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.
Authors
- Rainer Künnemeyer (ORCID: https://orcid.org/0000-0002-6361-0688)
- Andrew McGlone (ORCID: https://orcid.org/0000-0001-6772-0270)
- Jason Sun (ORCID: https://orcid.org/0000-0002-0499-4263)
- Zhen Wang (ORCID: https://orcid.org/0000-0002-8182-2852)
Institutions
- Plant & Food Research (NZ)
- The Dodd-Walls Centre for Photonic and Quantum Technologies (NZ)
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
- Field-Weighted Citation Impact
- 0.00