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Joy Sim
Joy Sim
在 student.otago.ac.nz 的电子邮件经过验证 - 首页
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引用次数
年份
Food neophobia, food choice and the details of cultured meat acceptance
RP Hamlin, LS McNeill, J Sim
Meat Science 194, 108964, 2022
322022
Near-infrared reflectance spectroscopy accurately predicted isotope and elemental compositions for origin traceability of coffee
J Sim, C McGoverin, I Oey, R Frew, B Kebede
Food Chemistry 427, 136695, 2023
92023
Stable isotope and trace element analyses with non‐linear machine‐learning data analysis improved coffee origin classification and marker selection
J Sim, C Mcgoverin, I Oey, R Frew, B Kebede
Journal of the Science of Food and Agriculture 103 (9), 4704-4718, 2023
52023
Support vector regression for prediction of stable isotopes and trace elements using hyperspectral imaging on coffee for origin verification
J Sim, Y Dixit, C Mcgoverin, I Oey, R Frew, MM Reis, B Kebede
Food Research International 174, 113518, 2023
42023
Machine learning-driven hyperspectral imaging for non-destructive origin verification of green coffee beans across continents, countries, and regions
J Sim, Y Dixit, C Mcgoverin, I Oey, R Frew, MM Reis, B Kebede
Food Control 156, 110159, 2024
32024
The Potential of NIR Spectroscopy and Chemometrics to Discriminate Roast Degrees and Predict Volatiles in Coffee
S Green, E Fanning, J Sim, GT Eyres, R Frew, B Kebede
Molecules 29 (2), 318, 2024
2024
Optimisation of vibrational spectroscopy instruments and pre-processing for classification problems across various decision parameters
J Sim, C McGoverin, I Oey, R Frew, B Kebede
Food Innovation and Advances 3 (1), 52-63, 2024
2024
Rapid and non-destructive origin traceability using a multi-omics and machine learning approach: Coffee as a case study
JF Sim
University of Otago, 0
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