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| 基于近红外光谱技术的沙棘籽油鉴伪方法研究 |
| Discerning of seabuckthorn seed oil by near-infrared spectroscopy |
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| DOI： |
| 中文关键词: 沙棘籽油 真伪鉴别 近红外透反射光谱 簇类独立软模式 偏最小二乘判别 支持向量机 |
| 英文关键词:seabuckthorn seed oil discernment near-infrared transflectance spectroscopy soft independent modeling of class analogy partial least squares discriminant analysis support vector machine |
| 基金项目: |
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| 中文摘要: |
| 针对市场上沙棘籽油质量参差不齐的情况，结合近红外光谱技术研究沙棘籽油快速鉴伪的方法。采用234份沙棘籽油、其他植物油、掺假沙棘籽油的近红外透反射光谱，结合簇类独立软模式法（SIMCA）、偏最小二乘判别法（PLS-DA）、支持向量机法（SVM）3种化学计量学方法，在4 000～6 000 cm-1波段范围内分别建立这3类油的判别模型，并用117份独立样品对模型进行验证。结果表明：3种建模方法均得到了满意的结果，其中SVM在训练和验证过程中均得到100%的正确率，判别效果最好；近红外光谱技术应用于识别纯沙棘籽油和区分沙棘籽油掺假类别具有实用性，近红外光谱技术应用于沙棘籽油鉴伪是可行的。 |
| 英文摘要: |
| Aiming at the quality problems of seabuckthorn seed oil on market, the method was developed for rapid discerning of seabuckthorn seed oil by near-infrared spectroscopy. The transflectance spectra between 4 000 cm-1 and 6 000 cm-1 of two hundreds and thirty-four samples were collected including pure seabuckthorn seed oils, other vegetable oils and adulterated seabuckthorn seed oils. The chemometrics methods of soft independent modeling of class analogy(SIMCA), partial least squares discriminant analysis(PLS-DA) and support vector machine(SVM) were adopted to estabish discrimination models of the mentioned three types of oils respectively. And one hundred and seventeen independent samples were prepared for model validation. Satisfactory results were obtained by the three chemometrics methods. The discrimination accuracy of SVM was the best, reaching 100% for calibration and independent validation. The applications of near-infrared spectroscopy technology in discerning pure seabuckthorn seed oil and adulteration type were practical. It was feasible to discern seabuckthorn seed oil rapidly by near-infrared spectroscopy. |
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