Shrimp classification for white spot syndrome detection through enhanced gated recurrent unit-based wild geese migration optimization algorithm - Ramachandran, L.; Mangaiyarkarasi, S. P.; Subramanian, A.; Senthilkumar, S. (Virus genes, 2024)
The major dangerous viral infection for cultivated shrimps is WSSV. The virus is extremely dangerous, spreads swiftly, and may result in up to 100% mortality in 3–10 days. The vast wrapped double stranded DNA virus known as WSSV describes a member of the Nimaviridae viral family’s species Whispovirus. It impacts a variety of crustacean hosts but predominantly marine shrimp species that are raised for commercial purposes. The entire age groups are affected by the virus, which leads to widespread mortality. Mesodermal and ectodermal tissues, like the lymph nodes, gills, and cuticular epithelium, represents the centres of infection. Complete genome sequencing related to the WSSV strains from Thailand, China, and Taiwan has identified minute genetic variations amongst them. There exist conflicting findings on the causes of WSSV pathogenicity, which involve variations in the size associated with the genome, the count of tandem repeats, and the availability or lack of certain proteins. Hence, this paper plans to perform the shrimp classification for the WSSV on the basis of novel deep learning methodology. Initially, the data is gathered from the farms as well as internet sources. Next, the pre-processing of the gathered shrimp images is accomplished using the LBP technique. These pre-processed images undergo the segmentation process utilizing the TGVFCMS approach. The extraction of the features from these segmented images is performed by the PLDA technique. In the final step, the classification of the shrimp into healthy shrimp and WSSV affected shrimp is done by the EGRU, in which the parameter tuning is accomplished by the wild GMO algorithm with the consideration of accuracy maximization as the major objective function. Performance indicators for accuracy have been compared with those of various conventional methods, and the results show that the methodology is capable of accurately identifying the shrimp WSSV illness.