The extraction of spectral parameters is very difficult because of the limited energy resolution for NaI( TI) gamma-ray detectors. For statistical fluctuation of radioactivity under complex environment,some smoothing ...The extraction of spectral parameters is very difficult because of the limited energy resolution for NaI( TI) gamma-ray detectors. For statistical fluctuation of radioactivity under complex environment,some smoothing filtering methods are proposed to solve the problem. These methods include adopting method of arithmetic moving average,center of gravity,least squares of polynomial,slide converter of discrete funcion convolution etc. The process of spectrum data is realized,and the results are assessed in H / FWHM( Peak High / Full Width at Half Maximum) and peak area based on the Matlab programming. The results indicate that different methods smoothed spectrum have respective superiority in different ergoregion,but the Gaussian function theory in discrete function convolution slide method is used to filter the complex γ-spectrum on Embedded system platform,and the statistical fluctuation of γ-spectrum is filtered well.展开更多
Plants produce a variety of metabolites that are essential for plant growth and human health.To fully understand the diversity of metabolites in certain plants,lots of methods have been developed for metabolites detec...Plants produce a variety of metabolites that are essential for plant growth and human health.To fully understand the diversity of metabolites in certain plants,lots of methods have been developed for metabolites detection and data processing.In the data-processing procedure,how to effectively reduce false-positive peaks,analyze large-scale metabolic data,and annotate plant metabolites remains challenging.In this review,we introduce and discuss some prominent methods that could be exploited to solve these problems,including a five-step filtering method for reducing false-positive signals in LC-MS analysis,QPMASS for analyzing ultra-large GC-MS data,and MetDNA for annotating metabolites.The main applications of plant metabolomics in species discrimination,metabolic pathway dissection,population genetic studies,and some other aspects are also highlighted.To further promote the development of plant metabolomics,more effective and integrated methods/platforms for metabolite detection and comprehensive databases for metabolite identification are highly needed.With the improvement of these technologies and the development of genomics and transcriptomics,plant metabolomics will be widely used in many fields.展开更多
基金Sponsored by the Natural Science Fundation of Jiangxi Province(Grant No.20114BAB211026 and 20122BAB201028)the Open Science Fund from Key Laboratory of Radioactive Geology and Exploration Technology Fundamental Science for National Defense,East China Institute of Technology(Grant No.2010RGET11)
文摘The extraction of spectral parameters is very difficult because of the limited energy resolution for NaI( TI) gamma-ray detectors. For statistical fluctuation of radioactivity under complex environment,some smoothing filtering methods are proposed to solve the problem. These methods include adopting method of arithmetic moving average,center of gravity,least squares of polynomial,slide converter of discrete funcion convolution etc. The process of spectrum data is realized,and the results are assessed in H / FWHM( Peak High / Full Width at Half Maximum) and peak area based on the Matlab programming. The results indicate that different methods smoothed spectrum have respective superiority in different ergoregion,but the Gaussian function theory in discrete function convolution slide method is used to filter the complex γ-spectrum on Embedded system platform,and the statistical fluctuation of γ-spectrum is filtered well.
基金supported by the Strategic Priority Research Program of the Chinese Academy of Sciences(XDB27010202)the National Natural Science Foundation of China(31920103003)the National Key Research and Development Program of China(2016YFD0100904).
文摘Plants produce a variety of metabolites that are essential for plant growth and human health.To fully understand the diversity of metabolites in certain plants,lots of methods have been developed for metabolites detection and data processing.In the data-processing procedure,how to effectively reduce false-positive peaks,analyze large-scale metabolic data,and annotate plant metabolites remains challenging.In this review,we introduce and discuss some prominent methods that could be exploited to solve these problems,including a five-step filtering method for reducing false-positive signals in LC-MS analysis,QPMASS for analyzing ultra-large GC-MS data,and MetDNA for annotating metabolites.The main applications of plant metabolomics in species discrimination,metabolic pathway dissection,population genetic studies,and some other aspects are also highlighted.To further promote the development of plant metabolomics,more effective and integrated methods/platforms for metabolite detection and comprehensive databases for metabolite identification are highly needed.With the improvement of these technologies and the development of genomics and transcriptomics,plant metabolomics will be widely used in many fields.
