Related references
Note: Only part of the references are listed.Volatile compounds of five types of unifloral honey in Northwest China: Correlation with aroma and floral origin based on HS-SPME/GC-MS combined with chemometrics
Min Zhu et al.
FOOD CHEMISTRY (2022)
Organosulfur volatile profiles in Italian red garlic (Allium Sativum L.) varieties investigated by HS-SPME/GC-MS and chemometrics
Alessandra Biancolillo et al.
FOOD CONTROL (2022)
Kaempferol-3-O-galactoside as a marker for authenticating Lespedeza bicolor Turcz. monofloral honey
Caijun Ren et al.
FOOD RESEARCH INTERNATIONAL (2022)
Chemometric approaches for the optimization of headspace-solid phase microextraction to analyze volatile compounds in coriander (Coriandrum sativum L.)
Shouhui Wei et al.
LWT-FOOD SCIENCE AND TECHNOLOGY (2022)
Proteomic analysis of honey. Identification of unique peptide markers for authentication of NZ manuka (Leptospermum scoparium) honey
Jessie Bong et al.
FOOD CHEMISTRY (2021)
Ultrasound-assisted extraction of antioxidant phenolic compounds from Lavandula angustifolia flowers using natural deep eutectic solvents: An experimental design approach
Hamza Alasalvar et al.
SUSTAINABLE CHEMISTRY AND PHARMACY (2021)
Volatile profile and aroma potential of tropical Syrah wines elaborated in different maturation and maceration times using comprehensive two-dimensional gas chromatography and olfactometry
Janaina Aith Barbara et al.
FOOD CHEMISTRY (2020)
Development of a fast method for the determination of pesticide multiresidues in tomatoes using QuEChERS and GC-MS/MS
Quanzeng Wei et al.
EUROPEAN FOOD RESEARCH AND TECHNOLOGY (2020)
Optimization of fungi co-fermentation for improving anthraquinone contents and antioxidant activity using artificial neural networks
Jiao Yang et al.
FOOD CHEMISTRY (2020)
Bioengineering for multiple PAHs degradation for contaminated sediments: Response surface methodology (RSM) and artificial neural network (ANN)
Bhumi K. Sachaniya et al.
CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS (2020)
Development and optimization of a HS-SPME-GC-MS methodology to quantify volatile carbonyl compounds in Port wines
Nathalie Moreira et al.
FOOD CHEMISTRY (2019)
Floral nectar chitinase is a potential marker for monofloral honey botanical origin authentication: A case study from loquat (Eriobotrya japonica Lindl.)
Yue-Qin Song et al.
FOOD CHEMISTRY (2019)
Effects of honey-extracted polyphenols on serum antioxidant capacity and metabolic phenotype in rats
Haoan Zhao et al.
FOOD & FUNCTION (2019)
Predicting electricity consumption in a building using an optimized back-propagation and Levenberg-Marquardt back-propagation neural network: Case study of a shopping mall in China
Zhaoyang Ye et al.
SUSTAINABLE CITIES AND SOCIETY (2018)
Identification of monofloral honeys using HPLC-ECD and chemometrics
Jing Zhao et al.
FOOD CHEMISTRY (2016)
Optimization of medium composition for two-step fermentation of vitamin C based on artificial neural network-genetic algorithm techniques
Yu Yang et al.
BIOTECHNOLOGY & BIOTECHNOLOGICAL EQUIPMENT (2015)
Neural networks applied to discriminate botanical origin of honeys
Ofelia Anjos et al.
FOOD CHEMISTRY (2015)
Chemometric approach to the optimization of HS-SPME/GC-MS for the determination of multiclass pesticide residues in fruits and vegetables
Lukman Bola Abdulra'uf et al.
FOOD CHEMISTRY (2015)
Chemical and sensory comparison of fresh and dried lulo (Solanum quitoense Lam.) fruit aroma
Diana Paola Forero et al.
FOOD CHEMISTRY (2015)
OPTIMIZATION OF THE MEDIUM FOR LACTOBACILLUS ACIDOPHILUS BY PLACKETT-BURMAN AND STEEPEST ASCENT EXPERIMENT
He Chen et al.
ACTA SCIENTIARUM POLONORUM-TECHNOLOGIA ALIMENTARIA (2015)
MZmine 2: Modular framework for processing, visualizing, and analyzing mass spectrometry-based molecular profile data
Tomas Pluskal et al.
BMC BIOINFORMATICS (2010)
Share Paper
