Microscopic water dispersion and hydrogen-bonding structures in margarine spreads with Raman hyperspectral imaging and machine learning

被引:2
|
作者
Taylor, J. Nicholas [1 ]
Bando, Kazuki [1 ,2 ]
Tsukagoshi, Shiori [3 ]
Tanaka, Leo [3 ]
Fujita, Katsumasa [1 ,2 ,4 ]
Fujita, Satoshi [1 ,2 ]
机构
[1] AIST Osaka Univ, Adv Photon & Biosensing Open Innovat Lab, Suita, Osaka 5650871, Japan
[2] Osaka Univ, Dept Appl Phys, 2-1 Yamadaoka, Suita, Osaka 5650871, Japan
[3] Megmilk Snow Brand Co Ltd, Milk Sci Res Inst, 1-1-2 Minamidai, Kawagoe, Saitama 3501165, Japan
[4] Osaka Univ, Inst Open & Transdisciplinary Res Initiat, Suita, Osaka 5650871, Japan
基金
日本科学技术振兴机构;
关键词
Raman hyperspectral microscopy; Machine learning; Margarine; Water-in-oil emulsion; Morphology; Fat crystals; IN-OIL EMULSIONS; FAT; SELECTION; CRYSTALS;
D O I
10.1016/j.foodchem.2024.142035
中图分类号
O69 [应用化学];
学科分类号
081704 ;
摘要
Margarine, a water-in-oil (W/O) emulsion, offers advantages such as lower costs in comparison to similar products, but large amounts of saturated fats pose health risks. Reduction of saturated fat content is difficult and often leads to "oil-off," i.e., the seepage of liquid oil from the mixture, resulting in undesirable appearance and texture. Investigations into the phenomenon have often focused on morphology at the water-oil interfaces, and this work establishes Raman imaging as a powerful application for observing microscopic morphologies of W/O emulsions. We analyze morphologies of 5 distinct margarine spreads that differ in manufacturing date, formulation, and manufacturing process. More robust H-bonding in the oil phase of the emulsions co-occurred with smaller amounts of oil-off, suggesting that H-bonding interactions between emulsifier molecules, water, and crystallized fats in the lipid phase of the W/O emulsions results in an emulsion that is less susceptible to the production of oil-off.
引用
收藏
页数:10
相关论文
共 47 条
  • [1] Spectroscopic characterization of microscopic hydrogen-bonding disparities in supercritical water
    Wernet, P
    Testemale, D
    Hazemann, JL
    Argoud, R
    Glatzel, P
    Pettersson, LGM
    Nilsson, A
    Bergmann, U
    JOURNAL OF CHEMICAL PHYSICS, 2005, 123 (15):
  • [2] EFFECTS OF HYDROGEN-BONDING ON THE RAMAN INTENSITIES OF METHANOL, ETHANOL AND WATER
    ABE, N
    ITO, M
    JOURNAL OF RAMAN SPECTROSCOPY, 1978, 7 (03) : 161 - 167
  • [3] Spectroscopic probing of local hydrogen-bonding structures in liquid water
    Myneni, S
    Luo, Y
    Näslund, LA
    Cavalleri, M
    Ojamäe, L
    Ogasawara, H
    Pelmenschikov, A
    Wernet, P
    Väterlein, P
    Heske, C
    Hussain, Z
    Pettersson, LGM
    Nilsson, A
    JOURNAL OF PHYSICS-CONDENSED MATTER, 2002, 14 (08) : L213 - L219
  • [4] RAMAN-SPECTROSCOPIC STUDY OF HYDROGEN-BONDING OF POLYACRYLAMIDE IN HEAVY-WATER
    TANAKA, N
    ITO, K
    KITANO, H
    MACROMOLECULES, 1994, 27 (02) : 540 - 544
  • [5] Classification of skin cancer based on hyperspectral microscopic imaging and machine learning
    Qia, Meijie
    Liu, Yujie
    Li, Yanru
    Liu, Lixin
    Zhang, Zhoufeng
    SPIE-CLP CONFERENCE ON ADVANCED PHOTONICS 2022, 2023, 12601
  • [6] Staging of Skin Cancer Based on Hyperspectral Microscopic Imaging and Machine Learning
    Liu, Lixin
    Qi, Meijie
    Li, Yanru
    Liu, Yujie
    Liu, Xing
    Zhang, Zhoufeng
    Qu, Junle
    BIOSENSORS-BASEL, 2022, 12 (10):
  • [7] HYDROGEN-BONDING IN HYDROGEN-PEROXIDE AND WATER - A RAMAN-STUDY OF THE LIQUID-STATE
    GIGUERE, PA
    CHEN, H
    JOURNAL OF RAMAN SPECTROSCOPY, 1984, 15 (03) : 199 - 204
  • [8] New insight on the hydrogen bonding structures of nanoconfined water: a Raman study
    Crupi, Vincenza
    Interdonato, Salvatore
    Longo, Francesca
    Majolino, Domenico
    Migliardo, Placido
    Venuti, Valentina
    JOURNAL OF RAMAN SPECTROSCOPY, 2008, 39 (02) : 244 - 249
  • [9] Water clusters: Fascinating hydrogen-bonding networks, solvation shell structures, and proton motion
    Cheng, HP
    JOURNAL OF PHYSICAL CHEMISTRY A, 1998, 102 (31): : 6201 - 6204
  • [10] Hyperspectral Chemical Imaging of Single Bacterial Cell Structure by Raman Spectroscopy and Machine Learning
    Barzan, Giulia
    Sacco, Alessio
    Mandrile, Luisa
    Giovannozzi, Andrea Mario
    Portesi, Chiara
    Rossi, Andrea Mario
    APPLIED SCIENCES-BASEL, 2021, 11 (08):