A Scalable Aggregated and Nondestructive Sampling Approach for Food Safety Monitoring of Fresh-Cut Produce During...

Area of Science:

• Food Science
• Microbiology
• Analytical Chemistry

Background:

• Representative sampling is crucial for detecting low-prevalence microbial contamination in fresh produce.
• Conventional grab sampling may miss localized contamination due to heterogeneous microbial distribution.

Purpose of the Study:

• To evaluate a cloth-based aggregated, nondestructive sampling approach against traditional grab sampling for fresh-cut produce.
• To assess the efficacy of cloth sampling in detecting microbial contamination under commercial processing conditions.

Main Methods:

• Paired aggregated cloth and grab samples were collected concurrently from five fresh-cut produce matrices.
• Samples were analyzed using PCR targeting indicator microorganisms and microbial groups.
• Detection frequencies were compared using the exact McNemar test.

Main Results:

• Cloth sampling yielded significantly higher detection rates for specific targets (tetA, tetB) in diced carrots.
• For most other targets and matrices, cloth sampling showed equivalent detection performance to grab sampling.
• Aggregated cloth sampling increased sampled surface area, generating more representative samples.

Conclusions:

• Aggregated cloth sampling is a scalable and effective alternative to conventional grab sampling for detecting microbial contamination in fresh-cut produce.
• This method enhances labor efficiency and standardizes sampling procedures in commercial settings.
• Target selection is critical for maximizing the discriminatory power of microbial detection methods.