Identification of common buckwheat (Fagopyrum esculentum Moench) adulterated in Tartary buckwheat (Fagopyrum tataricum (L.) Gaertn) flour based on near-infrared spectroscopy and chemometrics
Tài liệu tham khảo
Bala, 2022, Prediction of maize flour adulteration in chickpea flour (besan) using near infrared spectroscopy, J. Food Sci. Technol., 59, 3130, 10.1007/s13197-022-05456-7
Basri, 2017, Classification and quantification of palm oil adulteration via portable NIR spectroscopy, Spectrochim. Acta Mol. Biomol. Spectrosc., 173, 335, 10.1016/j.saa.2016.09.028
Chen, 2019, Application of near infrared spectroscopy combined with SVR algorithm in rapid detection of cAMP content in red jujube, Optik, 194, 10.1016/j.ijleo.2019.163063
Chen, 2018, Fast quantitative detection of sesame oil adulteration by near-infrared spectroscopy and chemometric models, Vib. Spectrosc., 99, 178, 10.1016/j.vibspec.2018.10.003
Chen, 2019, Quantifying several adulterants of notoginseng powder by near-infrared spectroscopy and multivariate calibration, Spectrochim. Acta, 211, 280, 10.1016/j.saa.2018.12.003
Dou, 2022, Adulteration detection of essence in sesame oil based on headspace gas chromatography-ion mobility spectrometry, Food Chem., 370, 10.1016/j.foodchem.2021.131373
Du, 2021, Adulteration detection of corn oil, rapeseed oil and sunflower oil in camellia oil by in situ diffuse reflectance near-infrared spectroscopy and chemometrics, Food Control, 121, 10.1016/j.foodcont.2020.107577
Firmani, 2019, Near infrared (NIR) spectroscopy-based classification for the authentication of Darjeeling black tea, Food Control, 100, 292, 10.1016/j.foodcont.2019.02.006
Gunning, 2023, Authentication of saffron using 60 MHz 1H NMR spectroscopy, Food Chem., 404, 10.1016/j.foodchem.2022.134649
He, 2019, The nutritive value and progress in development and utilization of Tartary buckwheat, Farm Products Processing, 23, 69
Khamsopha, 2021, Utilizing near infrared hyperspectral imaging for quantitatively predicting adulteration in tapioca starch, Food Control, 123, 10.1016/j.foodcont.2020.107781
Kim, 2023, Development and validation of a multiplex real-time PCR assay for accurate authentication of common buckwheat (Fagopyrum esculentum) and tartary buckwheat (Fagopyrum tataricum) in food, Food Control, 145, 10.1016/j.foodcont.2022.109442
Leng, 2021, Fast quantification of total volatile basic nitrogen (TVB-N) content in beef and pork by near-infrared spectroscopy: comparison of SVR and PLS model, Meat Sci., 180, 10.1016/j.meatsci.2021.108559
Li, 2022, Comparative metabolomics study of Tartary (Fagopyrum tataricum (L.) Gaertn) and common (Fagopyrum esculentum Moench) buckwheat seeds, Food Chem., 371, 10.1016/j.foodchem.2021.131125
Li, 2019, Metabolite profiling and transcriptome analyses provide insights into the flavonoid biosynthesis in the developing seed of tartary buckwheat (Fagopyrum tataricum), J. Agric. Food Chem., 67, 11262, 10.1021/acs.jafc.9b03135
Li, 2021, A novel duplex SYBR green real-time PCR with melting curve analysis method for beef adulteration detection, Food Chem., 338, 10.1016/j.foodchem.2020.127932
Li, 2020, Rapid detection of saffron (Crocus sativus L.) Adulterated with lotus stamens and corn stigmas by near-infrared spectroscopy and chemometrics, Ind. Crop. Prod., 152, 10.1016/j.indcrop.2020.112539
Li, 2023, Identification of aged-rice adulteration based on near-infrared spectroscopy combined with partial least squares regression and characteristic wavelength variables, Food Chem. X, 17, 10.1016/j.fochx.2022.100539
Lima, 2020, Fast quantitative detection of black pepper and cumin adulterations by near-infrared spectroscopy and multivariate modeling, Food Control, 107, 10.1016/j.foodcont.2019.106802
Liu, 2019, Rapid identification and quantification of Panax notoginseng with its adulterants by near infrared spectroscopy combined with chemometrics, Spectrochim. Acta, 206, 23, 10.1016/j.saa.2018.07.094
Luo, 2021, Quantitative detection of soluble solids content, pH, and total phenol in Cabernet Sauvignon grapes based on near infrared spectroscopy, Int. J. Food Eng., 17, 365, 10.1515/ijfe-2020-0198
Mahgoub, 2020, Near-infrared spectroscopy combined with chemometrics for quality control of German chamomile (Matricaria recutita L.) and detection of its adulteration by related toxic plants, Microchem. J., 158, 10.1016/j.microc.2020.105153
Park, 2015, Hyperspectral microscope imaging methods to classify gram-positive and gram-negative foodborne pathogenic bacteria, T ASABE, 58, 5
Popa, 2020, Rapid adulteration detection of cold pressed oils with their refined versions by UV–Vis spectroscopy, Sci REP-UK, 10
Rismiwandira, 2021, Application of Fourier Transform Near-Infrared (FT-NIR) spectroscopy for detection of adulteration in palm sugar, IOP Conf. Ser. Earth Environ. Sci., 653, 10.1088/1755-1315/653/1/012122
Rukundo, 2020, Use of a handheld near infrared spectrometer and partial least squares regression to quantify metanil yellow adulteration in turmeric powder, J. Near Infrared Spectrosc., 28, 81, 10.1177/0967033519898889
Santos, 2016, Detection and quantification of milk adulteration using time domain nuclear magnetic resonance (TD-NMR), Microchem. J., 124, 15, 10.1016/j.microc.2015.07.013
Shi, 2021, Characterization of key aroma compounds in tartary buckwheat (fagopyrum tataricum Gaertn.) by means of sensory-directed flavor analysis [J], J. Agric. Food Chem., 69, 11361, 10.1021/acs.jafc.1c03708
Sun, 2017, CARS-ABC-SVR model for predicting leaf moisture of leaf-used lettuce based on hyperspectral, Trans. Chin. Soc. Agric. Eng., 33, 178
Sun, 2021, Rapid detection and quantification of adulteration in Chinese hawthorn fruits powder by near-infrared spectroscopy combined with chemometrics, Spectrochim. Acta, 250, 10.1016/j.saa.2020.119346
Sun, 2021, An improved grid search algorithm to optimize SVR for prediction, Soft Comput., 25, 5633, 10.1007/s00500-020-05560-w
Tu, 2015, Qualitative-quantitative analysis of rice bran oil adulteration based on laser near infrared spectroscopy, Spectrosc. Spectr. Anal., 35, 1539
Wang, 2016, Adulteration detection of buckwheat powder by clustering analysis of flavonoid components, Sci Technol Food Ind, 37, 309
Wang, 2018, Potential of near infrared spectroscopy and pattern recognition for rapid discrimination and quantification of Gleditsia sinensis thorn powder with adulterants [J], J. Pharm. Biomed. Anal., 160, 64, 10.1016/j.jpba.2018.07.036
Wang, 2022, Portable NIR spectroscopy and PLS based variable selection for adulteration detection in quinoa flour, Food Control, 138, 10.1016/j.foodcont.2022.108970
Wu, 2017, Quantitative identification of adulterated Sichuan pepper powder by near-infrared spectroscopy coupled with chemometrics, J. Food Qual., 1
Yan, 2019, A modification of the bootstrapping soft shrinkage approach for spectral variable selection in the issue of over-fitting, model accuracy and variable selection credibility, Spectrochim. Acta, 210, 362, 10.1016/j.saa.2018.10.034
Yi, 2017, Near-infrared reflectance spectroscopy for the prediction of chemical composition in walnut kernel, Int. J. Food Prop., 20, 1633, 10.1080/10942912.2016.1217006
Zhang, 2022, Nondestructive detection for adulteration of panax notoginseng powder based on hyperspectral imaging combined with arithmetic optimization algorithm‐support vector regression, J. Food Process. Eng., 45, 10.1111/jfpe.14096
Zhang, 2014, Determination of quality parameters of tomato paste using guided microwave spectroscopy, Food Control, 40, 214, 10.1016/j.foodcont.2013.12.008
Zhao, 2019, Application of invasive weed optimization and least square support vector machine for prediction of beef adulteration with spoiled beef based on visible near-infrared (Vis-NIR) hyperspectral imaging, Meat Sci., 151, 75, 10.1016/j.meatsci.2019.01.010
Zhou, 2020, Discrimination of Tetrastigma hemsleyanum according to geographical origin by near-infrared spectroscopy combined with a deep learning approach, Spectrochim. Acta Mol. Biomol. Spectrosc., 238, 10.1016/j.saa.2020.118380
Zhou, 2020, Detection of chemical oxygen demand (COD) of water quality based on fluorescence emission spectra, Spectrosc. Spectr. Anal., 40, 1143
Zuo, 2014, Application of UV similarity in buckwheat powder adulteration [J], The Food Industry, 35, 92