info:eu-repo/semantics/article
Determination of fat content in chicken hamburgers using NIR spectroscopy and the Successive Projections Algorithm for interval selection in PLS regression (iSPA-PLS)
Fecha
2018-01-15Registro en:
Krepper, Gabriela; Romeo, Florencia; Fernandes, David Douglas de Sousa; Diniz, Paulo Henrique Gonçalves Dias; Araújo, Mário César Ugulino de; et al.; Determination of fat content in chicken hamburgers using NIR spectroscopy and the Successive Projections Algorithm for interval selection in PLS regression (iSPA-PLS); Pergamon-Elsevier Science Ltd; Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy; 189; 15-1-2018; 300-306
1386-1425
CONICET Digital
CONICET
Autor
Krepper, Gabriela
Romeo, Florencia
Fernandes, David Douglas de Sousa
Diniz, Paulo Henrique Gonçalves Dias
Araújo, Mário César Ugulino de
Di Nezio, Maria Susana
Pistonesi, Marcelo Fabian
Centurión, María Eugenia
Resumen
Determining fat content in hamburgers is very important to minimize or control the negative effects of fat on human health, effects such as cardiovascular diseases and obesity, which are caused by the high consumption of saturated fatty acids and cholesterol. This study proposed an alternative analytical method based on Near Infrared Spectroscopy (NIR) and Successive Projections Algorithm for interval selection in Partial Least Squares regression (iSPA-PLS) for fat content determination in commercial chicken hamburgers. For this, 70 hamburger samples with a fat content ranging from 14.27 to 32.12 mg kg− 1 were prepared based on the upper limit recommended by the Argentinean Food Codex, which is 20% (w w− 1). NIR spectra were then recorded and then preprocessed by applying different approaches: base line correction, SNV, MSC, and Savitzky-Golay smoothing. For comparison, full-spectrum PLS and the Interval PLS are also used. The best performance for the prediction set was obtained for the first derivative Savitzky-Golay smoothing with a second-order polynomial and window size of 19 points, achieving a coefficient of correlation of 0.94, RMSEP of 1.59 mg kg− 1, REP of 7.69% and RPD of 3.02. The proposed methodology represents an excellent alternative to the conventional Soxhlet extraction method, since waste generation is avoided, yet without the use of either chemical reagents or solvents, which follows the primary principles of Green Chemistry. The new method was successfully applied to chicken hamburger analysis, and the results agreed with those with reference values at a 95% confidence level, making it very attractive for routine analysis.