Related Experiment Video
Updated: Jun 14, 2025
11:49
Cereal Crop Ear Counting in Field Conditions Using Zenithal RGB Images
Published on: February 2, 2019
9.3K
A Synergistic Approach Using Photoacoustic Spectroscopy and AI-Based Image Analysis for Post-Harvest Quality
Mioara Petrus1, Cristina Popa1, Ana Maria Bratu1
1Laser Department, National Institute for Laser, Plasma and Radiation Physics, 409 Atomistilor St., P.O. Box MG 36, 077125 Magurele, Romania.
Molecules (Basel, Switzerland)
|June 13, 2025
Summary
This study uses CO2 laser photoacoustic spectroscopy (CO2LPAS) to monitor fruit gases like ethylene and ammonia. This non-invasive method helps detect fruit spoilage and optimize storage for pears.
Area of Science:
- Agricultural Science
- Analytical Chemistry
- Biotechnology
Background:
- Post-harvest fruit quality is crucial for supply chains.
- Traditional monitoring methods can be invasive or time-consuming.
- Understanding fruit respiration and volatile compound changes is key to quality preservation.
Purpose of the Study:
- To introduce a non-invasive CO2 laser photoacoustic spectroscopy (CO2LPAS) method for monitoring fruit respiration.
- To analyze volatile compounds (ethylene, ethanol, ammonia) during pear shelf-life.
- To explore AI models for early detection of fruit ripening and spoilage.
Main Methods:
- Application of CO2 laser photoacoustic spectroscopy (CO2LPAS) for real-time gas analysis.
- Continuous monitoring of ethylene, ethanol, and ammonia concentrations in pears.
- Development and application of artificial intelligence (AI) models, including convolutional neural networks (CNNs), for data interpretation.
Main Results:
- CO2LPAS provided sensitive, non-destructive detection of trace gases.
- Supermarket pears showed earlier ethylene peaks, and ethanol accumulated over time.
- Ammonia levels increased in late senescence, indicating potential as a novel biomarker for fruit degradation.
- AI models successfully identified ripening and spoilage patterns from volatile compound profiles.
Conclusions:
- CO2LPAS is a powerful tool for non-invasive, real-time monitoring of post-harvest fruit quality.
- Ammonia shows promise as a biomarker for detecting fruit senescence.
- AI-enhanced volatile compound analysis can improve early spoilage detection in climacteric fruits.
- This approach offers new strategies for optimizing fruit storage and distribution.
