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Food safety is a matter of great significance for the global population. Therefore, researchers have been developing and validating analytical methods to extract, separate and quantitate a variety of hazardous and nutritional analytes in various food commodities. Due to the complexity of food components, a suitable pretreatment method is required to eliminate matrix effects and lower the detection limit. Afterward, chromatography and mass spectrometry are powerful tools in the guarantee of food safety and quality. This book is the reprint of a Special Issue of Separations, “Advances of Accurate Quantification Methods in Food Analysis”, and provides an overview of recent trends in food analytical methods. Both novel sample pretreatment and detection techniques are covered, with the aim of accurate quantification. This Special Issue received nine contributions that covered the latest analytical methods, and focused on pesticides, mycotoxin, antibiotics, metal ions, organic selenium and anthocyanins.

Research & information: general --- Chemistry --- Analytical chemistry --- extract-dilute-shoot --- fosetyl-aluminum --- hydrophilic interaction liquid chromatography --- wheat flour --- broiler tissue --- orbitrap high resolution mass spectrometry --- mycotoxins --- rapid screening --- solid phase extraction --- selenium --- speciation --- enzymatic hydrolysis --- HPLC-ICP-MS --- egg --- aquaculture products --- antibiotic residues --- liquid chromatography tandem mass spectrometry (LC/MS/MS) --- sample pre-treatment --- matrix effects --- QuEChERS --- gas-chromatography high resolution mass spectrometry --- liquid-chromatography high resolution mass spectrometry --- pesticide residues --- cottonseed hull --- raw milk 1 --- pesticides 2 --- screening 3 --- QuEChERS 4 --- high-throughput 5 --- mini solid-phase extraction --- multiclass pesticide residues --- tobacco --- gas chromatography quadrupole time-of-flight mass spectrometry --- arsenic speciation --- rice flour --- ultrasound-assisted extraction --- anthocyanins --- grapes --- UPLC-Q-TOFMS --- QAMS --- n/a

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Metabolomics data analysis strategies are central to transforming raw metabolomics data files into meaningful biochemical interpretations that answer biological questions or generate novel hypotheses. This book contains a variety of papers from a Special Issue around the theme “Best Practices in Metabolomics Data Analysis”. Reviews and strategies for the whole metabolomics pipeline are included, whereas key areas such as metabolite annotation and identification, compound and spectral databases and repositories, and statistical analysis are highlighted in various papers. Altogether, this book contains valuable information for researchers just starting in their metabolomics career as well as those that are more experienced and look for additional knowledge and best practice to complement key parts of their metabolomics workflows.

metabolic networks --- mass spectral libraries --- metabolite annotation --- metabolomics data mapping --- nontarget analysis --- liquid chromatography mass spectrometry --- compound identification --- tandem mass spectral library --- forensics --- wastewater --- gut microbiome --- meta-omics --- metagenomics --- metabolomics --- metabolic reconstructions --- genome-scale metabolic modeling --- constraint-based modeling --- flux balance --- host–microbiome --- metabolism --- global metabolomics --- LC-MS --- spectra processing --- pathway analysis --- enrichment analysis --- mass spectrometry --- liquid chromatography --- MS spectral prediction --- metabolite identification --- structure-based chemical classification --- rule-based fragmentation --- combinatorial fragmentation --- time series --- PLS --- NPLS --- variable selection --- bootstrapped-VIP --- data repository --- computational metabolomics --- reanalysis --- lipidomics --- data processing --- triplot --- multivariate risk modeling --- environmental factors --- disease risk --- chemical classification --- in silico workflows --- metabolome mining --- molecular families --- networking --- substructures --- mass spectrometry imaging --- metabolomics imaging --- biostatistics --- ion selection algorithms --- liquid chromatography high-resolution mass spectrometry --- data-independent acquisition --- all ion fragmentation --- targeted analysis --- untargeted analysis --- R programming --- full-scan MS/MS processing --- R-MetaboList 2 --- liquid chromatography–mass spectrometry (LC/MS) --- fragmentation (MS/MS) --- data-dependent acquisition (DDA) --- simulator --- in silico --- untargeted metabolomics --- liquid chromatography–mass spectrometry (LC-MS) --- experimental design --- sample preparation --- univariate and multivariate statistics --- metabolic pathway and network analysis --- LC–MS --- metabolic profiling --- computational statistical --- unsupervised learning --- supervised learning