Microbial Indicator Profiling of Fresh Produce and Environmental Samples from Farms and Packing Facilities in...

To compare microbiological indicator and pathogen contamination among different types of fresh produce and environmental samples along the production chain, 636 samples of produce (rinsates from cantaloupe melons, jalapeño peppers, and tomatoes) and environmental samples (rinsates from hands of workers, soil, and water) were collected at four successive steps in the production process (from the field before harvest through the packing facility) on 11 farms in northern Mexico during 2011 and 2012. Samples were assayed for enteric pathogens (Escherichia coli O157:H7, other Shiga toxigenic E. coli, Salmonella, and Listeria monocytogenes) and microbial indicators (coliforms, other E. coli strains, and Enterococcus spp.). Salmonella was the only pathogen detected; it was found in one preharvest jalapeño sample (detection limits: 0.0033 CFU/ml in produce and hand samples, 0.0013 CFU/ml in water, and 0.04 CFU/g in soil). Microbial indicator profiles for produce, worker hands, and soil from jalapeño and tomato farms were similar, but cantaloupe farm samples had higher indicator levels (P < 0.05 for all comparisons) on fruit (6.5, 2.8, and 7.2 log CFU per fruit) and hands (6.6, 3.1, and 7.1 log CFU per hand) for coliforms, E. coli, and Enterococcus, respectively, and lower E. coli levels in soil (<1 CFU/g). In water from tomato farms, E. coli indicators were significantly more prevalent (70 to 89% of samples were positive; P = 0.01 to 0.02), and geometric mean levels were higher (0.3 to 0.6 log CFU/100 ml) than those in cantaloupe farm water (32 to 38% of samples were positive, geometric mean <1 CFU/100 ml). Microbial indicators were present during all production steps, but prevalence and levels were generally highest at the final on-farm production step (the packing facility) (P < 0.03 for significant comparisons). The finding that microbial contamination on produce farms is influenced by produce type and production step can inform the design of effective approaches to mitigate microbial contamination.