Emerging technologies based on artificial intelligence (AI) can be developed for any field of applied research.
Examples of the DAFW outputs are:
- Deep and machine learning modelling based on remote sensing for Livestock identification and welfare assessment
- Assessment of aroma profiles in cocoa plantations based on aerial photogrammetry, canopy architecture and AI
- Assessment of big data related to environmental factors affecting dairy cow stress and milk productivity and quality
- Remote sensing and AI to assess crop water status
- Use of robotics and remote sensing to assess the intensity of beer sensory descriptors , consumers acceptability , proteins and other physicochemical parameters
- Use of biometrics from consumers to assess acceptability of beer , and insect-based snacks
- A portable electronic nose (e-nose) coupled with AI to assess aromas in beer, smoke taint in wines after bushfires and detecting pest and diseases in crops , and
- NIR and machine learning to assess physicochemical parameters and sensory descriptors of beer , and physicochemical parameters in chocolate , detection of pest and diseases in crops, assessment of berry cell death and plant water status, among others.
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Deep and machine learning modelling based on remote sensing for Livestock identification and welfare assessment
Development and application of computer vision techniques coupled with machine and deep learning for identification and assessment of welfare of livestock such as cattle, sheep and pigs as well as prediction of produce quality traits and yield. This also includes deployment of artificial intelligence models using Jetson technology.
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UAV‐based remote sensing and GIS mapping of crops and produce assessment
UAV‐based remote sensing and GIS mapping of processed data for irrigation scheduling, plant water status assessment, nutrient assessment, pest and disease early prediction and smoke contamination.
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Artificial intelligence/machine learning agriculture, food and animal sciences
Machine learning based modelling and artificial intelligence applications for agriculture, food and animal sciences
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Robotics, sensory evaluation/biometrics and machine learning modelling for brewages
Integration of Robotics, sensory analysis of food and brewages with biometrics and machine learning algorithms to understand consumer preferences and quality of food and brewage products.
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Computer application development for agriculture, food and wine sciences
Mobile computer applications development to be used for agriculture, food and wine sciences.
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Advanced analytical platforms for plant physiology, climate change, sensory technologies and robotics
The DAFW group has expertise in the use and maintenance of state-of-the-art instrumentation to obtain direct measurements of plant physiology and through remote sensing.