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電子鼻發(fā)表文章-多元統(tǒng)計分析結合電子鼻和電子舌試驗簡化了中國種植...
閱讀：1052 發(fā)布時間：2020-3-10| 提 供 商 | 上海瑞玢智能科技有限公司 | 資料大小 | 2.2MB |
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該文章用iNose電子鼻進行實驗，開展了如下實驗。
【摘要】本研究旨在開發(fā)一種基于電子鼻和電子舌試驗及其組合的快速簡便的方法來追蹤在中國種植的黑果枸杞（LRM）的地理來源，收獲年份和品種。應用主成分分析（PCA）和線性判別分析（LDA）進行定性分類和定量預測。結果表明：電子鼻和電子舌的測定及其組合未能識別LRM的收獲年份和種類，但是在追蹤LRM地理來源方面取得了可靠的結果，總分類能力分別為86.4％，86.8％和92.6％。除此之外，與儀器分析或傳統(tǒng)方法如化學分析方法和感官評估相比，分析程序需要更短的時間和更少的化學試劑。這項研究表明，多變量統(tǒng)計分析結合電子鼻和電子舌測定可能是一個可靠簡便的追蹤LRM地理起源的方法。
【關鍵詞】電子鼻；氣味指紋分析系統(tǒng)；氣體分析儀；質構儀；電子舌；氣味分析儀；離子遷移譜；生物芯片；3D打印機；肉嫩度儀；物性測試儀；凝膠強度測定儀；微量過濾系統(tǒng)
【ABSTRACT】：This study aims to develop a fast and simple method to trace the geographical origins, harvest years and varieties of Lycium ruthenicum Murray (LRM) grown in China by employing e-nose and e-tongue assays and their combination.
Principal component analysis (PCA) and linear discriminant analysis (LDA) were applied for qualitative classification and quantitative prediction. The results showed that e-nose and e-tongue assays and their combination failed to recognize harvest years and varieties of LRM, but achieved reliable results for tracing LRM geographical origins with a total classification ability of 86.4%, 86.8% and 92.6% respectively. In addition, the analysis procedure required shorter time and less chemical reagents as compared to high-end instrumental analysis or traditional methods like chemical analytical methods and sensory evaluation. This study demonstrated that the m*riate statistical analysis combined with e-nose and e-tongue assays could be a reliable and simplified method of tracing the geographical origins of LRM。