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An automatic chemiluminescence magnetic enzyme immunoassay based on the high specificity of antigen and antibody was developed for rapid and quantitative determination of lead in grain. By optimizing the pre-treatment conditions and the reaction conditions of chemiluminescence magnetic enzyme immunoassay, the automatic determination of lead in rice, wheat and corn samples was realized. The detection range was 0.05~0.71 mg/kg, and the limit of detection was 0.02 mg/kg in rice and corn and 0.01 mg/kg in wheat. The recovery range was 89.2%~113.6%, and the relative standard deviations were all less than 10%. Based on the chemiluminescence immune platform, the developed method can realize eight samples simultaneous auto-detection within 30 min. Meanwhile, the automatic detection method can avoid human errors, and greatly improve the accuracy and efficiency, showing a good application prospect in the rapid quantitative detection of lead in grain.

Grain and oil matrix reference materials are commonly used in the evaluation of analysis methods, capability verification, and quality control of laboratory analysis and testing processes, due to the consistent composition with actual samples. They play irreplaceable roles in ensuring the accuracy and reliability of test results and are important “measuring instruments” in the field of analysis. In recent years, the domestic and international development status, types, and typical applications of reference materials for grain and oil matrices were reviewed in this paper. Based on the analysis of the main problems existing in this field，the demand and trend of the RMs for grain and oil matrices were prospected，which can provide more meaningful reference for the future research on grain and oil RMs.

Sample representativeness is the premise to ensure the authenticity and accuracy of test results. The application scenario of unmanned detection is taken as the research object. Through the research on the uniformity of major heavy metals content detection in the sample processing of unmanned sample sampler, it is clear that mixing operation and sampling control are the necessary steps to ensure the representativeness of samples. By the method of combining dyeing simulation and actual sample verification, the key parameters such as the blending operation mode and parameters, the amount of samples crushed and tested for automatic sampling were systematically studied, and an optimal blending sampling scheme was obtained to ensure the representativeness of samples for unmanned heavy metal testing. The results showed that, the anchor type mountain paddle was used to stir 100 laps in revolution mode or repeat mix and separate samples for 3 times, and the minimum sample sampling amount for crushing was 150 g. The maximum crushed particle size of the sample was 1 mm and the minimum weight was 0.5g. This scheme was suitable for the representative detection of lead and cadmium elements in rice and wheat samples less than 6 kg. The research results provide technical supports for ensuring the representativeness and accuracy of heavy metal detection results in grain.

Food safety problems caused by excessive metals have potential health hazards related to people’s heath. The development of rapid detection technology for heavy metals in food is an effective means to prevent food with excessive heavy metals from entering the market. However, the accuracy and stability of the rapid detection of heavy metals in food is difficult to be guaranteed due to the low limit of the target element and the interference of sample matrix after pretreatment. Adsorption materials could have good accumulation on heavy metals, and are effective to remove the matrix of food, which provides technical support for the realization of rapid detection of heavy metals in food. Based on the analysis and summary of the current research on the application of adsorption materials for detecting heavy metals in food, the advantages and disadvantages of adsorption materials including absorbability and limit of detection were discussed, and the development trend in the future was also prospected.

The objection was to evaluate the applicability of an automated method for aflatoxins analysis by using Immunoaffinity Magnetic Bead - UPLC. The results showed that the average recovery of the mmunoaffinity Magnetic Bead was above 95%, and the relative standard deviation was less than 3.3%. The results of the quality control samples were within the range of the reference uncertainty. The method was accurate and reliable.T testing (sig. (bilateral) = 0.533) proved that there was no significant difference between two independent purification instruments.62 researchers evaluated two methods of purifications with immunomagnetic beads and immunoaffinity column. T testing has proved that the results of the two methods were no significant difference.However, the dispersion degree of the immunomagnetic bead automated processing method was smaller than that of the immunoaffinity column method. Moreover, the z-value of all the test were less than 2 (| Z | ≤2). Hence, this method can detect cereals and oils. In addition, the method is environmentally friendly, simply, and lower-cost, which greatly improved detection efficiency and level.

A new pretreatment method for the determination of cadmium in grain was developed: citric acid extraction method. The basic parameters affecting the citric acid extraction were optimized, and the best pretreatment conditions were obtained. The accuracy of the method was investigated by using certified reference materials and reference materials. The citric acid was fixed in 10 mL centrifuge tube, which provided technical support for the application of this method. After optimization, only citric acid and water are needed to determinate the cadmium in grains. The detected results of certified reference materials and reference materials were all within the assigned values. The RSD of 7 independent tests was less than 5%. The method has good precision and accuracy. The detection limit and quantitative limit of the method are 0.039 ng/mL and 0.129 ng/mL, respectively which can meet the requirements of cadmium detection in grains. The whole pretreatment process can complete in 15 minutes, which is safe, green, simple and easy to operate.

The uncertainty of GC method in the determination of fatty acids in peanut oil was evaluated based on Monte Carlo method (MCM). The results show thatthe uncertainty of C16:0 is 10.78%±0.23%, C18:0 is 3.52%±0.08%, C18:1n9c is 45.75%±0.58%, C18:2n6c is 32.10%±0.52%, C22:0 is2.84±0.07%. The MCM method avoids the complicated measurement deduction such as partial derivative of measurement model and the process of type A and type B evaluation when used to evaluate the measurement uncertainty. The uncertainty of measurement of 21 fatty acid components in peanut oil can be easily and quickly calculated by MCM software.This method provides technical support for improving the evaluation ability of laboratory uncertainty.