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Comparison of combination and first overtone spectral regions for near-infrared calibration models for glucose and other biomolecules in aqueous solutions

机译:水溶液中葡萄糖和其他生物分子的近红外校准模型的组合和第一泛音谱区域的比较

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Partial least squares calibration models are compared for the measurement of glucose, lactate, urea, ascorbate, triacetin, and alanine in aqueous solutions from single-beam spectra collected over the first overtone (65005500 cm(-1)) and the combination (5000-4000 cm(-1)) regions of the near-infrared spectrum. Spectra are collected under two sets of conditions with one designed for combination spectra and the other designed for first overtone spectra. As part of the optimization of conditions, an exponential function is presented that accurately characterizes the strong dependency between spectral quality and sample thickness. Sample thickness set for the first overtone and combination spectra are 7.5 and 1.5 mm, respectively. Independent calibration models are established for each solute from both combination and first overtone spectra. Direct comparison reveals superior performance by models generated from combination spectra, particularly for glucose and urea. Standard error of prediction (SEP) values are 1.12 and 0.45 mM for glucose models generated from first overtone and combination spectra, respectively. SEP values for urea are 7.33 and 0.10 mM for first overtone and combination spectra, respectively. Such high SEP values for urea with first overtone spectra correspond to an inability to quantify urea from these spectra because of a lack urea-specific molecular absorption features in this spectral region. Net analyte signal (NAS) is used to quantify the degree of selectivity provided within the first overtone and combination spectral regions. The superior selectivity of combination spectra is confirmed by comparing the length of the NAS vectors for each matrix component.
机译:比较了部分最小二乘校准模型,以从通过第一泛音(65005500 cm(-1))和组合(5000-5000)收集的单束光谱中测量水溶液中的葡萄糖,乳酸,尿素,抗坏血酸,三醋精和丙氨酸。 4000 cm(-1))区域的近红外光谱。光谱是在两组条件下收集的,一组条件用于组合光谱,另一组条件用于第一泛音光谱。作为条件优化的一部分,提出了一个指数函数,该函数精确地表征了光谱质量和样品厚度之间的强相关性。为第一泛音和组合光谱设置的样品厚度分别为7.5和1.5 mm。针对组合和第一泛音谱中的每种溶质建立独立的校准模型。直接比较通过组合光谱生成的模型显示出优异的性能,尤其是对于葡萄糖和尿素而言。对于由第一泛音和组合光谱生成的葡萄糖模型,预测的标准误差(SEP)值分别为1.12和0.45 mM。对于第一泛音谱图和组合谱图,尿素的SEP值分别为7.33和0.10 mM。具有第一泛音光谱的尿素的如此高的SEP值对应于无法从这些光谱中量化尿素,因为在该光谱区域缺乏尿素特异性分子吸收特征。净分析物信号(NAS)用于量化在第一泛音和组合光谱区域内提供的选择性程度。通过比较每个矩阵成分的NAS向量的长度,可以确定组合光谱的优越选择性。

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