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Volume 30
Issue 11
10.3390/molecules30112431
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This is an early access version, the complete PDF, HTML, and XML versions will be available soon.
Article

A Synergistic Approach Using Photoacoustic Spectroscopy and AI-Based Image Analysis for Post-Harvest Quality Assessment of Conference Pears

by
Mioara Petrus
1,*,
Cristina Popa
1,
Ana Maria Bratu
1,
Vasile Bercu
2,
Leonard Gebac
2,
Delia-Mihaela Mihai
2,
Ana-Cornelia Butcaru
3,
Florin Stanica
4 and
Ruxandra Gogot
4
1
Laser Department, National Institute for Laser, Plasma and Radiation Physics, 409 Atomistilor St., P.O. Box MG 36, 077125 Magurele, Romania
2
Faculty of Physics, University of Bucharest, 405, Atomistilor Str., 077125 Magurele, Romania
3
Research Center for Studies of Food Quality and Agricultural Products, University of Agronomic Sciences and Veterinary Medicine, 59, Marasti Blvd., 011464 Bucharest, Romania
4
Faculty of Horticulture, University of Agronomic Sciences and Veterinary Medicine, 59, Marasti Blvd., 011464 Bucharest, Romania
*
Author to whom correspondence should be addressed.
Molecules 2025, 30(11), 2431; https://doi.org/10.3390/molecules30112431
Submission received: 1 May 2025 / Revised: 28 May 2025 / Accepted: 30 May 2025 / Published: 1 June 2025
(This article belongs to the Special Issue Exclusive Feature Papers in Physical Chemistry, 3nd Edition)
Versions Notes

Abstract

This study presents a non-invasive approach to monitoring post-harvest fruit quality by applying CO2 laser photoacoustic spectroscopy (CO2LPAS) to study the respiration of “Conference” pears from local and commercially stored (supermarket) sources. Concentrations of ethylene (C2H4), ethanol (C2H6O), and ammonia (NH3) were continuously monitored under shelf-life conditions. Our results reveal that ethylene emission peaks earlier in supermarket pears, likely due to post-harvest treatments, while ethanol accumulates over time, indicating fermentation-related deterioration. Significantly, ammonia levels increased during the late stages of senescence, suggesting its potential role as a novel biomarker for fruit degradation. The application of CO2LPAS enabled highly sensitive, real-time detection of trace gases without damaging the fruit, offering a powerful alternative to traditional monitoring methods. Additionally, artificial intelligence (AI) models, particularly convolutional neural networks (CNNs), were explored to enhance data interpretation, enabling early detection of ripening and spoilage patterns through volatile compound profiling. This study advances our understanding of post-harvest physiological processes and proposes new strategies for improving storage and distribution practices for climacteric fruits.
Keywords: ethylene; ethanol; ammonia; CO2 laser photoacoustic spectroscopy; post-harvest quality; fruit senescence; artificial intelligence; convolutional neural network ethylene; ethanol; ammonia; CO2 laser photoacoustic spectroscopy; post-harvest quality; fruit senescence; artificial intelligence; convolutional neural network

Share and Cite

MDPI and ACS Style

Petrus, M.; Popa, C.; Bratu, A.M.; Bercu, V.; Gebac, L.; Mihai, D.-M.; Butcaru, A.-C.; Stanica, F.; Gogot, R. A Synergistic Approach Using Photoacoustic Spectroscopy and AI-Based Image Analysis for Post-Harvest Quality Assessment of Conference Pears. Molecules 2025, 30, 2431. https://doi.org/10.3390/molecules30112431

AMA Style

Petrus M, Popa C, Bratu AM, Bercu V, Gebac L, Mihai D-M, Butcaru A-C, Stanica F, Gogot R. A Synergistic Approach Using Photoacoustic Spectroscopy and AI-Based Image Analysis for Post-Harvest Quality Assessment of Conference Pears. Molecules. 2025; 30(11):2431. https://doi.org/10.3390/molecules30112431

Chicago/Turabian Style

Petrus, Mioara, Cristina Popa, Ana Maria Bratu, Vasile Bercu, Leonard Gebac, Delia-Mihaela Mihai, Ana-Cornelia Butcaru, Florin Stanica, and Ruxandra Gogot. 2025. "A Synergistic Approach Using Photoacoustic Spectroscopy and AI-Based Image Analysis for Post-Harvest Quality Assessment of Conference Pears" Molecules 30, no. 11: 2431. https://doi.org/10.3390/molecules30112431

APA Style

Petrus, M., Popa, C., Bratu, A. M., Bercu, V., Gebac, L., Mihai, D.-M., Butcaru, A.-C., Stanica, F., & Gogot, R. (2025). A Synergistic Approach Using Photoacoustic Spectroscopy and AI-Based Image Analysis for Post-Harvest Quality Assessment of Conference Pears. Molecules, 30(11), 2431. https://doi.org/10.3390/molecules30112431

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