温度对花生油中黄曲霉毒素B1激光诱导荧光检测模型的影响

Influences of temperature on the detection model of aflatoxin B1 in peanut oil by laser induced fluorescence spectrometry

中文关键词:  激光诱导荧光  花生油  黄曲霉毒素B1(AFB1)  温度  全局判别模型

英文关键词:laser induced fluorescence  peanut oil  aflatoxin B1  temperature  global discriminant model

中文摘要:

      目的 利用激光诱导的方式产生荧光检测花生油中的黄曲霉毒素B1 (aflatoxin B1, AFB1), 并探究温度对检测结果的影响。方法 通过采集10、20、30、40、50 ℃下污染AFB1花生油的光谱信息, 建立线性判别(linear discriminant analysis, LDA)模型对其进行定性分析, 建立偏最小二乘回归模型进行定量分析。结果 单温度LDA模型在预测该温度下样本正确率在84%以上, 全局LDA模型比单温度LDA模型预测结果的正确率低, 使用偏最小二乘回归(partial least squares regression, PLSR)模型在单温度和混合温度下均不能实现定量预测。对单一品种花生油建立PLSR定量模型的结果表明在20 ℃条件下模型表现最稳定, 样品预测结果最好。结论 本研究提出在定性判别分析时可建立全局模型以适应温度对检测过程的影响, 在定量分析时单温度模型比全局模型更能实现精准预测。

英文摘要:

      Objective To detect aflatoxin B1 (AFB1) in peanut oil by laser induced fluorescence and explore the effects of temperature on the detection results. Methods The spectral information of AFB1 contaminated peanut oil at temperatures of 10, 20, 30, 40 and 50 ℃ was collected, linear discriminant analysis (LDA) model was established for qualitative analysis, and partial least squares regression model was established for quantitative analysis. Results The accuracy of the single-temperature LDA detection model in predicting samples at this single temperature exceeded 84%. The global LDA model was lower prediction accuracy than the single-temperature LDA model. The partial least squares regression (PLSR) model could not achieve quantitative prediction at either single temperature or mixed temperature. The PLSR quantitative model developed for single-variety peanut oil demonstrated optimal stability at 20 °C, yielding the most accurate sample predictions. Conclusion This study proposes that a global model can be established during qualitative discriminant analysis to adapt to the impact of temperature on the detection process. In quantitative analysis, the single temperature model can achieve more accurate predictions than the global model.