Napredna pretraga

Pregled bibliografske jedinice broj: 1025746

Application of multivariate regression and artificial neural network modelling for prediction of physical and chemical properties of medicinal plants aqueous extracts


Jurinjak Tušek, Ana; Jurina, Tamara; Benković, Maja; Valinger, Davor; Belščak-Cvitanović, Ana; Gajdoš Kljusurić, Jasenka
Application of multivariate regression and artificial neural network modelling for prediction of physical and chemical properties of medicinal plants aqueous extracts // Journal of Applied Research on Medicinal and Aromatic Plants (2019) (znanstveni, prihvaćen)


Naslov
Application of multivariate regression and artificial neural network modelling for prediction of physical and chemical properties of medicinal plants aqueous extracts

Autori
Jurinjak Tušek, Ana ; Jurina, Tamara ; Benković, Maja ; Valinger, Davor ; Belščak-Cvitanović, Ana ; Gajdoš Kljusurić, Jasenka

Vrsta, podvrsta
Radovi u časopisima, znanstveni

Izvornik
Journal of Applied Research on Medicinal and Aromatic Plants (2019)

Status rada
Prihvaćen

Ključne riječi
Multivariate regression ; artificial neural network ; medicinal plants aqueous extracts

Sažetak
In recent years, multivariate modelling techniques have been employed with the aim of analysing, describing, and generally interpreting multidimensional data obtained from experiments. The objective of this study was to evaluate the applicability of multiple linear regression, nonlinear regression, piecewise linear regression, and artificial neural network modelling for the prediction of the physical properties (total dissolved solids, extraction yield), and chemical properties (total phenolic content and antioxidant activity) of the aqueous extracts of nine medicinal plants (dandelion, camomile, lavender, lemon balm, marigold, mint, nettle, plantain, and yarrow), prepared in dynamic experiments based on the extraction conditions (time and temperature), and plant species. Results indicated that simple multivariate regression models could be used for prediction of physical and chemical properties of medicinal plants aqueous extracts (the highest R2 were obtained for total phenolic content), while the artificial neural network proved a very effective tool (R2 > 0.9) for simultaneous prediction of both physical and chemical properties of medicinal plants aqueous extracts.

Izvorni jezik
Engleski

Znanstvena područja
Biotehnologija, Prehrambena tehnologija

Citiraj ovu publikaciju

Jurinjak Tušek, Ana; Jurina, Tamara; Benković, Maja; Valinger, Davor; Belščak-Cvitanović, Ana; Gajdoš Kljusurić, Jasenka
Application of multivariate regression and artificial neural network modelling for prediction of physical and chemical properties of medicinal plants aqueous extracts // Journal of Applied Research on Medicinal and Aromatic Plants (2019) (znanstveni, prihvaćen)
Jurinjak Tušek, A., Jurina, T., Benković, M., Valinger, D., Belščak-Cvitanović, A. & Gajdoš Kljusurić, J. (2019) Application of multivariate regression and artificial neural network modelling for prediction of physical and chemical properties of medicinal plants aqueous extracts. Prihvaćen za objavljivanje u Journal of Applied Research on Medicinal and Aromatic Plants. [Preprint].
@unknown{unknown, year = {2019}, keywords = {multivariate regression, artificial neural network, medicinal plants aqueous extracts}, journal = {Journal of Applied Research on Medicinal and Aromatic Plants}, title = {Application of multivariate regression and artificial neural network modelling for prediction of physical and chemical properties of medicinal plants aqueous extracts}, keyword = {multivariate regression, artificial neural network, medicinal plants aqueous extracts} }

Časopis indeksira:


  • Web of Science Core Collection (WoSCC)
    • Emerging Sources Citation Index (ESCI)
  • Scopus