HYBRID EVENT: You can participate in person at Valencia, Spain or Virtually from your home or work.

2nd Edition of International Conference on Analytical and Bioanalytical Techniques

September 14-16, 2023 | Hybrid Event

September 14-16, 2023 | Valencia, Spain
Bio Analytica 2022

Hu Xiaofeng

Hu Xiaofeng, Speaker at Bioanalytica Conferences
Oil Crops Research Institute, China
Title: Nanomaterial-based Intelligent Point-of-care Testing for Food Safety: Mycotoxins

Abstract:

Mycotoxins are typical pollutants that endanger foods and have harmful effects such as carcinogenic, teratogenic, and mutagenic. Aflatoxin B1 is recognized as a class I carcinogen by the International Agency for Research on Cancer. Cyclopiazonic acid can easily cause degenerative diseases of the liver, pancreas, spleen, and kidney, and zearalenone is accessible to reproductive damage function. Mycotoxin pollution easily occurs in each grain and oil product, such as harvest, storage, transportation, and processing. Mixed mycotoxin pollution is more serious to people's life and health than single mycotoxin pollution because of its additive and synergistic effect. To prevent the frequent occurrence caused by mycotoxin pollution and ensure the food quality and safety "from farm to table", the key is to study and establish a point-of-care test (POCT) to find the mixed mycotoxins pollution in time and reduce the enormous economic losses. The existing detection technology is mainly based on extensive instrument analysis such as high-performance liquid chromatography and mass spectrometry, which are costly, time-consuming, and cannot transmit and share detection results in real-time. The combination of smartphones and POCT modules can realize new methods of intelligent POCT of mycotoxins. It has the advantages of low detection costs, short time, high sensitivity, high throughput, and sharing detection results in real-time. Given the scientific problems of poor detection sensitivity, low throughput, and difficulty in real-time transmission and sharing of detection results in the existing intelligent POCT for mycotoxins in foods, we studied a high sensitivity and high-throughput Intelligent POCT for multi-mycotoxins. We analyzed the sensitivity enhancement and noise reduction mechanism to provide a theoretical basis for intelligent POCT of multi-mycotoxins in foods.

Audience Take Away:

  • The audience can learn about the status of mycotoxins contamination in food and current detection methods, which can help them expand their research or teaching.
  • The audience can learn the sensitization and noise reduction mechanism of mycotoxins detection, which will help them better understand the theoretical basis of intelligent detection.
  • The audience can learn about the combination of intelligent detection and food safety technology, which will help them understand intelligent detection and future research.

Biography:

Dr. Hu Xiaofeng is a researcher at Chinese Academy of Agricultural Sciences. She completed her PhD in Food Safety in 2022. Facing extremely hazardous aflatoxin and other mycotoxins extensively existing in contaminated agricultural and food products and food so far, Enzyme-linked immunosorbent assay (ELISA), biosensor, liquid/gas chromatography, and mass spectrometry can hardly meet the request the needs of high-sensitivity and rapid detection from farm to table. Thus, Hu’s research has applied basic research on Biosensors for food and feed safety and minimized analytical sensors in food safety and environment monitoring. Specifically, Hu has involved the development of critical antibodies with high affinity, tracing nanomaterials, novel biosensors, and their application in the agricultural and food industry. She published 17 papers, and authorized 1 American invention patent, 1 Australian invention patent, and 7 Chinese invention patents. She participated in the formulation of 6 Chinese national or agricultural industry standards. The rapid detection technology she developed has been widely used in Singapore, India, and 23 provinces in China.

Watsapp