Truffles are highly prized edible fungi that grow underground in symbiosis with plant roots. Renowned for their rarity, distinctive aroma, and impressive health benefits (e.g., antioxidant, anti-inflammatory, and antimicrobial properties), truffles are considered one of the most expensive food products globally. Their characteristic scent ranges from earthy, garlicky, and leathery to vanilla-like or even gasoline-like. This unique aroma is produced by a complex blend of volatile organic compounds (VOCs), including alcohols, ketones, aldehydes, and sulfur compounds. Despite the identification of over 200 VOCs in truffle species, only a small fraction is responsible for the distinctive truffle aroma, known as “aroma-active compounds.” The aromatic profile of a single truffle species typically includes 30–60 VOCs.
Truffle hunters have traditionally relied on trained animals, such as pigs and dogs, to locate truffles underground. These animals can detect the VOCs emitted by truffles with remarkable accuracy. However, this method presents challenges such as the need for animal training, limited working hours, and variability in performance based on animal behavior. An electronic nose (e-nose) offers a non-invasive, consistent, and reliable alternative to traditional truffle detection methods. By mimicking the olfactory system, an e-nose can detect and analyze the VOCs responsible for the distinctive aroma of truffles. This method is more scalable, requires no animal training, and can potentially offer real-time, field-deployable solutions to truffle hunters and food industries. The development of an e-nose for truffle detection could revolutionize the way truffles are located and ensure the sustainability of this luxury food industry.
Main tasks:
• Design and development of an electronic nose system for detecting truffle-specific VOCs.
• Characterization and analysis of truffle VOCs using gas sensors and machine learning techniques.
• Development and optimization of sensor arrays for the detection of aroma-active compounds.
• Field testing and validation of the e-nose prototype in simulated environments.
Student background:
• Sensor technology, electronic engineering, or chemical engineering.
• Basic knowledge of gas sensors and volatile organic compounds.
• Familiarity with data analysis, machine learning, and signal processing is a plus.
Benefits for the student:
• Hands-on experience in sensor design, data acquisition, and signal processing.
• In-depth knowledge of electronic nose technology and its real-world applications.
• Opportunity to contribute to an innovative solution in the luxury food sector.
• Experience in interdisciplinary research, combining electronics, chemistry, and food science.
Truffles are highly prized edible fungi that grow underground in symbiosis with plant roots. Renowned for their rarity, distinctive aroma, and impressive health benefits (e.g., antioxidant, anti-inflammatory, and antimicrobial properties), truffles are considered one of the most expensive food products globally. Their characteristic scent ranges from earthy, garlicky, and leathery to vanilla-like or even gasoline-like. This unique aroma is produced by a complex blend of volatile organic compounds (VOCs), including alcohols, ketones, aldehydes, and sulfur compounds. Despite the identification of over 200 VOCs in truffle species, only a small fraction is responsible for the distinctive truffle aroma, known as “aroma-active compounds.” The aromatic profile of a single truffle species typically includes 30–60 VOCs.
Truffle hunters have traditionally relied on trained animals, such as pigs and dogs, to locate truffles underground. These animals can detect the VOCs emitted by truffles with remarkable accuracy. However, this method presents challenges such as the need for animal training, limited working hours, and variability in performance based on animal behavior. An electronic nose (e-nose) offers a non-invasive, consistent, and reliable alternative to traditional truffle detection methods. By mimicking the olfactory system, an e-nose can detect and analyze the VOCs responsible for the distinctive aroma of truffles. This method is more scalable, requires no animal training, and can potentially offer real-time, field-deployable solutions to truffle hunters and food industries. The development of an e-nose for truffle detection could revolutionize the way truffles are located and ensure the sustainability of this luxury food industry.
Main tasks:
• Design and development of an electronic nose system for detecting truffle-specific VOCs.
• Characterization and analysis of truffle VOCs using gas sensors and machine learning techniques.
• Development and optimization of sensor arrays for the detection of aroma-active compounds.
• Field testing and validation of the e-nose prototype in simulated environments.
Student background:
• Sensor technology, electronic engineering, or chemical engineering.
• Basic knowledge of gas sensors and volatile organic compounds.
• Familiarity with data analysis, machine learning, and signal processing is a plus.
Benefits for the student:
• Hands-on experience in sensor design, data acquisition, and signal processing.
• In-depth knowledge of electronic nose technology and its real-world applications.
• Opportunity to contribute to an innovative solution in the luxury food sector.
• Experience in interdisciplinary research, combining electronics, chemistry, and food science.