A unified spectra analysis workflow for the assessment of microbial contamination of ready to eat green salads: Comparative study and application of non-invasive sensors

TL;DR

This study introduces a unified spectral analysis workflow that uses non-invasive sensors to accurately estimate microbial contamination and shelf life of ready-to-eat green salads, demonstrating its effectiveness across different storage conditions.

Contribution

A novel, robust spectra analysis workflow combining normalization, feature selection, and partial least squares regression for assessing microbial contamination in leafy greens.

Findings

Effective estimation of microbial contamination using non-invasive sensors.

Workflow performs well under both static and dynamic temperature conditions.

Potential for low-cost sensor development in food quality assessment.

Abstract

The present study provides a comparative assessment of non-invasive sensors as means of estimating the microbial contamination and time-on-shelf (i.e. storage time) of leafy green vegetables, using a novel unified spectra analysis workflow. Two fresh ready-to-eat green salads were used in the context of this study for the purpose of evaluating the efficiency and practical application of the presented workflow: rocket and baby spinach salads. The employed analysis workflow consisted of robust data normalization, powerful feature selection based on random forests regression, and selection of the number of partial least squares regression coefficients in the training process by estimating the knee-point on the explained variance plot. Training processes were based on microbiological and spectral data derived during storage of green salad samples at isothermal conditions (4, 8 and 12C), whereas testing was performed on data during storage under dynamic temperature conditions (simulating real-life temperature fluctuations in the food supply chain). Since an increasing interest in the use of non-invasive sensors in food quality assessment has been made evident in recent years, the unified spectra analysis workflow described herein, by being based on the creation/usage of limited sized featured sets, could be very useful in food-specific low-cost sensor development.