Related Experiment Video
Updated: Oct 11, 2025

Deep Neural Networks for Image-Based Dietary Assessment
Published on: March 13, 2021
Long-term stable, high accuracy, and visual detection platform for In-field analysis of nitrite in food based on
Zhao-Jing Huang1, Jia-Yi Luo1, Feng-Ying Zheng2
1College of Chemistry, Chemical Engineering & Environmental Science, Minnan Normal University, Zhangzhou 36300, China.
Abstract:
Nitrite is one of the most common carcinogens in daily food. Its simple, rapid, inexpensive, and in-field measurement is important for food safety, based on the requirements of the standard from Codex Alimentarius Commission and China. Using polyacrylonitrile (PAN) and thin layer silica gel (SG), p-aminophenylcyclic acid (SA) and naphthalene ethylenediamine hydrochloride (NEH), as carriers and chromogenic agents, respectively, PAN-NSS as nitrite color sensor is proposed. After fixing and protecting of SA and NEH with layer-upon-layer PAN, the validity period of the test paper can be prolonged from 7 days to more than 30 days. The reproducibility of PAN-NSS preparation is ensured by electrospinning. Combined with PAN-NSS, deep convolutional neural network (DCNN) and APP as a visual monitoring platform, which has the functions of rapid sampling, data processing and transmission, intuitive feedback, etc., and provides a fully integrated detection system for field detection.
More Related Videos
12:50Colorimetric Paper-based Detection of Escherichia coli, Salmonella spp., and Listeria monocytogenes from Large Volumes of Agricultural Water
Published on: June 9, 2014
06:19Integration of Animal Behavioral Assessment and Convolutional Neural Network to Study Wasabi-Alcohol Taste-Smell Interaction
Published on: August 16, 2024