Page 22 - InnoRenew CoE International Conference 2022
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Implementation of spectral sensors and chemometric modelling for
development and support of smart supply chain in the agri-food sector
Albert Kravos1*, Jakub Sandak1;2, Anna Sandak1,3,
1 InnoRenew CoE, Livade 6A, 6310 Izola, Slovenia, albert.kravos@innorenew.eu; jakub.sandak@innorenew.eu; anna.sandak@innorenew.eu
2 University of Primorska, Andrej Marušič Institute, Muzejski trg 2, 6000 Koper, Slovenia jakub.sandak@upr.si
3 University of Primorska, Faculty of Mathematics, Natural Sciences and Information Technologies, Glagoljaška 8, 6000 Koper, Slovenia, anna.
sandak@famnit.upr.si
* Corresponding author
Circular bioeconomy and bio-based product production are becoming essential in the current transition from
a fossil-based economy to a new sustainable green economy. In this context, the possibility to give new life to
underexploited bio-based side streams and residues has enormous benefits. High quality olive leaves represent
a potentially lucrative feedstock for various biorefinery routes; however, the chemical concentration of the
extractives varies considerably between feedstock provenance defining the leaf’s industrial value.
There is limited availability of analytical technologies suitable for in-field assessment of the chemical-physical
properties of biomass. However, intensive progress in smart, portable, and relatively low-cost sensors suitable
for the characterisation of materials is occurring. The real challenge is the development of the spectra post-
processing routines, especially chemometric models linking the light absorbance spectrum with specific
biomass characteristics. Implementation of an approach directly at the site of collection of the leaves will avoid
biorefining of poor-quality biomass and allow the highest concentration of extractives to be processed.
The desired solution will identify high-quality leaves that feature high concentrations of oleuropein, apigenin-
like polyphenols, luteolin-like polyphenols, total polyphenols, oleanolic acid, total triterpenes, essential oil, lignin,
cellulose, and hemicellulose. In concomitance with the OLEAF4VALUE project optimal portable spectrometers
will be investigated. The required chemometric models will be built without advanced data mining; however,
implementation of deep learning for achieving all our goals is not excluded.
Keywords: chemometrics, spectroscopy, circular economy, chemical-physical modelling biomass
Acknowledgement: Authors acknowledge the European Commission for funding the InnoRenew project
(grant agreement #739574 under the Horizon2020 Widespread-2-Teaming program), and the Republic of
Slovenia (investment funding from the Republic of Slovenia and the European Regional Development Fund).
The project OLEAF4VALUE has received funding from the Bio Based Industries Joint Undertaking (JU) under
grant agreement No 101023256. The JU receives support from the European Union’s Horizon 2020 research
and innovation program and the Bio Based Industries Consortium.
22 1 7 – 1 8 N OVE M B E R 2 0 2 2 I I Z O L A , S LOVE N I A
development and support of smart supply chain in the agri-food sector
Albert Kravos1*, Jakub Sandak1;2, Anna Sandak1,3,
1 InnoRenew CoE, Livade 6A, 6310 Izola, Slovenia, albert.kravos@innorenew.eu; jakub.sandak@innorenew.eu; anna.sandak@innorenew.eu
2 University of Primorska, Andrej Marušič Institute, Muzejski trg 2, 6000 Koper, Slovenia jakub.sandak@upr.si
3 University of Primorska, Faculty of Mathematics, Natural Sciences and Information Technologies, Glagoljaška 8, 6000 Koper, Slovenia, anna.
sandak@famnit.upr.si
* Corresponding author
Circular bioeconomy and bio-based product production are becoming essential in the current transition from
a fossil-based economy to a new sustainable green economy. In this context, the possibility to give new life to
underexploited bio-based side streams and residues has enormous benefits. High quality olive leaves represent
a potentially lucrative feedstock for various biorefinery routes; however, the chemical concentration of the
extractives varies considerably between feedstock provenance defining the leaf’s industrial value.
There is limited availability of analytical technologies suitable for in-field assessment of the chemical-physical
properties of biomass. However, intensive progress in smart, portable, and relatively low-cost sensors suitable
for the characterisation of materials is occurring. The real challenge is the development of the spectra post-
processing routines, especially chemometric models linking the light absorbance spectrum with specific
biomass characteristics. Implementation of an approach directly at the site of collection of the leaves will avoid
biorefining of poor-quality biomass and allow the highest concentration of extractives to be processed.
The desired solution will identify high-quality leaves that feature high concentrations of oleuropein, apigenin-
like polyphenols, luteolin-like polyphenols, total polyphenols, oleanolic acid, total triterpenes, essential oil, lignin,
cellulose, and hemicellulose. In concomitance with the OLEAF4VALUE project optimal portable spectrometers
will be investigated. The required chemometric models will be built without advanced data mining; however,
implementation of deep learning for achieving all our goals is not excluded.
Keywords: chemometrics, spectroscopy, circular economy, chemical-physical modelling biomass
Acknowledgement: Authors acknowledge the European Commission for funding the InnoRenew project
(grant agreement #739574 under the Horizon2020 Widespread-2-Teaming program), and the Republic of
Slovenia (investment funding from the Republic of Slovenia and the European Regional Development Fund).
The project OLEAF4VALUE has received funding from the Bio Based Industries Joint Undertaking (JU) under
grant agreement No 101023256. The JU receives support from the European Union’s Horizon 2020 research
and innovation program and the Bio Based Industries Consortium.
22 1 7 – 1 8 N OVE M B E R 2 0 2 2 I I Z O L A , S LOVE N I A
