{"title":"Dual-Mode Batteryless Ammonia Sensor Using Polyvinyl Alcohol-Reinforced Clitoria ternatea Anthocyanin With Graphene Nanoplatelets for Enhanced Food Quality Monitoring","authors":"Thiresamary Kurian;Chun-Hui Tan;Pei-Song Chee;Vinod Ganesan","doi":"10.1109/JSEN.2024.3392954","DOIUrl":null,"url":null,"abstract":"In the food industry, confusion stemming from expiration and date labels contributes to unnecessary food waste, underscoring the growing need for innovative food freshness sensors. This study presents a novel, cost-effective, and environmentally friendly dual-mode ammonia sensor tailored for real-time quality monitoring of protein-rich food products. Utilizing naturally occurring anthocyanin extracted from Clitoria ternatea (CT) and reinforced with polyvinyl alcohol (PVA) in a paper-based colorimetric system, the sensor demonstrates heightened sensitivity to ammonia gas, a key indicator of spoilage in protein-rich foods. Integration of a graphene nanoplatelets (GNPs) layer enables additional resistive gas sensing capabilities. The practicality and versatility of the fabricated sensor are enhanced by integrating near-field communication (NFC) technology, which facilitates batteryless and wireless sensing response transmission. The fabrication process of the sensor involves a straightforward, low-temperature solution route utilizing dip-coating and brush-coating methods. The incorporation of PVA significantly amplifies the colorimetric response, evidenced by a 44% increase in total color change compared to non-PVA reinforced sensors. This augmentation results in a more pronounced color change, which is readily discernible to the naked eye. The developed dual-mode sensor, equipped with NFC, is successfully applied to monitor shrimp freshness, demonstrating distinct color changes and NFC tag readability in response to ammonia release during spoilage. With its attributes of cost-effectiveness, environmental friendliness, simplicity, and wireless capabilities, this sensor offers a promising solution for widespread adoption in the food industry. This work contributes to advancing sensor technology, providing a versatile tool to ensure the quality and safety of perishable goods.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":null,"pages":null},"PeriodicalIF":4.3000,"publicationDate":"2024-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Sensors Journal","FirstCategoryId":"103","ListUrlMain":"https://ieeexplore.ieee.org/document/10516306/","RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
引用次数: 0
Abstract
In the food industry, confusion stemming from expiration and date labels contributes to unnecessary food waste, underscoring the growing need for innovative food freshness sensors. This study presents a novel, cost-effective, and environmentally friendly dual-mode ammonia sensor tailored for real-time quality monitoring of protein-rich food products. Utilizing naturally occurring anthocyanin extracted from Clitoria ternatea (CT) and reinforced with polyvinyl alcohol (PVA) in a paper-based colorimetric system, the sensor demonstrates heightened sensitivity to ammonia gas, a key indicator of spoilage in protein-rich foods. Integration of a graphene nanoplatelets (GNPs) layer enables additional resistive gas sensing capabilities. The practicality and versatility of the fabricated sensor are enhanced by integrating near-field communication (NFC) technology, which facilitates batteryless and wireless sensing response transmission. The fabrication process of the sensor involves a straightforward, low-temperature solution route utilizing dip-coating and brush-coating methods. The incorporation of PVA significantly amplifies the colorimetric response, evidenced by a 44% increase in total color change compared to non-PVA reinforced sensors. This augmentation results in a more pronounced color change, which is readily discernible to the naked eye. The developed dual-mode sensor, equipped with NFC, is successfully applied to monitor shrimp freshness, demonstrating distinct color changes and NFC tag readability in response to ammonia release during spoilage. With its attributes of cost-effectiveness, environmental friendliness, simplicity, and wireless capabilities, this sensor offers a promising solution for widespread adoption in the food industry. This work contributes to advancing sensor technology, providing a versatile tool to ensure the quality and safety of perishable goods.
期刊介绍:
The fields of interest of the IEEE Sensors Journal are the theory, design , fabrication, manufacturing and applications of devices for sensing and transducing physical, chemical and biological phenomena, with emphasis on the electronics and physics aspect of sensors and integrated sensors-actuators. IEEE Sensors Journal deals with the following:
-Sensor Phenomenology, Modelling, and Evaluation
-Sensor Materials, Processing, and Fabrication
-Chemical and Gas Sensors
-Microfluidics and Biosensors
-Optical Sensors
-Physical Sensors: Temperature, Mechanical, Magnetic, and others
-Acoustic and Ultrasonic Sensors
-Sensor Packaging
-Sensor Networks
-Sensor Applications
-Sensor Systems: Signals, Processing, and Interfaces
-Actuators and Sensor Power Systems
-Sensor Signal Processing for high precision and stability (amplification, filtering, linearization, modulation/demodulation) and under harsh conditions (EMC, radiation, humidity, temperature); energy consumption/harvesting
-Sensor Data Processing (soft computing with sensor data, e.g., pattern recognition, machine learning, evolutionary computation; sensor data fusion, processing of wave e.g., electromagnetic and acoustic; and non-wave, e.g., chemical, gravity, particle, thermal, radiative and non-radiative sensor data, detection, estimation and classification based on sensor data)
-Sensors in Industrial Practice