Botelho Bruno G, Reis Nádia, Oliveira Leandro S, Sena Marcelo M
Departamento de Química, ICEx, Universidade Federal de Minas Gerais, 31270-901 Belo Horizonte, MG, Brazil.
Faculdade de Farmácia, Universidade Federal de Minas Gerais, 31270-901 Belo Horizonte, MG, Brazil.
Food Chem. 2015 Aug 15;181:31-7. doi: 10.1016/j.foodchem.2015.02.077. Epub 2015 Feb 20.
This paper proposed a new screening method for the simultaneous detection of five common adulterants in raw cow milk by using attenuated total reflectance (ATR) mid infrared spectroscopy and multivariate supervised classification (partial least squares discrimination analysis - PLSDA). The method was able to detect the presence of the adulterants water, starch, sodium citrate, formaldehyde and sucrose in milk samples containing from one up to five of these analytes, in the range of 0.5-10% w/v. A multivariate qualitative validation was performed, estimating specific figures of merit, such as false positive and false negative rates, selectivity, specificity and efficiency rates, accordance and concordance. The proposed method does not need any sample pretreatment, requires a small amount of sample (30 μL), is fast and simple, being suitable for the control of raw milk in a dairy industry or for the quality inspection of commercialized milk.
本文提出了一种利用衰减全反射(ATR)中红外光谱和多元监督分类(偏最小二乘判别分析 - PLSDA)同时检测生牛奶中五种常见掺假物的新筛选方法。该方法能够在含有上述一种至五种分析物的牛奶样品中,检测出浓度范围为0.5 - 10% w/v的掺假物水、淀粉、柠檬酸钠、甲醛和蔗糖。进行了多变量定性验证,估算了诸如假阳性和假阴性率、选择性、特异性和效率率、一致性和协调性等特定的品质因数。所提出的方法无需任何样品预处理,所需样品量少(30 μL),快速简便,适用于乳制品行业中生牛奶的检测或商业化牛奶的质量检验。