为探究直接复热、水浴复热、微波复热和汽蒸复热方式对川菜回锅肉风味的影响,该研究以智能感官技术中的电子鼻和电子舌与氨基酸分析仪和顶空气相色谱-离子迁移谱(HS-GC-IMS)相结合,对回锅肉在4种复热方式处理下的风味特征进行了系统分...为探究直接复热、水浴复热、微波复热和汽蒸复热方式对川菜回锅肉风味的影响,该研究以智能感官技术中的电子鼻和电子舌与氨基酸分析仪和顶空气相色谱-离子迁移谱(HS-GC-IMS)相结合,对回锅肉在4种复热方式处理下的风味特征进行了系统分析。结果表明,电子鼻和电子舌能有效识别回锅肉的香气与口感特征;其中微波复热显著提升了回锅肉的营养价值。该研究共检测到17种游离氨基酸,经微波复热处理后的回锅肉总游离氨基酸含量达到最高值(202.08±6.68)mg/g。偏最小二乘判别分析(partial least squares discriminant analysis,PLS-DA)模型显示直接复热与汽蒸复热之间的风味差异最显著,根据变量重要性投影(variable importance in projection,VIP)值,筛选出22种关键差异香气物质,包括1-戊烯-3-醇、顺-2-戊烯醇等,可作为区分不同复热方式回锅肉香气特征的挥发性标志物。该研究为回锅肉的复热方式提供了重要理论依据,并为进一步探究不同复热方式对回锅肉风味的影响提供了数据支持。展开更多
对不同产地仿刺参( Apostichopus Japonicus )磷脂轮廓进行分析,并筛选潜在的产地差异磷脂标志物,为产地溯源提供方法学参考。通过超高效液相色谱-四极杆飞行时间串联质谱(UHPLC-ESI-TOF-HRMS)对不同产地(胶南、威海和大连)仿刺参磷脂...对不同产地仿刺参( Apostichopus Japonicus )磷脂轮廓进行分析,并筛选潜在的产地差异磷脂标志物,为产地溯源提供方法学参考。通过超高效液相色谱-四极杆飞行时间串联质谱(UHPLC-ESI-TOF-HRMS)对不同产地(胶南、威海和大连)仿刺参磷脂轮廓进行分析,采用主成分分析法(PCA)对不同产地的仿刺参进行聚类分析,并构建正交偏最小二乘法-判别分析(OPLS-DA)模型,用于寻找不同产地仿刺参的磷脂分子标志物。结果表明,在仿刺参样品中共鉴定出160个磷脂分子种,据此构建的OPLS-DA模型[ R 2 X =0.889(cum), R 2 Y =0.979(cum), Q 2 =0.954(cum)]能够实现对3种不同产地仿刺参的有效区分和聚类,并筛选出以磷脂酰乙醇胺(PE)和磷脂酰胆碱(PC)为主的10个产地差异磷脂分子标志物。本研究所构建的方法能够基于磷脂轮廓对不同产地仿刺参进行有效区分,可应用于仿刺参的产地鉴别和溯源工作,为高值海产品的溯源研究提供方法学参考,并为评价不同产地仿刺参营养价值差异研究提供数据支持。展开更多
The Gaussian mixture model (GMM), k-nearest neighbor (k-NN), quadratic discriminant analysis (QDA), and linear discriminant analysis (LDA) were compared to classify wrist motions using surface electromyogram (EMG). Ef...The Gaussian mixture model (GMM), k-nearest neighbor (k-NN), quadratic discriminant analysis (QDA), and linear discriminant analysis (LDA) were compared to classify wrist motions using surface electromyogram (EMG). Effect of feature selection in EMG signal processing was also verified by comparing classification accuracy of each feature, and the enhancement of classification accuracy by normalization was confirmed. EMG signals were acquired from two electrodes placed on the forearm of twenty eight healthy subjects and used for recognition of wrist motion. Features were extracted from the obtained EMG signals in the time domain and were applied to classification methods. The difference absolute mean value (DAMV), difference absolute standard deviation value (DASDV), mean absolute value (MAV), root mean square (RMS) were used for composing 16 double features which were combined of two channels. In the classification methods, the highest accuracy of classification showed in the GMM. The most effective combination of classification method and double feature was (MAV, DAMV) of GMM and its classification accuracy was 96.85%. The results of normalization were better than those of non-normalization in GMM, k-NN, and LDA.展开更多
文摘为探究直接复热、水浴复热、微波复热和汽蒸复热方式对川菜回锅肉风味的影响,该研究以智能感官技术中的电子鼻和电子舌与氨基酸分析仪和顶空气相色谱-离子迁移谱(HS-GC-IMS)相结合,对回锅肉在4种复热方式处理下的风味特征进行了系统分析。结果表明,电子鼻和电子舌能有效识别回锅肉的香气与口感特征;其中微波复热显著提升了回锅肉的营养价值。该研究共检测到17种游离氨基酸,经微波复热处理后的回锅肉总游离氨基酸含量达到最高值(202.08±6.68)mg/g。偏最小二乘判别分析(partial least squares discriminant analysis,PLS-DA)模型显示直接复热与汽蒸复热之间的风味差异最显著,根据变量重要性投影(variable importance in projection,VIP)值,筛选出22种关键差异香气物质,包括1-戊烯-3-醇、顺-2-戊烯醇等,可作为区分不同复热方式回锅肉香气特征的挥发性标志物。该研究为回锅肉的复热方式提供了重要理论依据,并为进一步探究不同复热方式对回锅肉风味的影响提供了数据支持。
文摘对不同产地仿刺参( Apostichopus Japonicus )磷脂轮廓进行分析,并筛选潜在的产地差异磷脂标志物,为产地溯源提供方法学参考。通过超高效液相色谱-四极杆飞行时间串联质谱(UHPLC-ESI-TOF-HRMS)对不同产地(胶南、威海和大连)仿刺参磷脂轮廓进行分析,采用主成分分析法(PCA)对不同产地的仿刺参进行聚类分析,并构建正交偏最小二乘法-判别分析(OPLS-DA)模型,用于寻找不同产地仿刺参的磷脂分子标志物。结果表明,在仿刺参样品中共鉴定出160个磷脂分子种,据此构建的OPLS-DA模型[ R 2 X =0.889(cum), R 2 Y =0.979(cum), Q 2 =0.954(cum)]能够实现对3种不同产地仿刺参的有效区分和聚类,并筛选出以磷脂酰乙醇胺(PE)和磷脂酰胆碱(PC)为主的10个产地差异磷脂分子标志物。本研究所构建的方法能够基于磷脂轮廓对不同产地仿刺参进行有效区分,可应用于仿刺参的产地鉴别和溯源工作,为高值海产品的溯源研究提供方法学参考,并为评价不同产地仿刺参营养价值差异研究提供数据支持。
基金Project(NIPA-2012-H0401-12-1007) supported by the MKE(The Ministry of Knowledge Economy), Korea, supervised by the NIPAProject(2010-0020163) supported by Key Research Institute Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education, Science and Technology, Korea
文摘The Gaussian mixture model (GMM), k-nearest neighbor (k-NN), quadratic discriminant analysis (QDA), and linear discriminant analysis (LDA) were compared to classify wrist motions using surface electromyogram (EMG). Effect of feature selection in EMG signal processing was also verified by comparing classification accuracy of each feature, and the enhancement of classification accuracy by normalization was confirmed. EMG signals were acquired from two electrodes placed on the forearm of twenty eight healthy subjects and used for recognition of wrist motion. Features were extracted from the obtained EMG signals in the time domain and were applied to classification methods. The difference absolute mean value (DAMV), difference absolute standard deviation value (DASDV), mean absolute value (MAV), root mean square (RMS) were used for composing 16 double features which were combined of two channels. In the classification methods, the highest accuracy of classification showed in the GMM. The most effective combination of classification method and double feature was (MAV, DAMV) of GMM and its classification accuracy was 96.85%. The results of normalization were better than those of non-normalization in GMM, k-NN, and LDA.
