CTA R&D&I Incentives Program
Agrosap and US develop technology to reduce mycotoxin contamination of food from barley and wheat
The POSHMyCo R&D&I project, funded by CTA through the European Era-Net Cofund ICT-AGRI-FOOD, applies smart agricultural technologies to reduce the risk of mycotoxin contamination in food from barley and wheat.
The effects of mycotoxins on human health range from acute intoxication to long-term effects such as immunodeficiency and cancer.

The Sevillian technology company Agrosap (Precision Agricultural Solutions S. L.) is developing, in collaboration with the University of Seville and other European partners, an R&D&I project funded by CTA (Technological Corporation of Andalusia) through the European Era-Net Cofund ICT-AGRI-FOOD to develop a technology that will reduce mycotoxin contamination of foodstuffs from barley and wheat.

The health effects of mycotoxins range from acute intoxication to long-term effects such as immunodeficiency and cancer. The POSHMyCo project will establish for the first time a novel solution to reduce the risk of mycotoxin contamination in food products from barley and wheat grains through the use of smart agricultural technologies. This will reduce risks to human and animal health, improve farmers’ profitability and reduce the environmental footprint of agricultural production.

In addition to Agrosap and the University of Seville, the project consortium includes the University of Ghent (Belgium) as coordinator, the Aristotle University of Thessaloniki (Greece), the Vytautas Magnus University (Lithuania) and the Swedish University of Agricultural Sciences (Sweden). The project is funded by CTA, but within the framework of the European Era-Net Cofund ICT-AGRI-FOOD, to which CTA belongs and which is a grouping of European funding agencies. The Era-Net allows transnational collaborative R&D&I projects to be developed, with each member of the consortia being a beneficiary, financed by the funding agency of the corresponding country and co-financed by the European Commission.

“Thanks to CTA, we have been able to access funds to continue building the future of the Andalusian agri-food sector using precision agriculture” says Agrosap founding partner and University of Seville researcher Manuel Pérez, who adds that he especially values CTA’s incentive program for its impact on public-private collaborations.

The solution developed will reduce risks to human and animal health, improve farmers' profitability and reduce the environmental footprint of agricultural production.

ICT for precision agriculture

The POSHMyCo project will apply technologies such as GPS systems for variable application of fungicides and intelligent spraying, or sensors for selective harvesting, capable of differentiating between healthy and unhealthy ears or differentiating the part of the harvest that should be used for human food, animal feed or biofuels.

During the three-year duration of the project (2021-2023), POSHMyCo will address issues related to mycotoxin contamination of food, feed and agricultural products, which represent a serious global concern that threatens to have adverse economic and health impacts on both animals and humans. Mycotoxin-contaminated feed has also been reported to have consequences for animal health, such as feed rejection, weight loss and reproductive defects. For agricultural producers, direct economic losses are related to reduced crop yields, reduced animal performance and reduced income due to losses of contaminated food and feed. Currently, producers do not have a validated methodology for determining toxin contamination levels prior to harvesting cereal crops.

The University of Seville POSHMyCo team is formed by Manuel Pérez-Ruiz (PI), Gregorio Egea Cegarra (CO-PI), Nuria López Martínez and Manuel Avilés Guerrero, all of them professors and researchers at the School of Agricultural Engineering (ETSIA) and belonging to the AGR Smart Biosystem Laboratory (AGR278) research group, www.smartbiosystemlab.com) that will develop a system for quantification of mycotoxins in wheat and barley through remote sensing and artificial intelligence techniques.

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