排序方式： 共有15条查询结果，搜索用时 15 毫秒
1.
为实现不同产地地枫皮快速鉴别并筛选出高药效成分的种质,利用红外光谱结合主成分分析模型和簇类独立软模式法（SIMCA）对不同产地地枫皮药材进行检测,同时在主成分分析模型中提取载荷因子对其进行分析。结果显示:1）各产地红外光谱经过SNV标准归一化后,主成分分析模型中前3个主成分能够分析出代表87%的样品变量信息,样本在主成分空间中聚集成为7个不同的类别。2）SIMCA模型能成功地对不同产地未知地枫皮样本进行预测且判断准确率均达100%。3）载荷因子分析表明,A、B及E产地样本地枫皮素、厚朴醇及芳香类化合物的含量比其他产地高,不同产地样品中芳香类物质差异主要体现在槲皮素含量的不同。 相似文献
2.
《北京林业大学学报》2012,34(3)
为实现不同产地地枫皮快速鉴别并筛选出高药效成分的种质,利用红外光谱结合主成分分析模型和簇类独立软模式法（SIMCA）对不同产地地枫皮药材进行检测,同时在主成分分析模型中提取载荷因子对其进行分析。结果显示：1）各产地红外光谱经过SNV标准归一化后,主成分分析模型中前3个主成分能够分析出代表87％的样品变量信息,样本在主成分空间中聚集成为7个不同的类别。2）SIMCA模型能成功地对不同产地未知地枫皮样本进行预测且判断准确率均达100％。3）载荷因子分析表明,A、B及E产地样本地枫皮素、厚朴醇及芳香类化合物的含量比其他产地高,不同产地样品中芳香类物质差异主要体现在槲皮素含量的不同。 相似文献
3.
基于可见/近红外光谱与SIMCA和PLS-DA的脐橙品种识别 总被引：2，自引：7，他引：2
脐橙的优良品种选育是通过芽变选种获得,为了选择一些具有特殊性状的脐橙芽变进行培植,需要对脐橙的品种进行鉴别。该研究应用可见/近红外光谱分析方法结合软独立模式分类（SIMCA）和偏最小二乘判别分析（PLS-DA）模式识别方法对赣南脐橙的品种进行识别。研究结果表明,采用原始近红外光谱结合SIMCA方法,实现了纽贺尔、奈弗宁娜、华脐以及朋娜4种脐橙的100%的识别;应用近红外光谱结合PLS-DA方法对校正样本建立判别模型,其校正及验证结果与实际分类变量的相关系数均大于0.970,交叉验证均方根误差（RMSECV）和预测均方根误差（RMSEP）都小于0.100,利用模型对验证集中纽贺尔、奈弗宁娜、华脐以及朋娜4种脐橙的识别率均为100%。为脐橙优良品种的选育提供快速鉴别分析方法。 相似文献
4.
利用傅里叶变换红外光谱法（FTIR）结合软独立模式分类法（SIMCA）对不同类别的牛奶进行识别。通过对光谱数据基线校正和Savitzky-Golay平滑处理后,在3100～850cm-1光谱区域,利用留一交互验证法建立获得主成分分析（PCA）最优模型。在α=5%显著水平下,最优模型对纯牛奶、低乳糖奶、低脂奶和高蛋白奶的识别率分别为80%、80%、100%和80%,拒绝率分别为93%、100%、100%和93%。表明FTIR结合SIMCA可成为快速识别牛奶类别的有效方法。 相似文献
5.
利用近红外光谱结合SIMCA模式识别法来检测马尾松木材单板节子.结果表明,通过培训集样本建立的基于主成分分析的SIMCA判别模型对有无节子两种类型样本进行回判和对未知节子类型的样本(包括无节子和有节子样本)的判别正确率均达到90％～100％,说明应用近红外光谱结合SIMCA模式识别法可以快速有效地检测木材表面的节子缺陷. 相似文献
6.
以垦粳5号、垦粳6号、垦粳9号和鸿育001-1共4个水稻品种为研究对象,采用近红外光谱技术分别结合SIMCA和偏最小二乘法判别分析法（PLS-DA）对4个水稻品种进行鉴别。采用SIMCA分类法,实现了4个水稻品种100%的区分;采用PLS-DA方法对校正样本建立判别模型,其校正集结果和参考值之间的相关系数最小值为0.95,验证集结果与参考值之间的相关系数最小值为0.94,对验证集中4个水稻品种的识别率为100%。试验结果表明,应用近红外光谱技术结合SIMCA分类法和PLS-DA法均可实现对水稻品种的快速鉴别。 相似文献
7.
模拟了几种常用饲料原料在卧式混合机中的混合过程,通过美国ASD公司的QualitySpec5070近红外光谱仪全程采集了样本的近红外光谱数据,对样本数据进行了适当的预处理与波段选择,并建立了3种不同的有监督定性分析模型来判别饲料混合均匀状态。结果表明,模型的预测准确率均大于85%,为快速、准确、稳定地检测饲料混合均匀度提供了新的途径。 相似文献
8.
为探明电子舌对调味料酒生产工艺的判别能力和理化指标的预测能力,本研究采用电子舌和理化检测手段,结合不同统计方法,对54份料酒样品分别建立定性和定量分析模型。结果表明,应用主成分分析(PCA)可以区分不同生产工艺的料酒样品,第一主成分为鲜味,贡献率62.4%,第二主成分为酸味,贡献率33.2%;应用簇类独立软模式法(SIMCA)可以准确判别酿造料酒和配制料酒,各传感器区分能力(DP)>5,识别率达到100%;应用偏最小二乘法(PLS)将传感器信号与行标方法检测结果进行拟合,总酸、氨基酸态氮和食盐的验证集标准偏差与预测标准偏差的比值(RPD)分别为12.1、6.5和14.1,建立的模型效果良好,可进行准确的定标和预测;酒精度RPD值为2.7,也可进行定量分析,但模型稳定性较弱。本研究结果为应用电子舌对调味料酒进行品质区分和检测提供了理论和实践基础。 相似文献
9.
This study deals with the suitable discriminant techniques of wood-based materials by means of near-infrared spectroscopy
(NIRS) and several chemometric analyses. The concept of Mahalanobis' generalized distance, K nearest neighbors (KNN), and
soft independent modeling of class analogy (SIMCA) were evaluated to determine the best analytical procedure. The difference
in the accuracy of classification with the spectrophotometer, the wavelength range as the explanatory variables, and the light-exposure
condition of the sample were examined in detail. It was difficult to apply Mahalanobis' generalized distances to the classification
of wood-based materials where NIR spectra varied widely within the sample category. The performance of KNN in the NIR region
(800–2500 nm), for which the device used in the laboratory was employed, exhibited a high rate of correct answers of validation
(>98%) independent of the light-exposure conditions of the sample. When employing the device used in the field, both KNN and
SIMCA revealed correct answers of validation (>88%) at wavelengths of 550–1010 nm. These results suggest the applicability
of NIRS to a reasonable classification of used wood at the factory and at job sites.
Received: March 13, 2002 / Accepted: July 19, 2002
Acknowledgments The authors thank Gifu Prefectural Human Life Technology Research Institute and Kubota Co. for their support. We also thank
Professor Dr. Shiro Kimura and Dr. Hideyuki Yokochi for their constructive discussions about the research. 相似文献
10.
Hui-Ping Wang Yu-Jie Liang Qi Zhang Ding-Xin LongWei Li Li LiLin Yang Xian-Zhong Yan Yi-Jun Wu 《Pesticide biochemistry and physiology》2011,101(3):232-239
Previous studies have demonstrated that the anticholinesterase pesticides chlorpyrifos and carbaryl are neurotoxic to mammals. However, the toxicity of these pesticides to other organs and their potential interactive effects remain unclear. Our goal in this study was to assess the toxicities of ingestion of chlorpyrifos and carbaryl both separately, and in combination to non-nervous systems, especially the effect on urinary metabolic profiles, in rats. Chlorpyrifos, carbaryl and a mixture of these pesticides, were administered orally to Wistar rats for 90 consecutive days. Histopathological examination of liver and kidney and metabonomic analysis based on the urinary 1H nuclear magnetic resonance spectra were used to investigate the toxic effects. The results showed that no histopathological changes were observed in the liver or kidney tissues, but metabonomic analysis revealed alternations in a number of urinary metabolites involving in the energy metabolism in liver mitochondria. Treatment of rats with chlorpyrifos alone led to an increase in creatine, glycine, dimethylglycine, dimethylamine, glutamine, succinate, alanine, lactate, and glucose. The categories of main differential urinary metabolites in carbaryl-treated rats were similar to those in chlorpyrifos-treated rats, whereas the changes were of varying degree. A combination of a low dose of chlorpyrifos and carbaryl resulted in an increase in the levels of main urinary metabolites compared to the controls, and the increase in signal intensity of the main metabolites was lower than that in the rats exposed to chlorpyrifos or carbaryl alone. All above results suggest that chronic exposure to chlorpyrifos and carbaryl alone, or in combination could cause disturbance of metabolic function in liver mitochondria and renal failure. Overall, we have shown that urine metabonomic analysis is non-invasive, sensitive, and relatively fast for assessing the individual or mutual effects following exposure to pesticides. 相似文献