 ng g-1 Benchmark Level. The ESA data showed a reduction in the proportion of samples with acrylamide exceeding 750 ng g-1, from over 40% in 2002 to 7.75% in 2019. Seasonality was evident, with highest acrylamide levels from November to May. Crisp type had little effect except that thicker types had a higher proportion of samples containing >750 ng g-1 acrylamide. Analysis of the region of origin in Europe of the final product revealed improvements in the east and north. Geographical factors combined with seasonality continued to be problematic but was also an aspect in which progress was most evident. The findings show that improvements have been made in reducing the number of samples with very high levels of acrylamide, but do not suggest that mean acrylamide levels could be reduced substantially below where they have been since 2011, or that levels could be kept consistently below the current Benchmark Level.
Keyphrases
  • big data
  • machine learning
  • single cell
  • data analysis
  • deep learning