2022
DOI: 10.1007/s11694-022-01554-4
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Quality classification of kiwifruit under different storage conditions based on deep learning and hyperspectral imaging technology

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Cited by 15 publications
(7 citation statements)
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“…However, the TSS content of kiwifruit puree showed a significant decrease after hypothermia treatment. These changes were probably due to the lower respiratory intensity of kiwifruit during hypothermia pretreatment and the reduced conversion of starch to soluble sugars (Yuchen et al, 2022). TSS content did not change significantly after thermal‐SF treatment compared to unprocessed‐SF, but HHP‐SF treatment significantly increased the TSS content.…”
Section: Resultsmentioning
confidence: 99%
“…However, the TSS content of kiwifruit puree showed a significant decrease after hypothermia treatment. These changes were probably due to the lower respiratory intensity of kiwifruit during hypothermia pretreatment and the reduced conversion of starch to soluble sugars (Yuchen et al, 2022). TSS content did not change significantly after thermal‐SF treatment compared to unprocessed‐SF, but HHP‐SF treatment significantly increased the TSS content.…”
Section: Resultsmentioning
confidence: 99%
“…However, there are certain limitations in real-time detection capability and cost-effectiveness analysis, including difficulties in the application to different types of fruits or production environments, and no discussion on cost–benefit factor. Yuchen Zhao et al [ 17 ] used deep learning and hyperspectral imaging technology for quality classification research on kiwifruit under different storage conditions. The results showed that hyperspectral imaging combined with artificial intelligence technology can effectively assess the quality changes of kiwifruit under different storage conditions.…”
Section: Introductionmentioning
confidence: 99%
“…Zhao et al used hyperspectral imaging technology in the near infrared region to study kiwifruit quality changes under different storage conditions. 11 Liu et al used a support vector machine (SVM) as a classifier based on hyperspectral feature fusion to achieve rapid and non-destructive identification of rapeseed varieties. 12 At present, some spectral imaging devices on the market have the advantages of small size, low cost and mass production, and can be widely put into practical use.…”
Section: Introductionmentioning
confidence: 99%