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| Optimization of pretreatment conditions for determination of No. 6 solvent residual in vegetable oil by ultrasound-headspace gas chromatography based on response surface methodology and genetic algorithm-artificial neural network |
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| DOI：10.12166/j.zgyz.1003-7969/2020.02.026 |
| KeyWord:ultrasound No.6 solvent response surface methodology neural network vegetable oil solvent residual |
| FundProject:湖南省食品药品监督管理局食品药品安全科技项目（湘食药科 R201701） |
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| Abstract: |
| A new method for the determination of No.6 solvent residual in vegetable oil by ultrasound-headspace gas chromatography (UV-HGC) was established.The effects of ultrasonic power, ultrasonic time and ultrasonic temperature on the determination of No.6 solvent residual in vegetable oil were investigated by single factor experiment. Subsequently, the conditions of UV-HGC were optimized using response surface methodology (RSM) and genetic algorithm-artificial neural network (GA-ANN). The results indicated that the GA-ANN showed better prediction and optimization abilities than RSM with lower relative error value (5.95% versus 915%) and higher determination coefficient (R2) (0.949 5 versus 0.891 4).The optimal pretreatment conditions of UV-HGC were obtained by GA-ANN as follows:ultrasonic power 500 W, ultrasonic time 7 min and ultrasonic temperature 50 ℃.Under the optimal conditions, the No.6 solvent in vegetable oils showed good linear relationships in the range of 9.53-200 mg/kg mass concentration with the correlation coefficients 0.999 4. The average recoveries were 95.5%, 98.6% and 100.4% at low, medium and high standard addition levels respectively, and the relative standard deviation (RSD) was less than 3.5%.The limits of detection (LOD) and quantification (LOQ) of the method were 1.85 mg/kg and 9.53 mg/kg.The method was simple, rapid, sensitive and accurate, and it was suitable for the determination of No.6 solvents residual in vegetable oil. |
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