A phage- and colorimetric sensor-based artificial nose model for banana ripening analysis

Abstract

Climacteric fruits ripen in the storage process after harvest, so technology that can continuously monitor and selectively respond to the condition of the fruits is required. We made a colorimetric sensor array that can perform complex analysis on two VOCs that occur rapidly as bananas ripen. The sensor array consisting of five types of functional bioreceptor using genetically engineered bacteriophages forms a unique colorimetric pattern through reaction with VOCs. Hierarchical clustering was used for colorimetric information, and meaningful classification was obtained according to VOCs exposure conditions. Our group presents an artificial nose model with approximately 95% classification ability for the process of ripening a real banana for 15 days. This artificial nose model is a low-cost sensor platform that enables real-time analysis and mass testing based on a page-based colorimetric sensor system with a simple configuration. We describe a page-based artificial nose technology that can be widely used in food distribution as well as environmental monitoring and health care.