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Early decay detection in fruit by hyperspectral imaging–Principles and application potential

高光谱成像 采后 计算机科学 质量(理念) 环境科学 遥感 生化工程 生物技术 生物 人工智能 园艺 工程类 地理 认识论 哲学
作者
Dedong Min,Jiangsan Zhao,Gernot Bodner,Maratab Ali,Fujun Li,Xinhua Zhang,Boris Rewald
出处
期刊:Food Control [Elsevier]
卷期号:152: 109830-109830 被引量:41
标识
DOI:10.1016/j.foodcont.2023.109830
摘要

Although fruits are rich in health-promoting properties and associated with several health benefits to humans, they are highly susceptible to pathogen infection which results in the deterioration of fruit quality and food waste and subsequent increased economic losses. Consequently, the development of techniques to detect decaying fruits at an early stage of infection during the postharvest period is an ecological and economic necessity. The use of hyperspectral imaging has recently been recognized as an effective and non-destructive approach for assessing fruit quality. In this article, fundamental knowledge of hyperspectral image acquisition, image sensing modes and hardware, and basic imaging processing techniques are summarized. Given the importance, the review focuses on recent advances in hyperspectral imaging techniques in detecting the decay of fruits such as citrus, apple, peach, and different berries at the early stages of fungal infection. Challenges and future research needed to allow for the implementation of hyperspectral imaging for fruit decay detection in industrial sorting processes have been addressed. To summarize, hyperspectral imaging is already today capable to detect early decay in fruit. However, detection times in-line, adjustment of models by specialists and costs of hardware are still hampering its broad implementation.
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