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Ultraviolet Spectroscopy Method for Classifying Vinegars

机译:紫叶类紫外光谱法

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摘要

An inexpensive and simple approach using ultraviolet-spectroscopy to distinguish vinegar samples was developed. Vinegar samples were diluted with distilled water(water/vinegar was 6/1, v/v), then distilled with rotary evaporator at 45°C. The distilled liquid was introduced into the UV-Vis 2550 spectrophotometer to scan the UV spectrum from 245 nm to 330 nm, distilled water was used as reference solution. Once spectra were collected, principal components analysis (PCA) and artificial neural network (ANN) were employed for the exploratory analysis and the development of classification models, respectively. The criteria for discrimination were various raw materials and the different fermentation process of vinegars. The correct rate of the classification according to the production process was more than 90% and it was 100% according to the raw materials. The ANN model also could be used to class vinegar samples according to the raw materials, the correct rate was 80.95% in this research.
机译:开发了一种利用紫外光谱来区分醋样品的廉价且简单的方法。用蒸馏水(水/醋为6/1,v / v)稀释醋样品,然后在45℃下用旋转蒸发器蒸馏。将蒸馏液引入UV-Vis 2550分光光度计中以扫描来自245nm至330nm的UV光谱,蒸馏水用作参考溶液。一旦收集光谱,分别用于分别用于探索性分析和分类模型的开发的主成分分析(PCA)和人工神经网络(ANN)。歧视标准是各种原料和醋的不同发酵过程。根据生产过程的正确分类速率超过90%,根据原料100%。 ANN模型也可用于根据原材料的醋样品,在本研究中正确的速率为80.95%。

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