Validation of multivariate calibration models in the determination of sugar cane quality parameters by near infrared spectroscopy

The determination of soluble solids (BRIX), polarizable sugars (POL) and reducing sugars (RS) sugar cane juice by using near infrared spectroscopy (NIR) and multivariate calibration was developed and validated by calculation of figures of merit. Due to the heterogeneity of the samples, first it was necessary to optimize the calibration set by outlier elimination. The figures of merit such as: sensitivity, analytical sensitivity, selectivity, confidence limit, precision (mean, repeatability), accuracy and signal-to-noise ratio were calculated. Feasible results were obtained for BRIX and POL with RMSEP values of 0.28 and 0.42% of juice and precision of 0.02 and 0.08% of juice, respectively. For both BRIX and POL goodness of fit showed correlation coefficients of 0.99. These results indicate that the models developed for BRIX and POL can be used as an alternative to standard procedures in the sugar cane industry.Os teores de sólidos solúveis (BRIX), açúcares polarizáveis (POL) e açúcares redutores (RS) em caldo de cana foram determinados utilizando espectroscopia na região do infravermelho próximo (NIR) e calibração multivariada, a qual foi validada pelo cálculo das figuras de mérito. Devido à heterogeneidade das amostras, foi necessário, como primeira etapa do trabalho, a otimização dos conjutos de calibração e validação através da eliminação das amostras anômalas (outliers). As figuras de mérito como: sensibilidade, sensibilidade analítica, seletividade, limites de confiança, precisão (média, repetibilidade), exatidão e razão sinal-ruído foram calculadas. Resultados viáveis foram obtidos para BRIX e POL apresentando resultados de RMSEP de 0,28 e 0,42% de caldo, respectivamente. Os coeficientes de correlação para ambos os parâmetros foram de 0,99. Estes resultados indicam que os modelos desenvolvidos para BRIX e POL podem ser seguramente utilizados como uma alternativa em relação ao método padrão utilizado na indústria alcooleira.259266Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES

State of the art of figures of merit in multivariate calibration

The validation of an analytical procedure must be certified through the determination of parameters known as figures of merit. For first order data, the acuracy, precision, robustness and bias is similar to the methods of univariate calibration. Linearity, sensitivity, signal to noise ratio, adjustment, selectivity and confidence intervals need different approaches, specific for multivariate data. Selectivity and signal to noise ratio are more critical and they only can be estimated by means of the calculation of the net analyte signal. In second order calibration, some differentes approaches are necessary due to data structure.12781287Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq

Estado da arte de figuras de mérito em calibração multivariada

The validation of an analytical procedure must be certified through the determination of parameters known as figures of merit. For first order data, the acuracy, precision, robustness and bias is similar to the methods of univariate calibration. Linearity, sensitivity, signal to noise ratio, adjustment, selectivity and confidence intervals need different approaches, specific for multivariate data. Selectivity and signal to noise ratio are more critical and they only can be estimated by means of the calculation of the net analyte signal. In second order calibration, some differentes approaches are necessary due to data structure

Toxic Metals (Pb and Cd) and Their Respective Antagonists (Ca and Zn) in Infant Formulas and Milk Marketed in Brasilia, Brazil

In non-ideal scenarios involving partial or non-breastfeeding, cow’s milk-based dairy products are mainstream in infant feeding. Therefore, it is important to study the concentrations of potentially neurotoxic contaminants (Pb and Cd) and their respective counteracting elements (Ca and Zn) in infant dairy products. Fifty-five brands of infant formulas and milk sold in Brasilia, Brazil were analyzed. The dairy products came from areas in the central-west (26%), southeast (29%) and south of Brazil (36%) extending as far as Argentina (7%) and the Netherlands (2%). For toxic Pb and Cd, median concentrations in powdered samples were 0.109 mg/kg and 0.033 mg/kg, respectively; in fluid samples median Pb concentration was 0.084 mg/kg, but median Cd concentration was below the limit of detection and overall values were below reference safety levels. However, 62% of these samples presented higher Pb concentration values than those established by FAO/WHO. Although the inverse correlation between Cd and Zn (Spearman r = −0.116; P = 0.590) was not statistically significant, the positive correlation between Ca and Pb was (Spearman r = 0.619; P < 0.0001). Additionally, there was a significant correlation between Pb and Cd. Furthermore, the study also revealed that provision of the essential trace element Zn in infant formulas can provide adequate amounts of the recommended daily requirements. Infant formulas and milk sold for consumption by infants and children can be an efficient tool to monitor neurotoxic metal risk exposure among young children

CLASSIFICAÇÃO DE ÁGUAS MINERAIS BASEADA EM IMAGENS DIGITAIS OBTIDAS POR SMARTPHONES

This work describes a new procedure for classification of mineral waters based on digital images acquired by smartphones. Commercial waters from eight mineral springs plus distilled water and tap water were combined with eriochrome T black or murexide and transferred to a cuvette, which was positioned into a light controlled chamber. RGB (Red, Blue and Green) measurements of cuvette images were acquired in real time, using a free smartphone app, and employed as variables for the exploratory analysis. 2D data dispersion along component B for murexide (x axis) and component R for eriochrome T black (y axis) provides the clear visualization of clusters using the raw variables. Hierarchical cluster analysis (HCA) applied to this data confirmed the efficient discrimination of samples providing the characterization of nine clusters for the ten classes of water investigated. The classification of samples based on a k-nearest neighbors (k-NN) modelled to the efficiency rate of 100% for 8 classes and of 94.4% and 50% for the remaining classes, respectively, indicating the adequate performance of the proposed strategy. Considering the facilities to acquire the data, such as low cost instrumentation and reagents, and the rapidity of the procedures, this alternative may be applied for verification of commercial water adulteration