Pregled bibliografske jedinice broj: 890675
Near-infrared spectroscopic characterization of steviol glycosides extracted from Stevia rebaudiana Bertoni using high-power ultrasound and gas-phase plasma
Near-infrared spectroscopic characterization of steviol glycosides extracted from Stevia rebaudiana Bertoni using high-power ultrasound and gas-phase plasma // Journal of food and nutrition research, 56 (2017), 2; 109-120 (međunarodna recenzija, članak, znanstveni)
CROSBI ID: 890675 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
Near-infrared spectroscopic characterization of steviol glycosides extracted from Stevia rebaudiana Bertoni using high-power ultrasound and gas-phase plasma
Autori
Kujundžić, Dijana ; Režek Jambrak, Anet ; Vukušić, Tomislava ; Stulić, Sanja ; Gajdoš Kljusurić, Jasenka ; Banović, Mara ; Herceg, Zoran
Izvornik
Journal of food and nutrition research (1336-8672) 56
(2017), 2;
109-120
Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni
Ključne riječi
steviol glycosides ; near-infrared spectroscopy ; gas-phase plasma ; high-intensity ultrasound ; principal component analysis ; partial least squares regression
Sažetak
The purpose of this study was to examine the possibility of extraction of steviol glycosides from dried leaves of Stevia rebaudiana by application of high-intensity ultrasound and gas atmospheric plasma, in which water is used as a solvent. In contrast to Soxhlet extraction (by water), an increase in the yield of average value of steviol glycosides was achieved by ultrasound (59 %) and gas plasma (43 %). Highest effect was at treatment for 30 min, the amplitude of 90 μm, and a temperature of 45 °C. After gas plasma treatments, the average yield of steviol glycosides (101.34 g·kg⁻¹) was slightly lower than that after the application of ultrasound. This study also established a near-infrared spectroscopy (NIR) model for direct and rapid analysis of the expected content of steviosides. NIR spectroscopy showed the capacity that, combined with multivariate analysis tools (principal component analysis, partial least squares regression), was successful in grouping data.
Izvorni jezik
Engleski
Znanstvena područja
Prehrambena tehnologija
POVEZANOST RADA
Ustanove:
Prehrambeno-biotehnološki fakultet, Zagreb
Profili:
Zoran Herceg
(autor)
Anet Režek Jambrak
(autor)
Tomislava Vukušić Pavičić
(autor)
Mara Banović
(autor)
Jasenka Gajdoš Kljusurić
(autor)
Citiraj ovu publikaciju:
Časopis indeksira:
- Current Contents Connect (CCC)
- Web of Science Core Collection (WoSCC)
- Science Citation Index Expanded (SCI-EXP)
- SCI-EXP, SSCI i/ili A&HCI
- Scopus