光谱学与光谱分析, 2016, 36 (4): 967, 网络出版: 2016-12-20  

近红外光谱结合非负回归系数回归法(配方回归)解析混合样品的组成比例

Study on the Analysis of the Proportion of Mixed Samples with Near Infrared Spectroscopy and Non-Negative Coefficients Regression
作者单位
1 中国农业大学信息与电气工程学院, 北京 100083
2 上海烟草集团有限责任公司, 上海 200082
3 中国农业大学理学院, 北京 100083
摘要
准确、 快速解析混合样品的组成比例对食品、 农产品加工过程的质量控制和配方设计具有重要作用。 传统的解决方法多是利用大量代表性样品建立统计模型来实现, 耗时耗力。 以醇类及酸类液体混合样品及其低浓度溶液混合样品(无近红外特征吸收的四氯化碳(CCl4)为溶剂介质)的透射光谱, 以及片状烟叶样品漫反射光谱为例, 采用导数和S.G.平滑, 结合非负回归系数回归法(配方回归)验证了在一定条件下解析混合样品组成比例的可行性。 结果表明, 对醇酸类液体透射光谱, 根据非负回归系数回归法得到的解析比例更接近于醇酸类液体的实际摩尔比例, 与实际摩尔比例的误差在8%以内, 其低浓度溶液的解析效果更优, 与实际摩尔比例的误差在4%以内; 对片状烟叶的漫反射光谱, 根据非负回归系数回归法得到的解析比例与实际质量比例的误差在10%以内; 同时, 混合样品的实际光谱与理论解析光谱之间均具有高度一致性, F和t检验的结果均在0.01水平上, 无显著性差异, 从理论上分析了解析比例的可靠性。 该方法只需已知几种纯样品的光谱数据, 即可解析出混合样品的纯样品组成比例, 具有较好应用前景。
Abstract
In the process of practical production, it is important to accurately analyze the proportion of mixed samples with high speed, which plays a great role for quality control and formulation design in food and agricultural processing. Traditional solution is to build statistical model with a large number of representative samples, which is both labor-intensive and time-consuming. In this paper, the proportion of alcohol and acids mixed samples, and their dilute solution mixed samples(used carbon tetrachloride (CCl4) which has no near-infrared absorption characteristics as the solvent medium), as well as sheet tobacco leaf mixed samples are respectively analyzed by using near infrared spectroscopy, SG smooth and non-negative coefficients regression, which verifies the feasibility of analyzing the proportion of the mixed samples. The results show that, the analytic proportion of transmission spectra of alcohol and acids according to non-negative coefficients regression is closer to actual molar proportion with result error less than 4%. The result of the dilute solution is much better with error less than 4%. The analytic proportion of diffuse reflectance spectra of sheet tobacco leaf according to non-negative coefficients regression is highly accurate with error less than 10%. In the meantime, it has a highly consistency between actual spectra and analytic spectra of mixed samples; and the result of F-test and T-test shows that there is no significant difference between them and the confidence level is 0.01. It has the reliability of analytical proportion in theory. With the spectral data of several pure samples, the proportion of mixed samples can be thus analyzed, which has a good application prospect for quality control and formulation design in food and agricultural processing.

李雪莹, 束茹欣, 栾丽丽, 李凯, 杨凯, 李军会, 赵龙莲, 张晔晖, 张录达. 近红外光谱结合非负回归系数回归法(配方回归)解析混合样品的组成比例[J]. 光谱学与光谱分析, 2016, 36(4): 967. LI Xue-ying, SHU Ru-xin, LUAN Li-li, LI Kai, YANG Kai, LI Jun-hui, ZHAO Long-lian, ZHANG Ye-hui, ZHANG Lu-da. Study on the Analysis of the Proportion of Mixed Samples with Near Infrared Spectroscopy and Non-Negative Coefficients Regression[J]. Spectroscopy and Spectral Analysis, 2016, 36(4): 967.

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