Rapid analysis of sugars in fruit juices by FT-NIR spectroscopy

被引:135
|
作者
Rodriguez-Saona, LE
Fry, FS
McLaughlin, MA
Calvey, EM
机构
[1] US FDA, Washington, DC 20204 USA
[2] JIFSAN, Washington, DC 20204 USA
关键词
sugars; fruit juices; FT-NIR spectroscopy; multivariate analysis;
D O I
10.1016/S0008-6215(01)00244-0
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
A simple analytical procedure using FT-NIR and multivariate techniques for the rapid determination of individual sugars in fruit juices was evaluated. Different NIR detection devices and sample preparation methods were tested by using model solutions to determine their analytical performance. Aqueous solutions of sugar mixtures (glucose, fructose, and sucrose; 0-8% w/v) were used to develop a calibration model. Direct measurements were made by transflection using a reflectance accessory, by transmittance using a 0.5-mm cell, and by reflectance using a fiberglass paper filter. FT-NIR spectral data were transformed to the second derivative. Partial least-squares regression (PLSR) was used to create calibration models that were cross-validated (leave-one-out approach). The prediction ability of the models was evaluated on fruit juices and compared with HPLC and standard enzymatic techniques. The PLSR loading spectra showed characteristic absorption bands for the different sugars. Models generated from transmittance spectra gave the best performance with standard error of prediction (SEP) < 0.10% and R-2 of 99.9% that accurately and precisely predicted the sugar levels in juices, whereas lower precision was obtained with models generated from reflectance spectra. FT-NIR spectroscopy allowed for the rapid ( similar to 3 min analysis time), accurate and non-destructive analysis of sugars in juices and could be applied in quality control of beverages or to monitor for adulteration or contamination. (C) 2001 Elsevier Science Ltd. All rights reserved.
引用
收藏
页码:63 / 74
页数:12
相关论文
共 50 条
  • [41] Evaluation of two miniaturized FT-NIR spectrometers for rapid soil property analysis
    Sorenson, Preston T.
    Bulmer, David
    Peak, Derek
    SOIL SCIENCE SOCIETY OF AMERICA JOURNAL, 2024, 88 (01) : 126 - 135
  • [42] FT-NIR analysis of different garlic cultivars
    Giuseppe Acri
    Barbara Testagrossa
    Giuseppe Vermiglio
    Journal of Food Measurement and Characterization, 2016, 10 : 127 - 136
  • [43] FT-NIR analysis of different garlic cultivars
    Acri, Giuseppe
    Testagrossa, Barbara
    Vermiglio, Giuseppe
    JOURNAL OF FOOD MEASUREMENT AND CHARACTERIZATION, 2016, 10 (01) : 127 - 136
  • [44] Quantitative analysis of organic acids in pomelo fruit using FT-NIR spectroscopy coupled with network kernel PLS regression
    Chen, Huazhou
    Lin, Bin
    Cai, Ken
    Chen, An
    Hong, Shaoyong
    INFRARED PHYSICS & TECHNOLOGY, 2021, 112
  • [45] Characteristic Wavelengths Analysis of Apple Flesh Browning Based on FT-NIR Spectroscopy
    Li, Guifeng
    ADVANCES IN CHEMICAL ENGINEERING III, PTS 1-4, 2013, 781-784 : 1566 - 1569
  • [46] Quantitative analysis of organic acids in pomelo fruit using FT-NIR spectroscopy coupled with network kernel PLS regression
    Chen, Huazhou
    Lin, Bin
    Cai, Ken
    Chen, An
    Hong, Shaoyong
    Infrared Physics and Technology, 2021, 112
  • [47] Rapid Geographical Origin Identification and Quality Assessment of Angelicae Sinensis Radix by FT-NIR Spectroscopy
    Zhang, Zhen-yu
    Wang, Ying-jun
    Yan, Hui
    Chang, Xiang-wei
    Zhou, Gui-sheng
    Zhu, Lei
    Liu, Pei
    Guo, Sheng
    Dong, Tina T. X.
    Duan, Jin-ao
    JOURNAL OF ANALYTICAL METHODS IN CHEMISTRY, 2021, 2021
  • [48] Application of FT-NIR and FT-IR spectroscopy to fish fillet authentication
    Alamprese, Cristina
    Casiraghi, Ernestina
    LWT-FOOD SCIENCE AND TECHNOLOGY, 2015, 63 (01) : 720 - 725
  • [49] DEVELOPMENT OF METHOD FOR RAPID PREDICTION OF CHEMICAL COMPONENTS OF DHAINCHA USING FT-NIR SPECTROSCOPY AND CHEMOMETRICS
    Uddin, M. Nashir
    Ray, Swapan Kumer
    Islam, M. Saiful
    Nayeem, Jannatun
    Jahan, M. Sarwar
    J-FOR-JOURNAL OF SCIENCE & TECHNOLOGY FOR FOREST PRODUCTS AND PROCESSES, 2017, 6 (04): : 22 - 28
  • [50] A rapid and effective method for species identification of edible boletes: FT-NIR spectroscopy combined with ResNet
    Chen, Jian
    Liu, Honggao
    Li, Jieqing
    Wang, Yuanzhong
    JOURNAL OF FOOD COMPOSITION AND ANALYSIS, 2022, 112