Research background. Considering the importance of consumption of berry fruits with proven health-beneficial properties and difficulties in quality control of products of specific botanical and geographic origin, a fingerprint method was developed, based on advanced data analysis (pattern recognition, classification), in order to relate the variability of nutrients in the selected cultivars to primary metabolite profile. Experimental approach. Forty-five samples of genuine berry fruit cultivars (strawberry, raspberry, blackberry, black currant, blueberry, gooseberry, chokeberry, cape gooseberry and goji berry) were characterized according to chromatographic profiles of primary metabolites (sugars, lipids and fatty acids) obtained by three chromatographic techniques (high-performance thin-layer chromatography, gas chromatography coupled to mass spectrometry, and high-performance anion-exchange chromatography with pulsed amperometric detection). Results and conclusions. Comprehensive analysis allowed monitoring and identification of metabolites belonging to polar lipids, mono-, di- and triacylglycerols, free fatty acids, free sterols, sterol esters, mono- to heptasaccharides and sugar alcohols. Chemical fingerprint of berry seeds showed the uniformity of primary metabolites within each fruit species, but revealed differences depending on the botanical origin. All three chromatographic methods provided a discriminative, informative and predictive metabolomics methodology, which proved to be useful for chemotaxonomic classification. Novelty and scientific contribution. A novel methodology for the identification of bioactive compounds from primary metabolites of natural products was described. The proposed untargeted metabolite profiling approach could be used in the future as a routine method for tracing of novel bioactive compounds. The knowledge of metabolite composition obtained in this study can provide a better assessment of genotypic and phenotypic differences between berry fruit species and varieties, and could contribute to the development of new breeding programs., Pozadina istraživanja. Imajući u vidu značaj konzumiranja bobičastog voća dokazanog blagotvornog učinka na organizam, ali i teškoće u kontroli kvalitete proizvoda specifičnog botaničkog i geografskog podrijetla, u radu je predložena metodologija zasnovana na kemijskom profiliranju i naprednoj analizi podataka (prepoznavanje obrazaca i klasifikacija), koja bi se mogla koristiti za procjenu autentičnosti određenih vrsta na osnovu njihovog profila primarnih metabolita. Eksperimentalni pristup. Ukupno je okarakterizirano 45 uzoraka različitih sorata bobičastog voća (jagoda, malina, kupina, crni ribiz, borovnica, ogrozd, aronija, peruanska jagoda i goji) na osnovu kemijskih profila primarnih metabolita (šećera, lipida i masnih kiselina) dobivenih pomoću triju kromatografskih tehnika (tankoslojnom kromatografijom velike učinkovitosti, plinskom kromatografijom spregnutom s masenom spektrometrijom i ionskom kromatografijom s pulsnom amperometrijskom detekcijom). Rezultati i zaključci. Sveobuhvatnom kemijskom analizom identificirane su različite klase metabolita: polarni lipidi, mono-, di- i triacilgliceroli, slobodne masne kiseline, slobodni steroli, sterolni esteri, mono- do heptasaharidi i šećerni alkoholi. Rezultati pokazuju da uzorci koji pripadaju istoj biljnoj vrsti imaju sličan kemijski profil, a različite vrste imaju različit sastav primarnih metabolita. Sve tri kromatografske metode pružaju diskriminativnu, informativnu i prediktivnu metabolomičku metodologiju primjenjivu u kemotaksonomskoj klasifikaciji. Novina i znanstveni doprinos. Opisana je nova metodologija identifikacije bioaktivnih spojeva iz primarnih metabolita prirodnih proizvoda. Predloženi pristup neciljanog profiliranja metabolita mogao bi se koristiti kao rutinska metoda pronalaska novih bioaktivnih spojeva. Poznavanje sastava metabolita omogućuje bolju procjenu genotipskih i fenotipskih razlika između sorata bobičastog voća, što može pridonijeti razvoju novih programa oplemenjivanja.