This work proposes the use of bandstop filtering (BSF) as a pretreatment method in the quantitative analysis of glucose from both near‐infrared (NIR) and midinfrared (MIR) spectra. The proposed method is investigated and evaluated against the traditional bandpass filtering (BPF) and implemented with the linear calibration models principal component regression (PCR) and partial least squares regression (PLSR) to predict the glucose from an aqueous mixture consisting of glucose and human serum albumin dissolved in a phosphate buffer solution. The results obtained show that BSF pretreatment achieves better prediction performance than BPF in both the NIR and MIR spectral regions. For detailed analysis, the BPF and BSF were implemented under both the Butterworth and Chebyshev filter configurations in both bands; in the NIR region, the Butterworth BSF combined with the PLSR model provides the best glucose prediction by reducing the root mean square error of prediction (RMSEP) from 100 mg/dL without filtering to 34 mg/dL with a coefficient of determination R2 of .982. In the MIR region, the Chebyshev BSF combined with either PLSR or PCR improves the glucose prediction by reducing the RMSEP by 54% compared with 45% when using BPF and with R2 of.995.

中文翻译：

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近红外和中红外光谱葡萄糖定量分析中的数字带阻滤波

这项工作建议使用带阻滤波 (BSF) 作为一种预处理方法，用于从近红外 (NIR) 和中红外 (MIR) 光谱定量分析葡萄糖。针对传统带通滤波 (BPF) 对所提出的方法进行了研究和评估，并使用线性校准模型主成分回归 (PCR) 和偏最小二乘回归 (PLSR) 实施，以预测由葡萄糖和人血清组成的水性混合物中的葡萄糖白蛋白溶解在磷酸盐缓冲溶液中。获得的结果表明，BSF 预处理在 NIR 和 MIR 光谱区域都实现了比 BPF 更好的预测性能。为进行详细分析，BPF 和 BSF 在两个频段的 Butterworth 和 Chebyshev 滤波器配置下实现；在 NIR 区域，Butterworth BSF 与 PLSR 模型相结合，通过将预测的均方根误差 (RMSEP) 从 100 mg/dL 降低到 34 mg/dL，确定系数 R2 为 0.982，从而提供了最佳的葡萄糖预测。在 MIR 区域，切比雪夫 BSF 与 PLSR 或 PCR 相结合，通过将 RMSEP 降低 54% 提高了葡萄糖预测，而使用 BPF 和 R2 为 0.995 时降低了 45%。