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首页> 外文期刊>Macedonian Journal of Chemistry and Chemical Engineering >Simultaneous determination of acesulfame-K, aspartame and stevioside in sweetener blends by ultraviolet spectroscopy with variable selection by sipls algorithm
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Simultaneous determination of acesulfame-K, aspartame and stevioside in sweetener blends by ultraviolet spectroscopy with variable selection by sipls algorithm

机译:紫外光谱法同时测定糖精中乙酰磺胺酸钾,阿斯巴甜和甜菊糖的含量

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摘要

A chemometric-assisted UV absorption spectroscopic method is proposed for the simultaneous determination of acesulfame-K, aspartame and stevioside in raw powder mixtures of commercial sweeteners. The synergy interval partial least squares (siPLS) algorithm was applied to select the optimum spectral range and their combinations. The utilization of spectral region selection aims to construct better partial least squares (PLS) model than that established from the full-spectrum range. The results show that the siPLS algorithm can find out an optimized combination of spectral regions, yielding lower relative standard error of prediction (RSEP) and root mean square error of prediction (RMSEP), as well as simplifying the model. The RMSEP and RSEP obtained after selection of intervals by siPLS were 0.1330 μg·ml –1 and 1.50 % for acesulfame-K, 0.2540 μg·ml –1 and 1.64 % for aspartame, 1.4041 μg·ml –1 and 2.03 % for stevioside respectively. The recovery values range from 98.12 % to 101.88 % for acesulfame-K, 98.63 % to 102.96% for aspartame, and 96.38 % to 104.04 % for stevioside respectively.
机译:提出了一种化学计量紫外吸收光谱法,用于同时测定市售甜味剂原料粉末混合物中的乙酰磺胺酸钾,阿斯巴甜和甜菊糖苷。应用协同区间偏最小二乘(siPLS)算法选择最佳光谱范围及其组合。频谱区域选择的利用旨在构建比从全光谱范围建立的模型更好的偏最小二乘(PLS)模型。结果表明,siPLS算法可以找到光谱区域的最佳组合,从而产生较低的相对预测标准误差(RSEP)和均方根预测误差(RMSEP),并简化了模型。通过siPLS选择间隔后得到的RMSEP和RSEP:乙酰磺胺酸钾为0.1330μg·ml –1和1.50%,阿斯巴甜为0.2540μg·ml –1和1.64%,甜菊糖苷为1.4041μg·ml –1和2.03% 。乙酰磺胺酸钾的回收率分别为98.12%至101.88%,阿斯巴甜的回收率为98.63%至102.96%,甜菊糖的回收率为96.38%至104.04%。

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