Identification and quantification of adulterated honey by Raman spectroscopy combined with convolutional neural network and chemometrics

Recent advances in analytical techniques for the detection of adulteration and authenticity of bee products – A review

(2021) Ziying Wang et al.   Food Additives and Contaminants Part A-Chemistry Analysis Control Exposure & Risk Assessment

Improved 1D convolutional neural network adapted to near-infrared spectroscopy for rapid discrimination of Anoectochilus roxburghii and its counterfeits

(2021) Qinqin Chai et al.   JOURNAL OF PHARMACEUTICAL AND BIOMEDICAL ANALYSIS

Mid-infrared spectra feature extraction and visualization by convolutional neural network for sugar adulteration identification of honey and real-world application

(2021) Qianqian Li et al.   LWT-FOOD SCIENCE AND TECHNOLOGY

Detection of acacia honey adulteration with high fructose corn syrup through determination of targeted α‑Dicarbonyl compound using ion mobility-mass spectrometry coupled with UHPLC-MS/MS

(2021) Sha Yan et al.   FOOD CHEMISTRY

Attenuated Total Reflectance-Fourier transform infrared spectroscopy coupled with chemometrics for the rapid detection of coconut water adulteration

(2021) Thomas A. Teklemariam et al.   FOOD CHEMISTRY

Classifying breast cancer tissue by Raman spectroscopy with one-dimensional convolutional neural network

(2021) Danying Ma et al.   SPECTROCHIMICA ACTA PART A-MOLECULAR AND BIOMOLECULAR SPECTROSCOPY

Efficient extraction of deep image features using convolutional neural network (CNN) for applications in detecting and analysing complex food matrices

(2021) Yao Liu et al.   TRENDS IN FOOD SCIENCE & TECHNOLOGY

Understanding the learning mechanism of convolutional neural networks in spectral analysis

(2020) Xiaolei Zhang et al.   ANALYTICA CHIMICA ACTA

Peach variety detection using VIS-NIR spectroscopy and deep learning

(2020) Dian Rong et al.   COMPUTERS AND ELECTRONICS IN AGRICULTURE

Tutorial: multivariate classification for vibrational spectroscopy in biological samples

(2020) Camilo L. M. Morais et al.   Nature Protocols

Detection of adulteration in Chinese honey using NIR and ATR-FTIR spectral data fusion

(2020) Furong Huang et al.   SPECTROCHIMICA ACTA PART A-MOLECULAR AND BIOMOLECULAR SPECTROSCOPY

Manuka honey adulteration detection based on near-infrared spectroscopy combined with aquaphotomics

(2020) Xinhao Yang et al.   LWT-FOOD SCIENCE AND TECHNOLOGY

Potential of smartphone-coupled micro NIR spectroscopy for quality control of green tea

(2020) Luqing Li et al.   SPECTROCHIMICA ACTA PART A-MOLECULAR AND BIOMOLECULAR SPECTROSCOPY

Raman spectroscopy coupled with chemometrics for food authentication: A review

(2020) Yi Xu et al.   TRAC-TRENDS IN ANALYTICAL CHEMISTRY

Low risk of category misdiagnosis of rice syrup adulteration in three botanical origin honey by ATR-FTIR and general model

(2020) Qianqian Li et al.   FOOD CHEMISTRY

Combination of Convolutional Neural Networks and Recurrent Neural Networks for predicting soil properties using Vis–NIR spectroscopy

(2020) Jiechao Yang et al.   GEODERMA

Rapid quantitative detection of the discrepant compounds in differently processed Curcumae Rhizoma products by FT-NIR combined with VCPA-GA technology

(2020) Zhenwei Lan et al.   JOURNAL OF PHARMACEUTICAL AND BIOMEDICAL ANALYSIS

Challenges and a step forward in honey classification based on Raman spectroscopy

(2020) Dana Alina Magdas et al.   FOOD CONTROL

DeepSpectra: An end-to-end deep learning approach for quantitative spectral analysis

(2019) Xiaolei Zhang et al.   ANALYTICA CHIMICA ACTA

Current trends and recent advances on food authenticity technologies and chemometric approaches

(2019) Sonia Medina et al.   TRENDS IN FOOD SCIENCE & TECHNOLOGY

Standardization of complex biologically derived spectrochemical datasets

(2019) Camilo L. M. Morais et al.   Nature Protocols

Identification and quantification of counterfeit sesame oil by 3D fluorescence spectroscopy and convolutional neural network

(2019) Xijun Wu et al.   FOOD CHEMISTRY

A screening method based on Visible-NIR spectroscopy for the identification and quantification of different adulterants in high-quality honey

(2019) Ma José Aliaño-González et al.   TALANTA

Convolutional decoding of thermographic images to locate and quantify honey adulterations

(2019) Manuel Izquierdo et al.   TALANTA

Feature visualization of Raman spectrum analysis with deep convolutional neural network

(2019) Masashi Fukuhara et al.   ANALYTICA CHIMICA ACTA

Evaluation of honey in terms of quality and authenticity based on the general physicochemical pattern, major sugar composition and δ13C signature

(2019) Elisabeta-Irina Geană et al.   FOOD CONTROL

Visible imaging to convolutionally discern and authenticate varieties of rice and their derived flours

(2019) Manuel Izquierdo et al.   FOOD CONTROL

Compositional identification and authentication of Chinese honeys by 1H NMR combined with multivariate analysis

(2019) Chenxi He et al.   FOOD RESEARCH INTERNATIONAL

Use of spectroscopic methods in combination with linear discriminant analysis for authentication of food products

(2018) M. Esteki et al.   FOOD CONTROL

Physicochemical characterization of Lavandula spp. honey with FT-Raman spectroscopy

(2018) Ofélia Anjos et al.   TALANTA

Rapid prediction of phenolic compounds and antioxidant activity of Sudanese honey using Raman and Fourier transform infrared (FT-IR) spectroscopy

(2017) Haroon Elrasheid Tahir et al.   FOOD CHEMISTRY

Application of analytical methods in authentication and adulteration of honey

(2017) Amna Jabbar Siddiqui et al.   FOOD CHEMISTRY

Composition and properties of Apis mellifera honey: A review

(2017) Adriane Alexandre Machado De-Melo et al.   JOURNAL OF APICULTURAL RESEARCH

Recent advancements in detecting sugar-based adulterants in honey – A challenge

(2017) Liming Wu et al.   TRAC-TRENDS IN ANALYTICAL CHEMISTRY

Classification of Honey According to Geographical and Botanical Origins and Detection of Its Adulteration Using Voltammetric Electronic Tongue

(2016) Madiha Bougrini et al.   Food Analytical Methods

Using sensor and spectral analysis to classify botanical origin and determine adulteration of raw honey

(2016) Zhilin Gan et al.   JOURNAL OF FOOD ENGINEERING

Detection of honey adulteration with starch syrup by high performance liquid chromatography

(2015) Shaoqing Wang et al.   FOOD CHEMISTRY

A review of vibrational spectroscopic techniques for the detection of food authenticity and adulteration

(2015) Santosh Lohumi et al.   TRENDS IN FOOD SCIENCE & TECHNOLOGY

2-Acetylfuran-3-Glucopyranoside as a Novel Marker for the Detection of Honey Adulterated with Rice Syrup

(2013) Xiaofeng Xue et al.   JOURNAL OF AGRICULTURAL AND FOOD CHEMISTRY

Rapid analysis of sugars in honey by processing Raman spectrum using chemometric methods and artificial neural networks

(2012) Beril Özbalci et al.   FOOD CHEMISTRY

Detection of adulteration in honey samples added various sugar syrups with 13C/12C isotope ratio analysis method

(2012) Murat Tosun   FOOD CHEMISTRY

Carbohydrate Composition of High-Fructose Corn Syrups (HFCS) Used for Bee Feeding: Effect on Honey Composition

(2010) Ana Isabel Ruiz-Matute et al.   JOURNAL OF AGRICULTURAL AND FOOD CHEMISTRY

Detection of adulterations of honey with high fructose syrups from inulin by GC analysis

(2010) A.I. Ruiz-Matute et al.   JOURNAL OF FOOD COMPOSITION AND ANALYSIS

Key wavelengths screening using competitive adaptive reweighted sampling method for multivariate calibration

(2009) Hongdong Li et al.   ANALYTICA CHIMICA ACTA