Quality detection and storage and preservation of black diamond apples in Linzhi, Tibet based on hyperspectral and deep learning approach
Publié en ligne: 05 août 2024
Reçu: 20 avr. 2024
Accepté: 06 juil. 2024
DOI: https://doi.org/10.2478/amns-2024-1940
Mots clés
© 2024 Dandan Xu et al., published by Sciendo
This work is licensed under the Creative Commons Attribution 4.0 International License.
Apples are abundant in essential nutrients, including a variety of minerals and vitamins, and are readily digestible and assimilated by the human body. Commonly consumed worldwide, apples are particularly diverse in their varieties. The “Black Diamond” apple from Linzhi, Tibet, stands out as a significant fresh variety. This study utilizes hyperspectral imaging and deep learning techniques to investigate the impact of room temperature storage on the quality of Linzhi “Black Diamond” apples. Specifically, we assess alterations in quality indices such as hardness, weight loss, sugar-acid ratio, as well as the content of phenolics ketones, and volatile aromatic compounds. Our findings provide detailed insights into the effects of ambient storage conditions on the sensory and nutritional quality of these distinctive apples.
