Naslov
Trends in chemometrics and effects of processing and extraction of biologically active compounds

Autori
Putnik, P ; Granato, D ; Da Cruz, A.G. ; Rodionova, O.Y. ; Pomerantsev, A. ; Bursac Kovacevic, D.

Vrsta, podvrsta i kategorija rada
Sažeci sa skupova, sažetak, ostalo

Izvornik
2nd Food Chemistry Conference: Shaping the Future of Food Quality, Safety, Nutrition and Health / - Sevilla : Elsevier, 2019, IN06-IN06

Skup
2nd Food Chemistry Conference: Shaping the Future of Food Quality, Safety, Nutrition and Health

Mjesto i datum
Sevilla, Španjolska, 17.09.2019. - 19.09.2019

Vrsta sudjelovanja
Pozvano predavanje

Vrsta recenzije
Međunarodna recenzija

Ključne riječi
chemometrics ; factor analysis ; multivariate analysis ; mathematical modeling ; experimental design ; statistics ; biologically active compounds ;

Sažetak
Chemometrics is a set of mathematical and statistical methods that are used to optimize design of experiments and to extract useful information form large datasets. Complex datasets quite often have numerous sources of variations, with one or more dependent variables assessed against the two or more dependent variables, hence the need to employ some type of multivariate statistics. It is critical to decrease the chances of type I error, by comparing (calculating) all the effects of independent variables, in a single multivariate test. The most common types of multivariate tests include multivariate analysis of variance (MANOVA), various forms of factor analysis (such as principal components analysis, PCA), mathematical modeling, and many others. Bioactive compounds (BAC) are interesting for functional food production. Their extraction and processing mostly revolves around the central problem of thermal (in)stability and environmental issues that are relevant for industry. Here multivariate statistics can offer the best mathematical solutions for optimal industrial production or devise various indexes that are able to follow changes of entire chemical footprint during the extraction of target compounds. For instance, multivariate statistics is useful to determine optimal extraction parameters for antioxidants while simultaneously evaluating the effects and interactions of extraction parameters.

Izvorni jezik
Engleski

Znanstvena područja
Prehrambena tehnologija

POVEZANOST RADA