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Multivariate optimization techniques in food analysis – A review
- Source :
- Food Chemistry. 273:3-8
- Publication Year :
- 2019
- Publisher :
- Elsevier BV, 2019.
-
Abstract
- This work presents a critical review of multivariate techniques employed for optimization of methods developed in food analysis. A comparison between the response surface methodologies has been performed, it evidencing advantages and drawbacks of these. Applications of the main chemometric tools (central composite and Box Behnken designs and Doehlert matrix) often utilized for optimization of sample preparation procedures and also instrumental conditions of analytical techniques for determination of organic and inorganic species in food samples are shown. Also, a brief discussion on the use of multiple responses and robustness test in food analysis has been presented.
- Subjects :
- Multivariate statistics
Central composite design
Computer science
010401 analytical chemistry
04 agricultural and veterinary sciences
General Medicine
Multivariate optimization
040401 food science
01 natural sciences
Box–Behnken design
Food Analysis
0104 chemical sciences
Analytical Chemistry
0404 agricultural biotechnology
Robustness (computer science)
Multivariate Analysis
Doehlert matrix
Sample preparation
Biochemical engineering
Food Science
Subjects
Details
- ISSN :
- 03088146
- Volume :
- 273
- Database :
- OpenAIRE
- Journal :
- Food Chemistry
- Accession number :
- edsair.doi.dedup.....e644e2f659ec93782b11532f7d8ec5a1
- Full Text :
- https://doi.org/10.1016/j.foodchem.2017.11.114