Mycotoxins have a significant impact on food safety. Overall, foods contaminated with aflatoxins present a clear food security threat regarding their impact on human health, especially concerning the established causal association with liver cancer, synergistic effects with hepatitis B, and potential association with growth inhibition and immune system suppression. Fusarium species are the main cause of trichothecene type B contamination in cereals. In fact, F. graminearum is considered to be the predominant pathogen causing Fusarium Head Blight (FHB) in many countries. FHB can also cause indirect loss, because the fungus contaminates grain with potent mycotoxins, especially deoxynivalenol (DON).
Could the Precision Agriculture help to minimize the contamination of mycotoxins in cereals? A consortium of investigators led by Ghent University seeks to answer this question. Particularly, this group of researchers from public and private institutions will determinate whether the risk of mycotoxin contamination in barley and wheat grain can be mitigated by Fusarium Preventive Site Specific Spraying (PSSS) in combination with Selective Harvesting (SH). This is the main objective of the POSHMyCo project.
POSHMyCo (Potential of selective harvest based on mycotoxins content assessment in cereal crops) is an ambitious and innovative EU-funded ICT-AGRI-FOOD project. Aristotle University Thessaloniki (Greece), Swedish University of Agricultural Sciences (Sweden), Vytautas Magnus University (Lithuania), University of Sevilla (Spain) and the Precision Agriculture company Agrosap (Spain), coordinated by Ghent University (Belgium) will work together during the next three years to establish an integrated ICT solution of sensing, modelling and control to reduce DON and subsequently decrease the human and livestock risks to mycotoxin exposure, while increasing the farmer profitability. This will be achieved through a combined solution of PSSS and SH, based on:
- Development in on-line measurement of FHB in barley and wheat using a novel multi-sensor data fusion approach.
- New algorithms to quantify mycotoxin in barley and wheat grains based of infield measured FHB.
- Spatial information on soil and crop acquired by exploiting IoT-based sensor technologies.
- Developing advanced computational methodologies for data fusion and decision-making in order to constitute a fully decision supported loop of PSSS and SH.
- Developing a user-friendly interface platform.
- Developing a cloud-based framework for extracting hidden patterns of data.
- Data management and processing using open source software tools such as QGIS, Hadoop, or Apache Spark.
- Data visualization for faster actions and communicate findings in constructive ways.
In summary, the aim of this project is to evaluate the potential of a multi-sensor, data fusion approach for detecting and forecasting Fusarium and mycotoxin spread in the field for reducing the risk of mycotoxin contamination in wheat and barley grain by PSSS and SH. Securing clean of mycotoxin contaminated grains will reduce the risk to human health, leading to improved food safety