Učni načrt predmeta

Predmet:
Sledljivost in pristnost živil
Course:
Food Traceability and Authenticity
Študijski program in stopnja /
Study programme and level		 Študijska smer /
Study field		 Letnik /
Academic year		 Semester /
Semester
Ekotehnologije, 3. stopnja 1 1
Ecotechnologies, 3rd cycle 1 1
Vrsta predmeta / Course type
Izbirni
Univerzitetna koda predmeta / University course code:
EKO3-705
Predavanja
Lectures		 Seminar
Seminar		 Vaje
Tutorial		 Klinične vaje
work		 Druge oblike
študija		 Samost. delo
Individ. work		 ECTS
30 30 30 210 10

*Navedena porazdelitev ur velja, če je vpisanih vsaj 15 študentov. Drugače se obseg izvedbe kontaktnih ur sorazmerno zmanjša in prenese v samostojno delo. / This distribution of hours is valid if at least 15 students are enrolled. Otherwise the contact hours are linearly reduced and transfered to individual work.

Nosilec predmeta / Course leader:
prof. dr. Nives Ogrinc
Sodelavci / Lecturers:
prof. dr. Barbara Koroušić Seljak , prof. dr. Janez Plavec
Jeziki / Languages:
Predavanja / Lectures:
Slovenian, English
Vaje / Tutorial:
Slovenian, English
Pogoji za vključitev v delo oz. za opravljanje študijskih obveznosti:
Prerequisites:

Zaključen študij druge stopnje ustrezne (naravoslovne ali tehniške) smeri ali zaključen študij drugih smeri z dokazanim poznavanjem osnov področja predmeta (pisna dokazila, pogovor). Potrebna so tudi osnovna znanja iz računalništva in statistike.

Completed second level studies in natural sciences or engineering or completed second level studies in other fields with proven knowledge of fundamentals in the field of this course (certificates, interview). The basic knowledge in computer science and statistics is needed.

Vsebina:
Content (Syllabus outline):

Podiplomskim študentom zagotoviti znanje na področju sistema zagotavljanja pristnosti in sledljivosti živil.
Sistemi sledljivosti nam podaja informacije o pristnosti in izvoru proizvoda v verigi preskrbe s hrano. Prav na področju sledljivosti živil so se pojavile zahteve po bolj sofisticiranih instrumentih in primernih analitskih metodah, ki omogočajo boljše kvalitativne in kvantitativne rezultate. Tako raziskovalci vključeni v sodobno znanost o živilih potrebujejo ustrezno znanje za delo na naprednih analitskih orodjih, da se lahko soočijo s kompleksnostjo samega problema in ustvarjajo rezultate na racionalen način.

V okviru predmeta bomo predstavili različne pristope in metode, ki se uporabljajo pri sledljivosti na področju živilstva:
- Podane bodo teoretične osnove ter regulative, norme, certificiranje in standardi, ki vključujejo sledljivost.
- Predstavljene bodo vrste potvorb, ki se pojavljajo v živilih, in načini reševanja problemov z naprednimi analitskimi metodami, ki se navezujejo na kakovost in varnost živil.
- Predstavili bomo principe in aplikacije uporabe stabilnih izotopov lahkih elementov (H, C, N, O in S), težjih elementov (Sr) in elementov v sledovih, ki se uporabljajo pri določanju pristnosti in sledljivosti živil.
- Podane bodo osnove in principi delovanja masne spektrometrije in NMR ter meroslovni principi, ki zagotavljajo sledljive in primerljive rezultate meritev.
- Sledila bo predstavitev ovrednotenja, dokumentiranja in analize pridobljenih podatkov na področju pristnosti in sledljivosti.
- Uporaba naprednih statističnih metod kot so linearna diskriminantna analiza, analiza glavnih osi.
- Uporaba prostorskega modeliranja vključno z uporabo geografskega informacijskega sistema (GIS) in izdelavo »isoscapes« na lokalnem, regionalnem in svetovnem nivoju. Principi prostorskega modeliranja bodo predstavljeni na osnovnem, teoretično-metodološkem nivoju.
- V okviru predmeta bodo predstavljeni tudi drugi načini sledljivosti, ki se uporabljajo na področju živilstva, kot so npr. črtne kode, radiofrekvenčna identifikacija (RFID).

Predstavitev primerov iz prakse in industrije.

The course is open to graduate students who wish to understand better systems and concepts relating to food authenticity and traceability.
Traceability systems provide information on the history, authenticity and the origin of a product in the supply food chain. Improvements in this field are increasing rapidly as is the demand for robust analytical methods and strategies that can deliver better qualitative and quantitative results. This is the reality for many working in modern food science, so it is essential to have sufficient knowledge to make the most of what these technologies have to offer.

The postgraduate course will explore all aspects of food traceability including the following:
- Theoretical background and overview on legislation, norms, certification and standards involving traceability.
- The different types of fraud and the opportunities to identify fraud using advanced analytical methods and the link between food quality and safety.
- The principles and use of stable isotopes of light elements (H, C, N, O and S), non-traditional isotopes (Sr) and trace elements in determining authenticity.
- Principles of mass spectrometry and NMR techniques. Validation of analytical methods; Traceability and comparability of the results.
- How to evaluate, document and analyse food authenticity and traceability data.
- The use of advanced statistical methods such as principal component analysis and linear discrimination analysis.
- The use of spatial modelling including the geographical information system (GIS) approach and "isoscapes" on the local, regional and global scale. It will also provide students with an understanding of the principles of spatial modelling at the basic, theoretical and methodological level.
- The course will also cover other ways of tracing food that are used in the food industry, such as barcodes, radio frequency identification (RFID).

Case studies including industrial aspect.

Temeljna literatura in viri / Readings:

- Food Authenticity and Traceability, volume in Woodhead Publishing Series in Food Science, Technology
and Nutrition; Edited by M. Lees, ISBN: 978-1-85573-526-2.
- Food Chain Integrity: A Holistic Approach to Food Traceability, Safety, Quality and Authenticity
(Woodhead Publishing Series in Food Science, Technology and Nutrition); Edited by J. Hoorfar, K.
Jordan, F. Butler, R. Prugger, ISBN: 978-0857090683.
- Milan Hladnik, Verjetnost in statistika. Založba FE in FRI, 2002.
- David S. Moore, Statistika: znanost o podatkih. Purdue University, prevod v slovenščino 2010; dostopno
na http://studentski.net/gradivo/ulj_fri_ri3_ovs_sno_statistika__znanost_o_podatkih_01__knjiga?r=1
(september 2016).
- Katarina Košmelj, Uporabna statistika, 2. dop. Izdaja. Biotehniška fakulteta, Univerza v Ljubljani, 2007;
dostopno na http://www.bf.uni-lj.si/fileadmin/groups/2721/Uporabna_statistika_okt_2007/Uporabna_statistika_01.pdf (september 2016).
- Pregledni članki iz: Food Chemistry, Journal of Agricultural and Food Chemistry, Journal of Food
Composition and Analysis, Journal of Food Science, Comprehensive Reviews in Food Science and Food
Safety itd., tekoča periodika, druga učna gradiva …"

Cilji in kompetence:
Objectives and competences:

Izobraževalni cilji:
Študenti bodo poglobili znanje o uporabi različnih metod in pristopov pri določanju pristnosti in sledljivosti živil:
- uporaba naprednih analitskih metod, ki vključujejo stabilne izotope (IRMS, NMR tehnike), hitre metode (FTIR, UV-VIS) in določanje elementne sestave (ICP-MS, XRF);
- modeliranje in geoinformatika.

Študijski rezultati:
Vse to naj bi študentom omogočilo napredno in interdisciplinarno razumevanje področja kontrole, varnosti in kakovosti ter porekla živil in njihovo sledljivost v dobavni verigi.

The curriculum is designed to provide students with an understanding of the latest principles, practices regarding food authenticity and traceability systems including:
- a comprehensive understanding of advanced analytical methods including stable isotopes (IRMS, NMR techniques), fast methods (FTIR, UV-VIS), determination of elemental composition (ICP-MS, XRF),
- modelling and geoinformatics in relation to food authenticity and traceability.

This course gives students an advanced and interdisciplinary understanding of control, safety, quality and provenance of food products and their traceability along the supply chain.

Predvideni študijski rezultati:
Intendeded learning outcomes:

Znanje in razumevanje:
- osnovo znanje o definiciji pojmov, ki so povezani s sledljivostjo in pristnostjo živil;
- identifikacijo možnih potvorb in z njimi poveznih nevarnosti;
- razumeti principe osnov uporabe stabilnih izotopov lahkih elementov in elementne sestave pri določanju pristnosti in sledljivosti živil;
- obdelava in dokumentacija rezultatov z naprednimi statističnimi metodami in modeliranjem;
- uporaba pridobljenih znanj pri reševanju praktičnih problemov poveznih s pristnostjo in sledljivostjo živil.

Splošne kompetence:
- obvladanje raziskovalnih metod na področju pristnosti in sledljivosti živil v povezavi s kakovostjo in varnostjo;
- sposobnost uporabe pridobljenega znanja in spretnosti pri izvedbi analiz in obdelavi podatkov v praksi;
- izboljšati način analitičnega in kritičnega razmišljanja, uporabnega tudi v vsakodnevnem življenju, ter komunikacijske sposobnosti;
- kooperativnost, delo v skupini (in v mednarodnem okolju).

Knowledge and Understanding:
- gain knowledge of the definitions of concepts related to food authenticity and traceability;
- identify the common types of food frauds and the associated hazards;
- understand the basic principles of using stable isotopes of light elements and elemental composition for determining food autheticity and traceability;
- document and evaluate data using advanced statistical methods and modeling;
- select and carry out appropriate techniques to solve analytical problems associated with food authenticity and traceability.

General Competences:
- the student will master research methods in the field of traceability for food safety and quality control;
- ability to use the knowledge and skills acquired to analyze and interpret experimental data obtained from different instrumental measurements;
- demonstrate analytical and critical thinking as well as life-long learning and communication skills;
- ability to work on an interdisciplinary team (in international environment).

Metode poučevanja in učenja:
Learning and teaching methods:

Predavanja, priprava seminarjev - timsko delo in debate. Poudarek je predvsem na reševanju realnih problemov, ki so povezani z raziskovalnim delom kandidata.

Lectures, seminars – team work and discussions.
The focus is on solving real problems that are related to the research work of the student.

Načini ocenjevanja:
Delež v % / Weight in %
Assesment:
Seminarska naloga
30 %
Seminar work
Ustni zagovor seminarske naloge
30 %
Oral defense of seminar work
Študenti bodo morali razviti študijo v povezavi z njihovo kariero
40 %
Students will be required to develop an enquiry linked to their specialist pathway
Reference nosilca / Lecturer's references:
1. MAHYNSKI, Nathan A., STROJNIK, Lidija, SHEN, Vincent Kevin, OGRINC, Nives. Comparing machine learning models to chemometric ones to detect food fraud : a case study in Slovenian fruits and vegetables. Food chemistry. 2025, vol. 486, [article no.] 144569, pp. 1-12, ilustr. ISSN 1873-7072. DOI: 10.1016/j.foodchem.2025.144569.
2. GIANNIOTI, Zoe, OGRINC, Nives, SUMAN, Michele, CAMIN, Federica, BONTEMPO, Luana. Isotope ratio mass spectrometry (IRMS) methods for distinguishing organic from conventional food products: a review. TrAC trends in analytical chemistry 2024, 170, [article no.] 117476, str. 1-20, ilustr. ISSN 1879-3142. DOI: 10.1016/j.trac.2023.117476
3. HADŽI, San, ŽIVIČ, Zala, KOVAČIČ, Matic, ZAVRTANIK, Uroš, HAESAERTS, Sarah, CHARLIER, Daniel, PLAVEC, Janez, VOLKOV, Alexander N., LAH, Jurij, LORIS, Remy. Fuzzy recognition by the prokaryotic transcription factor HigA2 from Vibrio cholerae. Nature communications. 2024, vol. 15, article no. 3105, str. 1-12, ilustr. ISSN 2041-1723. DOI: 10.1038/s41467-024-47296-3.
4. TERRO, Cathrine, MODIC, Robert, OGRINC, Matevž, SIMČIČ, Andraž, DROLE, Jan, EFTIMOV, Tome, KOROUŠIĆ-SELJAK, Barbara, OGRINC, Nives. IsoFoodTrack : a comprehensive database and management system based on stable isotope ratio analysis for combating food fraud. Frontiers in nutrition. 2025, vol. 12, str. 1-11, ilustr. ISSN 2296-861X. DOI: 10.3389/fnut.2025.1516521.
5. EMARA, Yasmine, KOROUŠIĆ-SELJAK, Barbara, GIBNEY, Eillen R., POPOVSKI, Gorjan, PRAVST, Igor, FANTKE, Peter. Workflow for building interoperable food and nutrition security (FNS) data platforms. Trends in food science & technology. 2022, 46 str. ISSN 0924-2244. DOI: 10.1016/j.tifs.2022.03.022.