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Food waste as a carbon source in carbon quantum dots technology and their applications in food safety detection

食品工业 食物垃圾 食品包装 碳纤维 重金属 环境科学 环境污染 食品安全 食品添加剂 食品加工 业务 废物管理 食品科学 工程类 材料科学 化学 环境化学 环境保护 复合材料 复合数
作者
Hanzhi Fan,Min Zhang,Bhesh Bhandari,Chaohui Yang
出处
期刊:Trends in Food Science and Technology [Elsevier]
卷期号:95: 86-96 被引量:158
标识
DOI:10.1016/j.tifs.2019.11.008
摘要

In recent years, carbon quantum dots (CQDs) has received a lot of attentions owing to their great physical and optical properties. There are different kinds of carbon sources applied in various fields, however, CQDs used in the food industry have higher requirements for their safety. Therefore, it is the best way to use natural materials for preparing CQDs without the participation of chemicals. Up to now, there are many natural food products for preparing CQDs. However, food waste is often overlooked. Actually, food waste is rich in carbon sources. And the efficient utilization of food waste plays a positive role in economic benefit and environmental pollution. Proper use of food waste as carbon source not only facilitates food safety detection but also increases byproduct value. This paper was intended to review the research progress of food waste utilization as carbon precursor and applications in food safety detection. The approaches of preparing CQDs from different sorts of food wastes, the characteristics and applications of CQDs were described in detail. Particularly the applications in food quality and safety detection including food additives, heavy metal ions were also elaborated. Currently, food waste as carbon source could be divided into plant byproducts, animal food byproducts and food processing byproducts. Moreover, there are many applications of food waste as carbon precursor in CQDs technology to detect food additives and heavy metal ions. However, detection of pathogens and other harmful substances in food industry is rare. Last but not least, it was concluded that food waste had potential to prepare CQDs and be applied to food safety detection.
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