Optimization of Experimental Parameters in Analysis of Pharmaceutical Pellets by Near Infrared-Chemical Imaging (NIR-CI) and Multivariate Curve Resolution with Alternating Least Squares (MCR-ALS)

Da-Col, José Augusto; Poppi, Ronei J.

doi:10.21577/0103-5053.20180059

José Augusto Da-Col ^** e-mail: jose.col@udesc.br ^##Present address: Departamento de Química, Centro de Ciências Tecnológicas, Universidade do Estado de Santa Catarina (UDESC), 89219-710 Joinville-SC, Brazil (http://www.cct.udesc.br).

Laboratório de Quimiometria em Química Analítica (LAQQA), Instituto de Química, Universidade Estadual de Campinas, CP 6154, 13083-970 Campinas-SP, Brazil

Ronei J. Poppi

Laboratório de Quimiometria em Química Analítica (LAQQA), Instituto de Química, Universidade Estadual de Campinas, CP 6154, 13083-970 Campinas-SP, Brazil

* e-mail: jose.col@udesc.br

#Present address: Departamento de Química, Centro de Ciências Tecnológicas, Universidade do Estado de Santa Catarina (UDESC), 89219-710 Joinville-SC, Brazil (http://www.cct.udesc.br).

Operating condition	6.25 µm	25 µm	50 µm
Resolution / cm^-1	16	16	16
Scans number	32	32	32
Spectral range / cm^-1	7800-4000	7800-4000	7800-4000
Pixel size / µm	6.25	25	50
Image area / µm	1300 × 1300	1300 × 1300	1300 × 1300
Image area in pixel number	208 × 208	52 × 52	26 × 26
Pure substances area / µm	75 × 75	300 × 300	600 × 600
Pure substances area in pixel number	12 × 12	12 × 12	12 × 12
Spectra number	43264	2704	676
Variables number	476	476	476

Pixel size / µm	Correlation coefficient
Pixel size / µm	Sucrose	Starch	SiO₂	Ketoprofen
6.25	0.8005	0.8705	0.9464	0.9597
25	0.9607	0.9485	0.6112	0.9903
50	0.9836	0.9766	0.8751	0.9922

Figure of merit	Pixel size
Figure of merit	6.25 µm	25 µm	50 µm
Percentage of variance explained (r²) / %	91.19	99.82	99.88
Percentage of lack of fit (LOF) / %	0.0381	0.00263	0.00000725

Component	Pure substances spectra		Between models
Component	With instrumental signal	Using PURE function	Between models
Sucrose	0.9607	0.9866	0.9860
Starch	0.9485	0.9849	0.9609
SiO₂	0.6112	0.9184	0.8466
Ketoprofen	0.9903	0.9831	0.9936

Component	Pure substances spectra		Between models
Component	Individual matrix	Augmented matrix	Between models
Sucrose	0.9607	0.9846	0.9931
Starch	0.9485	0.9813	0.9711
SiO₂	0.6112	0.5848	0.9812
Ketoprofen	0.9903	0.9895	0.9994

Figure of merit	Individual matrix	Augmented matrix
Variance explained (r²) / %	99.82	99.83
Lack of fit (LOF) / %	0.00263	0.00632

Component	Sample P1	Sample P2	Sample P3
Sucrose	0.9607	0.9820	0.9076
Starch	0.9485	0.9437	0.9518
SiO₂	0.6112	0.6066	0.5644
Ketoprofen	0.9903	0.9947	0.9881

Figure of merit	Sample P1	Sample P2	Sample P3
Variance explained (r²) / %	99.82	99.86	99.87
Lack of fit (LOF) / %	0.00263	0.00150	0.00434

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Optimization of Experimental Parameters in Analysis of Pharmaceutical Pellets by Near Infrared-Chemical Imaging (NIR-CI) and Multivariate Curve Resolution with Alternating Least Squares (MCR-ALS)