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. 2019 Jun 27;14(6):e0218956.
doi: 10.1371/journal.pone.0218956. eCollection 2019.

Climate change impacts on aflatoxin B1 in maize and aflatoxin M1 in milk: A case study of maize grown in Eastern Europe and imported to the Netherlands

Affiliations

Climate change impacts on aflatoxin B1 in maize and aflatoxin M1 in milk: A case study of maize grown in Eastern Europe and imported to the Netherlands

H J Van der Fels-Klerx et al. PLoS One. .

Abstract

Various models and datasets related to aflatoxins in the maize and dairy production chain have been developed and used but they have not yet been linked with each other. This study aimed to investigate the impacts of climate change on aflatoxin B1 production in maize and its consequences on aflatoxin M1 contamination in dairy cow's milk, using a full chain modelling approach. To this end, available models and input data were chained together in a modelling framework. As a case study, we focused on maize grown in Eastern Europe and imported to the Netherlands to be fed-as part of dairy cows' compound feed-to dairy cows in the Netherlands. Three different climate models, one aflatoxin B1 prediction model and five different carryover models were used. For this particular case study of East European maize, most of the calculations suggest an increase (up to 50%) of maximum mean aflatoxin M1 in milk by 2030, except for one climate (DMI) model suggesting a decrease. Results from all combinations of carryover and climate models suggest a similar or slight increase (up to 0.6%) of the chance of finding aflatoxin M1 in milk above the EC limit of 0.05 μg/kg by 2030. Results varied mainly with the climate model data and carryover model considered. The model framework infrastructure is flexible so that forecasting models for other mycotoxins or other food safety hazards as well as other production chains, together with necessary input databases, can easily be included as well. This modelling framework for the first time links datasets and models related to aflatoxin B1 in maize and related aflatoxin M1 the dairy production chain to obtain a unique predictive methodology based on Monte Carlo simulation. Such an integrated approach with scenario analysis provides possibilities for policy makers and risk managers to study the effects of changes in the beginning of the chain on the end product.

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Conflict of interest statement

The authors have declared that no competing interests exist.

Figures

Fig 1
Fig 1. Set-up of the model chain.
Box 1–2 show the two models that are linked. Box A-D provide the input for the forecasting model, and box E-H are the input for the Carryover model. Box F and I are predicted model outcomes.
Fig 2
Fig 2. Maps of predicted mean aflatoxin (AfB1) concentration (μg/kg) in maize grown in Ukraine, for baseline conditions and for 2030 using three different climate models (DMI, ETHZ, and METO).

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