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Integrating a Low-Cost Electronic Nose and Machine Learning Modelling to Assess Coffee Aroma Profile and Intensity

Sensors (Basel, Switzerland), 2021-03, Vol.21 (6), p.2016

2021

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Early Detection of Aphid Infestation and Insect-Plant Interaction Assessment in Wheat Using a Low-Cost Electronic Nose (E-Nose), Near-Infrared Spectroscopy and Machine Learning Modeling

Sensors (Basel, Switzerland), 2021-09, Vol.21 (17), p.5948

2021

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Urban Green Infrastructure Monitoring Using Remote Sensing from Integrated Visible and Thermal Infrared Cameras Mounted on a Moving Vehicle

Sensors (Basel, Switzerland), 2021-01, Vol.21 (1), p.295

2021

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Editorial: Special Issue “Implementation of Sensors and Artificial Intelligence for Environmental Hazards Assessment in Urban, Agriculture and Forestry Systems”

Sensors (Basel, Switzerland), 2021-09, Vol.21 (19), p.6383

2021

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Early Detection of Fusarium oxysporum Infection in Processing Tomatoes ( Solanum lycopersicum ) and Pathogen-Soil Interactions Using a Low-Cost Portable Electronic Nose and Machine Learning Modeling

Sensors (Basel, Switzerland), 2022-11, Vol.22 (22), p.8645

2022

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Artificial Intelligence Applied to a Robotic Dairy Farm to Model Milk Productivity and Quality based on Cow Data and Daily Environmental Parameters

Sensors (Basel, Switzerland), 2020-05, Vol.20 (10), p.2975

2020

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Berry Cell Vitality Assessment and the Effect on Wine Sensory Traits Based on Chemical Fingerprinting, Canopy Architecture and Machine Learning Modelling

Sensors (Basel, Switzerland), 2021-11, Vol.21 (21), p.7312

2021

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Machine Learning Modeling of Wine Sensory Profiles and Color of Vertical Vintages of Pinot Noir Based on Chemical Fingerprinting, Weather and Management Data

Sensors (Basel, Switzerland), 2020-06, Vol.20 (13), p.3618

2020

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Actual evapotranspiration and energy balance estimation from vineyards using micro-meteorological data and machine learning modeling

Agricultural water management, 2024-05, Vol.297, p.108834, Article 108834

2024

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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

Sensors (Basel, Switzerland), 2020-09, Vol.20 (18), p.5108

2020

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Livestock Identification Using Deep Learning for Traceability

Sensors (Basel, Switzerland), 2022-10, Vol.22 (21), p.8256

2022

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Biometric Physiological Responses from Dairy Cows Measured by Visible Remote Sensing Are Good Predictors of Milk Productivity and Quality through Artificial Intelligence

Sensors (Basel, Switzerland), 2021-10, Vol.21 (20), p.6844

2021

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Non-Invasive Sheep Biometrics Obtained by Computer Vision Algorithms and Machine Learning Modeling Using Integrated Visible/Infrared Thermal Cameras

Sensors (Basel, Switzerland), 2020-11, Vol.20 (21), p.6334

2020

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New developments and opportunities for AI in viticulture, pomology, and soft-fruit research: a mini-review and invitation to contribute articles

Frontiers in Horticulture, 2023-10, Vol.2

2023

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Non-Invasive Tools to Detect Smoke Contamination in Grapevine Canopies, Berries and Wine: A Remote Sensing and Machine Learning Modeling Approach

Sensors (Basel, Switzerland), 2019-07, Vol.19 (15), p.3335

2019

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Overexpressing Arabidopsis thaliana ACBP6 in transgenic rapid-cycling Brassica napus confers cold tolerance

Plant methods, 2022-05, Vol.18 (1), p.62-62, Article 62

2022

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Modeling Pinot Noir Aroma Profiles Based on Weather and Water Management Information Using Machine Learning Algorithms: A Vertical Vintage Analysis Using Artificial Intelligence

Foods, 2019-12, Vol.9 (1), p.33

2019

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Animal biometric assessment using non-invasive computer vision and machine learning are good predictors of dairy cows age and welfare: The future of automated veterinary support systems

Journal of agriculture and food research, 2022-12, Vol.10, p.100388, Article 100388

2022

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A Digital Approach to Evaluate the Effect of Berry Cell Death on Pinot Noir Wines’ Quality Traits and Sensory Profiles Using Non-Destructive Near-Infrared Spectroscopy

Beverages (Basel), 2020-06, Vol.6 (2), p.39

2020

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Effects of Different Beer Compounds on Biometrically Assessed Emotional Responses in Consumers

Fermentation (Basel), 2023-03, Vol.9 (3), p.269

2023

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Novel digital technologies implemented in sensory science and consumer perception

Current opinion in food science, 2021-10, Vol.41, p.99-106

2021

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Implementation of Sensors and Artificial Intelligence for Environmental Hazards Assessment in Urban, Agriculture and Forestry Systems

2022

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Early Detection of IFusarium oxysporum/I Infection in Processing Tomatoes and Pathogen–Soil Interactions Using a Low-Cost Portable Electronic Nose and Machine Learning Modeling

Sensors (Basel, Switzerland), 2022-11, Vol.22 (22)

2022

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The livestock farming digital transformation: implementation of new and emerging technologies using artificial intelligence

Animal health research reviews, 2022-06, Vol.23 (1), p.59-71

2022

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Novel Method to Conduct Remote Sensory Sessions and Biometrics during Isolation

Biology and life sciences forum, 2021-10, Vol.6 (1), p.88

2021

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Integrating a Low-Cost Electronic Nose and Machine Learning Modelling to Assess Coffee Aroma Profile and Intensity

Early Detection of Aphid Infestation and Insect-Plant Interaction Assessment in Wheat Using a Low-Cost Electronic Nose (E-Nose), Near-Infrared Spectroscopy and Machine Learning Modeling

Urban Green Infrastructure Monitoring Using Remote Sensing from Integrated Visible and Thermal Infrared Cameras Mounted on a Moving Vehicle

Editorial: Special Issue “Implementation of Sensors and Artificial Intelligence for Environmental Hazards Assessment in Urban, Agriculture and Forestry Systems”

Early Detection of Fusarium oxysporum Infection in Processing Tomatoes ( Solanum lycopersicum ) and Pathogen-Soil Interactions Using a Low-Cost Portable Electronic Nose and Machine Learning Modeling

Artificial Intelligence Applied to a Robotic Dairy Farm to Model Milk Productivity and Quality based on Cow Data and Daily Environmental Parameters

Berry Cell Vitality Assessment and the Effect on Wine Sensory Traits Based on Chemical Fingerprinting, Canopy Architecture and Machine Learning Modelling

Machine Learning Modeling of Wine Sensory Profiles and Color of Vertical Vintages of Pinot Noir Based on Chemical Fingerprinting, Weather and Management Data

Actual evapotranspiration and energy balance estimation from vineyards using micro-meteorological data and machine learning modeling

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

Livestock Identification Using Deep Learning for Traceability

Biometric Physiological Responses from Dairy Cows Measured by Visible Remote Sensing Are Good Predictors of Milk Productivity and Quality through Artificial Intelligence

Non-Invasive Sheep Biometrics Obtained by Computer Vision Algorithms and Machine Learning Modeling Using Integrated Visible/Infrared Thermal Cameras

New developments and opportunities for AI in viticulture, pomology, and soft-fruit research: a mini-review and invitation to contribute articles

Non-Invasive Tools to Detect Smoke Contamination in Grapevine Canopies, Berries and Wine: A Remote Sensing and Machine Learning Modeling Approach

Overexpressing Arabidopsis thaliana ACBP6 in transgenic rapid-cycling Brassica napus confers cold tolerance

Modeling Pinot Noir Aroma Profiles Based on Weather and Water Management Information Using Machine Learning Algorithms: A Vertical Vintage Analysis Using Artificial Intelligence

Animal biometric assessment using non-invasive computer vision and machine learning are good predictors of dairy cows age and welfare: The future of automated veterinary support systems

A Digital Approach to Evaluate the Effect of Berry Cell Death on Pinot Noir Wines’ Quality Traits and Sensory Profiles Using Non-Destructive Near-Infrared Spectroscopy

Effects of Different Beer Compounds on Biometrically Assessed Emotional Responses in Consumers

Novel digital technologies implemented in sensory science and consumer perception

Implementation of Sensors and Artificial Intelligence for Environmental Hazards Assessment in Urban, Agriculture and Forestry Systems

Early Detection of IFusarium oxysporum/I Infection in Processing Tomatoes and Pathogen–Soil Interactions Using a Low-Cost Portable Electronic Nose and Machine Learning Modeling

The livestock farming digital transformation: implementation of new and emerging technologies using artificial intelligence

Novel Method to Conduct Remote Sensory Sessions and Biometrics during Isolation

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