The resilience of the pork supply chain to a food safety outbreak: The case of dioxins.

Food supply chains are constantly challenged by food safety hazards entering the chain. The ability of the supply chain to provide safe food within a reasonable time after such a food safety threat or shock can be investigated with the concept of resilience using food safety as an indicator. Resilience is then defined as the food safety performance deviation due to the shock and takes both the severity of the shock as well as the time to fully recover or reach a new equilibrium into account. This study developed a stochastic simulation model to evaluate the resilience of the Dutch pork supply chain to dioxin contamination in the feed. The resilience of the supply chain as well as the potential costs associated with the contamination are compared between several monitoring strategies with the aim to determine the optimal control points for dioxin monitoring. Model results show that collecting and analyzing samples at more than one control point along the pork supply chain, in particular at feed mills and fat melting facilities, resulted in the highest resilience and the lowest costs after a shock. This model and these results can be used by public and private decision makers to make proactive and informed decisions on the monitoring strategies to control dioxins in the pork supply chain that result in optimal resilience to a dioxin crises.

Factors influencing the fate of chemical food safety hazards in the terrestrial circular primary food production system-A comprehensive review.

Food safety is recognized as a major hurdle in the transition toward circular food production systems due to the potential reintroduction and accumulation of chemical contaminants in these food systems. Effectively managing these hazardous contaminants in a risk-based manner requires quantitative insights into the factors influencing the presence and fate of contaminants in the entire circular food chain. A systematic literature review was performed to gain an up-to-date overview of the known factors and their influence on the transfer and accumulation of contaminants. This review focused on the terrestrial circular primary food production system, including the pathways between waste- or byproduct-based fertilizers, soil, crops, animal feed, and farmed animals. This review revealed an imbalance in research regarding the different pathways: studies on the soil-to-crop pathway were most abundant. The factors identified can be categorized as compound-related (intrinsic) factors, such as hydrophobicity, molecular weight, and chain length, and extrinsic factors, such as soil organic matter and carbon, pH, milk yield of cows, crop age, and biomass. Quantitative data on the influence of the identified factors were limited. Most studies quantified the influence of individual factors, whereas only a few studies quantified the combined effect of multiple factors. By providing a holistic insight into the influential factors and the quantification of their influence on the fate of contaminants, this review contributes to the improvement of food safety management for chemical hazards when transitioning to a circular food system.

Effects of Climate Change on Areas Suitable for Maize Cultivation and Aflatoxin Contamination in Europe.

The climate is changing in Europe: average temperatures are increasing, and so is the frequency of extreme weather events. Climate change has a severe impact on areas suitable for growing certain crops and on food safety, for example, affecting the occurrence of the aflatoxin contamination of maize. The aim of this study was to obtain insights into the impact of climate change on possible changes in land use in Europe, particularly in areas suitable for maize cultivation, and on the probability of the mycotoxin contamination of maize in order to give directions for long-term adaptation to climate change. By combining a land use model and a mycotoxin prediction model, the suitability of land for maize cultivation and the probability of aflatoxin contamination were estimated for suitable areas in Europe, comparing the current climate with the 2050 scenario. In 2050, the occurrence of aflatoxin contamination in Europe is predicted to severely increase, especially in Central and Southern Europe. More northern regions, presently unsuitable for maize cultivation, will become suitable for maize cultivation in 2050. In the baseline scenario, most regions suitable for maize cultivation have a low probability of aflatoxin contamination, whereas in 2050, about half of the regions suitable for maize cultivation have a medium to high probability of aflatoxin contamination. Regions for safely growing maize for human consumption will shift from the southern to the northern half of Europe.

Dynamic geospatial modeling of mycotoxin contamination of corn in Illinois: unveiling critical factors and predictive insights with machine learning.

Mycotoxin contamination of corn is a pervasive problem that negatively impacts human and animal health and causes economic losses to the agricultural industry worldwide. Historical aflatoxin (AFL) and fumonisin (FUM) mycotoxin contamination data of corn, daily weather data, satellite data, dynamic geospatial soil properties, and land usage parameters were modeled to identify factors significantly contributing to the outbreaks of mycotoxin contamination of corn grown in Illinois (IL), AFL >20 ppb, and FUM >5 ppm. Two methods were used: a gradient boosting machine (GBM) and a neural network (NN). Both the GBM and NN models were dynamic at a state-county geospatial level because they used GPS coordinates of the counties linked to soil properties. GBM identified temperature and precipitation prior to sowing as significant influential factors contributing to high AFL and FUM contamination. AFL-GBM showed that a higher aflatoxin risk index (ARI) in January, March, July, and November led to higher AFL contamination in the southern regions of IL. Higher values of corn-specific normalized difference vegetation index (NDVI) in July led to lower AFL contamination in Central and Southern IL, while higher wheat-specific NDVI values in February led to higher AFL. FUM-GBM showed that temperature in July and October, precipitation in February, and NDVI values in March are positively correlated with high contamination throughout IL. Furthermore, the dynamic geospatial models showed that soil characteristics were correlated with AFL and FUM contamination. Greater calcium carbonate content in soil was negatively correlated with AFL contamination, which was noticeable in Southern IL. Greater soil moisture and available water-holding capacity throughout Southern IL were positively correlated with high FUM contamination. The higher clay percentage in the northeastern areas of IL negatively correlated with FUM contamination. NN models showed high class-specific performance for 1-year predictive validation for AFL (73%) and FUM (85%), highlighting their accuracy for annual mycotoxin prediction. Our models revealed that soil, NDVI, year-specific weekly average precipitation, and temperature were the most important factors that correlated with mycotoxin contamination. These findings serve as reliable guidelines for future modeling efforts to identify novel data inputs for the prediction of AFL and FUM outbreaks and potential farm-level management practices.

Mycotoxins in wheat cultivated in the Netherlands: results from eight years of field surveys.

In the period 2009-2018, an annual field survey with commercial arable farms in the Netherlands was held, to collect data on agronomics of wheat fields as well as mycotoxin concentrations of the specific wheat field at harvest. In total, 293 full farm field records over 8 years were obtained. This study aimed to investigate (i) the occurrence of deoxynivalenol (DON) and other mycotoxins, as well as correlations between these mycotoxins, and (ii) the relationships between agronomics and the DON concentration in wheat kernels for wheat cultivated in the Netherlands. Results showed that mycotoxins most frequently observed in concentrations above the limit of quantification were DON, enniatin B and B1, HT-2 toxin, zearalenone (ZEN) and nivalenol. On average, DON was detected in 54% of the samples (> 50 µg/kg) ranging from 19 to 92% depending on the year. Positive samples (> 50 µg/kg) had DON concentrations ranging 53-15,400 µg/kg, with a median of 228 µg/kg. Co-occurrence between DON and ZEN as well as between each of DON and ZEN with their modified forms was confirmed by the data of this study. The year influenced the DON concentration in wheat the most, followed by the region. The results of this study show that DON levels in wheat can only be influenced in a limited manner by agronomic practices such as the use of fungicides against Fusarium spp. around flowering, crop rotation, or the use of resistant wheat cultivars.