Department of Food Science

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  1. Published

    Precision viticulture: Automatic selection of the regions of interest from moving wagon hyperspectral images of grapes for efficient SSC prediction

    Benelli, A., Cevoli, C., Fabbri, A., Engelsen, Søren Balling & Sørensen, Klavs Martin, 2024, In: Smart Agricultural Technology. 7, 10 p., 100434.

    Research output: Contribution to journal › Journal article › Research › peer-review

  2. Published

    Predicting Protein Content in Grain Using Hyperspectral Deep Learning

    Engstrøm, Ole-Christian Galbo, Dreier, E. S. & Steenstrup Pedersen, Kim, 2021, Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV) . IEEE, p. 1372-1380

    Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

  3. Published

    Predicting and understanding long-term consumer liking of standard versus novel chocolate: a repeated exposure study

    Sørensen, J. G., Wæhrens, S. S. & Byrne, D. V., 2015, In: Journal of Sensory Studies. 30, 5, p. 370-380 11 p.

    Research output: Contribution to journal › Journal article › Research › peer-review

  4. Published

    Predicting hydrolysis of whey protein by mid-infrared spectroscopy

    Poulsen, N. A., Eskildsen, C. E. A., Akkerman, M., Johansen, L. B., Hansen, M. S., Hansen, P. W., Skov, T. & Larsen, L. B., 2016, In: International Dairy Journal. 61, p. 44-50 7 p.

    Research output: Contribution to journal › Journal article › Research › peer-review

  5. Published

    Predicting outgrowth and inactivation of Clostridium perfringens in meat products during low temperature long time heat treatment

    Duan, Z., Hansen, T. H., Hansen, T. B., Dalgaard, P. & Knoechel, Susanne, 2016, In: International Journal of Food Microbiology. 230, p. 45-57 13 p.

    Research output: Contribution to journal › Journal article › Research › peer-review

  6. Published

    Predicting the ethanol potential of wheat straw using near-infrared spectroscopy and chemometrics: The challenge of inherently intercorrelated response functions

    Rinnan, Åsmund, Bruun, Sander, Lindedam, J., Decker, S. R., Turner, G. B., Felby, C. & Engelsen, Søren Balling, 2017, In: Analytica Chimica Acta. 962, p. 15-23 9 p.

    Research output: Contribution to journal › Journal article › Research › peer-review

  7. Published

    Predicting the reaction rates between flavonoids and methylglyoxal by combining molecular properties and machine learning

    Zhu, H., Liu, Jingyuan, Andersen, Mogens Larsen, Peters, G. H. J. & Lund, Marianne N., 2023, In: Food Bioscience. 54, 8 p., 102890.

    Research output: Contribution to journal › Journal article › Research › peer-review

  8. Published

    Predicting weight loss success on a new Nordic diet: an untargeted multi-platform metabolomics and machine learning approach

    Pigsborg, Kristina, Stentoft-Larsen, V., Demharter, S., Aldubayan, Mona Adnan Y, Trimigno, A., Khakimov, Bekzod, Engelsen, Søren Balling, Astrup, A., Hjorth, Mads Fiil, Dragsted, Lars Ove & Magkos, Faidon, 2023, In: Frontiers in Nutrition. 10, 12 p., 1191944.

    Research output: Contribution to journal › Journal article › Research › peer-review

  9. Published

    Prediction of Congou Black Tea Fermentation Quality Indices from Color Features Using Non-Linear Regression Methods

    Dong, C., Liang, G., Hu, B., Yuan, H., Jiang, Y., Zhu, H. & Qi, J., 2018, In: Scientific Reports. 8, 11 p., 10535 .

    Research output: Contribution to journal › Journal article › Research › peer-review

  10. Published

    Prediction of Milk Quality Parameters Using Vibrational Spectroscopy and Chemometrics: Opportunities and Challenges in Milk Phenotyping

    Eskildsen, C. E. A., 2016, Department of Food Science, Faculty of Science, University of Copenhagen.

    Research output: Book/Report › Ph.D. thesis › Research

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