Back to Search
Start Over
Detection of unexpected frauds: Screening and quantification of maleic acid in cassava starch by Fourier transform near-infrared spectroscopy.
- Source :
-
Food Chemistry . Jul2017, Vol. 227, p322-328. 7p. - Publication Year :
- 2017
-
Abstract
- Fourier transform near-infrared (FT-NIR) spectroscopy and chemometrics were adopted for the rapid analysis of a toxic additive, maleic acid (MA), which has emerged as a new extraneous adulterant in cassava starch (CS). After developing an untargeted screening method for MA detection in CS using one-class partial least squares (OCPLS), multivariate calibration models were subsequently developed using least squares support vector machine (LS-SVM) to quantitatively analyze MA. As a result, the OCPLS model using the second-order derivative (D2) spectra detected 0.6% (w/w) adulterated MA in CS, with a sensitivity of 0.954 and specificity of 0.956. The root mean squared error of prediction (RMSEP) was 0.192 (w/w, %) by using the standard normal variate (SNV) transformation LS-SVM. In conclusion, the potential of FT-NIR spectroscopy and chemometrics was demonstrated for application in rapid screening and quantitative analysis of MA in CS, which also implies that they have other promising applications for untargeted analysis. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 03088146
- Volume :
- 227
- Database :
- Academic Search Index
- Journal :
- Food Chemistry
- Publication Type :
- Academic Journal
- Accession number :
- 121558065
- Full Text :
- https://doi.org/10.1016/j.foodchem.2017.01.061