Abstract Shortwave handheld NIR spectroscopy coupled with multivariate algorithm was attempted to simultaneously classify and measure Sudan IV dye adulteration in palm oil samples. K-nearest neighbour (KNN) was used to develop a classification model to discriminate between authentic palm oil samples and Sudan IV dye adulterated (0.10 - 0.002 % w/w) ones. Principal component regression (PCR), partial least square regression (PLSR) and support vector machine regression (SVMR) algorithms were comparatively employed to quantify the addition of Sudan IV dye in authentic palm oil samples. The models were evaluated by the classification rate (R), correlation co-efficient in the calibration set/prediction set (Rp2/Rc2), and root mean square error of calibration/prediction (RMSEC/P). The developed multiplicative scatter correction plus KNN technique was found to accurately classify where R = 95.48 % and 97.00 % in the calibration set and prediction set respectively. Among the quantification model developed for measuring Sudan IV dye, standard normal variant preprocessing plus partial least square regression (SNV-PLSR) gave the best performance at Rc2 = 0.91, Rp2 = 0.90 and RMSEC = 0.0841, RMSEP = 0.0868 while standard normal variant preprocessing plus principal component regression gave Rc2 = 0.90, Rp2 = 0.90 and RMSEC = 0.0846, RMSEP = 0.870. The findings have proved that, the integrity of palm oil samples can be certified rapidly and nondestructively in terms of the presence of Sudan IV by using short wave handheld NIR spectroscopy. This offers the opportunity for incorporating NIR spectroscopy into mobile phone devices to enhance mobile detection.

中文翻译：

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使用短波手持光谱和模型比较分析预测棕榈油掺入苏丹 IV 染料

摘要 短波手持式近红外光谱结合多元算法试图同时对棕榈油样品中的苏丹IV染料掺假进行分类和测量。K-最近邻 (KNN) 用于开发分类模型，以区分真正的棕榈油样品和掺假苏丹 IV 染料（0.10 - 0.002 % w/w）的样品。主要成分回归 (PCR)、偏最小二乘回归 (PLSR) 和支持向量机回归 (SVMR) 算法被比较用于量化真实棕榈油样品中苏丹 IV 染料的添加。模型通过分类率 (R)、校准集/预测集的相关系数 (Rp2/Rc2) 和校准/预测的均方根误差 (RMSEC/P) 进行评估。发现开发的乘法散射校正加 KNN 技术可以准确地对校准集和预测集中的 R = 95.48 % 和 97.00 % 进行分类。在用于测量苏丹 IV 染料的量化模型中，标准正常变异预处理加偏最小二乘回归 (SNV-PLSR) 在 Rc2 = 0.91、Rp2 = 0.90 和 RMSEC = 0.0841、RMSEP = 0.0868 时表现最佳，而标准正常变异预处理加上主成分回归得出 Rc2 = 0.90、Rp2 = 0.90 和 RMSEC = 0.0846、RMSEP = 0.870。研究结果证明，使用短波手持式 NIR 光谱可以快速、无损地验证棕榈油样品的完整性，即苏丹 IV 的存在。