Food neophobia, food choice and the details of cultured meat acceptance RP Hamlin, LS McNeill, J Sim Meat Science 194, 108964, 2022 | 32 | 2022 |
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 | 9 | 2023 |
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 | 5 | 2023 |
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 | 4 | 2023 |
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 | 3 | 2024 |
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 | | |