ABSTRACT Two simple fingerprinting methods, flow-injection coupled to ultraviolet spectroscopy and proton nuclear magnetic resonance, were used for discriminating between Aurantii fructus immaturus and Fructus poniciri trifoliatae immaturus. Both methods were combined with partial least-squares discriminant analysis. In the flow-injection method, four data representations were evaluated: total ultraviolet absorbance chromatograms, averaged ultraviolet spectra, absorbance at 193, 205, 225, and 283 nm, and absorbance at 225 and 283 nm. Prediction rates of 100% were achieved for all data representations by partial least-squares discriminant analysis using leave-one-sample-out cross-validation. The prediction rate for the proton nuclear magnetic resonance data by partial least-squares discriminant analysis with leave-one-sample-out cross-validation was also 100%. A new validation set of data was collected by flow-injection with ultraviolet spectroscopic detection two weeks later and predicted by partial least-squares discriminant analysis models constructed by the initial data representations with no parameter changes. The classification rates were 95% with the total ultraviolet absorbance chromatograms datasets and 100% with the other three datasets. Flow-injection with ultraviolet detection and proton nuclear magnetic resonance are simple, high throughput, and low-cost methods for discrimination studies.

中文翻译：

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通过流动注射紫外光谱检测和质子核磁共振使用偏最小二乘判别分析区分枳实和枳实

摘要 两种简单的指纹识别方法，流动注射耦合紫外光谱法和质子核磁共振，被用于鉴别枳壳和三叶枳壳。这两种方法都与偏最小二乘判别分析相结合。在流动注射法中，评估了四种数据表示：总紫外吸收色谱图、平均紫外光谱、193、205、225 和 283 nm 处的吸光度，以及 225 和 283 nm 处的吸光度。通过使用留一样本交叉验证的偏最小二乘判别分析，所有数据表示的预测率都达到了 100%。通过偏最小二乘判别分析和留一样本交叉验证对质子核磁共振数据的预测率为100%。两周后通过流动注射和紫外光谱检测收集了一组新的验证数据，并通过由初始数据表示构建的偏最小二乘判别分析模型预测，没有参数变化。总紫外吸收色谱数据集的分类率为 95%，其他三个数据集的分类率为 100%。带有紫外线检测和质子核磁共振的流动注射是用于鉴别研究的简单、高通量和低成本的方法。两周后通过流动注射和紫外光谱检测收集了一组新的验证数据，并通过由初始数据表示构建的偏最小二乘判别分析模型预测，没有参数变化。总紫外吸收色谱数据集的分类率为 95%，其他三个数据集的分类率为 100%。带有紫外线检测和质子核磁共振的流动注射是用于鉴别研究的简单、高通量和低成本的方法。两周后通过流动注射和紫外光谱检测收集了一组新的验证数据，并通过由初始数据表示构建的偏最小二乘判别分析模型预测，没有参数变化。总紫外吸收色谱数据集的分类率为 95%，其他三个数据集的分类率为 100%。带有紫外线检测和质子核磁共振的流动注射是用于鉴别研究的简单、高通量和低成本的方法。