Abstract
Fungal infection of food causes billions of dollars of lost revenue per annum as well as health problems, to animals and humans, if consumed in sufficient quantities. Modern food sorting techniques rely on colour or other physical characteristics to filter diseased or otherwise unsuitable foodstuffs from healthy foodstuffs. Their speeds are such that up to 40,000 objects per second can be moved at 4 metres per second, through 1 m wide chutes that offer a wide view for colour and shape sorting. Grain type foods such as coffee or peanuts are often vulnerable to toxic infection from invading fungi. If this happens, then their texture, taste and colour can change. Up to now, only visible wavelengths and colour identification have been used to bulk-sort food, but there has been little research in the ultra violet regions of the spectrum to help identify fungus or toxin infection. This research specifically concentrated on the ultra violet (UV) spectral characteristics of food in an attempt to identify possible spectral changes that occur when healthy food items like peanuts become infected with toxin-producing fungi. Ultimately, the goal is to design, build and construct an optical detection system that can use these "spectral fingerprints" to more quickly and efficiently detect toxically infected food items.
Original language | English |
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Pages (from-to) | 1140-1148 |
Number of pages | 9 |
Journal | Proceedings of SPIE - The International Society for Optical Engineering |
Volume | 4876 |
Issue number | 2 |
DOIs | |
Publication status | Published - 2002 |
Event | Opto-Ireland 2002: Optics and Photonics Technologies and Applications - Galway, Ireland Duration: 5 Sep 2002 → 6 Sep 2002 |
Keywords
- Aflatoxin
- Aspergillus flavus
- Fluorescence
- Fungus
- Spectroscopy
- Ultra violet light