Statistical Approaches to Optimize Detection of MIB Off-Flavor in Aquaculture Raised Channel Catfish

Abstract

The catfish industry prides itself on preventing inadvertent sale of off-flavor fish. Typically, several fish are taste tested over several weeks before pond harvest to confirm good fish flavor quality. We collected several data sets of analytically measured off-flavor concentrations in catfish to assess the type of distribution (parametric/non-normal). Coincident measures of fat content were made on three subsections of each fillet. These data were then used to model the number of fish required to detect off-flavor in mixed populations containing on and off flavor fish. In fish collected from the same pond, off-flavor concentrations typically were not normally distributed, thereby requiring specialized statistical procedures. Even with log transformation, data still violated assumptions of normality. We used a non-parametric approach, using fish samples that were ordered, and then randomly sampled 1000 times, to determine the number of fish necessary to detect off-flavor. A sample of 40 fish was required to detect off-flavor when the population was nearly all on-flavor (97%) and 20% off-flavor fish. A sample size of six fish in a mixed population was effective in identifying off-flavor occurrence in 60% of ponds having off-flavor present. Sampling more fish fewer times can more accurately identify ponds containing mixed flavor fish populations than the current sampling procedure.