  Mycotoxin contamination in certain agricultural systems have been a serious
concern for human and animal health. Mycotoxins are toxic substances produced
mostly as secondary metabolites by fungi that grow on seeds and feed in the
field, or in storage. The food-borne Mycotoxins likely to be of greatest
significance for human health in tropical developing countries are Aflatoxins
and Fumonisins. Chili pepper is also prone to Aflatoxin contamination during
harvesting, production and storage periods.Various methods used for detection
of Mycotoxins give accurate results, but they are slow, expensive and
destructive. Destructive method is testing a material that degrades the sample
under investigation. Whereas, non-destructive testing will, after testing,
allow the part to be used for its intended purpose. Ultrasonic methods,
Multispectral image processing methods, Terahertz methods, X-ray and
Thermography have been very popular in nondestructive testing and
characterization of materials and health monitoring. Image processing methods
are used to improve the visual quality of the pictures and to extract useful
information from them. In this proposed work, the chili pepper samples will be
collected, and the X-ray, multispectral images of the samples will be processed
using image processing methods. The term "Computational Intelligence" referred
as simulation of human intelligence on computers. It is also called as
"Artificial Intelligence" (AI) approach. The techniques used in AI approach are
Neural network, Fuzzy logic and evolutionary computation. Finally, the
computational intelligence method will be used in addition to image processing
to provide best, high performance and accurate results for detecting the
Mycotoxin level in the samples collected.
