Skip to content
UT Oriental
  • Inicio
  • Soporte Técnico

UT Oriental
  • Inicio
  • Soporte Técnico

Deep learning-driven Vis/NIR spectroscopic devices for fruit quality assessment: A comprehensive review

Leave a Comment / Procesos Alimentarios / By admin
Bookmark (0)
Please login to bookmark Close

Publication date: October 2025

Source: Trends in Food Science & Technology, Volume 164

Author(s): Tao Jiang, Jianjun Ding, Yuhang Du, Shaofeng Yuan, Hang Yu, Weirong Yao

​Publication date: October 2025Source: Trends in Food Science & Technology, Volume 164Author(s): Tao Jiang, Jianjun Ding, Yuhang Du, Shaofeng Yuan, Hang Yu, Weirong Yao Read More

Related posts:

Default ThumbnailRecent advances in the detection of per- and polyfluoroalkyl substances (PFAS) in food: A review of optical sensors, electrochemical sensors, and biosensors Default ThumbnailDeep learning in food Science: Innovative approaches for predicting and simulating food-derived protein–peptides Default ThumbnailThe role of oil forms in extrusion for plant-based meat analog design: A review Default ThumbnailAI-empowered spectroscopic gas sensing towards real-time food system monitoring and predictive quality control Default ThumbnailFood contact materials based on N-halamines or photosensitizers: An emerging strategy for developing “rechargeable” antibacterial properties Default ThumbnailToward a new industry 5.0 paradigm for human-centered food manufacturing: AI-enabled digitization of nano-scale smart nutrient carriers
← Previous Post
Next Post →

Continuar buscando...

Nueva Información Actualizada

    © 2026 UT Oriental | Powered by UT Oriental

    Aviso importante: Por motivos de actualización administrativa y renovación de licencias, el servicio de esta biblioteca entrará en pausa próximamente.