Danfei Liu
Hunan University of Technology
12 Papers
1 Citations
Danfei Liu is an academic researcher from Hunan University of Technology. The author has contributed to research in topics: Chemistry & Medicine. The author has an hindex of 2, co-authored 5 publications.
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Papers
A colorimetric film based on polyvinyl alcohol/sodium carboxymethyl cellulose incorporated with red cabbage anthocyanin for monitoring pork freshness
TL;DR: In this article, the Fourier transform infrared (FTI) reflected that RCAs were fixed into CPVH films through the electrostatic interaction and hydrogen binding, which changed the spatial structure of the CMC-Na films.
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Novel colorimetric films based on polyvinyl alcohol/sodium carboxymethyl cellulose doped with anthocyanins and betacyanins to monitor pork freshness.
Danfei Liu,Chan Zhang,Yumei Pu,Siyuan Chen,Hui Li,Yun-Fei Zhong +5 more
TL;DR: In this paper , a colorimetric film was developed from polyvinyl alcohol/sodium carboxymethyl cellulose (PVA/CMC-Na, CPA) incorporated with anthocyanins (AHO) or betacyanins (BTA) or AHO and BTA mixtures (in the mass ratios of 2:2, 3:1, 1:3) for intelligent packaging.
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Recent Advances in pH-Responsive Freshness Indicators Using Natural Food Colorants to Monitor Food Freshness
Danfei Liu,Changfan Zhang,Yumei Pu,Siyuan Chen,Lei Liu,Zijie Cui,Yun-Fei Zhong +6 more
TL;DR: A review of pH-responsive freshness indicators based on natural food colorants and biodegradable polymers for monitoring packaged food quality can be found in this paper , where the authors address the challenges and prospects of pH responsive indicators in food packaging, to assist in promoting their commercial application.
Indicator films based on anthocyanins loaded on Metal-Organic Framework carriers and BP neural network for monitoring meat freshness
Danfei Liu,Yun-Fei Zhong,Xiaoxuan Li,Yumei Pu,Siyuan Chen,Changfa Zhang +5 more
TL;DR: Researchers developed indicator films using anthocyanins loaded on Metal-Organic Framework (MOF) carriers for monitoring meat freshness, achieving high sensitivity and accuracy with a BP neural network-based prediction model.
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Research progress of packaging indicating materials for real-time monitoring of food quality
TL;DR: In this article, the authors discuss the preparation of various types of TTIs based on different package indicating materials with a particular emphasis on how to improve their accuracy and stability, control the migration of toxic substances and to develop new TTIs.
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