Detection of internal browning in ‘Scilate’ apples with a high-speed linear-rail dual-laser scanning system

This study reports on a linear-rail, dual-laser scanning system for high-speed, non-destructive detection of internal quality of fruit. The system was used to detect internal browning of ‘Scilate’ apples. A sample of 200 ‘Scilate’ apples with four different (healthy, slight, moderate, and severe) levels of browning was investigated. The new system’s performance was compared to that of a bench-top near infrared spectroscopy (NIRS) system. Apples with moderate and severe browning were easily detected by both systems. A comprehensive binary classification was made between healthy apples and those with slight browning. The classification results showed that the dual-laser scanning system performed very well for classifying apples with slight internal browning, achieving high accuracies of around 90 % compared to that of 82 % with the NIRS method. The dual-laser system operated successfully while fruit were moving at high speeds of 1.125 m/s and was able to identify small or localised defects. • New high-speed non-destructive detection system for internal fruit defects is presented. • Ratio of two lasers of different wavelengths are scanned across fruit surface. • Results presented for apples with varying degrees of internal browning. • New method is superior to conventional broad-band NIRS using an interactance geometry.

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Publication Details

Journal
Postharvest Biology and Technology
Published
2024-09-20
DOI
https://doi.org/10.1016/j.postharvbio.2024.113200
Primary Topic
Spectroscopy and Chemometric Analyses
Type
article
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article

Detection of internal browning in ‘Scilate’ apples with a high-speed linear-rail dual-laser scanning system

Rainer Künnemeyer, Andrew McGlone, Jason Sun, Zhen Wang
Postharvest Biology and Technology
Spectroscopy and Chemometric Analyses
article

Detection of internal browning in ‘Scilate’ apples with a high-speed linear-rail dual-laser scanning system

Rainer Künnemeyer, Andrew McGlone, Jason Sun, Zhen Wang
article en

Abstract

This study reports on a linear-rail, dual-laser scanning system for high-speed, non-destructive detection of internal quality of fruit. The system was used to detect internal browning of ‘Scilate’ apples. A sample of 200 ‘Scilate’ apples with four different (healthy, slight, moderate, and severe) levels of browning was investigated. The new system’s performance was compared to that of a bench-top near infrared spectroscopy (NIRS) system. Apples with moderate and severe browning were easily detected by both systems. A comprehensive binary classification was made between healthy apples and those with slight browning. The classification results showed that the dual-laser scanning system performed very well for classifying apples with slight internal browning, achieving high accuracies of around 90 % compared to that of 82 % with the NIRS method. The dual-laser system operated successfully while fruit were moving at high speeds of 1.125 m/s and was able to identify small or localised defects. • New high-speed non-destructive detection system for internal fruit defects is presented. • Ratio of two lasers of different wavelengths are scanned across fruit surface. • Results presented for apples with varying degrees of internal browning. • New method is superior to conventional broad-band NIRS using an interactance geometry.

Postharvest Biology and TechnologyVol. 219
Plant & Food Research (NZ), The Dodd-Walls Centre for Photonic and Quantum Technologies (NZ)
Affordable and clean energy
Openalex Percentile: Top 86%
Spectroscopy and Chemometric Analyses
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Detection of internal browning in ‘Scilate’ apples with a high-speed linear-rail dual-laser scanning system — Rainer Künnemeyer, Andrew McGlone, et al. · Postharvest Biology and Technology (2024) | TGRS Research Map | TGRS