Recent developments in the application of nuclear technology in agro-food quality and safety control in China

Electrospun nanofiber-based sensors for the detection of chemical and biological contaminants/hazards in the food industries

Food contamination reveals a major health risk globally and presents a significant challenge for the food industry. It can stem from biological contaminants like pathogens, parasites, and viruses, or chemical contaminants such as heavy metals, pesticides, drugs, and hormones. There is also the possibility of naturally occurring hazardous chemicals. Consequently, the development of sensing platforms has become crucial to accurately and rapidly identify contaminants and hazards in food products. Electrospun nanofibers (NFs) offer a promising solution due to their unique three-dimensional architecture, large specific surface area, and ease of preparation. Moreover, NFs exhibit excellent biocompatibility, degradability, and adaptability, making monitoring more convenient and environmentally friendly. These characteristics also significantly reduce the detection process of contaminants. NF-based sensors have the ability to detect a wide range of biological, chemicals, and physical hazards. Recent research on NFs-based sensors for the detection of various food contaminants/hazards, such as pathogens, pesticide/drugs residues, toxins, allergens, and heavy metals, is presented in this review.

Application of stable isotopic and mineral elemental fingerprints in identifying the geographical originof concentrated apple juice in China

Food traceability is an important component of food safety and quality. Currently, there is no authentic established technique to identify the origin of concentrated apple juice (CAJ) in China. In this study, the isotopes of δ¹³C, δ¹⁸O and the contents of 32 elements in CAJ from five production areas (BHB, NWR, SCH, LP and YRAR) were determined. The δ¹³C, δ¹⁸O and 28 elements were significantly different (P < 0.05: post-hoc Duncan's test) in the five production areas. PCA, PLS-DA and OPLS-DA were employed for regional classification of samples. The results show that ten key variables (Tl, Se, δ¹⁸O, B, Mg, Sr, Nd, Mo, As, and Na) are more relevant for discrimination of the samples. These findings contribute to understanding the variations of stable isotopic and element compositions in Chinese CAJ depending on geographic origins and offer valuable insight into the control of fraudulent labeling regarding the geographic origins of CAJ.