A Monitoring Framework with Integrated Sensing Technologies for Enhanced Food Safety and Traceability.

Area of Science:

• Agricultural Engineering
• Environmental Science
• Food Science

Background:

• Existing food traceability systems often lack low-cost solutions for real-time environmental monitoring and pesticide detection.
• There is a growing demand from regulatory bodies and consumers for sustainable farming practices and transparent food production.

Purpose of the Study:

• To develop and validate a novel, low-cost framework for integrated food traceability.
• To enable remote monitoring of key environmental parameters and herbicide contamination during farming.
• To provide a system for in situ detection of pesticides, specifically glyphosate.

Main Methods:

• Development of a framework integrating commercial sensors and a proprietary automated system for glyphosate detection using Molecularly Imprinted Polymer (MIP) sensing technology.
• Implementation of a custom electronic mainboard (ElectroSense) for sensor readout and fluidic control, enabling unattended measurements.
• Monitoring of environmental parameters including temperature, humidity, soil moisture, pH, VOCs, and CO2.

Main Results:

• The framework was successfully validated in real crop environments, demonstrating efficacy in olive farming for food traceability.
• The automated glyphosate detection prototype proved capable of identifying unwanted contamination.
• The system showed good correlation between chemical sensor signals and pesticide treatments in a separate crop field.

Conclusions:

• The developed framework offers an integrated and cost-effective solution for food traceability and environmental monitoring in agriculture.
• The system addresses the need for accessible tools to ensure food quality and detect pesticide contamination.
• This technology supports sustainable farming initiatives and meets the demands for greater transparency in the food supply chain.