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Predicting the Heating Temperature of Soymilk Products Using Fluorescence Fingerprints

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Abstract

A novel measurement technique using fluorescence fingerprints (FFs) was developed to measure the degree of heat treatment applied to soymilk. FFs are a set of fluorescence spectra acquired at consecutive excitation wavelengths. Soymilk was heated at 50, 60, 70, 80, or 90 °C, for 10 min, and the samples were measured both in the liquid and freeze-dried forms. Partial least squares (PLS) regression models were constructed to predict heating temperature from the FFs of liquid soymilk and freeze-dried soymilk. Heating temperatures were predicted from soymilk FFs with root-mean-square errors of prediction (RMSEP) and R 2P of 7.20 °C and 0.92 and from freeze-dried soymilk FFs with RMSEP and R 2P of 9.00 °C and 0.89, respectively. The fluorescence of aromatic amino acids and Maillard products mainly contributed to the prediction models. FF measurement proved to be effective for the objective control of the soymilk heating process.

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Authors and Affiliations

  1. Faculty of Life and Environmental Sciences, University of Tsukuba, 1-1-1 Tennodai, Tsukuba, Ibaraki, 305-8572, Japan

    Mito Kokawa

  2. Fuji Oil Co., Ltd, 4-3 Kinunodai, Tsukubamirai-shi, Ibaraki, 300-2497, Japan

    Kotaro Nishi & Hiroko Ashida

  3. National Agriculture and Food Research Organization, Food Research Institute, 2-1-12 Kannondai, Tsukuba, Ibaraki, 305-8642, Japan

    Vipavee Trivittayasil, Junichi Sugiyama & Mizuki Tsuta

Authors
  1. Mito Kokawa
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  2. Kotaro Nishi
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  3. Hiroko Ashida
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  4. Vipavee Trivittayasil
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  5. Junichi Sugiyama
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  6. Mizuki Tsuta
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Correspondence to Mizuki Tsuta.

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Kokawa, M., Nishi, K., Ashida, H. et al. Predicting the Heating Temperature of Soymilk Products Using Fluorescence Fingerprints. Food Bioprocess Technol 10, 462–468 (2017). https://doi.org/10.1007/s11947-016-1835-6

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  • DOI: https://doi.org/10.1007/s11947-016-1835-6

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