Smart fingertip sensor for food quality control: fruit maturity assessment with a magnetic device

TL;DR

This paper introduces a magnetic cilia-based sensor for rapid, nondestructive assessment of fruit ripeness, demonstrating its effectiveness on blueberries and strawberries through measurable voltage responses correlated with maturity stages.

Contribution

It presents a novel magnetic nanocomposite cilia sensor for fruit quality evaluation, advancing nondestructive, quick assessment methods in the food industry.

Findings

Sensor voltage correlates with fruit ripeness stages.

Blueberries and strawberries show distinct voltage peaks at different maturity levels.

Sensor results align with sensory assessments of fruit freshness.

Abstract

Automated technologies for quality inspection of fruits have attracted great interest in the food industry. The development of nondestructive mechanisms to assess the quality of individual fruit prior to sale may lead to an increase in overall product quality, value, and consequently, producer competitiveness. However, the existing methods have limitations. Herein, a texture sensor based on highly sensitive hair-like cilia receptors, to allow a quick quality evaluation of fruit is proposed. The texture sensor consists of up to 100 magnetized nanocomposite cilia attached to a chip with magnetoresistive sensors in a full Wheatstone bridge architecture. In this paper we demonstrate the use of ciliary sensors in scanning fruits (blueberries and strawberries) in different maturation stages. The contact of the cilia with the fruit skin provided qualitative information about its texture in terms of ripeness stage. Less mature fruits exhibited, on average, a highest peak voltage of 0.14 mV for blueberries and 0.12 mV for strawberries, while overripe fruits exhibited 0.58 mV and 0.56 mV, respectively. The results were confirmed by sensorial assessment of the fruit freshness, and therefore attesting the application potential of the sensing technology for fruit quality control.