TY - JOUR
T1 - Identification and quantification of corncob as adulterant in corn dough and tortilla by MIR-FTIR spectroscopy and multivariate analysis
AU - Piña-Barrera, Andrés
AU - Meza-Márquez, Ofelia Gabriela
AU - Osorio-Revilla, Guillermo
AU - Gallardo-Velázquez, Tzayhrí
N1 - Funding Information:
Financial support from the Consejo Nacional de Ciencia y Tecnología (CONACyT) and the Secretaría de Estudios de Posgrado e Investigación del Instituto Politécnico Nacional de México (SIP-IPN) is greatly appreciated.
PY - 2014/1/2
Y1 - 2014/1/2
N2 - Fourier Transform Infrared (FTIR) spectroscopy coupled to chemometrics was developed to detect and quantify the adulteration in white and blue corn dough and white and blue corn tortilla, with corncob. The classification model, soft independent modeling of class analogy (SIMCA), showed 100% correct classification rate for adulterated samples from unadulterated ones. The best quantitative chemometric calibration model was developed with the partial least square (PLS) algorithm showing coefficient of determination (R2) between predicted and actual adulterant concentrations that range from 0.996 to 0.998 for all samples. Standard error of prediction (SEP) for the developed models ranged between 0.395 and 0.590 for all samples. The results showed that mid-infrared spectroscopy in conjunction with multivariate analysis can effectively be used to identify and quantify corncob in white and blue corn dough and in white and blue corn tortilla.
AB - Fourier Transform Infrared (FTIR) spectroscopy coupled to chemometrics was developed to detect and quantify the adulteration in white and blue corn dough and white and blue corn tortilla, with corncob. The classification model, soft independent modeling of class analogy (SIMCA), showed 100% correct classification rate for adulterated samples from unadulterated ones. The best quantitative chemometric calibration model was developed with the partial least square (PLS) algorithm showing coefficient of determination (R2) between predicted and actual adulterant concentrations that range from 0.996 to 0.998 for all samples. Standard error of prediction (SEP) for the developed models ranged between 0.395 and 0.590 for all samples. The results showed that mid-infrared spectroscopy in conjunction with multivariate analysis can effectively be used to identify and quantify corncob in white and blue corn dough and in white and blue corn tortilla.
KW - FTIR
KW - adulteration
KW - corn dough
KW - corn tortilla
KW - corncob
KW - multivariate analysis
UR - http://www.scopus.com/inward/record.url?scp=84896975319&partnerID=8YFLogxK
U2 - 10.1080/19476337.2013.796572
DO - 10.1080/19476337.2013.796572
M3 - Artículo
SN - 1947-6337
VL - 12
SP - 65
EP - 72
JO - CYTA - Journal of Food
JF - CYTA - Journal of Food
IS - 1
ER -