Research project
36 | monthsOILTRACE

Molecular solution for olive oil safety and traceability

Related toSpoke 03

Principal investigators
Wilma Sabetta

Other partecipantsNicolò Cultrera
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Project partners

Task involved

Task 3.3.1.

The task includes evaluation of safety parameters in traditional and novel foods through the development of: a) chemical sensors and immunosensors for the selective detection of algal and plant toxins, and trace allergens; b) portable devices based on laser photoacoustic spectroscopy (LPAS) and other spectroscopy techniques; c) Ambient Desorption Ionisation methods with High-Resolution Mass Spectrometry (DESI-HRMS); e) use of rt-PCR and digital droplet-PCR to evaluate new and (re)-emerging foodborne pathogenic species; f) metabolomics and proteomics strategies coupled to pathway analysis to evaluate the effects of emerging and re-emerging contaminants; d) analytical techniques, i.e., spectroscopic and MS-based, to determine biogenic amines, pesticides, veterinary drug residues, mycotoxins and processing toxicants; and g) new Matrix-Reference Materials to be characterised for food safety parameters will be developed, including preparation of test-lots, their characterization and homogeneity and stability studies.

Task 3.3.2.

Digital solutions will be developed by transfer of digitization models within the food supply chains and the development of data economy (IoT, Big Data, Edge Computing, etc.) and new “green solutions” in support to food safety, risk assessment and traceability. In addition, smart labels for food oxidation detection and shelf-life assessment will be considered. Tools to address metrological principles for reliability of measurement results and confidence in data for FAIR principles’ implementation will be applied. Finally, a database of food traceability data will be realised by implementing an IoT platform using a specific AI algorithm in real time, and data from WP1 and WP2 will be shared at national level by developing a new platform using ReCaS DataCenter.

Project deliverables

D3.3.1.1.

Safety assessment of traditional and novel foods through targeted and untargeted methodologies (M36)

D3.3.2.1.

Report on transfer and personalization of digitization models within the food supply chains (M36)

D3.3.2.2.

Report Big Data, new solution for food traceability and integrated management of productions (M36)

State of the art

Olive oil, with its high nutraceutical and commercial value, is often subjected to sophistication in mixing/replacement with other oils of lower quality both of the same and of different species as well as possible carriers of allergens. The ex post molecular certification of oil is crucial in quality control and food safety and is transferable within digitization models and the development of data economy in the agri-food chain. DNA unequivocally characterizes species and varieties during food preparation and storage foods: while remaining only in traces, it can be amplified in vitro. Olive oil traceability depends on the degree of DNA purification from the organic matrix and on the performance of the molecular markers. Specific nutritional properties of the oil are linked to the starting genotype as a functional food and integration in micronutrients, opening up the possibility of transferring it to customized personalized nutritional models, which can be integrated into smart labels.

Operation plan

The research focuses on Olea europaea L. cultivars and related mononovarietal oils or blends.
The state of the art on traceability with molecular tools and the transfer of digitization models as the development of the data economy within the oil food chain will be analyzed. Traditional genetic markers will be applied to uniquely ascertain the molecular profiles of olive cultivars and any other oil species used in adulterations and/or sources of allergens. The genomes of commercial olive cultivars will be sequenced, aligned and annotated with bioinformatic analysis and the relative biochemical and nutritional profiles will be defined for the production of BigData.
The CNR Patent 10476, 19 Oct 2018, no. 102.016.000.040.560 for DNA extraction from oily matrices will be applied. A minimum number of the most informative and stable EST markers and functional SNPs from fatty acid, α-tocopherol and triterpene pathways will be applied to ascertain the correspondence with commercial olive oils.

Expected results

  • Develop a list of universal molecular markers based on polymorphisms from genetic BigData.
  • Certify the absence of improper mixing of the olive oils with others of different specie origin.
  • Trace/verify ex post the genetic identity and correspondence between the commercial oils produced and the declared cultivars that contributed to the blends, with their specific nutritional properties.
  • Protect and enhance the oil production deriving from varieties of regional and national interest.
  • Develop molecular profiles of oils for the customization of digitization models within the food chain.