Flexible Vis/NIR wireless sensing system for banana monitoring

Food Quality and Safety, Journal Year: 2023, Volume and Issue: 7

Published: Jan. 1, 2023

Abstract Objectives The quality of the fruit seriously affects economic value fruit. Fruit is related to many ripening parameters, such as soluble solid content (SSC), pH, and firmness (FM), a complex process. Traditional methods are inefficient, do not guarantee quality, adapt current rhythm market. In this paper, was designed implemented for prediction maturity level classification Philippine Cavendish bananas. Materials Methods changes bananas in different stages were analyzed. Twelve light intensity reflectance values each stage compared conventionally measured SSC, FM, PH, color space. Results Our device can be with traditional forms measurement. experimental results show that established predictive model specific preprocessing modeling algorithms effectively determine various banana parameters (SSC, L*, a*, b*). RPD SSC a* greater than 3.0, L* b* between 2.5 pH FM 2.0 2.5. addition, new method (FSC) proposed, showed could classify classes (i.e. four levels) an accuracy rate up 97.5%. Finally, MLR FSC models imported into MCU realize near-range long-range real-time display data. Conclusions These also applied more broadly detection, providing basic framework future research.

Language: Английский

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Electronic Tongues and Noses: A General Overview

Biosensors, Journal Year: 2024, Volume and Issue: 14(4), P. 190 - 190

Published: April 13, 2024

As technology advances, electronic tongues and noses are becoming increasingly important in various industries. These devices can accurately detect identify different substances gases based on their chemical composition. This be incredibly useful fields such as environmental monitoring industrial food applications, where the quality safety of products or ecosystems should ensured through a precise analysis. Traditionally, this task is performed by an expert panel using laboratory tests but sometimes becomes bottleneck because time other human factors that solved with technologies provided tongue nose devices. Additionally, these used medical diagnosis, monitoring, even automotive industry to gas leaks. The possibilities endless, continue improve, they will undoubtedly play role improving our lives ensuring safety. Because multiple applications developments field last years, work present overview from point view approaches developed methodologies data analysis steps aim. In same manner, shows some found use ends conclusions about current state technologies.

Language: Английский

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Intelligent System/Equipment for Quality Deterioration Detection of Fresh Food: Recent Advances and Application

Foods, Journal Year: 2024, Volume and Issue: 13(11), P. 1662 - 1662

Published: May 25, 2024

The quality of fresh foods tends to deteriorate rapidly during harvesting, storage, and transportation. Intelligent detection equipment is designed monitor ensure product in the supply chain, measure appropriate food parameters real time, thus minimize degradation potential financial losses. Through various available tracking devices, consumers can obtain actionable information about products. This paper reviews recent progress intelligent for sensing deterioration foods, including computer vision equipment, electronic nose, smart colorimetric films, hyperspectral imaging (HSI), near-infrared spectroscopy (NIR), nuclear magnetic resonance (NMR), ultrasonic non-destructive testing, tracing equipment. These devices offer advantages high speed, operation, precision, sensitivity.

Language: Английский

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Electronic nose and its application in the food industry: a review

European Food Research and Technology, Journal Year: 2023, Volume and Issue: 250(1), P. 21 - 67

Published: Oct. 11, 2023

Language: Английский

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Rapid detection of adulterated lamb meat using near infrared and electronic nose: A F1-score-MRE data fusion approach

Food Chemistry, Journal Year: 2023, Volume and Issue: 439, P. 138123 - 138123

Published: Dec. 2, 2023

Language: Английский

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Electronic nose as a tool for early detection of diseases and quality monitoring in fresh postharvest produce: A comprehensive review

Comprehensive Reviews in Food Science and Food Safety, Journal Year: 2023, Volume and Issue: 22(3), P. 2408 - 2432

Published: April 11, 2023

Abstract Postharvest diseases and quality degradation are the major factors causing food losses in fresh produce supply chain. Hence, detecting deterioration at asymptomatic stage of enables growers to treat earlier, maintain reduce postharvest losses. With emergence numerous technologies detect early monitor produce, such as polymerase chain reaction, gas chromatography‐mass spectrophotometry, near‐infrared spectroscopy, electronic nose (EN) has also gained acknowledgement popularity past decade a robust non‐invasive analysis tool odor profile establish volatile biomarkers for metabolomics databases. However, literature reviewing EN research on detection after harvest is scarce. The fundamental concept working principles (odor sampling, detection, data acquisition method), well application whole, covered first section review. An in‐depth discussion identification monitoring provided subsequent sections, which key objective this comprehensive prospect, limitations, likely future developments sector further highlighted last section.

Language: Английский

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An energy-efficient classification system for peach ripeness using YOLOv4 and flexible piezoelectric sensor

Computers and Electronics in Agriculture, Journal Year: 2023, Volume and Issue: 210, P. 107909 - 107909

Published: May 17, 2023

Language: Английский

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Discrimination analysis of wines made from four species of blueberry through their olfactory signatures using an E-nose

LWT, Journal Year: 2023, Volume and Issue: 187, P. 115320 - 115320

Published: Sept. 1, 2023

Blueberries are rich in polyphenols, anthocyanins and vitamins. Products such as fermented beverages viable, these fruits have a short shelf life difficult to preserve. During the fermentation process, many volatile phenolic compounds released, which will define quality of product, bringing detectable aromas flavors. Some product evaluations can be performed through laboratory analyses, not always available, often expensive time-consuming. Other analyses carried out olfactory evaluation, work by experienced people sommeliers. From this perspective, presents an initial assessment organic (VOCs) samples four blueberry varieties over two seasons, using electronic nose collect compounds. Subsequently, six classifiers then used evaluate collected data. The results showed hits 99.7% all cases, indicating e-nose's ability differentiate by-products different blueberries present itself auxiliary method standard tests evaluation beverages, allowing comparative evaluations.

Language: Английский

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Effectiveness of an E-Nose Based on Metal Oxide Semiconductor Sensors for Coffee Quality Assessment

Chemosensors, Journal Year: 2025, Volume and Issue: 13(1), P. 23 - 23

Published: Jan. 18, 2025

Coffee quality, which ultimately is reflected in the beverage aroma, relies on several aspects requiring multiple approaches to check it, can be expensive and/or time-consuming. Therefore, this study aimed develop and calibrate an electronic nose (e-nose) coupled with chemometrics approach coffee-related quality tasks. Twelve different metal oxide sensors were employed e-nose construction. The tasks (i) separation of Coffea arabica canephora species, (ii) distinction between roasting profiles (light, medium, dark), (iii) expired non-expired coffees. Exploratory analysis principal component (PCA) pointed a fair grouping tested samples according their specification, indicating potential volatiles samples. Moreover, supervised classification employing soft independent modeling class analogies (SIMCA), partial least squares discriminant (PLS-DA), support vector machine (LS-SVM) led great results accuracy above 90% for every task. performance each model varies specific task, except LS-SVM models, presented perfect all combining distinct models could used multiple-purpose producers as low-cost, rapid, effective alternative assurance.

Language: Английский

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A Neural Network with Multiscale Convolution and Feature Attention Based on an Electronic Nose for Rapid Detection of Common Bunt Disease in Wheat Plants

Agriculture, Journal Year: 2025, Volume and Issue: 15(4), P. 415 - 415

Published: Feb. 16, 2025

Common bunt disease in wheat is a serious threat to crops and food security. Rapid assessments of its severity are essential for effective management. The electronic nose (e-nose) system used capture volatile organic compounds (VOCs), particularly trimethylamine (TMA), which serves as key marker common wheat. In this paper, the GFNN (gas feature neural network) model proposed detecting VOCs from e-nose system, providing lightweight efficient approach assessing severity. Multiscale convolution employed extract both global local features gas data, three attention mechanisms focus on important features. achieves 98.76% accuracy, 98.79% precision, 98.77% recall, an F1-score 98.75%, with only 0.04 million parameters 0.42 floating-point operations per second (FLOPS). Compared traditional current deep learning models, demonstrates superior performance, small-sample-size scenarios. It significantly improves performance extracting This study offers practical, rapid, cost-effective method monitoring managing wheat, enhancing crop protection

Language: Английский

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