Miniature spectrometer data analytics for food fraud

[1]  Shintaroh Ohashi,et al.  Application of the radial basis function neural networks to improve the nondestructive Vis/NIR spectrophotometric analysis of potassium in fresh lettuces , 2020, Journal of Food Engineering.

[2]  Hassan Sadrnia,et al.  Nondestructive classification of saffron using color and textural analysis , 2020, Food science & nutrition.

[3]  Hao Zhu,et al.  FTIR spectroscopy coupled with machine learning approaches as a rapid tool for identification and quantification of artificial sweeteners. , 2020, Food chemistry.

[4]  D. Cozzolino,et al.  Sensing the Addition of Vegetable Oils to Olive Oil: The Ability of UV–VIS and MIR Spectroscopy Coupled with Chemometric Analysis , 2019, Food Analytical Methods.

[5]  Yangping Wen,et al.  A novel strategy of near-infrared spectroscopy dimensionality reduction for discrimination of grades, varieties and origins of green tea , 2019, Vibrational Spectroscopy.

[6]  Paul Brereton,et al.  A systematic review of consumer perceptions of food fraud and authenticity: A European perspective , 2019 .

[7]  Figen Tokatli,et al.  Use of FTIR and UV-visible spectroscopy in determination of chemical characteristics of olive oils. , 2019, Talanta.

[8]  E. Teye,et al.  Feasibility Study of the Use of Handheld NIR Spectrometer for Simultaneous Authentication and Quantification of Quality Parameters in Intact Pineapple Fruits , 2019, Journal of Spectroscopy.

[9]  Yanhui Guo,et al.  Ensemble of subspace discriminant classifiers for schistosomal liver fibrosis staging in mice microscopic images , 2018, Health Information Science and Systems.

[10]  Hui Wang,et al.  Collaborative representation based classifier with partial least squares regression for the classification of spectral data , 2018, Chemometrics and Intelligent Laboratory Systems.

[11]  Patrick van der Smagt,et al.  Introduction to Neural Networks , 2009 .

[12]  Suqin Sun,et al.  A Simple and Portable Screening Method for Adulterated Olive Oils Using the Hand-Held FTIR Spectrometer and Chemometrics Tools. , 2018, Journal of food science.

[13]  Tigist Worku,et al.  Evaluation of a miniaturized NIR spectrometer for cultivar identification: The case of barley, chickpea and sorghum in Ethiopia , 2018, PloS one.

[14]  Ernestina Casiraghi,et al.  Handheld NIR device: A non-targeted approach to assess authenticity of fish fillets and patties. , 2018, Food chemistry.

[15]  Ana M. Jiménez-Carvelo,et al.  Chemometric classification and quantification of olive oil in blends with any edible vegetable oils using FTIR-ATR and Raman spectroscopy , 2017 .

[16]  H. Ayvaz,et al.  Quantification of soybean oil adulteration in extra virgin olive oil using portable raman spectroscopy , 2017, Journal of Food Measurement and Characterization.

[17]  Banu Ozen,et al.  Prediction of various chemical parameters of olive oils with Fourier transform infrared spectroscopy , 2015 .

[18]  Jun Bin,et al.  Application of random forests to select premium quality vegetable oils by their fatty acid composition. , 2014, Food chemistry.

[19]  Alejandro Cifuentes,et al.  Food analysis: Present, future, and foodomics , 2012 .

[20]  Salim Chitroub,et al.  Classifier combination and score level fusion: concepts and practical aspects , 2010 .

[21]  Lior Rokach,et al.  Ensemble-based classifiers , 2010, Artificial Intelligence Review.

[22]  Gerard Downey,et al.  Geographic Classification of Extra Virgin Olive Oils from the Eastern Mediterranean by Chemometric Analysis of Visible and Near-Infrared Spectroscopic Data , 2003, Applied spectroscopy.

[23]  Josef Kittler,et al.  Combining classifiers , 1996, Proceedings of 13th International Conference on Pattern Recognition.

[24]  Bernhard E. Boser,et al.  A training algorithm for optimal margin classifiers , 1992, COLT '92.

[25]  Ingrid Daubechies,et al.  Ten Lectures on Wavelets , 1992 .

[26]  J J Hopfield,et al.  Neural networks and physical systems with emergent collective computational abilities. , 1982, Proceedings of the National Academy of Sciences of the United States of America.

[27]  A. Savitzky,et al.  Smoothing and Differentiation of Data by Simplified Least Squares Procedures. , 1964 .

[28]  R. Fisher THE USE OF MULTIPLE MEASUREMENTS IN TAXONOMIC PROBLEMS , 1936 .

[29]  Waleed H. Abdulla,et al.  Honey botanical origin classification using hyperspectral imaging and machine learning , 2020 .