Assessment of Smoke Contamination in Grapevine Berries and Taint in Wines Due to Bushfires Using a Low-Cost E-Nose and an Artificial Intelligence Approach

Lignende værker

• Non-Invasive Tools to Detect Smoke Contamination in Grapevine Canopies, Berries and Wine: A Remote Sensing and Machine Learning Modeling Approach
  af: Fuentes, Sigfredo, et al.
  Udgivet: (2019)
• Classification of Smoke Contaminated Cabernet Sauvignon Berries and Leaves Based on Chemical Fingerprinting and Machine Learning Algorithms
  af: Summerson, Vasiliki, et al.
  Udgivet: (2020)
• Integrating a Low-Cost Electronic Nose and Machine Learning Modelling to Assess Coffee Aroma Profile and Intensity
  af: Gonzalez Viejo, Claudia, et al.
  Udgivet: (2021)
• Influence of Fruit Maturity at Harvest on the Intensity of Smoke Taint in Wine
  af: Ristic, Renata, et al.
  Udgivet: (2015)
• Machine Learning Modeling of Wine Sensory Profiles and Color of Vertical Vintages of Pinot Noir Based on Chemical Fingerprinting, Weather and Management Data
  af: Fuentes, Sigfredo, et al.
  Udgivet: (2020)