홈
탐색
nav.journalClub
트렌드
더보기
Synapse
⌘+K
Synapse
언어
한국어
한국어
Toward trustworthy non-destructive mango quality prediction using hyperspectral imaging and explainable AI | Synapse
March 3, 2026
View Full Paper
Toward trustworthy non-destructive mango quality prediction using hyperspectral imaging and explainable AI
HD
Haizhen Ding
Nanjing Agricultural University
JZ
Jingyuan Zhao
WW
Wensi Wang
Nanjing Agricultural University
See all
Key Points
Quality prediction is achieved through advanced hyperspectral imaging techniques, enhancing accuracy and trust.
The method focuses on fruit ripeness assessment, essential for consumer satisfaction and market value.
Utilization of explainable AI ensures that predictions are transparent and understandable for stakeholders.
This approach may enable significant improvements in agricultural practices and food supply chain management.
AI에게 질문
Mark Helpful
Like
Save
Bookmark
Relay
Share
View Full Paper
AI에게 질문
Mark Helpful
Like
Save
Bookmark
Relay
Share
View Full Paper
Cite This Study
Copy
Ding et al. (Mon,) studied this question.
synapsesocial.com/papers/69a76639badf0bb9e87dc354
https://doi.org/https://doi.org/10.1016/j.foodcont.2026.112026