排序方式： 共有21条查询结果，搜索用时 187 毫秒
1.
利用主成分分析法(Principal Component Analysis,PCA)和偏最小二乘法判别分析(Partial Least Squares Discriminant Analysis,PLS-DA)对晒青毛茶进行级别分类,并通过统计分析找出重要理化成分。结果表明:PCA和PLS-DA均可以直观地对晒青毛茶级别进行分类,其中能够稳定地分类出3级毛茶,而难以将6级和9级毛茶明显地分类。通过PCA载荷图(Loadings plot)和PLS-DA变量重要性因子(Variable important for the projection,VIP)分布图可得出氨基酸含量为级别分类的重要理化成分,其中赖氨酸(Lys)、脯氨酸(Pro)和苯丙氨酸(Phe)是对级别分类最重要的3种氨基酸组分。 相似文献
2.
Nuclear magnetic resonance (NMR) spectroscopy-based metabonomics is a powerful multivariate tool that can be used to characterize the unique metabolic profiles of living creatures. To test the hypothesis that NMR-based metabonomic analyses of serum would reveal metabolic differences between two types of horses, NMR spectra of serum samples drawn on 3 separate days from 2-year-old Mustangs (MU, n = 4) and 2 year-old Draft-cross (DC, n = 4) horses were compared. Metabonomic multivariate statistical analysis of the NMR spectra revealed clear and distinct clustering of each group. The metabolic separation between the Mustangs and Draft-crosses was due mainly to differences in urea, certain amino acids, acetate, lipoproteins, and glucose that probably reflected differences in growth rates and efficiency of protein utilization. NMR-based metabonomic analyses may be useful in detection and evaluation of metabolic differences between different types and physiologic states of horses. 相似文献
3.
This study aims to determine the authenticity of the geographical origin of rice using inductively coupled plasma atomic emission spectroscopy (ICP-AES) and chemometrics. The profiles of 25 elements in brown rice measured by ICP-AES were subjected to data-mining processes, including principal component analysis (PCA) and partial least-squares discriminant analysis (PLS-DA). PLS-DA clearly discriminated the geographical origin of rice samples grown in three countries. Eleven elements (Cu, Ag, Zn, Cr, Ca, Ba, Cd, Bi, K, Pb, and In) significantly contributed to the ability to discriminate the geographical origin of the rice. These results demonstrate the use of multielement profiling combined with chemometrics as a tool for discriminating food origins. This study extends our knowledge about the applications of both multielement profiling and chemometrics for the determination of food authenticity, and thus can be useful for controlling the geographical origin of rice by governmental administration and protecting consumers from improper domestic labeling. 相似文献
4.
妊娠诊断是肉兔繁殖管理中的重要环节,尤其是早期妊娠诊断,可提前未妊娠母兔的再授精时间,提高种兔利用率,缩短繁殖周期。针对人工摸胎诊断法存在对母兔腹内胚胎产生机械损伤、母兔应激反应大及对工人经验要求高等缺陷,该研究基于妊娠母兔与未妊娠母兔腹内有无孕囊组织所引起的光学特性差异,提出一种基于空间漫反射光的母兔妊娠诊断方法,研制了快速、无侵入式的便携诊断装置。该装置由具有2个红外发光二极管（Light Emitting Diode,LED,LED发光波长分别为850和930 nm）、3个硅基光电二极管和外围电路的传感探头和信号处理主机组成。利用该便携诊断装置采集130只人工授精14 d后的母兔（包括63只妊娠母兔和67只未妊娠母兔）腹部漫反射光强度数据,将采集的数据按照7∶3的比例划分为训练集和测试集,训练集数据分别用于建立偏最小二乘判别分析（Partial Least Squares Discrimination Analysis, PLS-DA）模型和支持向量机（Support Vector Machine, SVM）分类模型,测试集数据用于模型性能测试,并对比两种模型的分类性能。同时,利用PLS-DA对采样数据进行有监督的主成分分析和变量重要性分析,结果表明妊娠母兔与未妊娠母兔的采样数据之间存在差异,可以被较好的分类。对比两种分类模型的分类性能发现SVM对妊娠母兔和未妊娠母兔的分类性能均比PLS-DA好,对测试集数据的灵敏度、特异性和准确率分别为80.95%、83.33%和82.05%。研究结果表明,该研究提出的光学妊娠诊断方法可行,研制的诊断装置可对授精14 d后的母兔进行妊娠诊断,对提高兔产业体系智能化装备水平有积极的促进作用。 相似文献
5.
Blue mold and bitter rot, caused by Penicillium expansum and Colletotrichum gloeosporioides, respectively, are two of the most devastating diseases during and after storage of apple. The present project was conducted to evaluate the level of tolerance to these diseases in apple germplasm, and investigate possible associations with other fruit characteristics such as harvest date, firmness at harvest, softening (loss of firmness during storage) and sun-exposure. Apples were harvested at a maturation stage suitable for storage, inoculated with spore suspensions of P. expansum (127 cultivars) or C. gloeosporioides (70 cultivars), and stored for 6 or 12 weeks for early- and late-maturing cultivars, respectively. Fruit firmness was measured after harvest and after storage, and the difference was used as a measure of fruit softening. Average lesion diameter varied significantly among both early- and late-maturing cultivars. The amount of damage caused by the two diseases was significantly correlated across cultivars. Regression analyses indicated that lesion diameter was positively affected by fruit softening and negatively affected by harvest date and firmness at harvest. Impact of the independent variables was quantified with partial least squares discriminant analysis; approximately 40% of the genetic variation could be explained by these variables with harvest date being the most important. The effect of sun-exposure was analyzed on six bi-colored cultivars but the results were not conclusive. Cultivars that showed relatively small symptoms in spite of being early-maturing and/or only medium firm, may have other traits that are beneficial for storage and could therefore be especially useful in breeding programs. 相似文献
6.
基于可见/近红外光谱与SIMCA和PLS-DA的脐橙品种识别 总被引：9，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
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[目的]利用傅里叶变换红外光谱技术结合主成分（PCA）和偏最小二乘法判别分析（PLS-DA）,研究了红地球和皇家秋天葡萄苗叶片的红外光谱图.[方法]测试了2种葡萄苗60个样品的红外光谱,选取1 800 ～750 cm-1范围内原始光谱数据做二阶导数处理,显示在该区间存在明显的差异,利用该区间的二阶导数光谱数据进行主成分和偏最小二乘法判别分析.[结果] PCA和PLS-DA都能很好地区分2个品种的葡萄苗,其中主成分的正确率为100％,偏最小二乘法在隐含潜变量为9时正确率最高,此时2个葡萄品种的偏最小二乘法判别分析的正确率均达100％.[结论]小波变换结合PCA和PLS-DA用于傅里叶变化红外光谱技术能够准确地识别红地球和皇家秋天,为区分不同品种的葡萄苗提供快速、有效的方法. 相似文献
8.
Metabolomics - A robust bioanalytical approach for the discovery of the modes-of-action of pesticides: A review 总被引：1，自引：0，他引：1
The agrochemical industry is facing great undertaking that includes increasing demand for the development of new crop protection agents that are safe for the environment and the consumers, and at the same time combat the issue of the emergence of resistance pest strains. The mode-of-action (MoA) is among the features of a bioactive compound that largely determine whether the abovementioned issues are addressed or not, and subsequently whether its commercial development will be addressed. The early discovery of the MoA of bioactive compounds could accelerate pesticide research and development by reducing the required time and costs. Based on advances in synthetic and natural product chemistry, scientists have access to a vast number of compounds that could potentially be developed as crop protection agents. The screening of such compounds with respect to their MoA requires accurate and robust bioanalytical tools. Metabolomics is a powerful bioanalytical tool that will likely play a significant role in the acceleration of the discovery of MoA of bioactive compounds. In the present review, the capabilities and principles and applications of metabolomics for the study of the MoA of herbicides, insecticides, acaricides, fungicides, and antibiotics are discussed. 相似文献
9.
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
10.
可见/近红外光谱技术识别树叶树种的研究 总被引：1，自引：0，他引：1
探索使用可见/近红外光谱技术识别树叶树种的可行性,为野外可见/近红外光谱技术用于树种识别提供方法。本试验识别了9个树种,测试了光谱预处理方法、识别方法对可见/近红外光谱识别的准确率的影响。对9种阔叶树种共46棵树,分别采用距离法和PLS-DA建立识别模型,比较不同波段和导数预处理方法对模型预测效果的影响。结果表明,使用距离法对原始光谱进行识别时,识别准确率<50%,不能够有效识别树叶树种。使用距离法对预处理后的光谱进行识别时,识别准确率为近红外350～2 500nm(99.16%)>350～1 000nm(88.05%)>1 000～2 500nm(81.24%),且任意单个树种的识别准确率都>98%,能够有效识别树叶树种。使用偏最小二乘法(PLS-DA)结合单列识别变量矩阵时,识别准确率高达100%,识别模型的相关系数为0.993 6,RMSEC为0.120,RMSEP为0.144,但只能成功识别4种树叶树种,当树叶种数>4时,预测模型的识别准确率陡降。使用偏最小二乘法(PLS-DA)结合多列识别变量矩阵对9种树叶的识别准确率高达99.58%,识别模型的相关系数为0.888 6～0.956 9,RMSEC为0.084 5～0.15,RMSEP为0.088 7～0.155。本试验为可见/近红外光谱技术快速识别树种提供了一种新的方法和思路。 相似文献