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Detection of several common adulterants in raw milk by MID-infrared spectroscopy and one-class and multi-class
Carina de Souza Gondim1, Roberto Gonçalves Junqueira2, Scheilla Vitorino Carvalho de Souza2
1Department of Food Science, Faculty of Pharmacy (FAFAR), Federal University of Minas Gerais (UFMG), Av. Antônio Carlos, 6627, Campus da UFMG, Pampulha, 31270-010 Belo Horizonte, MG, Brazil; CAPES Foundation, Ministry of Education of Brazil, 70040-020 Brasília, DF, Brazil; Chemometrics, Qualimetrics and Nanosensors Group, Department of Analytical and Organic Chemistry, Rovira i Virgili University, Marcel·lí Domingo s/n, 43007 Tarragona, Spain.
Abstract:
A sequential strategy was proposed to detect adulterants in milk using a mid-infrared spectroscopy and soft independent modelling of class analogy technique. Models were set with low target levels of adulterations including formaldehyde (0.074g.L-1), hydrogen peroxide (21.0g.L-1), bicarbonate (4.0g.L-1), carbonate (4.0g.L-1), chloride (5.0g.L-1), citrate (6.5g.L-1), hydroxide (4.0g.L-1), hypochlorite (0.2g.L-1), starch (5.0g.L-1), sucrose (5.4g.L-1) and water (150g.L-1). In the first step, a one-class model was developed with unadulterated samples, providing 93.1% sensitivity. Four poorly assigned adulterants were discarded for the following step (multi-class modelling). Then, in the second step, a multi-class model, which considered unadulterated and formaldehyde-, hydrogen peroxide-, citrate-, hydroxide- and starch-adulterated samples was implemented, providing 82% correct classifications, 17% inconclusive classifications and 1% misclassifications. The proposed strategy was considered efficient as a screening approach since it would reduce the number of samples subjected to confirmatory analysis, time, costs and errors.