In this study, a prediction model based on Fourier transform mid-infrared spectroscopy was developed for the rapid detection of β-lactoglobulin in milk. The content of β-lactoglobulin in 260 different batches of milk samples was determined as reference by high performance liquid chromatography (HPLC), and the mid-infrared spectra of raw milk were collected using an Fourier transform mid-infrared spectrometer. The effective wavebands were selected, and the background noise was eliminated by Savitsky-Golay (SG) smoothing, first-order derivative or second-order derivative pretreatment before the establishment of the β-lactoglobulin prediction model by using partial least squares regression (PLSR). The results showed that SG five-point smoothing second-order derivative was the optimum preprocessing method. The PLSR model exhibited good prediction accuracy with correlation coefficient (R2) of 0.932 for the calibration set, root mean square error of calibration (RMSEC) of 0.049%, R2 of 0.923 for the calibration set, and root mean square error of prediction (RMSEP) of 0.057%.

An inductively coupled plasma-tandem mass spectrometry (ICP-MS/MS) method was established for the analysis of 26 inorganic elements in dairy products. Under MS/MS conditions, the 26 elements were detected in the no gas, collision gas (He) or reaction gas (H2, O2, NH3/He) mode and the optimal mode was selected for each of the elements. The results showed that calibration curve with good linearity was obtained for each element in the appropriate detection mode with a correlation coefficient greater than 0.999 0. The detection limits of the 26 inorganic elements ranged from 0.000 033 61 to 0.043 71 mg/kg. The spiked recoveries were between 95.50% and 104.21%, with a relative standard deviation (RSD) ≤ 3.94% (n = 11). The contents of Na, Mg, K, Ca, P, Fe and Zn were higher and the contents of the heavy metal elements Cr, As, Cd and Pb were lower in six kinds of dairy products, all of which were lower than the national standard limits. The method was characterized by simple pretreatment, high sensitivity, low limit of detection and high accuracy and could be used for the detection of inorganic elements in dairy products.

Aflatoxins (AFTs) is a group of secondary metabolites produced by Aspergillus flavus and Aspergillus parasiticus, which has stable physicochemical properties. Aflatoxin B1 (AFB1), aflatoxin B2 (AFB2), aflatoxin G1 (AFG1), aflatoxin G2 (AFG2), aflatoxin M1 (AFM1), and aflatoxin M2 (AFM2) are the common analogues of AFT, with AFB1 being the most toxic and widespread one. The International Agency for Research on Cancer (IARC) under the World Health Organization has classified AFB1 as a Group 1 carcinogen. When cows eat contaminated feedstuffs such as peanut, corn, rice, soybean and wheat, some of the AFTs are converted in the body into AFM1, and AFM2, which can exist in milk and dairy products. This paper compares the difference between Chinese and international limits for AFTs in foods, and summarizes the methods for detecting aflatoxin in milk and dairy products such as thin-layer chromatography (TLC), mass spectrometry (MS), spectroscopy, electrochemistry, and rapid test strips. This paper analyzes the advantages and limitations of these methods and predicts future directions in the development of aflatoxin detection technology in milk and dairy products. It is hoped that this review will help in the development of a more convenient, specific, and sensitive detection method for aflatoxin in milk and dairy products.