{"title":"Fractional Order Bioimpedance Modeling for Sensing Fruit Properties","authors":"B. Nayak, S. Swain, M.C. Tripathy","doi":"10.1016/j.jfoodeng.2025.112594","DOIUrl":null,"url":null,"abstract":"<div><div>The bioimpedance properties of fruits, governed by complex resistive and capacitive behaviors, offer critical insights into fruit quality, ripeness, and physiological state. This study presents a novel fractional-order bioimpedance analysis (FOBA) framework for modeling fruit bioimpedance using fractional capacitors. By modeling fruits as dielectric materials with a distributed relaxation time, fractional-order systems enable non-invasive evaluation of moisture, glucose, and starch content, all of which vary with ripening and directly influence dielectric constants and fractional capacitance. Utilizing a parallel-plate capacitor setup, the permittivity and fractional capacitance of fruit tissue are examined, where fractional-order parameters reflect cellular biochemical changes. This study identifies key dependencies of these parameters with dielectric constants as well as moisture, glucose, and starch concentrations. This provides a sensitive indicator of ripeness and freshness, making FOBA a valuable tool for real-time, fruit quality monitoring in the food industry. A case study has been implemented using 10 samples of each green (Macho Plantain) and yellow (Cavendish) banana, as a dielectric of fractional capacitors. Experimental results validate the fractional-order modeling and align closely with the MATLAB simulations demonstrating its effectiveness in capturing the dynamic electrical properties. Also, statistical error analysis has been conducted to show the correlation of the predicted model with experimental results with a tolerance of ±3%. The findings indicate potential applications in food industry quality control and supply chain management.</div></div>","PeriodicalId":359,"journal":{"name":"Journal of Food Engineering","volume":"397 ","pages":"Article 112594"},"PeriodicalIF":5.3000,"publicationDate":"2025-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Food Engineering","FirstCategoryId":"97","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0260877425001293","RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, CHEMICAL","Score":null,"Total":0}
引用次数: 0
Abstract
The bioimpedance properties of fruits, governed by complex resistive and capacitive behaviors, offer critical insights into fruit quality, ripeness, and physiological state. This study presents a novel fractional-order bioimpedance analysis (FOBA) framework for modeling fruit bioimpedance using fractional capacitors. By modeling fruits as dielectric materials with a distributed relaxation time, fractional-order systems enable non-invasive evaluation of moisture, glucose, and starch content, all of which vary with ripening and directly influence dielectric constants and fractional capacitance. Utilizing a parallel-plate capacitor setup, the permittivity and fractional capacitance of fruit tissue are examined, where fractional-order parameters reflect cellular biochemical changes. This study identifies key dependencies of these parameters with dielectric constants as well as moisture, glucose, and starch concentrations. This provides a sensitive indicator of ripeness and freshness, making FOBA a valuable tool for real-time, fruit quality monitoring in the food industry. A case study has been implemented using 10 samples of each green (Macho Plantain) and yellow (Cavendish) banana, as a dielectric of fractional capacitors. Experimental results validate the fractional-order modeling and align closely with the MATLAB simulations demonstrating its effectiveness in capturing the dynamic electrical properties. Also, statistical error analysis has been conducted to show the correlation of the predicted model with experimental results with a tolerance of ±3%. The findings indicate potential applications in food industry quality control and supply chain management.
期刊介绍:
The journal publishes original research and review papers on any subject at the interface between food and engineering, particularly those of relevance to industry, including:
Engineering properties of foods, food physics and physical chemistry; processing, measurement, control, packaging, storage and distribution; engineering aspects of the design and production of novel foods and of food service and catering; design and operation of food processes, plant and equipment; economics of food engineering, including the economics of alternative processes.
Accounts of food engineering achievements are of particular value.