Classification of biodiesel using NIR spectrometry and multivariate techniques.
This article describes the classification of biodiesel samples using NIR spectroscopy and chemometric techniques. A total of 108 spectra of biodiesel samples were taken (being three samples each of four types of oil, cottonseed, sunflower, soybean and canola), from nine manufacturers. The measurements for each of the three samples were in the spectral region between 12,500 and 4000 cm(-1). The data were preprocessed by selecting a spectral range of 5000-4500 cm(-1), and then a Savitzky-Golay second-order polynomial was used with 21 data points to obtain second derivative spectra. Characterization of the biodiesel was done using chemometric models based on hierarchical cluster analysis (HCA), principal component analysis (PCA) and soft independent modeling of class analogy (SIMCA) elaborated for each group of biodiesel samples (cotton, sunflower, soybean and canola). For the HCA and PCA, the formation of clusters for each group of biodiesel was observed, and SIMCA models were built using 18 spectral measurements for each type of biodiesel (training set), and nine spectral measurements to construct a classification set (except for the canola oil which used eight spectra). The SIMCA classifications obtained 100% accurate identifications. Using this strategy, it was feasible to classify biodiesel quickly and nondestructively without the need for various analytical determinations.
Universidade Estadual da Paraíba, Departamento de Química, 58.429-500, Campina Grande, PB, Brazil. germano.veras@pq.cnpq.br
Germano
G
Veras
Adriano de Araujo
Ade A
Gomes
Adenilton Camilo
AC
da Silva
Anna Luiza Bizerra
AL
de Brito
Pollyne Borborema Alves
PB
de Almeida
Everaldo Paulo
EP
de Medeiros
D056804:Biofuels / Q000032:analysis*; D016000:Cluster Analysis; D003369:Cottonseed Oil / Q000378:metabolism; D005229:Fatty Acids, Monounsaturated / Q000378:metabolism; D006368:Helianthus / Q000378:metabolism; D015999:Multivariate Analysis; D010363:Pattern Recognition, Automated; D000074262:Rapeseed Oil; D013025:Glycine max / Q000378:metabolism; D019265:Spectroscopy, Near-Infrared / Q000379:methods*; D013057:Spectrum Analysis / Q000379:methods
D056804:Biofuels; D003369:Cottonseed Oil; D005229:Fatty Acids, Monounsaturated; D000074262:Rapeseed Oil