Evaluation of a hybrid in-field sampling method for the detection of pathogenic bacteria through consideration of a priori knowledge of factors related to non-random contamination

Pre-harvest testing is increasingly used to enhance the microbial safety of fresh produce. Traditional sampling assumes that sample collectors have no information on potential contamination sources. Knowledge of such factors could potentially increase the effectiveness of pre-harvest sampling programs. Simulation modeling and field validation trials were used to evaluate a hybrid “Samples of Opportunity” (SOO) sampling method that included a portion of the samples based on the sampler's knowledge of risk factors in pre-harvest produce fields. Relative effectiveness of SOO sampling was compared with three traditional sampling methods. These evaluations were based on three non-random contamination scenarios. The mean detection probability of SOO is 96% higher than traditional sampling methods (p