Background
The flavours and aroma of food derive in part from human sensing of complex mixtures of volatile organic compounds (VOCs). Flavour is critical for consumers yet is challenging to define quantitatively; small changes in the amounts and types of VOCs in a foodstuff can profoundly alter how it is perceived. Evaluating aroma chemistry is currently time consuming and labour intensive, often needing panels of highly training individuals to directly sample and evaluate products one by one. This is often a rate limiting step in new product development.
Collaborators
This is a PhD project provided by the BBSRC Food Consortium. The Food Consortium CTP comprises four major food manufacturers together with the largest UK-based independent science and technology provider and trainer for the food industry (Campden BRI), and the Haydn Green Institute (Nottingham University Business School).
This industry-led collaborative programme will develop highly skilled PhD researchers and provide an innovation ecosystem through collaboration and partnership. As a successful PhD candidate, you will be part of a larger cohort of students with the opportunity to form strong links to industry and be part of a supportive network of peers, academic supervisors, industrial supervisors, and training partners.
Business facing training will include concepts and issues to consider when commercialising early-stage science and technology, using tools to help evaluate innovation and commercialisation strategies.
This PhD project is a scientific collaboration with researchers at Nestle Confectionary (based also in York).
Objectives
This PhD project will explore how state of the art analytical instrumentation, particularly on-line and real-time mass spectrometry, can help automate flavour detection and accelerate more sustainable product testing and development. The labs in York have pioneered the use of fast response VOC analysis and work closely with a range of instrument companies to test new technologies. In this project chemical ionisation mass spectrometry will be combined with innovative data techniques, including machine learning, to provide new methods for reliable categorisation of products and other critical diagnostics such as consumer perception and impurity detection. The project will include the development of sampling and screening methods, the production of novel calibration systems for flavour-relevant VOCs, and data workflows that allow for close to real-time interpretation. There will be a particular emphasis on the use of machine learning methods (notably random forest and boosted regression trees) as tools to categorise samples into class type, find outliners and identify causal contributions from individual or groups of VOCs in the aroma. The end goal for the industrial collaborator is to accelerate product testing and development and improve sustainability.
Experimental Approach
The project will be based on the use of a Syft Technologies on-line mass spectrometer (https://www.syft.com) that can provide rapid profiling of VOCs in complex products. This approach has been used extensively in the York labs to support analysis of emissions from consumer products and in ambient air; here the technique will move into new territory related to foodstuffs and aroma. An example application in WACL of this type of on-line MS techniques can be found in:
https://onlinelibrary.wiley.com/doi/pdfdirect/10.1111/ina.12652
On-line MS generates large volumes of data in real time and a major scientific challenge is to be able to use this for fast decision-making. The nature of online MS datasets makes them more amenable to automated inspection and data analytics than can be achieved with data from more traditional analytical approaches such as GC-FID and GC-MS. The project will use the R data platform to support machine learning approaches that will aim to provide categorisation of samples, find changes and deviations and locate outliers in aroma and VOC profile, tasks that previously relied on slow hands-on human olfactory testing.
Training.
The PhD student will have access to bespoke training provided by the Food Consortium CTP, which will include business-related training provided by the Nottingham University Business School.
All Chemistry research students have access to our innovative Doctoral Training in Chemistry (iDTC): cohort-based training to support the development of scientific, transferable and employability skills: https://www.york.ac.uk/chemistry/postgraduate/training/idtc/
The Department of Chemistry holds an Athena SWAN Gold Award and is committed to supporting equality and diversity for all staff and students. The Department strives to provide a working environment which allows all staff and students to contribute fully, to flourish, and to excel: https://www.york.ac.uk/chemistry/ed/
For more information about the project, click on the supervisor's name above to email the supervisor. For more information about the application process or funding, please click on email institution
This PhD will formally start on 1 October 2023. Induction activities may start a few days earlier.
To apply for this project, submit an online PhD in Chemistry application: https://www.york.ac.uk/study/postgraduate/courses/apply?course=DRPCHESCHE3
Application deadline is 2 July 2023, but may close earlier if a suitable candidate is found
You should hold or expect to achieve the equivalent of at least a UK upper second class degree in Chemistry or a related subject. Please check the entry requirements for your country: https://www.york.ac.uk/study/international/your-country/
This is a multidisciplinary project and so we welcome applications from across the full spectrum of STEM disciplines.
Equality, diversity and inclusion is fundamental to the success of the CTP programme. The full Equality, diversity and inclusion plan for the Food Consortium is available on request.
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