Nonlinear Law Spectral Technique to Analyze White Spot Syndrome Virus.

Abstract

In this paper a novel spectral technique based on KLaw Fourier nonlinear methodology is developed to classify White Spot Syndrome Virus inclusion bodies found in images from infected shrimp tissue samples. Shrimp culture is expanding in the world due to their high demand and price. This rapid increase in cultured shrimp production was achieved by geographical expansion and technological advances in reproduction in captivity of the white shrimp Penaeus vannamei, larval rearing, artificial diet and intensification in growth out systems. However, diseases are one of the major constraints for the sustainable increase of shrimp production. The white spot syndrome virus is a pandemic disease where frequently 100% mortality may occur within 2-3 days. However, several techniques have been implemented and developed for viral and bacterial analysis and diagnostic's tasks; histology is still considered the common tool in medical and veterinary fields. The slide images were acquired by a computational image capture system and a new spectral technique by the development of a spectral index is done to obtain a quantitative measurement of the complexity pattern found in White Spot Syndrome Virus inclusion bodies. After analysis the results show that inclusion bodies are well defined in a clear numerical fringe, obtained by the calculation of this spectral signature index.