Open AccessStudy of starch aging characteristics based on Terahertz technology
Author(s) -
Wang Tao,
Wang Shuya,
Zhai Chen,
Wang Liang,
Xie Yunfeng,
Li Qian,
Zheng Xu
Publication year - 2021
Publication title -
food science and nutrition
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.614
H-Index - 27
ISSN - 2048-7177
DOI - 10.1002/fsn3.2417
Subject(s) - starch , materials science , crystallinity , biological system , composite material , chemistry , food science , biology
Traditional methods for the determination of starch aging indicators often have a series of shortcomings such as time‐consuming, high cost, large human error, damage to samples, environmental pollution, and high requirements for inspectors. Therefore, it is meaningful to find or establish a dynamic fingerprint identification pattern that can detect the aging degree of starch during the process of processing or storage quickly and accurately. It not only provides guidance for starch food processing but also saves a lot of human, material resources, and time. Terahertz technology is an emerging molecular spectroscopy technology in the 21st century. It is with low energy and basically harmless to the human body. It can also realize nondestructive testing of samples. In the experiment, the samples were prepared by the tableting method and the samples containing 20% of 50 mg samples were prepared with polyethylene as the diluent. The thickness of the samples was 1 mm and the diameter was 13 mm. The terahertz time‐domain spectrometer was used to obtain the spectral information of aging starch at different aging times. After the pretreatment of the spectrum by vector normalization, first derivative, and multiple scattering correction, the prediction models of aging days, crystallinity, and resilience of aging starch were established, respectively. The determination coefficient ( R 2 ) of the established models is all greater than 95%, indicating that the established models are highly reliable and can be used to predict the aging days, crystallinity, and retrogradation degree of starch. And the R 2 of the prediction model based on the refractive index spectrum is greater than that of the absorption coefficient spectrum. The experimental method obtains the dynamic fingerprint identification map of starch in the aging process, realizes the real‐time monitoring and detection of the starch aging process, and provides an effective means for the production and processing of starch‐related industries.