Abstract A new methodology using differential pulse voltammetry and artificial neural network (ANN) for simultaneous determination of butylated hydroxyanisole (BHA), butylated hydroxytoluene (BHT), propyl gallate (PG) and tert-butylhydroquinone (TBHQ) in biodiesel samples is proposed. A platinum ultramicroelectrode (ume) was used as working electrode and measures were taken directly in biodiesel:ethanol medium without previous preparation. On this condition, detection limits for the antioxidants separately are 20.5, 32.4, 35.5 and 26.5 mg L−1 for BHA, BHT, PG and TBHQ, respectively. The artificial neural network model allowed the quantification of the individual concentrations overcoming the strongly overlapped voltammograms obtained for the mixture of the four antioxidants. For the model construction, a variable selection step through decision trees (DT) led to a reduction of prediction errors by 17.5%. The optimized DT-ANN model presented high correlation (0.97474, 0.99995, 0.98246 and 0.98928 for BHA, BHT, PG and TBHQ, respectively) between real and predicted values. Recovery percentages found were between 82.6% and 106.7%, except for two samples whose values were 76.0% and 114.7%. From the accuracy found between nominal and estimated concentration, it is inferred that the proposed methodology is a good alternative to quantify phenolic antioxidants in biodiesel samples.

中文翻译：

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人工神经网络辅助差分脉冲伏安法和决策树变量选择直接和同时测定生物柴油中的四种酚类抗氧化剂

摘要 提出了一种利用差分脉冲伏安法和人工神经网络 (ANN) 同时测定生物柴油样品中丁基羟基茴香醚 (BHA)、丁基羟基甲苯 (BHT)、没食子酸丙酯 (PG) 和叔丁基氢醌 (TBHQ) 的新方法。铂超微电极（ume）用作工作电极，直接在生物柴油：乙醇介质中进行测量，无需事先准备。在此条件下，BHA、BHT、PG 和 TBHQ 的抗氧化剂检测限分别为 20.5、32.4、35.5 和 26.5 mg L-1。人工神经网络模型允许对单个浓度进行量化，克服了为四种抗氧化剂的混合物获得的强烈重叠伏安图。对于模型构建，通过决策树 (DT) 进行的变量选择步骤使预测误差减少了 17.5%。优化后的 DT-ANN 模型在实际值和预测值之间呈现出高相关性（BHA、BHT、PG 和 TBHQ 分别为 0.97474、0.99995、0.98246 和 0.98928）。发现的回收率介于 82.6% 和 106.7% 之间，但两个样品的值分别为 76.0% 和 114.7%。根据标称浓度和估计浓度之间的准确性，可以推断出所提出的方法是量化生物柴油样品中酚类抗氧化剂的良好替代方法。6% 和 106.7%，除了两个样本的值分别为 76.0% 和 114.7%。根据标称浓度和估计浓度之间的准确性，可以推断出所提出的方法是量化生物柴油样品中酚类抗氧化剂的良好替代方法。6% 和 106.7%，除了两个样本的值分别为 76.0% 和 114.7%。根据标称浓度和估计浓度之间的准确性，可以推断出所提出的方法是量化生物柴油样品中酚类抗氧化剂的良好替代方法。